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  • Computational Methods, Genomics  (73)
  • Biotechnology & Synthetic Biology  (41)
  • Oxford University Press  (114)
  • 2015-2019  (114)
  • 1945-1949
  • 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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  • 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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  • 4
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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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  • 5
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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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  • 6
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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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  • 7
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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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  • 8
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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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  • 9
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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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  • 10
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    Endophytic fungi associated with Sudanese medicinal plants show cytotoxic and antibiotic potential (2016)
    Oxford University Press
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    Publication Date: 2016-05-12
    Description: In this study, we isolated 15 endophytic fungi from five Sudanese medicinal plants. Each fungal endophytic strain was identified by sequencing of internal transcribed spacer (ITS) regions of rDNA. Ethyl acetate extracts were prepared from each endophyte cultivated in vitro and tested for their respective antibacterial activities and antiproliferative activities against human cancer cells. Antibacterial screening was carried out against two bacterial strains: Gram-negative Escherichia coli and Gram-positive methicillin-resistant Staphylococcus aureus , by the broth dilution method. Cell viability was evaluated by the MTT procedure after exposure of MCF7 breast cancer cells and HT29 or HCT116 human colon adenocarcinoma cells to each endophytic extract. Of interest, Byssochlamys spectabilis isolated from Euphorbia prostata showed cytotoxicity (IC 50 = 1.51 ± 0.2 μg mL –1 ) against MCF7 cells, but had a low effect against HT29 or HCT116 cells (IC 50 〉 20 μg mL –1 ). Cladosporium cladosporioides 2, isolated from Vernonia amygdalina leaves, showed antiproliferative activities against MCF7 cells (IC 50 = 10.5 ± 1.5 μg mL –1 ) only. On the other hand, B. spectabilis and Alternaria sp. extract had antibacterial activities against the S. aureus strain. The findings of this work revealed that endophytic fungi associated with medicinal plants from Sudan could be considered as an attractive source of new therapeutic compounds.
    Keywords: Biotechnology & Synthetic Biology
    Print ISSN: 0378-1097
    Electronic ISSN: 1574-6968
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  • 11
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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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  • 12
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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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  • 13
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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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  • 14
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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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  • 15
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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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  • 16
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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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    De novo biosynthesis of resveratrol by site-specific integration of heterologous genes in Escherichia coli (2016)
    Oxford University Press
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    Publication Date: 2016-04-08
    Description: Resveratrol is a well-known triphenolic natural product present in red wine. For its contribution to human health, the demand for resveratrol as a food and nutrition supplement has increased significantly. In recent years, the rapid development of synthetic biology has promoted extensive work to increase the production of resveratrol in microbes. However, supplementation of expensive phenylpropanoic precursors was required in current engineered strains. Here, we first utilized the site-specific integration strategy to produce resveratrol in Escherichia coli . The genes tal , 4cl and sts were site-specific integrated into the loci of genes tyrR and trpED in the chromosome of E. coli BW25113 (DE3). The final strain was capable of producing 4.612 mg L –1 of resveratrol from glucose.
    Keywords: Biotechnology & Synthetic Biology
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  • 19
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    Overexpression of two stress-responsive, small, non-coding RNAs, 6S and tmRNA, imparts butanol tolerance in Clostridium acetobutylicum (2016)
    Oxford University Press
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    Publication Date: 2016-04-08
    Description: While extensively studied in several model organisms, the role of small, non-coding RNAs in the stress response remains largely unexplored in Clostridium organisms. About 100 years after the first industrial Acetone–Butanol–Ethanol fermentation process, based on the Weizmann Clostridium acetobutylicum strain, strain tolerance to butanol remains a crucial factor limiting the economics of the process. Several studies have examined the response of this organism to metabolite stress, and several genes have been engaged to impart enhanced tolerance, but no sRNAs have yet been directly engaged in this task. We show that the two stress-responsive sRNAs, 6S and tmRNA, upon overexpression impart tolerance to butanol as assessed by viability assays under process-relevant conditions. 6S overexpression enhances cell densities as well as butanol titres. We discuss the likely mechanisms that these two sRNAs might engage in this tolerance phenotype. Our data support the continued exploration of sRNAs as a basis for engineering enhanced tolerance and enhanced solvent production, especially because sRNA-based strategies impose a minimal metabolic burden on the cells.
    Keywords: Biotechnology & Synthetic Biology
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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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  • 21
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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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    Neofiscalin A and fiscalin C are potential novel indole alkaloid alternatives for the treatment of multidrug-resistant Gram-positive bacterial infections (2016)
    Oxford University Press
    Details
    Publication Date: 2016-07-02
    Description: Ten indole alkaloids were obtained from the marine sponge-associated fungus Neosartorya siamensis KUFA 0017. We studied the antimicrobial properties of these and of three other compounds previously isolated from the soil fungus N. siamensis KUFC 6349. Only neofiscalin A showed antimicrobial activity against Gram-positive bacteria, including methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus faecalis (VRE); with a minimum inhibitory concentration (MIC) of 8 μg mL –1 against both strains. Another compound, fiscalin C, presented synergistic activity against MRSA when combined with oxacillin, although alone showed no antibacterial effect. Moreover, neofiscalin A, when present at sub-MICs, hampered the ability of both MRSA and VRE strains to form a biofilm. Additionally, the biofilm inhibitory concentration values of neofiscalin A against the MRSA and VRE isolates were 96 and 80 μg mL –1 , respectively. At a concentration of 200 μg mL –1 , neofiscalin A was able to reduce the metabolic activity of the biofilms by ~50%. One important fact is that our results also showed that neofiscalin A had no cytotoxicity against a human brain capillary endothelial cell line.
    Keywords: Biotechnology & Synthetic Biology
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    The unconventional secretion of PepN is independent of a functional autophagy machinery in the filamentous fungus Aspergillus niger (2016)
    Oxford University Press
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    Publication Date: 2016-07-02
    Description: During unconventional protein secretion (UPS), proteins do not pass through the classical endoplasmic reticulum (ER)–Golgi-dependent pathway, but are transported to the cell membrane via alternative routes. One type of UPS is dependent on several autophagy-related (Atg) proteins in yeast and mammalian cells, but mechanisms for unconventional secretion are largely unknown for filamentous fungi. In this study, we investigated whether the autophagy machinery is used for UPS in the filamentous fungus Aspergillus niger . An aspartic protease, which we called PepN, was identified as being likely to be secreted unconventionally, as this protein is highly abundant in culture filtrates during carbon starvation while it lacks a conventional N-terminal secretion sequence. We analysed the presence of PepN in the culture filtrates of carbon starved wild-type, atg1 and atg8 deletion mutant strains by Western blot analysis and by secretome analysis using nanoLC-ESI-MS/MS (wild-type and atg8 deletion mutant). Besides the presence of carbohydrate-active enzymes and other types of proteases, PepN was abundantly found in culture filtrates of both wild-type and atg deletion strains, indicating that the secretion of PepN is independent of the autophagy machinery in A. niger and hence most likely occurs via a different mechanism.
