ArticleGenome biology and evolution2020
The Dynamics, Causes, and Impacts of Mammalian Evolutionary Rates Revealed by the Analyses of Capybara Draft Genome Sequences.
Article in Genome biology and evolution, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Transcriptome sequencing reveals the evolutionary histories and gene expression evolution in two related Pagurus species.PloS one · 2025Article
- Omics in mini-livestock: a genomic perspective on the future of sustainable food systems.Frontiers in genetics · 2025Review
- Population structure and evolutionary history of the greater cane rat (Frontiers in genetics · 2023Article
- The effects of sequencing depth on the assembly of coding and noncoding transcripts in the human genome.BMC genomics · 2022Article
- Concurrent Evolution of Antiaging Gene Duplications and Cellular Phenotypes in Long-Lived Turtles.Genome biology and evolution · 2021Article
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2 authors.
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Abstract
Capybara (Hydrochoerus hydrochaeri) is the largest species among the extant rodents. The draft genome of capybara was sequenced with the estimated genome size of 2.6 Gb. Although capybara is about 60 times larger than guinea pig, comparative analyses revealed that the neutral evolutionary rates of the two species were not substantially different. However, analyses of 39 mammalian genomes revealed very heterogeneous evolutionary rates. The highest evolutionary rate, 8.5 times higher than the human rate, was found in the Cricetidae-Muridae common ancestor after the divergence of Spalacidae. Muridae, the family with the highest number of species among mammals, emerged after the rate acceleration. Factors responsible for the evolutionary rate heterogeneity were investigated through correlations between the evolutionary rate and longevity, gestation length, litter frequency, litter size, body weight, generation interval, age at maturity, and taxonomic order. The regression analysis of these factors showed that the model with three factors (taxonomic order, generation interval, and litter size) had the highest predictive power (R2 = 0.74). These three factors determine the number of meiosis per unit time. We also conducted transcriptome analysis and found that the evolutionary rate dynamics affects the evolution of gene expression patterns.
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