ALBERT

Description: Differences in expression levels are an important source of phenotypic variation within and between populations. MicroRNAs (miRNAs) are key players in post-transcriptional gene regulation that are important for plant development and stress responses. We surveyed expression variation of miRNAs and mRNAs of six accessions from two rice subspecies Oryza sativa L. ssp. indica and Oryza sativa L. ssp . japonica using deep sequencing. While more than half (53.7%) of the mature miRNAs exhibit differential expression between grains and seedlings of rice, only 11.0% show expression differences between subspecies, with an additional 2.2% differentiated for the development-by-subspecies interaction. Expression variation is greater for lowly conserved miRNAs than highly conserved miRNAs, whereas the latter show stronger negative correlation with their targets in expression changes between subspecies. Using a permutation test, we identified 51 miRNA–mRNA pairs that correlate negatively or positively in expression level among cultivated rice. Genes involved in various metabolic processes and stress responses are enriched in the differentially expressed genes between rice indica and japonica subspecies. Our results indicate that stabilizing selection is the major force governing miRNA expression in cultivated rice, albeit positive selection may be responsible for much of the between-subspecies expression divergence.

Description: Geographical variation among contiguous populations is frequently attributed to ecological divergence or historical isolation followed by secondary contact. Distinguishing between these effects is key to studies of incipient speciation and could be revealed by different genomic signatures. We used RAD-seq analyses to examine morphologically divergent populations of the endemic lizard ( Gallotia galloti ) from the volcanic island of Tenerife. Previous analyses have suggested ecological and historical causes to explain the morphological diversity. Analyses of 276,483 single nucleotide polymorphisms (SNPs) from 〉20 Mbp of the genome revealed one genetically divergent population from Anaga, a region associated with divergent mtDNA lineages in other Tenerife endemics. This population also has a high number of private alleles, and its divergence can be explained by historical isolation. Bayesian outlier analyses identified a small proportion of SNPs as candidates for selection (0.04%) which were strongly differentiated between xeric and mesic habitat types. Individual testing for specific xeric–mesic selection using an alternative approach also supported ecological divergence in a similarly small proportion of SNPs. The study indicates the roles of both historical isolation and ecological divergence in shaping genomic diversity in G. galloti . However, north–south morphological divergence appears solely associated with the latter and likely involves a relatively small proportion of the genome.

Description: Streptococcus anginosus is a member of the normal oral flora that can become a pathogen causing pyogenic infections in humans. The genome of daptomycin-resistant strain J4206, originally isolated from a patient suffering from breakthrough bacteremia and septic shock at the University of Texas Health Science Center at San Antonio, was determined. The circular genome is 2,001,352 bp long with a GC content of 38.62% and contains multiple mobile genetic elements, including the phage-like chromosomal island SanCI that mediates a mutator phenotype, transposons, and integrative conjugative elements. Daptomycin resistance involves multiple alterations in the cell membrane and cell wall, and unique features were identified in J4206 that may contribute to resistance. A cluster of capsular polysaccharide (CPS) genes for choline metabolism and transport are present that may help neutralize cell surface charges, destabilizing daptomycin binding. Further, unique J4206 genes encoding sortases and LPXTG-target proteins that are involved in cell wall modification were present. The J4206 genome is phylogenetically closely related to the recently reported vancomycin-resistant SA1 strain; however, these genomes differ with SNPs in cardiolipin synthetase, histidine kinase yycG , teichoic acid modification genes, and other genes involved in cell surface modification. Transmission electron microscopy showed that the cell walls of both strains J4206 and SA1 were significantly thicker and more electron dense than daptomycin- and vancomycin-sensitive strain J4211. This comparative genomic study has identified unique genes as well as allelic variants in the J4206 genome that are involved in cell surface modification and thus might contribute to the acquisition of daptomycin resistance.

Description: Chromosome number changes during the evolution of angiosperms are likely to have played a major role in speciation. Their study is of utmost importance, especially now, as a probabilistic model is available to study chromosome evolution within a phylogenetic framework. In the present study, likelihood models of chromosome number evolution were fitted to the largest family of flowering plants, the Asteraceae. Specifically, a phylogenetic supertree of this family was used to reconstruct the ancestral chromosome number and infer genomic events. Our approach inferred that the ancestral chromosome number of the family is n = 9. Also, according to the model that best explained our data, the evolution of haploid chromosome numbers in Asteraceae was a very dynamic process, with genome duplications and descending dysploidy being the most frequent genomic events in the evolution of this family. This model inferred more than one hundred whole genome duplication events; however, it did not find evidence for a paleopolyploidization at the base of this family, which has previously been hypothesized on the basis of sequence data from a limited number of species. The obtained results and potential causes of these discrepancies are discussed.

Description: Ribosomal RNAs (rRNAs) account for 〉60% of all RNAs in eukaryotic cells and are encoded in the ribosomal DNA (rDNA) arrays. The rRNAs are produced from two sets of loci: the 5S rDNA array resides exclusively on human chromosome 1, whereas the 45S rDNA array resides on the short arm of five human acrocentric chromosomes. The 45S rDNA gives origin to the nucleolus, the nuclear organelle that is the site of ribosome biogenesis. Intriguingly, 5S and 45S rDNA arrays exhibit correlated copy number variation in lymphoblastoid cells (LCLs). Here we examined the genomic architecture and repeat content of the 5S and 45S rDNA arrays in multiple human genome assemblies (including PacBio MHAP assembly) and ascertained contacts between the rDNA arrays and the rest of the genome using Hi-C datasets from two human cell lines (erythroleukemia K562 and lymphoblastoid cells). Our analyses revealed that 5S and 45S arrays each have thousands of contacts in the folded genome, with rDNA-associated regions and genes dispersed across all chromosomes. The rDNA contact map displayed conserved and disparate features between two cell lines, and pointed to specific chromosomes, genomic regions, and genes with evidence of spatial proximity to the rDNA arrays; the data also showed a lack of direct physical interaction between the 5S and 45S rDNA arrays. Finally, the analysis identified an intriguing organization in the 5S array with Alu and 5S elements adjacent to one another and organized in opposite orientation along the array. Portraits of genome folding centered on the ribosomal DNA array could help understand the emergence of concerted variation, the control of 5S and 45S expression, as well as provide insights into an organelle that contributes to the spatial localization of human chromosomes during interphase.

Description: Conserved non-coding sequences (CNSs) of Eukaryotes are known to be significantly enriched in regulatory sequences. CNSs of diverse lineages follow different patterns in abundance, sequence composition, and location. Here, we report a thorough analysis of CNSs in diverse groups of Eukaryotes with respect to GC content heterogeneity. We examined 24 fungi, 19 invertebrates, and 12 non-mammalian vertebrates so as to find lineage specific features of CNSs. We found that fungi and invertebrate CNSs are predominantly GC rich as in plants we previously observed, whereas vertebrate CNSs are GC poor. This result suggests that the CNS GC content transition occurred from the ancestral GC rich state of Eukaryotes to GC poor in the vertebrate lineage due to the enrollment of GC poor transcription factor binding sites that are lineage specific. CNS GC content is closely linked with the nucleosome occupancy that determines the location and structural architecture of DNAs.

Description: Male mutation bias, when more mutations are passed on via the male germline than via the female germline, is observed across mammals. One common way to infer the magnitude of male mutation bias, α, is to compare levels of neutral sequence divergence between genomic regions that spend different amounts of time in the male and female germline. For great apes, including human, we show that estimates of divergence are reduced in putatively unconstrained regions near genes relative to unconstrained regions far from genes. Divergence increases with increasing distance from genes on both the X chromosome and autosomes, but increases faster on the X chromosome than autosomes. As a result, ratios of X/A divergence increase with increasing distance from genes and corresponding estimates of male mutation bias are significantly higher in intergenic regions near genes versus far from genes. Future studies in other species will need to carefully consider the effect that genomic location will have on estimates of male mutation bias.

Description: Great genetic variability among teleost immunomes, with gene losses and expansions of central adaptive and innate components, has been discovered through genome sequencing over the last few years. Here, we demonstrate that the innate Myxovirus resistance gene ( Mx ) is lost from the ancestor of Gadiformes and the closely related Stylephorus chordatus , thus predating the loss of Major Histocompatibility Complex class II ( MHCII ) in Gadiformes. Although the functional implication of Mx loss is still unknown, we demonstrate that this loss is one of several ancient events appearing in successive order throughout the evolution of teleost immunity. In particular, we find that the loss of Toll-like receptor 5 predates the loss of Mx involving the entire Paracanthopterygii lineage. Using a time-calibrated phylogeny, we show that loss of MHCII and Mx overlap with major paleoclimatic and geological events indicating that these genetic changes were adaptive responses to the changing environment at the time.

Description: Males and females often display extensive phenotypic differences, and many of these sexual dimorphisms are thought to result from differences between males and females in expression of genes present in both sexes. Sex-biased genes have been shown to exhibit accelerated rates of evolution in a wide array of species, however the cause of this remains enigmatic. In this study, we investigate the extent and evolutionary dynamics of sex-biased gene expression in zebrafish. Our results indicate that both male-biased genes and female-biased genes exhibit accelerated evolution at the protein level. In order to differentiate between adaptive and nonadaptive causes, we tested for codon usage bias and signatures of different selective regimes in our sequence data. Our results show that both male- and female-biased genes show signatures consistent with adaptive evolution. In order to test the generality of our findings across fish, we also analyzed publicly available data on sticklebacks, and found results consistent with our findings in zebrafish.

Description: Host–pathogen interactions may result in either directional selection or in pressure for the maintenance of polymorphism at the molecular level. Hence signatures of both positive and balancing selection are expected in immune genes. Because both overall selective pressure and specific targets may differ between species, large-scale population genomic studies are useful in detecting functionally important immune genes and comparing selective landscapes between taxa. Such studies are of particular interest in amphibians, a group threatened worldwide by emerging infectious diseases. Here, we present an analysis of polymorphism and divergence of 634 immune genes in two lineages of Lissotriton newts: L. montandoni and L. vulgaris graecus . Variation in newt immune genes has been shaped predominantly by widespread purifying selection and strong evolutionary constraint, implying long-term importance of these genes for functioning of the immune system. The two evolutionary lineages differ in the overall strength of purifying selection which can partially be explained by demographic history but may also signal differences in long-term pathogen pressure. The prevalent constraint notwithstanding, 23 putative targets of positive selection and 11 putative targets of balancing selection were identified. The latter were detected by composite tests involving the demographic model and further validated in independent population samples. Putative targets of balancing selection encode proteins which may interact closely with pathogens but include also regulators of immune response. The identified candidates will be useful for testing whether genes affected by balancing selection are more prone to interspecific introgression than other genes in the genome.