    Keywords: Biotechnology & Synthetic Biology
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    Effects of MreB paralogs on poly-{gamma}-glutamic acid synthesis and cell morphology in Bacillus amyloliquefaciens (2016)
    Oxford University Press
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    Publication Date: 2016-08-27
    Description: Actin-like MreB paralogs play important roles in cell shape maintenance, cell wall synthesis and the regulation of the D,L-endopeptidases, CwlO and LytE. The gram-positive bacteria, Bacillus amyloliquefaciens LL3, is a poly--glutamic acid (-PGA) producing strain that contains three MreB paralogs: MreB, Mbl and MreBH. In B. amyloliquefaciens , CwlO and LytE can degrade -PGA. In this study, we aimed to test the hypothesis that modulating transcript levels of MreB paralogs would alter the synthesis and degradation of -PGA. The results showed that overexpression or inhibition of MreB, Mbl or MreBH had distinct effects on cell morphology and the molecular weight of the -PGA products. In fermentation medium, cells of mreB inhibition mutant were 50.2% longer than LL3, and the -PGA titer increased by 55.7%. However, changing the expression level of mbl showed only slight effects on the morphology, -PGA molecular weight and titer. In the mreBH inhibition mutant, -PGA production and its molecular weight increased by 56.7% and 19.4%, respectively. These results confirmed our hypothesis that suppressing the expression of MreB paralogs might reduce -PGA degradation, and that improving the cell size could strengthen -PGA synthesis. This is the first report of enhanced -PGA production via suppression of actin-like MreB paralogs.
    Keywords: Biotechnology & Synthetic Biology
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    Unique transposon landscapes are pervasive across Drosophila melanogaster genomes (2015)
    Oxford University Press
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    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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    Industrial production of acetone and butanol by fermentation--100 years later (2016)
    Oxford University Press
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    Publication Date: 2016-06-08
    Description: Microbial production of acetone and butanol was one of the first large-scale industrial fermentation processes of global importance. During the first part of the 20th century, it was indeed the second largest fermentation process, superseded in importance only by the ethanol fermentation. After a rapid decline after the 1950s, acetone-butanol-ethanol (ABE) fermentation has recently gained renewed interest in the context of biorefinery approaches for the production of fuels and chemicals from renewable resources. The availability of new methods and knowledge opens many new doors for industrial microbiology, and a comprehensive view on this process is worthwhile due to the new interest. This thematic issue of FEMS Microbiology Letters, dedicated to the 100th anniversary of the first industrial exploitation of Chaim Weizmann's ABE fermentation process, covers the main aspects of old and new developments, thereby outlining a model development in biotechnology. All major aspects of industrial microbiology are exemplified by this single process. This includes new technologies, such as the latest developments in metabolic engineering, the exploitation of biodiversity and discoveries of new regulatory systems such as for microbial stress tolerance, as well as technological aspects, such as bio- and down-stream processing.
    Keywords: Biotechnology & Synthetic Biology
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    A new lactobacilli in vivo expression system for the production and delivery of heterologous proteins at mucosal surfaces (2016)
    Oxford University Press
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    Publication Date: 2016-06-02
    Description: Food-grade lactic acid bacteria, such as lactobacilli, represent good candidates for the development of mucosal vectors. Indeed, they are generally recognized as safe microorganisms and some strains display beneficial effects (probiotics). In this study, we described a new lactobacilli in vivo expression (LIVE) system for the production and delivery of therapeutic molecules at mucosal surfaces. The versatility and functionality of this system was successfully validated in several lactobacilli species; furthermore, we assessed in vivo LIVE system in two different mouse models of human pathologies: (i) a model of therapy against intestinal inflammation (inflammatory bowel diseases) and (ii) a model of vaccination against dental caries. We demonstrated that Lactobacillus gasseri expressing the anti-inflammatory cytokine IL-10 under LIVE system efficiently delivered the recombinant protein at mucosal surfaces and display anti-inflammatory effects. In the vaccination model against caries, LIVE system allowed the heterologous expression of Streptococcus mutans antigen GbpB by L. gasseri , leading to a stimulation of the host immune response.
    Keywords: Biotechnology & Synthetic Biology
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    Bioreactors and in situ product recovery techniques for acetone-butanol-ethanol fermentation (2016)
    Oxford University Press
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    Publication Date: 2016-06-02
    Description: The microbial fermentation process is one of the sustainable and environment-friendly ways to produce 1-butanol and other bio-based chemicals. The success of the fermentation process greatly relies on the choice of bioreactors and the separation methods. In this review, the history and the performance of bioreactors for the acetone–butanol–ethanol (ABE) fermentation is discussed. The subject is then focused on in situ product recovery (ISPR) techniques, particularly for the integrated extraction-gas stripping. The usefulness of this promising hybrid ISPR device is acknowledged by its incorporation with batch, fed-batch and continuous processes to improve the performance of ABE fermentation.
    Keywords: Biotechnology & Synthetic Biology
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    Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast (2016)
    Oxford University Press
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    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
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    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
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    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
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    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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    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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    An ensemble strategy that significantly improves de novo assembly of microbial genomes from metagenomic next-generation sequencing data (2015)
    Oxford University Press
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    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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    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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    Metabolic modeling of clostridia: current developments and applications (2016)
    Oxford University Press
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    Publication Date: 2016-01-29
    Description: Anaerobic Clostridium spp. is an important bioproduction microbial genus that can produce solvents and utilize a broad spectrum of substrates including cellulose and syngas. Genome-scale metabolic (GSM) models are increasingly being put forth for various clostridial strains to explore their respective metabolic capabilities and suitability for various bioconversions. In this study, we have selected representative GSM models for six different clostridia ( Clostridium acetobutylicum , C. beijerinckii , C. butyricum , C. cellulolyticum , C. ljungdahlii and C. thermocellum ) and performed a detailed model comparison contrasting their metabolic repertoire. We also discuss various applications of these GSM models to guide metabolic engineering interventions as well as assessing cellular physiology.
    Keywords: Biotechnology & Synthetic Biology
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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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    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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    Acetone-butanol-ethanol fermentation of corn stover: current production methods, economic viability and commercial use (2016)
    Oxford University Press
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    Publication Date: 2016-03-02
    Description: Biobutanol is a next-generation liquid biofuel with properties akin to those of gasoline. There is a widespread effort to commercialize biobutanol production from agricultural residues, such as corn stover, which do not compete with human and animal foods. This pursuit is backed by extensive government mandates to expand alternative energy sources. This review provides an overview of research on biobutanol production using corn stover feedstock. Structural composition, pretreatment, sugar yield (following pretreatment and hydrolysis) and generation of lignocellulose-derived microbial inhibitory compounds (LDMICs) from corn stover are discussed. The review also discusses different Clostridium species and strains employed for biobutanol production from corn stover-derived sugars with respect to solvent yields, tolerance to LDMICs and in situ solvent recovery (integrated fermentation). Further, the economics of cellulosic biobutanol production are highlighted and compared to corn starch-derived ethanol and gasoline. As discussed herein, the economic competitiveness of biobutanol production from corn stover largely depends on feedstock processing and fermentation process design.
