ALBERT

Description: Fishermen are known to try to avoid fishing in stormy weather, as storms pose a physical threat to fishers, their vessels, and their gear. In this article, a dataset and methods are developed to investigate the degree to which fishers avoid storms, estimate storm aversion parameters, and explore how this response varies across vessel characteristics and across regions of the United States. The data consist of vessel-level trip-taking decisions from six federal fisheries across the United States combined with marine storm warning data from the National Weather Service. The estimates of storm aversion can be used to parameterize predictive models. Fishers’ aversion to storms decreases with increasing vessel size and increases with the severity of the storm warning. This information contributes to our understanding of the risk-to-revenue trade-off that fishers evaluate every time they consider going to sea, and of the propensity of fishers to take adaptive actions to avoid facing additional physical risk.

Description: Sardine Sardinops sagax is an ecologically and economically important Clupeid found off the entire South African coast that includes both coastal upwelling and western boundary current systems. Although the management of the sardine fisheries historically assumed a single, panmictic population, the existence of three, semi-discrete subpopulations has recently been hypothesized. We conducted otolith δ18O and microstructure analyses to investigate nursery habitat temperatures and early life growth rates, respectively, of sardine collected from three biogeographic regions around South Africa’s coast to test that hypothesis. Analyses indicated that for both summer- and winter-captured adults and summer-captured juveniles, fishes from the west coast grew significantly slower in water that was several degrees cooler than those from the south and east coasts. This suggests that mixing of sardines between regions, particularly the west and other coasts, is relatively limited and supports the hypothesis of semi-discrete subpopulations. However, the west-south differences disappeared in the results for winter-captured juveniles, suggesting that differences in early life conditions between regions may change seasonally, and/or that all or most winter-captured juveniles originated from the west coast. Further elucidating the interactions between South African sardine subpopulations and the mechanisms thereof is important for sustainable harvesting of this species.

Description: CerealsDB (www.cerealsdb.uk.net) is an online repository of mainly hexaploid wheat (Triticum aestivum) single nucleotide polymorphisms (SNPs) and genotyping data. The CerealsDB website has been designed to enable wheat breeders and scientists to select the appropriate markers for research breeding tasks, such as marker-assisted selection. We report a large update of genotyping information for over 6000 wheat accessions and describe new webtools for exploring and visualizing the data. We also describe a new database of quantitative trait loci that links phenotypic traits to CerealsDB SNP markers and allelic scores for each of those markers. CerealsDB is an open-access website that hosts information on wheat SNPs considered useful for both plant breeders and research scientists. The latest CerealsDB database is available at https://www.cerealsdb.uk.net/cerealgenomics/CerealsDB/indexNEW.php.

Description: Progress towards ecosystem-based fisheries management calls for useful tools to prioritize actions. To select suitable methods for local circumstances, evaluating approaches used in other jurisdictions can be a cost-effective first step. We tested Productivity Susceptibility Analysis (PSA) to assess the potential vulnerability of the marine fish community in the Skagerrak–Kattegat (Eastern North Sea) to possible interactions with all Swedish fisheries operating in the area. This analysis combines attributes for a species productivity with attributes related to the susceptibility to capture to quantify a single score for vulnerability: high, medium, or low risk. Results indicate that demersal trawl and gillnet fisheries were associated with the highest risk levels if interaction occurs, i.e. having the highest prevalence of species with potentially high vulnerability to the fisheries. Mixed results were seen when comparing the assessment results with available data. The main benefit of utilizing PSA in the area is the comprehensiveness of the assessment, including data-deficient fisheries and species. Drawbacks include potential overestimation of actual risks. Overall, together with available data, PSA in the studied area provides a comprehensive map of potential risks for further actions and may progress a science-based, precautionary management of the area.

Description: While fisheries provide food and employment for hundreds of millions of people, they also can have significant impact on biodiversity. We explore the potential of area-based fisheries management to simultaneously maintain biodiversity and high levels of sustainable food production. We used two illustrative examples of fisheries that have different gear types, areas, and species to evaluate the trade-off between biodiversity and harvest. We calculate the optimal effort by gear and area that maximizes a weighted objective function of biodiversity and harvest, ranging from 100% of the weight on harvest to 100% on biodiversity. We found for both case studies that the trade-off was highly convex, with win–win solutions allowing for high levels of both fishery harvest and conservation. This is achieved by reducing or eliminating fishing effort that negatively impacts high conservation value species while maintaining fishing effort with gears and in areas where there is low conservation impact. We suggest that, in most fisheries, such situations can be found and that effective area-based management can provide for high levels of biodiversity protection and food production.

Description: Repeatability of study setups and reproducibility of research results by underlying data are major requirements in science. Until now, abstract models for describing the structural logic of studies in environmental sciences are lacking and tools for data management are insufficient. Mandatory for repeatability and reproducibility is the use of sophisticated data management solutions going beyond data file sharing. Particularly, it implies maintenance of coherent data along workflows. Design data concern elements from elementary domains of operations being transformation, measurement and transaction. Operation design elements and method information are specified for each consecutive workflow segment from field to laboratory campaigns. The strict linkage of operation design element values, operation values and objects is essential. For enabling coherence of corresponding objects along consecutive workflow segments, the assignment of unique identifiers and the specification of their relations are mandatory. The abstract model presented here addresses these aspects, and the software DiversityDescriptions (DWB-DD) facilitates the management of thusly connected digital data objects and structures. DWB-DD allows for an individual specification of operation design elements and their linking to objects. Two workflow design use cases, one for DNA barcoding and another for cultivation of fungal isolates, are given. To publish those structured data, standard schema mapping and XML-provision of digital objects are essential. Schemas useful for this mapping include the Ecological Markup Language, the Schema for Meta-omics Data of Collection Objects and the Standard for Structured Descriptive Data. Data pipelines with DWB-DD include the mapping and conversion between schemas and functions for data publishing and archiving according to the Open Archival Information System standard. The setting allows for repeatability of study setups, reproducibility of study results and for supporting work groups to structure and maintain their data from the beginning of a study. The theory of ‘FAIR++’ digital objects is introduced.

Description: Recent application of Fourier transform near infra-red spectroscopy (FT-NIRS) to predict age in fish otoliths has gained attention among fisheries managers as a potential alternative to costly production ageing of managed species. We assessed the age prediction capability of FT-NIRS scans in whole otoliths from red snapper, Lutjanus campechanus, collected from the US Gulf of Mexico and US Atlantic Ocean (South Atlantic). Otoliths were scanned with an FT-NIR spectrometer and resulting spectral signatures were regressed with traditionally estimated ages via partial least squares regression to produce calibration models, which were validated for predictive capability against test sets of otoliths. Calibration models successfully predicted age with R2 ranging 0.94–0.95, mean squared error ≤1.8 years, and bias 31 years were not well predicted, possibly due to light attenuation in the thickest otoliths. Our results suggest that FT-NIRS can improve efficiency in production ageing for fisheries management while maintaining data quality standards.

Description: This article investigates the diet of the snow crab (Chionoecetes opilio) and its feeding intensity in the Barents Sea. Data show that snow crab has a diverse diet that includes almost all types of benthic invertebrates living in the Barents Sea. There are differences between the diets of females and males and of juveniles and adults. Juveniles and females typically occupy shallow areas with communities of bivalve molluscs, while males typically live deeper on slopes and depressions where polychaetes and crustaceans are the most abundant groups. Stomach contents were analysed to determine the species composition and frequency of occurrence of various benthic taxa. Consumption of food was estimated and compared with data from the Russian seas of the Pacific region. The total annual consumption of macrozoobenthos by snow crab was calculated in accordance with its current distribution in the Barents Sea. Snow crab consumes at least 30 000 tonnes of benthos annually, which amounts to 0.1–0.2% of the total macrozoobenthic biomass in the investigated area. The population of snow crab causes the largest impact on the benthic communities in the northeastern part of the Barents Sea and near the south side of the Novaya Zemlya archipelago.

Description: Until the late 19th century, extensive beds of flat oyster Ostrea edulis populated the Central North Sea, which have vanished after intensive fisheries. At present, various initiatives are being carried out to investigate the potential to restore this former key species in the area. This historical ecological study contributes by delineating the former oyster bed area and through an assessment of its limits against known gradients in the North Sea. Extensive data from historical maps, texts, and ship-based surveys were used to synthesize our knowledge on the former beds. It was revealed that the area with oyster beds covered ∼6.2% of the total North Sea bottom, with a delineation that could partly be explained by hydrodynamic and temperature gradients. The position and extent of the area are notably different from the area that is used in recent feasibility studies on the restoration of North Sea oyster beds. The offshore oysters lived on muddy sand in relatively cold conditions, and there are several indications that their reproductive rate was low. The apparent disappearance of cold water adapted flat oysters will challenge restoration projects. This study provides indispensable information for the future restoration of flat oyster beds in the North Sea.

Description: : As sequencing becomes cheaper and more widely available, there is a greater need to quickly and effectively analyze large-scale genomic data. While the functionality of AVIA v1.0, whose implementation was based on ANNOVAR, was comparable with other annotation web servers, AVIA v2.0 represents an enhanced web-based server that extends genomic annotations to cell-specific transcripts and protein-level functional annotations. With AVIA’s improved interface, users can better visualize their data, perform comprehensive searches and categorize both coding and non-coding variants. Availability and implementation : AVIA is freely available through the web at http://avia.abcc.ncifcrf.gov . Contact : Hue.Vuong@fnlcr.nih.gov Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : As new methods for multivariate analysis of genome wide association studies become available, it is important to be able to combine results from different cohorts in a meta-analysis. The R package MultiMeta provides an implementation of the inverse-variance-based method for meta-analysis, generalized to an n -dimensional setting. Availability and implementation: The R package MultiMeta can be downloaded from CRAN. Contact: dragana.vuckovic@burlo.trieste.it ; vi1@sanger.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Some of the most dangerous pathogens such as Mycobacterium tuberculosis and Yersinia pestis evolve clonally . This means that little or no recombination occurs between strains belonging to these species. Paradoxically, although different members of these species show extreme sequence similarity of orthologous genes, some show considerable intraspecies phenotypic variation, the source of which remains elusive. To examine the possible sources of phenotypic variation within clonal pathogenic bacterial species, we carried out an extensive genomic and pan-genomic analysis of the sources of genetic variation available to a large collection of clonal and nonclonal pathogenic bacterial species. We show that while nonclonal species diversify through a combination of changes to gene sequences, gene loss and gene gain, gene loss completely dominates as a source of genetic variation within clonal species. Indeed, gene loss is so prevalent within clonal species as to lead to levels of gene content variation comparable to those found in some nonclonal species that are much more diverged in their gene sequences and that acquire a substantial number of genes horizontally. Gene loss therefore needs to be taken into account as a potential dominant source of phenotypic variation within clonal bacterial species.

Description: Obligate bacterial symbionts are widespread in many invertebrates, where they are often confined to specialized host cells and are transmitted directly from mother to progeny. Increasing numbers of these bacteria are being characterized but questions remain about their population structure and evolution. Here we take a comparative genomics approach to investigate two prominent bacterial symbionts (BFo1 and BFo2) isolated from geographically separated populations of western flower thrips, Frankliniella occidentalis. Our multifaceted approach to classifying these symbionts includes concatenated multilocus sequence analysis (MLSA) phylogenies, ribosomal multilocus sequence typing (rMLST), construction of whole-genome phylogenies, and in-depth genomic comparisons. We showed that the BFo1 genome clusters more closely to species in the genus Erwinia, and is a putative close relative to Erwinia aphidicola . BFo1 is also likely to have shared a common ancestor with Erwinia pyrifoliae/Erwinia amylovora and the nonpathogenic Erwinia tasmaniensis and genetic traits similar to Erwinia billingiae . The BFo1 genome contained virulence factors found in the genus Erwinia but represented a divergent lineage. In contrast, we showed that BFo2 belongs within the Enterobacteriales but does not group closely with any currently known bacterial species. Concatenated MLSA phylogenies indicate that it may have shared a common ancestor to the Erwinia and Pantoea genera, and based on the clustering of rMLST genes, it was most closely related to Pantoea ananatis but represented a divergent lineage. We reconstructed a core genome of a putative common ancestor of Erwinia and Pantoea and compared this with the genomes of BFo bacteria. BFo2 possessed none of the virulence determinants that were omnipresent in the Erwinia and Pantoea genera. Taken together, these data are consistent with BFo2 representing a highly novel species that maybe related to known Pantoea .

Description: Gene expression evolution occurs through changes in cis - or trans -regulatory elements or both. Interactions between transcription factors (TFs) and their binding sites (TFBSs) constitute one of the most important points where these two regulatory components intersect. In this study, we investigated the evolution of TFBSs in the promoter regions of different Saccharomyces strains and species. We divided the promoter of a gene into the proximal region and the distal region, which are defined, respectively, as the 200-bp region upstream of the transcription starting site and as the 200-bp region upstream of the proximal region. We found that the predicted TFBSs in the proximal promoter regions tend to be evolutionarily more conserved than those in the distal promoter regions. Additionally, Saccharomyces cerevisiae strains used in the fermentation of alcoholic drinks have experienced more TFBS losses than gains compared with strains from other environments (wild strains, laboratory strains, and clinical strains). We also showed that differences in TFBSs correlate with the cis component of gene expression evolution between species (comparing S. cerevisiae and its sister species Saccharomyces paradoxus ) and within species (comparing two closely related S. cerevisiae strains).