Description: Genomic variation in Indian populations is of great interest due to the diversity of ancestral components, social stratification, endogamy and complex admixture patterns. With an expanding population of 1.2 billion, India is also a treasure trove to catalogue innocuous as well as clinically relevant rare mutations. Recent studies have revealed four dominant ancestries in populations from mainland India: Ancestral North-Indian (ANI), Ancestral South-Indian (ASI), Ancestral Tibeto–Burman (ATB) and Ancestral Austro-Asiatic (AAA). The 1000 Genomes Project (KGP) Phase-3 data include about 500 genomes from five linguistically defined Indian-Subcontinent (IS) populations (Punjabi, Gujrati, Bengali, Telugu and Tamil) some of whom are recent migrants to USA or UK. Comparative analyses show that despite the distinct geographic origins of the KGP-IS populations, the ANI component is predominantly represented in this dataset. Previous studies demonstrated population substructure in the HapMap Gujrati population, and we found evidence for additional substructure in the Punjabi and Telugu populations. These substructured populations have characteristic/significant differences in heterozygosity and inbreeding coefficients. Moreover, we demonstrate that the substructure is better explained by factors like differences in proportion of ancestral components, and endogamy driven social structure rather than invoking a novel ancestral component to explain it. Therefore, using language and/or geography as a proxy for an ethnic unit is inadequate for many of the IS populations. This highlights the necessity for more nuanced sampling strategies or corrective statistical approaches, particularly for biomedical and population genetics research in India.

Description: Within the last 15 years, two related coronaviruses (Severe Acute Respiratory Syndrome [SARS]-CoV and Middle East Respiratory Syndrome [MERS]-CoV) expanded their host range to include humans, with increased virulence in their new host. Coronaviruses were recently found to have little intrinsic disorder compared with many other virus families. Because intrinsically disordered regions have been proposed to be important for rewiring interactions between virus and host, we investigated the conservation of intrinsic disorder and secondary structure in coronaviruses in an evolutionary context. We found that regions of intrinsic disorder are rarely conserved among different coronavirus protein families, with the primary exception of the nucleocapsid. Also, secondary structure predictions are only conserved across 50–80% of sites for most protein families, with the implication that 20–50% of sites do not have conserved secondary structure prediction. Furthermore, nonconserved structure sites are significantly less constrained in sequence divergence than either sites conserved in the secondary structure or sites conserved in loop. Avoiding regions symptomatic of conformational flexibility such as disordered sites and sites with nonconserved secondary structure to identify potential broad-specificity antiviral targets, only one sequence motif (five residues or longer) remains from the 〉10,000 starting sites across all coronaviruses in this study. The identified sequence motif is found within the nonstructural protein (NSP) 12 and constitutes an antiviral target potentially effective against the present day and future coronaviruses. On shorter evolutionary timescales, the SARS and MERS clades have more sequence motifs fulfilling the criteria applied. Interestingly, many motifs map to NSP12 making this a prime target for coronavirus antivirals.

Description: Species of the Fusarium fujikuroi species complex (FFC) cause a wide spectrum of often devastating diseases on diverse agricultural crops, including coffee, fig, mango, maize, rice, and sugarcane. Although species within the FFC are difficult to distinguish by morphology, and their genes often share 90% sequence similarity, they can differ in host plant specificity and life style. FFC species can also produce structurally diverse secondary metabolites (SMs), including the mycotoxins fumonisins, fusarins, fusaric acid, and beauvericin, and the phytohormones gibberellins, auxins, and cytokinins. The spectrum of SMs produced can differ among closely related species, suggesting that SMs might be determinants of host specificity. To date, genomes of only a limited number of FFC species have been sequenced. Here, we provide draft genome sequences of three more members of the FFC: a single isolate of F. mangiferae , the cause of mango malformation, and two isolates of F. proliferatum , one a pathogen of maize and the other an orchid endophyte. We compared these genomes to publicly available genome sequences of three other FFC species. The comparisons revealed species-specific and isolate-specific differences in the composition and expression ( in vitro and in planta ) of genes involved in SM production including those for phytohormome biosynthesis. Such differences have the potential to impact host specificity and, as in the case of F. proliferatum , the pathogenic versus endophytic life style.

Description: Every human suffers through life a number of papillomaviruses (PVs) infections, most of them asymptomatic. A notable exception are persistent infections by Human papillomavirus 16 (HPV16), the most oncogenic infectious agent for humans and responsible for most infection-driven anogenital cancers. Oncogenic potential is not homogeneous among HPV16 lineages, and genetic variation within HPV16 exhibits some geographic structure. However, an in-depth analysis of the HPV16 evolutionary history was still wanting. We have analyzed extant HPV16 diversity and compared the evolutionary and phylogeographical patterns of humans and of HPV16. We show that codivergence with modern humans explains at most 30% of the present viral geographical distribution. The most explanatory scenario suggests that ancestral HPV16 already infected ancestral human populations and that viral lineages co-diverged with the hosts in parallel with the split between archaic Neanderthal-Denisovans and ancestral modern human populations, generating the ancestral HPV16A and HPV16BCD viral lineages, respectively. We propose that after out-of-Africa migration of modern human ancestors, sexual transmission between human populations introduced HPV16A into modern human ancestor populations. We hypothesize that differential coevolution of HPV16 lineages with different but closely related ancestral human populations and subsequent host-switch events in parallel with introgression of archaic alleles into the genomes of modern human ancestors may be largely responsible for the present-day differential prevalence and association with cancers for HPV16 variants.

Description: Ongoing advances in sequencing technology have led to an explosive expansion in the molecular data available for building increasingly larger and more comprehensive timetrees. However, Bayesian relaxed-clock approaches frequently used to infer these timetrees impose a large computational burden and discourage critical assessment of the robustness of inferred times to model assumptions, influence of calibrations, and selection of optimal data subsets. We analyzed eight large, recently published, empirical datasets to compare time estimates produced by RelTime (a non-Bayesian method) with those reported by using Bayesian approaches. We find that RelTime estimates are very similar to Bayesian approaches, yet RelTime requires orders of magnitude less computational time. This means that the use of RelTime will enable greater rigor in molecular dating, because faster computational speeds encourage more extensive testing of the robustness of inferred timetrees to prior assumptions (models and calibrations) and data subsets. Thus, RelTime provides a reliable and computationally thrifty approach for dating the tree of life using large-scale molecular datasets.

Description: Gene clusters of recently duplicated genes are hotbeds for evolutionary change. However, our understanding of how mutational mechanisms and evolutionary forces shape the structural and functional evolution of these clusters is hindered by the high sequence identity among the copies, which typically results in their inaccurate representation in genome assemblies. The presumed testis-specific, chimeric gene Sdic originated, and tandemly expanded in Drosophila melanogaster , contributing to increased male-male competition. Using various types of massively parallel sequencing data, we studied the organization, sequence evolution, and functional attributes of the different Sdic copies. By leveraging long-read sequencing data, we uncovered both copy number and order differences from the currently accepted annotation for the Sdic region. Despite evidence for pervasive gene conversion affecting the Sdic copies, we also detected signatures of two episodes of diversifying selection, which have contributed to the evolution of a variety of C-termini and miRNA binding site compositions. Expression analyses involving RNA-seq datasets from 59 different biological conditions revealed distinctive expression breadths among the copies, with three copies being transcribed in females, opening the possibility to a sexually antagonistic effect. Phenotypic assays using Sdic knock-out strains indicated that should this antagonistic effect exist, it does not compromise female fertility. Our results strongly suggest that the genome consolidation of the Sdic gene cluster is more the result of a quick exploration of different paths of molecular tinkering by different copies than a mere dosage increase, which could be a recurrent evolutionary outcome in the presence of persistent sexual selection.

Description: Bats can perceive the world by using a wide range of sensory systems, and some of the systems have become highly specialized, such as auditory sensory perception. Among bat species, the Old World leaf-nosed bats and horseshoe bats (rhinolophoid bats) possess the most sophisticated echolocation systems. Here, we reported the whole-genome sequencing and de novo assembles of two rhinolophoid bats—the great leaf-nosed bat ( Hipposideros armiger ) and the Chinese rufous horseshoe bat ( Rhinolophus sinicus ). Comparative genomic analyses revealed the adaptation of auditory sensory perception in the rhinolophoid bat lineages, probably resulting from the extreme selectivity used in the auditory processing by these bats. Pseudogenization of some vision-related genes in rhinolophoid bats was observed, suggesting that these genes have undergone relaxed natural selection. An extensive contraction of olfactory receptor gene repertoires was observed in the lineage leading to the common ancestor of bats. Further extensive gene contractions can be observed in the branch leading to the rhinolophoid bats. Such concordance suggested that molecular changes at one sensory gene might have direct consequences for genes controlling for other sensory modalities. To characterize the population genetic structure and patterns of evolution, we re-sequenced the genome of 20 great leaf-nosed bats from four different geographical locations of China. The result showed similar sequence diversity values and little differentiation among populations. Moreover, evidence of genetic adaptations to high altitudes in the great leaf-nosed bats was observed. Taken together, our work provided a useful resource for future research on the evolution of bats.

Description: Molecular basis for mammalian echolocation has been receiving much concerns. Recent findings on the parallel evolution of prestin sequences among echolocating bats and toothed whales suggest that adaptations for high-frequency hearing have occurred during the evolution of echolocation. Here, we report that although the species tree for echolocating bats emitting echolocation calls with frequency modulated (FM) sweeps is paraphyletic, prestin exhibits similar functional changes between FM bats. Site-directed mutagenesis shows that the amino acid 308S in FM bats is responsible for the similar functional changes of prestin . We strongly support that the occurrence of serine at position 308 is a case of hemiplasy, caused by incomplete lineage sorting of an ancestral polymorphism. Our study not only reveals sophisticated molecular basis of echolocation in bats, but also calls for caution in the inference of molecular convergence in species experiencing rapid radiation.

Description: The genetic analysis of experimentally evolving populations typically relies on short reads from pooled individuals (Pool-Seq). While this method provides reliable allele frequency estimates, the underlying haplotype structure remains poorly characterized. With small population sizes and adaptive variants that start from low frequencies, the interpretation of selection signatures in most Evolve and Resequencing studies remains challenging. To facilitate the characterization of selection targets, we propose a new approach that reconstructs selected haplotypes from replicated time series, using Pool-Seq data. We identify selected haplotypes through the correlated frequencies of alleles carried by them. Computer simulations indicate that selected haplotype-blocks of several Mb can be reconstructed with high confidence and low error rates, even when allele frequencies change only by 20% across three replicates. Applying this method to real data from D. melanogaster populations adapting to a hot environment, we identify a selected haplotype-block of 6.93 Mb. We confirm the presence of this haplotype-block in evolved populations by experimental haplotyping, demonstrating the power and accuracy of our haplotype reconstruction from Pool-Seq data. We propose that the combination of allele frequency estimates with haplotype information will provide the key to understanding the dynamics of adaptive alleles.