    Keywords: Biotechnology & Synthetic Biology
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    A Pseudomonas putida double mutant deficient in butanol assimilation: a promising step for engineering a biological biofuel production platform (2016)
    Oxford University Press
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    Publication Date: 2016-02-20
    Description: Biological production in heterologous hosts is of interest for the production of the C4 alcohol (butanol) and other chemicals. However, some hurdles need to be overcome in order to achieve an economically viable process; these include avoiding the consumption of butanol and maintaining tolerance to this solvent during production. Pseudomonas putida is a potential host for solvent production; in order to further adapt P. putida to this role, we generated mini-Tn 5 mutant libraries in strain BIRD-1 that do not consume butanol. We analyzed the insertion site of the mini-Tn 5 in a mutant that was deficient in assimilation of butanol using arbitrary PCR followed by Sanger sequencing and found that the transposon was inserted in the malate synthase B gene. Here, we show that in a second round of mutagenesis a double mutant unable to take up butanol had an insertion in a gene coding for a multisensor hybrid histidine kinase. The genetic context of the histidine kinase sensor revealed the presence of a set of genes potentially involved in butanol assimilation; qRT-PCR analysis showed induction of this set of genes in the wild type and the malate synthase mutant but not in the double mutant.
    Keywords: Biotechnology & Synthetic Biology
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    Frontiers in microbial 1-butanol and isobutanol production (2016)
    Oxford University Press
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    Publication Date: 2016-02-20
    Description: The heavy dependence on petroleum-derived fuel has raised concerns about energy sustainability and climate change, which have prompted researchers to explore fuel production from renewable sources. 1-Butanol and isobutanol are promising biofuels that have favorable properties and can also serve as solvents or chemical feedstocks. Microbial production of these alcohols provides great opportunities to access a wide spectrum of renewable resources. In recent years, research has improved the native 1-butanol production and has engineered isobutanol production in various organisms to explore metabolic diversity and a broad range of substrates. This review focuses on progress in metabolic engineering for the production of these two compounds using various resources.
    Keywords: Biotechnology & Synthetic Biology
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  • 47
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    Recent progress in biobutanol tolerance in microbial systems with an emphasis on Clostridium (2016)
    Oxford University Press
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    Publication Date: 2016-02-20
    Description: Biobased production of butanol promises a more sustainable route for industrial production. However, butanol toxicity remains a barrier for achieving high product titers. Investigation into butanol stress has shed some light on its modes of toxicity. Unfortunately, there still remain significant shortfalls in our understanding of the complex interactions of butanol with cells. To address this knowledge gap, a diverse range of tools have been employed to gain a better understanding of the adverse effects of butanol on the cell. These findings have lead to the identification of possible molecular mechanisms associated with butanol tolerance, which can be harnessed for future strain development efforts. This review focuses on recent efforts to address the toxicity of butanol in microbial producers and offers some perspectives on the future direction of this research sector.
    Keywords: Biotechnology & Synthetic Biology
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  • 48
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    Synergistic effect of calcium and zinc on glucose/xylose utilization and butanol tolerance of Clostridium acetobutylicum (2016)
    Oxford University Press
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    Publication Date: 2016-02-25
    Description: Biobutanol outperforms bioethanol as an advanced biofuel, but is not economically competitive in terms of its titer, yield and productivity associated with feedstocks and energy cost. In this work, the synergistic effect of calcium and zinc was investigated in the acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum using glucose, xylose and glucose/xylose mixtures as carbon source(s). Significant improvements associated with enhanced glucose/xylose utilization, cell growth, acids re-assimilation and butanol biosynthesis were achieved. Especially, the maximum butanol and ABE production of 16.1 and 25.9 g L –1 were achieved from 69.3 g L –1 glucose with butanol/ABE productivities of 0.40 and 0.65 g L –1 h –1 compared to those of 11.7 and 19.4 g/L with 0.18 and 0.30 g L –1 h –1 obtained in the control respectively without any supplement. More importantly, zinc was significantly involved in the butanol tolerance based on the improved xylose utilization under various butanol-shock conditions (2, 4, 6, 8 and 10 g L –1 butanol). Under the same conditions, calcium and zinc co-supplementation led to the best xylose utilization and butanol production. These results suggested that calcium and zinc could play synergistic roles improving ABE fermentation by C. acetobutylicum .
    Keywords: Biotechnology & Synthetic Biology
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    Pseudomonas putida KT2440 markerless gene deletion using a combination of {lambda} Red recombineering and Cre/loxP site-specific recombination (2016)
    Oxford University Press
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    Publication Date: 2016-02-07
    Description: Pseudomonas putida KT2440 is a saprophytic, environmental microorganism that plays important roles in the biodegradation of environmental toxic compounds and production of polymers, chemicals and secondary metabolites. Gene deletion of KT2440 usually involves cloning of the flanking homologous fragments of the gene of interest into a suicide vector followed by transferring into KT2440 via triparental conjugation. Selection and counterselection steps are then employed to generate gene deletion mutant. However, these methods are tedious and are not suitable for the manipulation of multiple genes simultaneously. Herein, a two-step, markerless gene deletion method is presented. First, homologous armsflanked loxP-neo-loxP was knocked-in to replace the gene of interest, then the kanamycin resistance marker is removed by Cre recombinase catalyzed site-specific recombination. Both two-plasmid and one-plasmid gene systems were established. MekR/P mekA regulated gene expression system was found to be suitable for tight Cre expression in one-plasmid deletion system. The straightforward, time saving and highly efficient markerless gene deletion strategy has the potential to facilitate the genetics and functional genomics study of P. putida KT2440.
    Keywords: Biotechnology & Synthetic Biology
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    Evaluation of viability, metabolic activity and spore quantity in clostridial cultures during ABE fermentation (2016)
    Oxford University Press
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    Publication Date: 2016-03-02
    Description: Flow cytometry, in combination with fluorescent staining, was used to evaluate population heterogeneity in acetone-butanol–ethanol fermentation that was carried out with type strain Clostridium beijerinckii NCIMB 8052 and non-type C. pasteurianum NRRL B-598. A combination of propidium iodide (PI) and carboxyfluorescein diacetate (CFDA), PI plus Syto-9 and bis-oxonol (BOX) alone were employed to distinguish between active and damaged cells together with simultaneous detection of spores. These strategies provided valuable information on the physiological state of clostridia. CFDA and PI staining gave the best separation of four distinct subpopulations of enzymatically active cells, doubly stained cells, damaged cells and spores. Proportional representation of cells in particular sub-regions correlated with growth characteristics, fermentation parameters such as substrate consumption and product formation in both species under different cultivation conditions.
