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A significant fraction of mutations in proteins are deleterious and result in adverse consequences for protein function, stability, or interaction with other molecules. Intragenic compensation is a specific case of positive epistasis when a neutral missense mutation cancels effect of a deleterious mutation in the same protein. Permissive compensatory mutations facilitate protein evolution, since without them all sequences would be extremely conserved. Understanding compensatory mechanisms is an important scientific challenge at the intersection of protein biophysics and evolution. In human genetics, intragenic compensatory interactions are important since they may result in variable penetrance of pathogenic mutations or fixation of pathogenic human alleles in orthologous proteins from related species. The latter phenomenon complicates computational and clinical inference of an allele's pathogenicity. Deep mutational scanning is a relatively new technique that enables experimental studies of functional effects of thousands of mutations in proteins. We review the important aspects of the field and discuss existing limitations of current datasets. We reviewed ten published DMS datasets with quantified functional effects of single and double mutations and described rates and patterns of intragenic compensation in eight of them.The online version contains supplementary material available at 10.1007/s12551-022-01005-w.

MYB is a key regulator of definitive hematopoiesis and it is dispensable for the development of primitive hematopoietic cells in vertebrates. To delineate definitive versus primitive hematopoiesis during differentiation of human embryonic stem cells, we have introduced reporters into the MYB locus and inactivated the gene by bi-allelic targeting. To recapitulate the early developmental events more adequately, the mutant and wild type human embryonic stem cell lines were differentiated in defined culture conditions without the addition of hematopoietic cytokines. The differentiation of the reporter cell lines demonstrated that MYB is specifically expressed throughout emerging hematopoietic cell populations. Here we show that the disruption of the MYB gene leads to severe defects in the development and proliferation of primitive hematopoietic progenitors while the emergence of primitive blood cells is not affected. We also provide evidence that MYB is essential for neutrophil and T cell development and the upregulation of innate immunity genes during hematopoietic differentiation. Our results suggest that the endothelial origin of primitive blood cells is direct and does not include the intermediate step of primitive hematopoietic progenitors.

Background Structural annotation of genetic variants in the context of intermolecular interactions and protein stability can shed light onto mechanisms of disease-related phenotypes. Three-dimensional structures of related proteins in complexes with other proteins, nucleic acids, or ligands enrich such functional interpretation, since intermolecular interactions are well conserved in evolution. Results We present d-StructMAn, a novel computational method that enables structural annotation of local genetic variants, such as single-nucleotide variants and in-frame indels, and implements it in a highly efficient and user-friendly tool provided as a Docker container. Using d-StructMAn, we annotated several very large sets of human genetic variants, including all variants from ClinVar and all amino acid positions in the human proteome. We were able to provide annotation for more than 46% of positions in the human proteome representing over 60% proteins. Conclusions d-StructMAn is the first of its kind and a highly efficient tool for structural annotation of protein-coding genetic variation in the context of observed and potential intermolecular interactions. d-StructMAn is readily applicable to proteome-scale datasets and can be an instrumental building machine-learning tool for predicting genotype-to-phenotype relationships.

Current evidence from case/control studies indicates that genetic risk for psychiatric disorders derives primarily from numerous common variants, each with a small phenotypic impact. The literature describing apparent segregation of bipolar disorder (BP) in numerous multigenerational pedigrees suggests that, in such families, large-effect inherited variants might play a greater role. To identify roles of rare and common variants on BP, we conducted genetic analyses in 26 Colombia and Costa Rica pedigrees ascertained for bipolar disorder 1 (BP1), the most severe and heritable form of BP. In these pedigrees, we performed microarray SNP genotyping of 838 individuals and high-coverage whole-genome sequencing of 449 individuals. We compared polygenic risk scores (PRS), estimated using the latest BP1 genome-wide association study (GWAS) summary statistics, between BP1 individuals and related controls. We also evaluated whether BP1 individuals had a higher burden of rare deleterious single-nucleotide variants (SNVs) and rare copy number variants (CNVs) in a set of genes related to BP1. We found that compared with unaffected relatives, BP1 individuals had higher PRS estimated from BP1 GWAS statistics (P = 0.001 ~ 0.007) and displayed modest increase in burdens of rare deleterious SNVs (P = 0.047) and rare CNVs (P = 0.002 ~ 0.033) in genes related to BP1. We did not observe rare variants segregating in the pedigrees. These results suggest that small-to-moderate effect rare and common variants are more likely to contribute to BP1 risk in these extended pedigrees than a few large-effect rare variants.

