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  • Articles  (145)
  • Computational Methods, Genomics  (73)
  • Environmental Microbiology  (51)
  • Chromatin and Epigenetics  (21)
  • Oxford University Press  (145)
  • 2015-2019  (145)
  • Biology  (145)
  • 1
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    A low-latency, big database system and browser for storage, querying and visualization of 3D genomic data (2015)
    Oxford University Press
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    Publication Date: 2015-09-19
    Description: Recent releases of genome three-dimensional (3D) structures have the potential to transform our understanding of genomes. Nonetheless, the storage technology and visualization tools need to evolve to offer to the scientific community fast and convenient access to these data. We introduce simultaneously a database system to store and query 3D genomic data ( 3DBG ), and a 3D genome browser to visualize and explore 3D genome structures ( 3DGB ). We benchmark 3DBG against state-of-the-art systems and demonstrate that it is faster than previous solutions, and importantly gracefully scales with the size of data. We also illustrate the usefulness of our 3D genome Web browser to explore human genome structures. The 3D genome browser is available at http://3dgb.cs.mcgill.ca/ .
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 2
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    Analysis of strand-specific RNA-seq data using machine learning reveals the structures of transcription units in Clostridium thermocellum (2015)
    Oxford University Press
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    Publication Date: 2015-05-29
    Description: Identification of transcription units (TUs) encoded in a bacterial genome is essential to elucidation of transcriptional regulation of the organism. To gain a detailed understanding of the dynamically composed TU structures, we have used four strand-specific RNA-seq (ssRNA-seq) datasets collected under two experimental conditions to derive the genomic TU organization of Clostridium thermocellum using a machine-learning approach. Our method accurately predicted the genomic boundaries of individual TUs based on two sets of parameters measuring the RNA-seq expression patterns across the genome: expression-level continuity and variance. A total of 2590 distinct TUs are predicted based on the four RNA-seq datasets. Among the predicted TUs, 44% have multiple genes. We assessed our prediction method on an independent set of RNA-seq data with longer reads. The evaluation confirmed the high quality of the predicted TUs. Functional enrichment analyses on a selected subset of the predicted TUs revealed interesting biology. To demonstrate the generality of the prediction method, we have also applied the method to RNA-seq data collected on Escherichia coli and achieved high prediction accuracies. The TU prediction program named SeqTU is publicly available at https://code.google.com/p/seqtu/ . We expect that the predicted TUs can serve as the baseline information for studying transcriptional and post-transcriptional regulation in C. thermocellum and other bacteria.
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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  • 3
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    A thesaurus of genetic variation for interrogation of repetitive genomic regions (2015)
    Oxford University Press
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    Publication Date: 2015-05-29
    Description: Detecting genetic variation is one of the main applications of high-throughput sequencing, but is still challenging wherever aligning short reads poses ambiguities. Current state-of-the-art variant calling approaches avoid such regions, arguing that it is necessary to sacrifice detection sensitivity to limit false discovery. We developed a method that links candidate variant positions within repetitive genomic regions into clusters. The technique relies on a resource, a thesaurus of genetic variation, that enumerates genomic regions with similar sequence. The resource is computationally intensive to generate, but once compiled can be applied efficiently to annotate and prioritize variants in repetitive regions. We show that thesaurus annotation can reduce the rate of false variant calls due to mappability by up to three orders of magnitude. We apply the technique to whole genome datasets and establish that called variants in low mappability regions annotated using the thesaurus can be experimentally validated. We then extend the analysis to a large panel of exomes to show that the annotation technique opens possibilities to study variation in hereto hidden and under-studied parts of the genome.
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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  • 4
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    Oligomycins and pamamycin homologs impair motility and induce lysis of zoospores of the grapevine downy mildew pathogen, Plasmopara viticola (2016)
    Oxford University Press
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    Publication Date: 2016-07-20
    Description: Four antibiotics (pamamycin, oligomycin A, oligomycin B and echinosporin) were isolated and characterized from the fermentation broth of the marine Streptomyces strains B8496 and B8739. Bioassays revealed that each of these compounds impaired motility and caused subsequent lysis of P. viticola zoospores in a dose- and time-dependent manner. Pamamycin displayed the strongest motility inhibitory and lytic activities (IC 50 0.1 μg mL –1 ) followed by oligomycin B (IC 50 0.15 and 0.2 μg mL –1 ) and oligomycin F (IC 50 0.3 and 0.5 μg mL –1 ). Oligomycin A and echinosporin also showed motility inhibitory activities against the zoospores with IC 50 values of 3.0 and 10.0 μg mL –1 , respectively. This is the first report of motility inhibitory and lytic activities of these antibiotics against zoospores of a phytopathogenic peronosporomycete. Structures of all the isolated compounds were determined based on detailed spectroscopic analysis.
    Keywords: Environmental Microbiology
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  • 5
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    Diverse sulfur metabolisms from two subterranean sulfidic spring systems (2016)
    Oxford University Press
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    Publication Date: 2016-07-31
    Description: In sulfidic environments, microbes oxidize reduced sulfur compounds via several pathways. We used metagenomics to investigate sulfur metabolic pathways from microbial mat communities in two subterranean sulfidic streams in Lower Kane Cave, WY, USA and from Glenwood Hot Springs, CO, USA. Both unassembled and targeted recA gene assembly analyses revealed that these streams were dominated by Epsilonproteobacteria and Gammaproteobacteria , including groups related to Sulfurovum , Sulfurospirillum , Thiothrix and an epsilonproteobacterial group with no close cultured relatives. Genes encoding sulfide:quinone oxidoreductase (SQR) were abundant at all sites, but the specific SQR type and the taxonomic affiliation of each type differed between sites. The abundance of thiosulfate oxidation pathway genes (Sox) was not consistent between sites, although overall they were less abundant than SQR genes. Furthermore, the Sox pathway appeared to be incomplete in all samples. This work reveals both variations in sulfur metabolism within and between taxonomic groups found in these systems, and the presence of novel epsilonproteobacterial groups.
    Keywords: Environmental Microbiology
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  • 6
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    Mutations in NalC induce MexAB-OprM overexpression resulting in high level of aztreonam resistance in environmental isolates of Pseudomonas aeruginosa (2016)
    Oxford University Press
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    Publication Date: 2016-07-31
    Description: Pseudomonas aeruginosa is an opportunistic pathogen with high resistance to a wide variety of antimicrobials. The multidrug resistance pump MexAB-OprM promotes the efflux of various antibiotics, mostly when mutations accumulate in the transcriptional regulators MexR, NalC and NalD, thereby causing MexAB-OprM overexpression. In this work, a characterization of 50 P. aeruginosa isolates obtained from Brazilian agricultural soils to determine the reasons of their resistance to aztreonam was done. The majority of the isolates showed higher aztreonam resistance than wild-type strain by MIC method. DNA sequence analysis of mexR , nalC and nalD genes from 13 of these isolates showed the amino acid substitution in NalC for all tested isolates, just one mutation was detected in MexR and none in NalD. Furthermore, an increase in the level of mexA expression by real-time RT-PCR analysis in eight isolates harboring mutations in NalC was found. Although there was not a relationship between MIC of aztreonam and the level of mexA expression, on the other hand, the results presented here suggest that novel mutations in NalC, including Arg 97 -Gly and Ala 186 -Thr, are related to MexAB-OprM overexpression causing aztreonam resistance in P. aeruginosa environmental isolates.
    Keywords: Environmental Microbiology
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  • 7
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    Identification of active aerobic methanotrophs in plateau wetlands using DNA stable isotope probing (2016)
    Oxford University Press
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    Publication Date: 2016-07-31
    Description: Sedge-dominated wetlands on the Qinghai–Tibetan Plateau are methane emission centers. Methanotrophs at these sites play a role in reducing methane emissions, but relatively little is known about the composition of active methanotrophs in these wetlands. Here, we used DNA stable isotope probing to identify the key active aerobic methanotrophs in three sedge-dominated wetlands on the plateau. We found that Methylocystis species were active in two peatlands, Hongyuan and Dangxiong. Methylobacter species were found to be active only in Dangxiong peat. Hongyuan peat had the highest methane oxidation rate, and cross-feeding of carbon from methanotrophs to methylotrophic Hyphomicrobium species was observed. Owing to a low methane oxidation rate during the incubation, the labeling of methanotrophs in Maduo wetland samples was not detected. Our results indicate that there are large differences in the activity of methanotrophs in the wetlands of this region.
    Keywords: Environmental Microbiology
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  • 8
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    MiniTn7-transposon delivery vectors for inducible or constitutive fluorescent protein expression in Enterobacteriaceae (2016)
    Oxford University Press
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    Publication Date: 2016-08-05
    Description: Here we present the generation and function of two sets of bacterial plasmids that harbor fluorescent genes encoding either blue, cyan, yellow or red fluorescent proteins. In the first set, protein expression is controlled by the strong and constitutive nptII promoter whereas in the second set, the strong tac promoter was chosen that underlies LacI q regulation. Furthermore, the plasmids are mobilizable, contain Tn 7 transposons and a temperature-sensitive origin of replication. Using Escherichia coli S17-1 as donor strain, the plasmids allow fast and convenient Tn 7 -transposon delivery into many enterobacterial hosts, such as the here-used E. coli O157:H7. This procedure omits the need of preparing competent recipient cells and antibiotic resistances are only transiently conferred to the recipients. As the fluorescence proteins show little to no overlap in fluorescence emission, the constructs are well suited for the study of multicolored synthetic bacterial communities during biofilm production or in host colonization studies, e.g. of plant surfaces. Furthermore, tac promoter-reporter constructs allow the generation of so-called reproductive success reporters, which allow to estimate past doublings of bacterial individuals after introduction into environments, emphasizing the role of individual cells during colonization.
    Keywords: Environmental Microbiology
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  • 9
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    De novo deciphering three-dimensional chromatin interaction and topological domains by wavelet transformation of epigenetic profiles (2016)
    Oxford University Press
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    Publication Date: 2016-06-21
    Description: Defining chromatin interaction frequencies and topological domains is a great challenge for the annotations of genome structures. Although the chromosome conformation capture (3C) and its derivative methods have been developed for exploring the global interactome, they are limited by high experimental complexity and costs. Here we describe a novel computational method, called CITD, for de novo prediction of the chromatin interaction map by integrating histone modification data. We used the public epigenomic data from human fibroblast IMR90 cell and embryonic stem cell (H1) to develop and test CITD, which can not only successfully reconstruct the chromatin interaction frequencies discovered by the Hi-C technology, but also provide additional novel details of chromosomal organizations. We predicted the chromatin interaction frequencies, topological domains and their states (e.g. active or repressive) for 98 additional cell types from Roadmap Epigenomics and ENCODE projects. A total of 131 protein-coding genes located near 78 preserved boundaries among 100 cell types are found to be significantly enriched in functional categories of the nucleosome organization and chromatin assembly. CITD and its predicted results can be used for complementing the topological domains derived from limited Hi-C data and facilitating the understanding of spatial principles underlying the chromosomal organization.
    Keywords: Chromatin and Epigenetics
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  • 10
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    A new molecular signature method for prediction of driver cancer pathways from transcriptional data (2016)
    Oxford University Press
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    Publication Date: 2016-06-21
    Description: Assigning cancer patients to the most effective treatments requires an understanding of the molecular basis of their disease. While DNA-based molecular profiling approaches have flourished over the past several years to transform our understanding of driver pathways across a broad range of tumors, a systematic characterization of key driver pathways based on RNA data has not been undertaken. Here we introduce a new approach for predicting the status of driver cancer pathways based on signature functions derived from RNA sequencing data. To identify the driver cancer pathways of interest, we mined DNA variant data from TCGA and nominated driver alterations in seven major cancer pathways in breast, ovarian and colon cancer tumors. The activation status of these driver pathways were then characterized using RNA sequencing data by constructing classification signature functions in training datasets and then testing the accuracy of the signatures in test datasets. The signature functions differentiate well tumors with nominated pathway activation from tumors with no signs of activation: average AUC equals to 0.83. Our results confirm that driver genomic alterations are distinctively displayed at the transcriptional level and that the transcriptional signatures can generally provide an alternative to DNA sequencing methods in detecting specific driver pathways.
    Keywords: Computational Methods, Genomics
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  • 11
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    Increase of genetic diversity and clonal replacement of epidemic methicillin-resistant Staphylococcus aureus strains in South-East Austria (2016)
    Oxford University Press
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    Publication Date: 2016-06-23
    Description: Spa -typing and microarray techniques were used to study epidemiological changes in methicillin-resistant Staphylococcus aureus (MRSA) in South-East Austria. The population structure of 327 MRSA isolated between 2002 and 2012 was investigated. MRSA was assigned to 58 different spa types and 14 different MLST CC (multilocus sequence type clonal complexes); in particular, between 2007 and 2012, an increasing diversity in MRSA clones could be observed. The most abundant clonal complex was CC5. On the respective SCC mec cassettes, the CC5 isolates differed clearly within this decade and CC5/SCC mec I, the South German MRSA, predominant in 2002, was replaced by CC5/SCC mec II, the Rhine-Hesse MRSA in 2012. Whereas in many European countries MLST CC22-MRSA (EMRSA 15, the Barnim epidemic MRSA) is predominant, this clone occurred in Austria nearly 10 years later than in neighbouring countries. CC45, the Berlin EMRSA, epidemic in Germany, was only sporadically found in South-East Austria. The Irish ST8-MRSA-II represented by spa -type t190 was frequently found in 2002 and 2007, but disappeared in 2012. Our results demonstrate clonal replacement of MRSA clones within the last years in Austria. Ongoing surveillance is warranted for detection of changes within the MRSA population.
    Keywords: Environmental Microbiology
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  • 12
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    Effects of dietary fibre source on microbiota composition in the large intestine of suckling piglets (2016)
    Oxford University Press
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    Publication Date: 2016-06-23
    Description: This study aimed to investigate the effects of dietary fibre sources on the gut microbiota in suckling piglets, and to test the hypothesis that a moderate increase of dietary fibre may affect the gut microbiota during the suckling period. Suckling piglets were fed different fibre-containing diets or a control diet from postnatal day 7 to 22. Digesta samples from cecum, proximal colon and distal colon were used for Pig Intestinal Tract Chip analysis. The data showed that the effects of fibre-containing diet on the gut microbiota differed in the fibre source and gut location. The alfalfa diet increased Clostridium cluster XIVb and Sporobacter termitidis in the cecum compared to the pure cellulose diet. Compared to the control diet, the alfalfa diet also increased Coprococcus eutactus in the distal colon, while the pure cellulose diet decreased Eubacterium pyruvativorans in the cecum. The pure cellulose diet increased Prevotella ruminicola compared to the wheat bran diet. Interestingly, the alfalfa group had the lowest abundance of the potential pathogen Streptococcus suis in the cecum and distal colon. These results indicated that a moderate increase in dietary fibres affected the microbial composition in suckling piglets, and that the alfalfa inclusion produced some beneficial effects on the microbial communities.