    Keywords: Biotechnology & Synthetic Biology
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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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    Simultaneous saccharification and fermentation of dilute alkaline-pretreated corn stover for enhanced butanol production by Clostridium saccharobutylicum DSM 13864 (2016)
    Oxford University Press
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    Publication Date: 2016-02-03
    Description: Simultaneous saccharification and fermentation (SSF) process was applied for biobutanol production by Clostridium saccharobutylicum DSM 13864 from corn stover (CS). The key influential factors in SSF process, including corn steep liquor concentration, dry biomass and enzyme loading, SSF temperature, inoculation size and pre-hydrolysis time were optimized. In 5-L bioreactor with SSF process, butanol titer and productivity of 12.3 g/L and 0.257 g/L/h were achieved at 48 h, which were 20.6% and 21.2% higher than those in separate hydrolysis and fermentation (SHF), respectively. The butanol yield reached 0.175 g/g pretreated CS in SSF, representing 50.9% increase than that in SHF (0.116 g/g pretreated CS). This study proves the feasibility of efficient and economic production of biobutanol from CS by SSF.
    Keywords: Biotechnology & Synthetic Biology
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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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    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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    Construction and characterization of three protein-targeting expression system in Lactobacillus casei (2016)
    Oxford University Press
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    Publication Date: 2016-03-13
    Description: We previously reported that the β-1,4-Mannanase ( manB ) gene from Bacillus pumilus functions as a good reporter gene in Lactobacillus casei . Two vectors were constructed. One carries the signal peptide of secretion protein Usp45 (SP Usp45 ) from Lactococcus lactis (pELSH), and the other carries the full-length S-layer protein, SlpA, from L. acidophilus (pELWH). In this work, another vector, pELSPH, was constructed to include the signal peptide of protein SlpA (SP SlpA ), and the capacity of all three vectors to drive expression of the manB gene in L. casei was evaluated. The results showed that SP Usp45 is functionally recognized and processed by the L. casei secretion machinery. The SP Usp45 -mediated secretion efficiency was ~87%, and SP SlpA drove the export of secreted ManB with ~80% efficiency. SP SlpA secretion was highly efficient, and expressed SlpA was anchored to the cell wall by an unknown secretion mechanism. Full-length SlpA drove the cell wall-anchored expression of an SlpA-ManB fusion protein but at a much lower level than that of protein SlpA.
    Keywords: Biotechnology & Synthetic Biology
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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
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    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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    Hetero-oligomeric MspA pores in Mycobacterium smegmatis (2016)
    Oxford University Press
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    Publication Date: 2016-03-13
    Description: The porin MspA of Mycobacterium smegmatis is a biological nanopore used for DNA sequencing. The octameric MspA pore can be isolated from M. smegmatis in milligram quantities, is extremely stable against denaturation and rapidly inserts into lipid membranes. Here, we show that MspA pores composed of different Msp subunits are formed in M. smegmatis and that hetero-oligomers of different Msp monomers increase the heterogeneity of MspA pores designed for DNA sequencing. To improve the quality of preparations of mutant MspA proteins, all four msp genes were deleted from the M. smegmatis genome after insertion of an inducible porin gene from M. tuberculosis. In the msp quadruple mutant M. smegmatis ML712 no Msp porins were detected and mutant MspA proteins were produced at wild-type levels. Lipid bilayer experiments demonstrated that MspA pores isolated from ML712 formed functional channels and had a narrower conductance distribution than pores purified from M. smegmatis with background msp expression. Thus, the M. smegmatis msp quadruple mutant improves the homogeneity of MspA pores designed for DNA sequencing and might also facilitate the identification and functional characterization of other mycobacterial pore proteins.
    Keywords: Biotechnology & Synthetic Biology
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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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    Butanol formation from gaseous substrates (2016)
    Oxford University Press
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    Publication Date: 2016-03-04
    Description: Mostly, butanol is formed as a product by saccharolytic anaerobes, employing the so-called ABE fermentation (for acetone–butanol–ethanol). However, this alcohol can also be produced from gaseous substrates such as syn(thesis) gas (major components are carbon monoxide and hydrogen) by autotrophic acetogens. In view of economic considerations, a biotechnological process based on cheap and abundant gases such as CO and CO 2 as a carbon source is preferable to more expensive sugar or starch fermentation. In addition, any conflict for use of substrates that can also serve as human nutrition is avoided. Natural formation of butanol has been found with, e.g. Clostridium carboxidivorans , while metabolic engineering for butanol production was successful using, e.g. C. ljungdahlii . Production of butanol from CO 2 under photoautotrophic conditions was also possible by recombinant DNA construction of a respective cyanobacterial Synechococcus sp. PCC 7942 strain.
    Keywords: Biotechnology & Synthetic Biology
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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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    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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    Lichen-forming fungus Caloplaca flavoruscens inhibits transcription factors and chromatin remodeling system in fungi (2016)
    Oxford University Press
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    Publication Date: 2016-05-20
    Description: Lichen-forming fungi and extracts derived from them have been used as alternative medicine sources for millennia and recently there has been a renewed interest in their known bioactive properties for anticancer agents, cosmetics and antibiotics. Although lichen-forming fungus-derived compounds are biologically and commercially valuable, few studies have been performed to determine their modes of action. This study used chemical-genetic and chemogenomic high-throughput analyses to gain insight into the modes of action of Caloplaca flavoruscens extracts. High-throughput screening of 575 lichen extracts was performed and 39 extracts were identified which inhibited yeast growth. A C. flavoruscens extract was selected as a promising antifungal and was subjected to genome-wide haploinsufficiency profiling and homozygous profiling assays. These screens revealed that yeast deletion strains lacking Rsc8, Pro1 and Toa2 were sensitive to three concentrations (IC 25.5 , IC 25 and IC 50 , respectively) of C. flavoruscens extract. Gene-enrichment analysis of the data showed that C. flavoruscens extracts appear to perturb transcription and chromatin remodeling.
    Keywords: Biotechnology & Synthetic Biology
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    Cytotoxic damage of soybean agglutinin on intestinal epithelial cells of broiler chicks: in vitro protection by Bifidobacterium infantis CRL1395 (2016)
    Oxford University Press
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    Publication Date: 2016-05-20
    Description: Plant lectins, which are proteins/glycoproteins present in a wide range of vegetables, fruits, cereals and beans, are resistant to digestive enzymes and food cooking temperatures. They bind reversibly to specific glycosidic residues expressed on the membrane of intestinal epithelial cells (IEC) and cause anti-nutritional effects in humans and animals. Soybean lectin (SBA) has been detected in poultry diets, and its ability to bind to the intestinal epithelium has been reported. The development of new methods for removing SBA from feeds or to prevent interaction with the intestinal mucosa is of interest. In this study, the in vitro cytotoxicity of SBA on IEC of chicks was demonstrated for the first time. The LD 50 , assessed after 2 h exposure of IEC to SBA, was 6.13 μg mL –1 . The ability of Bifidobacterium infantis CRL1395 to bind SBA on the bacterial envelope was confirmed, and prevention of IEC cytotoxicity by lectin removal was demonstrated. Safety of B. infantis CRL1395, resistance to gastrointestinal stress and adhesion were also determined. It was concluded that the early administration of B. infantis CRL1395 to chicks would effectively reduce the toxicity of SBA. Besides, it would favour the colonization of the gut with a beneficial microbiota.
