Sequence-level mechanisms of human epigenome evolution.

DNA methylation and chromatin states play key roles in development and disease. However, the extent of recent evolutionary divergence in the human epigenome and the influential factors that have shaped it are poorly understood. To determine the links between genome sequence and human epigenome evolution, we examined the divergence of DNA methylation and chromatin states following segmental duplication events in the human lineage. Chromatin and DNA methylation states were found to have been generally well conserved following a duplication event, with the evolution of the epigenome largely uncoupled from the total number of genetic changes in the surrounding DNA sequence. However, the epigenome at tissue-specific, distal regulatory regions was observed to be unusually prone to diverge following duplication, with particular sequence differences, altering known sequence motifs, found to be associated with divergence in patterns of DNA methylation and chromatin. Alu elements were found to have played a particularly prominent role in shaping human epigenome evolution, and we show that human-specific AluY insertion events are strongly linked to the evolution of the DNA methylation landscape and gene expression levels, including at key neurological genes in the human brain. Studying paralogous regions within the same sample enables the study of the links between genome and epigenome evolution while controlling for biological and technical variation. We show DNA methylation and chromatin divergence between duplicated regions are linked to the divergence of particular genetic motifs, with Alu elements having played a disproportionate role in the evolution of the epigenome in the human lineage.

Properties of local interactions and their potential value in complementing genome-wide association studies.

Local interactions between neighbouring SNPs are hypothesized to be able to capture variants missing from genome-wide association studies (GWAS) via haplotype effects but have not been thoroughly explored. We have used a new high-throughput analysis tool to probe this underexplored area through full pair-wise genome scans and conventional GWAS in diastolic and systolic blood pressure and six metabolic traits in the Northern Finland Birth Cohort 1966 (NFBC1966) and the Atherosclerosis Risk in Communities study cohort (ARIC). Genome-wide significant interactions were detected in ARIC for systolic blood pressure between PLEKHA7 (a known GWAS locus for blood pressure) and GPR180 (which plays a role in vascular remodelling), and also for triglycerides as local interactions within the 11q23.3 region (replicated significantly in NFBC1966), which notably harbours several loci (BUD13, ZNF259 and APOA5) contributing to triglyceride levels. Tests of the local interactions within the 11q23.3 region conditional on the top GWAS signal suggested the presence of two independent functional variants, each with supportive evidence for their roles in gene regulation. Local interactions captured 9 additional GWAS loci identified in this study (3 significantly replicated) and 73 from previous GWAS (24 in the eight traits and 49 in related traits). We conclude that the detection of local interactions requires adequate SNP coverage of the genome and that such interactions are only likely to be detectable between SNPs in low linkage disequilibrium. Analysing local interactions is a potentially valuable complement to GWAS and can provide new insights into the biology underlying variation in complex traits.

The genomic signature of trait-associated variants.

BACKGROUND: Genome-wide association studies have identified thousands of SNP variants associated with hundreds of phenotypes. For most associations the causal variants and the molecular mechanisms underlying pathogenesis remain unknown. Exploration of the underlying functional annotations of trait-associated loci has thrown some light on their potential roles in pathogenesis. However, there are some shortcomings of the methods used to date, which may undermine efforts to prioritize variants for further analyses. Here, we introduce and apply novel methods to rigorously identify annotation classes showing enrichment or depletion of trait-associated variants taking into account the underlying associations due to co-location of different functional annotations and linkage disequilibrium. RESULTS: We assessed enrichment and depletion of variants in publicly available annotation classes such as genic regions, regulatory features, measures of conservation, and patterns of histone modifications. We used logistic regression to build a multivariate model that identified the most influential functional annotations for trait-association status of genome-wide significant variants. SNPs associated with all of the enriched annotations were 8 times more likely to be trait-associated variants than SNPs annotated with none of them. Annotations associated with chromatin state together with prior knowledge of the existence of a local expression QTL (eQTL) were the most important factors in the final logistic regression model. Surprisingly, despite the widespread use of evolutionary conservation to prioritize variants for study we find only modest enrichment of trait-associated SNPs in conserved regions. CONCLUSION: We established odds ratios of functional annotations that are more likely to contain significantly trait-associated SNPs, for the purpose of prioritizing GWAS hits for further studies. Additionally, we estimated the relative and combined influence of the different genomic annotations, which may facilitate future prioritization methods by adding substantial information.