    Keywords: Environmental Microbiology
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  • 13
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    Microbial detoxification in the gut of a specialist avian herbivore, the Greater Sage-Grouse (2016)
    Oxford University Press
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    Publication Date: 2016-06-23
    Description: One function of the gut microbiota gaining recent attention, especially in herbivorous mammals and insects, is the metabolism of plant secondary metabolites (PSMs). We investigated whether this function exists within the gut communities of a specialist avian herbivore. We sequenced the cecal metagenome of the Greater Sage-Grouse ( Centrocercus urophasianus ), which specializes on chemically defended sagebrush ( Artemisia spp.). We predicted that the cecal metagenome of the sage-grouse would be enriched in genes associated with the metabolism of PSMs when compared to the metagenome of the domestic chicken. We found that representation of microbial genes associated with ‘xenobiotic degradation and metabolism’ was 3-fold higher in the sage-grouse cecal metagenomes when compared to that of the domestic chicken. Further, we identified a complete metabolic pathway for the degradation of phenol to pyruvate, which was not detected in the metagenomes of the domestic chicken, bovine rumen or 14 species of mammalian herbivores. Evidence of monoterpene degradation (a major class of PSMs in sagebrush) was less definitive, although we did detect genes for several enzymes associated with this process. Overall, our results suggest that the gut microbiota of specialist avian herbivores plays a similar role to the microbiota of mammalian and insect herbivores in degrading PSMs.
    Keywords: Environmental Microbiology
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  • 14
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    DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences (2016)
    Oxford University Press
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    Publication Date: 2016-06-21
    Description: Modeling the properties and functions of DNA sequences is an important, but challenging task in the broad field of genomics. This task is particularly difficult for non-coding DNA, the vast majority of which is still poorly understood in terms of function. A powerful predictive model for the function of non-coding DNA can have enormous benefit for both basic science and translational research because over 98% of the human genome is non-coding and 93% of disease-associated variants lie in these regions. To address this need, we propose DanQ, a novel hybrid convolutional and bi-directional long short-term memory recurrent neural network framework for predicting non-coding function de novo from sequence. In the DanQ model, the convolution layer captures regulatory motifs, while the recurrent layer captures long-term dependencies between the motifs in order to learn a regulatory ‘grammar’ to improve predictions. DanQ improves considerably upon other models across several metrics. For some regulatory markers, DanQ can achieve over a 50% relative improvement in the area under the precision-recall curve metric compared to related models. We have made the source code available at the github repository http://github.com/uci-cbcl/DanQ .
    Keywords: Computational Methods, Genomics
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  • 15
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    Phylogeny-aware identification and correction of taxonomically mislabeled sequences (2016)
    Oxford University Press
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    Publication Date: 2016-06-21
    Description: Molecular sequences in public databases are mostly annotated by the submitting authors without further validation. This procedure can generate erroneous taxonomic sequence labels. Mislabeled sequences are hard to identify, and they can induce downstream errors because new sequences are typically annotated using existing ones. Furthermore, taxonomic mislabelings in reference sequence databases can bias metagenetic studies which rely on the taxonomy. Despite significant efforts to improve the quality of taxonomic annotations, the curation rate is low because of the labor-intensive manual curation process. Here, we present SATIVA, a phylogeny-aware method to automatically identify taxonomically mislabeled sequences (‘mislabels’) using statistical models of evolution. We use the Evolutionary Placement Algorithm (EPA) to detect and score sequences whose taxonomic annotation is not supported by the underlying phylogenetic signal, and automatically propose a corrected taxonomic classification for those. Using simulated data, we show that our method attains high accuracy for identification (96.9% sensitivity/91.7% precision) as well as correction (94.9% sensitivity/89.9% precision) of mislabels. Furthermore, an analysis of four widely used microbial 16S reference databases (Greengenes, LTP, RDP and SILVA) indicates that they currently contain between 0.2% and 2.5% mislabels. Finally, we use SATIVA to perform an in-depth evaluation of alternative taxonomies for Cyanobacteria. SATIVA is freely available at https://github.com/amkozlov/sativa .
    Keywords: Computational Methods, Genomics
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  • 16
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    iGEMS: an integrated model for identification of alternative exon usage events (2016)
    Oxford University Press
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    Publication Date: 2016-06-21
    Description: DNA microarrays and RNAseq are complementary methods for studying RNA molecules. Current computational methods to determine alternative exon usage (AEU) using such data require impractical visual inspection and still yield high false-positive rates. Integrated Gene and Exon Model of Splicing (iGEMS) adapts a gene-level residuals model with a gene size adjusted false discovery rate and exon-level analysis to circumvent these limitations. iGEMS was applied to two new DNA microarray datasets, including the high coverage Human Transcriptome Arrays 2.0 and performance was validated using RT-qPCR. First, AEU was studied in adipocytes treated with ( n = 9) or without ( n = 8) the anti-diabetes drug, rosiglitazone. iGEMS identified 555 genes with AEU, and robust verification by RT-qPCR (~90%). Second, in a three-way human tissue comparison (muscle, adipose and blood, n = 41) iGEMS identified 4421 genes with at least one AEU event, with excellent RT-qPCR verification (95%, n = 22). Importantly, iGEMS identified a variety of AEU events, including 3'UTR extension, as well as exon inclusion/exclusion impacting on protein kinase and extracellular matrix domains. In conclusion, iGEMS is a robust method for identification of AEU while the variety of exon usage between human tissues is 5–10 times more prevalent than reported by the Genotype-Tissue Expression consortium using RNA sequencing.
    Keywords: Computational Methods, Genomics
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  • 17
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    Endosymbiotic bacteria in honey bees: Arsenophonus spp. are not transmitted transovarially (2016)
    Oxford University Press
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    Publication Date: 2016-06-23
    Description: Intracellular endosymbiotic bacteria are common and can play a crucial role for insect pathology. Therefore, such bacteria could be a potential key to our understanding of major losses of Western honey bees ( Apis mellifera ) colonies. However, the transmission and potential effects of endosymbiotic bacteria in A. mellifera and other Apis spp. are poorly understood. Here, we explore the prevalence and transmission of the genera Arsenophonus , Wolbachia , Spiroplasma and Rickettsia in Apis spp. Colonies of A. mellifera ( N = 33, with 20 eggs from worker brood cells and 100 adult workers each) as well as mated honey bee queens of A. cerana , A. dorsata and A. florea ( N = 12 each) were screened using PCR. While Wolbachia , Spiroplasma and Rickettsia were not detected, Arsenophonus spp. were found in 24.2% of A. mellifera colonies and respective queens as well as in queens of A. dorsata (8.3%) and A. florea (8.3%), but not in A. cerana . The absence of Arsenophonus spp. from reproductive organs of A. mellifera queens and surface-sterilized eggs does not support transovarial vertical transmission. Instead, horizontal transmission is most likely.
    Keywords: Environmental Microbiology
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  • 18
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    TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data (2016)
    Oxford University Press
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    Publication Date: 2016-05-06
    Description: The Cancer Genome Atlas (TCGA) research network has made public a large collection of clinical and molecular phenotypes of more than 10 000 tumor patients across 33 different tumor types. Using this cohort, TCGA has published over 20 marker papers detailing the genomic and epigenomic alterations associated with these tumor types. Although many important discoveries have been made by TCGA's research network, opportunities still exist to implement novel methods, thereby elucidating new biological pathways and diagnostic markers. However, mining the TCGA data presents several bioinformatics challenges, such as data retrieval and integration with clinical data and other molecular data types (e.g. RNA and DNA methylation). We developed an R/Bioconductor package called TCGAbiolinks to address these challenges and offer bioinformatics solutions by using a guided workflow to allow users to query, download and perform integrative analyses of TCGA data. We combined methods from computer science and statistics into the pipeline and incorporated methodologies developed in previous TCGA marker studies and in our own group. Using four different TCGA tumor types (Kidney, Brain, Breast and Colon) as examples, we provide case studies to illustrate examples of reproducibility, integrative analysis and utilization of different Bioconductor packages to advance and accelerate novel discoveries.
    Keywords: Computational Methods, Genomics
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  • 19
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    Robust detection of alternative splicing in a population of single cells (2016)
    Oxford University Press
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    Publication Date: 2016-05-06
    Description: Single cell RNA-seq experiments provide valuable insight into cellular heterogeneity but suffer from low coverage, 3' bias and technical noise. These unique properties of single cell RNA-seq data make study of alternative splicing difficult, and thus most single cell studies have restricted analysis of transcriptome variation to the gene level. To address these limitations, we developed SingleSplice, which uses a statistical model to detect genes whose isoform usage shows biological variation significantly exceeding technical noise in a population of single cells. Importantly, SingleSplice is tailored to the unique demands of single cell analysis, detecting isoform usage differences without attempting to infer expression levels for full-length transcripts. Using data from spike-in transcripts, we found that our approach detects variation in isoform usage among single cells with high sensitivity and specificity. We also applied SingleSplice to data from mouse embryonic stem cells and discovered a set of genes that show significant biological variation in isoform usage across the set of cells. A subset of these isoform differences are linked to cell cycle stage, suggesting a novel connection between alternative splicing and the cell cycle.
    Keywords: Computational Methods, Genomics
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  • 20
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    Widespread ability of fungi to drive quinone redox cycling for biodegradation (2016)
    Oxford University Press
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    Publication Date: 2016-05-12
    Description: Wood-rotting fungi possess remarkably diverse extracellular oxidation mechanisms, including enzymes, such as laccase and peroxidases, and Fenton chemistry. The ability to biologically drive Fenton chemistry by the redox cycling of quinones has previously been reported to be present in both ecologically diverging main groups of wood-rotting basidiomycetes. Therefore, we investigated whether it is even more widespread among fungal organisms. Screening of a diverse selection of a total of 18 ascomycetes and basidiomycetes for reduction of the model compound 2,6-dimethoxy benzoquinone revealed that all investigated strains were capable of reducing it to its corresponding hydroquinone. In a second step, depolymerization of the synthetic polymer polystyrene sulfonate was used as a proxy for quinone-dependent Fenton-based biodegradation capabilities. A diverse subset of the strains, including environmentally ubiquitous molds, white-rot fungi, as well as peatland and aquatic isolates, caused substantial depolymerization indicative for the effective employment of quinone redox cycling as biodegradation tool. Our results may also open up new paths to utilize diverse fungi for the bioremediation of recalcitrant organic pollutants.
    Keywords: Environmental Microbiology
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    Properties and biotechnological applications of ice-binding proteins in bacteria (2016)
    Oxford University Press
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    Publication Date: 2016-05-12
    Description: Ice-binding proteins (IBPs), such as antifreeze proteins (AFPs) and ice-nucleating proteins (INPs), have been described in diverse cold-adapted organisms, and their potential applications in biotechnology have been recognized in various fields. Currently, both IBPs are being applied to biotechnological processes, primarily in medicine and the food industry. However, our knowledge regarding the diversity of bacterial IBPs is limited; few studies have purified and characterized AFPs and INPs from bacteria. Phenotypically verified IBPs have been described in members belonging to Gammaproteobacteria, Actinobacteria and Flavobacteriia classes, whereas putative IBPs have been found in Gammaproteobacteria, Alphaproteobacteria and Bacilli classes. Thus, the main goal of this minireview is to summarize the current information on bacterial IBPs and their application in biotechnology, emphasizing the potential application in less explored fields such as agriculture. Investigations have suggested the use of INP-producing bacteria antagonists and AFPs-producing bacteria (or their AFPs) as a very attractive strategy to prevent frost damages in crops. UniProt database analyses of reported IBPs (phenotypically verified) and putative IBPs also show the limited information available on bacterial IBPs and indicate that major studies are required.
    Keywords: Environmental Microbiology
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    Cloning, expression and mutation of a triazophos hydrolase gene from Burkholderia sp. SZL-1 (2016)
    Oxford University Press
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    Publication Date: 2016-05-12
    Description: Triazophos is a broad-spectrum and highly effective insecticide, and the residues of triazophos have been frequently detected in the environment. A triazophos-degrading bacterium, Burkholderia sp. SZL-1, was isolated from a long-term triazophos-polluted soil. Strain SZL-1 could hydrolyze triazophos to 1-phenyl-3-hydroxy-1,2,4-triazole, which was further utilized as the carbon sources for growth. The triazophos hydrolase gene trhA , cloned from strain SZL-1, was expressed and homogenously purified using Ni-nitrilotriacetic acid affinity chromatography. TrhA is 55 kDa and displays maximum activity at 25°C, pH 8.0. This enzyme still has nearly 60% activity at the range of 15°C–50°C for 30 min. TrhA was mutated by sequential error prone PCR and screened for improved activity for triazophos degradation. One purified variant protein (Val89-Gly89) named TrhA-M1 showed up to 3-fold improvement in specific activity against triazophos, and the specificity constants of K cat and K cat / K m for TrhA-M1 were improved up to 2.3- and 8.28-fold, respectively, compared to the wild-type enzyme. The results in this paper provided potential material for the contaminated soil remediation and hydrolase genetic structure research.
    Keywords: Environmental Microbiology
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    A case in support of implementing innovative bio-processes in the metal mining industry (2016)
    Oxford University Press
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    Publication Date: 2016-05-12
    Description: The metal mining industry faces many large challenges in future years, among which is the increasing need to process low-grade ores as accessible higher grade ores become depleted. This is against a backdrop of increasing global demands for base and precious metals, and rare earth elements. Typically about 99% of solid material hauled to, and ground at, the land surface currently ends up as waste (rock dumps and mineral tailings). Exposure of these to air and water frequently leads to the formation of acidic, metal-contaminated run-off waters, referred to as acid mine drainage, which constitutes a severe threat to the environment. Formation of acid drainage is a natural phenomenon involving various species of lithotrophic (literally ‘rock-eating’) bacteria and archaea, which oxidize reduced forms of iron and/or sulfur. However, other microorganisms that reduce inorganic sulfur compounds can essentially reverse this process. These microorganisms can be applied on industrial scale to precipitate metals from industrial mineral leachates and acid mine drainage streams, resulting in a net improvement in metal recovery, while minimizing the amounts of leachable metals to the tailings storage dams. Here, we advocate that more extensive exploitation of microorganisms in metal mining operations could be an important way to green up the industry, reducing environmental risks and improving the efficiency and the economy of metal recovery.
    Keywords: Environmental Microbiology
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    CARGO: effective format-free compressed storage of genomic information (2016)
    Oxford University Press
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    Publication Date: 2016-07-09
    Description: The recent super-exponential growth in the amount of sequencing data generated worldwide has put techniques for compressed storage into the focus. Most available solutions, however, are strictly tied to specific bioinformatics formats, sometimes inheriting from them suboptimal design choices; this hinders flexible and effective data sharing. Here, we present CARGO (Compressed ARchiving for GenOmics), a high-level framework to automatically generate software systems optimized for the compressed storage of arbitrary types of large genomic data collections. Straightforward applications of our approach to FASTQ and SAM archives require a few lines of code, produce solutions that match and sometimes outperform specialized format-tailored compressors and scale well to multi-TB datasets. All CARGO software components can be freely downloaded for academic and non-commercial use from http://bio-cargo.sourceforge.net .