Left ventricular noncompaction (LVNC) is a highly heterogeneous primary disorder of the myocardium. Its clinical features and genetic spectrum strongly overlap with other types of primary cardiomyopathies, in particular, hypertrophic cardiomyopathy. Study and the accumulation of genotype–phenotype correlations are the way to improve the precision of our diagnostics. We present a familial case of LVNC with arrhythmic and thrombotic complications, myocardial fibrosis and heart failure, cosegregating with the splicing variant in the FHOD3 gene. This is the first description of FHOD3-dependent LVNC to our knowledge. We also revise the assumed mechanism of pathogenesis in the case of FHOD3 splicing alterations.

SUMMARY We previously established the contribution of de novo damaging sequence variants to Tourette disorder (TD) through whole-exome sequencing of 511 trios. Here, we sequence an additional 291 TD trios and analyze the combined set of 802 trios. We observe an overrepresentation of de novo damaging variants in simplex, but not multiplex, families; we identify a high-confidence TD risk gene, CELSR3 (cadherin EGF LAG seven-pass G-type receptor 3); we find that the genes mutated in TD patients are enriched for those related to cell polarity, suggesting a common pathway underlying pathobiology; and we confirm a statistically significant excess of de novo copy number variants in TD. Finally, we identify significant overlap of de novo sequence variants between TD and obsessive-compulsive disorder and de novo copy number variants between TD and autism spectrum disorder, consistent with shared genetic risk., In Brief Wang et al. expand their earlier exome-sequencing work in TD, adding 291 trios and conducting combined analyses suggesting de novo variants carry more risk in individuals with unaffected parents, establishing de novo structural variants as risk factors, identifying CELSR3 as a risk gene, and implicating cell polarity in pathogenesis., Graphical Abstract

Vervet monkeys are among the most widely distributed nonhuman primates, show considerable phenotypic diversity, and have long been an important biomedical model for a variety of human diseases and in vaccine research. Using whole-genome sequencing data from 163 vervets sampled from across Africa and the Caribbean, we find high diversity within and between taxa and clear evidence that taxonomic divergence was reticulate rather than following a simple branching pattern. A scan for diversifying selection across taxa identifies strong and highly polygenic selection signals affecting viral processes. Furthermore, selection scores are elevated in genes whose human orthologs interact with HIV and in genes that show a response to experimental simian immunodeficiency virus (SIV) infection in vervet monkeys but not in rhesus macaques, suggesting that part of the signal reflects taxon-specific adaptation to SIV.

By analyzing multi-tissue gene expression and genome-wide genetic variation data in samples from a vervet monkey pedigree, we generated a transcriptome resource and produced the first catalogue of expression quantitative trait loci (eQTLs) in a non-human primate model. This catalogue contains more genome-wide significant eQTLs, per sample, than comparable human resources, and reveals sex and age-related expression patterns. Findings include a master regulatory locus that likely plays a role in immune function, and a locus regulating hippocampal long non-coding RNAs (lncRNAs), whose expression correlates with hippocampal volume. This resource will facilitate genetic investigation of quantitative traits, including brain and behavioral phenotypes relevant to neuropsychiatric disorders.

The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, has devastated health infrastructure around the world. Both ACE2 (an entry receptor) and TMPRSS2 (used by the virus for spike protein priming) are key proteins to SARS-CoV-2 cell entry, enabling progression to COVID-19 in humans. Comparative genomic research into critical ACE2 binding sites, associated with the spike receptor binding domain, has suggested that Old World primates may also be susceptible to disease from SARS-CoV-2 infection. Savanna monkeys (Chlorocebus spp.) are a widespread non-human primate with well-established potential as a bi-directional zoonotic/anthroponotic agent due to high levels of human interaction throughout their range in sub-Saharan Africa and the Caribbean. To characterize potential functional variation in savanna monkey ACE2 and TMPRSS2, we inspected recently published genomic data from 245 savanna monkeys, including 163 wild monkeys from Africa and the Caribbean and 82 captive monkeys from the Vervet Research Colony (VRC). We found several missense variants. One missense variant in ACE2 (X:14,077,550; Asp30Gly), common in Ch. sabaeus, causes a change in amino acid residue that has been inferred to reduce binding efficiency of SARS-CoV-2, suggesting potentially reduced susceptibility. The remaining populations appear as susceptible as humans, based on these criteria for receptor usage. All missense variants observed in wild Ch. sabaeus populations are also present in the VRC, along with two splice acceptor variants (at X:14,065,076) not observed in the wild sample that are potentially disruptive to ACE2 function. The presence of these variants in the VRC suggests a promising model for SARS-CoV-2 infection and vaccine and therapy development. In keeping with a One Health approach, characterizing actual susceptibility and potential for bi-directional zoonotic/anthroponotic transfer in savanna monkey populations may be an important consideration for controlling COVID-19 epidemics in communities with frequent human/non-human primate interactions that, in many cases, may have limited health infrastructure.

