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Introduction: Over 150,000 variants have been reported to cause Mendelian disease in the medical literature. It is still difficult to leverage this knowledge base in clinical practice as many reports lack strong statistical evidence or may include false associations. Clinical laboratories assess whether these variants (along with newly observed variants that are adjacent to these published ones) underlie clinical disorders.Materials and Methods: We measured whether citation data—including journal impact factor and the number of cited variants (NCV) in each gene with published disease associations—can be used to improve variant assessment.Results: Surprisingly, we find that impact factor is not predictive of pathogenicity, but the NCV score for each gene can provide statistical support of pathogenicity. When combining this gene-level citation metric with variant-level evolutionary conservation and structural features, classification accuracy reaches 89.5%. Further, variants identified in clinical exome sequencing cases have higher NCV scores than simulated rare variants from ExAC in matched genes and consequences (p-16).Discussion: Aggregate citation data can complement existing variant-based predictive algorithms, and can boost their performance without accessing and reviewing large numbers of manuscripts. The NCV is a slow-growing metric of scientific knowledge about each gene’s association with disease.Funding: This research was supported by NIH NHGRI grant HG007229 (C.C.) and NIGMS grant GM078598 (I.A., D.J., and S.S.).

© The Author(s), 2017. This is the authors version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Developmental Biology, doi:10.1016/j.ydbio.2017.02.019 We characterize the genetic diversity of Xenopus laevis strains using RNA-seq data and allele- specific analysis. This data provides a catalogue of coding variation, which can be used for improving the genomic sequence, as well as for better sequence alignment, probe design, and proteomic analysis. In addition, we paint a broad picture of the genetic landscape of the species by functionally annotating different classes of mutations with a well-established prediction tool (PolyPhen-2). Further, we specifically compare the variation in the progeny of four crosses: inbred genomic (J)- strain, outbred albino (B)-strain, and two hybrid crosses of J and B strains. We identify a subset of mutations specific to the B strain, which allows us to investigate the selection pressures affecting duplicated genes in this allotetraploid. From these crosses we find the ratio of non-synonymous to synonymous mutations is lower in duplicated genes, which suggests that they are under greater purifying selection. Surprisingly, we also find that function-altering ("damaging") mutations constitute a greater fraction of the non-synonymous variants in this group, which suggests a role for subfunctionalization in coding variation affecting duplicated genes. L.P. was supported by the NIH grant R01HD073104, also L.P., A.N. and V.S. were supported by R21HD81675, M.H. and E.P. by P40 OD010997. 2018-03-07

Non-African populations have experienced size reductions in the time since their split from West Africans, leading to the hypothesis that natural selection to remove weakly deleterious mutations has been less effective in the history of non-Africans. To test this hypothesis, we measured the per-genome accumulation of nonsynonymous substitutions across diverse pairs of populations. We find no evidence for a higher load of deleterious mutations in non-Africans. However, we detect significant differences among more divergent populations, as archaic Denisovans have accumulated nonsynonymous mutations faster than either modern humans or Neanderthals. To reconcile these findings with patterns that have been interpreted as evidence of the less effective removal of deleterious mutations in non-Africans than in West Africans, we use simulations to show that the observed patterns are not likely to reflect changes in the effectiveness of selection after the populations split but are instead likely to be driven by other population genetic factors.

Two more organisms from different taxonomic groups were added to a new version of the Integrated Sequence-Structure Database (ISSD). ISSD serves as an integrated source of sequence and structure information for the analysis of correlations between mRNA synonymous codon usage and three-dimensional structure of the encoded proteins. ISSD now holds 88 non-homologous Escherichia coli proteins and 25 yeast Saccharomyces cerevisiae proteins in addition to the expanded set of mammalian proteins, which includes 166 proteins (107 in ISSD Version 1.0). Comparison of ISSD sequences with organism-specific codon usage data derived from CUTG database shows that it is a representative subset of the GenBank coding sequences data. Preliminary results of the statistical analysis confirm that sequence-structure correlations observed by us earlier are also present in the upgraded ISSD (Version 2.0), including bacterial and yeast proteins. The ISSD Version 2.0 release includes an improved Web-based data search and retrieval system and is accessible via URL http://www.protein.bio.msu.su/issd/. ISSD can be also accessed at ExPASy, URL http://www.expasy.ch/swissmod/swiss-model.htm l