    Keywords: Biotechnology & Synthetic Biology
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    Catalytic upgrading of butyric acid towards fine chemicals and biofuels (2016)
    Oxford University Press
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    Publication Date: 2016-04-08
    Description: Fermentation-based production of butyric acid is robust and efficient. Modern catalytic technologies make it possible to convert butyric acid to important fine chemicals and biofuels. Here, current chemocatalytic and biocatalytic conversion methods are reviewed with a focus on upgrading butyric acid to 1-butanol or butyl-butyrate. Supported Ruthenium- and Platinum-based catalyst and lipase exhibit important activities which can pave the way for more sustainable process concepts for the production of green fuels and chemicals.
    Keywords: Biotechnology & Synthetic Biology
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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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    Development of an inducible transposon system for efficient random mutagenesis in Clostridium acetobutylicum (2016)
    Oxford University Press
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    Publication Date: 2016-04-15
    Description: Clostridium acetobutylicum is an industrially important Gram-positive organism, which is capable of producing economically important chemicals in the ABE (Acetone, Butanol and Ethanol) fermentation process. Renewed interests in the ABE process necessitate the availability of additional genetics tools to facilitate the derivation of a greater understanding of the underlying metabolic and regulatory control processes in operation through forward genetic strategies. In this study, a xylose inducible, mariner -based, transposon system was developed and shown to allow high-efficient random mutagenesis in the model strain ATCC 824. Of the thiamphenicol resistant colonies obtained, 91.9% were shown to be due to successful transposition of the catP- based mini-transposon element. Phenotypic screening of 200 transposon clones revealed a sporulation-defective clone with an insertion in spo0A , thereby demonstrating that this inducible transposon system can be used for forward genetic studies in C. acetobutylicum .
    Keywords: Biotechnology & Synthetic Biology
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    Keeping it simple: lessons from the golden era of antibiotic discovery (2016)
    Oxford University Press
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    Publication Date: 2016-04-15
    Description: Bacteria are becoming increasingly resistant to currently used antibiotics. At the same time, little progress has been made in discovering new antibacterial drugs to combat resistant organisms. History teaches us that ‘high tech’ target-based complex methods are not synonymous with success and a return to simple, systematic screening of natural products against bacteria from traditional and novel resources holds our greatest hope of success.
    Keywords: Biotechnology & Synthetic Biology
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    n-butanol: challenges and solutions for shifting natural metabolic pathways into a viable microbial production (2016)
    Oxford University Press
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    Publication Date: 2016-04-15
    Description: The economic upturn of the past 200 years would not have been conceivable without fossil resources such as coal and oil. However, the fossil-based economy increasingly reaches its limits and displays contradictions. Bioeconomy, strategically combining economy and ecology willing to make biobased and sustainable growth possible, is promising to make a significant contribution towards solving these issues. In this context, microbial bioconversions are promising to support partially the increasing need for materials and fuels starting from fresh, preferably waste, biomass. Butanol is a very attractive molecule finding applications both as a chemical platform and as a fuel. Today it principally derives from petroleum, but it also represents the final product of microbial catabolic pathways. Because of the need to maximize yield, titer and productivity to make the production competitive and viable, the challenge is to transform a robustly regulated metabolic network into the principal cellular activity. However, this goal can only be accomplished by a profound understanding of the cellular physiology, survival strategy and sensing/signalling cascades. Here, we shortly review on the natural cellular pathways and circumstances that lead to n -butanol accumulation, its physiological consequences that might not match industrial needs and on possible solutions for circumventing these natural constraints.
    Keywords: Biotechnology & Synthetic Biology
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    Downstream process options for the ABE fermentation (2016)
    Oxford University Press
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    Publication Date: 2016-04-20
    Description: Butanol is a very interesting substance both for the chemical industry and as a biofuel. The classical distillation process for the removal of butanol is far too energy demanding, at a factor of 220% of the energy content of butanol. Alternative separation processes studied are hybrid processes of gas-stripping, liquid–liquid extraction and pervaporation with distillation and a novel adsorption/drying/desorption hybrid process. Compared with the energy content of butanol, the resulting energy demand for butanol separation and concentration of optimized hybrid processes is 11%–22% for pervaporation/distillation and 11%–17% for liquid–liquid extraction/distillation. For a novel adsorption/drying/desorption process, the energy demand is 9.4%. But all downstream process options need further proof of industrial applicability.
    Keywords: Biotechnology & Synthetic Biology
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    System-level modeling of acetone-butanol-ethanol fermentation (2016)
    Oxford University Press
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    Publication Date: 2016-04-20
    Description: Acetone–butanol–ethanol (ABE) fermentation is a metabolic process of clostridia that produces bio-based solvents including butanol. It is enabled by an underlying metabolic reaction network and modulated by cellular gene regulation and environmental cues. Mathematical modeling has served as a valuable strategy to facilitate the understanding, characterization and optimization of this process. In this review, we highlight recent advances in system-level, quantitative modeling of ABE fermentation. We begin with an overview of integrative processes underlying the fermentation. Next we survey modeling efforts including early simple models, models with a systematic metabolic description, and those incorporating metabolism through simple gene regulation. Particular focus is given to a recent system-level model that integrates the metabolic reactions, gene regulation and environmental cues. We conclude by discussing the remaining challenges and future directions towards predictive understanding of ABE fermentation.
    Keywords: Biotechnology & Synthetic Biology
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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
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    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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    Cry-like genes, in an uncommon gene configuration, produce a crystal that localizes within the exosporium when expressed in an acrystalliferous strain of Bacillus thuringiensis (2016)
    Oxford University Press
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    Publication Date: 2016-02-10
    Description: Cry proteins are pesticidal toxins produced by the bacterium Bacillus thuringiensis (Bt), which aggregate in sporulating cells to form a crystal. Except in a relatively few cases, these crystals are located outside the exosporium that surrounds the spore. Bt2-56 is a strain of Bt that has the relatively uncommon characteristic of locating its Cry protein-containing crystal within the exosporium, and in association with a long, multifiber filament. With the ultimate goal of both understanding and manipulating the localization of Cry proteins within the exosporium, we sought to identify the genes coding for the exosporium-localized Cry proteins in Bt2-56. Herein we show (i) that five cry-like genes are present in the genome of Bt2-56, (ii) that two pairs of these genes show organizational similarity to a relatively uncommon gene configuration that coexpress a cry gene along with a gene whose product aids crystal formation and (iii) that when one of these two gene pairs (cry21A-cdA) is expressed in an acrystalliferous strain of Bt, crystals are formed that localize within the exosporium. In Bt ssp. finitimus , the only other strain in which crystal localization has been studied, a Cry protein needed expression of two non-cry ORFs in order to localize within the exosporium, indicating that there are some mechanistic differences for crystal localization between Bt ssp. finitimus and Bt2-56.
