ArticleBMC evolutionary biology2004
Evolutionary rate depends on number of protein-protein interactions independently of gene expression level.
Article in BMC evolutionary biology, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
- Rubisco is evolving for improved catalytic efficiency and COProceedings of the National Academy of Sciences of the United States of America · 2024Article
- Abundance Imparts Evolutionary Constraints of Similar Magnitude on the Buried, Surface, and Disordered Regions of Proteins.Frontiers in molecular biosciences · 2021Article
- Protein Complexes Form a Basis for Complex Hybrid Incompatibility.Frontiers in genetics · 2021Review
- Gene expression predictions and networks in natural populations supports the omnigenic theory.BMC genomics · 2020Article
- Identifying genuine protein-protein interactions within communities of gene co-expression networks using a deconvolution method.IET systems biology · 2019Article
- Position Matters: Network Centrality Considerably Impacts Rates of Protein Evolution in the Human Protein-Protein Interaction Network.Genome biology and evolution · 2017Article
- Differential variation patterns between hubs and bottlenecks in human protein-protein interaction networks.BMC evolutionary biology · 2016Article
- Complex Patterns of Association between Pleiotropy and Transcription Factor Evolution.Genome biology and evolution · 2016Article
- Positive Selection and Centrality in the Yeast and Fly Protein-Protein Interaction Networks.BioMed research international · 2016Article
- Lineage-specific sequence evolution and exon edge conservation partially explain the relationship between evolutionary rate and expression level in A. thaliana.Molecular ecology · 2015Article
- Evolutionary rate patterns of genes involved in the Drosophila Toll and Imd signaling pathway.BMC evolutionary biology · 2013Article
- Novel insights through the integration of structural and functional genomics data with protein networks.Journal of structural biology · 2012Article
- Evolutionary rate and duplicability in the Arabidopsis thaliana protein-protein interaction network.Genome biology and evolution · 2012Article
- Testing hypotheses on the rate of molecular evolution in relation to gene expression using microRNAs.Proceedings of the National Academy of Sciences of the United States of America · 2011Article
- The relationships among microRNA regulation, intrinsically disordered regions, and other indicators of protein evolutionary rate.Molecular biology and evolution · 2011Article
- Evidence for the additions of clustered interacting nodes during the evolution of protein interaction networks from network motifs.BMC evolutionary biology · 2011Article
- Community transcriptomics reveals universal patterns of protein sequence conservation in natural microbial communities.Genome biology · 2011Article
- Patterns of positive selection and neutral evolution in the protein-coding genes of Tetraodon and Takifugu.PloS one · 2011Article
- Understanding protein evolutionary rate by integrating gene co-expression with protein interactions.BMC systems biology · 2010Article
- Shifts in the intensity of purifying selection: an analysis of genome-wide polymorphism data from two closely related yeast species.Genome research · 2010Article
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Abstract
backgroundWhether or not a protein's number of physical interactions with other proteins plays a role in determining its rate of evolution has been a contentious issue. A recent analysis suggested that the observed correlation between number of interactions and evolutionary rate may be due to experimental biases in high-throughput protein interaction data sets. DISCUSSION: The number of interactions per protein, as measured by some protein interaction data sets, shows no correlation with evolutionary rate. Other data sets, however, do reveal a relationship. Furthermore, even when experimental biases of these data sets are taken into account, a real correlation between number of interactions and evolutionary rate appears to exist. SUMMARY: A strong and significant correlation between a protein's number of interactions and evolutionary rate is apparent for interaction data from some studies. The extremely low agreement between different protein interaction data sets indicates that interaction data are still of low coverage and/or quality. These limitations may explain why some data sets reveal no correlation with evolutionary rates.
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