Genome sequencing studies of nonhuman primate (NHP) pedigree and population samples are discovering variants on a large and rapidly growing scale. These studies are increasing the utility of several NHP species as model systems for human disease. In particular, by identifying homozygous protein truncating variants (hPTVs) in genes hypothesized to play a role in causing human diseases, it may be possible to elucidate mechanisms for the phenotypic impact of such variants through investigations that are infeasible in humans. The Caribbean vervet (Chlorocebus aethiops sabaeus) is uniquely valuable for this purpose, as the dramatic expansion of its population following severe bottlenecks has enabled PTVs that passed through the bottleneck to attain a relatively high frequency. Using whole genome sequence (WGS) data from 719 monkeys of the Vervet Research Colony (VRC) extended pedigree, we found 2,802 protein-truncating alleles in 1,747 protein-coding genes present in homozygous state in at least one monkey. Polymorphic sites for 923 SNV hPTVs were also observed in natural Caribbean populations from which the VRC descends. The vervet genome browser (VGB) includes information on these PTVs, together with a catalog of phenotypes and biological samples available for monkeys who carry them. We describe initial explorations of the possible impact of vervet PTVs on early infant mortality.

Background DNA methylation is involved in the regulation of gene expression. Although bisulfite-sequencing based methods profile DNA methylation at a single CpG resolution, methylation levels are usually averaged over genomic regions in the downstream bioinformatic analysis. Results We demonstrate that on the genome level a single CpG methylation can serve as a more accurate predictor of gene expression than an average promoter / gene body methylation. We define CpG traffic lights (CpG TL) as CpG dinucleotides with a significant correlation between methylation and expression of a gene nearby. CpG TL are enriched in all regulatory regions. Among all promoters, CpG TL are especially enriched in poised ones, suggesting involvement of DNA methylation in their regulation. Yet, binding of only a handful of transcription factors, such as NRF1, ETS, STAT and IRF-family members, could be regulated by direct methylation of transcription factor binding sites (TFBS) or its close proximity. For the majority of TF, an alternative scenario is more likely: methylation and inactivation of the whole regulatory element indirectly represses functional TF binding with a CpG TL being a reliable marker of such inactivation. Conclusions CpG TL provide a promising insight into mechanisms of enhancer activity and gene regulation linking methylation of single CpG to gene expression. CpG TL methylation can be used as reliable markers of enhancer activity and gene expression in applications, e.g. in clinic where measuring DNA methylation is easier compared to directly measuring gene expression due to more stable nature of DNA. Electronic supplementary material The online version of this article (10.1186/s12864-018-5387-1) contains supplementary material, which is available to authorized users.

MYB is a key regulator of definitive hematopoiesis that plays a critical role in the maintenance and multilineage differentiation of hematopoietic stem cells (HSCs). In vertebrate developmental models, MYB is thought to be dispensable for primitive hematopoiesis. To explore the role of MYB in human hematopoietic development, we have subjected human pluripotent stem cells (hPSCs) to mono- and bi-allelic gene targeting followed by hematopoietic differentiation in defined culture conditions. Here we show that MYB plays a central role in the development of human primitive blood cells. MYB expression was hematopoietic-specific and its induction coincided with emergence of the earliest primitive blood cells. Bi-allelic inactivation of MYB most severely affected the primitive erythroid progenitors of greater proliferative capacity and multilineage hematopoietic progenitors. The initial phase of the hematopoietic differentiation was not affected by the bi-allelic gene deficiency, but maturation of the primitive myeloid cells was found to be MYB-depended. Rescuing MYB expression in MYB-null cells shows that the gene is required for both development and proliferation of primitive clonogenic progenitors. In addition, our findings suggest that human primitive hematopoiesis emerge in several developmental cohorts.

Whole-exome sequencing (WES) and de novo variant detection have proven a powerful approach to gene discovery in complex neurodevelopmental disorders. We have completed WES of 325 Tourette disorder trios from the Tourette International Collaborative Genetics cohort and a replication sample of 186 trios from the Tourette Syndrome Association International Consortium on Genetics (511 total). We observe strong and consistent evidence for the contribution of de novo likely gene-disrupting (LGD) variants (rate ratio [RR] 2.32, p = 0.002). Additionally, de novo damaging variants (LGD and probably damaging missense) are overrepresented in probands (RR 1.37, p = 0.003). We identify four likely risk genes with multiple de novo damaging variants in unrelated probands: WWC1 (WW and C2 domain containing 1), CELSR3 (Cadherin EGF LAG seven-pass G-type receptor 3), NIPBL (Nipped-B-like), and FN1 (fibronectin 1). Overall, we estimate that de novo damaging variants in approximately 400 genes contribute risk in 12% of clinical cases. Video Abstract [Figure presented]

