Level Of Evolutionary Conservation Research Articles

Distinct types of short open reading frames are translated in plant cells.

Genomes contain millions of short (<100 codons) open reading frames (sORFs), which are usually dismissed during gene annotation. Nevertheless, peptides encoded by such sORFs can play important biological roles, and their impact on cellular processes has long been underestimated. Here, we analyzed approximately 70,000 transcribed sORFs in the model plant Physcomitrella patens (moss). Several distinct classes of sORFs that differ in terms of their position on transcripts and the level of evolutionary conservation are present in the moss genome. Over 5000 sORFs were conserved in at least one of 10 plant species examined. Mass spectrometry analysis of proteomic and peptidomic data sets suggested that tens of sORFs located on distinct parts of mRNAs and long noncoding RNAs (lncRNAs) are translated, including conserved sORFs. Translational analysis of the sORFs and main ORFs at a single locus suggested the existence of genes that code for multiple proteins and peptides with tissue-specific expression. Functional analysis of four lncRNA-encoded peptides showed that sORFs-encoded peptides are involved in regulation of growth and differentiation in moss. Knocking out lncRNA-encoded peptides resulted in a decrease of moss growth. In contrast, the overexpression of these peptides resulted in a diverse range of phenotypic effects. Our results thus open new avenues for discovering novel, biologically active peptides in the plant kingdom.

Untouchable genes in the human genome: Identifying ideal targets for cancer treatment

BackgroundUsually, genes with a higher-than-expected number of somatic mutations in tumor samples are assumed to be cancer related. We identified genes with a fewer-than-expected number of somatic mutations - “untouchable genes”. MethodsTo predict the expected number of somatic mutations, we used a linear regression model with the number of mutations in the gene as an outcome, and gene characteristics, including gene size, nucleotide composition, level of evolutionary conservation, expression level and others, as predictors. Analysis of residuals from the regression model was used to compare the observed and predicted number of mutations. ResultsWe have identified 19 genes with a less-than-expected number of loss-off-function (nonsense, frameshift or pathogenic missense) mutations – i.e., untouchable genes. The number of silent or neutral missense mutations in untouchable genes was equal or higher than the expected number. Many mucins, including MUC16, MUC17, MUC6, MUC5AC, MUC5B, and MUC12, are untouchable. We hypothesized that untouchable mucins help tumor cells to avoid immune response by providing a protective coat that prevents direct contact between effector immune cells, e.g., cytotoxic T-cells, and tumor cells. Survival analysis of available TCGA data demonstrated that overall survival of patients with low (below the median) expression of untouchable mucins was better compared to patients with high expression of untouchable mucins. Aside from mucins, we have identified a number of other untouchable genes. ConclusionsUntouchable genes may be ideal targets for cancer treatment since suppression of untouchable genes is expected to inhibit survival of tumor cells.

Gene characteristics predicting missense, nonsense and frameshift mutations in tumor samples

BackgroundBecause driver mutations provide selective advantage to the mutant clone, they tend to occur at a higher frequency in tumor samples compared to selectively neutral (passenger) mutations. However, mutation frequency alone is insufficient to identify cancer genes because mutability is influenced by many gene characteristics, such as size, nucleotide composition, etc. The goal of this study was to identify gene characteristics associated with the frequency of somatic mutations in the gene in tumor samples.ResultsWe used data on somatic mutations detected by genome wide screens from the Catalog of Somatic Mutations in Cancer (COSMIC). Gene size, nucleotide composition, expression level of the gene, relative replication time in the cell cycle, level of evolutionary conservation and other gene characteristics (totaling 11) were used as predictors of the number of somatic mutations. We applied stepwise multiple linear regression to predict the number of mutations per gene. Because missense, nonsense, and frameshift mutations are associated with different sets of gene characteristics, they were modeled separately. Gene characteristics explain 88% of the variation in the number of missense, 40% of nonsense, and 23% of frameshift mutations. Comparisons of the observed and expected numbers of mutations identified genes with a higher than expected number of mutations– positive outliers. Many of these are known driver genes. A number of novel candidate driver genes was also identified.ConclusionsBy comparing the observed and predicted number of mutations in a gene, we have identified known cancer-associated genes as well as 111 novel cancer associated genes. We also showed that adding the number of silent mutations per gene reported by genome/exome wide screens across all cancer type (COSMIC data) as a predictor substantially exceeds predicting accuracy of the most popular cancer gene predicting tool - MutsigCV.

Allelic Spectra of Risk SNPs Are Different for Environment/Lifestyle Dependent versus Independent Diseases.