Genetic mapping of mutations in model systems has facilitated the identification of genes contributing to fundamental biological processes including human diseases. However, this approach has historically required the prior characterization of informative markers. Here we report a fast and cost-effective method for genetic mapping using next-generation sequencing that combines single nucleotide polymorphism discovery, mutation localization, and potential identification of causal sequence variants. In contrast to prior approaches, we have developed a hidden Markov model to narrowly define the mutation area by inferring recombination breakpoints of chromosomes in the mutant pool. In addition, we created an interactive online software resource to facilitate automated analysis of sequencing data and demonstrate its utility in the zebrafish and mouse models. Our novel methodology and online tools will make next-generation sequencing an easily applicable resource for mutation mapping in all model systems., Harvard Stem Cell Institute (Junior Faculty Grant), National Institutes of Health (U.S.) (Grant 1R01DK090311), National Institutes of Health (U.S.) (Grant 5R01MH084676)

Homology-driven proteomics is a major tool to characterize proteomes of organisms with unsequenced genomes. This paper addresses practical aspects of automated homology–driven protein identifications by LC-MS/MS on a hybrid LTQ Orbitrap mass spectrometer. All essential software elements supporting the presented pipeline are either hosted at the publicly accessible web server, or are available for free download.

Only a small fraction of spectra acquired in LC-MS/MS runs matches peptides from target proteins upon database searches. The remaining, operationally termed background, spectra originate from a variety of poorly controlled sources and affect the throughput and confidence of database searches. Here, we report an algorithm and its software implementation that rapidly removes background spectra, regardless of their precise origin. The method estimates the dissimilarity distance between screened MS/MS spectra and unannotated spectra from a partially redundant background library compiled from several control and blank runs. Filtering MS/MS queries enhanced the protein identification capacity when searches lacked spectrum to sequence matching specificity. In sequence-similarity searches it reduced by, on average, 30-fold the number of orphan hits, which were not explicitly related to background protein contaminants and required manual validation. Removing high quality background MS/MS spectra, while preserving in the data set the genuine spectra from target proteins, decreased the false positive rate of stringent database searches and improved the identification of low-abundance proteins.

Eukaryotic DNA replication is highly stratified, with different genomic regions shown to replicate at characteristic times during S phase. Here we observe that mutation rate, as reflected in recent evolutionary divergence and human nucleotide diversity, is markedly increased in later-replicating regions of the human genome. All classes of substitutions are affected, suggesting a generalized mechanism involving replication time-dependent DNA damage. This correlation between mutation rate and regionally stratified replication timing may have substantial evolutionary implications.

We have constructed a non-homologous database, termed the Integrated Sequence-Structure Database (ISSD) which comprises the coding sequences of genes, amino acid sequences of the corresponding proteins, their secondary structure and straight phi,psi angles assignments, and polypeptide backbone coordinates. Each protein entry in the database holds the alignment of nucleotide sequence, amino acid sequence and the PDB three-dimensional structure data. The nucleotide and amino acid sequences for each entry are selected on the basis of exact matches of the source organism and cell environment. The current version 1.0 of ISSD is available on the WWW at http://www.protein.bio.msu.su/issd/ and includes 107 non-homologous mammalian proteins, of which 80 are human proteins. The database has been used by us for the analysis of synonymous codon usage patterns in mRNA sequences showing their correlation with the three-dimensional structure features in the encoded proteins. Possible ISSD applications include optimisation of protein expression, improvement of the protein structure prediction accuracy, and analysis of evolutionary aspects of the nucleotide sequence-protein structure relationship.

Non-African populations have experienced major bottlenecks in the time since their split from West Africans, which has led to the hypothesis that natural selection to remove weakly deleterious mutations may have been less effective in non-Africans. To directly test this hypothesis, we measure the per-genome accumulation of deleterious mutations across diverse humans. We fail to detect any significant differences, but find that archaic Denisovans accumulated non-synonymous mutations at a higher rate than modern humans, consistent with the longer separation time of modern and archaic humans. We also revisit the empirical patterns that have been interpreted as evidence for less effective removal of deleterious mutations in non-Africans than in West Africans, and show they are not driven by differences in selection after population separation, but by neutral evolution., 53 pages (22 page manuscript and 31 supplemental information)

PolyPhen-2 (Polymorphism Phenotyping v2), available as software and via a Web server, predicts the possible impact of amino acid substitutions on the stability and function of human proteins using structural and comparative evolutionary considerations. It performs functional annotation of single-nucleotide polymorphisms (SNPs), maps coding SNPs to gene transcripts, extracts protein sequence annotations and structural attributes, and builds conservation profiles. It then estimates the probability of the missense mutation being damaging based on a combination of all these properties. PolyPhen-2 features include a high-quality multiple protein sequence alignment pipeline and a prediction method employing machine-learning classification. The software also integrates the UCSC Genome Browser's human genome annotations and MultiZ multiple alignments of vertebrate genomes with the human genome. PolyPhen-2 is capable of analyzing large volumes of data produced by next-generation sequencing projects, thanks to built-in support for high-performance computing environments like Grid Engine and Platform LSF.