The next generation sequencing technologies produce unprecedented amounts of data on the genetic sequence of individual organisms. These sequences carry a substantial amount of variation that may or may be not related to a phenotype. Phenotypically important part of this variation often comes in form of protein-sequence altering (non-synonymous) single nucleotide variants (nsSNVs). Here we present StructMAn, a Web-based tool for annotation of human and non-human nsSNVs in the structural context. StructMAn analyzes the spatial location of the amino acid residue corresponding to nsSNVs in the three-dimensional (3D) protein structure relative to other proteins, nucleic acids and low molecular-weight ligands. We make use of all experimentally available 3D structures of query proteins, and also, unlike other tools in the field, of structures of proteins with detectable sequence identity to them. This allows us to provide a structural context for around 20% of all nsSNVs in a typical human sequencing sample, for up to 60% of nsSNVs in genes related to human diseases and for around 35% of nsSNVs in a typical bacterial sample. Each nsSNV can be visualized and inspected by the user in the corresponding 3D structure of a protein or protein complex. The StructMAn server is available at http://structman.mpi-inf.mpg.de.

It is widely anticipated that the coming year will be marked by the complete characterization of DNA sequence of protein coding regions of thousands of human individuals. A number of existing computational methods use comparative protein sequence analysis and analysis of protein structure to predict the functional effect of coding human alleles. Functional and structural analysis of coding allelic variants can inform various aspects of research on human genetic variation. In population and evolutionary genetics it helps estimating the strength of purifying selection against deleterious missense mutations and study the imprint of demographic history on deleterious genetic variation. In medical genetics it may assist in the interpretation of uncharacterized mutations in genes involved in monogenic and oligogenic diseases. It has a potnetial to facilitate medical sequencing studies searching for genes underlying Mendelian diseases or harboring rare alleles involved in complex traits.

Alternative splicing is a well-recognized mechanism of accelerated genome evolution. We have studied single-nucleotide polymorphisms and human-chimpanzee divergence in the exons of 6672 alternatively spliced human genes, with the aim of understanding the forces driving the evolution of alternatively spliced sequences. Here, we show that alternatively spliced exons and exon fragments (alternative exons) from minor isoforms experience lower selective pressure at the amino acid level, accompanied by selection against synonymous sequence variation. The results of the McDonald-Kreitman test suggest that alternatively spliced exons, unlike exons constitutively included in the mRNA, are also subject to positive selection, with up to 27% of amino acids fixed by positive selection.

We present a novel notion of binding site local similarity based on the analysis of complete protein environments of ligand fragments. Comparison of a query protein binding site (target) against the 3D structure of another protein (analog) in complex with a ligand enables ligand fragments from the analog complex to be transferred to positions in the target site, so that the complete protein environments of the fragment and its image are similar. The revealed environments are similarity regions and the fragments transferred to the target site are considered as binding patterns. The set of such binding patterns derived from a database of analog complexes forms a cloud-like structure (fragment cloud), which is a powerful tool for computational drug design. It has been shown on independent test sets that the combined use of a traditional energy-based score together with the cloud-based score responsible for the quality of embedding of a ligand into the fragment cloud improves the self-docking and screening results dramatically. The usage of a fragment cloud as a source of positioned molecular fragments fitting the binding protein environment has been validated by reproduction of experimental ligand optimization results. Proteins 2007. © 2007 Wiley-Liss, Inc.

Warren, Wesley C. et al., We describe a genome reference of the African green monkey or vervet (Chlorocebus aethiops). This member of the Old World monkey (OWM) superfamily is uniquely valuable for genetic investigations of simian immunodeficiency virus (SIV), for which it is the most abundant natural host species, and of a wide range of health-related phenotypes assessed in Caribbean vervets (C. a. sabaeus), whose numbers have expanded dramatically since Europeans introduced small numbers of their ancestors from West Africa during the colonial era. We use the reference to characterize the genomic relationship between vervets and other primates, the intra-generic phylogeny of vervet subspecies, and genome-wide structural variations of a pedigreed C. a. sabaeus population. Through comparative analyses with human and rhesus macaque, we characterize at high resolution the unique chromosomal fission events that differentiate the vervets and their close relatives from most other catarrhine primates, in whom karyotype is highly conserved. We also provide a summary of transposable elements and contrast these with the rhesus macaque and human. Analysis of sequenced genomes representing each of the main vervet subspecies supports previously hypothesized relationships between these populations, which range across most of sub-Saharan Africa, while uncovering high levels of genetic diversity within each. Sequence-based analyses of major histocompatibility complex (MHC) polymorphisms reveal extremely low diversity in Caribbean C. a. sabaeus vervets, compared to vervets from putatively ancestral West African regions. In the C. a. sabaeus research population, we discover the first structural variations that are, in some cases, predicted to have a deleterious effect; future studies will determine the phenotypic impact of these variations., Funding to R.K.W. was provided by NIH-NHGRI grant 5U54HG00307907. Support for the Vervet Research Colony was provided by NIH grant RR019963/OD010965 to J.R.K. Funding to N.B.F. was provided by NIH grants R01RR016300 and R01OD010980. The French National Agency for Research on AIDS and Viral Hepatitis (ANRS) provided funding to M.C.M.-T. Funding to M.R. and R.S. was provided by the Ministero della Universita’ e della Ricerca. Funding to K.D. was provided by Genome Canada and Genome Quebec. B.A. and R.N. acknowledge support from the Wellcome Trust (grant number WT095908) and the European Molecular Biology Laboratory.