Genome-wide association studies (GWAS) have generated sufficient data to assess the role of selection in shaping allelic diversity of disease-associated SNPs. Negative selection against disease risk variants is expected to reduce their frequencies making them overrepresented in the group of minor (<50%) alleles. Indeed, we found that the overall proportion of risk alleles was higher among alleles with frequency <50% (minor alleles) compared to that in the group of major alleles. We hypothesized that negative selection may have different effects on environment (or lifestyle)-dependent versus environment (or lifestyle)-independent diseases. We used an environment/lifestyle index (ELI) to assess influence of environmental/lifestyle factors on disease etiology. ELI was defined as the number of publications mentioning “environment” or “lifestyle” AND disease per 1,000 disease-mentioning publications. We found that the frequency distributions of the risk alleles for the diseases with strong environmental/lifestyle components follow the distribution expected under a selectively neutral model, while frequency distributions of the risk alleles for the diseases with weak environmental/lifestyle influences is shifted to the lower values indicating effects of negative selection. We hypothesized that previously selectively neutral variants become risk alleles when environment changes. The hypothesis of ancestrally neutral, currently disadvantageous risk-associated alleles predicts that the distribution of risk alleles for the environment/lifestyle dependent diseases will follow a neutral model since natural selection has not had enough time to influence allele frequencies. The results of our analysis suggest that prediction of SNP functionality based on the level of evolutionary conservation may not be useful for SNPs associated with environment/lifestyle dependent diseases.

An association-adjusted consensus deleterious scheme to classify homozygous Mis-sense mutations for personal genome interpretation.

BackgroundPersonal genome analysis is now being considered for evaluation of disease risk in healthy individuals, utilizing both rare and common variants. Multiple scores have been developed to predict the deleteriousness of amino acid substitutions, using information on the allele frequencies, level of evolutionary conservation, and averaged structural evidence. However, agreement among these scores is limited and they likely over-estimate the fraction of the genome that is deleterious.MethodThis study proposes an integrative approach to identify a subset of homozygous non-synonymous single nucleotide polymorphisms (nsSNPs). An 8-level classification scheme is constructed from the presence/absence of deleterious predictions combined with evidence of association with disease or complex traits. Detailed literature searches and structural validations are then performed for a subset of homozygous 826 mis-sense mutations in 575 proteins found in the genomes of 12 healthy adults.ResultsImplementation of the Association-Adjusted Consensus Deleterious Scheme (AACDS) classifies 11% of all predicted highly deleterious homozygous variants as most likely to influence disease risk. The number of such variants per genome ranges from 0 to 8 with no significant difference between African and Caucasian Americans. Detailed analysis of mutations affecting the APOE, MTMR2, THSB1, CHIA, αMyHC, and AMY2A proteins shows how the protein structure is likely to be disrupted, even though the associated phenotypes have not been documented in the corresponding individuals.ConclusionsThe classification system for homozygous nsSNPs provides an opportunity to systematically rank nsSNPs based on suggestive evidence from annotations and sequence-based predictions. The ranking scheme, in-depth literature searches, and structural validations of highly prioritized mis-sense mutations compliment traditional sequence-based approaches and should have particular utility for the development of individualized health profiles. An online tool reporting the AACDS score for any variant is provided at the authors’ website.

The 70S ribosome modulates the ATPase activity of Escherichia coli YchF

YchF is one of two universally conserved GTPases with unknown cellular function. As a first step toward elucidating YchF’s cellular role, we performed a detailed biochemical characterization of the protein from Escherichia coli. Our data from fluorescence titrations not only confirmed the surprising finding that YchFE.coli binds adenine nucleotides more efficiently than guanine nucleotides, but also provides the first evidence suggesting that YchF assumes two distinct conformational states (ATP- and ADP-bound) consistent with the functional cycle of a typical GTPase. Based on an in vivo pull-down experiment using a His-tagged variant of YchF from E. coli (YchFE.coli), we were able to isolate a megadalton complex containing the 70S ribosome. Based on this finding, we report the successful reconstitution of a YchF•70S complex in vitro, revealing an affinity (KD) of the YchFE.coli•ADPNP complex for 70S ribosomes of 3 μM. The in vitro reconstitution data also suggests that the identity of the nucleotide-bound state of YchF (ADP or ATP) modulates its affinity for 70S ribosomes. A detailed Michaelis-Menten analysis of YchF’s catalytic activity in the presence and the absence of the 70S ribosome and its subunits revealed for the first time that the 70S ribosome is able to stimulate YchF’s ATPase activity (~10-fold), confirming the ribosome as part of the functional cycle of YchF. Our findings taken together with previously reported data for the human homolog of YchF (hOLA1) indicate a high level of evolutionary conservation in the enzymatic properties of YchF and suggest that the ribosome is the main functional partner of YchF not only in bacteria.