Description: Gene duplication is a key factor contributing to phenotype diversity across and within species. Although the availability of complete genomes has led to the extensive study of genomic duplications, the dynamics and variability of gene duplications mediated by retrotransposition are not well understood. Here, we predict mRNA retrotransposition and use comparative genomics to investigate their origin and variability across primates. Analyzing seven anthropoid primate genomes, we found a similar number of mRNA retrotranspositions (~7,500 retrocopies) in Catarrhini (Old Word Monkeys, including humans), but a surprising large number of retrocopies (~10,000) in Platyrrhini (New World Monkeys), which may be a by-product of higher long interspersed nuclear element 1 activity in these genomes. By inferring retrocopy orthology, we dated most of the primate retrocopy origins, and estimated a decrease in the fixation rate in recent primate history, implying a smaller number of species-specific retrocopies. Moreover, using RNA-Seq data, we identified approximately 3,600 expressed retrocopies. As expected, most of these retrocopies are located near or within known genes, present tissue-specific and even species-specific expression patterns, and no expression correlation to their parental genes. Taken together, our results provide further evidence that mRNA retrotransposition is an active mechanism in primate evolution and suggest that retrocopies may not only introduce great genetic variability between lineages but also create a large reservoir of potentially functional new genomic loci in primate genomes.

Description: Viruses rely completely on the hosts’ machinery for translation of viral transcripts. However, for most viruses infecting humans, codon usage preferences (CUPrefs) do not match those of the host. Human papillomaviruses (HPVs) are a showcase to tackle this paradox: they present a large genotypic diversity and a broad range of phenotypic presentations, from asymptomatic infections to productive lesions and cancer. By applying phylogenetic inference and dimensionality reduction methods, we demonstrate first that genes in HPVs are poorly adapted to the average human CUPrefs, the only exception being capsid genes in viruses causing productive lesions. Phylogenetic relationships between HPVs explained only a small proportion of CUPrefs variation. Instead, the most important explanatory factor for viral CUPrefs was infection phenotype, as orthologous genes in viruses with similar clinical presentation displayed similar CUPrefs. Moreover, viral genes with similar spatiotemporal expression patterns also showed similar CUPrefs. Our results suggest that CUPrefs in HPVs reflect either variations in the mutation bias or differential selection pressures depending on the clinical presentation and expression timing. We propose that poor viral CUPrefs may be central to a trade-off between strong viral gene expression and the potential for eliciting protective immune response.

Description: Huntington's disease (HD) is a hereditary neurodegenerative disorder characterized by brain atrophy particularly in striatum leading to personality changes, chorea and dementia. Glycogen synthase kinase-3 (GSK-3) is a serine/threonine kinase in the crossroad of many signaling pathways that is highly pleiotropic as it phosphorylates more than hundred substrates including structural, metabolic, and signaling proteins. Increased GSK-3 activity is believed to contribute to the pathogenesis of neurodegenerative diseases like Alzheimer's disease and GSK-3 inhibitors have been postulated as therapeutic agents for neurodegeneration. Regarding HD, GSK-3 inhibitors have shown beneficial effects in cell and invertebrate animal models but no evident efficacy in mouse models. Intriguingly, those studies were performed without interrogating GSK-3 level and activity in HD brain. Here we aim to explore the level and also the enzymatic activity of GSK-3 in the striatum and other less affected brain regions of HD patients and of the R6/1 mouse model to then elucidate the possible contribution of its alteration to HD pathogenesis by genetic manipulation in mice. We report a dramatic decrease in GSK-3 levels and activity in striatum and cortex of HD patients with similar results in the mouse model. Correction of the GSK-3 deficit in HD mice, by combining with transgenic mice with conditional GSK-3 expression, resulted in amelioration of their brain atrophy and behavioral motor and learning deficits. Thus, our results demonstrate that decreased brain GSK-3 contributes to HD neurological phenotype and open new therapeutic opportunities based on increasing GSK-3 activity or attenuating the harmful consequences of its decrease.

Description: Spinocerebellar ataxia type 6 (SCA6) is dominantly inherited neurodegenerative disease, caused by an expansion of CAG repeat encoding a polyglutamine (PolyQ) tract in the Ca v 2.1 voltage-gated calcium channel. Its key pathological features include selective degeneration of the cerebellar Purkinje cells (PCs), a common target for PolyQ-induced toxicity in various SCAs. Mutant Ca v 2.1 confers toxicity primarily through a toxic gain-of-function mechanism; however, its molecular basis remains elusive. Here, we studied the cerebellar gene expression patterns of young Sca6 -MPI 118Q/118Q knockin (KI) mice, which expressed mutant Ca v 2.1 from an endogenous locus and recapitulated many phenotypic features of human SCA6. Transcriptional signatures in the MPI 118Q/118Q mice were distinct from those in the Sca1 154Q/2Q mice, a faithful SCA1 KI mouse model. Temporal expression profiles of the candidate genes revealed that the up-regulation of genes associated with microglial activation was initiated before PC degeneration and was augmented as the disease progressed. Histological analysis of the MPI 118Q/118Q cerebellum showed the predominance of M1-like pro-inflammatory microglia and it was concomitant with elevated expression levels of tumor necrosis factor, interleukin-6, Toll-like receptor (TLR) 2 and 7. Genetic ablation of MyD88, a major adaptor protein conveying TLR signaling, altered expression patterns of M1/M2 microglial phenotypic markers in the MPI 118Q/118Q cerebellum. More importantly, it ameliorated PC loss and partially rescued motor impairments in the early disease phase. These results suggest that early neuroinflammatory response may play an important role in the pathogenesis of SCA6 and its modulation could pave the way for slowing the disease progression during the early stage of the disease.

Description: Motivation: Stem cell differentiation is largely guided by master transcriptional regulators, but it also depends on the expression of other types of genes, such as cell cycle genes, signaling genes, metabolic genes, trafficking genes, etc. Traditional approaches to understanding gene expression patterns across multiple conditions, such as principal components analysis or K-means clustering, can group cell types based on gene expression, but they do so without knowledge of the differentiation hierarchy. Hierarchical clustering can organize cell types into a tree, but in general this tree is different from the differentiation hierarchy itself. Methods: Given the differentiation hierarchy and gene expression data at each node, we construct a weighted Euclidean distance metric such that the minimum spanning tree with respect to that metric is precisely the given differentiation hierarchy. We provide a set of linear constraints that are provably sufficient for the desired construction and a linear programming approach to identify sparse sets of weights, effectively identifying genes that are most relevant for discriminating different parts of the tree. Results: We apply our method to microarray gene expression data describing 38 cell types in the hematopoiesis hierarchy, constructing a weighted Euclidean metric that uses just 175 genes. However, we find that there are many alternative sets of weights that satisfy the linear constraints. Thus, in the style of random-forest training, we also construct metrics based on random subsets of the genes and compare them to the metric of 175 genes. We then report on the selected genes and their biological functions. Our approach offers a new way to identify genes that may have important roles in stem cell differentiation. Contact: tperkins@ohri.ca Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Principal component analysis (PCA) is a basic tool often used in bioinformatics for visualization and dimension reduction. However, it is known that PCA may not consistently estimate the true direction of maximal variability in high-dimensional, low sample size settings, which are typical for molecular data. Assuming that the underlying signal is sparse, i.e. that only a fraction of features contribute to a principal component (PC), this estimation consistency can be retained. Most existing sparse PCA methods use L1-penalization, i.e. the lasso , to perform feature selection. But, the lasso is known to lack variable selection consistency in high dimensions and therefore a subsequent interpretation of selected features can give misleading results. Results: We present S4VDPCA, a sparse PCA method that incorporates a subsampling approach, namely stability selection. S4VDPCA can consistently select the truly relevant variables contributing to a sparse PC while also consistently estimate the direction of maximal variability. The performance of the S4VDPCA is assessed in a simulation study and compared to other PCA approaches, as well as to a hypothetical oracle PCA that ‘knows’ the truly relevant features in advance and thus finds optimal, unbiased sparse PCs. S4VDPCA is computationally efficient and performs best in simulations regarding parameter estimation consistency and feature selection consistency. Furthermore, S4VDPCA is applied to a publicly available gene expression data set of medulloblastoma brain tumors. Features contributing to the first two estimated sparse PCs represent genes significantly over-represented in pathways typically deregulated between molecular subgroups of medulloblastoma. Availability and implementation: Software is available at https://github.com/mwsill/s4vdpca . Contact: m.sill@dkfz.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Glycans play critical roles in many biological processes, and their structural diversity is key for specific protein-glycan recognition. Comparative structural studies of biological molecules provide useful insight into their biological relationships. However, most computational tools are designed for protein structure, and despite their importance, there is no currently available tool for comparing glycan structures in a sequence order- and size-independent manner. Results: A novel method, GS-align, is developed for glycan structure alignment and similarity measurement. GS-align generates possible alignments between two glycan structures through iterative maximum clique search and fragment superposition. The optimal alignment is then determined by the maximum structural similarity score, GS-score, which is size-independent. Benchmark tests against the Protein Data Bank (PDB) N -linked glycan library and PDB homologous/non-homologous N -glycoprotein sets indicate that GS-align is a robust computational tool to align glycan structures and quantify their structural similarity. GS-align is also applied to template-based glycan structure prediction and monosaccharide substitution matrix generation to illustrate its utility. Availability and implementation: http://www.glycanstructure.org/gsalign . Contact: wonpil@ku.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Impedance-based technologies are advancing methods for measuring proliferation of adherent cell cultures non-invasively and in real time. The analysis of the resulting data has so far been hampered by inappropriate computational methods and the lack of systematic data to evaluate the characteristics of the assay. Results: We used a commercially available system for impedance-based growth measurement (xCELLigence) and compared the reported cell index with data from microscopy. We found that the measured signal correlates linearly with the cell number throughout the time of an experiment with sufficient accuracy in subconfluent cell cultures. The resulting growth curves for various colon cancer cells could be well described with the empirical Richards growth model, which allows for extracting quantitative parameters (such as characteristic cycle times). We found that frequently used readouts like the cell index at a specific time or the area under the growth curve cannot be used to faithfully characterize growth inhibition. We propose to calculate the average growth rate of selected time intervals to accurately estimate time-dependent IC50 values of drugs from growth curves. Contact: nils.bluethgen@charite.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Spliceosomal introns are a hallmark of eukaryotic genes that are hypothesized to play important roles in genome evolution but have poorly understood origins. Although most introns lack sequence homology to each other, new families of spliceosomal introns that are repeated hundreds of times in individual genomes have recently been discovered in a few organisms. The prevalence and conservation of these introner elements (IEs) or introner-like elements in other taxa, as well as their evolutionary relationships to regular spliceosomal introns, are still unknown. Here, we systematically investigate introns in the widespread marine green alga Micromonas and report new families of IEs, numerous intron presence–absence polymorphisms, and potential intron insertion hot-spots. The new families enabled identification of conserved IE secondary structure features and establishment of a novel general model for repetitive intron proliferation across genomes. Despite shared secondary structure, the IE families from each Micromonas lineage bear no obvious sequence similarity to those in the other lineages, suggesting that their appearance is intimately linked with the process of speciation. Two of the new IE families come from an Arctic culture ( Micromonas Clade E2) isolated from a polar region where abundance of this alga is increasing due to climate induced changes. The same two families were detected in metagenomic data from Antarctica—a system where Micromonas has never before been reported. Strikingly high identity between the Arctic isolate and Antarctic coding sequences that flank the IEs suggests connectivity between populations in the two polar systems that we postulate occurs through deep-sea currents. Recovery of Clade E2 sequences in North Atlantic Deep Waters beneath the Gulf Stream supports this hypothesis. Our research illuminates the dynamic relationships between an unusual class of repetitive introns, genome evolution, speciation, and global distribution of this sentinel marine alga.

Description: Cellular Ca 2+ homeostasis is tightly regulated and is pivotal to life. Inositol 1,4,5-trisphosphate receptors (IP 3 Rs) and ryanodine receptors (RyRs) are the major ion channels that regulate Ca 2+ release from intracellular stores. Although these channels have been extensively investigated in multicellular organisms, an appreciation of their evolution and the biology of orthologs in unicellular organisms is largely lacking. Extensive phylogenetic analyses reveal that the IP 3 R gene superfamily is ancient and diverged into two subfamilies, IP 3 R-A and IP 3 R-B/RyR, at the dawn of Opisthokonta. IP 3 R-B/RyR further diversified into IP 3 R-B and RyR at the stem of Filozoa. Subsequent evolution and speciation of Holozoa is associated with duplication of IP 3 R-A and RyR genes, and loss of IP 3 R-B in the vertebrate lineages. To gain insight into the properties of IP 3 R important for the challenges of multicellularity, the IP 3 R-A and IP 3 R-B family orthologs were cloned from Capsaspora owczarzaki, a close unicellular relative to Metazoa (designated as CO.IP 3 R-A and CO.IP 3 R-B). Both proteins were targeted to the endoplasmic reticulum. However, CO.IP 3 R-A, but strikingly not CO.IP 3 R-B, bound IP 3 , exhibited robust Ca 2+ release activity and associated with mammalian IP 3 Rs. These data indicate strongly that CO.IP 3 R-A as an exemplar of ancestral IP 3 R-A orthologs forms bona fide IP 3 -gated channels. Notably, however, CO.IP 3 R-A appears not to be regulated by Ca 2+ , ATP or Protein kinase A-phosphorylation. Collectively, our findings explore the origin, conservation, and diversification of IP 3 R gene families and provide insight into the functionality of ancestral IP 3 Rs and the added specialization of these proteins in Metazoa.