Description: Viral phylogenetic methods contribute to understanding how HIV spreads in populations, and thereby help guide the design of prevention interventions. So far, most analyses have been applied to well-sampled concentrated HIV-1 epidemics in wealthy countries. To direct the use of phylogenetic tools to where the impact of HIV-1 is greatest, the Phylogenetics And Networks for Generalized HIV Epidemics in Africa (PANGEA-HIV) consortium generates full-genome viral sequences from across sub-Saharan Africa. Analyzing these data presents new challenges, since epidemics are principally driven by heterosexual transmission and a smaller fraction of cases is sampled. Here, we show that viral phylogenetic tools can be adapted and used to estimate epidemiological quantities of central importance to HIV-1 prevention in sub-Saharan Africa. We used a community-wide methods comparison exercise on simulated data, where participants were blinded to the true dynamics they were inferring. Two distinct simulations captured generalized HIV-1 epidemics, before and after a large community-level intervention that reduced infection levels. Five research groups participated. Structured coalescent modeling approaches were most successful: phylogenetic estimates of HIV-1 incidence, incidence reductions, and the proportion of transmissions from individuals in their first 3 months of infection correlated with the true values (Pearson correlation 〉 90%), with small bias. However, on some simulations, true values were markedly outside reported confidence or credibility intervals. The blinded comparison revealed current limits and strengths in using HIV phylogenetics in challenging settings, provided benchmarks for future methods’ development, and supports using the latest generation of phylogenetic tools to advance HIV surveillance and prevention.

Description: Codon substitution models have traditionally attempted to uncover signatures of adaptation within protein-coding genes by contrasting the rates of synonymous and non-synonymous substitutions. Another modeling approach, known as the mutation–selection framework, attempts to explicitly account for selective patterns at the amino acid level, with some approaches allowing for heterogeneity in these patterns across codon sites. Under such a model, substitutions at a given position occur at the neutral or nearly neutral rate when they are synonymous, or when they correspond to replacements between amino acids of similar fitness; substitutions from high to low (low to high) fitness amino acids have comparatively low (high) rates. Here, we study the use of such a mutation–selection framework as a null model for the detection of adaptation. Following previous works in this direction, we include a deviation parameter that has the effect of capturing the surplus, or deficit, in non-synonymous rates, relative to what would be expected under a mutation–selection modeling framework that includes a Dirichlet process approach to account for across-codon-site variation in amino acid fitness profiles. We use simulations, along with a few real data sets, to study the behavior of the approach, and find it to have good power with a low false-positive rate. Altogether, we emphasize the potential of recent mutation–selection models in the detection of adaptation, calling for further model refinements as well as large-scale applications.

Description: Genetic variation among individuals within a population provides the raw material for phenotypic diversity upon which natural selection operates. Some given variants can act on multiple standing genomic variations simultaneously and release previously inaccessible phenotypes, leading to increased adaptive potential upon challenging environments. Previously, we identified such a variant related to a tRNA nonsense suppressor in yeast. When introduced into other genetic backgrounds, the suppressor led to an increased population phenotypic variance on various culture conditions, conferring background and environment specific selective advantages. Nonetheless, most isolates are intolerant to the suppressor on rich media due to a severe fitness cost. Here, we found that the tolerance to suppressor is related to a surprising level of fitness outburst, showing a trade-off effect to accommodate the cost of carrying the suppressor. To dissect the genetic basis of such trade-offs, we crossed strains with contrasting tolerance levels on rich media, and analyzed the fitness distribution patterns in the offspring. Combining quantitative tetrad analysis and bulk segregant analysis, we identified two genes, namely MKT1 and RGA1 , involved in suppressor tolerance. We showed that alleles from the tolerant parent for both genes conferred a significant gain of fitness, which increased the suppressor tolerance. Our results present a detailed dissection of suppressor tolerance in yeast and provide insights into the molecular basis of trade-offs between fitness and evolutionary potential.

Description: Modern population genomic datasets hold immense promise for revealing the evolutionary processes operating in natural populations, but a crucial prerequisite for this goal is the ability to model realistic evolutionary scenarios and predict their expected patterns in genomic data. To that end, we present SLiM 2: an evolutionary simulation framework that combines a powerful, fast engine for forward population genetic simulations with the capability of modeling a wide variety of complex evolutionary scenarios. SLiM achieves this flexibility through scriptability, which provides control over most aspects of the simulated evolutionary scenarios with a simple R-like scripting language called Eidos. An example SLiM simulation is presented to illustrate the power of this approach. SLiM 2 also includes a graphical user interface for simulation construction, interactive runtime control, and dynamic visualization of simulation output, facilitating easy and fast model development with quick prototyping and visual debugging. We conclude with a performance comparison between SLiM and two other popular forward genetic simulation packages.

Description: Closely spaced clusters of tandemly duplicated genes (CTDGs) contribute to the diversity of many phenotypes, including chemosensation, snake venom, and animal body plans. CTDGs have traditionally been identified subjectively as genomic neighborhoods containing several gene duplicates in close proximity; however, CTDGs are often highly variable with respect to gene number, intergenic distance, and synteny. This lack of formal definition hampers the study of CTDG evolutionary dynamics and the discovery of novel CTDGs in the exponentially growing body of genomic data. To address this gap, we developed a novel homology-based algorithm, CTDGFinder, which formalizes and automates the identification of CTDGs by examining the physical distribution of individual members of families of duplicated genes across chromosomes. Application of CTDGFinder accurately identified CTDGs for many well-known gene clusters (e.g., Hox and beta-globin gene clusters) in the human, mouse and 20 other mammalian genomes. Differences between previously annotated gene clusters and our inferred CTDGs were due to the exclusion of nonhomologs that have historically been considered parts of specific gene clusters, the inclusion or absence of genes between the CTDGs and their corresponding gene clusters, and the splitting of certain gene clusters into distinct CTDGs. Examination of human genes showing tissue-specific enhancement of their expression by CTDGFinder identified members of several well-known gene clusters (e.g., cytochrome P450s and olfactory receptors) and revealed that they were unequally distributed across tissues. By formalizing and automating CTDG identification, CTDGFinder will facilitate understanding of CTDG evolutionary dynamics, their functional implications, and how they are associated with phenotypic diversity.

Description: GenBank ® ( www.ncbi.nlm.nih.gov/genbank/ ) is a comprehensive database that contains publicly available nucleotide sequences for 370 000 formally described species. These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole genome shotgun (WGS) and environmental sampling projects. Most submissions are made using the web-based BankIt or the NCBI Submission Portal. GenBank staff assign accession numbers upon data receipt. Daily data exchange with the European Nucleotide Archive (ENA) and the DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through the NCBI Nucleotide database, which links to related information such as taxonomy, genomes, protein sequences and structures, and biomedical journal literature in PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. Recent updates include changes to policies regarding sequence identifiers, an improved 16S submission wizard, targeted loci studies, the ability to submit methylation and BioNano mapping files, and a database of anti-microbial resistance genes.

Description: The abnormal transcriptional regulation of non-coding RNAs (ncRNAs) and protein-coding genes (PCGs) is contributed to various biological processes and linked with human diseases, but the underlying mechanisms remain elusive. In this study, we developed ChIPBase v2.0 ( http://rna.sysu.edu.cn/chipbase/ ) to explore the transcriptional regulatory networks of ncRNAs and PCGs. ChIPBase v2.0 has been expanded with ~10 200 curated ChIP-seq datasets, which represent about 20 times expansion when comparing to the previous released version. We identified thousands of binding motif matrices and their binding sites from ChIP-seq data of DNA-binding proteins and predicted millions of transcriptional regulatory relationships between transcription factors (TFs) and genes. We constructed ‘Regulator’ module to predict hundreds of TFs and histone modifications that were involved in or affected transcription of ncRNAs and PCGs. Moreover, we built a web-based tool, Co-Expression, to explore the co-expression patterns between DNA-binding proteins and various types of genes by integrating the gene expression profiles of ~10 000 tumor samples and ~9100 normal tissues and cell lines. ChIPBase also provides a ChIP-Function tool and a genome browser to predict functions of diverse genes and visualize various ChIP-seq data. This study will greatly expand our understanding of the transcriptional regulations of ncRNAs and PCGs.

Description: We present an update of the Eukaryotic Promoter Database EPD ( http://epd.vital-it.ch ), more specifically on the EPDnew division, which contains comprehensive organisms-specific transcription start site (TSS) collections automatically derived from next generation sequencing (NGS) data. Thanks to the abundant release of new high-throughput transcript mapping data (CAGE, TSS-seq, GRO-cap) the database could be extended to plant and fungal species. We further report on the expansion of the mass genome annotation (MGA) repository containing promoter-relevant chromatin profiling data and on improvements for the EPD entry viewers. Finally, we present a new data access tool, ChIP-Extract, which enables computational biologists to extract diverse types of promoter-associated data in numerical table formats that are readily imported into statistical analysis platforms such as R.

Description: GETPrime ( http://bbcftools.epfl.ch/getprime ) is a database with a web frontend providing gene- and transcript-specific, pre-computed qPCR primer pairs. The primers have been optimized for genome-wide specificity and for allowing the selective amplification of one or several splice variants of most known genes. To ease selection, primers have also been ranked according to defined criteria such as genome-wide specificity (with BLAST), amplicon size, and isoform coverage. Here, we report a major upgrade (2.0) of the database: eight new species (yeast, chicken, macaque, chimpanzee, rat, platypus, pufferfish, and Anolis carolinensis ) now complement the five already included in the previous version (human, mouse, zebrafish, fly, and worm). Furthermore, the genomic reference has been updated to Ensembl v81 (while keeping earlier versions for backward compatibility) as a result of re-designing the back-end database and automating the import of relevant sections of the Ensembl database in species-independent fashion. This also allowed us to map known polymorphisms to the primers (on average three per primer for human), with the aim of reducing experimental error when targeting specific strains or individuals. Another consequence is that the inclusion of future Ensembl releases and other species has now become a relatively straightforward task.

Description: R-loopDB ( http://rloop.bii.a-star.edu.sg ) was originally constructed as a collection of computationally predicted R-loop forming sequences (RLFSs) in the human genic regions. The renewed R-loopDB provides updates, improvements and new options, including access to recent experimental data. It includes genome-scale prediction of RLFSs for humans, six other animals and yeast. Using the extended quantitative model of RLFSs (QmRLFS), we significantly increased the number of RLFSs predicted in the human genes and identified RLFSs in other organism genomes. R-loopDB allows searching of RLFSs in the genes and in the 2 kb upstream and downstream flanking sequences of any gene. R-loopDB exploits the Ensembl gene annotation system, providing users with chromosome coordinates, sequences, gene and genomic data of the 1 565 795 RLFSs distributed in 121 056 genic or proximal gene regions of the covered organisms. It provides a comprehensive annotation of Ensembl RLFS-positive genes including 93 454 protein coding genes, 12 480 long non-coding RNA and 7 568 small non-coding RNA genes and 7 554 pseudogenes. Using new interface and genome viewers of R-loopDB, users can search the gene(s) in multiple species with keywords in a single query. R-loopDB provides tools to carry out comparative evolution and genome-scale analyses in R-loop biology.

Description: RNAcentral is a database of non-coding RNA (ncRNA) sequences that aggregates data from specialised ncRNA resources and provides a single entry point for accessing ncRNA sequences of all ncRNA types from all organisms. Since its launch in 2014, RNAcentral has integrated twelve new resources, taking the total number of collaborating database to 22, and began importing new types of data, such as modified nucleotides from MODOMICS and PDB. We created new species-specific identifiers that refer to unique RNA sequences within a context of single species. The website has been subject to continuous improvements focusing on text and sequence similarity searches as well as genome browsing functionality. All RNAcentral data is provided for free and is available for browsing, bulk downloads, and programmatic access at http://rnacentral.org/ .