The fourth author's name was spelled incorrectly. The correct name is: Ivan A. Adzhubei. The correct citation is: Schmidt S, Gerasimova A, Kondrashov FA, Adzhubei IA, Kondrashov AS, et al. (2008) Hypermutable Non-Synonymous Sites Are under Stronger Negative Selection. PLoS Genet 4(11): e1000281. doi:10.1371/journal.pgen.1000281

We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view about chromatin structure has emerged, including its interrelationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded novel mechanistic and evolutionary insights about the functional landscape of the human genome. Together, these studies are defining a path forward to pursue a more-comprehensive characterisation of human genome function.

A comparison of corresponding sets of proteins encoded by closely related genes from organisms representing all three domains of life (Bacteria, Archaea and Eukaryota) suggests that the order in which the genetic code was assembled over 3.5 billion years ago continues to influence the evolution of proteins today. Across these diverse genomes, evolving proteins have accumulated Cys, Met, His, Ser and Phe, and lost many of their Pro, Ala, Glu and Gly residues. The same nine amino acids are currently accrued or lost in human proteins as shown by analysis of nucleotide polymorphisms. The amino acids with declining frequencies were probably among the first incorporated into the genetic code, and most of those with increasing frequencies were probably recruited late. Amino acid composition of proteins varies substantially between taxa and, thus, can evolve. For example, proteins from organisms with (G + C)-rich (or (A + T)-rich) genomes contain more (or fewer) amino acids encoded by (G + C)-rich codons1,2,3,4. However, no universal trends in ongoing changes of amino acid frequencies have been reported. We compared sets of orthologous proteins encoded by triplets of closely related genomes from 15 taxa representing all three domains of life (Bacteria, Archaea and Eukaryota), and used phylogenies to polarize amino acid substitutions. Cys, Met, His, Ser and Phe accrue in at least 14 taxa, whereas Pro, Ala, Glu and Gly are consistently lost. The same nine amino acids are currently accrued or lost in human proteins, as shown by analysis of non-synonymous single-nucleotide polymorphisms. All amino acids with declining frequencies are thought to be among the first incorporated into the genetic code; conversely, all amino acids with increasing frequencies, except Ser, were probably recruited late5,6,7. Thus, expansion of initially under-represented amino acids, which began over 3,400 million years ago8,9, apparently continues to this day.

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.

Examination of nascent globin peptides accumulating in vitro during globin synthesis in rabbit reticulocyte lysates was carried out. A view was supported that nonrandom distribution of codons with different usage frequencies in mRNA may determine the messenger's translation kinetics. Regions of reduced translation of alpha- and beta-globin polypeptide chains were localized, and the cotranslational protein-folding model suggested previously was substantiated. An active conjunction of synthesis and folding of proteins was proposed as one of the main destinations of a translation nonuniformity.

Hurst .1 and, earlier, McDonald2 confirm the pattern of amino-acid gain and loss that we report3. However, they attribute this pattern to properties of the mutation-selection equilibrium, arguing that gainer amino acids are more common than losers among weakly deleterious, rare polymorphisms, which segregate within one or both compared species but never reach fixation. Indeed, we all1,2,3 concur that gainers are, mostly, under-represented, whereas losers are over-represented with respect to mutations ( Table 3 of ref. 3). Still, we cannot agree that the effect of weak negative selection is a viable alternative to our original explanation.

Nature 433, 633–638 (2005) We reported a universal trend of amino-acid gain and loss observed for recent evolutionary history among a diverse set of 15 taxa, with amino acids of declining frequencies being the first to be incorporated into the genetic code and those of increasing frequencies being late recruits.

Circular dichroism has been used to investigate the histone H1 and H5 C-terminal fragments and beta-endorphin conformation. It has been shown that in aqueous solution these polypeptides preferably adopt the left-handed helical conformation of the poly-L-proline II type. A break in the linear temperature dependence of the CD value was found in the temperature interval between 50 and 55 degrees C. It was proposed to be due to non-cooperative disordering of the conformation caused by the destruction of the hydration shell.