Description: Marriage rules, the community prescriptions that dictate who an individual can or cannot marry, are extremely diverse and universally present in traditional societies. A major focus of research in the early decades of modern anthropology, marriage rules impose social and economic forces that help structure societies and forge connections between them. However, in those early anthropological studies, the biological benefits or disadvantages of marriage rules could not be determined. We revisit this question by applying a novel simulation framework and genome-wide data to explore the effects of Asymmetric Prescriptive Alliance, an elaborate set of marriage rules that has been a focus of research for many anthropologists. Simulations show that strict adherence to these marriage rules reduces genetic diversity on the autosomes, X chromosome and mitochondrial DNA, but relaxed compliance produces genetic diversity similar to random mating. Genome-wide data from the Indonesian community of Rindi, one of the early study populations for Asymmetric Prescriptive Alliance, are more consistent with relaxed compliance than strict adherence. We therefore suggest that, in practice, marriage rules are treated with sufficient flexibility to allow social connectivity without significant degradation of biological diversity.

Description: The environment has profound effects on the expression of many traits and reaction norms describe the expression dynamics of a trait across a broad range of environmental conditions. Here, we analyze gene expression in Drosophila melanogaster across four different developmental temperatures (13–29 °C). Gene expression is highly plastic with 83.3% of the genes being differentially expressed. We distinguished three components of plasticity: 1) Dynamics of gene expression intensity (sum of change), 2) direction of change, and 3) curvature of the reaction norm (linear vs. quadratic). Studying their regulatory architecture we found that all three plasticity components were most strongly affected by the number of different transcription factors (TFs) binding to the target gene. More TFs were found in genes with less expression changes across temperatures. Although the effect of microRNAs was weaker, we consistently noted a trend in the opposite direction. The most plastic genes were regulated by fewer TFs and more microRNAs than less plastic genes. Different patterns of plasticity were also reflected by their functional characterization based on gene ontology. Our results suggest that reaction norms provide an important key to understand the functional requirements of natural populations exposed to variable environmental conditions.

Description: Recent advances in paleogenomic technologies have enabled an increasingly detailed understanding of the evolutionary relationships of now-extinct mammalian taxa. However, a number of enigmatic Quaternary species have never been characterized with molecular data, often because available fossils are rare or are found in environments that are not optimal for DNA preservation. Here, we analyze paleogenomic data extracted from bones attributed to the late Pleistocene western camel, Camelops cf. hesternus, a species that was distributed across central and western North America until its extinction approximately 13,000 years ago. Despite a modal sequence length of only around 35 base pairs, we reconstructed high-coverage complete mitochondrial genomes and low-coverage partial nuclear genomes for each specimen. We find that Camelops is sister to African and Asian bactrian and dromedary camels, to the exclusion of South American camelids (llamas, guanacos, alpacas, and vicuñas). These results contradict previous morphology-based phylogenetic models for Camelops , which suggest instead a closer relationship between Camelops and the South American camelids. The molecular data imply a Late Miocene divergence of the Camelops clade from lineages that separately gave rise to the extant camels of Eurasia. Our results demonstrate the increasing capacity of modern paleogenomic methods to resolve evolutionary relationships among distantly related lineages.

Description: Recent developments in the analysis of amino acid covariation are leading to breakthroughs in protein structure prediction, protein design, and prediction of the interactome. It is assumed that observed patterns of covariation are caused by molecular coevolution, where substitutions at one site affect the evolutionary forces acting at neighboring sites. Our theoretical and empirical results cast doubt on this assumption. We demonstrate that the strongest coevolutionary signal is a decrease in evolutionary rate and that unfeasibly long times are required to produce coordinated substitutions. We find that covarying substitutions are mostly found on different branches of the phylogenetic tree, indicating that they are independent events that may or may not be attributable to coevolution. These observations undermine the hypothesis that molecular coevolution is the primary cause of the covariation signal. In contrast, we find that the pairs of residues with the strongest covariation signal tend to have low evolutionary rates, and that it is this low rate that gives rise to the covariation signal. Slowly evolving residue pairs are disproportionately located in the protein’s core, which explains covariation methods’ ability to detect pairs of residues that are close in three dimensions. These observations lead us to propose the "coevolution paradox": The strength of coevolution required to cause coordinated changes means the evolutionary rate is so low that such changes are highly unlikely to occur. As modern covariation methods may lead to breakthroughs in structural genomics, it is critical to recognize their biases and limitations.

Description: We present a modified GPU (graphics processing unit) version of MrBayes, called ta(MC) 3 (GPU MrBayes V3.1), for Bayesian phylogenetic inference on protein data sets. Our main contributions are 1) utilizing 64-bit variables, thereby enabling ta(MC) 3 to process larger data sets than MrBayes; and 2) to use Kahan summation to improve accuracy, convergence rates, and consequently runtime. Versus the current fastest software, we achieve a speedup of up to around 2.5 (and up to around 90 vs. serial MrBayes), and more on multi-GPU hardware. GPU MrBayes V3.1 is available from http://sourceforge.net/projects/mrbayes-gpu/ .

Description: Understanding the genetic and molecular bases of the ability to distinguish self from nonself (allorecognition) and mechanisms underlying evolution of allorecognition systems is an important endeavor for understanding cases where it becomes dysfunctional, such as in autoimmune disorders. In filamentous fungi, allorecognition can result in vegetative or heterokaryon incompatibility, which is a type of programmed cell death that occurs following fusion of genetically different cells. Allorecognition is genetically controlled by het loci, with coexpression of any combination of incompatible alleles triggering vegetative incompatibility. Herein, we identified, characterized, and inferred the evolutionary history of candidate het loci in the filamentous fungus Neurospora crassa . As characterized het loci encode proteins carrying an HET domain, we annotated HET domain genes in 25 isolates from a natural population along with the N. crassa reference genome using resequencing data. Because allorecognition systems can be affected by frequency-dependent selection favoring rare alleles (i.e., balancing selection), we mined resequencing data for HET domain loci whose alleles displayed elevated levels of variability, excess of intermediate frequency alleles, and deep gene genealogies. From these analyses, 34 HET domain loci were identified as likely to be under balancing selection. Using transformation, incompatibility assays and genetic analyses, we determined that one of these candidates functioned as a het locus ( het-e ). The het-e locus has three divergent allelic groups that showed signatures of positive selection, intra- and intergroup recombination, and trans-species polymorphism. Our findings represent a compelling case of balancing selection functioning on multiple alleles across multiple loci potentially involved in allorecognition.

Description: Scoring the impact of noncoding variation on the function of cis -regulatory regions, on their chromatin state, and on the qualitative and quantitative expression levels of target genes is a fundamental problem in evolutionary genomics. A particular challenge is how to model the divergence of quantitative traits and to identify relationships between the changes across the different levels of the genome, the chromatin activity landscape, and the transcriptome. Here, we examine the use of the Ornstein–Uhlenbeck (OU) model to infer selection at the level of predicted cis -regulatory modules (CRMs), and link these with changes in transcription factor binding and chromatin activity. Using publicly available cross-species ChIP-Seq and STARR-Seq data we show how OU can be applied genome-wide to identify candidate transcription factors for which binding site and CRM turnover is correlated with changes in regulatory activity. Next, we profile open chromatin in the developing eye across three Drosophila species. We identify the recognition motifs of the chromatin remodelers, Trithorax-like and Grainyhead as mostly correlating with species-specific changes in open chromatin. In conclusion, we show in this study that CRM scores can be used as quantitative traits and that motif discovery approaches can be extended towards more complex models of divergence.

Description: How populations that inhabit the same geographical area become genetically differentiated is not clear. To investigate this, we characterized phenotypic and genetic differences between two populations of Saccharomyces cerevisiae that in some cases inhabit the same environment but show relatively little gene flow. We profiled stress sensitivity in a group of vineyard isolates and a group of oak-soil strains and found several niche-related phenotypes that distinguish the populations. We performed bulk-segregant mapping on two of the distinguishing traits: The vineyard-specific ability to grow in grape juice and oak-specific tolerance to the cell wall damaging drug Congo red. To implicate causal genes, we also performed a chemical genomic screen in the lab-strain deletion collection and identified many important genes that fell under quantitative trait loci peaks. One gene important for growth in grape juice and identified by both the mapping and the screen was SSU1 , a sulfite-nitrite pump implicated in wine fermentations. The beneficial allele is generated by a known translocation that we reasoned may also serve as a genetic barrier. We found that the translocation is prevalent in vineyard strains, but absent in oak strains, and presents a postzygotic barrier to spore viability. Furthermore, the translocation was associated with a fitness cost to the rapid growth rate seen in oak-soil strains. Our results reveal the translocation as a dual-function locus that enforces ecological differentiation while producing a genetic barrier to gene flow in these sympatric populations.

Description: Species tree reconstruction has been a subject of substantial research due to its central role across biology and medicine. A species tree is often reconstructed using a set of gene trees or by directly using sequence data. In either of these cases, one of the main confounding phenomena is the discordance between a species tree and a gene tree due to evolutionary events such as duplications and losses. Probabilistic methods can resolve the discordance by coestimating gene trees and the species tree but this approach poses a scalability problem for larger data sets. We present MixTreEM-DLRS: A two-phase approach for reconstructing a species tree in the presence of gene duplications and losses. In the first phase, MixTreEM, a novel structural expectation maximization algorithm based on a mixture model is used to reconstruct a set of candidate species trees, given sequence data for monocopy gene families from the genomes under study. In the second phase, PrIME-DLRS, a method based on the DLRS model (Åkerborg O, Sennblad B, Arvestad L, Lagergren J. 2009. Simultaneous Bayesian gene tree reconstruction and reconciliation analysis. Proc Natl Acad Sci U S A. 106(14):5714–5719), is used for selecting the best species tree. PrIME-DLRS can handle multicopy gene families since DLRS, apart from modeling sequence evolution, models gene duplication and loss using a gene evolution model (Arvestad L, Lagergren J, Sennblad B. 2009. The gene evolution model and computing its associated probabilities. J ACM. 56(2):1–44). We evaluate MixTreEM-DLRS using synthetic and biological data, and compare its performance with a recent genome-scale species tree reconstruction method PHYLDOG ( Boussau B, Szöllősi GJ, Duret L, Gouy M, Tannier E, Daubin V. 2013 . Genome-scale coestimation of species and gene trees. Genome Res. 23(2):323–330) as well as with a fast parsimony-based algorithm Duptree (Wehe A, Bansal MS, Burleigh JG, Eulenstein O. 2008. Duptree: a program for large-scale phylogenetic analyses using gene tree parsimony. Bioinformatics 24(13):1540–1541). Our method is competitive with PHYLDOG in terms of accuracy and runs significantly faster and our method outperforms Duptree in accuracy. The analysis constituted by MixTreEM without DLRS may also be used for selecting the target species tree, yielding a fast and yet accurate algorithm for larger data sets. MixTreEM is freely available at http://prime.scilifelab.se/mixtreem/ .

Description: Contrasting with birds and mammals, poikilothermic vertebrates often have homomorphic sex chromosomes, possibly resulting from high rates of sex-chromosome turnovers and/or occasional X–Y recombination. Strong support for the latter mechanism was provided by four species of European tree frogs, which inherited from a common ancestor (~5 Ma) the same pair of homomorphic sex chromosomes (linkage group 1, LG1), harboring the candidate sex-determining gene Dmrt1. Here, we test sex linkage of LG1 across six additional species of the Eurasian Hyla radiation with divergence times ranging from 6 to 40 Ma. LG1 turns out to be sex linked in six of nine resolved cases. Mapping the patterns of sex linkage to the Hyla phylogeny reveals several transitions in sex-determination systems within the last 10 My, including one switch in heterogamety. Phylogenetic trees of DNA sequences along LG1 are consistent with occasional X–Y recombination in all species where LG1 is sex linked. These patterns argue against one of the main potential causes for turnovers, namely the accumulation of deleterious mutations on nonrecombining chromosomes. Sibship analyses show that LG1 recombination is strongly reduced in males from most species investigated, including some in which it is autosomal. Intrinsically low male recombination might facilitate the evolution of male heterogamety, and the presence of important genes from the sex-determination cascade might predispose LG1 to become a sex chromosome.