The e(y)2 gene of Drosophila melanogaster encodes the ubiquitous evolutionarily conserved co-activator of RNA polymerase II that is involved in transcription regulation of a high number of genes. The Drosophila e(y)2b gene, paralogue of the e(y)2 has been found. The analysis of structure of the e(y)2, e(y)2b and its orthologues from other species reveals that the e(y)2 gene derived as a result of retroposition of the e(y)2b during Drosophila evolution. The mRNA-derived retrogenes lack introns or regulatory regions; most of them become pseudogenes whereas some acquire tissue-specific functions. Here we describe the different situation: the e(y)2 retrogene performs the general function and is ubiquitously expressed, while the source gene is functional only in a small group of male germ cells. This must have resulted from retroposition into a transcriptionally favorable region of the genome.

The accumulation of genome-wide information on single nucleotide polymorphisms in humans provides an unprecedented opportunity to detect the evolutionary forces responsible for heterogeneity of the level of genetic variability across loci. Previous studies have shown that history of recombination events has produced long haplotype blocks in the human genome, which contribute to this heterogeneity. Other factors, however, such as natural selection or the heterogeneity of mutation rates across loci, may also lead to heterogeneity of genetic variability. We compared synonymous and non-synonymous variability within human genes with their divergence from murine orthologs. We separately analyzed the non-synonymous variants predicted to damage protein structure or function and the variants predicted to be functionally benign. The predictions were based on comparative sequence analysis and, in some cases, on the analysis of protein structure. A strong correlation between non-synonymous, benign variability and non-synonymous human-mouse divergence suggests that selection played an important role in shaping the pattern of variability in coding regions of human genes. However, the lack of correlation between deleterious variability and evolutionary divergence shows that a substantial proportion of the observed non-synonymous single-nucleotide polymorphisms reduces fitness and never reaches fixation. Evolutionary and medical implications of the impact of selection on human polymorphisms are discussed.

Next-generation sequencing enables simultaneous analysis of hundreds of human genomes associated with a particular phenotype, for example, a disease. These genomes naturally contain a lot of sequence variation that ranges from single-nucleotide variants (SNVs) to large-scale structural rearrangements. In order to establish a functional connection between genotype and disease-associated phenotypes, one needs to distinguish disease drivers from neutral passenger variants. Functional annotation based on experimental assays is feasible only for a limited number of candidate mutations. Thus alternative computational tools are needed. A possible approach to annotating mutations functionally is to consider their spatial location relative to functionally relevant sites in three-dimensional (3D) structures of the harboring proteins. This is impeded by the lack of available protein 3D structures. Complementing experimentally resolved structures with reliable computational models is an attractive alternative. We developed a structure-based approach to characterizing comprehensive sets of non-synonymous single-nucleotide variants (nsSNVs): associated with cancer, non-cancer diseases and putatively functionally neutral. We searched experimentally resolved protein 3D structures for potential homology-modeling templates for proteins harboring corresponding mutations. We found such templates for all proteins with disease-associated nsSNVs, and 51 and 66% of proteins carrying common polymorphisms and annotated benign variants. Many mutations caused by nsSNVs can be found in protein–protein, protein–nucleic acid or protein–ligand complexes. Correction for the number of available templates per protein reveals that protein–protein interaction interfaces are not enriched in either cancer nsSNVs, or nsSNVs associated with non-cancer diseases. Whereas cancer-associated mutations are enriched in DNA-binding proteins, they are rarely located directly in DNA-interacting interfaces. In contrast, mutations associated with non-cancer diseases are in general rare in DNA-binding proteins, but enriched in DNA-interacting interfaces in these proteins. All disease-associated nsSNVs are overrepresented in ligand-binding pockets, and nsSNVs associated with non-cancer diseases are additionally enriched in protein core, where they probably affect overall protein stability.

