Many mutations disappear from the population because they impair protein function and/or stability. Thus, amino acid positions that are essential for proper function evolve more slowly than others, or in other words, the slow evolutionary rate of a position reflects its importance. ConSurf (http://consurf.tau.ac.il), reviewed in this manuscript, exploits this to reveal key amino acid positions that are important for maintaining the native conformation(s) of the protein and its function, be it binding, catalysis, transport, etc. Given the sequence or 3D structure of the query protein as input, a search for similar sequences is conducted and the sequences are aligned. The multiple sequence alignment is subsequently used to calculate the evolutionary rates of each amino acid site, using Bayesian or maximum‐likelihood algorithms. Both algorithms take into account the evolutionary relationships between the sequences, reflected in phylogenetic trees, to alleviate problems due to uneven (biased) sampling in sequence space. This is particularly important when the number of sequences is low. The ConSurf‐DB, a new release of which is presented here, provides precalculated ConSurf conservation analysis of nearly all available structures in the Protein DataBank (PDB). The usefulness of ConSurf for the study of individual proteins and mutations, as well as a range of large‐scale, genome‐wide applications, is reviewed.

Positively charged electrostatic patches on protein surfaces are usually indicative of nucleic acid binding interfaces. Interestingly, many proteins which are not involved in nucleic acid binding possess large positive patches on their surface as well. In some cases, the positive patches on the protein are related to other functional properties of the protein family. PatchFinderPlus (PFplus) http://pfp.technion.ac.il is a web-based tool for extracting and displaying continuous electrostatic positive patches on protein surfaces. The input required for PFplus is either a four letter PDB code or a protein coordinate file in PDB format, provided by the user. PFplus computes the continuum electrostatics potential and extracts the largest positive patch for each protein chain in the PDB file. The server provides an output file in PDB format including a list of the patch residues. In addition, the largest positive patch is displayed on the server by a graphical viewer (Jmol), using a simple color coding.

Motivation: The study of RNA virus populations is a challenging task. Each population of RNA virus is composed of a collection of different, yet related genomes often referred to as mutant spectra or quasispecies. Virologists using deep sequencing technologies face major obstacles when studying virus population dynamics, both experimentally and in natural settings due to the relatively high error rates of these technologies and the lack of high performance pipelines. In order to overcome these hurdles we developed a computational pipeline, termed ViVan (Viral Variance Analysis). ViVan is a complete pipeline facilitating the identification, characterization and comparison of sequence variance in deep sequenced virus populations.Results: Applying ViVan on deep sequenced data obtained from samples that were previously characterized by more classical approaches, we uncovered novel and potentially crucial aspects of virus populations. With our experimental work, we illustrate how ViVan can be used for studies ranging from the more practical, detection of resistant mutations and effects of antiviral treatments, to the more theoretical temporal characterization of the population in evolutionary studies.Availability and implementation: Freely available on the web at http://www.vivanbioinfo.orgContact: nshomron@post.tau.ac.ilSupplementary information: Supplementary data are available at Bioinformatics online.

This report uses WES to uncover rare genetic variants in AMD. A null-variant in HMCN1 has been identified in one AMD family, and a missense variant in CFI was discovered in two other families. These variants confirm the genetic complexity and significance of rare genetic variants in the pathogenesis of AMD.

After a pandemic wave in 2009 following their introduction in the human population, the H1N1pdm09 viruses replaced the previously circulating, pre-pandemic H1N1 virus and, along with H3N2 viruses, are now responsible for the seasonal influenza type A epidemics. So far, the evolutionary potential of influenza viruses has been mainly documented by consensus sequencing data. However, like other RNA viruses, influenza A viruses exist as a population of diverse, albeit related, viruses, or quasispecies. Interest in this quasispecies nature has increased with the development of next generation sequencing (NGS) technologies that allow a more in-depth study of the genetic variability. NGS deep sequencing methodologies were applied to determine the whole genome genetic heterogeneity of the three categories of influenza A viruses that circulated in humans between 2007 and 2012 in France, directly from clinical respiratory specimens. Mutation frequencies and single nucleotide polymorphisms were used for comparisons to address the level of natural intrinsic heterogeneity of influenza A viruses. Clear differences in single nucleotide polymorphism profiles between seasons for a given subtype also revealed the constant genetic drift that human influenza A virus quasispecies undergo.

We present genetic and statistical evidence that the R320Q substitution in SMYD1 underlies an inherited form of the AnWj-negative blood group phenotype. The mechanism by which the mutation leads to this phenotype remains to be determined.

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