scholarly journals Intermolecular interactions drive protein adaptive and co-adaptive evolution at both species and population levels

2021 ◽  
Author(s):  
Junhui Peng ◽  
Li Zhao
Keyword(s):  
Intermolecular Interactions ◽  
Adaptive Evolution ◽  
Large Scale ◽  
Genomic Analysis ◽  
Building Blocks ◽  
Protein Coding ◽  
Functional Annotations ◽  
Protein Coding Genes ◽  
Almost All ◽  
Evolution Of Proteins

AbstractProteins are the building blocks for almost all the functions in cells. Understanding the molecular evolution of proteins and the forces that shape protein evolution is an essential step in understanding the basis of function and evolution. Previous studies have shown that adaptation occurs frequently at the protein surface, such as in genes involved in host-pathogen interactions. However, it remains unclear whether adaptive sites are distributed randomly or at regions that are associated with particular structural or functional characteristics across the genome, since many of the proteins lack structural or functional annotations. Here, we seek to tackle this question by combining large-scale bioinformatic prediction, structural analysis, phylogenetic inference, and population genomic analysis of Drosophila protein-coding genes. By estimating and comparing the rate of adaptive substitutions at protein and residue level, we showed that adaptation is more relevant to function-related rather than structure-related properties. Among the function-related properties, we found that molecular interactions in proteins contribute to adaptive evolution, and putative binding residues exhibit higher rates of adaptation. We observed that physical interactions might play a role in the co-adaptation of fast-adaptive proteins. We found that strongly differentiated amino acids in protein coding genes are mostly adaptive, which may contribute to the long-term adaptive evolution. Our results suggest important roles of intermolecular interactions and co-adaptation in the adaptive evolution of proteins both at the species and population levels.

scholarly journals Intermolecular interactions drive protein adaptive and co-adaptive evolution at both species and population levels

2021 ◽  
Author(s):  
Junhui Peng ◽  
Nicolas Svetec ◽  
Li Zhao
Keyword(s):  
Intermolecular Interactions ◽  
Adaptive Evolution ◽  
Large Scale ◽  
Genomic Analysis ◽  
Building Blocks ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Drosophila Protein ◽  
Almost All ◽  
Evolution Of Proteins

Abstract Proteins are the building blocks for almost all the functions in cells. Understanding the molecular evolution of proteins and the forces that shape protein evolution is essential in understanding the basis of function and evolution. Previous studies have shown that adaptation frequently occurs at the protein surface, such as in genes involved in host-pathogen interactions. However, it remains unclear whether adaptive sites are distributed randomly or at regions associated with particular structural or functional characteristics across the genome, since many proteins lack structural or functional annotations. Here, we seek to tackle this question by combining large-scale bioinformatic prediction, structural analysis, phylogenetic inference, and population genomic analysis of Drosophila protein-coding genes. We found that protein sequence adaptation is more relevant to function-related rather than structure-related properties. Interestingly, intermolecular interactions contribute significantly to protein adaptation. We further showed that intermolecular interactions, such as physical interactions, may play a role in the co-adaptation of fast-adaptive proteins. We found that strongly differentiated amino acids across geographic regions in protein-coding genes are mostly adaptive, which may contribute to the long-term adaptive evolution. This strongly indicates that a number of adaptive sites tend to be repeatedly mutated and selected in evolution, in the past, present, and maybe future. Our results highlight the important roles of intermolecular interactions and co-adaptation in the adaptive evolution of proteins both at the species and population levels.

scholarly journals PaperBLAST: Text-mining papers for information about homologs

2017 ◽  
Author(s):  
Morgan N. Price ◽  
Adam P. Arkin
Keyword(s):  
Text Mining ◽  
Genome Sequencing ◽  
Full Text ◽  
Large Scale ◽  
Scientific Literature ◽  
Protein Sequences ◽  
Protein Coding ◽  
Link Protein ◽  
Protein Coding Genes ◽  
Link Type

AbstractLarge-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific literature. To make this information accessible, PaperBLAST uses EuropePMC to search the full text of scientific articles for references to genes. PaperBLAST also takes advantage of curated resources that link protein sequences to scientific articles (Swiss-Prot, GeneRIF, and EcoCyc). PaperBLAST’s database includes over 700,000 scientific articles that mention over 400,000 different proteins. Given a protein of interest, PaperBLAST quickly finds similar proteins that are discussed in the literature and presents snippets of text from relevant articles or from the curators. PaperBLAST is available at http://papers.genomics.lbl.gov/.