Description: SNP2TFBS is a computational resource intended to support researchers investigating the molecular mechanisms underlying regulatory variation in the human genome. The database essentially consists of a collection of text files providing specific annotations for human single nucleotide polymorphisms (SNPs), namely whether they are predicted to abolish, create or change the affinity of one or several transcription factor (TF) binding sites. A SNP's effect on TF binding is estimated based on a position weight matrix (PWM) model for the binding specificity of the corresponding factor. These data files are regenerated at regular intervals by an automatic procedure that takes as input a reference genome, a comprehensive SNP catalogue and a collection of PWMs. SNP2TFBS is also accessible over a web interface, enabling users to view the information provided for an individual SNP, to extract SNPs based on various search criteria, to annotate uploaded sets of SNPs or to display statistics about the frequencies of binding sites affected by selected SNPs. Homepage: http://ccg.vital-it.ch/snp2tfbs/ .

Description: The 2017 update of NGSmethDB stores whole genome methylomes generated from short-read data sets obtained by bisulfite sequencing (WGBS) technology. To generate high-quality methylomes, stringent quality controls were integrated with third-part software, adding also a two-step mapping process to exploit the advantages of the new genome assembly models. The samples were all profiled under constant parameter settings, thus enabling comparative downstream analyses. Besides a significant increase in the number of samples, NGSmethDB now includes two additional data-types, which are a valuable resource for the discovery of methylation epigenetic biomarkers: (i) differentially methylated single-cytosines; and (ii) methylation segments (i.e. genome regions of homogeneous methylation). The NGSmethDB back-end is now based on MongoDB , a NoSQL hierarchical database using JSON-formatted documents and dynamic schemas, thus accelerating sample comparative analyses. Besides conventional database dumps, track hubs were implemented, which improved database access, visualization in genome browsers and comparative analyses to third-part annotations. In addition, the database can be also accessed through a RESTful API. Lastly, a Python client and a multiplatform virtual machine allow for program-driven access from user desktop. This way, private methylation data can be compared to NGSmethDB without the need to upload them to public servers. Database website: http://bioinfo2.ugr.es/NGSmethDB .

Description: Increasing evidence has revealed that RNA subcellular localization is a very important feature for deeply understanding RNA's biological functions after being transported into intra- or extra-cellular regions. RNALocate is a web-accessible database that aims to provide a high-quality RNA subcellular localization resource and facilitate future researches on RNA function or structure. The current version of RNALocate documents more than 37 700 manually curated RNA subcellular localization entries with experimental evidence, involving more than 21 800 RNAs with 42 subcellular localizations in 65 species, mainly including Homo sapiens, Mus musculus and Saccharomyces cerevisiae etc. Besides, RNA homology, sequence and interaction data have also been integrated into RNALocate. Users can access these data through online search, browse, blast and visualization tools. In conclusion, RNALocate will be of help in elucidating the entirety of RNA subcellular localization, and developing new prediction methods. The database is available at http://www.rna-society.org/rnalocate/ .

Description: We present three clustered protein sequence databases, Uniclust90, Uniclust50, Uniclust30 and three databases of multiple sequence alignments (MSAs), Uniboost10, Uniboost20 and Uniboost30, as a resource for protein sequence analysis, function prediction and sequence searches. The Uniclust databases cluster UniProtKB sequences at the level of 90%, 50% and 30% pairwise sequence identity. Uniclust90 and Uniclust50 clusters showed better consistency of functional annotation than those of UniRef90 and UniRef50, owing to an optimised clustering pipeline that runs with our MMseqs2 software for fast and sensitive protein sequence searching and clustering. Uniclust sequences are annotated with matches to Pfam, SCOP domains, and proteins in the PDB, using our HHblits homology detection tool. Due to its high sensitivity, Uniclust contains 17% more Pfam domain annotations than UniProt. Uniboost MSAs of three diversities are built by enriching the Uniclust30 MSAs with local sequence matches from MMseqs2 profile searches through Uniclust30. All databases can be downloaded from the Uniclust server at uniclust.mmseqs.com. Users can search clusters by keywords and explore their MSAs, taxonomic representation, and annotations. Uniclust is updated every two months with the new UniProt release.

Description: Transcription factors (TFs) play a pivotal role in transcriptional regulation, making them crucial for cell survival and important biological functions. For the regulation of transcription, interactions of different regulatory proteins known as transcription co-factors (TcoFs) and TFs are essential in forming necessary protein complexes. Although TcoFs themselves do not bind DNA directly, their influence on transcriptional regulation and initiation, although indirect, has been shown to be significant, with the functionality of TFs strongly influenced by the presence of TcoFs. In the TcoF-DB v2 database, we collect information on TcoFs. In this article, we describe updates and improvements implemented in TcoF-DB v2. TcoF-DB v2 provides several new features that enables exploration of the roles of TcoFs. The content of the database has significantly expanded, and is enriched with information from Gene Ontology, biological pathways, diseases and molecular signatures. TcoF-DB v2 now includes many more TFs; has substantially increased the number of human TcoFs to 958, and now includes information on mouse (418 new TcoFs). TcoF-DB v2 enables the exploration of information on TcoFs and allows investigations into their influence on transcriptional regulation in humans and mice. TcoF-DB v2 can be accessed at http://tcofdb.org/ .

Description: InterPro ( http://www.ebi.ac.uk/interpro/ ) is a freely available database used to classify protein sequences into families and to predict the presence of important domains and sites. InterProScan is the underlying software that allows both protein and nucleic acid sequences to be searched against InterPro's predictive models, which are provided by its member databases. Here, we report recent developments with InterPro and its associated software, including the addition of two new databases (SFLD and CDD), and the functionality to include residue-level annotation and prediction of intrinsic disorder. These developments enrich the annotations provided by InterPro, increase the overall number of residues annotated and allow more specific functional inferences.

Description: The latest version of the CATH-Gene3D protein structure classification database has recently been released (version 4.1, http://www.cathdb.info ). The resource comprises over 300 000 domain structures and over 53 million protein domains classified into 2737 homologous superfamilies, doubling the number of predicted protein domains in the previous version. The daily-updated CATH-B, which contains our very latest domain assignment data, provides putative classifications for over 100 000 additional protein domains. This article describes developments to the CATH-Gene3D resource over the last two years since the publication in 2015, including: significant increases to our structural and sequence coverage; expansion of the functional families in CATH; building a support vector machine (SVM) to automatically assign domains to superfamilies; improved search facilities to return alignments of query sequences against multiple sequence alignments; the redesign of the web pages and download site.

Description: Evolutionary Classification Of protein Domains (ECOD) ( http://prodata.swmed.edu/ecod ) comprehensively classifies protein with known spatial structures maintained by the Protein Data Bank (PDB) into evolutionary groups of protein domains. ECOD relies on a combination of automatic and manual weekly updates to achieve its high accuracy and coverage with a short update cycle. ECOD classifies the approximately 120 000 depositions of the PDB into more than 500 000 domains in ~3400 homologous groups. We show the performance of the weekly update pipeline since the release of ECOD, describe improvements to the ECOD website and available search options, and discuss novel structures and homologous groups that have been classified in the recent updates. Finally, we discuss the future directions of ECOD and further improvements planned for the hierarchy and update process.

Description: In this work, we developed a database WERAM ( http://weram.biocuckoo.org/ ) for histone acetyltransferases, histone deacetylases, histone methyltransferases, histone demethylases and acetyl- or methyl-binding proteins, which catalyze, remove and recognize histone acetylation and methylation sites as ‘writers’, ‘erasers’ and ‘readers’, and synergistically determine the ‘histone code’. From the scientific literature, we totally collected over 580 experimentally identified histone regulators from eight model organisms, including Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Caenorhabditis elegans, Arabidopsis thaliana, Schizosaccharomyces pombe and Saccharomyces cerevisiae . We also collected ~900 site-specific regulator-histone relations from the eight species. According to the experimental evidence, known histone regulators were classified into distinct families. To computationally detect more proteins in eukaryotes, we constructed hidden Markov model (HMM) profiles for histone regulator families. For families without HMM profiles, we also conducted orthologous searches. Totally, WERAM database contained more than 20 thousand non-redundant histone regulators from 148 eukaryotes. The detailed annotations and classification information of histone regulators were provided, together with site-specific histone substrates if available.

Description: The database JET2 Viewer, openly accessible at http://www.jet2viewer.upmc.fr/ , reports putative protein binding sites for all three-dimensional (3D) structures available in the Protein Data Bank (PDB). This knowledge base was generated by applying the computational method JET 2 at large-scale on more than 20 000 chains. JET 2 strategy yields very precise predictions of interacting surfaces and unravels their evolutionary process and complexity. JET2 Viewer provides an online intelligent display, including interactive 3D visualization of the binding sites mapped onto PDB structures and suitable files recording JET 2 analyses. Predictions were evaluated on more than 15 000 experimentally characterized protein interfaces. This is, to our knowledge, the largest evaluation of a protein binding site prediction method. The overall performance of JET 2 on all interfaces are: Sen = 52.52, PPV = 51.24, Spe = 80.05, Acc = 75.89. The data can be used to foster new strategies for protein–protein interactions modulation and interaction surface redesign.

Description: RepeatsDB 2.0 (URL: http://repeatsdb.bio.unipd.it/ ) is an update of the database of annotated tandem repeat protein structures. Repeat proteins are a widespread class of non-globular proteins carrying heterogeneous functions involved in several diseases. Here we provide a new version of RepeatsDB with an improved classification schema including high quality annotations for ~5400 protein structures. RepeatsDB 2.0 features information on start and end positions for the repeat regions and units for all entries. The extensive growth of repeat unit characterization was possible by applying the novel ReUPred annotation method over the entire Protein Data Bank, with data quality is guaranteed by an extensive manual validation for 〉60% of the entries. The updated web interface includes a new search engine for complex queries and a fully re-designed entry page for a better overview of structural data. It is now possible to compare unit positions, together with secondary structure, fold information and Pfam domains. Moreover, a new classification level has been introduced on top of the existing scheme as an independent layer for sequence similarity relationships at 40%, 60% and 90% identity.

Description: All cellular life contains an extensive array of membrane transport proteins. The vast majority of these transporters have not been experimentally characterized. We have developed a bioinformatic pipeline to identify and annotate complete sets of transporters in any sequenced genome. This pipeline is now fully automated enabling it to better keep pace with the accelerating rate of genome sequencing. This manuscript describes TransportDB 2.0 ( http://www.membranetransport.org/transportDB2/ ), a completely updated version of TransportDB, which provides access to the large volumes of data generated by our automated transporter annotation pipeline. The TransportDB 2.0 web portal has been rebuilt to utilize contemporary JavaScript libraries, providing a highly interactive interface to the annotation information, and incorporates analysis tools that enable users to query the database on a number of levels. For example, TransportDB 2.0 includes tools that allow users to select annotated genomes of interest from the thousands of species held in the database and compare their complete transporter complements.