Description: It has been hypothesised that positive associations between age and levels of oxidative stress-generated damage to DNA may be related to an age-dependent decline in DNA repair activity. The objective of this study was to investigate the association between age and repair activity of oxidatively damaged DNA in peripheral blood mononuclear cells (PBMCs). We isolated PBMCs from subjects aged 18–83 years, as part of a health survey of the Danish population that focussed on lifestyle factors. The level of DNA repair activity was measured as incisions on potassium bromate-damaged DNA by the comet assay. There was an inverse association between age and DNA repair activity with a 0.65% decline in activity per year from age 18 to 83 (95% confidence interval: 0.16–1.14% per year). Univariate regression analysis also indicated inverse associations between DNA repair activity and waist-hip ratio ( P 〈 0.05) and plasma concentrations of glycosylated hemoglobin ( P = 0.07). However, multivariate regression analysis only showed an inverse association between age and DNA repair activity ( P 〈 0.05), indicating that the decline in repair activity was not mediated by metabolic risk factors. In summary, the results show an inverse association between age and DNA repair activity of oxidatively damaged DNA.

Description: Exposure to traffic-related particulate matter (PM) has been associated with increased risk of lung disease, cancer and cardiovascular disease especially in elderly and overweight subjects. The proposed mechanisms involve intracellular production of reactive oxygen species (ROS), inflammation and oxidation-induced DNA damage studied mainly in young normal-weight subjects. We performed a controlled cross-over, randomised, single-blinded, repeated-measure study where 60 healthy subjects (25 males and 35 females) with age 55–83 years and body mass index above 25kg/m 2 were exposed for 5h to either particle-filtered or sham-filtered air from a busy street with number of concentrations and PM 2.5 levels of 1800/cm 3 versus 23 000/cm 3 and 3 µg/m 3 versus 24 µg/m 3 , respectively. Peripheral blood mononuclear cells (PBMCs) were collected and assayed for production of ROS with and without ex vivo exposure to nanosized carbon black as well as expression of genes related to inflammation ( chemokine (C-C motif) ligand 2 , interleukin-8 and tumour necrosis factor ), oxidative stress response ( heme oxygenase (decycling)-1 ) and DNA repair ( oxoguanine DNA glycosylase ). DNA strand breaks and oxidised purines were assayed by the alkaline comet assay. No statistically significant differences were found for any biomarker immediately after exposure to PM from urban street air although strand breaks and oxidised purines combined were significantly associated with the particle number concentration during exposure. In conclusion, 5h of controlled exposure to PM from urban traffic did not change the gene expression related to inflammation, oxidative stress or DNA repair, ROS production or oxidatively damaged DNA in PBMCs from elderly overweight human subjects.

Description: Ionising radiation causes free radical–mediated damage in cellular DNA. This damage is manifested as chromosomal aberrations and micronuclei (MN) in proliferating cells. Sesamol, present in sesame seeds, has the potential to scavenge free radicals; therefore, it can reduce radiation-induced cytogenetic damage in cells. The aim of this study was to investigate the radioprotective potential of sesamol in bone marrow cells of mice and related haematopoietic system against radiation-induced genotoxicity. A comparative study with melatonin was designed for assessing the radioprotective potential of sesamol. C57BL/6 mice were administered intraperitoneally with either sesamol or melatonin (10 and 20mg/kg body weight) 30min prior to 2-Gy whole-body irradiation (WBI) and sacrificed after 24h. Total chromosomal aberrations (TCA), MN and cell cycle analyses were performed using bone marrow cells. The comet assay was performed on bone marrow cells, splenocytes and lymphocytes. Blood was drawn to study haematological parameters. Prophylactic doses of sesamol (10 and 20mg/kg) in irradiated mice reduced TCA and micronucleated polychromatic erythrocyte frequency in bone marrow cells by 57% and 50%, respectively, in comparison with radiation-only groups. Sesamol-reduced radiation-induced apoptosis and facilitated cell proliferation. In the comet assay, sesamol (20mg/kg) treatment reduced radiation-induced comets (% DNA in tail) compared with radiation only ( P 〈 0.05). Sesamol also increased granulocyte populations in peripheral blood similar to melatonin. Overall, the radioprotective efficacy of sesamol was found to be similar to that of melatonin. Sesamol treatment also showed recovery of relative spleen weight at 24h of WBI. The results strongly suggest the radioprotective efficacy of sesamol in the haematopoietic system of mice.

Description: Individualized treatment rules recommend treatments on the basis of individual patient characteristics. A high-quality treatment rule can produce better patient outcomes, lower costs and less treatment burden. If a treatment rule learned from data is to be used to inform clinical practice or provide scientific insight, it is crucial that it be interpretable; clinicians may be unwilling to implement models they do not understand, and black-box models may not be useful for guiding future research. The canonical example of an interpretable prediction model is a decision tree. We propose a method for estimating an optimal individualized treatment rule within the class of rules that are representable as decision trees. The class of rules we consider is interpretable but expressive. A novel feature of this problem is that the learning task is unsupervised, as the optimal treatment for each patient is unknown and must be estimated. The proposed method applies to both categorical and continuous treatments and produces favourable marginal mean outcomes in simulation experiments. We illustrate it using data from a study of major depressive disorder.

Description: Sufficient dimension reduction in regression aims to reduce the predictor dimension by replacing the original predictors with some set of linear combinations of them without loss of information. Numerous dimension reduction methods have been developed based on this paradigm. However, little effort has been devoted to diagnostic studies within the context of dimension reduction. In this paper we introduce methods to check goodness-of-fit for a given dimension reduction subspace. The key idea is to extend the so-called distance correlation to measure the conditional dependence relationship between the covariates and the response given a reduction subspace. Our methods require minimal assumptions, which are usually much less restrictive than the conditions needed to justify the original methods. Asymptotic properties of the test statistic are studied. Numerical examples demonstrate the effectiveness of the proposed approach.

Description: We propose a geometric framework to assess sensitivity of Bayesian procedures to modelling assumptions based on the nonparametric Fisher–Rao metric. While the framework is general, the focus of this article is on assessing local and global robustness in Bayesian procedures with respect to perturbations of the likelihood and prior, and on the identification of influential observations. The approach is based on a square-root representation of densities, which enables analytical computation of geodesic paths and distances, facilitating the definition of naturally calibrated local and global discrepancy measures. An important feature of our approach is the definition of a geometric $\epsilon$ -contamination class of sampling distributions and priors via intrinsic analysis on the space of probability density functions. We demonstrate the applicability of our framework to generalized mixed-effects models and to directional and shape data.

Description: With the discovery of an increasing number of causal genes for complex human disorders, it is crucial to assess the genetic risk of disease onset for individuals who are carriers of these causal mutations and to compare the distribution of the age-at-onset for such individuals with the distribution for noncarriers. In many genetic epidemiological studies that aim to estimate causal gene effect on disease, the age-at-onset of disease is subject to censoring. In addition, the mutation carrier or noncarrier status of some individuals may be unknown, due to the high cost of in-person ascertainment by collecting DNA samples or because of the death of older individuals. Instead, the probability of such individuals’ mutation status can be obtained from various other sources. When mutation status is missing, the available data take the form of censored mixture data. Recently, various methods have been proposed for risk estimation using such data, but none is efficient for estimating a nonparametric distribution. We propose a fully efficient sieve maximum likelihood estimation method, in which we estimate the logarithm of the hazard ratio between genetic mutation groups using B-splines, while applying nonparametric maximum likelihood estimation to the reference baseline hazard function. Our estimator can be calculated via an expectation-maximization algorithm which is much faster than existing methods. We show that our estimator is consistent and semiparametrically efficient and establish its asymptotic distribution. Simulation studies demonstrate the superior performance of the proposed method, which is used to estimate the distribution of the age-at-onset of Parkinson's disease for carriers of mutations in the leucine-rich repeat kinase 2, LRRK2, gene.

Description: Smoothing splines provide flexible nonparametric regression estimators. However, the high computational cost of smoothing splines for large datasets has hindered their wide application. In this article, we develop a new method, named adaptive basis sampling, for efficient computation of smoothing splines in super-large samples. Except for the univariate case where the Reinsch algorithm is applicable, a smoothing spline for a regression problem with sample size n can be expressed as a linear combination of n basis functions and its computational complexity is generally O ( n 3 ). We achieve a more scalable computation in the multivariate case by evaluating the smoothing spline using a smaller set of basis functions, obtained by an adaptive sampling scheme that uses values of the response variable. Our asymptotic analysis shows that smoothing splines computed via adaptive basis sampling converge to the true function at the same rate as full basis smoothing splines. Using simulation studies and a large-scale deep earth core-mantle boundary imaging study, we show that the proposed method outperforms a sampling method that does not use the values of response variables.

Description: We propose tests for nonlinear serial dependence in time series under the null hypothesis of general linear dependence, in contrast to the more widely studied null hypothesis of independence. The approach is based on combining an entropy dependence metric, which possesses many desirable properties and is used as a test statistic, with a suitable extension of surrogate data methods, a class of Monte Carlo distribution-free tests for nonlinearity, and a smoothed sieve bootstrap scheme. We show how, in the same way as the autocorrelation function is used for linear models, our tests can in principle be employed to detect the lags at which a significant nonlinear relationship is present. We prove the asymptotic validity of the proposed procedures and the corresponding inferences. The small-sample performance of the tests in terms of power and size is assessed through a simulation study. Applications to real datasets of different kinds are also presented.

Description: Contamination caused by outliers is inevitable in data analysis, and robust statistical methods are often needed. In this paper we develop a new approach for robust data analysis on the basis of scoring rules. A scoring rule is a discrepancy measure to assess the quality of probabilistic forecasts. We propose a simple method of estimating not only parameters in the statistical model but also the contamination ratio, i.e., the ratio of outliers. The outliers are detected based on the estimated contamination ratio. For this purpose, we use scoring rules with extended statistical models called unnormalized models. Regression problems are also considered. We study complex heterogeneous contamination wherein the contamination ratio in a response variable may depend on covariate variables, and propose a simple method to estimate a robust regression function and expected contamination ratio. Simulation studies demonstrate the effectiveness of our method.

Description: The sample covariance matrix, which is well known to be highly nonrobust, plays a central role in many classical multivariate statistical methods. A popular way of making such multivariate methods more robust is to replace the sample covariance matrix with some robust scatter matrix. The aim of this paper is to point out that multivariate methods often require that certain properties of the covariance matrix hold also for the robust scatter matrix in order for the corresponding robust plug-in method to be a valid approach, but that not all scatter matrices possess the desired properties. Plug-in methods for independent components analysis, observational regression and graphical modelling are considered in more detail. For each case, it is shown that replacing the sample covariance matrix with a symmetrized robust scatter matrix yields a valid robust multivariate procedure.

Description: So-called big data are likely to have complex structure, in particular implying that estimates of precision obtained by applying standard statistical procedures are likely to be misleading, even if the point estimates of parameters themselves may be reasonably satisfactory. While this possibility is best explored in the context of each special case, here we outline a fairly general representation of the accretion of error in large systems and explore the possible implications for the estimation of regression coefficients. The discussion raises issues broadly parallel to the distinction between short-range and long-range dependence in time series theory.

Description: This paper extends the classical two-regime threshold autoregressive model by introducing hysteresis to its regime-switching structure, which leads to a new model: the hysteretic autoregressive model. The proposed model enjoys the piecewise linear structure of a threshold model but has a more flexible regime switching mechanism. A sufficient condition is given for geometric ergodicity. Conditional least squares estimation is discussed, and the asymptotic distributions of its estimators and information criteria for model selection are derived. Simulation results and an example support the model.

Description: This paper points out an error in Davidov and Iliopoulos's ( Biometrika 100 , 778–80) proof of convergence of an iterative algorithm for the proportional likelihood ratio model. It is shown that the iterative algorithm increases the likelihood in each iteration and converges under mild additional conditions when the odds ratio function is bounded.