scholarly journals Comparative analysis of chloroplast genomes for five Dicliptera species (Acanthaceae): molecular structure, phylogenetic relationships, and adaptive evolution

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8450 ◽  
Author(s):  
Sunan Huang ◽  
Xuejun Ge ◽  
Asunción Cano ◽  
Betty Gaby Millán Salazar ◽  
Yunfei Deng
Keyword(s):  
Adaptive Evolution ◽  
Phylogenetic Relationships ◽  
Single Copy ◽  
Rrna Genes ◽  
Trna Genes ◽  
Evolutionary Analysis ◽  
Protein Coding ◽  
Variable Regions ◽  
Protein Coding Genes ◽  
Chloroplast Genomes

The genus Dicliptera (Justicieae, Acanthaceae) consists of approximately 150 species distributed throughout the tropical and subtropical regions of the world. Newly obtained chloroplast genomes (cp genomes) are reported for five species of Dilciptera (D. acuminata, D. peruviana, D. montana, D. ruiziana and D. mucronata) in this study. These cp genomes have circular structures of 150,689–150,811 bp and exhibit quadripartite organizations made up of a large single copy region (LSC, 82,796–82,919 bp), a small single copy region (SSC, 17,084–17,092 bp), and a pair of inverted repeat regions (IRs, 25,401–25,408 bp). Guanine-Cytosine (GC) content makes up 37.9%–38.0% of the total content. The complete cp genomes contain 114 unique genes, including 80 protein-coding genes, 30 transfer RNA (tRNA) genes, and four ribosomal RNA (rRNA) genes. Comparative analyses of nucleotide variability (Pi) reveal the five most variable regions (trnY-GUA-trnE-UUC, trnG-GCC, psbZ-trnG-GCC, petN-psbM, and rps4-trnL-UUA), which may be used as molecular markers in future taxonomic identification and phylogenetic analyses of Dicliptera. A total of 55-58 simple sequence repeats (SSRs) and 229 long repeats were identified in the cp genomes of the five Dicliptera species. Phylogenetic analysis identified a close relationship between D. ruiziana and D. montana, followed by D. acuminata, D. peruviana, and D. mucronata. Evolutionary analysis of orthologous protein-coding genes within the family Acanthaceae revealed only one gene, ycf15, to be under positive selection, which may contribute to future studies of its adaptive evolution. The completed genomes are useful for future research on species identification, phylogenetic relationships, and the adaptive evolution of the Dicliptera species.

scholarly journals Comparative genomic analysis of Methanimicrococcus blatticola provides insights into host adaptation in archaea and the evolution of methanogenesis

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Courtney M. Thomas ◽  
Najwa Taib ◽  
Simonetta Gribaldo ◽  
Guillaume Borrel
Keyword(s):  
Gut Microbiota ◽  
Large Scale ◽  
Genomic Analysis ◽  
Host Adaptation ◽  
Comparative Genomic Analysis ◽  
Comparative Genomic ◽  
Methyl Branch ◽  
Mechanisms Of Adaptation ◽  
Hydrogenotrophic Methanogens ◽  
Almost All

AbstractOther than the Methanobacteriales and Methanomassiliicoccales, the characteristics of archaea that inhabit the animal microbiome are largely unknown. Methanimicrococcus blatticola, a member of the Methanosarcinales, currently reunites two unique features within this order: it is a colonizer of the animal digestive tract and can only reduce methyl compounds with H2 for methanogenesis, a increasingly recognized metabolism in the archaea and whose origin remains debated. To understand the origin of these characteristics, we have carried out a large-scale comparative genomic analysis. We infer the loss of more than a thousand genes in M. blatticola, by far the largest genome reduction across all Methanosarcinales. These include numerous elements for sensing the environment and adapting to more stable gut conditions, as well as a significant remodeling of the cell surface components likely involved in host and gut microbiota interactions. Several of these modifications parallel those previously observed in phylogenetically distant archaea and bacteria from the animal microbiome, suggesting large-scale convergent mechanisms of adaptation to the gut. Strikingly, M. blatticola has lost almost all genes coding for the H4MPT methyl branch of the Wood–Ljungdahl pathway (to the exception of mer), a phenomenon never reported before in any member of Class I or Class II methanogens. The loss of this pathway illustrates one of the evolutionary processes that may have led to the emergence of methyl-reducing hydrogenotrophic methanogens, possibly linked to the colonization of organic-rich environments (including the animal gut) where both methyl compounds and hydrogen are abundant.