    Keywords: Biotechnology & Synthetic Biology
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    Production of biobutanol from cellulose hydrolysate by the Escherichia coli co-culture system (2016)
    Oxford University Press
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    Publication Date: 2016-02-12
    Description: The commercialization of the n -butanol bioprocess is largely dependent on the price of feedstocks. Renewable cellulose appears to be an appealing feedstock. The microbial production of n -butanol still remains challenging because of the limited availability of intracellular NADH. To address this issue, an Escherichia coli strain carrying the clostridial CoA-dependent pathway was supplied with heterologous formate dehydrogenase. With the cellulose hydrolysate of rice straw, this single strain produced cellulosic biobutanol with a production yield at 35% of the theoretical and a productivity of 0.093 g L –1  h –1 . In an alternative method, the production involved a co-culture system consisting of two separate strains provided with the full CoA-dependent pathway. This system achieved a production yield and productivity reaching 62.8% of the theoretical and 0.163 g L –1  h –1 , respectively. The result indicates that the E. coli co-culture system is technically promising for the production of cellulosic biobutanol.
    Keywords: Biotechnology & Synthetic Biology
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    Preparation and evaluation of MS2 bacteriophage-like particles packaging hepatitis E virus RNA (2016)
    Oxford University Press
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    Publication Date: 2016-11-09
    Description: Hepatitis E virus (HEV) is the pathogen causing hepatitis E (HE). It arouses global public health concern since it is a zoonotic disease. The objective of this letter is to report a cost-effective internal control prepared for monitoring procedures of HEV reverse transcriptase (RT)-PCR detection. A selected conserved HEV RNA fragment was integrated into the downstream of the truncated MS2 bacteriophage genome based on Armored RNA technology. The resulting MS2-HEV gene harbored by the pET-28b-MS2-HEV plasmid was transformed into E. coli BL21(DE3) for expression analysis by SDS-PAGE. The expression products were purified and concentrated by ultrasonication and ultrafiltration separation. The morphology and stability properties of the virus-like particles (VLPs) were evaluated by electron microscopy scanning and nuclease challenges, respectively. SDS-PAGE results showed that the constructed MS2-HEV gene expressed efficiently and the purity of the VLPs was highly consistent with the result in electron microscopy. Stability evaluation results demonstrated that the prepared VLPs exhibited strong resistance to DNase I and RNase A attacks and also performed long-lasting protection of coated HEV RNA for at least 4 months at –20°C. These data revealed that the prepared VLPs meet the basic requirements of use as internal control material in the HEV RNA amplification assay.
    Keywords: Biotechnology & Synthetic Biology
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    Epigenetics knocks on synthetic biology's door (2016)
    Oxford University Press
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    Publication Date: 2016-09-08
    Description: Epigenetics is the study of heritable changes in gene expression without concomitant changes in DNA sequence. Due to its relevance in development, differentiation and human health, epigenetics has recently become an emerging area of science with regard to eukaryotic organisms and has shown enormous potential in synthetic biology. However, significant examples of epigenetic regulation in bacterial synthetic biology have not yet been reported. In the current study, we present the first model of such an epigenetic circuit. We termed the circuit the alternator circuit because parental cells carrying this circuit and their progeny alternate between distinct and heritable cellular fates without undergoing changes in genome sequence. Furthermore, we demonstrated that the alternator circuit exhibits hysteresis because its output depends not only on its present state but also on its previous states.
    Keywords: Biotechnology & Synthetic Biology
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    Robust lineage reconstruction from high-dimensional single-cell data (2016)
    Oxford University Press
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    Publication Date: 2016-08-20
    Description: Single-cell gene expression data provide invaluable resources for systematic characterization of cellular hierarchy in multi-cellular organisms. However, cell lineage reconstruction is still often associated with significant uncertainty due to technological constraints. Such uncertainties have not been taken into account in current methods. We present ECLAIR (Ensemble Cell Lineage Analysis with Improved Robustness), a novel computational method for the statistical inference of cell lineage relationships from single-cell gene expression data. ECLAIR uses an ensemble approach to improve the robustness of lineage predictions, and provides a quantitative estimate of the uncertainty of lineage branchings. We show that the application of ECLAIR to published datasets successfully reconstructs known lineage relationships and significantly improves the robustness of predictions. ECLAIR is a powerful bioinformatics tool for single-cell data analysis. It can be used for robust lineage reconstruction with quantitative estimate of prediction accuracy.
    Keywords: Computational Methods, Genomics
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    The endolysin from the Enterococcus faecalis bacteriophage VD13 and conditions stimulating its lytic activity (2016)
    Oxford University Press
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    Publication Date: 2016-10-12
    Description: Bacteriophages produce endolysins (peptidoglycan hydrolases) to lyse the host cell from within and release nascent bacteriophage particles. Recombinant endolysins can lyse Gram-positive bacteria when added exogenously. As a potential alternative antimicrobial, we cloned and expressed the enterococcal VD13 bacteriophage endolysin. VD13 endolysin has a CHAP catalytic domain with 92% identity with the bacteriophage IME-EF1 endolysin. The predicted size of VD13 endolysin is ~27 kDa as verified by SDS-PAGE. The VD13 endolysin lyses Enterococcus faecalis strains, but not E. faecium or other non-enterococci. VD13 endolysin has activity from pH 4 to pH 8, with peak activity at pH 5, and exhibits greater activity in the presence of calcium. Optimum activity at pH 5 occurs in the absence of NaCl. VD13 endolysin, in ammonium acetate (C 2 H 3 O 2 NH 4 ) calcium chloride (CaCl 2 ) buffer pH 5, is stimulated to higher activity upon heating at temperatures up to 65°C for 30 min, whereas activity is lost upon heating to 42°C, in pH 7 buffer.
    Keywords: Biotechnology & Synthetic Biology
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    Cultivation of an immobilized (hyper)thermophilic marine microbial community in a bioreactor (2016)
    Oxford University Press
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    Publication Date: 2016-09-08
    Description: Cultivation in a bioreactor of immobilized deep-sea hydrothermal microbial community was tested in order to assess the stability and reactivity of this new system. A community composed of eight hydrothermal strains was entrapped in a polymer matrix that was used to inoculate a continuous culture in a gas-lift bioreactor. The continuous culture was performed for 41 days at successively 60°C, 55°C, 60°C, 85°C and 60°C, at pH 6.5, in anaerobic condition and constant dilution rate. Oxic stress and pH variations were tested at the beginning of the incubation. Despite these detrimental conditions, three strains including two strict anaerobes were maintained in the bioreactor. High cell concentrations (3 x 10 8 cells mL –1 ) and high ATP contents were measured in both liquid fractions and beads. Cloning-sequencing and qPCR revealed that Bacillus sp. dominated at the early stage, and was later replaced by Thermotoga maritima and Thermococcus sp. Acetate, formate and propionate concentrations varied simultaneously in the liquid fractions. These results demonstrate that these immobilized cells were reactive to culture conditions. They were protected inside the beads during the stress period and released in the liquid fraction when conditions were more favorable. This confirms the advantage of immobilization that highlights the resilience capacity of certain hydrothermal microorganisms after a stress period.