Description: Motivation: The storage and transmission of high-throughput sequencing data consumes significant resources. As our capacity to produce such data continues to increase, this burden will only grow. One approach to reduce storage and transmission requirements is to compress this sequencing data. Results: We present a novel technique to boost the compression of sequencing that is based on the concept of bucketing similar reads so that they appear nearby in the file. We demonstrate that, by adopting a data-dependent bucketing scheme and employing a number of encoding ideas, we can achieve substantially better compression ratios than existing de novo sequence compression tools, including other bucketing and reordering schemes. Our method, Mince, achieves up to a 45% reduction in file sizes (28% on average) compared with existing state-of-the-art de novo compression schemes. Availability and implementation : Mince is written in C++11, is open source and has been made available under the GPLv3 license. It is available at http://www.cs.cmu.edu/~ckingsf/software/mince . Contact: carlk@cs.cmu.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : Current methods for motif discovery from chromatin immunoprecipitation followed by sequencing (ChIP-seq) data often identify non-targeted transcription factor (TF) motifs, and are even further limited when peak sequences are similar due to common ancestry rather than common binding factors. The latter aspect particularly affects a large number of proteins from the Cys 2 His 2 zinc finger (C2H2-ZF) class of TFs, as their binding sites are often dominated by endogenous retroelements that have highly similar sequences. Here, we present recognition code-assisted discovery of regulatory elements (RCADE) for motif discovery from C2H2-ZF ChIP-seq data. RCADE combines predictions from a DNA recognition code of C2H2-ZFs with ChIP-seq data to identify models that represent the genuine DNA binding preferences of C2H2-ZF proteins. We show that RCADE is able to identify generalizable binding models even from peaks that are exclusively located within the repeat regions of the genome, where state-of-the-art motif finding approaches largely fail. Availability and implementation: RCADE is available as a webserver and also for download at http://rcade.ccbr.utoronto.ca/ . Supplementary information: Supplementary data are available at Bioinformatics online. Contact: t.hughes@utoronto.ca

Description: Motivation: Phylogenetic estimates from published studies can be archived using general platforms like Dryad (Vision, 2010) or TreeBASE (Sanderson et al. , 1994). Such services fulfill a crucial role in ensuring transparency and reproducibility in phylogenetic research. However, digital tree data files often require some editing (e.g. rerooting) to improve the accuracy and reusability of the phylogenetic statements. Furthermore, establishing the mapping between tip labels used in a tree and taxa in a single common taxonomy dramatically improves the ability of other researchers to reuse phylogenetic estimates. As the process of curating a published phylogenetic estimate is not error-free, retaining a full record of the provenance of edits to a tree is crucial for openness, allowing editors to receive credit for their work and making errors introduced during curation easier to correct. Results : Here, we report the development of software infrastructure to support the open curation of phylogenetic data by the community of biologists. The backend of the system provides an interface for the standard database operations of creating, reading, updating and deleting records by making commits to a git repository. The record of the history of edits to a tree is preserved by git’s version control features. Hosting this data store on GitHub ( http://github.com/ ) provides open access to the data store using tools familiar to many developers. We have deployed a server running the ‘phylesystem-api’, which wraps the interactions with git and GitHub. The Open Tree of Life project has also developed and deployed a JavaScript application that uses the phylesystem-api and other web services to enable input and curation of published phylogenetic statements. Availability and implementation : Source code for the web service layer is available at https://github.com/OpenTreeOfLife/phylesystem-api . The data store can be cloned from: https://github.com/OpenTreeOfLife/phylesystem . A web application that uses the phylesystem web services is deployed at http://tree.opentreeoflife.org/curator . Code for that tool is available from https://github.com/OpenTreeOfLife/opentree . Contact : mtholder@gmail.com

Description: Motivation: Chromatin Immunoprecipitation followed by sequencing (ChIP-seq) detects genome-wide DNA–protein interactions and chromatin modifications, returning enriched regions (ERs), usually associated with a significance score. Moderately significant interactions can correspond to true, weak interactions, or to false positives; replicates of a ChIP-seq experiment can provide co-localised evidence to decide between the two cases. We designed a general methodological framework to rigorously combine the evidence of ERs in ChIP-seq replicates, with the option to set a significance threshold on the repeated evidence and a minimum number of samples bearing this evidence. Results : We applied our method to Myc transcription factor ChIP-seq datasets in K562 cells available in the ENCODE project. Using replicates, we could extend up to 3 times the ER number with respect to single-sample analysis with equivalent significance threshold. We validated the ‘rescued’ ERs by checking for the overlap with open chromatin regions and for the enrichment of the motif that Myc binds with strongest affinity; we compared our results with alternative methods (IDR and jMOSAiCS), obtaining more validated peaks than the former and less peaks than latter, but with a better validation. Availability and implementation : An implementation of the proposed method and its source code under GPLv3 license are freely available at http://www.bioinformatics.deib.polimi.it/MSPC/ and http://mspc.codeplex.com/ , respectively. Contact : marco.morelli@iit.it Supplementary information: Supplementary Material are available at Bioinformatics online.

Description: : We announce the release of kSNP3.0, a program for SNP identification and phylogenetic analysis without genome alignment or the requirement for reference genomes. kSNP3.0 is a significantly improved version of kSNP v2. Availability and implementation : kSNP3.0 is implemented as a package of stand-alone executables for Linux and Mac OS X under the open-source BSD license. The executable packages, source code and a full User Guide are freely available at https://sourceforge.net/projects/ksnp/files/ Contact: barryghall@gmail.com

Description: Motivation: We have created an R package named phylogeo that provides a set of geographic utilities for sequencing-based microbial ecology studies. Although the geographic location of samples is an important aspect of environmental microbiology, none of the major software packages used in processing microbiome data include utilities that allow users to map and explore the spatial dimension of their data. phylogeo solves this problem by providing a set of plotting and mapping functions that can be used to visualize the geographic distribution of samples, to look at the relatedness of microbiomes using ecological distance, and to map the geographic distribution of particular sequences. By extending the popular phyloseq package and using the same data structures and command formats, phylogeo allows users to easily map and explore the geographic dimensions of their data from the R programming language. Availability and Implementation: phylogeo is documented and freely available http://zachcp.github.io/phylogeo Contact : zcharlop@rockefeller.edu

Description: : Gener is a development module for programming chemical controllers based on DNA strand displacement. Gener is developed with the aim of providing a simple interface that minimizes the opportunities for programming errors: Gener allows the user to test the computations of the DNA programs based on a simple two-domain strand displacement algebra, the minimal available so far. The tool allows the user to perform stepwise computations with respect to the rules of the algebra as well as exhaustive search of the computation space with different options for exploration and visualization. Gener can be used in combination with existing tools, and in particular, its programs can be exported to Microsoft Research’s DSD tool as well as to LaTeX. Availability and implementation : Gener is available for download at the Cosbi website at http://www.cosbi.eu/research/prototypes/gener as a windows executable that can be run on Mac OS X and Linux by using Mono. Contact : ozan@cosbi.eu

Description: Motivation: Molecular dynamics simulations provide atomic insight into the physicochemical characteristics of lipid membranes and hence, a wide range of force field families capable of modelling various lipid types have been developed in recent years. To model membranes in a biologically realistic lipid composition, simulation systems containing multiple different lipids must be assembled. Results: We present a new web service called MemGen that is capable of setting up simulation systems of heterogenous lipid membranes. MemGen is not restricted to certain lipid force fields or lipid types, but instead builds membranes from uploaded structure files which may contain any kind of amphiphilic molecule. MemGen works with any all-atom or united-atom lipid representation. Availability and implementation: MemGen is freely available without registration at http://memgen.uni-goettingen.de . Contact: jhub@gwdg.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Environmental control of flowering allows plant reproduction to occur under optimal conditions and facilitates adaptation to different locations. At high latitude, flowering of many plants is controlled by seasonal changes in day length. The photoperiodic flowering pathway confers this response in the Brassicaceae, which colonized temperate latitudes after divergence from the Cleomaceae, their subtropical sister family. The CONSTANS (CO) transcription factor of Arabidopsis thaliana , a member of the Brassicaceae, is central to the photoperiodic flowering response and shows characteristic patterns of transcription required for day-length sensing. CO is believed to be widely conserved among flowering plants; however, we show that it arose after gene duplication at the root of the Brassicaceae followed by divergence of transcriptional regulation and protein function. CO has two close homologs, CONSTANS-LIKE1 ( COL1 ) and COL2 , which are related to CO by tandem duplication and whole-genome duplication, respectively. The single CO homolog present in the Cleomaceae shows transcriptional and functional features similar to those of COL1 and COL2 , suggesting that these were ancestral. We detect cis -regulatory and codon changes characteristic of CO and use transgenic assays to demonstrate their significance in the day-length-dependent activation of the CO target gene FLOWERING LOCUS T. Thus, the function of CO as a potent photoperiodic flowering switch evolved in the Brassicaceae after gene duplication. The origin of CO may have contributed to the range expansion of the Brassicaceae and suggests that in other families CO genes involved in photoperiodic flowering arose by convergent evolution.

Description: The high regulatory complexity of vertebrates has been related to two rounds of whole genome duplication (2R-WGD) that occurred before the divergence of the major vertebrate groups. Following these events, many developmental transcription factors (TFs) were retained in multiple copies and subsequently specialized in diverse functions, whereas others reverted to their singleton state. TFs are known to be generally rich in amino acid repeats or low-complexity regions (LCRs), such as polyalanine or polyglutamine runs, which can evolve rapidly and potentially influence the transcriptional activity of the protein. Here we test the hypothesis that LCRs have played a major role in the diversification of TF gene duplicates. We find that nearly half of the TF gene families originated during the 2R-WGD contains LCRs. The number of gene duplicates with LCRs is 155 out of 550 analyzed (28%), about twice as many as the number of single copy genes with LCRs (15 out of 115, 13%). In addition, duplicated TFs preferentially accumulate certain LCR types, the most prominent of which are alanine repeats. We experimentally test the role of alanine-rich LCRs in two different TF gene families, PHOX2A/PHOX2B and LHX2/LHX9. In both cases, the presence of the alanine-rich LCR in one of the copies (PHOX2B and LHX2) significantly increases the capacity of the TF to activate transcription. Taken together, the results provide strong evidence that LCRs are important driving forces of evolutionary change in duplicated genes.

Description: Studies of species with continental distributions continue to identify intraspecific lineages despite continuous habitat. Lineages may form due to isolation by distance, adaptation, divergence across barriers, or genetic drift following range expansion. We investigated lineage diversification and admixture within American black bears ( Ursus americanus ) across their range using 22 k single nucleotide polymorphisms and mitochondrial DNA sequences. We identified three subcontinental nuclear clusters which we further divided into nine geographic regions: Alaskan (Alaska-East), eastern (Central Interior Highlands, Great Lakes, Northeast, Southeast), and western (Alaska-West, West, Pacific Coast, Southwest). We estimated that the western cluster diverged 67 ka, before eastern and Alaskan divergence 31 ka; these divergence dates contrasted with those from the mitochondrial genome where clades A and B diverged 1.07 Ma, and clades A-east and A-west diverged 169 ka. We combined estimates of divergence timing with hindcast species distribution models to infer glacial refugia for the species in Beringia, Pacific Northwest, Southwest, and Southeast. Our results show a complex arrangement of admixture due to expansion out of multiple refugia. The delineation of the genomic population clusters was inconsistent with the ranges for 16 previously described subspecies. Ranges for U. a. pugnax and U. a. cinnamomum were concordant with admixed clusters, calling into question how to order taxa below the species level. Additionally, our finding that U. a. floridanus has not diverged from U. a. americanus also suggests that morphology and genetics should be reanalyzed to assess taxonomic designations relevant to the conservation management of the species.

Description: Deinococcus bacteria are extremely resistant to radiation, oxidation, and desiccation. Resilience to these factors has been suggested to be due to enhanced damage prevention and repair mechanisms, as well as highly efficient antioxidant protection systems. Here, using mutation-accumulation experiments, we find that the GC-rich Deinococcus radiodurans has an overall background genomic mutation rate similar to that of E. coli , but differs in mutation spectrum, with the A/T to G/C mutation rate (based on a total count of 88 A:T-〉G:C transitions and 82 A:T-〉C:G transversions) per site per generation higher than that in the other direction (based on a total count of 157 G:C-〉A:T transitions and 33 G:C-〉T:A transversions). We propose that this unique spectrum is shaped mainly by the abundant uracil DNA glycosylases reducing G:C-〉A:T transitions, adenine methylation elevating A:T-〉C:G transversions, and absence of cytosine methylation decreasing G:C-〉A:T transitions. As opposed to the greater than 100 x elevation of the mutation rate in MMR – (DNA Mismatch Repair deficient) strains of most other organisms, MMR – D. radiodurans only exhibits a 4-fold elevation, raising the possibility that other DNA repair mechanisms compensate for a relatively low-efficiency DNA MMR pathway. As D. radiodurans has plentiful insertion sequence (IS) elements in the genome and the activities of IS elements are rarely directly explored, we also estimated the insertion (transposition) rate of the IS elements to be 2.50 x 10 –3 per genome per generation in the wild-type strain; knocking out MMR did not elevate the IS element insertion rate in this organism.

Description: Because mating systems affect population genetics and ecology, they are expected to impact the molecular evolution of species. Self-fertilizing species experience reduced effective population size, recombination rates, and heterozygosity, which in turn should decrease the efficacy of natural selection, both adaptive and purifying, and the strength of meiotic drive processes such as GC-biased gene conversion. The empirical evidence is only partly congruent with these predictions, depending on the analyzed species, some, but not all, of the expected effects have been observed. One possible reason is that self-fertilization is an evolutionary dead-end, so that most current selfers recently evolved self-fertilization, and their genome has not yet been strongly impacted by selfing. Here, we investigate the molecular evolution of two groups of freshwater snails in which mating systems have likely been stable for several millions of years. Analyzing coding sequence polymorphism, divergence, and expression levels, we report a strongly reduced genetic diversity, decreased efficacy of purifying selection, slower rate of adaptive evolution, and weakened codon usage bias/GC-biased gene conversion in the selfer Galba compared with the outcrosser Physa , in full agreement with theoretical expectations. Our results demonstrate that self-fertilization, when effective in the long run, is a major driver of population genomic and molecular evolutionary processes. Despite the genomic effects of selfing, Galba truncatula seems to escape the demographic consequences of the genetic load. We suggest that the particular ecology of the species may buffer the negative consequences of selfing, shedding new light on the dead-end hypothesis.