scholarly journals A Bayesian Mutation–Selection Framework for Detecting Site-Specific Adaptive Evolution in Protein-Coding Genes

2020 ◽  
Author(s):  
Nicolas Rodrigue ◽  
Thibault Latrille ◽  
Nicolas Lartillot
Keyword(s):  
Adaptive Evolution ◽  
Real Data ◽  
Data Sets ◽  
Protein Coding ◽  
Site Specific ◽  
Protein Coding Genes ◽  
Codon Substitution ◽  
Selection Framework ◽  
Dna Alignment ◽  
The Impact

Abstract In recent years, codon substitution models based on the mutation–selection principle have been extended for the purpose of detecting signatures of adaptive evolution in protein-coding genes. However, the approaches used to date have either focused on detecting global signals of adaptive regimes—across the entire gene—or on contexts where experimentally derived, site-specific amino acid fitness profiles are available. Here, we present a Bayesian site-heterogeneous mutation–selection framework for site-specific detection of adaptive substitution regimes given a protein-coding DNA alignment. We offer implementations, briefly present simulation results, and apply the approach on a few real data sets. Our analyses suggest that the new approach shows greater sensitivity than traditional methods. However, more study is required to assess the impact of potential model violations on the method, and gain a greater empirical sense its behavior on a broader range of real data sets. We propose an outline of such a research program.

scholarly journals Discovering long noncoding RNA predictors of anticancer drug sensitivity beyond protein-coding genes

2019 ◽  
Vol 116 (44) ◽  
pp. 22020-22029 ◽  
Author(s):  
Aritro Nath ◽  
Eunice Y. T. Lau ◽  
Adam M. Lee ◽  
Paul Geeleher ◽  
William C. S. Cho ◽  
...  
Keyword(s):  
Anticancer Drug ◽  
Noncoding Rna ◽  
Large Scale ◽  
Drug Response ◽  
Cancer Cell Line ◽  
Systematic Evaluation ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Clinical Biomarkers ◽  
Response Predictors

Large-scale cancer cell line screens have identified thousands of protein-coding genes (PCGs) as biomarkers of anticancer drug response. However, systematic evaluation of long noncoding RNAs (lncRNAs) as pharmacogenomic biomarkers has so far proven challenging. Here, we study the contribution of lncRNAs as drug response predictors beyond spurious associations driven by correlations with proximal PCGs, tissue lineage, or established biomarkers. We show that, as a whole, the lncRNA transcriptome is equally potent as the PCG transcriptome at predicting response to hundreds of anticancer drugs. Analysis of individual lncRNAs transcripts associated with drug response reveals nearly half of the significant associations are in fact attributable to proximal cis-PCGs. However, adjusting for effects of cis-PCGs revealed significant lncRNAs that augment drug response predictions for most drugs, including those with well-established clinical biomarkers. In addition, we identify lncRNA-specific somatic alterations associated with drug response by adopting a statistical approach to determine lncRNAs carrying somatic mutations that undergo positive selection in cancer cells. Lastly, we experimentally demonstrate that 2 lncRNAs, EGFR-AS1 and MIR205HG, are functionally relevant predictors of anti-epidermal growth factor receptor (EGFR) drug response.

scholarly journals Preliminary assessment of adaptive evolution of mitochondrial protein coding genes in darters (Percidae: Etheostomatinae)

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 464 ◽  
Author(s):  
Leos G. Kral ◽  
Sara Watson
Keyword(s):  
Positive Selection ◽  
Adaptive Evolution ◽  
Gene Evolution ◽  
Mitochondrial Gene ◽  
Mitochondrial Protein ◽  
Preliminary Assessment ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Show Evidence ◽  
Selection Of

Background: Mitochondrial DNA of vertebrates contains genes for 13 proteins involved in oxidative phosphorylation. Some of these genes have been shown to undergo adaptive evolution in a variety of species. This study examines all mitochondrial protein coding genes in 11 darter species to determine if any of these genes show evidence of positive selection. Methods: The mitogenome from four darter was sequenced and annotated. Mitogenome sequences for another seven species were obtained from GenBank. Alignments of each of the protein coding genes were subject to codon-based identification of positive selection by Selecton, MEME and FEL. Results: Evidence of positive selection was obtained for six of the genes by at least one of the methods. CYTB was identified as having evolved under positive selection by all three methods at the same codon location. Conclusions: Given the evidence for positive selection of mitochondrial protein coding genes in darters, a more extensive analysis of mitochondrial gene evolution in all the extant darter species is warranted.

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