Description: SWISS-MODEL Repository (SMR) is a database of annotated 3D protein structure models generated by the automated SWISS-MODEL homology modeling pipeline. It currently holds 〉400 000 high quality models covering almost 20% of Swiss-Prot/UniProtKB entries. In this manuscript, we provide an update of features and functionalities which have been implemented recently. We address improvements in target coverage, model quality estimates, functional annotations and improved in-page visualization. We also introduce a new update concept which includes regular updates of an expanded set of core organism models and UniProtKB-based targets, complemented by user-driven on-demand update of individual models. With the new release of the modeling pipeline, SMR has implemented a REST-API and adopted an open licencing model for accessing model coordinates, thus enabling bulk download for groups of targets fostering re-use of models in other contexts. SMR can be accessed at https://swissmodel.expasy.org/repository .

Description: The Database of Protein Disorder (DisProt, URL: www.disprot.org ) has been significantly updated and upgraded since its last major renewal in 2007. The current release holds information on more than 800 entries of IDPs/IDRs, i.e. intrinsically disordered proteins or regions that exist and function without a well-defined three-dimensional structure. We have re-curated previous entries to purge DisProt from conflicting cases, and also upgraded the functional classification scheme to reflect continuous advance in the field in the past 10 years or so. We define IDPs as proteins that are disordered along their entire sequence, i.e. entirely lack structural elements, and IDRs as regions that are at least five consecutive residues without well-defined structure. We base our assessment of disorder strictly on experimental evidence, such as X-ray crystallography and nuclear magnetic resonance (primary techniques) and a broad range of other experimental approaches (secondary techniques). Confident and ambiguous annotations are highlighted separately. DisProt 7.0 presents classified knowledge regarding the experimental characterization and functional annotations of IDPs/IDRs, and is intended to provide an invaluable resource for the research community for a better understanding structural disorder and for developing better computational tools for studying disordered proteins.

Description: The Protein Circular Dichroism Data Bank (PCDDB) has been in operation for more than 5 years as a public repository for archiving circular dichroism spectroscopic data and associated bioinformatics and experimental metadata. Since its inception, many improvements and new developments have been made in data display, searching algorithms, data formats, data content, auxillary information, and validation techniques, as well as, of course, an increase in the number of holdings. It provides a site ( http://pcddb.cryst.bbk.ac.uk ) for authors to deposit experimental data as well as detailed information on methods and calculations associated with published work. It also includes links for each entry to bioinformatics databases. The data are freely available to accessors either as single files or as complete data bank downloads. The PCDDB has found broad usage by the structural biology, bioinformatics, analytical and pharmaceutical communities, and has formed the basis for new software and methods developments.

Description: The Membranome database was developed to assist analysis and computational modeling of single-pass (bitopic) transmembrane (TM) proteins and their complexes by providing structural information about these proteins on a genomic scale. The database currently collects data on 〉6000 bitopic proteins from Homo sapiens, Arabidopsis thaliana, Dictyostelium discoideum, Saccharomyces cerevisiae, Escherichia coli and Methanocaldococcus jannaschii . It presents the following data: (i) hierarchical classification of bitopic proteins into 15 functional classes, 689 structural superfamilies and 1404 families; (ii) 446 complexes of bitopic proteins with known three-dimensional (3D) structures classified into 129 families; (iii) computationally generated three-dimensional models of TM α-helices positioned in membranes; (iv) amino acid sequences, domain architecture, functional annotation and available experimental structures of bitopic proteins; (v) TM topology and intracellular localization, (vi) physical interactions between proteins from the database along with links to other resources. The database is freely accessible at http://membranome.org . There is a variety of options for browsing, sorting, searching and retrieval of the content, including downloadable coordinate files of TM domains with calculated membrane boundaries.

Description: The TSTMP database is designed to help the target selection of human transmembrane proteins for structural genomics projects and structure modeling studies. Currently, there are only 60 known 3D structures among the polytopic human transmembrane proteins and about a further 600 could be modeled using existing structures. Although there are a great number of human transmembrane protein structures left to be determined, surprisingly only a small fraction of these proteins have ‘selected’ (or above) status according to the current version the TargetDB/TargetTrack database. This figure is even worse regarding those transmembrane proteins that would contribute the most to the structural coverage of the human transmembrane proteome. The database was built by sorting out proteins from the human transmembrane proteome with known structure and searching for suitable model structures for the remaining proteins by combining the results of a state-of-the-art transmembrane specific fold recognition algorithm and a sequence similarity search algorithm. Proteins were searched for homologues among the human transmembrane proteins in order to select targets whose successful structure determination would lead to the best structural coverage of the human transmembrane proteome. The pipeline constructed for creating the TSTMP database guarantees to keep the database up-to-date. The database is available at http://tstmp.enzim.ttk.mta.hu .

Description: The Protein Data Bank Japan (PDBj, http://pdbj.org ), a member of the worldwide Protein Data Bank (wwPDB), accepts and processes the deposited data of experimentally determined macromolecular structures. While maintaining the archive in collaboration with other wwPDB partners, PDBj also provides a wide range of services and tools for analyzing structures and functions of proteins. We herein outline the updated web user interfaces together with RESTful web services and the backend relational database that support the former. To enhance the interoperability of the PDB data, we have previously developed PDB/RDF, PDB data in the Resource Description Framework (RDF) format, which is now a wwPDB standard called wwPDB/RDF. We have enhanced the connectivity of the wwPDB/RDF data by incorporating various external data resources. Services for searching, comparing and analyzing the ever-increasing large structures determined by hybrid methods are also described.

Description: KEGG ( http://www.kegg.jp/ or http://www.genome.jp/kegg/ ) is an encyclopedia of genes and genomes. Assigning functional meanings to genes and genomes both at the molecular and higher levels is the primary objective of the KEGG database project. Molecular-level functions are stored in the KO (KEGG Orthology) database, where each KO is defined as a functional ortholog of genes and proteins. Higher-level functions are represented by networks of molecular interactions, reactions and relations in the forms of KEGG pathway maps, BRITE hierarchies and KEGG modules. In the past the KO database was developed for the purpose of defining nodes of molecular networks, but now the content has been expanded and the quality improved irrespective of whether or not the KOs appear in the three molecular network databases. The newly introduced addendum category of the GENES database is a collection of individual proteins whose functions are experimentally characterized and from which an increasing number of KOs are defined. Furthermore, the DISEASE and DRUG databases have been improved by systematic analysis of drug labels for better integration of diseases and drugs with the KEGG molecular networks. KEGG is moving towards becoming a comprehensive knowledge base for both functional interpretation and practical application of genomic information.

Description: The use of high-throughput array and sequencing technologies has produced unprecedented amounts of gene expression data in central public depositories, including the Gene Expression Omnibus (GEO). The immense amount of expression data in GEO provides both vast research opportunities and data analysis challenges. Co-expression analysis of high-dimensional expression data has proven effective for the study of gene functions, and several co-expression databases have been developed. Here, we present a new co-expression database, COEXPEDIA ( www.coexpedia.org ), which is distinctive from other co-expression databases in three aspects: (i) it contains only co-functional co-expressions that passed a rigorous statistical assessment for functional association, (ii) the co-expressions were inferred from individual studies, each of which was designed to investigate gene functions with respect to a particular biomedical context such as a disease and (iii) the co-expressions are associated with medical subject headings (MeSH) that provide biomedical information for anatomical, disease, and chemical relevance. COEXPEDIA currently contains approximately eight million co-expressions inferred from 384 and 248 GEO series for humans and mice, respectively. We describe how these MeSH-associated co-expressions enable the identification of diseases and drugs previously unknown to be related to a gene or a gene group of interest.

Description: A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein–protein association data for a large number of organisms. The associations in STRING include direct (physical) interactions, as well as indirect (functional) interactions, as long as both are specific and biologically meaningful. Apart from collecting and reassessing available experimental data on protein–protein interactions, and importing known pathways and protein complexes from curated databases, interaction predictions are derived from the following sources: (i) systematic co-expression analysis, (ii) detection of shared selective signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computational transfer of interaction knowledge between organisms based on gene orthology. In the latest version 10.5 of STRING, the biggest changes are concerned with data dissemination: the web frontend has been completely redesigned to reduce dependency on outdated browser technologies, and the database can now also be queried from inside the popular Cytoscape software framework. Further improvements include automated background analysis of user inputs for functional enrichments, and streamlined download options. The STRING resource is available online, at http://string-db.org/ .

Description: The Biological General Repository for Interaction Datasets (BioGRID: https://thebiogrid.org ) is an open access database dedicated to the annotation and archival of protein, genetic and chemical interactions for all major model organism species and humans. As of September 2016 (build 3.4.140), the BioGRID contains 1 072 173 genetic and protein interactions, and 38 559 post-translational modifications, as manually annotated from 48 114 publications. This dataset represents interaction records for 66 model organisms and represents a 30% increase compared to the previous 2015 BioGRID update. BioGRID curates the biomedical literature for major model organism species, including humans, with a recent emphasis on central biological processes and specific human diseases. To facilitate network-based approaches to drug discovery, BioGRID now incorporates 27 501 chemical–protein interactions for human drug targets, as drawn from the DrugBank database. A new dynamic interaction network viewer allows the easy navigation and filtering of all genetic and protein interaction data, as well as for bioactive compounds and their established targets. BioGRID data are directly downloadable without restriction in a variety of standardized formats and are freely distributed through partner model organism databases and meta-databases.

Description: The FAIRDOMHub is a repository for publishing FAIR (Findable, Accessible, Interoperable and Reusable) Data, Operating procedures and Models ( https://fairdomhub.org/ ) for the Systems Biology community. It is a web-accessible repository for storing and sharing systems biology research assets. It enables researchers to organize, share and publish data, models and protocols, interlink them in the context of the systems biology investigations that produced them, and to interrogate them via API interfaces. By using the FAIRDOMHub, researchers can achieve more effective exchange with geographically distributed collaborators during projects, ensure results are sustained and preserved and generate reproducible publications that adhere to the FAIR guiding principles of data stewardship.

Description: Despite progress in understanding microbial biogeography of surface soils, few studies have investigated depth-dependent distributions of terrestrial microorganisms in subsoils. We leveraged high-throughput sequencing of 16S rRNA genes obtained from soils collected from the rare Charitable Research Reserve (Cambridge, ON, Canada) to assess the influence of depth on bacterial communities across various land-use types. Although bacterial communities were strongly influenced by depth across all sites, the magnitude of this influence was variable and demonstrated that land-use attributes also played a significant role in shaping soil bacterial communities. Soil pH exhibited a large gradient across samples and strongly influenced shifts in bacterial communities with depth and across different land-use systems, especially considering that physicochemical conditions showed generally consistent trends with depth. We observed significant ( p ≤ 0.001) and strongly correlated taxa with depth and pH, with a strong predominance of positively depth-correlated OTUs without cultured representatives. These findings highlight the importance of depth in soil biogeographical surveys and that subsurface soils harbour understudied bacterial members with potentially unique and important functions in deeper soil horizons that remain to be characterized.