BiForce Toolbox: powerful high-throughput computational analysis of gene-gene interactions in genome-wide association studies.

Genome-wide association studies (GWAS) have discovered many loci associated with common disease and quantitative traits. However, most GWAS have not studied the gene-gene interactions (epistasis) that could be important in complex trait genetics. A major challenge in analysing epistasis in GWAS is the enormous computational demands of analysing billions of SNP combinations. Several methods have been developed recently to address this, some using computers equipped with particular graphical processing units, most restricted to binary disease traits and all poorly suited to general usage on the most widely used operating systems. We have developed the BiForce Toolbox to address the demand for high-throughput analysis of pairwise epistasis in GWAS of quantitative and disease traits across all commonly used computer systems. BiForce Toolbox is a stand-alone Java program that integrates bitwise computing with multithreaded parallelization and thus allows rapid full pairwise genome scans via a graphical user interface or the command line. Furthermore, BiForce Toolbox incorporates additional tests of interactions involving SNPs with significant marginal effects, potentially increasing the power of detection of epistasis. BiForce Toolbox is easy to use and has been applied in multiple studies of epistasis in large GWAS data sets, identifying interesting interaction signals and pathways.

High-throughput analysis of epistasis in genome-wide association studies with BiForce.

MOTIVATION: Gene-gene interactions (epistasis) are thought to be important in shaping complex traits, but they have been under-explored in genome-wide association studies (GWAS) due to the computational challenge of enumerating billions of single nucleotide polymorphism (SNP) combinations. Fast screening tools are needed to make epistasis analysis routinely available in GWAS. RESULTS: We present BiForce to support high-throughput analysis of epistasis in GWAS for either quantitative or binary disease (case-control) traits. BiForce achieves great computational efficiency by using memory efficient data structures, Boolean bitwise operations and multithreaded parallelization. It performs a full pair-wise genome scan to detect interactions involving SNPs with or without significant marginal effects using appropriate Bonferroni-corrected significance thresholds. We show that BiForce is more powerful and significantly faster than published tools for both binary and quantitative traits in a series of performance tests on simulated and real datasets. We demonstrate BiForce in analysing eight metabolic traits in a GWAS cohort (323 697 SNPs, >4500 individuals) and two disease traits in another (>340 000 SNPs, >1750 cases and 1500 controls) on a 32-node computing cluster. BiForce completed analyses of the eight metabolic traits within 1 day, identified nine epistatic pairs of SNPs in five metabolic traits and 18 SNP pairs in two disease traits. BiForce can make the analysis of epistasis a routine exercise in GWAS and thus improve our understanding of the role of epistasis in the genetic regulation of complex traits. AVAILABILITY AND IMPLEMENTATION: The software is free and can be downloaded from http://bioinfo.utu.fi/BiForce/. CONTACT: wenhua.wei@igmm.ed.ac.uk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A genome-wide screen in human embryonic stem cells reveals novel sites of allele-specific histone modification associated with known disease loci.

BACKGROUND: Chromatin structure at a given site can differ between chromosome copies in a cell, and such imbalances in chromatin structure have been shown to be important in understanding the molecular mechanisms controlling several disease loci. Human genetic variation, DNA methylation, and disease have been intensely studied, uncovering many sites of allele-specific DNA methylation (ASM). However, little is known about the genome-wide occurrence of sites of allele-specific histone modification (ASHM) and their relationship to human disease. The aim of this study was to investigate the extent and characteristics of sites of ASHM in human embryonic stem cells (hESCs). RESULTS: Using a statistically rigorous protocol, we investigated the genomic distribution of ASHM in hESCs, and their relationship to sites of allele-specific expression (ASE) and DNA methylation. We found that, although they were rare, sites of ASHM were substantially enriched at loci displaying ASE. Many were also found at known imprinted regions, hence sites of ASHM are likely to be better markers of imprinted regions than sites of ASM. We also found that sites of ASHM and ASE in hESCs colocalize at risk loci for developmental syndromes mediated by deletions, providing insights into the etiology of these disorders. CONCLUSION: These results demonstrate the potential importance of ASHM patterns in the interpretation of disease loci, and the protocol described provides a basis for similar studies of ASHM in other cell types to further our understanding of human disease susceptibility.