Description: Choosing the number of components in a finite mixture model is a challenging task. In this article, we study the behaviour of information criteria for selecting the mixture order, based on either the observed likelihood or the complete likelihood including component labels. We propose a new observed likelihood criterion called aic mix , which is shown to be order consistent. We further show that when there is a nontrivial level of classification uncertainty in the true model, complete likelihood criteria asymptotically underestimate the true number of components. A simulation study illustrates the potentially poor finite-sample performance of complete likelihood criteria, while aic mix and the Bayesian information criterion perform strongly regardless of the level of classification uncertainty.

Description: Outlier detection is an integral component of statistical modelling and estimation. For high-dimensional data, classical methods based on the Mahalanobis distance are usually not applicable. We propose an outlier detection procedure that replaces the classical minimum covariance determinant estimator with a high-breakdown minimum diagonal product estimator. The cut-off value is obtained from the asymptotic distribution of the distance, which enables us to control the Type I error and deliver robust outlier detection. Simulation studies show that the proposed method behaves well for high-dimensional data.

Description: This paper adopts a nonparametric Bayesian approach to testing whether a function is monotone. Two new families of tests are constructed. The first uses constrained smoothing splines with a hierarchical stochastic-process prior that explicitly controls the prior probability of monotonicity. The second uses regression splines together with two proposals for the prior over the regression coefficients. Via simulation, the finite-sample performance of the tests is shown to improve upon existing frequentist and Bayesian methods. The asymptotic properties of the Bayes factor for comparing monotone versus nonmonotone regression functions in a Gaussian model are also studied. Our results significantly extend those currently available, which chiefly focus on determining the dimension of a parametric linear model.

Description: The paper develops hierarchical empirical Bayes and benchmarked hierarchical empirical Bayes estimators of positive small area means under multiplicative models. The usual benchmarking requirement is that the small area estimates, when aggregated, should equal the direct estimates for the larger geographical areas. However, while estimating positive small area parameters, the conventional squared error or weighted squared error loss subject to the usual benchmark constraint may not produce positive estimators, so it is necessary to seek other loss functions. We consider a multiplicative model for the original data for estimating positive small area means, and suggest a variant of the Kullback–Leibler divergence as a loss function. The prediction errors of the suggested hierarchical empirical Bayes estimators are investigated asymptotically, and their second-order unbiased estimators are provided. Bootstrapped estimators of these prediction errors for both hierarchical empirical Bayes and benchmarked hierarchical empirical Bayes estimators are also given. The performance of the suggested procedures is investigated through simulation as well as with an example.

Description: Odds ratios can be estimated in case-control studies using standard logistic regression, ignoring the outcome-dependent sampling. In this paper we discuss an analogous result for treatment effects on the treated in matched cohort studies. Specifically, in studies where a sample of treated subjects is observed along with a separate sample of possibly matched controls, we show that efficient and doubly robust estimators of effects on the treated are computationally equivalent to standard estimators, which ignore the matching and exposure-based sampling. This is not the case for general average effects. We also show that matched cohort studies are often more efficient than random sampling for estimating effects on the treated, and derive the optimal number of matches for a given set of matching variables. We illustrate our results via simulation and in a matched cohort study of the effect of hysterectomy on the risk of cardiovascular disease.

Description: Current status data occur in contexts including demographic studies and tumorigenicity experiments. In such cases, each subject is observed only once and the failure time of interest is either left- or right-censored (Kalbfleisch & Prentice, 2002). Many methods have been developed for the analysis of such data (Huang, 1996; Sun, 2006), most of which assume that the failure time and the observation time are independent completely or given covariates. In this paper, we present a sieve maximum likelihood approach for current status data when independence does not hold. A copula model and monotone I-splines are used and the asymptotic properties of the resulting estimators are established. In particular, the estimated regression parameters are shown to be semiparametrically efficient. An illustrative example is provided.

Description: Motivation: In practice, identifying and interpreting the functional impacts of the regulatory relationships between micro-RNA and messenger-RNA is non-trivial. The sheer scale of possible micro-RNA and messenger-RNA interactions can make the interpretation of results difficult. Results: We propose a supervised framework, pMim, built upon concepts of significance combination, for jointly ranking regulatory micro-RNA and their potential functional impacts with respect to a condition of interest. Here, pMim directly tests if a micro-RNA is differentially expressed and if its predicted targets, which lie in a common biological pathway, have changed in the opposite direction. We leverage the information within existing micro-RNA target and pathway databases to stabilize the estimation and annotation of micro-RNA regulation making our approach suitable for datasets with small sample sizes. In addition to outputting meaningful and interpretable results, we demonstrate in a variety of datasets that the micro-RNA identified by pMim, in comparison to simpler existing approaches, are also more concordant with what is described in the literature. Availability and implementation: This framework is implemented as an R function, pMim , in the package sydSeq available from http://www.ellispatrick.com/r-packages . Contact: jean.yang@sydney.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Cellular mRNA levels originate from the combined action of multiple regulatory processes, which can be recapitulated by the rates of pre-mRNA synthesis, pre-mRNA processing and mRNA degradation. Recent experimental and computational advances set the basis to study these intertwined levels of regulation. Nevertheless, software for the comprehensive quantification of RNA dynamics is still lacking. Results: INSPEcT is an R package for the integrative analysis of RNA- and 4sU-seq data to study the dynamics of transcriptional regulation. INSPEcT provides gene-level quantification of these rates, and a modeling framework to identify which of these regulatory processes are most likely to explain the observed mRNA and pre-mRNA concentrations. Software performance is tested on a synthetic dataset, instrumental to guide the choice of the modeling parameters and the experimental design. Availability and implementation: INSPEcT is submitted to Bioconductor and is currently available as Supplementary Additional File S1 . Contact: mattia.pelizzola@iit.it Supplementary Information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Experimentally determined gene regulatory networks can be enriched by computational inference from high-throughput expression profiles. However, the prediction of regulatory interactions is severely impaired by indirect and spurious effects, particularly for eukaryotes. Recently, published methods report improved predictions by exploiting the a priori known targets of a regulator (its local topology) in addition to expression profiles. Results: We find that methods exploiting known targets show an unexpectedly high rate of false discoveries. This leads to inflated performance estimates and the prediction of an excessive number of new interactions for regulators with many known targets. These issues are hidden from common evaluation and cross-validation setups, which is due to Simpson’s paradox. We suggest a confidence score recalibration method (CoRe) that reduces the false discovery rate and enables a reliable performance estimation. Conclusions: CoRe considerably improves the results of network inference methods that exploit known targets. Predictions then display the biological process specificity of regulators more correctly and enable the inference of accurate genome-wide regulatory networks in eukaryotes. For yeast, we propose a network with more than 22 000 confident interactions. We point out that machine learning approaches outside of the area of network inference may be affected as well. Availability and implementation: Results, executable code and networks are available via our website http://www.bio.ifi.lmu.de/forschung/CoRe . Contact: robert.kueffner@helmholtz-muenchen.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Stoichiometric and constraint-based methods of computational strain design have become an important tool for rational metabolic engineering. One of those relies on the concept of constrained minimal cut sets (cMCSs). However, as most other techniques, cMCSs may consider only reaction (or gene) knockouts to achieve a desired phenotype. Results : We generalize the cMCSs approach to constrained regulatory MCSs (cRegMCSs), where up/downregulation of reaction rates can be combined along with reaction deletions. We show that flux up/downregulations can virtually be treated as cuts allowing their direct integration into the algorithmic framework of cMCSs. Because of vastly enlarged search spaces in genome-scale networks, we developed strategies to (optionally) preselect suitable candidates for flux regulation and novel algorithmic techniques to further enhance efficiency and speed of cMCSs calculation. We illustrate the cRegMCSs approach by a simple example network and apply it then by identifying strain designs for ethanol production in a genome-scale metabolic model of Escherichia coli. The results clearly show that cRegMCSs combining reaction deletions and flux regulations provide a much larger number of suitable strain designs, many of which are significantly smaller relative to cMCSs involving only knockouts. Furthermore, with cRegMCSs, one may also enable the fine tuning of desired behaviours in a narrower range. The new cRegMCSs approach may thus accelerate the implementation of model-based strain designs for the bio-based production of fuels and chemicals. Availability and implementation: MATLAB code and the examples can be downloaded at http://www.mpi-magdeburg.mpg.de/projects/cna/etcdownloads.html . Contact : krishna.mahadevan@utoronto.ca or klamt@mpi-magdeburg.mpg.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Lipids are a large and diverse group of biological molecules with roles in membrane formation, energy storage and signaling. Cellular lipidomes may contain tens of thousands of structures, a staggering degree of complexity whose significance is not yet fully understood. High-throughput mass spectrometry-based platforms provide a means to study this complexity, but the interpretation of lipidomic data and its integration with prior knowledge of lipid biology suffers from a lack of appropriate tools to manage the data and extract knowledge from it. Results: To facilitate the description and exploration of lipidomic data and its integration with prior biological knowledge, we have developed a knowledge resource for lipids and their biology—SwissLipids. SwissLipids provides curated knowledge of lipid structures and metabolism which is used to generate an in silico library of feasible lipid structures. These are arranged in a hierarchical classification that links mass spectrometry analytical outputs to all possible lipid structures, metabolic reactions and enzymes. SwissLipids provides a reference namespace for lipidomic data publication, data exploration and hypothesis generation. The current version of SwissLipids includes over 244 000 known and theoretically possible lipid structures, over 800 proteins, and curated links to published knowledge from over 620 peer-reviewed publications. We are continually updating the SwissLipids hierarchy with new lipid categories and new expert curated knowledge. Availability: SwissLipids is freely available at http://www.swisslipids.org/ . Contact: alan.bridge@isb-sib.ch Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Both the quantitative real-time polymerase chain reaction (qPCR) and quantitative isothermal amplification (qIA) are standard methods for nucleic acid quantification. Numerous real-time read-out technologies have been developed. Despite the continuous interest in amplification-based techniques, there are only few tools for pre-processing of amplification data. However, a transparent tool for precise control of raw data is indispensable in several scenarios, for example, during the development of new instruments. Results: chipPCR is an R package for the pre-processing and quality analysis of raw data of amplification curves. The package takes advantage of R ’s S 4 object model and offers an extensible environment. chipPCR contains tools for raw data exploration: normalization, baselining, imputation of missing values, a powerful wrapper for amplification curve smoothing and a function to detect the start and end of an amplification curve. The capabilities of the software are enhanced by the implementation of algorithms unavailable in R , such as a 5-point stencil for derivative interpolation. Simulation tools, statistical tests, plots for data quality management, amplification efficiency/quantification cycle calculation, and datasets from qPCR and qIA experiments are part of the package. Core functionalities are integrated in GUIs (web-based and standalone shiny applications), thus streamlining analysis and report generation. Availability and implementation: http://cran.r-project.org/web/packages/chipPCR . Source code: https://github.com/michbur/chipPCR . Contact : stefan.roediger@b-tu.de Supplementary information: Supplementary data are available at Bioinformatics online.

Description: : A key to understanding RNA function is to uncover its complex 3D structure. Experimental methods used for determining RNA 3D structures are technologically challenging and laborious, which makes the development of computational prediction methods of substantial interest. Previously, we developed the iFoldRNA server that allows accurate prediction of short (〈50 nt) tertiary RNA structures starting from primary sequences. Here, we present a new version of the iFoldRNA server that permits the prediction of tertiary structure of RNAs as long as a few hundred nucleotides. This substantial increase in the server capacity is achieved by utilization of experimental information such as base-pairing and hydroxyl-radical probing. We demonstrate a significant benefit provided by integration of experimental data and computational methods. Availability and implementation: http://ifoldrna.dokhlab.org Contact: dokh@unc.eu

Description: : The ms-data-core-api is a free, open-source library for developing computational proteomics tools and pipelines. The Application Programming Interface, written in Java, enables rapid tool creation by providing a robust, pluggable programming interface and common data model. The data model is based on controlled vocabularies/ontologies and captures the whole range of data types included in common proteomics experimental workflows, going from spectra to peptide/protein identifications to quantitative results. The library contains readers for three of the most used Proteomics Standards Initiative standard file formats: mzML, mzIdentML, and mzTab. In addition to mzML, it also supports other common mass spectra data formats: dta, ms2, mgf, pkl, apl (text-based), mzXML and mzData (XML-based). Also, it can be used to read PRIDE XML, the original format used by the PRIDE database, one of the world-leading proteomics resources. Finally, we present a set of algorithms and tools whose implementation illustrates the simplicity of developing applications using the library. Availability and implementation: The software is freely available at https://github.com/PRIDE-Utilities/ms-data-core-api . Supplementary information: Supplementary data are available at Bioinformatics online Contact: juan@ebi.ac.uk

Description: : Scanning probe microscopy (SPM) is already a relevant tool in biological research at the nanoscale. We present ‘Flatten plus’, a recent and helpful implementation in the well-known WSxM free software package. ‘Flatten plus’ allows reducing low-frequency noise in SPM images in a semi-automated way preventing the appearance of typical artifacts associated with such filters. Availability and implementation: WSxM is a free software implemented in C++ supported on MS Windows, but it can also be run under Mac or Linux using emulators such as Wine or Parallels. WSxM can be downloaded from http://www.wsxmsolutions.com/ . Contact: ignacio.horcas@wsxmsolutions.com