    Keywords: Biotechnology & Synthetic Biology
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    The exon quantification pipeline (EQP): a comprehensive approach to the quantification of gene, exon and junction expression from RNA-seq data (2016)
    Oxford University Press
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    Publication Date: 2016-09-20
    Description: The quantification of transcriptomic features is the basis of the analysis of RNA-seq data. We present an integrated alignment workflow and a simple counting-based approach to derive estimates for gene, exon and exon–exon junction expression. In contrast to previous counting-based approaches, EQP takes into account only reads whose alignment pattern agrees with the splicing pattern of the features of interest. This leads to improved gene expression estimates as well as to the generation of exon counts that allow disambiguating reads between overlapping exons. Unlike other methods that quantify skipped introns, EQP offers a novel way to compute junction counts based on the agreement of the read alignments with the exons on both sides of the junction, thus providing a uniformly derived set of counts. We evaluated the performance of EQP on both simulated and real Illumina RNA-seq data and compared it with other quantification tools. Our results suggest that EQP provides superior gene expression estimates and we illustrate the advantages of EQP's exon and junction counts. The provision of uniformly derived high-quality counts makes EQP an ideal quantification tool for differential expression and differential splicing studies. EQP is freely available for download at https://github.com/Novartis/EQP-cluster .
    Keywords: Computational Methods, Genomics
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    Boiler: lossy compression of RNA-seq alignments using coverage vectors (2016)
    Oxford University Press
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    Publication Date: 2016-09-20
    Description: We describe Boiler, a new software tool for compressing and querying large collections of RNA-seq alignments. Boiler discards most per-read data, keeping only a genomic coverage vector plus a few empirical distributions summarizing the alignments. Since most per-read data is discarded, storage footprint is often much smaller than that achieved by other compression tools. Despite this, the most relevant per-read data can be recovered; we show that Boiler compression has only a slight negative impact on results given by downstream tools for isoform assembly and quantification. Boiler also allows the user to pose fast and useful queries without decompressing the entire file. Boiler is free open source software available from github.com/jpritt/boiler .
    Keywords: Computational Methods, Genomics
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    A simple technique for suppressor detection in Escherichia coli (2016)
    Oxford University Press
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    Publication Date: 2016-10-12
    Description: To study the viability of a gyrA S83 stop mutation found in an Escherichia coli J53 ciprofloxacin-resistant strain (J53 CipR27), a pBR322 derivative was constructed with a TAG mutation in the bla gene knocking out ampicillin resistance. Ampicillin resistance was restored, suggesting that the strain contains tRNA suppressor activity able to suppress the UAG codon gyrA and allow viability. The method was applied to 22 unique clinical E. coli isolates, and all were found to have low-level suppressor activity.
    Keywords: Biotechnology & Synthetic Biology
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    Global transcript structure resolution of high gene density genomes through multi-platform data integration (2016)
    Oxford University Press
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    Publication Date: 2016-10-14
    Description: Annotation of herpesvirus genomes has traditionally been undertaken through the detection of open reading frames and other genomic motifs, supplemented with sequencing of individual cDNAs. Second generation sequencing and high-density microarray studies have revealed vastly greater herpesvirus transcriptome complexity than is captured by existing annotation. The pervasive nature of overlapping transcription throughout herpesvirus genomes, however, poses substantial problems in resolving transcript structures using these methods alone. We present an approach that combines the unique attributes of Pacific Biosciences Iso-Seq long-read, Illumina short-read and deepCAGE (Cap Analysis of Gene Expression) sequencing to globally resolve polyadenylated isoform structures in replicating Epstein-Barr virus (EBV). Our method, Transcriptome Resolution through Integration of Multi-platform Data (TRIMD), identifies nearly 300 novel EBV transcripts, quadrupling the size of the annotated viral transcriptome. These findings illustrate an array of mechanisms through which EBV achieves functional diversity in its relatively small, compact genome including programmed alternative splicing (e.g. across the IR1 repeats), alternative promoter usage by LMP2 and other latency-associated transcripts, intergenic splicing at the BZLF2 locus, and antisense transcription and pervasive readthrough transcription throughout the genome.
    Keywords: Computational Methods, Genomics
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    Identification of multi-loci hubs from 4C-seq demonstrates the functional importance of simultaneous interactions (2016)
    Oxford University Press
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    Publication Date: 2016-10-14
    Description: Use of low resolution single cell DNA FISH and population based high resolution chromosome conformation capture techniques have highlighted the importance of pairwise chromatin interactions in gene regulation. However, it is unlikely that associations involving regulatory elements act in isolation of other interacting partners that also influence their impact. Indeed, the influence of multi-loci interactions remains something of an enigma as beyond low-resolution DNA FISH we do not have the appropriate tools to analyze these. Here we present a method that uses standard 4C-seq data to identify multi-loci interactions from the same cell. We demonstrate the feasibility of our method using 4C-seq data sets that identify known pairwise and novel tri-loci interactions involving the Tcrb and Igk antigen receptor enhancers. We further show that the three Igk enhancers, MiE, 3'E and Ed, interact simultaneously in this super-enhancer cluster, which add to our previous findings showing that loss of one element decreases interactions between all three elements as well as reducing their transcriptional output. These findings underscore the functional importance of simultaneous interactions and provide new insight into the relationship between enhancer elements. Our method opens the door for studying multi-loci interactions and their impact on gene regulation in other biological settings.
    Keywords: Computational Methods, Genomics
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    Enterotoxigenic Escherichia coli heat-stable toxin and heat-labile toxin toxoid fusion 3xSTaN12S-dmLT induces neutralizing anti-STa antibodies in subcutaneously immunized mice (2016)
    Oxford University Press
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    Publication Date: 2016-11-17
    Description: Enterotoxigenic Escherichia coli (ETEC) bacteria producing heat-stable toxin (STa) and/or heat-labile toxin (LT) are among top causes of children's diarrhea and travelers’ diarrhea. Currently no vaccines are available for ETEC associated diarrhea. A major challenge in developing ETEC vaccines is the inability to stimulate protective antibodies against the key STa toxin that is potently toxic and also poorly immunogenic. A recent study suggested toxoid fusion 3xSTa N12S -dmLT, which consists of a monomer LT toxoid (LT R192G/L211A ) and three copies of STa toxoid STa N12S , may represent an optimal immunogen inducing neutralizing antibodies against STa toxin [IAI 2014, 82(5):1823-32]. In this study, we immunized mice with this fusion protein following a different parenteral route and using different adjuvants to further characterize immunogenicity of this toxoid fusion. Data from this study showed that 3xSTa N12S -dmLT toxoid fusion induced neutralizing anti-STa antibodies in the mice following subcutaneous immunization, as effectively as in the mice under intraperitoneal route. Data also indicated that double mutant LT (dmLT) can be an effective adjuvant for this toxoid fusion in mice subcutaneous immunization. Results from this study affirmed that toxoid fusion 3xSTa N12S -dmLT induces neutralizing antibodies against STa toxin, suggesting this toxoid fusion is potentially a promising immunogen for ETEC vaccine development.