Widespread signatures of recent selection linked to nucleosome positioning in the human lineage.

In this study we investigated the strengths and modes of selection associated with nucleosome positioning in the human lineage through the comparison of interspecies and intraspecies rates of divergence. We identify significant evidence for both positive and negative selection linked to human nucleosome positioning for the first time, implicating a widespread and important role for DNA sequence in the location of well-positioned nucleosomes. Selection appears to be acting on particular base substitutions to maintain optimum GC compositions in core and linker regions, with, e.g., unexpectedly elevated rates of C→T substitutions during recent human evolution at linker regions 60-90 bp from the nucleosome dyad but significant depletion of the same substitutions within nucleosome core regions. These patterns are strikingly consistent with the known relationships between genomic sequence composition and nucleosome assembly. By stratifying nucleosomes according to the GC content of their genomic neighborhood, we also show that the strength and direction of selection detected is dictated by local GC content. Intriguingly these signatures of selection are not restricted to nucleosomes in close proximity to exons, suggesting the correct positioning of nucleosomes is not only important in and around coding regions. This analysis provides strong evidence that the genomic sequences associated with nucleosomes are not evolving neutrally, and suggests that underlying DNA sequence is an important factor in nucleosome positioning. Recent signatures of selection linked to genomic features as ubiquitous as the nucleosome have important implications for human genome evolution and disease.

The retroviral proteinase active site and the N-terminus of Ddi1 are required for repression of protein secretion.

The Ddi1 protein of the yeast Saccharomyces cerevisiae is involved in numerous interactions with the ubiquitin system, which may be mediated by its N-terminal ubiquitin like domain and its C-terminal ubiquitin associated domain. Ddi1 also contains a central region with all the features of a retroviral aspartic proteinase, which was shown to be important in cell-cycle control. Here we demonstrate an additional role for this domain, along with the N-terminal region, in protein secretion. These results further substantiate the hypothesis that Ddi1 functions in vivo as a catalytically-active aspartic proteinase.

Chromatin structure and evolution in the human genome.

BACKGROUND: Evolutionary rates are not constant across the human genome but genes in close proximity have been shown to experience similar levels of divergence and selection. The higher-order organisation of chromosomes has often been invoked to explain such phenomena but previously there has been insufficient data on chromosome structure to investigate this rigorously. Using the results of a recent genome-wide analysis of open and closed human chromatin structures we have investigated the global association between divergence, selection and chromatin structure for the first time. RESULTS: In this study we have shown that, paradoxically, synonymous site divergence (dS) at non-CpG sites is highest in regions of open chromatin, primarily as a result of an increased number of transitions, while the rates of other traditional measures of mutation (intergenic, intronic and ancient repeat divergence as well as SNP density) are highest in closed regions of the genome. Analysis of human-chimpanzee divergence across intron-exon boundaries indicates that although genes in relatively open chromatin generally display little selection at their synonymous sites, those in closed regions show markedly lower divergence at their fourfold degenerate sites than in neighbouring introns and intergenic regions. Exclusion of known Exonic Splice Enhancer hexamers has little affect on the divergence observed at fourfold degenerate sites across chromatin categories; however, we show that closed chromatin is enriched with certain classes of ncRNA genes whose RNA secondary structure may be particularly important. CONCLUSION: We conclude that, overall, non-CpG mutation rates are lowest in open regions of the genome and that regions of the genome with a closed chromatin structure have the highest background mutation rate. This might reflect lower rates of DNA damage or enhanced DNA repair processes in regions of open chromatin. Our results also indicate that dS is a poor measure of mutation rates, particularly when used in closed regions of the genome, as genes in closed regions generally display relatively strong levels of selection at their synonymous sites.

Computational disease gene identification: a concert of methods prioritizes type 2 diabetes and obesity candidate genes.