Description: Studies in model organisms have yielded considerable insights into the etiology of disease and our understanding of evolutionary processes. Caenorhabditis elegans is among the most powerful model organisms used to understand biology. However, C. elegans is not used as extensively as other model organisms to investigate how natural variation shapes traits, especially through the use of genome-wide association (GWA) analyses. Here, we introduce a new platform, the C. elegans Natural Diversity Resource (CeNDR) to enable statistical genetics and genomics studies of C. elegans and to connect the results to human disease. CeNDR provides the research community with wild strains, genome-wide sequence and variant data for every strain, and a GWA mapping portal for studying natural variation in C. elegans . Additionally, researchers outside of the C. elegans community can benefit from public mappings and integrated tools for comparative analyses. CeNDR uses several databases that are continually updated through the addition of new strains, sequencing data, and association mapping results. The CeNDR data are accessible through a freely available web portal located at http://www.elegansvariation.org or through an application programming interface.

Description: The Candida Genome Database (CGD, http://www.candidagenome.org/ ) is a freely available online resource that provides gene, protein and sequence information for multiple Candida species, along with web-based tools for accessing, analyzing and exploring these data. The mission of CGD is to facilitate and accelerate research into Candida pathogenesis and biology, by curating the scientific literature in real time, and connecting literature-derived annotations to the latest version of the genomic sequence and its annotations. Here, we report the incorporation into CGD of Assembly 22, the first chromosome-level, phased diploid assembly of the C. albicans genome, coupled with improvements that we have made to the assembly using additional available sequence data. We also report the creation of systematic identifiers for C. albicans genes and sequence features using a system similar to that adopted by the yeast community over two decades ago. Finally, we describe the incorporation of JBrowse into CGD, which allows online browsing of mapped high throughput sequencing data, and its implementation for several RNA-Seq data sets, as well as the whole genome sequencing data that was used in the construction of Assembly 22.

Description: Ensembl ( www.ensembl.org ) is a database and genome browser for enabling research on vertebrate genomes. We import, analyse, curate and integrate a diverse collection of large-scale reference data to create a more comprehensive view of genome biology than would be possible from any individual dataset. Our extensive data resources include evidence-based gene and regulatory region annotation, genome variation and gene trees. An accompanying suite of tools, infrastructure and programmatic access methods ensure uniform data analysis and distribution for all supported species. Together, these provide a comprehensive solution for large-scale and targeted genomics applications alike. Among many other developments over the past year, we have improved our resources for gene regulation and comparative genomics, and added CRISPR/Cas9 target sites. We released new browser functionality and tools, including improved filtering and prioritization of genome variation, Manhattan plot visualization for linkage disequilibrium and eQTL data, and an ontology search for phenotypes, traits and disease. We have also enhanced data discovery and access with a track hub registry and a selection of new REST end points. All Ensembl data are freely released to the scientific community and our source code is available via the open source Apache 2.0 license.

Description: Over the past years, CRISPR/Cas9 mediated genome editing has developed into a powerful tool for modifying genomes in various organisms. In high-throughput screens, CRISPR/Cas9 mediated gene perturbations can be used for the systematic functional analysis of whole genomes. Discoveries from such screens provide a wealth of knowledge about gene to phenotype relationships in various biological model systems. However, a database resource to query results efficiently has been lacking. To this end, we developed GenomeCRISPR ( http://genomecrispr.org ), a database for genome-scale CRISPR/Cas9 screens. Currently, GenomeCRISPR contains data on more than 550 000 single guide RNAs (sgRNA) derived from 84 different experiments performed in 48 different human cell lines, comprising all screens in human cells using CRISPR/Cas published to date. GenomeCRISPR provides data mining options and tools, such as gene or genomic region search. Phenotypic and genome track views allow users to investigate and compare the results of different screens, or the impact of different sgRNAs on the gene of interest. An Application Programming Interface (API) allows for automated data access and batch download. As more screening data will become available, we also aim at extending the database to include functional genomic data from other organisms and enable cross-species comparisons.

Description: Manteia is an integrative database available online at http://manteia.igbmc.fr which provides a large array of OMICs data related to the development of the mouse, chicken, zebrafish and human. The system is designed to use different types of data together in order to perform advanced datamining, test hypotheses or provide candidate genes involved in biological processes or responsible for human diseases. In this new version of the database, Manteia has been enhanced with new expression data originating from microarray and next generation sequencing experiments. In addition, the system includes new statistics tools to analyze lists of genes in order to compare their functions and highlight their specific features. One of the main novelties of this release is the integration of a machine learning tool called Lookalike that we have developed to analyze the different datasets present in the system in order to identify new disease genes. This tool identifies the key features of known disease genes to provide and rank new candidates with similar properties from the genome. It is also designed to highlight and take into account the specificities of a disease in order to increase the accuracy of its predictions.

Description: The HmtDB resource hosts a database of human mitochondrial genome sequences from individuals with healthy and disease phenotypes. The database is intended to support both population geneticists as well as clinicians undertaking the task to assess the pathogenicity of specific mtDNA mutations. The wide application of next-generation sequencing (NGS) has provided an enormous volume of high-resolution data at a low price, increasing the availability of human mitochondrial sequencing data, which called for a cogent and significant expansion of HmtDB data content that has more than tripled in the current release. We here describe additional novel features, including: (i) a complete, user-friendly restyling of the web interface, (ii) links to the command-line stand-alone and web versions of the MToolBox package, an up-to-date tool to reconstruct and analyze human mitochondrial DNA from NGS data and (iii) the implementation of the Reconstructed Sapiens Reference Sequence (RSRS) as mitochondrial reference sequence. The overall update renders HmtDB an even more handy and useful resource as it enables a more rapid data access, processing and analysis. HmtDB is accessible at http://www.hmtdb.uniba.it/ .

Description: The Gene Expression Database (GXD; www.informatics.jax.org/expression.shtml ) is an extensive and well-curated community resource of mouse developmental expression information. Through curation of the scientific literature and by collaborations with large-scale expression projects, GXD collects and integrates data from RNA in situ hybridization, immunohistochemistry, RT-PCR, northern blot and western blot experiments. Expression data from both wild-type and mutant mice are included. The expression data are combined with genetic and phenotypic data in Mouse Genome Informatics (MGI) and made readily accessible to many types of database searches. At present, GXD includes over 1.5 million expression results and more than 300 000 images, all annotated with detailed and standardized metadata. Since our last report in 2014, we have added a large amount of data, we have enhanced data and database infrastructure, and we have implemented many new search and display features. Interface enhancements include: a new Mouse Developmental Anatomy Browser; interactive tissue-by-developmental stage and tissue-by-gene matrix views; capabilities to filter and sort expression data summaries; a batch search utility; gene-based expression overviews; and links to expression data from other species.

Description: Upon the first publication of the fifth iteration of the Functional Annotation of Mammalian Genomes collaborative project, FANTOM5, we gathered a series of primary data and database systems into the FANTOM web resource ( http://fantom.gsc.riken.jp ) to facilitate researchers to explore transcriptional regulation and cellular states. In the course of the collaboration, primary data and analysis results have been expanded, and functionalities of the database systems enhanced. We believe that our data and web systems are invaluable resources, and we think the scientific community will benefit for this recent update to deepen their understanding of mammalian cellular organization. We introduce the contents of FANTOM5 here, report recent updates in the web resource and provide future perspectives.

Description: OrthoDB is a comprehensive catalog of orthologs, genes inherited by extant species from a single gene in their last common ancestor. In 2016 OrthoDB reached its 9th release, growing to over 22 million genes from over 5000 species, now adding plants, archaea and viruses. In this update we focused on usability of this fast-growing wealth of data: updating the user and programmatic interfaces to browse and query the data, and further enhancing the already extensive integration of available gene functional annotations. Collating functional annotations from over 100 resources, and enabled us to propose descriptive titles for 87% of ortholog groups. Additionally, OrthoDB continues to provide computed evolutionary annotations and to allow user queries by sequence homology. The OrthoDB resource now enables users to generate publication-quality comparative genomics charts, as well as to upload, analyze and interactively explore their own private data. OrthoDB is available from http://orthodb.org .

Description: RNA editing by A-to-I deamination is the prominent co-/post-transcriptional modification in humans. It is carried out by ADAR enzymes and contributes to both transcriptomic and proteomic expansion. RNA editing has pivotal cellular effects and its deregulation has been linked to a variety of human disorders including neurological and neurodegenerative diseases and cancer. Despite its biological relevance, many physiological and functional aspects of RNA editing are yet elusive. Here, we present REDIportal, available online at http://srv00.recas.ba.infn.it/atlas/ , the largest and comprehensive collection of RNA editing in humans including more than 4.5 millions of A-to-I events detected in 55 body sites from thousands of RNAseq experiments. REDIportal embeds RADAR database and represents the first editing resource designed to answer functional questions, enabling the inspection and browsing of editing levels in a variety of human samples, tissues and body sites. In contrast with previous RNA editing databases, REDIportal comprises its own browser (JBrowse) that allows users to explore A-to-I changes in their genomic context, empathizing repetitive elements in which RNA editing is prominent.

Description: The Zebrafish Model Organism Database (ZFIN; http://zfin.org ) is the central resource for zebrafish ( Danio rerio) genetic, genomic, phenotypic and developmental data. ZFIN curators provide expert manual curation and integration of comprehensive data involving zebrafish genes, mutants, transgenic constructs and lines, phenotypes, genotypes, gene expressions, morpholinos, TALENs, CRISPRs, antibodies, anatomical structures, models of human disease and publications. We integrate curated, directly submitted, and collaboratively generated data, making these available to zebrafish research community. Among the vertebrate model organisms, zebrafish are superbly suited for rapid generation of sequence-targeted mutant lines, characterization of phenotypes including gene expression patterns, and generation of human disease models. The recent rapid adoption of zebrafish as human disease models is making management of these data particularly important to both the research and clinical communities. Here, we describe recent enhancements to ZFIN including use of the zebrafish experimental conditions ontology, ‘Fish’ records in the ZFIN database, support for gene expression phenotypes, models of human disease, mutation details at the DNA, RNA and protein levels, and updates to the ZFIN single box search.

Description: Autoantibodies refer to antibodies that target self-antigens, which can play pivotal roles in maintaining homeostasis, distinguishing normal from tumor tissue and trigger autoimmune diseases. In the last three decades, tremendous efforts have been devoted to elucidate the generation, evolution and functions of autoantibodies, as well as their target autoantigens. However, reports of these countless previously identified autoantigens are randomly dispersed in the literature. Here, we constructed an AAgAtlas database 1.0 using text-mining and manual curation. We extracted 45 830 autoantigen-related abstracts and 94 313 sentences from PubMed using the keywords of either ‘autoantigen’ or ‘autoantibody’ or their lexical variants, which were further refined to 25 520 abstracts, 43 253 sentences and 3984 candidates by our bio-entity recognizer based on the Protein Ontology. Finally, we identified 1126 genes as human autoantigens and 1071 related human diseases, with which we constructed a human autoantigen database (AAgAtlas database 1.0). The database provides a user-friendly interface to conveniently browse, retrieve and download human autoantigens as well as their associated diseases. The database is freely accessible at http://biokb.ncpsb.org/aagatlas/ . We believe this database will be a valuable resource to track and understand human autoantigens as well as to investigate their functions in basic and translational research.