    Keywords: Computational Methods, Genomics
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    InPhaDel: integrative shotgun and proximity-ligation sequencing to phase deletions with single nucleotide polymorphisms (2016)
    Oxford University Press
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    Publication Date: 2016-07-09
    Description: Phasing of single nucleotide (SNV), and structural variations into chromosome-wide haplotypes in humans has been challenging, and required either trio sequencing or restricting phasing to population-based haplotypes. Selvaraj et al . demonstrated single individual SNV phasing is possible with proximity ligated (HiC) sequencing. Here, we demonstrate HiC can phase structural variants into phased scaffolds of SNVs. Since HiC data is noisy, and SV calling is challenging, we applied a range of supervised classification techniques, including Support Vector Machines and Random Forest, to phase deletions. Our approach was demonstrated on deletion calls and phasings on the NA12878 human genome. We used three NA12878 chromosomes and simulated chromosomes to train model parameters. The remaining NA12878 chromosomes withheld from training were used to evaluate phasing accuracy. Random Forest had the highest accuracy and correctly phased 86% of the deletions with allele-specific read evidence. Allele-specific read evidence was found for 76% of the deletions. HiC provides significant read evidence for accurately phasing 33% of the deletions. Also, eight of eight top ranked deletions phased by only HiC were validated using long range polymerase chain reaction and Sanger. Thus, deletions from a single individual can be accurately phased using a combination of shotgun and proximity ligation sequencing. InPhaDel software is available at: http://l337x911.github.io/inphadel/.
    Keywords: Computational Methods, Genomics
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    Redundans: an assembly pipeline for highly heterozygous genomes (2016)
    Oxford University Press
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    Publication Date: 2016-07-09
    Description: Many genomes display high levels of heterozygosity (i.e. presence of different alleles at the same loci in homologous chromosomes), being those of hybrid organisms an extreme such case. The assembly of highly heterozygous genomes from short sequencing reads is a challenging task because it is difficult to accurately recover the different haplotypes. When confronted with highly heterozygous genomes, the standard assembly process tends to collapse homozygous regions and reports heterozygous regions in alternative contigs. The boundaries between homozygous and heterozygous regions result in multiple assembly paths that are hard to resolve, which leads to highly fragmented assemblies with a total size larger than expected. This, in turn, causes numerous problems in downstream analyses such as fragmented gene models, wrong gene copy number, or broken synteny. To circumvent these caveats we have developed a pipeline that specifically deals with the assembly of heterozygous genomes by introducing a step to recognise and selectively remove alternative heterozygous contigs. We tested our pipeline on simulated and naturally-occurring heterozygous genomes and compared its accuracy to other existing tools. Our method is freely available at https://github.com/Gabaldonlab/redundans .
    Keywords: Computational Methods, Genomics
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    Inducible DamID systems for genomic mapping of chromatin proteins in Drosophila (2016)
    Oxford University Press
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    Publication Date: 2016-07-09
    Description: Dam identification (DamID) is a powerful technique to generate genome-wide maps of chromatin protein binding. Due to its high sensitivity, it is particularly suited to study the genome interactions of chromatin proteins in small tissue samples in model organisms such as Drosophila . Here, we report an intein-based approach to tune the expression level of Dam and Dam-fusion proteins in Drosophila by addition of a ligand to fly food. This helps to suppress possible toxic effects of Dam. In addition, we describe a strategy for genetically controlled expression of Dam in a specific cell type in complex tissues. We demonstrate the utility of the latter by generating a glia-specific map of Polycomb in small samples of brain tissue. These new DamID tools will be valuable for the mapping of binding patterns of chromatin proteins in Drosophila tissues and especially in cell lineages.
    Keywords: Chromatin and Epigenetics
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    Following the footprints of polymorphic inversions on SNP data: from detection to association tests (2015)
    Oxford University Press
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    Publication Date: 2015-05-03
    Description: Inversion polymorphisms have important phenotypic and evolutionary consequences in humans. Two different methodologies have been used to infer inversions from SNP dense data, enabling the use of large cohorts for their study. One approach relies on the differences in linkage disequilibrium across breakpoints; the other one captures the internal haplotype groups that tag the inversion status of chromosomes. In this article, we assessed the convergence of the two methods in the detection of 20 human inversions that have been reported in the literature. The methods converged in four inversions including inv-8p23, for which we studied its association with low-BMI in American children. Using a novel haplotype tagging method with control on inversion ancestry, we computed the frequency of inv-8p23 in two American cohorts and observed inversion haplotype admixture. Accounting for haplotype ancestry, we found that the European inverted allele in children carries a recessive risk of underweight, validated in an independent Spanish cohort (combined: OR= 2.00, P = 0.001). While the footprints of inversions on SNP data are complex, we show that systematic analyses, such as convergence of different methods and controlling for ancestry, can reveal the contribution of inversions to the ancestral composition of populations and to the heritability of human disease.
    Keywords: Computational Methods, Genomics
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    Reconstructing genome-scale metabolic models with merlin (2015)
    Oxford University Press
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    Publication Date: 2015-05-03
    Description: The Metabolic Models Reconstruction Using Genome-Scale Information ( merlin ) tool is a user-friendly Java application that aids the reconstruction of genome-scale metabolic models for any organism that has its genome sequenced. It performs the major steps of the reconstruction process, including the functional genomic annotation of the whole genome and subsequent construction of the portfolio of reactions. Moreover, merlin includes tools for the identification and annotation of genes encoding transport proteins, generating the transport reactions for those carriers. It also performs the compartmentalisation of the model, predicting the organelle localisation of the proteins encoded in the genome and thus the localisation of the metabolites involved in the reactions promoted by such enzymes. The gene-proteins-reactions (GPR) associations are automatically generated and included in the model. Finally, merlin expedites the transition from genomic data to draft metabolic models reconstructions exported in the SBML standard format, allowing the user to have a preliminary view of the biochemical network, which can be manually curated within the environment provided by merlin .
    Keywords: Computational Methods, Genomics
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    Inferential modeling of 3D chromatin structure (2015)
    Oxford University Press
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    Publication Date: 2015-05-03
    Description: For eukaryotic cells, the biological processes involving regulatory DNA elements play an important role in cell cycle. Understanding 3D spatial arrangements of chromosomes and revealing long-range chromatin interactions are critical to decipher these biological processes. In recent years, chromosome conformation capture (3C) related techniques have been developed to measure the interaction frequencies between long-range genome loci, which have provided a great opportunity to decode the 3D organization of the genome. In this paper, we develop a new Bayesian framework to derive the 3D architecture of a chromosome from 3C-based data. By modeling each chromosome as a polymer chain, we define the conformational energy based on our current knowledge on polymer physics and use it as prior information in the Bayesian framework. We also propose an expectation-maximization (EM) based algorithm to estimate the unknown parameters of the Bayesian model and infer an ensemble of chromatin structures based on interaction frequency data. We have validated our Bayesian inference approach through cross-validation and verified the computed chromatin conformations using the geometric constraints derived from fluorescence in situ hybridization (FISH) experiments. We have further confirmed the inferred chromatin structures using the known genetic interactions derived from other studies in the literature. Our test results have indicated that our Bayesian framework can compute an accurate ensemble of 3D chromatin conformations that best interpret the distance constraints derived from 3C-based data and also agree with other sources of geometric constraints derived from experimental evidence in the previous studies. The source code of our approach can be found in https://github.com/wangsy11/InfMod3DGen .
    Keywords: Computational Methods, Genomics
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    Integrating motif, DNA accessibility and gene expression data to build regulatory maps in an organism (2015)
    Oxford University Press
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    Publication Date: 2015-05-03
    Description: Characterization of cell type specific regulatory networks and elements is a major challenge in genomics, and emerging strategies frequently employ high-throughput genome-wide assays of transcription factor (TF) to DNA binding, histone modifications or chromatin state. However, these experiments remain too difficult/expensive for many laboratories to apply comprehensively to their system of interest. Here, we explore the potential of elucidating regulatory systems in varied cell types using computational techniques that rely on only data of gene expression, low-resolution chromatin accessibility, and TF–DNA binding specificities (‘motifs’). We show that static computational motif scans overlaid with chromatin accessibility data reasonably approximate experimentally measured TF–DNA binding. We demonstrate that predicted binding profiles and expression patterns of hundreds of TFs are sufficient to identify major regulators of ~200 spatiotemporal expression domains in the Drosophila embryo. We are then able to learn reliable statistical models of enhancer activity for over 70 expression domains and apply those models to annotate domain specific enhancers genome-wide. Throughout this work, we apply our motif and accessibility based approach to comprehensively characterize the regulatory network of fruitfly embryonic development and show that the accuracy of our computational method compares favorably to approaches that rely on data from many experimental assays.
    Keywords: Computational Methods, Genomics
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    Nitric oxide scavengers differentially inhibit ammonia oxidation in ammonia-oxidizing archaea and bacteria (2016)
    Oxford University Press
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    Publication Date: 2016-04-01
    Description: Differential inhibitors are important for measuring the relative contributions of microbial groups, such as ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA), to biogeochemical processes in environmental samples. In particular, 2-phenyl-4,4,5,5-tetramethylimidazoline-1-oxyl 3-oxide (PTIO) represents a nitric oxide scavenger used for the specific inhibition of AOA, implicating nitric oxide as an intermediate of thaumarchaeotal ammonia oxidation. This study investigated four alternative nitric oxide scavengers for their ability to differentially inhibit AOA and AOB in comparison to PTIO. Caffeic acid, curcumin, methylene blue hydrate and trolox were tested on Nitrosopumilus maritimus , two unpublished AOA representatives (AOA-6f and AOA-G6) as well as the AOB representative Nitrosomonas europaea . All four scavengers inhibited ammonia oxidation by AOA at lower concentrations than for AOB. In particular, differential inhibition of AOA and AOB by caffeic acid (100 μM) and methylene blue hydrate (3 μM) was comparable to carboxy-PTIO (100 μM) in pure and enrichment culture incubations. However, when added to aquarium sponge biofilm microcosms, both scavengers were unable to inhibit ammonia oxidation consistently, likely due to degradation of the inhibitors themselves. This study provides evidence that a variety of nitric oxide scavengers result in differential inhibition of ammonia oxidation in AOA and AOB, and provides support to the proposed role of nitric oxide as a key intermediate in the thaumarchaeotal ammonia oxidation pathway.
    Keywords: Environmental Microbiology
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    A statistical framework for revealing signaling pathways perturbed by DNA variants (2015)
    Oxford University Press
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    Publication Date: 2015-06-24
    Description: Much of the inter-individual variation in gene expression is triggered via perturbations of signaling networks by DNA variants. We present a novel probabilistic approach for identifying the particular pathways by which DNA variants perturb the signaling network. Our procedure, called PINE, relies on a systematic integration of established biological knowledge of signaling networks with data on transcriptional responses to various experimental conditions. Unlike previous approaches, PINE provides statistical aspects that are critical for prioritizing hypotheses for followup experiments. Using simulated data, we show that higher accuracy is attained with PINE than with existing methods. We used PINE to analyze transcriptional responses of immune dendritic cells to several pathogenic stimulations. PINE identified statistically significant genetic perturbations in the pathogen-sensing signaling network, suggesting previously uncharacterized regulatory mechanisms for functional DNA variants.
    Keywords: Computational Methods, Genomics
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    Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses (2015)
    Oxford University Press
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    Publication Date: 2015-08-29
    Description: Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates this by modelling heterogeneity at both the sample and observational levels as part of the differential expression analysis. At the sample level this is achieved by fitting a log-linear variance model that includes common sample-specific or group-specific parameters that are shared between genes. The estimated sample variance factors are then converted to weights and combined with observational level weights obtained from the mean–variance relationship of the log-counts-per-million using ‘voom’. A comprehensive analysis involving both simulations and experimental RNA-sequencing data demonstrates that this strategy leads to a universally more powerful analysis and fewer false discoveries when compared to conventional approaches. This methodology has wide application and is implemented in the open-source ‘limma’ package.
    Keywords: Computational Methods, Genomics
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    RAX2: a genome-wide detection method of condition-associated transcription variation (2015)
    Oxford University Press
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    Publication Date: 2015-08-29
    Description: Most mammalian genes have mRNA variants due to alternative promoter usage, alternative splicing, and alternative cleavage and polyadenylation. Expression of alternative RNA isoforms has been found to be associated with tumorigenesis, proliferation and differentiation. Detection of condition-associated transcription variation requires association methods. Traditional association methods such as Pearson chi-square test and Fisher Exact test are single test methods and do not work on count data with replicates. Although the Cochran Mantel Haenszel (CMH) approach can handle replicated count data, our simulations showed that multiple CMH tests still had very low power. To identify condition-associated variation of transcription, we here proposed a ranking analysis of chi-squares (RAX2) for large-scale association analysis. RAX2 is a nonparametric method and has accurate and conservative estimation of FDR profile. Simulations demonstrated that RAX2 performs well in finding condition-associated transcription variants. We applied RAX2 to primary T-cell transcriptomic data and identified 1610 (16.3%) tags associated in transcription with immune stimulation at FDR 〈 0.05. Most of these tags also had differential expression. Analysis of two and three tags within genes revealed that under immune stimulation short RNA isoforms were preferably used.
    Keywords: Computational Methods, Genomics
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    A novel isolate and widespread abundance of the candidate alphaproteobacterial order (Ellin 329), in southern Appalachian peatlands (2016)
    Oxford University Press
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    Publication Date: 2016-07-02
    Description: Peatlands of all latitudes play an integral role in global climate change by serving as a carbon sink and a primary source of atmospheric methane; however, the microbial ecology of mid-latitude peatlands is vastly understudied. Herein, next generation Illumina amplicon sequencing of small subunit rRNA genes was utilized to elucidate the microbial communities in three southern Appalachian peatlands. In contrast to northern peatlands, Proteobacteria dominated over Acidobacteria in all three sites. An average of 11 bacterial phyla was detected at relative abundance values 〉1%, with three candidate divisions (OP3, WS3 and NC10) represented, indicating high phylogenetic diversity. Physiological traits of isolates within the candidate alphaproteobacterial order, Ellin 329, obtained here and in previous studies indicate that bacteria of this order may be involved in hydrolysis of poly-, di- and monosaccharides. Community analyses indicate that Ellin 329 is the third most abundant order and is most abundant near the surface layers where plant litter decomposition should be primarily occurring. In sum, members of Ellin 329 likely play important roles in organic matter decomposition, in southern Appalachian peatlands and should be investigated further in other peatlands and ecosystem types.
    Keywords: Environmental Microbiology
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    Marine phage genomics: the tip of the iceberg (2016)
    Oxford University Press
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    Publication Date: 2016-07-02
    Description: Marine viruses are the most abundant biological entity in the oceans, the majority of which infect bacteria and are known as bacteriophages. Yet, the bulk of bacteriophages form part of the vast uncultured dark matter of the microbial biosphere. In spite of the paucity of cultured marine bacteriophages, it is known that marine bacteriophages have major impacts on microbial population structure and the biogeochemical cycling of key elements. Despite the ecological relevance of marine bacteriophages, there are relatively few isolates with complete genome sequences. This minireview focuses on knowledge gathered from these genomes put in the context of viral metagenomic data and highlights key advances in the field, particularly focusing on genome structure and auxiliary metabolic genes.
    Keywords: Environmental Microbiology
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    Plants of the fynbos biome harbour host species-specific bacterial communities (2016)
    Oxford University Press
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    Publication Date: 2016-07-02
    Description: The fynbos biome in South Africa is globally recognised as a plant biodiversity hotspot. However, very little is known about the bacterial communities associated with fynbos plants, despite interactions between primary producers and bacteria having an impact on the physiology of both partners and shaping ecosystem diversity. This study reports on the structure, phylogenetic composition and potential roles of the endophytic bacterial communities located in the stems of three fynbos plants ( Erepsia anceps , Phaenocoma prolifera and Leucadendron laureolum ). Using Illumina MiSeq 16S rRNA sequencing we found that different subpopulations of Deinococcus-Thermus, Alphaproteobacteria, Acidobacteria and Firmicutes dominated the endophytic bacterial communities. Alphaproteobacteria and Actinobacteria were prevalent in P. prolifera , whereas Deinococcus-Thermus dominated in L. laureolum , revealing species-specific host–bacteria associations. Although a high degree of variability in the endophytic bacterial communities within hosts was observed, we also detected a core microbiome across the stems of the three plant species, which accounted for 72% of the sequences. Altogether, it seems that both deterministic and stochastic processes shaped microbial communities. Endophytic bacterial communities harboured putative plant growth-promoting bacteria, thus having the potential to influence host health and growth.