Genome-wide experimental methods to identify disease genes, such as linkage analysis and association studies, generate increasingly large candidate gene sets for which comprehensive empirical analysis is impractical. Computational methods employ data from a variety of sources to identify the most likely candidate disease genes from these gene sets. Here, we review seven independent computational disease gene prioritization methods, and then apply them in concert to the analysis of 9556 positional candidate genes for type 2 diabetes (T2D) and the related trait obesity. We generate and analyse a list of nine primary candidate genes for T2D genes and five for obesity. Two genes, LPL and BCKDHA, are common to these two sets. We also present a set of secondary candidates for T2D (94 genes) and for obesity (116 genes) with 58 genes in common to both diseases.

Heterotachy in mammalian promoter evolution.

We have surveyed the evolutionary trends of mammalian promoters and upstream sequences, utilising large sets of experimentally supported transcription start sites (TSSs). With 30,969 well-defined TSSs from mouse and 26,341 from human, there are sufficient numbers to draw statistically meaningful conclusions and to consider differences between promoter types. Unlike previous smaller studies, we have considered the effects of insertions, deletions, and transposable elements as well as nucleotide substitutions. The rate of promoter evolution relative to that of control sequences has not been consistent between lineages nor within lineages over time. The most pronounced manifestation of this heterotachy is the increased rate of evolution in primate promoters. This increase is seen across different classes of mutation, including substitutions and micro-indel events. We investigated the relationship between promoter and coding sequence selective constraint and suggest that they are generally uncorrelated. This analysis also identified a small number of mouse promoters associated with the immune response that are under positive selection in rodents. We demonstrate significant differences in divergence between functional promoter categories and identify a category of promoters, not associated with conventional protein-coding genes, that has the highest rates of divergence across mammals. We find that evolutionary rates vary both on a fine scale within mammalian promoters and also between different functional classes of promoters. The discovery of heterotachy in promoter evolution, in particular the accelerated evolution of primate promoters, has important implications for our understanding of human evolution and for strategies to detect primate-specific regulatory elements.

Genome-wide analysis of mammalian promoter architecture and evolution.

Mammalian promoters can be separated into two classes, conserved TATA box-enriched promoters, which initiate at a well-defined site, and more plastic, broad and evolvable CpG-rich promoters. We have sequenced tags corresponding to several hundred thousand transcription start sites (TSSs) in the mouse and human genomes, allowing precise analysis of the sequence architecture and evolution of distinct promoter classes. Different tissues and families of genes differentially use distinct types of promoters. Our tagging methods allow quantitative analysis of promoter usage in different tissues and show that differentially regulated alternative TSSs are a common feature in protein-coding genes and commonly generate alternative N termini. Among the TSSs, we identified new start sites associated with the majority of exons and with 3' UTRs. These data permit genome-scale identification of tissue-specific promoters and analysis of the cis-acting elements associated with them.

The complexity of selection at the major primate beta-defensin locus.

BACKGROUND: We have examined the evolution of the genes at the major human beta-defensin locus and the orthologous loci in a range of other primates and mouse. For the first time these data allow us to examine selective episodes in the more recent evolutionary history of this locus as well as the ancient past. We have used a combination of maximum likelihood based tests and a maximum parsimony based sliding window approach to give a detailed view of the varying modes of selection operating at this locus. RESULTS: We provide evidence for strong positive selection soon after the duplication of these genes within an ancestral mammalian genome. Consequently variable selective pressures have acted on beta-defensin genes in different evolutionary lineages, with episodes both of negative, and more rarely positive selection, during the divergence of primates. Positive selection appears to have been more common in the rodent lineage, accompanying the birth of novel, rodent-specific beta-defensin genes. These observations allow a fuller understanding of the evolution of mammalian innate immunity. In both the rodent and primate lineages, sites in the second exon have been subject to positive selection and by implication are important in functional diversity. A small number of sites in the mature human peptides were found to have undergone repeated episodes of selection in different primate lineages. Particular sites were consistently implicated by multiple methods at positions throughout the mature peptides. These sites are clustered at positions predicted to be important for the specificity of the antimicrobial or chemoattractant properties of beta-defensins. Surprisingly, sites within the prepropeptide region were also implicated as being subject to significant positive selection, suggesting previously unappreciated functional significance for this region. CONCLUSIONS: Identification of these putatively functional sites has important implications for our understanding of beta-defensin function and for novel antibiotic design.