Description: COSMIC, the Catalogue of Somatic Mutations in Cancer ( http://cancer.sanger.ac.uk ) is a high-resolution resource for exploring targets and trends in the genetics of human cancer. Currently the broadest database of mutations in cancer, the information in COSMIC is curated by expert scientists, primarily by scrutinizing large numbers of scientific publications. Over 4 million coding mutations are described in v78 (September 2016), combining genome-wide sequencing results from 28 366 tumours with complete manual curation of 23 489 individual publications focused on 186 key genes and 286 key fusion pairs across all cancers. Molecular profiling of large tumour numbers has also allowed the annotation of more than 13 million non-coding mutations, 18 029 gene fusions, 187 429 genome rearrangements, 1 271 436 abnormal copy number segments, 9 175 462 abnormal expression variants and 7 879 142 differentially methylated CpG dinucleotides. COSMIC now details the genetics of drug resistance, novel somatic gene mutations which allow a tumour to evade therapeutic cancer drugs. Focusing initially on highly characterized drugs and genes, COSMIC v78 contains wide resistance mutation profiles across 20 drugs, detailing the recurrence of 301 unique resistance alleles across 1934 drug-resistant tumours. All information from the COSMIC database is available freely on the COSMIC website.

Description: De novo germline mutations (DNMs) are the rarest genetic variants proven to cause a considerable number of sporadic genetic diseases, such as autism spectrum disorders, epileptic encephalopathy, schizophrenia, congenital heart disease, type 1 diabetes, and hearing loss. However, it is difficult to accurately assess the cause of DNMs and identify disease-causing genes from the considerable number of DNMs in probands. A common method to this problem is to identify genes that harbor significantly more DNMs than expected by chance, with accurate background DNM rate (DNMR) required. Therefore, in this study, we developed a novel database named mirDNMR for the collection of gene-centered background DNMRs obtained from different methods and population variation data. The database has the following functions: (i) browse and search the background DNMRs of each gene predicted by four different methods, including GC content (DNMR-GC), sequence context (DNMR-SC), multiple factors (DNMR-MF) and local DNA methylation level (DNMR-DM); (ii) search variant frequencies in publicly available databases, including ExAC, ESP6500, UK10K, 1000G and dbSNP and (iii) investigate the DNM burden to prioritize candidate genes based on the four background DNMRs using three statistical methods (TADA, Binomial and Poisson test). As a case study, we successfully employed our database in candidate gene prioritization for a sporadic complex disease: intellectual disability. In conclusion, mirDNMR ( https://www.wzgenomics.cn/mirdnmr/ ) can be widely used to identify the genetic basis of sporadic genetic diseases.

Description: Glycosaminoglycans (GAGs) are linear polysaccharides comprised of disaccharide repeat units, a hexuronic acid, glucuronic acid or iduronic acid, linked to a hexosamine, N -acetylglucosamine (GlcNAc) or N -acetylgalactosamine. GAGs undergo further modification such as epimerization and sulfation. These polysaccharides are abundant in the extracellular matrix and connective tissues. GAGs function in stabilization of the fibrillar extracellular matrix, control of hydration, regulation of tissue, organism development by controlling cell cycle, cell behavior and differentiation. Niche adapted bacteria express enzymes called polysaccharide lyases (PL), which degrade GAGs for their nutrient content. PL have been classified into 24 sequence-related families. Comparison of 3D structures of the prototypic members of these families allowed identification of distant evolutionary relationships between lyases that were unrecognized at the sequence level, and identified occurrences of convergent evolution. We have characterized structurally and enzymatically heparinase III from Bacteroides thetaiotaomicron (BtHepIII; gene BT4657), which is classified within the PL12 family. BtHepIII is a 72.5 kDa protein. We present the X-ray structures of two crystal forms of BtHepIII at resolution 1.8 and 2.4 Å. BtHepIII contains two domains, the N-terminal α-helical domain forming a toroid and the C-terminal β-sheet domain. Comparison with recently determined structures of two other heparinases from the same PL12 family allowed us to identify structural flexibility in the arrangement of the domains indicating open–close movement. Based on comparison with other GAG lyases, we identified Tyr301 as the main catalytic residue and confirmed this by site-directed mutagenesis. We have characterized substrate preference of BtHepIII toward sulfate-poor heparan sulfate substrate.

Description: Sialyltransferases are a family of 20 gene products in mice and humans that transfer sialic acid from its activated precursor, CMP-sialic acid, to the terminus of glycoprotein and glycolipid acceptors. ST3Gal-II (coded by the St3gal2 gene) transfers sialic acid preferentially to the three positions of galactose on the Galβ1-3GalNAc terminus of gangliosides GM1 and GD1b to synthesize GD1a and GT1b, respectively. Mice with a targeted disruption of St3gal2 unexpectedly displayed late-onset obesity and insulin resistance. At 3 months of age, St3gal2 -null mice were the same weight as their wild type (WT) counterparts, but by 13 months on standard chow they were visibly obese, 22% heavier and with 37% greater fat/lean ratio than WT mice. St3gal2 -null mice became hyperglycemic and displayed impaired glucose tolerance by 9 months of age. They had sharply reduced insulin responsiveness despite equivalent pancreatic islet morphology. Analyses of insulin receptor (IR) tyrosine kinase substrate IRS-1 and downstream target Akt revealed decreased insulin-induced phosphorylation in adipose tissue but not liver or skeletal muscle of St3gal2 -null mice. Thin-layer chromatography and mass spectrometry revealed altered ganglioside profiles in the adipose tissue of St3gal2 -null mice compared to WT littermates. Metabolically, St3gal2 -null mice display a reduced respiratory exchange ratio compared to WT mice, indicating a preference for lipid oxidation as an energy source. Despite their altered metabolism, St3gal2 -null mice were hyperactive. We conclude that altered ganglioside expression in adipose tissue results in diminished IR sensitivity and late-onset obesity.

Description: Hyaluronan synthases (HAS) normally make large (〉MDa) hyaluronan (HA) products. Smaller HA fragments (e.g. 100–400 kDa) produced in vivo are associated with inflammation and cell signaling by HA receptors that bind small, but not large, HA. Although HA fragments can arise from breakdown by hyaluronidases, HAS might also be regulated directly to synthesize small HA. Here we examined the Streptococcus equisimilis HAS (SeHAS) C-terminus, which contains a tandem B-X 7 -B motif (K 398 -X 7 -R 406 -X 7 -K 414 ), by testing the effects of 27 site-specific scanning mutations and 7 C-terminal truncations on HA synthesis activity and weight-average mass. Although HAS enzymes cannot be HA-binding proteins, these motifs are highly conserved within the Class I HAS family. Fifteen Arg 406 mutants made large MDa HA (86–110% wildtype size), with specific activities from 70% to 177% of wildtype. In contrast, 10 of 12 Lys 398 mutants made HA that was 8–14% of wildtype size (≤250–480 kDa), with specific activities from 14% to 64% of wildtype. Four nearly inactive (2% wildtype activity) C-terminal truncation mutants made MDa HA (56–71% wildtype). The results confirm earlier findings with Cys-mutants [Weigel PH, Baggenstoss BA. 2012. Hyaluronan synthase polymerizing activity and control of product size are discrete enzyme functions that can be uncoupled by mutagenesis of conserved cysteines. Glycobiology 22:1302–1310] that HAS uses two independent activities to control HA size and HA synthesis rate; these are two separate functions. We conclude that HAS regulatory modifications that alter tandem B-X 7 -B motif conformation could mimic these mutagenesis-induced effects, allowing HAS in vivo to make small HA directly. The results also support a model in which the tandem-motif region is part of the intra-HAS pore and interacts directly with HA.

Description: The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET ( http://www.disgenet.org ), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype–phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.

Description: The MalaCards human disease database ( http://www.malacards.org/ ) is an integrated compendium of annotated diseases mined from 68 data sources. MalaCards has a web card for each of ~20 000 disease entries, in six global categories. It portrays a broad array of annotation topics in 15 sections, including Summaries, Symptoms, Anatomical Context, Drugs, Genetic Tests, Variations and Publications. The Aliases and Classifications section reflects an algorithm for disease name integration across often-conflicting sources, providing effective annotation consolidation. A central feature is a balanced Genes section, with scores reflecting the strength of disease-gene associations. This is accompanied by other gene-related disease information such as pathways, mouse phenotypes and GO-terms, stemming from MalaCards’ affiliation with the GeneCards Suite of databases. MalaCards’ capacity to inter-link information from complementary sources, along with its elaborate search function, relational database infrastructure and convenient data dumps, allows it to tackle its rich disease annotation landscape, and facilitates systems analyses and genome sequence interpretation. MalaCards adopts a ‘flat’ disease-card approach, but each card is mapped to popular hierarchical ontologies (e.g. International Classification of Diseases, Human Phenotype Ontology and Unified Medical Language System) and also contains information about multi-level relations among diseases, thereby providing an optimal tool for disease representation and scrutiny.

Description: The FlyRNAi database of the Drosophila RNAi Screening Center (DRSC) and Transgenic RNAi Project (TRiP) at Harvard Medical School and associated DRSC/TRiP Functional Genomics Resources website ( http://fgr.hms.harvard.edu ) serve as a reagent production tracking system, screen data repository, and portal to the community. Through this portal, we make available protocols, online tools, and other resources useful to researchers at all stages of high-throughput functional genomics screening, from assay design and reagent identification to data analysis and interpretation. In this update, we describe recent changes and additions to our website, database and suite of online tools. Recent changes reflect a shift in our focus from a single technology (RNAi) and model species ( Drosophila ) to the application of additional technologies (e.g. CRISPR) and support of integrated, cross-species approaches to uncovering gene function using functional genomics and other approaches.

Description: The Human Induced Pluripotent Stem Cell Initiative (HipSci) isf establishing a large catalogue of human iPSC lines, arguably the most well characterized collection to date. The HipSci portal enables researchers to choose the right cell line for their experiment, and makes HipSci's rich catalogue of assay data easy to discover and reuse. Each cell line has genomic, transcriptomic, proteomic and cellular phenotyping data. Data are deposited in the appropriate EMBL-EBI archives, including the European Nucleotide Archive (ENA), European Genome-phenome Archive (EGA), ArrayExpress and PRoteomics IDEntifications (PRIDE) databases. The project will make 500 cell lines from healthy individuals, and from 150 patients with rare genetic diseases; these will be available through the European Collection of Authenticated Cell Cultures (ECACC). As of August 2016, 238 cell lines are available for purchase. Project data is presented through the HipSci data portal ( http://www.hipsci.org/lines ) and is downloadable from the associated FTP site ( ftp://ftp.hipsci.ebi.ac.uk/vol1/ftp ). The data portal presents a summary matrix of the HipSci cell lines, showing available data types. Each line has its own page containing descriptive metadata, quality information, and links to archived assay data. Analysis results are also available in a Track Hub, allowing visualization in the context of public genomic annotations ( http://www.hipsci.org/data/trackhubs ).