    Keywords: Environmental Microbiology
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    Millimeter scale electron conduction through exoelectrogenic mixed species biofilms (2016)
    Oxford University Press
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    Publication Date: 2016-07-03
    Description: The functioning of many natural and engineered environments is dependent on long distance electron transfer mediated through electrical currents. These currents have been observed in exoelectrogenic biofilms and it has been proposed that microbial biofilms can mediate electron transfer via electrical currents on the centimeter scale. However, direct evidence to confirm this hypothesis has not been demonstrated and the longest known electrical transfer distance for single species exoelectrogenic biofilms is limited to 100 μm. In the present study, biofilms were developed on electrodes with electrically non-conductive gaps from 50 μm to 1 mm and the in situ conductance of biofilms was evaluated over time. Results demonstrated that the exoelectrogenic mixed species biofilms in the present study possess the ability to transfer electrons through electrical currents over a distance of up to 1 mm, 10 times further than previously observed. Results indicate the possibility of interspecies interactions playing an important role in the spatial development of exoelectrogenic biofilms, suggesting that these biological networks might remain conductive even at longer distance. These findings have significant implications in regards to future optimization of microbial electrochemical systems.
    Keywords: Environmental Microbiology
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    Simultaneous detection of somatic and F-specific coliphages in different settings by Escherichia coli strain CB390 (2016)
    Oxford University Press
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    Publication Date: 2016-08-28
    Description: Bacteriophages are increasingly being used as water quality indicators. Two groups of phages infecting Escherichia coli , somatic and F-specific coliphages, are being considered as indicators of fecal and viral contamination for several types of water around the world. However, some uncertainties remain regarding which coliphages to assess. Recently, E. coli strain CB390 has been reported to be suitable for simultaneous detection of both groups, which seems to be more informative than determining only one of the groups. Here, a significant number of samples from different settings, mostly those where F-specific phages have been reported to outnumber somatic coliphages, are analyzed for somatic coliphages, F-specific RNA phages by standardized methods and coliphages detected by host strain CB390. The results presented here confirm that the numbers of phages counted using CB390 are equivalent to the sum of the somatic and F-specific coliphages counted independently in all settings. Hence the usefulness of this strain for simultaneous detection of somatic and F-specific coliphages is confirmed. Also, sets of data on the presence of coliphages in reclaimed and groundwater are reported.
    Keywords: Environmental Microbiology
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    DREAMing: a simple and ultrasensitive method for assessing intratumor epigenetic heterogeneity directly from liquid biopsies (2015)
    Oxford University Press
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    Publication Date: 2015-12-16
    Description: Many cancers comprise heterogeneous populations of cells at primary and metastatic sites throughout the body. The presence or emergence of distinct subclones with drug-resistant genetic and epigenetic phenotypes within these populations can greatly complicate therapeutic intervention. Liquid biopsies of peripheral blood from cancer patients have been suggested as an ideal means of sampling intratumor genetic and epigenetic heterogeneity for diagnostics, monitoring and therapeutic guidance. However, current molecular diagnostic and sequencing methods are not well suited to the routine assessment of epigenetic heterogeneity in difficult samples such as liquid biopsies that contain intrinsically low fractional concentrations of circulating tumor DNA (ctDNA) and rare epigenetic subclonal populations. Here we report an alternative approach, deemed DREAMing (Discrimination of Rare EpiAlleles by Melt), which uses semi-limiting dilution and precise melt curve analysis to distinguish and enumerate individual copies of epiallelic species at single-CpG-site resolution in fractions as low as 0.005%, providing facile and inexpensive ultrasensitive assessment of locus-specific epigenetic heterogeneity directly from liquid biopsies. The technique is demonstrated here for the evaluation of epigenetic heterogeneity at p14 ARF and BRCA1 gene-promoter loci in liquid biopsies obtained from patients in association with non-small cell lung cancer (NSCLC) and myelodysplastic/myeloproliferative neoplasms (MDS/MPN), respectively.
    Keywords: Chromatin and Epigenetics
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    A polymerase engineered for bisulfite sequencing (2015)
    Oxford University Press
    Details
    Publication Date: 2015-12-16
    Description: Bisulfite sequencing is a key methodology in epigenetics. However, the standard workflow of bisulfite sequencing involves heat and strongly basic conditions to convert the intermediary product 5,6-dihydrouridine-6-sulfonate (dhU6S) (generated by reaction of bisulfite with deoxycytidine (dC)) to uracil (dU). These harsh conditions generally lead to sample loss and DNA damage while milder conditions may result in incomplete conversion of intermediates to uracil. Both can lead to poor recovery of bisulfite-treated DNA by the polymerase chain reaction (PCR) as either damaged DNA and/or intermediates of bisulfite treatment are poor substrate for standard DNA polymerases. Here we describe an engineered DNA polymerase (5D4) with an enhanced ability to replicate and PCR amplify bisulfite-treated DNA due to an ability to bypass both DNA lesions and bisulfite intermediates, allowing significantly milder conversion conditions and increased sensitivity in the PCR amplification of bisulfite-treated DNA. Incorporation of the 5D4 DNA polymerase into the bisulfite sequencing workflow thus promises significant sensitivity and efficiency gains.
    Keywords: Chromatin and Epigenetics
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    Unique transposon landscapes are pervasive across Drosophila melanogaster genomes (2015)
    Oxford University Press
    Details
    Publication Date: 2015-12-16
    Description: To understand how transposon landscapes (TLs) vary across animal genomes, we describe a new method called the Transposon Insertion and Depletion AnaLyzer (TIDAL) and a database of 〉300 TLs in Drosophila melanogaster (TIDAL-Fly). Our analysis reveals pervasive TL diversity across cell lines and fly strains, even for identically named sub-strains from different laboratories such as the ISO1 strain used for the reference genome sequence. On average, 〉500 novel insertions exist in every lab strain, inbred strains of the Drosophila Genetic Reference Panel (DGRP), and fly isolates in the Drosophila Genome Nexus (DGN). A minority (〈25%) of transposon families comprise the majority (〉70%) of TL diversity across fly strains. A sharp contrast between insertion and depletion patterns indicates that many transposons are unique to the ISO1 reference genome sequence. Although TL diversity from fly strains reaches asymptotic limits with increasing sequencing depth, rampant TL diversity causes unsaturated detection of TLs in pools of flies. Finally, we show novel transposon insertions negatively correlate with Piwi-interacting RNA (piRNA) levels for most transposon families, except for the highly-abundant roo retrotransposon. Our study provides a useful resource for Drosophila geneticists to understand how transposons create extensive genomic diversity in fly cell lines and strains.
    Keywords: Computational Methods, Genomics
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    Uptake and effect of rare earth elements on gene expression in Methylosinus trichosporium OB3b (2016)
    Oxford University Press
    Details
    Publication Date: 2016-06-04
    Description: It is well known that Methylosinus trichosporium OB3b has two forms of methane monooxygenase (MMO) responsible for the initial conversion of methane to methanol, a cytoplasmic (soluble) methane monooxygenase and a membrane-associated (particulate) methane monooxygenase, and that copper strongly regulates expression of these alternative forms of MMO. More recently, it has been discovered that M. trichosporium OB3b has multiple types of the methanol dehydrogenase (MeDH), i.e. the Mxa-type MeDH (Mxa-MeDH) and Xox-type MeDH (Xox-MeDH), and the expression of these two forms is regulated by the availability of the rare earth element (REE), cerium. Here, we extend these studies and show that lanthanum, praseodymium, neodymium and samarium also regulate expression of alternative forms of MeDH. The effect of these REEs on MeDH expression, however, was only observed in the absence of copper. Further, a mutant of M. trichosporium OB3b, where the Mxa-MeDH was knocked out, was able to grow in the presence of lanthanum, praseodymium and neodymium, but was not able to grow in the presence of samarium. Collectively, these data suggest that multiple levels of gene regulation by metals exist in M. trichosporium OB3b, but that copper overrides the effect of other metals by an as yet unknown mechanism.
    Keywords: Environmental Microbiology
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    Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast (2016)
    Oxford University Press
    Details
    Publication Date: 2016-06-03
    Description: Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments.
    Keywords: Computational Methods, Genomics
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    f-divergence cutoff index to simultaneously identify differential expression in the integrated transcriptome and proteome (2016)
    Oxford University Press
    Details
    Publication Date: 2016-06-03
    Description: The ability to integrate ‘omics’ (i.e. transcriptomics and proteomics) is becoming increasingly important to the understanding of regulatory mechanisms. There are currently no tools available to identify differentially expressed genes (DEGs) across different ‘omics’ data types or multi-dimensional data including time courses. We present fCI (f-divergence Cut-out Index), a model capable of simultaneously identifying DEGs from continuous and discrete transcriptomic, proteomic and integrated proteogenomic data. We show that fCI can be used across multiple diverse sets of data and can unambiguously find genes that show functional modulation, developmental changes or misregulation. Applying fCI to several proteogenomics datasets, we identified a number of important genes that showed distinctive regulation patterns. The package fCI is available at R Bioconductor and http://software.steenlab.org/fCI/ .
    Keywords: Computational Methods, Genomics
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    CLASS2: accurate and efficient splice variant annotation from RNA-seq reads (2016)
    Oxford University Press
    Details
    Publication Date: 2016-06-03
    Description: Next generation sequencing of cellular RNA is making it possible to characterize genes and alternative splicing in unprecedented detail. However, designing bioinformatics tools to accurately capture splicing variation has proven difficult. Current programs can find major isoforms of a gene but miss lower abundance variants, or are sensitive but imprecise. CLASS2 is a novel open source tool for accurate genome-guided transcriptome assembly from RNA-seq reads based on the model of splice graph. An extension of our program CLASS, CLASS2 jointly optimizes read patterns and the number of supporting reads to score and prioritize transcripts, implemented in a novel, scalable and efficient dynamic programming algorithm. When compared against reference programs, CLASS2 had the best overall accuracy and could detect up to twice as many splicing events with precision similar to the best reference program. Notably, it was the only tool to produce consistently reliable transcript models for a wide range of applications and sequencing strategies, including ribosomal RNA-depleted samples. Lightweight and multi-threaded, CLASS2 requires 〈3GB RAM and can analyze a 350 million read set within hours, and can be widely applied to transcriptomics studies ranging from clinical RNA sequencing, to alternative splicing analyses, and to the annotation of new genomes.
    Keywords: Computational Methods, Genomics
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    FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing (2016)
    Oxford University Press
    Details
    Publication Date: 2016-09-20
    Description: Allele-specific copy number analysis (ASCN) from next generation sequencing (NGS) data can greatly extend the utility of NGS beyond the identification of mutations to precisely annotate the genome for the detection of homozygous/heterozygous deletions, copy-neutral loss-of-heterozygosity (LOH), allele-specific gains/amplifications. In addition, as targeted gene panels are increasingly used in clinical sequencing studies for the detection of ‘actionable’ mutations and copy number alterations to guide treatment decisions, accurate, tumor purity-, ploidy- and clonal heterogeneity-adjusted integer copy number calls are greatly needed to more reliably interpret NGS-based cancer gene copy number data in the context of clinical sequencing. We developed FACETS, an ASCN tool and open-source software with a broad application to whole genome, whole-exome, as well as targeted panel sequencing platforms. It is a fully integrated stand-alone pipeline that includes sequencing BAM file post-processing, joint segmentation of total- and allele-specific read counts, and integer copy number calls corrected for tumor purity, ploidy and clonal heterogeneity, with comprehensive output and integrated visualization. We demonstrate the application of FACETS using The Cancer Genome Atlas (TCGA) whole-exome sequencing of lung adenocarcinoma samples. We also demonstrate its application to a clinical sequencing platform based on a targeted gene panel.
    Keywords: Computational Methods, Genomics
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    A genome-wide approach for detecting novel insertion-deletion variants of mid-range size (2016)
    Oxford University Press
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    Publication Date: 2016-09-03
    Description: We present SWAN, a statistical framework for robust detection of genomic structural variants in next-generation sequencing data and an analysis of mid-range size insertion and deletions (〈10 Kb) for whole genome analysis and DNA mixtures. To identify these mid-range size events, SWAN collectively uses information from read-pair, read-depth and one end mapped reads through statistical likelihoods based on Poisson field models. SWAN also uses soft-clip/split read remapping to supplement the likelihood analysis and determine variant boundaries. The accuracy of SWAN is demonstrated by in silico spike-ins and by identification of known variants in the NA12878 genome. We used SWAN to identify a series of novel set of mid-range insertion/deletion detection that were confirmed by targeted deep re-sequencing. An R package implementation of SWAN is open source and freely available.
    Keywords: Computational Methods, Genomics
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    Establishment of a promoter-based chromatin architecture on recently replicated DNA can accommodate variable inter-nucleosome spacing (2016)
    Oxford University Press
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    Publication Date: 2016-09-03
    Description: Nucleosomes, the fundamental subunits of eukaryotic chromatin, are organized with respect to transcriptional start sites. A major challenge to the persistence of this organization is the disassembly of nucleosomes during DNA replication. Here, we use complimentary approaches to map the locations of nucleosomes on recently replicated DNA. We find that nucleosomes are substantially realigned with promoters during the minutes following DNA replication. As a result, the nucleosomal landscape is largely re-established before newly replicated chromosomes are partitioned into daughter cells and can serve as a platform for the re-establishment of gene expression programmes. When the supply of histones is disrupted through mutation of the chaperone Caf1, a promoter-based architecture is generated, but with increased inter-nucleosomal spacing. This indicates that the chromatin remodelling enzymes responsible for spacing nucleosomes are capable of organizing nucleosomes with a range of different linker DNA lengths.
    Keywords: Chromatin and Epigenetics
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    NEpiC: a network-assisted algorithm for epigenetic studies using mean and variance combined signals (2016)
    Oxford University Press
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    Publication Date: 2016-09-20
    Description: DNA methylation plays an important role in many biological processes. Existing epigenome-wide association studies (EWAS) have successfully identified aberrantly methylated genes in many diseases and disorders with most studies focusing on analysing methylation sites one at a time. Incorporating prior biological information such as biological networks has been proven to be powerful in identifying disease-associated genes in both gene expression studies and genome-wide association studies (GWAS) but has been under studied in EWAS. Although recent studies have noticed that there are differences in methylation variation in different groups, only a few existing methods consider variance signals in DNA methylation studies. Here, we present a network-assisted algorithm, NEpiC, that combines both mean and variance signals in searching for differentially methylated sub-networks using the protein–protein interaction (PPI) network. In simulation studies, we demonstrate the power gain from using both the prior biological information and variance signals compared to using either of the two or neither information. Applications to several DNA methylation datasets from the Cancer Genome Atlas (TCGA) project and DNA methylation data on hepatocellular carcinoma (HCC) from the Columbia University Medical Center (CUMC) suggest that the proposed NEpiC algorithm identifies more cancer-related genes and generates better replication results.
