Evolution of proteins and gene expression levels are coupled in Drosophila and are independently associated with mRNA abundance, protein length, and number of protein-protein interactions - PubMed (original) (raw)
Comparative Study
. 2005 May;22(5):1345-54.
doi: 10.1093/molbev/msi122. Epub 2005 Mar 2.
Affiliations
- PMID: 15746013
- DOI: 10.1093/molbev/msi122
Comparative Study
Evolution of proteins and gene expression levels are coupled in Drosophila and are independently associated with mRNA abundance, protein length, and number of protein-protein interactions
Bernardo Lemos et al. Mol Biol Evol. 2005 May.
Abstract
Organismic evolution requires that variation at distinct hierarchical levels and attributes be coherently integrated, often in the face of disparate environmental and genetic pressures. A central part of the evolutionary analysis of biological systems remains to decipher the causal connections between organism-wide (or genome-wide) attributes (e.g., mRNA abundance, protein length, codon bias, recombination rate, genomic position, mutation rate, etc) as well as their role-together with mutation, selection, and genetic drift-in shaping patterns of evolutionary variation in any of the attributes themselves. Here we combine genome-wide evolutionary analysis of protein and gene expression data to highlight fundamental relationships among genomic attributes and their associations with the evolution of both protein sequences and gene expression levels. Our results show that protein divergence is positively coupled with both gene expression polymorphism and divergence. We show moreover that although the number of protein-protein interactions in Drosophila is negatively associated with protein divergence as well as gene expression polymorphism and divergence, protein-protein interactions cannot account for the observed coupling between regulatory and structural evolution. Furthermore, we show that proteins with higher rates of amino acid substitutions tend to have larger sizes and tend to be expressed at lower mRNA abundances, whereas genes with higher levels of gene expression divergence and polymorphism tend to have shorter sizes and tend to be expressed at higher mRNA abundances. Finally, we show that protein length is negatively associated with both number of protein-protein interactions and mRNA abundance and that interacting proteins in Drosophila show similar amounts of divergence. We suggest that protein sequences and gene expression are subjected to similar evolutionary dynamics, possibly because of similarity in the fitness effect (i.e., strength of stabilizing selection) of disruptions in a gene's protein sequence or its mRNA expression. We conclude that, as more and better data accumulate, understanding the causal connections among biological traits and how they are integrated over time to constrain or promote structural and regulatory evolution may finally become possible.
Similar articles
- Common pattern of evolution of gene expression level and protein sequence in Drosophila.
Nuzhdin SV, Wayne ML, Harmon KL, McIntyre LM. Nuzhdin SV, et al. Mol Biol Evol. 2004 Jul;21(7):1308-17. doi: 10.1093/molbev/msh128. Epub 2004 Mar 19. Mol Biol Evol. 2004. PMID: 15034135 - Regulatory evolution across the protein interaction network.
Lemos B, Meiklejohn CD, Hartl DL. Lemos B, et al. Nat Genet. 2004 Oct;36(10):1059-60. doi: 10.1038/ng1427. Epub 2004 Sep 19. Nat Genet. 2004. PMID: 15378060 - Gene expression intensity shapes evolutionary rates of the proteins encoded by the vertebrate genome.
Subramanian S, Kumar S. Subramanian S, et al. Genetics. 2004 Sep;168(1):373-81. doi: 10.1534/genetics.104.028944. Genetics. 2004. PMID: 15454550 Free PMC article. - Genetic recombination and molecular evolution.
Charlesworth B, Betancourt AJ, Kaiser VB, Gordo I. Charlesworth B, et al. Cold Spring Harb Symp Quant Biol. 2009;74:177-86. doi: 10.1101/sqb.2009.74.015. Epub 2009 Sep 4. Cold Spring Harb Symp Quant Biol. 2009. PMID: 19734202 Review. - An integrated view of the correlations between genomic and phenomic variables.
Yang D, Jiang Y, He F. Yang D, et al. J Genet Genomics. 2009 Nov;36(11):645-51. doi: 10.1016/S1673-8527(08)60156-3. J Genet Genomics. 2009. PMID: 19932460 Review.
Cited by
- The Effects of De Novo Mutation on Gene Expression and the Consequences for Fitness in Chlamydomonas reinhardtii.
Balogun EJ, Ness RW. Balogun EJ, et al. Mol Biol Evol. 2024 Mar 1;41(3):msae035. doi: 10.1093/molbev/msae035. Mol Biol Evol. 2024. PMID: 38366781 Free PMC article. - Predicting evolutionary targets and parameters of gene deletion from expression data.
Campelo Dos Santos AL, DeGiorgio M, Assis R. Campelo Dos Santos AL, et al. Bioinform Adv. 2024 Jan 17;4(1):vbae002. doi: 10.1093/bioadv/vbae002. eCollection 2024. Bioinform Adv. 2024. PMID: 38282974 Free PMC article. - Predicting gene expression divergence between single-copy orthologs in two species.
Piya AA, DeGiorgio M, Assis R. Piya AA, et al. Genome Biol Evol. 2023 May 12;15(5):evad078. doi: 10.1093/gbe/evad078. Online ahead of print. Genome Biol Evol. 2023. PMID: 37170892 Free PMC article. - Transcriptional misexpression in hybrids between species linked by gene flow is associated with patterns of sequence divergence.
Díaz F, Wolf J, de Brito RA. Díaz F, et al. Genome Biol Evol. 2023 May 8;15(5):evad071. doi: 10.1093/gbe/evad071. Online ahead of print. Genome Biol Evol. 2023. PMID: 37154104 Free PMC article. - Genes Vary Greatly in Their Propensity for Collateral Fitness Effects of Mutations.
Mehlhoff JD, Ostermeier M. Mehlhoff JD, et al. Mol Biol Evol. 2023 Mar 4;40(3):msad038. doi: 10.1093/molbev/msad038. Mol Biol Evol. 2023. PMID: 36798991 Free PMC article.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Molecular Biology Databases