Genome-wide association studies (GWAS) have identified >500 common variants associated with quantitative metabolic traits, but in aggregate such variants explain at most 20–30% of the heritable component of population variation in these traits. To further investigate the impact of genotypic variation on metabolic traits, we conducted re-sequencing studies in >6,000 members of a Finnish population cohort (The Northern Finland Birth Cohort of 1966 [NFBC]) and a type 2 diabetes case-control sample (The Finland-United States Investigation of NIDDM Genetics [FUSION] study). By sequencing the coding sequence and 5′ and 3′ untranslated regions of 78 genes at 17 GWAS loci associated with one or more of six metabolic traits (serum levels of fasting HDL-C, LDL-C, total cholesterol, triglycerides, plasma glucose, and insulin), and conducting both single-variant and gene-level association tests, we obtained a more complete understanding of phenotype-genotype associations at eight of these loci. At all eight of these loci, the identification of new associations provides significant evidence for multiple genetic signals to one or more phenotypes, and at two loci, in the genes ABCA1 and CETP, we found significant gene-level evidence of association to non-synonymous variants with MAF, Author Summary Abnormal serum levels of various metabolites, including measures relevant to cholesterol, other fats, and sugars, are known to be risk factors for cardiovascular disease and type 2 diabetes. Identification of the genes that play a role in generating such abnormalities could advance the development of new treatment and prevention strategies for these disorders. Investigations of common genetic variants carried out in large sets of research subjects have successfully pinpointed such genes within many regions of the human genome. However, these studies often have not led to the identification of the specific genetic variations affecting metabolic traits. To attempt to detect such causal variations, we sequenced genes in 17 genomic regions implicated in metabolic traits in >6,000 people from Finland. By conducting statistical analyses relating specific variations (individually and grouped by gene) to the measures for these metabolic traits observed in the study subjects, we added to our understanding of how genotypes affect these traits. Our findings support a long-held hypothesis that the unique history of the Finnish population provides important advantages for analyzing the relationship between genetic variations and biomedically important traits.

Regions flanking (3’ and 5’) the protein-coding region of a gene that are transcribed but not translated (stands for untranslated region).

Alternative splicing is an important mechanism of generating protein diversity and accelerated genome evolution. The mode of the selection acting in constitutive, major alternative and minor alternative regions of human genes is different. Whereas constitutive and major alternative regions tend to evolve under negative (stabilizing) selection, alternatively spliced exons from minor isoforms experience lower selective pressure at the amino acid level accompanied by weak selection against synonymous sequence variation. The McDonald–Kreitman test uses the nucleotide variation for a gene or a set of genes between and within species to detect the positive Darwinian selection in the presence of negative selection. The results of the test suggest that alternatively spliced exons are also subject to positive selection, with up to 27% of amino acids fixed by positive selection. Key concepts Alternative splicing is an important mechanism of generating protein diversity and accelerated genome evolution. Alternatively spliced regions are often evolutionarily young. There is a difference in the selection mode in constitutive, major alternative, and minor alternative regions of human genes. Constitutive and major alternative regions evolve under negative (stabilizing) selection. Up to 27% of positions in minor alternative regions may be experiencing positive selection. Keywords: alternative splicing; positive selection; human genome; molecular evolution; McDonald–Kreitman test

Microcin C (McC), an inhibitor of the growth of enteric bacteria, consists of a heptapeptide with a modified AMP residue attached to the backbone of the C-terminal aspartate through an N -acyl phosphamidate bond. Here we identify maturation intermediates produced by cells lacking individual mcc McC biosynthesis genes. We show that the products of the mccD and mccE genes are required for attachment of a 3-aminopropyl group to the phosphate of McC and that this group increases the potency of inhibition of the McC target, aspartyl-tRNA synthetase.

Background The mapping of quantitative trait loci in rat and mouse has been extremely successful in identifying chromosomal regions associated with human disease-related phenotypes. However, identifying the specific phenotype-causing DNA sequence variations within a quantitative trait locus has been much more difficult. The recent availability of genomic sequence from several mouse inbred strains (including C57BL/6J, 129X1/SvJ, 129S1/SvImJ, A/J, and DBA/2J) has made it possible to catalog DNA sequence differences within a quantitative trait locus derived from crosses between these strains. However, even for well-defined quantitative trait loci ( Description To help identify functional DNA sequence variations within quantitative trait loci we have used the Ensembl annotated genome sequence to compile a database of mouse single nucleotide polymorphisms (SNPs) that are predicted to cause missense, nonsense, frameshift, or splice site mutations (available at http://bioinfo.embl.it/SnpApplet/). For missense mutations we have used the PolyPhen and PANTHER algorithms to predict whether amino acid changes are likely to disrupt protein function. Conclusion We have developed a database of mouse SNPs predicted to cause missense, nonsense, frameshift, and splice-site mutations. Our analysis revealed that 20% and 14% of missense SNPs are likely to be deleterious according to PolyPhen and PANTHER, respectively, and 6% are considered deleterious by both algorithms. The database also provides gene expression and functional annotations from the Symatlas, Gene Ontology, and OMIM databases to further assess candidate phenotype-causing mutations. To demonstrate its utility, we show that Mouse SNP Miner successfully finds a previously identified candidate SNP in the taste receptor, Tas1r3, that underlies sucrose preference in the C57BL/6J strain. We also use Mouse SNP Miner to derive a list of candidate phenotype-causing mutations within a previously uncharacterized QTL for response to morphine in the 129/Sv strain.