    Keywords: Chromatin and Epigenetics
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    Comprehensive analysis of high-throughput screens with HiTSeekR (2016)
    Oxford University Press
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    Publication Date: 2016-08-20
    Description: High-throughput screening (HTS) is an indispensable tool for drug (target) discovery that currently lacks user-friendly software tools for the robust identification of putative hits from HTS experiments and for the interpretation of these findings in the context of systems biology. We developed HiTSeekR as a one-stop solution for chemical compound screens, siRNA knock-down and CRISPR/Cas9 knock-out screens, as well as microRNA inhibitor and -mimics screens. We chose three use cases that demonstrate the potential of HiTSeekR to fully exploit HTS screening data in quite heterogeneous contexts to generate novel hypotheses for follow-up experiments: (i) a genome-wide RNAi screen to uncover modulators of TNFα, (ii) a combined siRNA and miRNA mimics screen on vorinostat resistance and (iii) a small compound screen on KRAS synthetic lethality. HiTSeekR is publicly available at http://hitseekr.compbio.sdu.dk . It is the first approach to close the gap between raw data processing, network enrichment and wet lab target generation for various HTS screen types.
    Keywords: Computational Methods, Genomics
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    Single base resolution analysis of 5-hydroxymethylcytosine in 188 human genes: implications for hepatic gene expression (2016)
    Oxford University Press
    Details
    Publication Date: 2016-08-20
    Description: To improve the epigenomic analysis of tissues rich in 5-hydroxymethylcytosine (hmC), we developed a novel protocol called TAB-Methyl-SEQ, which allows for single base resolution profiling of both hmC and 5-methylcytosine by targeted next-generation sequencing. TAB-Methyl-SEQ data were extensively validated by a set of five methodologically different protocols. Importantly, these extensive cross-comparisons revealed that protocols based on Tet1-assisted bisulfite conversion provided more precise hmC values than TrueMethyl-based methods. A total of 109 454 CpG sites were analyzed by TAB-Methyl-SEQ for mC and hmC in 188 genes from 20 different adult human livers. We describe three types of variability of hepatic hmC profiles: (i) sample-specific variability at 40.8% of CpG sites analyzed, where the local hmC values correlate to the global hmC content of livers (measured by LC-MS), (ii) gene-specific variability, where hmC levels in the coding regions positively correlate to expression of the respective gene and (iii) site-specific variability, where prominent hmC peaks span only 1 to 3 neighboring CpG sites. Our data suggest that both the gene- and site-specific components of hmC variability might contribute to the epigenetic control of hepatic genes. The protocol described here should be useful for targeted DNA analysis in a variety of applications.
    Keywords: Chromatin and Epigenetics
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    Microbial impact on polysulfide dynamics in the environment (2016)
    Oxford University Press
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    Publication Date: 2016-05-12
    Description: Polysulfides (S x 2– ) are sulfide oxidation intermediates that are important for a variety of environmentally relevant processes including pyrite formation, organic matter sulfidization, isotope exchange among reduced sulfur species, and metal chelation. In addition to their chemical reactivity, laboratory experiments with microbial cultures and enzymes indicate both indirect and direct roles for microorganisms in affecting polysulfide chemistry in natural environments through production and consumption. As polysulfides have been detected in a wide array of natural systems ranging from microbial mats to hydrothermal vents, constraining their biogeochemical cycling has broad impacts. However, many questions remain regarding the processes responsible for polysulfide dynamics in these environments and the precise role that microorganisms play in these processes. This review provides a summary of laboratory experiments investigating the role of polysulfides in microbial metabolism, and observations of polysulfides in the environment in order to provide further insight into and highlight open questions about this significant component of the sulfur cycle.
    Keywords: Environmental Microbiology
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    An ensemble strategy that significantly improves de novo assembly of microbial genomes from metagenomic next-generation sequencing data (2015)
    Oxford University Press
    Details
    Publication Date: 2015-04-21
    Description: Next-generation sequencing (NGS) approaches rapidly produce millions to billions of short reads, which allow pathogen detection and discovery in human clinical, animal and environmental samples. A major limitation of sequence homology-based identification for highly divergent microorganisms is the short length of reads generated by most highly parallel sequencing technologies. Short reads require a high level of sequence similarities to annotated genes to confidently predict gene function or homology. Such recognition of highly divergent homologues can be improved by reference-free ( de novo ) assembly of short overlapping sequence reads into larger contigs. We describe an ensemble strategy that integrates the sequential use of various de Bruijn graph and overlap-layout-consensus assemblers with a novel partitioned sub-assembly approach. We also proposed new quality metrics that are suitable for evaluating metagenome de novo assembly. We demonstrate that this new ensemble strategy tested using in silico spike-in, clinical and environmental NGS datasets achieved significantly better contigs than current approaches.
    Keywords: Computational Methods, Genomics
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    Distinguishing between productive and abortive promoters using a random forest classifier in Mycoplasma pneumoniae (2015)
    Oxford University Press
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    Publication Date: 2015-04-21
    Description: Distinguishing between promoter-like sequences in bacteria that belong to true or abortive promoters, or to those that do not initiate transcription at all, is one of the important challenges in transcriptomics. To address this problem, we have studied the genome-reduced bacterium Mycoplasma pneumoniae , for which the RNAs associated with transcriptional start sites have been recently experimentally identified. We determined the contribution to transcription events of different genomic features: the –10, extended –10 and –35 boxes, the UP element, the bases surrounding the –10 box and the nearest-neighbor free energy of the promoter region. Using a random forest classifier and the aforementioned features transformed into scores, we could distinguish between true, abortive promoters and non-promoters with good –10 box sequences. The methods used in this characterization of promoters can be extended to other bacteria and have important applications for promoter design in bacterial genome engineering.
    Keywords: Computational Methods, Genomics
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    Pathway analysis from lists of microRNAs: common pitfalls and alternative strategy (2015)
    Oxford University Press
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    Publication Date: 2015-04-21
    Description: MicroRNAs (miRNAs) are involved in the regulation of gene expression at a post-transcriptional level. As such, monitoring miRNA expression has been increasingly used to assess their role in regulatory mechanisms of biological processes. In large scale studies, once miRNAs of interest have been identified, the target genes they regulate are often inferred using algorithms or databases. A pathway analysis is then often performed in order to generate hypotheses about the relevant biological functions controlled by the miRNA signature. Here we show that the method widely used in scientific literature to identify these pathways is biased and leads to inaccurate results. In addition to describing the bias and its origin we present an alternative strategy to identify potential biological functions specifically impacted by a miRNA signature. More generally, our study exemplifies the crucial need of relevant negative controls when developing, and using, bioinformatics methods.
    Keywords: Computational Methods, Genomics
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    Identification of protein complexes that bind to histone H3 combinatorial modifications using super-SILAC and weighted correlation network analysis (2015)
    Oxford University Press
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    Publication Date: 2015-02-18
    Description: The large number of chemical modifications that are found on the histone proteins of eukaryotic cells form multiple complex combinations, which can act as recognition signals for reader proteins. We have used peptide capture in conjunction with super-SILAC quantification to carry out an unbiased high-throughput analysis of the composition of protein complexes that bind to histone H3K9/S10 and H3K27/S28 methyl-phospho modifications. The accurate quantification allowed us to perform Weighted correlation network analysis (WGCNA) to obtain a systems-level view of the histone H3 histone tail interactome. The analysis reveals the underlying modularity of the histone reader network with members of nuclear complexes exhibiting very similar binding signatures, which suggests that many proteins bind to histones as part of pre-organized complexes. Our results identify a novel complex that binds to the double H3K9me3/S10ph modification, which includes Atrx, Daxx and members of the FACT complex. The super-SILAC approach allows comparison of binding to multiple peptides with different combinations of modifications and the resolution of the WGCNA analysis is enhanced by maximizing the number of combinations that are compared. This makes it a useful approach for assessing the effects of changes in histone modification combinations on the composition and function of bound complexes.
    Keywords: Chromatin and Epigenetics
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    Post-conversion targeted capture of modified cytosines in mammalian and plant genomes (2015)
    Oxford University Press
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    Publication Date: 2015-07-12
    Description: We present a capture-based approach for bisulfite-converted DNA that allows interrogation of pre-defined genomic locations, allowing quantitative and qualitative assessments of 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) at CG dinucleotides and in non-CG contexts (CHG, CHH) in mammalian and plant genomes. We show the technique works robustly and reproducibly using as little as 500 ng of starting DNA, with results correlating well with whole genome bisulfite sequencing data, and demonstrate that human DNA can be tested in samples contaminated with microbial DNA. This targeting approach will allow cell type-specific designs to maximize the value of 5mC and 5hmC sequencing.
    Keywords: Chromatin and Epigenetics
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    Targeting chromatin binding regulation of constitutively active AR variants to overcome prostate cancer resistance to endocrine-based therapies (2015)
    Oxford University Press
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    Publication Date: 2015-07-12
    Description: Androgen receptor (AR) variants (AR-Vs) expressed in prostate cancer (PCa) lack the AR ligand binding domain (LBD) and function as constitutively active transcription factors. AR-V expression in patient tissues or circulating tumor cells is associated with resistance to AR-targeting endocrine therapies and poor outcomes. Here, we investigated the mechanisms governing chromatin binding of AR-Vs with the goal of identifying therapeutic vulnerabilities. By chromatin immunoprecipitation and sequencing (ChIP-seq) and complementary biochemical experiments, we show that AR-Vs display a binding preference for the same canonical high-affinity androgen response elements (AREs) that are preferentially engaged by AR, albeit with lower affinity. Dimerization was an absolute requirement for constitutive AR-V DNA binding and transcriptional activation. Treatment with the bromodomain and extraterminal (BET) inhibitor JQ1 resulted in inhibition of AR-V chromatin binding and impaired AR-V driven PCa cell growth in vitro and in vivo . Importantly, this was associated with a novel JQ1 action of down-regulating AR-V transcript and protein expression. Overall, this study demonstrates that AR-Vs broadly restore AR chromatin binding events that are otherwise suppressed during endocrine therapy, and provides pre-clinical rationale for BET inhibition as a strategy for inhibiting expression and chromatin binding of AR-Vs in PCa.
    Keywords: Chromatin and Epigenetics
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    LARVA: an integrative framework for large-scale analysis of recurrent variants in noncoding annotations (2015)
    Oxford University Press
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    Publication Date: 2015-09-30
    Description: In cancer research, background models for mutation rates have been extensively calibrated in coding regions, leading to the identification of many driver genes, recurrently mutated more than expected. Noncoding regions are also associated with disease; however, background models for them have not been investigated in as much detail. This is partially due to limited noncoding functional annotation. Also, great mutation heterogeneity and potential correlations between neighboring sites give rise to substantial overdispersion in mutation count, resulting in problematic background rate estimation. Here, we address these issues with a new computational framework called LARVA. It integrates variants with a comprehensive set of noncoding functional elements, modeling the mutation counts of the elements with a β-binomial distribution to handle overdispersion. LARVA, moreover, uses regional genomic features such as replication timing to better estimate local mutation rates and mutational hotspots. We demonstrate LARVA's effectiveness on 760 whole-genome tumor sequences, showing that it identifies well-known noncoding drivers, such as mutations in the TERT promoter. Furthermore, LARVA highlights several novel highly mutated regulatory sites that could potentially be noncoding drivers. We make LARVA available as a software tool and release our highly mutated annotations as an online resource ( larva.gersteinlab.org ).
    Keywords: Computational Methods, Genomics
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    Beegle: from literature mining to disease-gene discovery (2016)
    Oxford University Press
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    Publication Date: 2016-01-30
    Description: Disease-gene identification is a challenging process that has multiple applications within functional genomics and personalized medicine. Typically, this process involves both finding genes known to be associated with the disease (through literature search) and carrying out preliminary experiments or screens (e.g. linkage or association studies, copy number analyses, expression profiling) to determine a set of promising candidates for experimental validation. This requires extensive time and monetary resources. We describe Beegle , an online search and discovery engine that attempts to simplify this process by automating the typical approaches. It starts by mining the literature to quickly extract a set of genes known to be linked with a given query, then it integrates the learning methodology of Endeavour (a gene prioritization tool) to train a genomic model and rank a set of candidate genes to generate novel hypotheses. In a realistic evaluation setup, Beegle has an average recall of 84% in the top 100 returned genes as a search engine, which improves the discovery engine by 12.6% in the top 5% prioritized genes. Beegle is publicly available at http://beegle.esat.kuleuven.be/ .
    Keywords: Computational Methods, Genomics
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    A computational method for studying the relation between alternative splicing and DNA methylation (2016)
    Oxford University Press
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    Publication Date: 2016-01-30
    Description: Alternative splicing is an important mechanism in eukaryotes that expands the transcriptome and proteome significantly. It plays an important role in a number of biological processes. Understanding its regulation is hence an important challenge. Recently, increasing evidence has been collected that supports an involvement of intragenic DNA methylation in the regulation of alternative splicing. The exact mechanisms of regulation, however, are largely unknown, and speculated to be complex: different methylation profiles might exist, each of which could be associated with a different regulation mechanism. We present a computational technique that is able to determine such stable methylation patterns and allows to correlate these patterns with inclusion propensity of exons. Pattern detection is based on dynamic time warping (DTW) of methylation profiles, a sophisticated similarity measure for signals that can be non-trivially transformed. We design a flexible self-organizing map approach to pattern grouping. Exemplary application on available data sets indicates that stable patterns which correlate non-trivially with exon inclusion do indeed exist. To improve the reliability of these predictions, further studies on larger data sets will be required. We have thus taken great care that our software runs efficiently on modern hardware, so that it can support future studies on large-scale data sets.
    Keywords: Computational Methods, Genomics
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    Mercury resistance transposons in Bacilli strains from different geographical regions (2016)
    Oxford University Press
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    Publication Date: 2016-02-20
    Description: A total of 65 spore-forming mercury-resistant bacteria were isolated from natural environments worldwide in order to understand the acquisition of additional genes by and dissemination of mercury resistance transposons across related Bacilli genera by horizontal gene movement. PCR amplification using a single primer complementary to the inverted repeat sequence of Tn MERI1 -like transposons showed that 12 of 65 isolates had a transposon-like structure. There were four types of amplified fragments: Tn 5084 , Tn 5085 , Tn d MER3 (a newly identified deleted transposon-like fragment) and Tn 6294 (a newly identified transposon). Tn d MER3 is a 3.5-kb sequence that carries a merRETPA operon with no merB or transposase genes. It is related to the mer operon of Bacillus licheniformis strain FA6-12 from Russia. DNA homology analysis shows that Tn 6294 is an 8.5-kb sequence that is possibly derived from Tn d MER3 by integration of a Tn MERI1 -type transposase and resolvase genes and in addition the merR2 and merB1 genes. Bacteria harboring Tn 6294 exhibited broad-spectrum mercury resistance to organomercurial compounds, although Tn 6294 had only merB1 and did not have the merB2 and merB3 sequences for organomercurial lyases found in Tn 5084 of B. cereus strain RC607. Strains with Tn 6294 encode mercuric reductase (MerA) of less than 600 amino acids in length with a single N-terminal mercury-binding domain, whereas MerA encoded by strains MB1 and RC607 has two tandem domains. Thus, Tn d MER3 and Tn 6294 are shorter prototypes for Tn MERI1 -like transposons. Identification of Tn 6294 in Bacillus sp. from Taiwan and in Paenibacillus sp. from Antarctica indicates the wide horizontal dissemination of Tn MERI1 -like transposons across bacterial species and geographical barriers.