    Keywords: Biotechnology & Synthetic Biology
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    Identify bilayer modules via pseudo-3D clustering: applications to miRNA-gene bilayer networks (2016)
    Oxford University Press
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    Publication Date: 2016-12-01
    Description: Module identification is a frequently used approach for mining local structures with more significance in global networks. Recently, a wide variety of bilayer networks are emerging to characterize the more complex biological processes. In the light of special topological properties of bilayer networks and the accompanying challenges, there is yet no effective method aiming at bilayer module identification to probe the modular organizations from the more inspiring bilayer networks. To this end, we proposed the pseudo-3D clustering algorithm, which starts from extracting initial non-hierarchically organized modules and then iteratively deciphers the hierarchical organization of modules according to a bottom-up strategy. Specifically, a modularity function for bilayer modules was proposed to facilitate the algorithm reporting the optimal partition that gives the most accurate characterization of the bilayer network. Simulation studies demonstrated its robustness and outperformance against alternative competing methods. Specific applications to both the soybean and human miRNA-gene bilayer networks demonstrated that the pseudo-3D clustering algorithm successfully identified the overlapping, hierarchically organized and highly cohesive bilayer modules. The analyses on topology, functional and human disease enrichment and the bilayer subnetwork involved in soybean fat biosynthesis provided both the theoretical and biological evidence supporting the effectiveness and robustness of pseudo-3D clustering algorithm.
    Keywords: Computational Methods, Genomics
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    Finding approximate gene clusters with GECKO 3 (2016)
    Oxford University Press
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    Publication Date: 2016-12-01
    Description: Gene-order-based comparison of multiple genomes provides signals for functional analysis of genes and the evolutionary process of genome organization. Gene clusters are regions of co-localized genes on genomes of different species. The rapid increase in sequenced genomes necessitates bioinformatics tools for finding gene clusters in hundreds of genomes. Existing tools are often restricted to few (in many cases, only two) genomes, and often make restrictive assumptions such as short perfect conservation, conserved gene order or monophyletic gene clusters. We present Gecko 3, an open-source software for finding gene clusters in hundreds of bacterial genomes, that comes with an easy-to-use graphical user interface. The underlying gene cluster model is intuitive, can cope with low degrees of conservation as well as misannotations and is complemented by a sound statistical evaluation. To evaluate the biological benefit of Gecko 3 and to exemplify our method, we search for gene clusters in a dataset of 678 bacterial genomes using Synechocystis sp. PCC 6803 as a reference. We confirm detected gene clusters reviewing the literature and comparing them to a database of operons; we detect two novel clusters, which were confirmed by publicly available experimental RNA-Seq data. The computational analysis is carried out on a laptop computer in 〈40 min.
    Keywords: Computational Methods, Genomics
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    OmpF of Pectobacterium carotovorum subsp. carotovorum Pcc3 is required for carocin D sensitivity (2016)
    Oxford University Press
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    Publication Date: 2016-12-23
    Description: Carocin D is a bacteriocin produced by Pectobacterium carotovorum subsp. carotovorum Pcc21. Carocin D inhibits the growth of P . carotovorum subsp. carotovorum and closely related strains. Pectobacterium carotovorum subsp. carotovorum is a causative bacterium for soft rot disease and leads to severe economic losses. Bacteriocins recognize and interact with a specific membrane protein of target bacteria as a receptor. To identify the receptor responsible for carocin D recognition, mutants that underwent a phenotypic change from carocin D sensitivity to carocin D insensitivity were screened. Based on Tn 5 insertions, carocin D sensitivity was dependent on expression of the outer membrane protein OmpF. The insensitivity of the mutant (Pcc3MR) to carocin D was complemented with ompF from carocin D-sensitive strains, not from carocin D-resistant strains. The selectivity between sensitive and resistant strains could be attributed to variation in OmpFs in the cell-surface-exposed regions. Based on sequence analysis and complementation assays, it appears that carocin D uses OmpF as a receptor and is translocated by the TonB system. According to previously reported translocation mechanisms of colicins, OmpF works along with the TolA system rather than the TonB system. Therefore, the current findings suggest that carocin D is imported by a unique colicin-like bacteriocin translocation system.
    Keywords: Biotechnology & Synthetic Biology
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    A framework for improving microRNA prediction in non-human genomes (2015)
    Oxford University Press
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    Publication Date: 2015-11-17
    Description: The prediction of novel pre-microRNA (miRNA) from genomic sequence has received considerable attention recently. However, the majority of studies have focused on the human genome. Previous studies have demonstrated that sensitivity (correctly detecting true miRNA) is sustained when human-trained methods are applied to other species, however they have failed to report the dramatic drop in specificity (the ability to correctly reject non-miRNA sequences) in non-human genomes. Considering the ratio of true miRNA sequences to pseudo-miRNA sequences is on the order of 1:1000, such low specificity prevents the application of most existing tools to non-human genomes, as the number of false positives overwhelms the true predictions. We here introduce a framework (SMIRP) for creating species-specific miRNA prediction systems, leveraging sequence conservation and phylogenetic distance information. Substantial improvements in specificity and precision are obtained for four non-human test species when our framework is applied to three different prediction systems representing two types of classifiers (support vector machine and Random Forest), based on three different feature sets, with both human-specific and taxon-wide training data. The SMIRP framework is potentially applicable to all miRNA prediction systems and we expect substantial improvement in precision and specificity, while sustaining sensitivity, independent of the machine learning technique chosen.
    Keywords: Computational Methods, Genomics
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    Efficient exploration of pan-cancer networks by generalized covariance selection and interactive web content (2015)
    Oxford University Press
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    Publication Date: 2015-08-29
    Description: Statistical network modeling techniques are increasingly important tools to analyze cancer genomics data. However, current tools and resources are not designed to work across multiple diagnoses and technical platforms, thus limiting their applicability to comprehensive pan-cancer datasets such as The Cancer Genome Atlas (TCGA). To address this, we describe a new data driven modeling method, based on generalized Sparse Inverse Covariance Selection (SICS). The method integrates genetic, epigenetic and transcriptional data from multiple cancers, to define links that are present in multiple cancers, a subset of cancers, or a single cancer. It is shown to be statistically robust and effective at detecting direct pathway links in data from TCGA. To facilitate interpretation of the results, we introduce a publicly accessible tool ( cancerlandscapes.org ), in which the derived networks are explored as interactive web content, linked to several pathway and pharmacological databases. To evaluate the performance of the method, we constructed a model for eight TCGA cancers, using data from 3900 patients. The model rediscovered known mechanisms and contained interesting predictions. Possible applications include prediction of regulatory relationships, comparison of network modules across multiple forms of cancer and identification of drug targets.
    Keywords: Computational Methods, Genomics
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