Human single nucleotide polymorphisms (SNPs) represent the most frequent type of human population DNA variation. One of the main goals of SNP research is to understand the genetics of the human phenotype variation and especially the genetic basis of human complex diseases. Non-synonymous coding SNPs (nsSNPs) comprise a group of SNPs that, together with SNPs in regulatory regions, are believed to have the highest impact on phenotype. Here we present a World Wide Web server to predict the effect of an nsSNP on protein structure and function. The prediction method enabled analysis of the publicly available SNP database HGVbase, which gave rise to a dataset of nsSNPs with predicted functionality. The dataset was further used to compare the effect of various structural and functional characteristics of amino acid substitutions responsible for phenotypic display of nsSNPs. We also studied the dependence of selective pressure on the structural and functional properties of proteins. We found that in our dataset the selection pressure against deleterious SNPs depends on the molecular function of the protein, although it is insensitive to several other protein features considered. The strongest selective pressure was detected for proteins involved in transcription regulation.

The purpose of the work was to investigate at the molecular structural and energy levels the consequence of amino acid substitutions in collagen that cause systemic diseases. The data have been systematized on defects in human collagen III, and the patterns of single-nucleotide polymorphisms collected. Then molecular mechanics calculations were performed for native and mutant collagen molecule fragments. The observed energy components and structural alterations that accompany particular amino acid substitutions were used to propose an interpretation of negative consequences in terms of stability and hydration of the macromolecule.

Single nucleotide polymorphisms (SNPs) constitute the bulk of human genetic variation, occurring with an average density of approximately 1/1000 nucleotides of a genotype. SNPs are either neutral allelic variants or are under selection of various strengths, and the impact of SNPs on fitness remains unknown. Identification of SNPs affecting human phenotype, especially leading to risks of complex disorders, is one of the key problems of medical genetics. SNPs in protein-coding regions that cause amino acid variants (non-synonymous cSNPs) are most likely to affect phenotypes. We have developed a straightforward and reliable method based on physical and comparative considerations that estimates the impact of an amino acid replacement on the three-dimensional structure and function of the protein. We estimate that approximately 20% of common human non-synonymous SNPs damage the protein. The average minor allele frequency of such SNPs in our data set was two times lower than that of benign non-synonymous SNPs. The average human genotype carries approximately 10(3) damaging non-synonymous SNPs that together cause a substantial reduction in fitness.

We present a new method of segmentation of nucleotide sequences into regions with different average composition. The sequence is modelled as a series of segments; within each segment the sequence is considered as a random sequence of independent and identically distributed variables. The partition algorithm includes two stages. In the first stage the optimal partition is found, which maximises the overall product of marginal likelihoods calculated for each segment. To prevent segmentation into short segments, the border insertion penalty may be introduced. In the next stage segments with close compositions are merged. Filtration is performed with the help of partition function calculated for all possible subsets of boundaries that belong to the optimal partition. The long sequences can be segmented by dividing sequences and segmenting those parts separately. The contextual effects of repeats, genes and other genomic elements are readily visualised.