    Keywords: Environmental Microbiology
    Print ISSN: 0378-1097
    Electronic ISSN: 1574-6968
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    BubbleTree: an intuitive visualization to elucidate tumoral aneuploidy and clonality using next generation sequencing data (2016)
    Oxford University Press
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    Publication Date: 2016-03-01
    Description: Tumors are characterized by properties of genetic instability, heterogeneity, and significant oligoclonality. Elucidating this intratumoral heterogeneity is challenging but important. In this study, we propose a framework, BubbleTree, to characterize the tumor clonality using next generation sequencing (NGS) data. BubbleTree simultaneously elucidates the complexity of a tumor biopsy, estimating cancerous cell purity, tumor ploidy, allele-specific copy number, and clonality and represents this in an intuitive graph. We further developed a three-step heuristic method to automate the interpretation of the BubbleTree graph, using a divide-and-conquer strategy. In this study, we demonstrated the performance of BubbleTree with comparisons to similar commonly used tools such as THetA2, ABSOLUTE, AbsCN-seq and ASCAT, using both simulated and patient-derived data. BubbleTree outperformed these tools, particularly in identifying tumor subclonal populations and polyploidy. We further demonstrated BubbleTree's utility in tracking clonality changes from patients’ primary to metastatic tumor and dating somatic single nucleotide and copy number variants along the tumor clonal evolution. Overall, the BubbleTree graph and corresponding model is a powerful approach to provide a comprehensive spectrum of the heterogeneous tumor karyotype in human tumors. BubbleTree is R-based and freely available to the research community ( https://www.bioconductor.org/packages/release/bioc/html/BubbleTree.html ).
    Keywords: Computational Methods, Genomics
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    Fungal denitrification: Bipolaris sorokiniana exclusively denitrifies inorganic nitrogen in the presence and absence of oxygen (2016)
    Oxford University Press
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    Publication Date: 2016-02-07
    Description: Fungi may play an important role in the production of the greenhouse gas nitrous oxide (N 2 O). Bipolaris sorokiniana is a ubiquitous saprobe found in soils worldwide, yet denitrification by this fungal strain has not previously been reported. We aimed to test if B. sorokiniana would produce N 2 O and CO 2 in the presence of organic and inorganic forms of nitrogen (N) under microaerobic and anaerobic conditions. Nitrogen source (organic-N, inorganic-N, no-N control) significantly affected N 2 O and CO 2 production both in the presence and absence of oxygen, which contrasts with bacterial denitrification. Inorganic N addition increased denitrification of N 2 O (from 0 to 0.3 μg N 2 0-N h –1  g –1 biomass) and reduced respiration of CO 2 (from 0.1 to 0.02 mg CO 2 h –1  g –1 biomass). Isotope analyses indicated that nitrite, rather than ammonium or glutamine, was transformed to N 2 O. Results suggest the source of N may play a larger role in fungal N 2 O production than oxygen status.
    Keywords: Environmental Microbiology
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    Genome-wide profiling of nucleosome sensitivity and chromatin accessibility in Drosophila melanogaster (2016)
    Oxford University Press
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    Publication Date: 2016-02-20
    Description: Nucleosomal DNA is thought to be generally inaccessible to DNA-binding factors, such as micrococcal nuclease (MNase). Here, we digest Drosophila chromatin with high and low concentrations of MNase to reveal two distinct nucleosome types: MNase-sensitive and MNase-resistant. MNase-resistant nucleosomes assemble on sequences depleted of A/T and enriched in G/C-containing dinucleotides, whereas MNase-sensitive nucleosomes form on A/T-rich sequences found at transcription start and termination sites, enhancers and DNase I hypersensitive sites. Estimates of nucleosome formation energies indicate that MNase-sensitive nucleosomes tend to be less stable than MNase-resistant ones. Strikingly, a decrease in cell growth temperature of about 10°C makes MNase-sensitive nucleosomes less accessible, suggesting that observed variations in MNase sensitivity are related to either thermal fluctuations of chromatin fibers or the activity of enzymatic machinery. In the vicinity of active genes and DNase I hypersensitive sites nucleosomes are organized into periodic arrays, likely due to ‘phasing’ off potential barriers formed by DNA-bound factors or by nucleosomes anchored to their positions through external interactions. The latter idea is substantiated by our biophysical model of nucleosome positioning and energetics, which predicts that nucleosomes immediately downstream of transcription start sites are anchored and recapitulates nucleosome phasing at active genes significantly better than sequence-dependent models.
    Keywords: Chromatin and Epigenetics
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    Permissiveness of freshly isolated environmental strains of amoebae for growth of Legionella pneumophila (2016)
    Oxford University Press
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    Publication Date: 2016-02-20
    Description: Legionella pneumophila is a pathogenic bacterium commonly found in water and responsible for severe pneumonia. Free-living amoebae are protozoa also found in water, which feed on bacteria by phagocytosis. Under favorable conditions, some L. pneumophila are able to resist phagocytic digestion and even multiply within amoebae. However, it is not clear whether L. pneumophila could infect at a same rate a large range of amoebae or if there is some selectivity towards specific amoebal genera or strains. Also, most studies have been performed using collection strains and not with freshly isolated strains. In our study, we assess the permissiveness of freshly isolated environmental strains of amoebae, belonging to three common genera (i.e. Acanthamoeba, Naegleria and Vermamoeba ), for growth of L. pneumophila at three different temperatures. Our results indicated that all the tested strains of amoebae were permissive to L. pneumophila Lens and that there was no significant difference between the strains. Intracellular proliferation was more efficient at a temperature of 40°C. In conclusion, our work suggests that, under favorable conditions, virulent strains of L. pneumophila could equally infect a large number of isolates of common freshwater amoeba genera.
    Keywords: Environmental Microbiology
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    ENmix: a novel background correction method for Illumina HumanMethylation450 BeadChip (2016)
    Oxford University Press
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    Publication Date: 2016-02-20
    Description: The Illumina HumanMethylation450 BeadChip is increasingly utilized in epigenome-wide association studies, however, this array-based measurement of DNA methylation is subject to measurement variation. Appropriate data preprocessing to remove background noise is important for detecting the small changes that may be associated with disease. We developed a novel background correction method, ENmix, that uses a mixture of exponential and truncated normal distributions to flexibly model signal intensity and uses a truncated normal distribution to model background noise. Depending on data availability, we employ three approaches to estimate background normal distribution parameters using (i) internal chip negative controls, (ii) out-of-band Infinium I probe intensities or (iii) combined methylated and unmethylated intensities. We evaluate ENmix against other available methods for both reproducibility among duplicate samples and accuracy of methylation measurement among laboratory control samples. ENmix out-performed other background correction methods for both these measures and substantially reduced the probe-design type bias between Infinium I and II probes. In reanalysis of existing EWAS data we show that ENmix can identify additional CpGs, and results in smaller P -value estimates for previously-validated CpGs. We incorporated the method into R package ENmix , which is freely available from Bioconductor website.
    Keywords: Chromatin and Epigenetics
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    Discovery and characterization of Alu repeat sequences via precise local read assembly (2015)
    Oxford University Press
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    Publication Date: 2015-12-02
    Description: Alu insertions have contributed to 〉11% of the human genome and ~30–35 Alu subfamilies remain actively mobile, yet the characterization of polymorphic Alu insertions from short-read data remains a challenge. We build on existing computational methods to combine Alu detection and de novo assembly of WGS data as a means to reconstruct the full sequence of insertion events from Illumina paired end reads. Comparison with published calls obtained using PacBio long-reads indicates a false discovery rate below 5%, at the cost of reduced sensitivity due to the colocation of reference and non-reference repeats. We generate a highly accurate call set of 1614 completely assembled Alu variants from 53 samples from the Human Genome Diversity Project (HGDP) panel. We utilize the reconstructed alternative insertion haplotypes to genotype 1010 fully assembled insertions, obtaining 〉99% agreement with genotypes obtained by PCR. In our assembled sequences, we find evidence of premature insertion mechanisms and observe 5' truncation in 16% of Alu Ya5 and Alu Yb8 insertions. The sites of truncation coincide with stem-loop structures and SRP9/14 binding sites in the Alu RNA, implicating L1 ORF2p pausing in the generation of 5' truncations. Additionally, we identified variable Alu J and Alu S elements that likely arose due to non-retrotransposition mechanisms.
    Keywords: Computational Methods, Genomics
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    Detection of differentially methylated regions from whole-genome bisulfite sequencing data without replicates (2015)
    Oxford University Press
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    Publication Date: 2015-12-02
    Description: DNA methylation is an important epigenetic modification involved in many biological processes and diseases. Recent developments in whole genome bisulfite sequencing (WGBS) technology have enabled genome-wide measurements of DNA methylation at single base pair resolution. Many experiments have been conducted to compare DNA methylation profiles under different biological contexts, with the goal of identifying differentially methylated regions (DMRs). Due to the high cost of WGBS experiments, many studies are still conducted without biological replicates. Methods and tools available for analyzing such data are very limited. We develop a statistical method, DSS-single, for detecting DMRs from WGBS data without replicates. We characterize the count data using a rigorous model that accounts for the spatial correlation of methylation levels, sequence depth and biological variation. We demonstrate that using information from neighboring CG sites, biological variation can be estimated accurately even without replicates. DMR detection is then carried out via a Wald test procedure. Simulations demonstrate that DSS-single has greater sensitivity and accuracy than existing methods, and an analysis of H1 versus IMR90 cell lines suggests that it also yields the most biologically meaningful results. DSS-single is implemented in the Bioconductor package DSS.
    Keywords: Chromatin and Epigenetics
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    Conditional mutual inclusive information enables accurate quantification of associations in gene regulatory networks (2015)
    Oxford University Press
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    Publication Date: 2015-03-14
    Description: Mutual information (MI), a quantity describing the nonlinear dependence between two random variables, has been widely used to construct gene regulatory networks (GRNs). Despite its good performance, MI cannot separate the direct regulations from indirect ones among genes. Although the conditional mutual information (CMI) is able to identify the direct regulations, it generally underestimates the regulation strength, i.e. it may result in false negatives when inferring gene regulations. In this work, to overcome the problems, we propose a novel concept, namely conditional mutual inclusive information (CMI2), to describe the regulations between genes. Furthermore, with CMI2, we develop a new approach, namely CMI2NI (CMI2-based network inference), for reverse-engineering GRNs. In CMI2NI, CMI2 is used to quantify the mutual information between two genes given a third one through calculating the Kullback–Leibler divergence between the postulated distributions of including and excluding the edge between the two genes. The benchmark results on the GRNs from DREAM challenge as well as the SOS DNA repair network in Escherichia coli demonstrate the superior performance of CMI2NI. Specifically, even for gene expression data with small sample size, CMI2NI can not only infer the correct topology of the regulation networks but also accurately quantify the regulation strength between genes. As a case study, CMI2NI was also used to reconstruct cancer-specific GRNs using gene expression data from The Cancer Genome Atlas (TCGA). CMI2NI is freely accessible at http://www.comp-sysbio.org/cmi2ni .
    Keywords: Computational Methods, Genomics
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    CODEX: a normalization and copy number variation detection method for whole exome sequencing (2015)
    Oxford University Press
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    Publication Date: 2015-04-02
    Description: High-throughput sequencing of DNA coding regions has become a common way of assaying genomic variation in the study of human diseases. Copy number variation (CNV) is an important type of genomic variation, but detecting and characterizing CNV from exome sequencing is challenging due to the high level of biases and artifacts. We propose CODEX, a normalization and CNV calling procedure for whole exome sequencing data. The Poisson latent factor model in CODEX includes terms that specifically remove biases due to GC content, exon capture and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based exome sequencing data. CODEX is compared to existing methods on a population analysis of HapMap samples from the 1000 Genomes Project, and shown to be more accurate on three microarray-based validation data sets. We further evaluate performance on 222 neuroblastoma samples with matched normals and focus on a well-studied rare somatic CNV within the ATRX gene. We show that the cross-sample normalization procedure of CODEX removes more noise than normalizing the tumor against the matched normal and that the segmentation procedure performs well in detecting CNVs with nested structures.
    Keywords: Computational Methods, Genomics
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    Comprehensive discovery of DNA motifs in 349 human cells and tissues reveals new features of motifs (2015)
    Oxford University Press
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    Publication Date: 2015-01-10
    Description: Comprehensive motif discovery under experimental conditions is critical for the global understanding of gene regulation. To generate a nearly complete list of human DNA motifs under given conditions, we employed a novel approach to de novo discover significant co-occurring DNA motifs in 349 human DNase I hypersensitive site datasets. We predicted 845 to 1325 motifs in each dataset, for a total of 2684 non-redundant motifs. These 2684 motifs contained 54.02 to 75.95% of the known motifs in seven large collections including TRANSFAC. In each dataset, we also discovered 43 663 to 2 013 288 motif modules, groups of motifs with their binding sites co-occurring in a significant number of short DNA regions. Compared with known interacting transcription factors in eight resources, the predicted motif modules on average included 84.23% of known interacting motifs. We further showed new features of the predicted motifs, such as motifs enriched in proximal regions rarely overlapped with motifs enriched in distal regions, motifs enriched in 5' distal regions were often enriched in 3' distal regions, etc. Finally, we observed that the 2684 predicted motifs classified the cell or tissue types of the datasets with an accuracy of 81.29%. The resources generated in this study are available at http://server.cs.ucf.edu/predrem/ .
    Keywords: Computational Methods, Genomics
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    Quantification of read species behavior within whole genome sequencing of cancer genomes for the stratification and visualization of genomic variation (2016)
    Oxford University Press
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    Publication Date: 2016-05-20
    Description: The cancer genome is abnormal genome, and the ability to monitor its sequence had undergone a technological revolution. Yet prognosis and diagnosis remain an expert-based decision, with only limited abilities to provide machine-based decisions. We introduce a heterogeneity-based method for stratifying and visualizing whole-genome sequencing (WGS) reads. This method uses the heterogeneity within WGS reads to markedly reduce the dimensionality of next-generation sequencing data; it is available through the tool HiBS (Heterogeneity-Based Subclassification) that allows cancer sample classification. We validated HiBS using 〉200 WGS samples from nine different cancer types from The Cancer Genome Atlas (TCGA). With HiBS, we show progress with two WGS related issues: (i) differentiation between normal (NB) and tumor (TP) samples based solely on the information structure of their WGS data, and (ii) identification of specific regions of chromosomal amplification/deletion and their association with tumor stage. By comparing results to those obtained through available WGS analyses tools, we demonstrate some of the novelties obtained by the approach implemented in HiBS and also show nearly perfect normal/tumor classification, used to identify known and unknown chromosomal aberrations. Finally, the HiBS index has been associated with breast cancer tumor stage.
    Keywords: Computational Methods, Genomics
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    Circular RNA profile in gliomas revealed by identification tool UROBORUS (2016)
    Oxford University Press
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    Publication Date: 2016-05-20
    Description: Recent evidence suggests that many endogenous circular RNAs (circRNAs) may play roles in biological processes. However, the expression patterns and functions of circRNAs in human diseases are not well understood. Computationally identifying circRNAs from total RNA-seq data is a primary step in studying their expression pattern and biological roles. In this work, we have developed a computational pipeline named UROBORUS to detect circRNAs in total RNA-seq data. By applying UROBORUS to RNA-seq data from 46 gliomas and normal brain samples, we detected thousands of circRNAs supported by at least two read counts, followed by successful experimental validation on 24 circRNAs from the randomly selected 27 circRNAs. UROBORUS is an efficient tool that can detect circRNAs with low expression levels in total RNA-seq without RNase R treatment. The circRNAs expression profiling revealed more than 476 circular RNAs differentially expressed in control brain tissues and gliomas. Together with parental gene expression, we found that circRNA and its parental gene have diversified expression patterns in gliomas and control brain tissues. This study establishes an efficient and sensitive approach for predicting circRNAs using total RNA-seq data. The UROBORUS pipeline can be accessed freely for non-commercial purposes at http://uroborus.openbioinformatics.org/ .