Description: : Despite the plethora of methods available for the functional analysis of omics data, obtaining comprehensive-yet detailed understanding of the results remains challenging. This is mainly due to the lack of publicly available tools for the visualization of this type of information. Here we present an R package called GOplot, based on ggplot2, for enhanced graphical representation. Our package takes the output of any general enrichment analysis and generates plots at different levels of detail: from a general overview to identify the most enriched categories (bar plot, bubble plot) to a more detailed view displaying different types of information for molecules in a given set of categories (circle plot, chord plot, cluster plot). The package provides a deeper insight into omics data and allows scientists to generate insightful plots with only a few lines of code to easily communicate the findings. Availability and Implementation: The R package GOplot is available via CRAN-The Comprehensive R Archive Network: http://cran.r-project.org/web/packages/GOplot . The shiny web application of the Venn diagram can be found at: https://wwalter.shinyapps.io/Venn/ . A detailed manual of the package with sample figures can be found at https://wencke.github.io/ Contact: fscabo@cnic.es or mricote@cnic.es

Description: Motivation: Horizontal transfer of transposable (HTT) elements among eukaryotes was discovered in the mid-1980s. As then, 〉300 new cases have been described. New findings about HTT are revealing the evolutionary impact of this phenomenon on host genomes. In order to provide an up to date, interactive and expandable database for such events, we developed the HTT-DB database. Results: HTT-DB allows easy access to most of HTT cases reported along with rich information about each case. Moreover, it allows the user to generate tables and graphs based on searches using Transposable elements and/or host species classification and export them in several formats. Availability and implementation: This database is freely available on the web at http://lpa.saogabriel.unipampa.edu.br:8080/httdatabase . HTT-DB was developed based on Java and MySQL with all major browsers supported. Tools and software packages used are free for personal or non-profit projects. Contact: bdotto82@gmail.com or gabriel.wallau@gmail.com

Description: Historically, genome-wide and molecular characterization of the genus Listeria has concentrated on the important human pathogen Listeria monocytogenes and a small number of closely related species, together termed Listeria sensu strictu. More recently, a number of genome sequences for more basal, and nonpathogenic, members of the Listeria genus have become available, facilitating a wider perspective on the evolution of pathogenicity and genome level evolutionary dynamics within the entire genus (termed Listeria sensu lato). Here, we have sequenced the genomes of additional Listeria fleischmannii and Listeria newyorkensis isolates and explored the dynamics of genome evolution in Listeria sensu lato. Our analyses suggest that acquisition of genetic material through gene duplication and divergence as well as through lateral gene transfer (mostly from outside Listeria ) is widespread throughout the genus. Novel genetic material is apparently subject to rapid turnover. Multiple lines of evidence point to significant differences in evolutionary dynamics between the most basal Listeria subclade and all other congeners, including both sensu strictu and other sensu lato isolates. Strikingly, these differences are likely attributable to stochastic, population-level processes and contribute to observed variation in genome size across the genus. Notably, our analyses indicate that the common ancestor of Listeria sensu lato lacked flagella, which were acquired by lateral gene transfer by a common ancestor of Listeria grayi and Listeria sensu strictu, whereas a recently functionally characterized pathogenicity island, responsible for the capacity to produce cobalamin and utilize ethanolamine/propane-2-diol, was acquired in an ancestor of Listeria sensu strictu.

Description: Taeniid cestodes (including the human parasites Echinococcus spp. and Taenia solium ) have very few mobile genetic elements (MGEs) in their genome, despite lacking a canonical PIWI pathway. The MGEs of these parasites are virtually unexplored, and nothing is known about their expression and silencing. In this work, we report the discovery of a novel family of small nonautonomous long terminal repeat retrotransposons (also known as terminal-repeat retrotransposons in miniature, TRIMs) which we have named ta-TRIM (taeniid TRIM). ta-TRIM s are only the second family of TRIM elements discovered in animals, and are likely the result of convergent reductive evolution in different taxonomic groups. These elements originated at the base of the taeniid tree and have expanded during taeniid diversification, including after the divergence of closely related species such as Echinococcus multilocularis and Echinococcus granulosus . They are massively expressed in larval stages, from a small proportion of full-length copies and from isolated terminal repeats that show transcriptional read-through into downstream regions, generating novel noncoding RNAs and transcriptional fusions to coding genes. In E. multilocularis , ta-TRIM s are specifically expressed in the germinative cells (the somatic stem cells) during asexual reproduction of metacestode larvae. This would provide a developmental mechanism for insertion of ta-TRIM s into cells that will eventually generate the adult germ line. Future studies of active and inactive ta-TRIM elements could give the first clues on MGE silencing mechanisms in cestodes.

Description: Even though mitochondrial genomes, which characterize eukaryotic cells, were first discovered more than 50 years ago, mitochondrial genomics remains an important topic in molecular biology and genome sciences. The Phylum Alveolata comprises three major groups (ciliates, apicomplexans, and dinoflagellates), the mitochondrial genomes of which have diverged widely. Even though the gene content of dinoflagellate mitochondrial genomes is reportedly comparable to that of apicomplexans, the highly fragmented and rearranged genome structures of dinoflagellates have frustrated whole genomic analysis. Consequently, noncoding sequences and gene arrangements of dinoflagellate mitochondrial genomes have not been well characterized. Here we report that the continuous assembled genome (~326 kb) of the dinoflagellate, Symbiodinium minutum , is AT-rich (~64.3%) and that it contains three protein-coding genes. Based upon in silico analysis, the remaining 99% of the genome comprises transcriptomic noncoding sequences. RNA edited sites and unique, possible start and stop codons clarify conserved regions among dinoflagellates. Our massive transcriptome analysis shows that almost all regions of the genome are transcribed, including 27 possible fragmented ribosomal RNA genes and 12 uncharacterized small RNAs that are similar to mitochondrial RNA genes of the malarial parasite, Plasmodium falciparum . Gene map comparisons show that gene order is only slightly conserved between S. minutu m and P. falciparum . However, small RNAs and intergenic sequences share sequence similarities with P. falciparum , suggesting that the function of noncoding sequences has been preserved despite development of very different genome structures.

Description: Sialic acid acetyl esterase (SIAE) removes acetyl moieties from the hydroxyl groups in position 9 and 4 of sialic acid. Recently, a dispute has been opened on its association to autoimmunity. In order to get new insights on human SIAE biology and to clarify its seemingly contradictory molecular properties, we combined in silico characterization, phylogenetic analysis and homology modeling with cellular studies in COS7 cells. Genomic and phylogenetic analysis revealed that in most tissues only the "long" isoform, originally referred to lysosomal sialic acid esterase, is detected. Using the homology modeling approach, we predicted a model of SIAE 3D structure, which fulfills the topological features of SGNH-hydrolase family. In addition, the model and site-directed mutagenesis experiments allowed the definition of the residues involved in catalysis. SIAE transient expression revealed that the protein is glycosylated and is active in vitro as an esterase with a pH optimum corresponding to 8.4–8.5. Moreover, glycosylation influences the biological activity of the enzyme and is essential for release of SIAE into the culture medium. According to these findings, co-localization experiments demonstrated the presence of SIAE in membranous structures corresponding to endoplasmic reticulum and Golgi complex. Thus, at least in COS7 cells, SIAE behaves as a typical secreted enzyme, subjected to glycosylation and located along the classical secretory route or in the extracellular space. In these environments, the enzyme could act on 9- O -acetylated sialic acid residues, contributing to the fine-tuning of the various functions played by this acidic sugar.

Description: Vaccination against the ubiquitous parasite Toxoplasma gondii would provide the most efficient prevention against toxoplasmosis-related congenital, brain and eye diseases in humans. We investigated the immune response elicited by pathogen-specific glycosylphosphatidylinositol (GPI) glycoconjugates using carbohydrate microarrays in a BALB/c mouse model. We further examined the protective properties of the glycoconjugates in a lethal challenge model using the virulent T. gondii RH strain. Upon immunization, mice raised antibodies that bind to the respective GPIs on carbohydrate microarrays, but were mainly directed against an unspecific GPI epitope including the linker. The observed immune response, though robust, was unable to provide protection in mice when challenged with a lethal dose of viable tachyzoites. We demonstrate that anti-GPI antibodies raised against the here described semi-synthetic glycoconjugates do not confer protective immunity against T. gondii in BALB/c mice.

Description: Carbohydrate antigens are valuable as components of vaccines for bacterial infectious agents and human immunodeficiency virus (HIV), and for generating immunotherapeutics against cancer. The crystal structures of anti-carbohydrate antibodies in complex with antigen reveal the key features of antigen recognition and provide information that can guide the design of vaccines, particularly synthetic ones. This review summarizes structural features of anti-carbohydrate antibodies to over 20 antigens, based on six categories of glyco-antigen: (i) the glycan shield of HIV glycoproteins; (ii) tumor epitopes; (iii) glycolipids and blood group A antigen; (iv) internal epitopes of bacterial lipopolysaccharides; (v) terminal epitopes on polysaccharides and oligosaccharides, including a group of antibodies to Kdo-containing Chlamydia epitopes; and (vi) linear homopolysaccharides.

Description: Sialic acids (SAs) are widely expressed on immune cells and their levels and linkages named as sialylation status vary upon cellular environment changes related to both physiological and pathological processes. In this study, we performed a global profiling of the sialylation status of macrophages and their release of SAs in the cell culture medium by using flow cytometry, confocal microscopy and liquid chromatography tandem mass spectrometry (LC-MS/MS). Both flow cytometry and confocal microscopy results showed that cell surface α-2,3-linked SAs were predominant in the normal culture condition and changed slightly upon treatment with atorvastatin for 24 h, whereas α-2,6-linked SAs were negligible in the normal culture condition but significantly increased after treatment. Meanwhile, the amount of total cellular SAs increased about three times (from 369 ± 29 to 1080 ± 50 ng/mL) upon treatment as determined by the LC-MS/MS method. On the other hand, there was no significant change for secreted free SAs and conjugated SAs in the medium. These results indicated that the cell surface α-2,6 sialylation status of macrophages changes distinctly upon atorvastatin stimulation, which may reflect on the biological functions of the cells.

Description: Evolutionary studies usually use a two-step process to investigate sequence data. Step one estimates a multiple sequence alignment (MSA) and step two applies phylogenetic methods to ask evolutionary questions of that MSA. Modern phylogenetic methods infer evolutionary parameters using maximum likelihood or Bayesian inference, mediated by a probabilistic substitution model that describes sequence change over a tree. The statistical properties of these methods mean that more data directly translates to an increased confidence in downstream results, providing the substitution model is adequate and the MSA is correct. Many studies have investigated the robustness of phylogenetic methods in the presence of substitution model misspecification, but few have examined the statistical properties of those methods when the MSA is unknown. This simulation study examines the statistical properties of the complete two-step process when inferring sequence divergence and the phylogenetic tree topology. Both nucleotide and amino acid analyses are negatively affected by the alignment step, both through inaccurate guide tree estimates and through overfitting to that guide tree. For many alignment tools these effects become more pronounced when additional sequences are added to the analysis. Nucleotide sequences are particularly susceptible, with MSA errors leading to statistical support for long-branch attraction artifacts, which are usually associated with gross substitution model misspecification. Amino acid MSAs are more robust, but do tend to arbitrarily resolve multifurcations in favor of the guide tree. No inference strategies produce consistently accurate estimates of divergence between sequences, although amino acid MSAs are again more accurate than their nucleotide counterparts. We conclude with some practical suggestions about how to limit the effect of MSA uncertainty on evolutionary inference.

Description: The evolution of mitochondrial information processing pathways, including replication, transcription and translation, is characterized by the gradual replacement of mitochondrial-encoded proteins with nuclear-encoded counterparts of diverse evolutionary origins. Although the ancestral enzymes involved in mitochondrial transcription and replication have been replaced early in eukaryotic evolution, mitochondrial translation is still carried out by an apparatus largely inherited from the α-proteobacterial ancestor. However, variation in the complement of mitochondrial-encoded molecules involved in translation, including transfer RNAs (tRNAs), provides evidence for the ongoing evolution of mitochondrial protein synthesis. Here, we investigate the evolution of the mitochondrial translational machinery using recent genomic and transcriptomic data from animals that have experienced the loss of mt-tRNAs, including phyla Cnidaria and Ctenophora, as well as some representatives of all four classes of Porifera. We focus on four sets of mitochondrial enzymes that directly interact with tRNAs: Aminoacyl-tRNA synthetases, glutamyl-tRNA amidotransferase, tRNA Ile lysidine synthetase, and RNase P. Our results support the observation that the fate of nuclear-encoded mitochondrial proteins is influenced by the evolution of molecules encoded in mitochondrial DNA, but in a more complex manner than appreciated previously. The data also suggest that relaxed selection on mitochondrial translation rather than coevolution between mitochondrial and nuclear subunits is responsible for elevated rates of evolution in mitochondrial translational proteins.