To the Editor: Applications of rapidly advancing sequencing technologies exacerbate the need to interpret individual sequence variants. Sequencing of phenotyped clinical subjects will soon become a method of choice in studies of the genetic causes of Mendelian and complex diseases. New exon capture techniques will direct sequencing efforts towards the most informative and easily interpretable protein-coding fraction of the genome. Thus, the demand for computational predictions of the impact of protein sequence variants will continue to grow. Here we present a new method and the corresponding software tool, PolyPhen-2 (http://genetics.bwh.harvard.edu/pph2/), which is different from the early tool PolyPhen1 in the set of predictive features, alignment pipeline, and the method of classification (Fig. 1a). PolyPhen-2 uses eight sequence-based and three structure-based predictive features (Supplementary Table 1) which were selected automatically by an iterative greedy algorithm (Supplementary Methods). Majority of these features involve comparison of a property of the wild-type (ancestral, normal) allele and the corresponding property of the mutant (derived, disease-causing) allele, which together define an amino acid replacement. Most informative features characterize how well the two human alleles fit into the pattern of amino acid replacements within the multiple sequence alignment of homologous proteins, how distant the protein harboring the first deviation from the human wild-type allele is from the human protein, and whether the mutant allele originated at a hypermutable site2. The alignment pipeline selects the set of homologous sequences for the analysis using a clustering algorithm and then constructs and refines their multiple alignment (Supplementary Fig. 1). The functional significance of an allele replacement is predicted from its individual features (Supplementary Figs. 2–4) by Naive Bayes classifier (Supplementary Methods). Figure 1 PolyPhen-2 pipeline and prediction accuracy. (a) Overview of the algorithm. (b) Receiver operating characteristic (ROC) curves for predictions made by PolyPhen-2 using five-fold cross-validation on HumDiv (red) and HumVar3 (light green). UniRef100 (solid ... We used two pairs of datasets to train and test PolyPhen-2. We compiled the first pair, HumDiv, from all 3,155 damaging alleles with known effects on the molecular function causing human Mendelian diseases, present in the UniProt database, together with 6,321 differences between human proteins and their closely related mammalian homologs, assumed to be non-damaging (Supplementary Methods). The second pair, HumVar3, consists of all the 13,032 human disease-causing mutations from UniProt, together with 8,946 human nsSNPs without annotated involvement in disease, which were treated as non-damaging. We found that PolyPhen-2 performance, as presented by its receiver operating characteristic curves, was consistently superior compared to PolyPhen (Fig. 1b) and it also compared favorably with the three other popular prediction tools4–6 (Fig. 1c). For a false positive rate of 20%, PolyPhen-2 achieves the rate of true positive predictions of 92% and 73% on HumDiv and HumVar, respectively (Supplementary Table 2). One reason for a lower accuracy of predictions on HumVar is that nsSNPs assumed to be non-damaging in HumVar contain a sizable fraction of mildly deleterious alleles. In contrast, most of amino acid replacements assumed non-damaging in HumDiv must be close to selective neutrality. Because alleles that are even mildly but unconditionally deleterious cannot be fixed in the evolving lineage, no method based on comparative sequence analysis is ideal for discriminating between drastically and mildly deleterious mutations, which are assigned to the opposite categories in HumVar. Another reason is that HumDiv uses an extra criterion to avoid possible erroneous annotations of damaging mutations. For a mutation, PolyPhen-2 calculates Naive Bayes posterior probability that this mutation is damaging and reports estimates of false positive (the chance that the mutation is classified as damaging when it is in fact non-damaging) and true positive (the chance that the mutation is classified as damaging when it is indeed damaging) rates. A mutation is also appraised qualitatively, as benign, possibly damaging, or probably damaging (Supplementary Methods). The user can choose between HumDiv- and HumVar-trained PolyPhen-2. Diagnostics of Mendelian diseases requires distinguishing mutations with drastic effects from all the remaining human variation, including abundant mildly deleterious alleles. Thus, HumVar-trained PolyPhen-2 should be used for this task. In contrast, HumDiv-trained PolyPhen-2 should be used for evaluating rare alleles at loci potentially involved in complex phenotypes, dense mapping of regions identified by genome-wide association studies, and analysis of natural selection from sequence data, where even mildly deleterious alleles must be treated as damaging.

Background Gene duplications are a source of new genes and protein functions. The innovative role of duplication events makes families of paralogous genes an interesting target for studies in evolutionary biology. Here we study global trends in the evolution of human genes that resulted from recent duplications. Results The pressure of negative selection is weaker during a short time immediately after a duplication event. Roughly one fifth of genes in paralogous gene families are evolving asymmetrically: one of the proteins encoded by two closest paralogs accumulates amino acid substitutions significantly faster than its partner. This asymmetry cannot be explained by differences in gene expression levels. In asymmetric gene pairs the number of deleterious mutations is increased in one copy, while decreased in the other copy as compared to genes constituting non-asymmetrically evolving pairs. The asymmetry in the rate of synonymous substitutions is much weaker and not significant. Conclusions The increase of negative selection pressure over time after a duplication event seems to be a major trend in the evolution of human paralogous gene families. The observed asymmetry in the evolution of paralogous genes shows that in many cases one of two gene copies remains practically unchanged, while the other accumulates functional mutations. This supports the hypothesis that slowly evolving gene copies preserve their original functions, while fast evolving copies obtain new specificities or functions. Reviewers This article was reviewed by Dr. Igor Rogozin (nominated by Dr. Arcady Mushegian), Dr. Fyodor Kondrashov, and Dr. Sergei Maslov.