    Keywords: Computational Methods, Genomics
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    Modeling the combined effect of RNA-binding proteins and microRNAs in post-transcriptional regulation (2016)
    Oxford University Press
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    Publication Date: 2016-05-20
    Description: Recent studies show that RNA-binding proteins (RBPs) and microRNAs (miRNAs) function in coordination with each other to control post-transcriptional regulation (PTR). Despite this, the majority of research to date has focused on the regulatory effect of individual RBPs or miRNAs. Here, we mapped both RBP and miRNA binding sites on human 3'UTRs and utilized this collection to better understand PTR. We show that the transcripts that lack competition for HuR binding are destabilized more after HuR depletion. We also confirm this finding for PUM1(2) by measuring genome-wide expression changes following the knockdown of PUM1(2) in HEK293 cells. Next, to find potential cooperative interactions, we identified the pairs of factors whose sites co-localize more often than expected by random chance. Upon examining these results for PUM1(2), we found that transcripts where the sites of PUM1(2) and its interacting miRNA form a stem-loop are more stabilized upon PUM1(2) depletion. Finally, using dinucleotide frequency and counts of regulatory sites as features in a regression model, we achieved an AU-ROC of 0.86 in predicting mRNA half-life in BEAS-2B cells. Altogether, our results suggest that future studies of PTR must consider the combined effects of RBPs and miRNAs, as well as their interactions.
    Keywords: Computational Methods, Genomics
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    Using intron position conservation for homology-based gene prediction (2016)
    Oxford University Press
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    Publication Date: 2016-05-20
    Description: Annotation of protein-coding genes is very important in bioinformatics and biology and has a decisive influence on many downstream analyses. Homology-based gene prediction programs allow for transferring knowledge about protein-coding genes from an annotated organism to an organism of interest. Here, we present a homology-based gene prediction program called GeMoMa. GeMoMa utilizes the conservation of intron positions within genes to predict related genes in other organisms. We assess the performance of GeMoMa and compare it with state-of-the-art competitors on plant and animal genomes using an extended best reciprocal hit approach. We find that GeMoMa often makes more precise predictions than its competitors yielding a substantially increased number of correct transcripts. Subsequently, we exemplarily validate GeMoMa predictions using Sanger sequencing. Finally, we use RNA-seq data to compare the predictions of homology-based gene prediction programs, and find again that GeMoMa performs well. Hence, we conclude that exploiting intron position conservation improves homology-based gene prediction, and we make GeMoMa freely available as command-line tool and Galaxy integration.
    Keywords: Computational Methods, Genomics
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    Identification of a small-molecule ligand of the epigenetic reader protein Spindlin1 via a versatile screening platform (2016)
    Oxford University Press
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    Publication Date: 2016-05-20
    Description: Epigenetic modifications of histone tails play an essential role in the regulation of eukaryotic transcription. Writer and eraser enzymes establish and maintain the epigenetic code by creating or removing posttranslational marks. Specific binding proteins, called readers, recognize the modifications and mediate epigenetic signalling. Here, we present a versatile assay platform for the investigation of the interaction between methyl lysine readers and their ligands. This can be utilized for the screening of small-molecule inhibitors of such protein–protein interactions and the detailed characterization of the inhibition. Our platform is constructed in a modular way consisting of orthogonal in vitro binding assays for ligand screening and verification of initial hits and biophysical, label-free techniques for further kinetic characterization of confirmed ligands. A stability assay for the investigation of target engagement in a cellular context complements the platform. We applied the complete evaluation chain to the Tudor domain containing protein Spindlin1 and established the in vitro test systems for the double Tudor domain of the histone demethylase JMJD2C. We finally conducted an exploratory screen for inhibitors of the interaction between Spindlin1 and H3K4me3 and identified A366 as the first nanomolar small-molecule ligand of a Tudor domain containing methyl lysine reader.
    Keywords: Chromatin and Epigenetics
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    Comparison of circular RNA prediction tools (2016)
    Oxford University Press
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    Publication Date: 2016-04-08
    Description: CircRNAs are novel members of the non-coding RNA family. For several decades circRNAs have been known to exist, however only recently the widespread abundance has become appreciated. Annotation of circRNAs depends on sequencing reads spanning the backsplice junction and therefore map as non-linear reads in the genome. Several pipelines have been developed to specifically identify these non-linear reads and consequently predict the landscape of circRNAs based on deep sequencing datasets. Here, we use common RNAseq datasets to scrutinize and compare the output from five different algorithms; circRNA_finder, find_circ, CIRCexplorer, CIRI, and MapSplice and evaluate the levels of bona fide and false positive circRNAs based on RNase R resistance. By this approach, we observe surprisingly dramatic differences between the algorithms specifically regarding the highly expressed circRNAs and the circRNAs derived from proximal splice sites. Collectively, this study emphasizes that circRNA annotation should be handled with care and that several algorithms should ideally be combined to achieve reliable predictions.
    Keywords: Computational Methods, Genomics
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    Solid and liquid media for isolating and cultivating acidophilic and acid-tolerant sulfate-reducing bacteria (2016)
    Oxford University Press
    Details
    Publication Date: 2016-04-24
    Description: Growth media have been developed to facilitate the enrichment and isolation of acidophilic and acid-tolerant sulfate-reducing bacteria (aSRB) from environmental and industrial samples, and to allow their cultivation in vitro . The main features of the ‘standard’ solid and liquid devised media are as follows: (i) use of glycerol rather than an aliphatic acid as electron donor; (ii) inclusion of stoichiometric concentrations of zinc ions to both buffer pH and to convert potentially harmful hydrogen sulphide produced by the aSRB to insoluble zinc sulphide; (iii) inclusion of Acidocella aromatica (an heterotrophic acidophile that does not metabolize glycerol or yeast extract) in the gel underlayer of double layered (overlay) solid media, to remove acetic acid produced by aSRB that incompletely oxidize glycerol and also aliphatic acids (mostly pyruvic) released by acid hydrolysis of the gelling agent used (agarose). Colonies of aSRB are readily distinguished from those of other anaerobes due to their deposition and accumulation of metal sulphide precipitates. Data presented illustrate the effectiveness of the overlay solid media described for isolating aSRB from acidic anaerobic sediments and low pH sulfidogenic bioreactors.
    Keywords: Environmental Microbiology
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    Comprehensive evaluation of fusion transcript detection algorithms and a meta-caller to combine top performing methods in paired-end RNA-seq data (2016)
    Oxford University Press
    Details
    Publication Date: 2016-03-19
    Description: Background: Fusion transcripts are formed by either fusion genes (DNA level) or trans-splicing events (RNA level). They have been recognized as a promising tool for diagnosing, subtyping and treating cancers. RNA-seq has become a precise and efficient standard for genome-wide screening of such aberration events. Many fusion transcript detection algorithms have been developed for paired-end RNA-seq data but their performance has not been comprehensively evaluated to guide practitioners. In this paper, we evaluated 15 popular algorithms by their precision and recall trade-off, accuracy of supporting reads and computational cost. We further combine top-performing methods for improved ensemble detection. Results: Fifteen fusion transcript detection tools were compared using three synthetic data sets under different coverage, read length, insert size and background noise, and three real data sets with selected experimental validations. No single method dominantly performed the best but SOAPfuse generally performed well, followed by FusionCatcher and JAFFA. We further demonstrated the potential of a meta-caller algorithm by combining top performing methods to re-prioritize candidate fusion transcripts with high confidence that can be followed by experimental validation. Conclusion: Our result provides insightful recommendations when applying individual tool or combining top performers to identify fusion transcript candidates.
    Keywords: Computational Methods, Genomics
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    A rapid and sensitive colorimetric measurement of antibiotic efficacy against Escherichia coli in vitro (2016)
    Oxford University Press
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    Publication Date: 2016-03-13
    Description: A common dye of prussian blue (PB) as an indicator was used to develop a colorimetric method for detecting the efficacy of the antibiotics in vitro. Considering the electronic production capacity of microbial respiration, ferricyanide was employed in transferring electrons from target microorganism of Escherichia coli ( E. coli ) to produce ferrocyanide. Subsequently, ferrocyanide reacted with ferric ions to form PB. In view of relationship between the PB yield and the bacterial activity, the efficacy of the antibiotics on E. coli was directly detected at 700 nm of PB absorption. When the 5% activity of antibiotics on 20 isolates of E. coli was quantified as 5% efficacy, the applied concentrations of eight antibiotics, such as cefepime, ceftriaxone sodium, cefoperazone sodium, piperacillin sodium, amoxicillin, gentamicin, amikacin and levofloxacin were 2, 2, 4, 4, 10, 4, 8 and 8 μg mL –1 , respectively. To compare with minimum inhibitory concentration results obtained by Clinical and Laboratory Standards Institute broth macrodilution method, the results of PB methods showed good agreements except with gentamicin. Paired t- test result ( P ) also showed that difference between two methods was statistically significant ( P = 0.006).
    Keywords: Environmental Microbiology
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    EMERGE: a flexible modelling framework to predict genomic regulatory elements from genomic signatures (2016)
    Oxford University Press
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    Publication Date: 2016-03-19
    Description: Regulatory DNA elements, short genomic segments that regulate gene expression, have been implicated in developmental disorders and human disease. Despite this clinical urgency, only a small fraction of the regulatory DNA repertoire has been confirmed through reporter gene assays. The overall success rate of functional validation of candidate regulatory elements is low. Moreover, the number and diversity of datasets from which putative regulatory elements can be identified is large and rapidly increasing. We generated a flexible and user-friendly tool to integrate the information from different types of genomic datasets, e.g. ATAC-seq, ChIP-seq, conservation, aiming to increase the ease and success rate of functional prediction. To this end, we developed the EMERGE program that merges all datasets that the user considers informative and uses a logistic regression framework, based on validated functional elements, to set optimal weights to these datasets. ROC curve analysis shows that a combination of datasets leads to improved prediction of tissue-specific enhancers in human, mouse and Drosophila genomes. Functional assays based on this prediction can be expected to have substantially higher success rates. The resulting integrated signal for prediction of functional elements can be plotted in a build-in genome browser or exported for further analysis.
    Keywords: Computational Methods, Genomics
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    Modeling co-occupancy of transcription factors using chromatin features (2016)
    Oxford University Press
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    Publication Date: 2016-03-19
    Description: Regulation of gene expression requires both transcription factor (TFs) and epigenetic modifications, and interplays between the two types of factors have been discovered. However study of relationships between chromatin features and TF–TF co-occupancy remains limited. Here, we revealed the relationship by first illustrating distinct profile patterns of chromatin features related to different binding events, including single TF binding and TF–TF co-occupancy of 71 TFs from five human cell lines. We further implemented statistical analyses to demonstrate the relationship by accurately predicting co-occupancy genome-widely using chromatin features including DNase I hypersensitivity, 11 histone modifications (HMs) and GC content. Remarkably, our results showed that the combination of chromatin features enables accurate predictions across the five cells. For individual chromatin features, DNase I enables high and consistent predictions. H3K27ac, H3K4me 2, H3K4me3 and H3K9ac are more reliable predictors than other HMs. Although the combination of 11 HMs achieves accurate predictions, their predictive ability varies considerably when a model obtained from one cell is applied to others, indicating relationship between HMs and TF–TF co-occupancy is cell type dependent. GC content is not a reliable predictor, but the addition of GC content to any other features enhances their predictive ability. Together, our results elucidate a strong relationship between TF–TF co-occupancy and chromatin features.
    Keywords: Computational Methods, Genomics
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    Discovering hotspots in functional genomic data superposed on 3D chromatin configuration reconstructions (2016)
    Oxford University Press
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    Publication Date: 2016-03-19
    Description: The spatial organization of the genome influences cellular function, notably gene regulation. Recent studies have assessed the three-dimensional (3D) co-localization of functional annotations (e.g. centromeres, long terminal repeats) using 3D genome reconstructions from Hi-C (genome-wide chromosome conformation capture) data; however, corresponding assessments for continuous functional genomic data (e.g. chromatin immunoprecipitation-sequencing (ChIP-seq) peak height) are lacking. Here, we demonstrate that applying bump hunting via the patient rule induction method (PRIM) to ChIP-seq data superposed on a Saccharomyces cerevisiae 3D genome reconstruction can discover ‘functional 3D hotspots’, regions in 3-space for which the mean ChIP-seq peak height is significantly elevated. For the transcription factor Swi6, the top hotspot by P -value contains MSB2 and ERG11 – known Swi6 target genes on different chromosomes. We verify this finding in a number of ways. First, this top hotspot is relatively stable under PRIM across parameter settings. Second, this hotspot is among the top hotspots by mean outcome identified by an alternative algorithm, k -Nearest Neighbor ( k -NN) regression. Third, the distance between MSB2 and ERG11 is smaller than expected (by resampling) in two other 3D reconstructions generated via different normalization and reconstruction algorithms. This analytic approach can discover functional 3D hotspots and potentially reveal novel regulatory interactions.
    Keywords: Computational Methods, Genomics
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    Exposure of Metarhizium acridum mycelium to light induces tolerance to UV-B radiation (2016)
    Oxford University Press
    Details
    Publication Date: 2016-03-04
    Description: Metarhizium acridum is an entomopathogenic fungus commonly used as a bioinsecticide. The conidium is the fungal stage normally employed as field inoculum in biological control programs and must survive under field conditions such as high ultraviolet-B (UV-B) exposure. Light, which is an important stimulus for many fungi, has been shown to induce the production of M. robertsii conidia with increased stress tolerance. Here we show that a two-hour exposure to white or blue/UV-A light of fast-growing mycelium induces tolerance to subsequent UV-B irradiation. Red light, however, does not have the same effect. In addition, we established that this induction can take place with as little as 1 min of white-light exposure. This brief illumination scheme could be relevant in future studies of M. acridum photobiology and for the production of UV-B resistant mycelium used in mycelium-based formulations for biological control.
    Keywords: Environmental Microbiology
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    Photorhabdus luminescens LN2 requires rpoS for nematicidal activity and nematode development (2016)
    Oxford University Press
    Details
    Publication Date: 2016-03-04
    Description: Photorhabdus (Enterobacteriaceae) bacteria are pathogenic to insects and mutualistic with entomopathogenic Heterorhabditis nematodes . Photorhabdus luminescens subsp. akhurstii LN2, associated with Heterorhabditis indica LN2, shows nematicidal activity against H. bacteriophora H06 infective juveniles (IJs). In the present study, an rpoS mutant of P. luminescens LN2 was generated through allelic exchange to examine the effects of rpoS deletion on the nematicidal activity and nematode development. The results showed that P. luminescens LN2 required rpoS for nematicidal activity against H06 nematodes, normal IJ recovery and development of H. indica LN2, however, not for the bacterial colonization in LN2 and H06 IJs. This provides cues for further understanding the role of rpoS in the mutualistic association between entomopathogenic nematodes and their symbionts.