Description: The expansion of DUF1220 domain copy number during human evolution is a dramatic example of rapid and repeated domain duplication. Although patterns of expression, homology, and disease associations suggest a role in cortical development, this hypothesis has not been robustly tested using phylogenetic methods. Here, we estimate DUF1220 domain counts across 12 primate genomes using a nucleotide Hidden Markov Model. We then test a series of hypotheses designed to examine the potential evolutionary significance of DUF1220 copy number expansion. Our results suggest a robust association with brain size, and more specifically neocortex volume. In contradiction to previous hypotheses, we find a strong association with postnatal brain development but not with prenatal brain development. Our results provide further evidence of a conserved association between specific loci and brain size across primates, suggesting that human brain evolution may have occurred through a continuation of existing processes.

Description: Adaptor proteins (AP 1–5) are heterotetrameric complexes that facilitate specialized cargo sorting in vesicular-mediated trafficking. Mutations in AP5Z1 , encoding a subunit of the AP-5 complex, have been reported to cause hereditary spastic paraplegia (HSP), although their impact at the cellular level has not been assessed. Here we characterize three independent fibroblast lines derived from skin biopsies of patients harbouring nonsense mutations in AP5Z1 and presenting with spastic paraplegia accompanied by neuropathy, parkinsonism and/or cognitive impairment. In all three patient-derived lines, we show that there is complete loss of AP-5 protein and a reduction in the associated AP-5 µ5 protein. Using ultrastructural analysis, we show that these patient-derived lines consistently exhibit abundant multilamellar structures that are positive for markers of endolysosomes and are filled with aberrant storage material organized as exaggerated multilamellar whorls, striated belts and ‘fingerprint bodies’. This phenotype can be replicated in a HeLa cell culture model by siRNA knockdown of AP-5 . The cellular phenotype bears striking resemblance to features described in a number of lysosomal storage diseases (LSDs). Collectively, these findings reveal an emerging picture of the role of AP-5 in endosomal and lysosomal homeostasis, illuminates a potential pathomechanism that is relevant to the role of AP-5 in neurons and expands the understanding of recessive HSPs. Moreover, the resulting accumulation of storage material in endolysosomes leads us to propose that AP-5 deficiency represents a new type of LSDs.

Description: Cleft palate is a common birth defect in humans. Therefore, understanding the molecular genetics of palate development is important from both scientific and medical perspectives. Lhx6 and Lhx8 encode LIM homeodomain transcription factors, and inactivation of both genes in mice resulted in profound craniofacial defects including cleft secondary palate. The initial outgrowth of the palate was severely impaired in the mutant embryos, due to decreased cell proliferation. Through genome-wide transcriptional profiling, we discovered that p57 Kip2 ( Cdkn1c ), encoding a cell cycle inhibitor, was up-regulated in the prospective palate of Lhx6 –/– ;Lhx8 –/– mutants. p57 Kip2 has been linked to Beckwith–Wiedemann syndrome and IMAGe syndrome in humans, which are developmental disorders with increased incidents of palate defects among the patients. To determine the molecular mechanism underlying the regulation of p57 Kip2 by the Lhx genes, we combined chromatin immunoprecipitation, in silico search for transcription factor-binding motifs, and in vitro reporter assays with putative cis-regulatory elements. The results of these experiments indicated that LHX6 and LHX8 regulated p57 Kip2 via both direct and indirect mechanisms, with the latter mediated by Forkhead box (FOX) family transcription factors. Together, our findings uncovered a novel connection between the initiation of palate development and a cell cycle inhibitor via LHX. We propose a model in which Lhx6 and Lhx8 negatively regulate p57 Kip2 expression in the prospective palate area to allow adequate levels of cell proliferation and thereby promote normal palate development. This is the first report elucidating a molecular genetic pathway downstream of Lhx in palate development.

Description: Keratoconus is a degenerative eye condition which results from thinning of the cornea and causes vision distortion. Treatments such as ultraviolet (UV) cross-linking have proved effective for management of keratoconus when performed in early stages of the disease. The central corneal thickness (CCT) is a highly heritable endophenotype of keratoconus, and it is estimated that up to 95% of its phenotypic variance is due to genetics. Genome-wide association efforts of CCT have identified common variants (i.e. minor allele frequency (MAF) 〉5%). However, these studies typically ignore the large set of exonic variants whose MAF is usually low. In this study, we performed a CCT exome-wide association analysis in a sample of 1029 individuals from a population-based study in Western Australia. We identified a genome-wide significant exonic variant rs121908120 ( P = 6.63 x 10 –10 ) in WNT10A . This gene is 437 kb from a gene previously associated with CCT ( USP37 ). We showed in a conditional analysis that the WNT10A variant completely accounts for the signal previously seen at USP37 . We replicated our finding in independent samples from the Brisbane Adolescent Twin Study, Twin Eye Study in Tasmania and the Rotterdam Study. Further, we genotyped rs121908120 in 621 keratoconus cases and compared the frequency to a sample of 1680 unscreened controls from the Queensland Twin Registry. We found that rs121908120 increases the risk of keratoconus two times (odds ratio 2.03, P = 5.41 x 10 –5 ).

Description: Somatic cell cytokinesis was shown to involve the insertion of sphingolipids (SLs) to midbodies prior to abscission. Spermatogenic midbodies transform into stable intercellular bridges (ICBs) connecting clonal daughter cells in a syncytium. This process requires specialized SL structures. (1) Using high resolution-mass spectrometric imaging, we show in situ a biphasic pattern of SL synthesis with testis-specific anchors. This pattern correlates with and depends on ceramide synthase 3 (CerS3) localization in both, pachytene spermatocytes until completion of meiosis and elongating spermatids. (2) Blocking the pathways to germ cell-specific ceramides (CerS3-KO) and further to glycosphingolipids (glucosylceramide synthase-KO) in mice highlights the need for special SLs for spermatid ICB stability. In contrast to somatic mitosis these SLs require ultra-long polyunsaturated anchors with unique physico-chemical properties, which can only be provided by CerS3. Loss of these anchors causes enhanced apoptosis during meiosis, formation of multinuclear giant cells and spermatogenic arrest. Hence, testis-specific SLs, which we also link to CerS3 in human testis, are quintessential for male fertility.

Description: Therapy-responsive biomarkers are an important and unmet need in the muscular dystrophy field where new treatments are currently in clinical trials. By using a comprehensive high-resolution mass spectrometry approach and western blot validation, we found that two fragments of the myofibrillar structural protein myomesin-3 (MYOM3) are abnormally present in sera of Duchenne muscular dystrophy (DMD) patients, limb-girdle muscular dystrophy type 2D (LGMD2D) and their respective animal models. Levels of MYOM3 fragments were assayed in therapeutic model systems: (1) restoration of dystrophin expression by antisense oligonucleotide-mediated exon-skipping in mdx mice and (2) stable restoration of α-sarcoglycan expression in KO-SGCA mice by systemic injection of a viral vector. Following administration of the therapeutic agents MYOM3 was restored toward wild-type levels. In the LGMD model, where different doses of vector were used, MYOM3 restoration was dose-dependent. MYOM3 fragments showed lower inter-individual variability compared with the commonly used creatine kinase assay, and correlated better with the restoration of the dystrophin-associated protein complex and muscle force. These data suggest that the MYOM3 fragments hold promise for minimally invasive assessment of experimental therapies for DMD and other neuromuscular disorders.

Description: RNA interference (RNAi) offers a promising therapeutic approach for dominant genetic disorders that involve gain-of-function mechanisms. One candidate disease for RNAi therapy application is myotonic dystrophy type 1 (DM1), which results from toxicity of a mutant mRNA. DM1 is caused by expansion of a CTG repeat in the 3' UTR of the DMPK gene. The expression of DMPK mRNA containing an expanded CUG repeat (CUG exp ) leads to defects in RNA biogenesis and turnover. We designed miRNA-based RNAi hairpins to target the CUG exp mRNA in the human α-skeletal muscle actin long-repeat ( HSA LR ) mouse model of DM1. RNAi expression cassettes were delivered to HSA LR mice using recombinant adeno-associated viral (rAAV) vectors injected intravenously as a route to systemic gene therapy. Vector delivery significantly reduced disease pathology in muscles of the HSA LR mice, including a reduction in the CUG exp mRNA, a reduction in myotonic discharges, a shift toward adult pre-mRNA splicing patterns, reduced myofiber hypertrophy and a decrease in myonuclear foci containing the CUG exp mRNA. Significant reversal of hallmarks of DM1 in the rAAV RNAi-treated HSA LR mice indicate that defects characteristic of DM1 can be mitigated with a systemic RNAi approach targeting the nuclei of terminally differentiated myofibers. Efficient rAAV-mediated delivery of RNAi has the potential to provide a long-term therapy for DM1 and other dominant muscular dystrophies.

Description: Motivation : The majority of variation identified by genome wide association studies falls in non-coding genomic regions and is hypothesized to impact regulatory elements that modulate gene expression. Here we present a statistically rigorous software tool GREGOR (Genomic Regulatory Elements and Gwas Overlap algoRithm) for evaluating enrichment of any set of genetic variants with any set of regulatory features. Using variants from five phenotypes, we describe a data-driven approach to determine the tissue and cell types most relevant to a trait of interest and to identify the subset of regulatory features likely impacted by these variants. Last, we experimentally evaluate six predicted functional variants at six lipid-associated loci and demonstrate significant evidence for allele-specific impact on expression levels. GREGOR systematically evaluates enrichment of genetic variation with the vast collection of regulatory data available to explore novel biological mechanisms of disease and guide us toward the functional variant at trait-associated loci. Availability and implementation : GREGOR, including source code, documentation, examples, and executables, is available at http://genome.sph.umich.edu/wiki/GREGOR . Contact : cristen@umich.edu Supplementary information : Supplementary data are available at Bioinformatics online.

Description: Motivation: Genome and transcriptome analyses can be used to explore cancers comprehensively, and it is increasingly common to have multiple omics data measured from each individual. Furthermore, there are rich functional data such as predicted impact of mutations on protein coding and gene/protein networks. However, integration of the complex information across the different omics and functional data is still challenging. Clinical validation, particularly based on patient outcomes such as survival, is important for assessing the relevance of the integrated information and for comparing different procedures. Results: An analysis pipeline is built for integrating genomic and transcriptomic alterations from whole-exome and RNA sequence data and functional data from protein function prediction and gene interaction networks. The method accumulates evidence for the functional implications of mutated potential driver genes found within and across patients. A driver-gene score (DGscore) is developed to capture the cumulative effect of such genes. To contribute to the score, a gene has to be frequently mutated, with high or moderate mutational impact at protein level, exhibiting an extreme expression and functionally linked to many differentially expressed neighbors in the functional gene network. The pipeline is applied to 60 matched tumor and normal samples of the same patient from The Cancer Genome Atlas breast-cancer project. In clinical validation, patients with high DGscores have worse survival than those with low scores ( P = 0.001). Furthermore, the DGscore outperforms the established expression-based signatures MammaPrint and PAM50 in predicting patient survival. In conclusion, integration of mutation, expression and functional data allows identification of clinically relevant potential driver genes in cancer. Availability and implementation: The documented pipeline including annotated sample scripts can be found in http://fafner.meb.ki.se/biostatwiki/driver-genes/ . Contact: yudi.pawitan@ki.se Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: With improvements in next-generation sequencing technologies and reductions in price, ordered RNA-seq experiments are becoming common. Of primary interest in these experiments is identifying genes that are changing over time or space, for example, and then characterizing the specific expression changes. A number of robust statistical methods are available to identify genes showing differential expression among multiple conditions, but most assume conditions are exchangeable and thereby sacrifice power and precision when applied to ordered data. Results: We propose an empirical Bayes mixture modeling approach called EBSeq-HMM. In EBSeq-HMM, an auto-regressive hidden Markov model is implemented to accommodate dependence in gene expression across ordered conditions. As demonstrated in simulation and case studies, the output proves useful in identifying differentially expressed genes and in specifying gene-specific expression paths. EBSeq-HMM may also be used for inference regarding isoform expression. Availability and implementation: An R package containing examples and sample datasets is available at Bioconductor. Contact: kendzior@biostat.wisc.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: Sequence discovery tools play a central role in several fields of computational biology. In the framework of Transcription Factor binding studies, most of the existing motif finding algorithms are computationally demanding, and they may not be able to support the increasingly large datasets produced by modern high-throughput sequencing technologies. Results: We present FastMotif, a new motif discovery algorithm that is built on a recent machine learning technique referred to as Method of Moments. Based on spectral decompositions, our method is robust to model misspecifications and is not prone to locally optimal solutions. We obtain an algorithm that is extremely fast and designed for the analysis of big sequencing data. On HT-Selex data, FastMotif extracts motif profiles that match those computed by various state-of-the-art algorithms, but one order of magnitude faster. We provide a theoretical and numerical analysis of the algorithm’s robustness and discuss its sensitivity with respect to the free parameters. Availability and implementation: The Matlab code of FastMotif is available from http://lcsb-portal.uni.lu/bioinformatics . Contact: vlassis@adobe.com Supplementary information: Supplementary data are available at Bioinformatics online.