Presenting ENCODE

The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription-factor association, chromatin structure and histone modification. In this overview, the Consortium guides the readers through the project itself, the data and their integrated analyses. Eighty per cent of the human genome now has at least one biochemical function assigned to it. In addition to expanding our understanding of how gene expression is regulated on a genome-wide scale, the newly identified functional elements should help researchers to interpret the results of genome-wide associated studies because many correspond to sites associated with human disease. This paper describes the first extensive map of human DNaseI hypersensitive sites — markers of regulatory DNA — in 125 diverse cell and tissue types. Integration of this information with other data sets generated by ENCODE (Encyclopedia of DNA Elements) identified new relationships between chromatin accessibility, transcription, DNA methylation and regulatory-factor occupancy patterns. Evolutionary-conservation analysis revealed signatures of recent functional constraint within DNaseI hypersensitive sites. DNaseI footprinting detects DNA sequences that are protected from cleavage by DNaseI because they are bound by regulatory factors. Studying these footprints in 41 diverse cell and tissue types, the authors describe millions of short sequence elements that are conserved recognition sequences for DNA-binding proteins. The effort nearly doubles the size of the human cis-regulatory lexicon and provides insight into chromatin states and levels of evolutionary conservation. A large collection of novel regulatory-factor recognition motifs that closely parallel major regulators of development, differentiation and pluripotency is also described. This manuscript describes the effort of the ENCODE (Encyclopedia of DNA Elements) Consortium to examine the principles of human transcriptional regulatory networks, using a subset of 119 transcription factors. The results are integrated with other genomic information to form a multi-level meta-network in which different levels have distinct properties. The findings will aid future interpretations of human genomics and help us to understand the basic principles of human biology and disease. These authors describe the ENCODE (Encyclopedia of DNA Elements) effort to provide a complete catalogue of primary and processed RNAs found either in specific sub-cellular compartments or throughout the cell. They show that three-quarters of the human genome can be transcribed, and provide a wealth of information about the range and levels of expression, localization, processing fates and modifications of both known and previously unannotated RNAs. Collectively, these observations suggest that the current concept of a gene should be revisited. In this ENCODE (Encyclopedia of DNA Elements) manuscript, the authors use chromosome conformation capture carbon copy (5C2) to look at the relationships between functional elements and distal target genes in 1% of the human genome in three dimensions. They describe numerous long-range interactions between promoters and distal sites that include elements resembling enhancers, promoters and CTCF-bound sites, their genomic distribution and complex interactions. Because only ∼7% of looping interactions are with the nearest gene, genomic proximity is not a simple predictor for long-range interactions.

ConSurf 2005: the projection of evolutionary conservation scores of residues on protein structures

Key amino acid positions that are important for maintaining the 3D structure of a protein and/or its function(s), e.g. catalytic activity, binding to ligand, DNA or other proteins, are often under strong evolutionary constraints. Thus, the biological importance of a residue often correlates with its level of evolutionary conservation within the protein family. ConSurf () is a web-based tool that automatically calculates evolutionary conservation scores and maps them on protein structures via a user-friendly interface. Structurally and functionally important regions in the protein typically appear as patches of evolutionarily conserved residues that are spatially close to each other. We present here version 3.0 of ConSurf. This new version includes an empirical Bayesian method for scoring conservation, which is more accurate than the maximum-likelihood method that was used in the earlier release. Various additional steps in the calculation can now be controlled by a number of advanced options, thus further improving the accuracy of the calculation. Moreover, ConSurf version 3.0 also includes a measure of confidence for the inferred amino acid conservation scores.

Purification and characterization of cyclic AMP-dependent protein kinase from Candida albicans

A protein (molecular mass 66 kDa) that bound cAMP in a highly specific manner was purified to electrophoretic homogeneity from yeast cells of the important opportunistic fungal pathogen Candida albicans . The protein was identified as a regulatory subunit of a cAMP-dependent protein kinase (protein kinase A; PKA) when it was incubated with protein kinase activity partly purified from C. albicans : phosphotransferase activity was inhibited in a dose-dependent manner and the inhibition was readily reversed by the addition of cAMP. In general, the substrate specificity of the C. albicans PKA catalytic subunit reflected that observed for other PKAs. Furthermore, enzyme activity was sensitive to the specific and potent inhibitor of mammalian PKAs, PKI 6–22′ and the C. albicans regulatory subunit inhibited bovine PKA catalytic subunit activity. These results indicate a high level of evolutionary conservation of the genes encoding PKA regulatory and catalytic subunits.