    Keywords: Environmental Microbiology
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    Simultaneous characterization of sense and antisense genomic processes by the double-stranded hidden Markov model (2016)
    Oxford University Press
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    Publication Date: 2016-03-19
    Description: Hidden Markov models (HMMs) have been extensively used to dissect the genome into functionally distinct regions using data such as RNA expression or DNA binding measurements. It is a challenge to disentangle processes occurring on complementary strands of the same genomic region. We present the double-stranded HMM (dsHMM), a model for the strand-specific analysis of genomic processes. We applied dsHMM to yeast using strand specific transcription data, nucleosome data, and protein binding data for a set of 11 factors associated with the regulation of transcription.The resulting annotation recovers the mRNA transcription cycle (initiation, elongation, termination) while correctly predicting strand-specificity and directionality of the transcription process. We find that pre-initiation complex formation is an essentially undirected process, giving rise to a large number of bidirectional promoters and to pervasive antisense transcription. Notably, 12% of all transcriptionally active positions showed simultaneous activity on both strands. Furthermore, dsHMM reveals that antisense transcription is specifically suppressed by Nrd1, a yeast termination factor.
    Keywords: Computational Methods, Genomics
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    csaw: a Bioconductor package for differential binding analysis of ChIP-seq data using sliding windows (2016)
    Oxford University Press
    Details
    Publication Date: 2016-03-19
    Description: Chromatin immunoprecipitation with massively parallel sequencing (ChIP-seq) is widely used to identify binding sites for a target protein in the genome. An important scientific application is to identify changes in protein binding between different treatment conditions, i.e. to detect differential binding. This can reveal potential mechanisms through which changes in binding may contribute to the treatment effect. The csaw package provides a framework for the de novo detection of differentially bound genomic regions. It uses a window-based strategy to summarize read counts across the genome. It exploits existing statistical software to test for significant differences in each window. Finally, it clusters windows into regions for output and controls the false discovery rate properly over all detected regions. The csaw package can handle arbitrarily complex experimental designs involving biological replicates. It can be applied to both transcription factor and histone mark datasets, and, more generally, to any type of sequencing data measuring genomic coverage. csaw performs favorably against existing methods for de novo DB analyses on both simulated and real data. csaw is implemented as a R software package and is freely available from the open-source Bioconductor project.
    Keywords: Computational Methods, Genomics
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    Estimate of within population incremental selection through branch imbalance in lineage trees (2016)
    Oxford University Press
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    Publication Date: 2016-03-19
    Description: Incremental selection within a population, defined as limited fitness changes following mutation, is an important aspect of many evolutionary processes. Strongly advantageous or deleterious mutations are detected using the synonymous to non-synonymous mutations ratio. However, there are currently no precise methods to estimate incremental selection. We here provide for the first time such a detailed method and show its precision in multiple cases of micro-evolution. The proposed method is a novel mixed lineage tree/sequence based method to detect within population selection as defined by the effect of mutations on the average number of offspring. Specifically, we propose to measure the log of the ratio between the number of leaves in lineage trees branches following synonymous and non-synonymous mutations. The method requires a high enough number of sequences, and a large enough number of independent mutations. It assumes that all mutations are independent events. It does not require of a baseline model and is practically not affected by sampling biases. We show the method's wide applicability by testing it on multiple cases of micro-evolution. We show that it can detect genes and inter-genic regions using the selection rate and detect selection pressures in viral proteins and in the immune response to pathogens.
    Keywords: Computational Methods, Genomics
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    Diversity and distribution of catechol 2, 3-dioxygenase genes in surface sediments of the Bohai Sea (2016)
    Oxford University Press
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    Publication Date: 2016-05-05
    Description: Catechol 2, 3-dioxygenase (C23O) is the key enzyme for aerobic aromatic degradation. Based on clone libraries and quantitative real-time polymerase chain reaction, we characterized diversity and distribution patterns of C23O genes in surface sediments of the Bohai Sea. The results showed that sediments of the Bohai Sea were dominated by genes related to C23O subfamily I.2.A. The samples from wastewater discharge area (DG) and aquaculture farm (KL) showed distinct composition of C23O genes when compared to the samples from Bohai Bay (BH), and total organic carbon was a crucial determinant accounted for the composition variation. C6BH12-38 and C2BH2-35 displayed the highest gene copies and highest ratios to the 16S rRNA genes in KL, and they might prefer biologically labile aromatic hydrocarbons via aquaculture inputs. Meanwhile, C7BH3-48 showed the highest gene copies and highest ratios to the 16S rRNA genes in DG, and this could be selective effect of organic loadings from wastewater discharge. An evident increase in C6BH12-38 and C7BH3-48 gene copies and reduction in diversity of C23O genes in DG and KL indicated composition perturbations of C23O genes and potential loss in functional redundancy. We suggest that ecological habitat and trophic specificity could shape the distribution of C23O genes in the Bohai Sea sediments.
    Keywords: Environmental Microbiology
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    COSMOS: accurate detection of somatic structural variations through asymmetric comparison between tumor and normal samples (2016)
    Oxford University Press
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    Publication Date: 2016-05-06
    Description: An important challenge in cancer genomics is precise detection of structural variations (SVs) by high-throughput short-read sequencing, which is hampered by the high false discovery rates of existing analysis tools. Here, we propose an accurate SV detection method named COSMOS, which compares the statistics of the mapped read pairs in tumor samples with isogenic normal control samples in a distinct asymmetric manner. COSMOS also prioritizes the candidate SVs using strand-specific read-depth information. Performance tests on modeled tumor genomes revealed that COSMOS outperformed existing methods in terms of F-measure. We also applied COSMOS to an experimental mouse cell-based model, in which SVs were induced by genome engineering and gamma-ray irradiation, followed by polymerase chain reaction-based confirmation. The precision of COSMOS was 84.5%, while the next best existing method was 70.4%. Moreover, the sensitivity of COSMOS was the highest, indicating that COSMOS has great potential for cancer genome analysis.
    Keywords: Computational Methods, Genomics
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    Impact of pnpR, a LysR-type regulator-encoding gene, on the cellular processes of Pseudomonas putida DLL-E4 (2016)
    Oxford University Press
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    Publication Date: 2016-05-20
    Description: LysR-type transcriptional regulators (LTTRs) regulate various cellular processes in bacteria. pnpR is an LTTR-encoding gene involved in the regulation of hydroquinone (HQ) degradation, and its effects on the cellular processes of Pseudomonas putida DLL-E4 were investigated at the physiological, biochemical and molecular levels. Reverse transcription polymerase chain reaction revealed that pnpR positively regulated its own expression and that of the pnpC1C2DECX1X2 operon; additionally, pnpR partially regulated the expression of pnpA when P. putida was grown on para -nitrophenol (PNP) or HQ. Strains DLL-E4 and DLL- pnpR exhibited similar cellular morphologies and growth rates. Transcriptome analysis revealed that pnpR regulated the expression of genes in addition to those involved in PNP degradation. A total of 20 genes were upregulated and 19 genes were downregulated by at least 2-fold in strain DLL- pnpR relative to strain DLL-E4. Bioinformatic analysis revealed putative PnpR-binding sites located in the upstream regions of genes involved in PNP degradation, carbon catabolite repression and other cellular processes. The utilization of L-aspartic acid, L-histidine, L-pyroglutamic acid, L-serine, -aminobutyric acid, D,L-lactic acid, D-saccharic acid, succinic acid and L-alaninamide was increased at least 1.3-fold in strain DLL- pnpR as shown by BIOLOG assays, indicating that pnpR plays a potential negative regulation role in the utilization of carbon sources.
    Keywords: Environmental Microbiology
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    Substantial DNA methylation differences between two major neuronal subtypes in human brain (2016)
    Oxford University Press
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    Publication Date: 2016-04-08
    Description: The brain is built from a large number of cell types which have been historically classified using location, morphology and molecular markers. Recent research suggests an important role of epigenetics in shaping and maintaining cell identity in the brain. To elucidate the role of DNA methylation in neuronal differentiation, we developed a new protocol for separation of nuclei from the two major populations of human prefrontal cortex neurons—GABAergic interneurons and glutamatergic (GLU) projection neurons. Major differences between the neuronal subtypes were revealed in CpG, non-CpG and hydroxymethylation (hCpG). A dramatically greater number of undermethylated CpG sites in GLU versus GABA neurons were identified. These differences did not directly translate into differences in gene expression and did not stem from the differences in hCpG methylation, as more hCpG methylation was detected in GLU versus GABA neurons. Notably, a comparable number of undermethylated non-CpG sites were identified in GLU and GABA neurons, and non-CpG methylation was a better predictor of subtype-specific gene expression compared to CpG methylation. Regions that are differentially methylated in GABA and GLU neurons were significantly enriched for schizophrenia risk loci. Collectively, our findings suggest that functional differences between neuronal subtypes are linked to their epigenetic specification.
    Keywords: Chromatin and Epigenetics
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    Prioritizing and selecting likely novel miRNAs from NGS data (2016)
    Oxford University Press
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    Publication Date: 2016-04-08
    Description: Small non-coding RNAs play a key role in many physiological and pathological processes. Since 2004, miRNA sequences have been catalogued in miRBase, which is currently in its 21st version. We investigated sequence and structural features of miRNAs annotated in the miRBase and compared them between different versions of this reference database. We have identified that the two most recent releases (v20 and v21) are influenced by next-generation sequencing based miRNA predictions and show significant deviation from miRNAs discovered prior to the high-throughput profiling period. From the analysis of miRBase, we derived a set of key characteristics to predict new miRNAs and applied the implemented algorithm to evaluate novel blood-borne miRNA candidates. We carried out 705 individual whole miRNA sequencings of blood cells and collected a total of 9.7 billion reads. Using miRDeep2 we initially predicted 1452 potentially novel miRNAs. After excluding false positives, 518 candidates remained. These novel candidates were ranked according to their distance to the features in the early miRBase versions allowing for an easier selection of a subset of putative miRNAs for validation. Selected candidates were successfully validated by qRT-PCR and northern blotting. In addition, we implemented a web-server for ranking potential miRNA candidates, which is available at: www.ccb.uni-saarland.de/novomirank .
    Keywords: Computational Methods, Genomics
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    Methanogen communities in a municipal landfill complex in China (2016)
    Oxford University Press
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    Publication Date: 2016-04-20
    Description: Landfills are significant global sources of atmospheric methane, but little is known about the ecology and community structure of methanogens in these sites. Here, we investigated the methanogen community based on methyl coenzyme M reductase A gene amplicons in the vertical profiles of three different sites at a municipal landfill complex in China. Links between methanogen communities and refuse properties were explored using multivariate analysis. Clone library results showed that most clones (92%) were related to the hydrogenotrophic methanogens, Methanomicrobiales. Almost all of the Methanomicrobiales clones retrieved in this study are members of the genus Methanoculleus . Eight clones were affiliated with the genus Methanofollis . The remaining clones were clustered within the genus Methanosarcina . Terminal restriction fragment length polymorphism profiles showed that the landfill was predominated by 22 taxa, making up 69%–96% of the community. Of these, a single taxon comprised 36%–65% of the communities across all sites and depths. Principal components analysis separated the methanogen community into three groups, irrespective of site or depth. Redundancy analysis suggested that total phosphorus and pH play roles in structuring methanogen communities in landfills.
    Keywords: Environmental Microbiology
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    Standardizing chromatin research: a simple and universal method for ChIP-seq (2016)
    Oxford University Press
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    Publication Date: 2016-04-21
    Description: Chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq) is a key technique in chromatin research. Although heavily applied, existing ChIP-seq protocols are often highly fine-tuned workflows, optimized for specific experimental requirements. Especially the initial steps of ChIP-seq, particularly chromatin shearing, are deemed to be exceedingly cell-type-specific, thus impeding any protocol standardization efforts. Here we demonstrate that harmonization of ChIP-seq workflows across cell types and conditions is possible when obtaining chromatin from properly isolated nuclei. We established an ultrasound-based nuclei extraction method (NEXSON: Nuclei EXtraction by SONication) that is highly effective across various organisms, cell types and cell numbers. The described method has the potential to replace complex cell-type-specific, but largely ineffective, nuclei isolation protocols. By including NEXSON in ChIP-seq workflows, we completely eliminate the need for extensive optimization and sample-dependent adjustments. Apart from this significant simplification, our approach also provides the basis for a fully standardized ChIP-seq and yields highly reproducible transcription factor and histone modifications maps for a wide range of different cell types. Even small cell numbers (~10 000 cells per ChIP) can be easily processed without application of modified chromatin or library preparation protocols.
    Keywords: Chromatin and Epigenetics
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    Gene integrated set profile analysis: a context-based approach for inferring biological endpoints (2016)
    Oxford University Press
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    Publication Date: 2016-04-21
    Description: The identification of genes with specific patterns of change (e.g. down-regulated and methylated) as phenotype drivers or samples with similar profiles for a given gene set as drivers of clinical outcome, requires the integration of several genomic data types for which an ‘integrate by intersection’ (IBI) approach is often applied. In this approach, results from separate analyses of each data type are intersected, which has the limitation of a smaller intersection with more data types. We introduce a new method, GISPA (Gene Integrated Set Profile Analysis) for integrated genomic analysis and its variation, SISPA (Sample Integrated Set Profile Analysis) for defining respective genes and samples with the context of similar, a priori specified molecular profiles. With GISPA, the user defines a molecular profile that is compared among several classes and obtains ranked gene sets that satisfy the profile as drivers of each class. With SISPA, the user defines a gene set that satisfies a profile and obtains sample groups of profile activity. Our results from applying GISPA to human multiple myeloma (MM) cell lines contained genes of known profiles and importance, along with several novel targets, and their further SISPA application to MM coMMpass trial data showed clinical relevance.
    Keywords: Computational Methods, Genomics
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    CrossHub: a tool for multi-way analysis of The Cancer Genome Atlas (TCGA) in the context of gene expression regulation mechanisms (2016)
    Oxford University Press
    Details
    Publication Date: 2016-04-21
    Description: The contribution of different mechanisms to the regulation of gene expression varies for different tissues and tumors. Complementation of predicted mRNA–miRNA and gene–transcription factor (TF) relationships with the results of expression correlation analyses derived for specific tumor types outlines the interactions with functional impact in the current biomaterial. We developed CrossHub software, which enables two-way identification of most possible TF–gene interactions: on the basis of ENCODE ChIP-Seq binding evidence or Jaspar prediction and co-expression according to the data of The Cancer Genome Atlas (TCGA) project, the largest cancer omics resource. Similarly, CrossHub identifies mRNA–miRNA pairs with predicted or validated binding sites (TargetScan, mirSVR, PicTar, DIANA microT, miRTarBase) and strong negative expression correlations. We observed partial consistency between ChIP-Seq or miRNA target predictions and gene–TF/miRNA co-expression, demonstrating a link between these indicators. Additionally, CrossHub expression-methylation correlation analysis can be used to identify hypermethylated CpG sites or regions with the greatest potential impact on gene expression. Thus, CrossHub is capable of outlining molecular portraits of a specific gene and determining the three most common sources of expression regulation: promoter/enhancer methylation, miRNA interference and TF-mediated activation or repression. CrossHub generates formatted Excel workbooks with the detailed results. CrossHub is freely available at https://sourceforge.net/projects/crosshub/ .
    Keywords: Computational Methods, Genomics
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