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The negative correlation between the rate of protein evolution and expression level of a gene has been recognized as a universal law of the evolutionary biology (Koonin 2011). In our study, we apply a population-based approach to systematically investigate the relative importance of unequal mutation rate, linkage, and selection in the origin of the expression-polymorphism anticorrelation. We analyzed the DNA sequence of protein coding genes of 24 Saccharomyces cerevisiae and 58 Schizosaccharomyces pombe strains. We found that highly expressed genes had a substantially decreased number of polymorphic sites when compared with genes transcribed less extensively. This expression-dependent reduction was especially strong in the nonsynonymous sites, although it was also present in the synonymous sites and untranslated regions, both up and down of a gene. Most importantly, no such trend was found in introns. We used these observations, as well as analyses of site frequency spectra and data from mutation accumulation experiments, to show that the purifying selection acting on nonsynonymous sites was the main, but not exclusive, factor impeding molecular evolution within the coding sequences of highly expressed genes. Linkage could not fully explain the observed pattern of polymorphism within the untranslated regions and synonymous sites, although the contribution of selection acting directly on synonymous variants was extremely small. Finally, we found that the impact of mutational bias was rather negligible.
Pubmed ID: 30321329
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Original SAMTOOLS package has been split into three separate repositories including Samtools, BCFtools and HTSlib. Samtools for manipulating next generation sequencing data used for reading, writing, editing, indexing,viewing nucleotide alignments in SAM,BAM,CRAM format. BCFtools used for reading, writing BCF2,VCF, gVCF files and calling, filtering, summarising SNP and short indel sequence variants. HTSlib used for reading, writing high throughput sequencing data.
View all literature mentionsCollection of genome databases for vertebrates and other eukaryotic species with DNA and protein sequence search capabilities. Used to automatically annotate genome, integrate this annotation with other available biological data and make data publicly available via web. Ensembl tools include BLAST, BLAT, BioMart and the Variant Effect Predictor (VEP) for all supported species.
View all literature mentionsModel organism database that provides organization of and access to scientific data for the fission yeast Schizosaccharomyces pombe. PomBase supports genomic sequence and features, genome-wide datasets and manual literature curation. PomBase also provides a community hub for researchers, providing genome statistics, a community curation interface, news, events, documentation, mailing lists, and welcomes data submissions.
View all literature mentionsThis genomic tRNA database contains tRNA gene predictions made by the program tRNAscan-SE (Lowe & Eddy, Nucl Acids Res 25: 955-964, 1997) on complete or nearly complete genomes. Unless otherwise noted, all annotation is automated, and has not been inspected for agreement with published literature. Transfer RNAs (tRNAs) represent the single largest, best-understood class of non-protein coding RNA genes found in all living organisms. By far, the major source of new tRNAs is computational identification of genes within newly sequenced genomes. To organize the rapidly growing collection and enable systematic analyses, we created the Genomic tRNA Database (GtRNAdb). The web resource provides overview statistics of tRNA genes within each analyzed genome, including information by isotype and genetic locus, easily downloadable primary sequences, graphical secondary structures and multiple sequence alignments. Direct links for each gene to UCSC eukaryotic and microbial genome browsers provide graphical display of tRNA genes in the context of all other local genetic information. The database can be searched by primary sequence similarity, tRNA characteristics or phylogenetic group. Inevitably with automated sequence analysis, we find exceptions to general identification rules, isoacceptor type predictions (esp. due to variable post-transcriptional anticodon modification), and questionable tRNA identifications (due to pseudogenes, SINES, or other tRNA-derived elements). We attempt to document all cases we come across, and welcome feedback on new or unrecognized discrepancies.
View all literature mentionsData analysis service to predict the functional consequences of known and unknown variants.
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