POCUS: mining genomic sequence annotation to predict disease genes.

Here we present POCUS (prioritization of candidate genes using statistics), a novel computational approach to prioritize candidate disease genes that is based on over-representation of functional annotation between loci for the same disease. We show that POCUS can provide high (up to 81-fold) enrichment of real disease genes in the candidate-gene shortlists it produces compared with the original large sets of positional candidates. In contrast to existing methods, POCUS can also suggest counterintuitive candidates.

The comparative proteomics of ubiquitination in mouse.

Ubiquitination is a common posttranslational modification in eukaryotic cells, influencing many fundamental cellular processes. Defects in ubiquitination and the processes it mediates are involved in many human disease states. The ubiquitination of a substrate involves four classes of enzymes:a ubiquitin-activating enzyme (E1), a ubiquitin-conjugating enzyme (E2), a ubiquitin protein ligase (E3), and a de-ubiquitinating enzyme (DUB). A substantial number of E1s (four), E2s (13), E3s (97), and DUBs (six) that were previously unknown in the mouse are included in the FANTOM2 Representative Transcript and Protein Set (RTPS). Many of the genes encoding these proteins will constitute promising candidates for involvement in disease. In addition, the RTPS provides the basis for the most comprehensive survey of ubiquitination-associated proteins across eukaryotes undertaken to date. Comparisons of these proteins across human and other organisms suggest that eukaryotic evolution has been associated with an increase in the number and diversity of E3s (possessing either zinc-finger RING, F-box, or HECT domains) and DUBs (containing the ubiquitin thiolesterase family 2 domain). These increases in numbers are too large to be accounted for by the presence of fragmentary proteins in the data sets examined. Much of this innovation appears to have been associated with the emergence of multicellular organisms, and subsequently of vertebrates, increasing the opportunity for complex regulation of ubiquitination-mediated cellular and developmental processes.

Duplication and selection in the evolution of primate beta-defensin genes.

BACKGROUND: Innate immunity is the first line of defense against microorganisms in vertebrates and acts by providing an initial barrier to microorganisms and triggering adaptive immune responses. Peptides such as beta-defensins are an important component of this defense, providing a broad spectrum of antimicrobial activity against bacteria, fungi, mycobacteria and several enveloped viruses. Beta-defensins are small cationic peptides that vary in their expression patterns and spectrum of pathogen specificity. Disruptions in beta-defensin function have been implicated in human diseases, including cystic fibrosis, and a fuller understanding of the variety, function and evolution of human beta-defensins might form the basis for novel therapies. Here we use a combination of laboratory and computational techniques to characterize the main human beta-defensin locus on chromosome 8p22-p23. RESULTS: In addition to known genes in the region we report the genomic structures and expression patterns of four novel human beta-defensin genes and a related pseudogene. These genes show an unusual pattern of evolution, with rapid divergence between second exon sequences that encode the mature beta-defensin peptides matched by relative stasis in first exons that encode signal peptides. CONCLUSIONS: We conclude that the 8p22-p23 locus has evolved by successive rounds of duplication followed by substantial divergence involving positive selection, to produce a diverse cluster of paralogous genes established before the human-baboon divergence more than 23 million years ago. Positive selection, disproportionately favoring alterations in the charge of amino-acid residues, is implicated as driving second exon divergence in these genes.

UBA domain containing proteins in fission yeast.

The ubiquitin-proteasome pathway for intracellular proteolysis is involved in a series of cellular and molecular functions, including the degradation of bulk proteins, cell cycle control, DNA repair, antigen presentation, vesicle transport and the regulation of signal transudation pathways and transcription. Considering this variety of cell biological processes, it is puzzling that until recently only very few proteins were known to possess the ability to interact specifically with ubiquitin chains. However, several ubiquitin binding proteins have now been identified and the binding domains have been characterised on both the functional and structural levels. One example of a widespread ubiquitin binding module is the ubiquitin associated (UBA) domain. Here, we discuss the approximately 15 UBA domain containing proteins encoded in the relatively small genome of the fission yeast Schizosaccharomyces pombe. The proteins display remarkable differences in their domain organisation, indicating that these potential ubiquitin binding proteins are involved in various cell activities.