Description: A cornerstone of modern biomedical research is the use of animal models to study disease mechanisms and to develop new therapeutic approaches. In order to help the research community to better explore the similarities and differences of genomic response between human inflammatory diseases and murine models, we developed KERIS: kaleidoscope of gene responses to inflammation between species (available at http://www.igenomed.org/keris/ ). As of June 2016, KERIS includes comparisons of the genomic response of six human inflammatory diseases (burns, trauma, infection, sepsis, endotoxin and acute respiratory distress syndrome) and matched mouse models, using 2257 curated samples from the Inflammation and the Host Response to Injury Glue Grant studies and other representative studies in Gene Expression Omnibus. A researcher can browse, query, visualize and compare the response patterns of genes, pathways and functional modules across different diseases and corresponding murine models. The database is expected to help biologists choosing models when studying the mechanisms of particular genes and pathways in a disease and prioritizing the translation of findings from disease models into clinical studies.

Description: The Mouse Genome Database (MGD: http://www.informatics.jax.org ) is the primary community data resource for the laboratory mouse. It provides a highly integrated and highly curated system offering a comprehensive view of current knowledge about mouse genes, genetic markers and genomic features as well as the associations of those features with sequence, phenotypes, functional and comparative information, and their relationships to human diseases. MGD continues to enhance access to these data, to extend the scope of data content and visualizations, and to provide infrastructure and user support that ensures effective and efficient use of MGD in the advancement of scientific knowledge. Here, we report on recent enhancements made to the resource and new features.

Description: The correlation of phenotypic outcomes with genetic variation and environmental factors is a core pursuit in biology and biomedicine. Numerous challenges impede our progress: patient phenotypes may not match known diseases, candidate variants may be in genes that have not been characterized, model organisms may not recapitulate human or veterinary diseases, filling evolutionary gaps is difficult, and many resources must be queried to find potentially significant genotype–phenotype associations. Non-human organisms have proven instrumental in revealing biological mechanisms. Advanced informatics tools can identify phenotypically relevant disease models in research and diagnostic contexts. Large-scale integration of model organism and clinical research data can provide a breadth of knowledge not available from individual sources and can provide contextualization of data back to these sources. The Monarch Initiative ( monarchinitiative.org ) is a collaborative, open science effort that aims to semantically integrate genotype–phenotype data from many species and sources in order to support precision medicine, disease modeling, and mechanistic exploration. Our integrated knowledge graph, analytic tools, and web services enable diverse users to explore relationships between phenotypes and genotypes across species.

Description: DrugCentral ( http://drugcentral.org ) is an open-access online drug compendium. DrugCentral integrates structure, bioactivity, regulatory, pharmacologic actions and indications for active pharmaceutical ingredients approved by FDA and other regulatory agencies. Monitoring of regulatory agencies for new drugs approvals ensures the resource is up-to-date. DrugCentral integrates content for active ingredients with pharmaceutical formulations, indexing drugs and drug label annotations, complementing similar resources available online. Its complementarity with other online resources is facilitated by cross referencing to external resources. At the molecular level, DrugCentral bridges drug-target interactions with pharmacological action and indications. The integration with FDA drug labels enables text mining applications for drug adverse events and clinical trial information. Chemical structure overlap between DrugCentral and five online drug resources, and the overlap between DrugCentral FDA-approved drugs and their presence in four different chemical collections, are discussed. DrugCentral can be accessed via the web application or downloaded in relational database format.

Description: The human disease methylation database (DiseaseMeth,  http://bioinfo.hrbmu.edu.cn/diseasemeth/ ) is an interactive database that aims to present the most complete collection and annotation of aberrant DNA methylation in human diseases, especially various cancers. Recently, the high-throughput microarray and sequencing technologies have promoted the production of methylome data that contain comprehensive knowledge of human diseases. In this DiseaseMeth update, we have increased the number of samples from 3610 to 32 701, the number of diseases from 72 to 88 and the disease–gene associations from 216 201 to 679 602. DiseaseMeth version 2.0 provides an expanded comprehensive list of disease–gene associations based on manual curation from experimental studies and computational identification from high-throughput methylome data. Besides the data expansion, we also updated the search engine and visualization tools. In particular, we enhanced the differential analysis tools, which now enable online automated identification of DNA methylation abnormalities in human disease in a case-control or disease–disease manner. To facilitate further mining of the disease methylome, three new web tools were developed for cluster analysis, functional annotation and survival analysis. DiseaseMeth version 2.0 should be a useful resource platform for further understanding the molecular mechanisms of human diseases.

Description: Glycoside hydrolases (GHs) are enzymes that catalyze the hydrolysis of glycosidic bonds in glycoconjugates, oligo- and polysaccharides. A classification of these enzymes based on conserved sequence and structure motifs supported by the Carbohydrate Active Enzyme (CAZy) database has proven useful in the systematic groupings of similar enzymes into families. The human pathogen Mycobacterium tuberculosis employs 30 GHs to perform a variety of different functions, which can be divided into four broad categories: α-glucan metabolism, peptidoglycan remodeling, β-glycan hydrolysis and α-demannosylation. The review presented here shows how the GHs that have been characterized play a role in each category. Expanding the genomic analysis of GH presence to other Mycobacterium species has highlighted the importance of certain families—most notably GH13 and GH23—in the general genomic make-up of mycobacteria. Since many GHs are still uncharacterized and considered as "conserved hypothetical" proteins, the grouping of them into respective families provides a strong prediction on their putative biological functions.

Description: Glycosylation is a group of post-translational modifications that displays a large variety of structures and are implicated in a plethora of biological processes. Therefore, studying glycosylation requires different technical approaches and reliable tools, lectins being part of them. Here, we describe the use of the recombinant mushroom lectin PVL to discriminate O -GlcNAcylation, a modification consisting in the attachment of a single N -acetylglucosamine residue to proteins confined within the cytosolic, nuclear and mitochondrial compartments. Recombinant PVL ( Psathyrella velutina lectin) (rPVL) displays significantly stronger affinity for GlcNAc over Neu5Ac residues as verified by thermal shift assays and surface plasmon resonance experiments, being therefore an excellent alternative to WGA (wheat germ agglutinin). Labeling of rPVL with biotin or HRP (horseradish peroxidase) allows its useful and efficient utilization by western blot. The staining of whole cell lysates with  labeled-rPVL was dramatically decreased in response to O -GlcNAc transferase knockdown and seen to increase after pharmacological blockade of O -GlcNAcase. Also, HRP-rPVL seemed to be more sensitive than the anti- O -GlcNAc antibody RL2. Thus, rPVL is a potent new tool to selectively detect O -GlcNAcylated proteins.

Description: The thermostable β-glucosidase from Thermotoga neapolitana , Tn Bgl3B, is a monomeric three-domain representative from glycoside hydrolase family 3. By using chemical reactivation with exogenous nucleophiles in previous studies with Tn Bg13B, the catalytic nucleophile (D242) and corresponding acid/base residue (E458) were determined. Identifying these residues led to the attempt of converting Tn Bgl3B into a β-glucosynthase, where three nucleophilic variants were created ( Tn Bgl3B_D242G, Tn Bgl3B_D242A, Tn Bgl3B_D242S) and all of them failed to exhibit glucosynthase activity. A deeper analysis of the Tn Bgl3B active site led to the generation of three additional variants, each of which received a single-point mutation. Two of these variants were altered at the –1 subsite (Y210F, W243F) and the third received a substitution near the binding site's aglycone region (N248R). Kinetic evaluation of these three variants revealed that W243F substitution reduced hydrolytic turnover while maintaining K M . This key W243F mutation was then introduced into the original nucleophile variants and the resulting double mutants were successfully converted into β-glucosynthases that were assayed using two separate biosynthetic methods. The first reaction used an α-glucosyl fluoride donor with a 4-nitrophenyl-β- d -glucopyranoside (4NPGlc) acceptor, and the second used 4NPGlc as both the donor and acceptor in the presence of the exogenous nucleophile formate. The primary specificity observed was a β-1,3-linked disaccharide product, while a secondary β-1,4-linked disaccharide product was observed with increased incubation times. Additional analysis revealed that substituting quercetin-3-glycoside for the second reaction's acceptor molecule resulted in the successful production of quercetin-3,4'-diglycosides with yields up to 40%.

Description: Polypeptide GalNAc-transferases (GalNAc-Ts) constitute a family of 20 human glycosyltransferases (comprising 9 subfamilies), which initiate mucin-type O- glycosylation. The O -glycoproteome is thought to be differentially regulated via the different substrate specificities and expression patterns of each GalNAc-T isoforms. Here, we present a comprehensive in vitro analysis of the peptide substrate specificity of GalNAc-T13, showing that it essentially overlaps with the ubiquitous expressed GalNAc-T1 isoform found in the same subfamily as T13. We have also identified and partially characterized nine splice variants of GalNAc-T13, which add further complexity to the GalNAc-T family. Two variants with changes in their lectin domains were characterized by in vitro glycosylation assays, and one (39Ex9) was inactive while the second one (Ex10b) had essentially unaltered activity. We used reverse transcription-polymerase chain reaction analysis of human neuroblastoma cell lines, normal brain and a small panel of neuroblastoma tumors to demonstrate that several splice variants (Ex10b, Ex9, Ex2-7 and Ex6/8-39bpEx9) were highly expressed in tumor cell lines compared with normal brain, although the functional implications remain to be unveiled. In summary, the GalNAc-T13 isoform is predicted to function similarly to GalNAc-T1 against peptide substrates in vivo, in contrast to a prior report, but is unique by being selectively expressed in the brain.

Description: AtPID ( Arabidopsis thaliana P rotein I nteractome D atabase, available at http://www.megabionet.org/atpid ) is an integrated database resource for protein interaction network and functional annotation. In the past few years, we collected 5564 mutants with significant morphological alterations and manually curated them to 167 plant ontology (PO) morphology categories. These single/multiple-gene mutants were indexed and linked to 3919 genes. After integrated these genotype–phenotype associations with the comprehensive protein interaction network in AtPID, we developed a Naïve Bayes method and predicted 4457 novel high confidence gene-PO pairs with 1369 genes as the complement. Along with the accumulated novel data for protein interaction and functional annotation, and the updated visualization toolkits, we present a genome-scale resource for genotype–phenotype associations for Arabidopsis in AtPID 5.0. In our updated website, all the new genotype–phenotype associations from mutants, protein network, and the protein annotation information can be vividly displayed in a comprehensive network view, which will greatly enhance plant protein function and genotype–phenotype association studies in a systematical way.

Description: We describe updates to the Rice SNP-Seek Database since its first release. We ran a new SNP-calling pipeline followed by filtering that resulted in complete, base, filtered and core SNP datasets. Besides the Nipponbare reference genome, the pipeline was run on genome assemblies of IR 64, 93-11, DJ 123 and Kasalath. New genotype query and display features are added for reference assemblies, SNP datasets and indels. JBrowse now displays BAM, VCF and other annotation tracks, the additional genome assemblies and an embedded VISTA genome comparison viewer. Middleware is redesigned for improved performance by using a hybrid of HDF5 and RDMS for genotype storage. Query modules for genotypes, varieties and genes are improved to handle various constraints. An integrated list manager allows the user to pass query parameters for further analysis. The SNP Annotator adds traits, ontology terms, effects and interactions to markers in a list. Web-service calls were implemented to access most data. These features enable seamless querying of SNP-Seek across various biological entities, a step toward semi-automated gene-trait association discovery. URL: http://snp-seek.irri.org .