ArticleMarine biotechnology (New York, N.Y.)2019
Adaptive Evolution Patterns in the Pacific Oyster Crassostrea gigas.
Article in Marine biotechnology (New York, N.Y.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Genomic Landscape of Mutational Biases in the Pacific Oyster Crassostrea gigas.Genome biology and evolution · 2020Article
- Evaluation of Genomic Selection for Seven Economic Traits in Yellow Drum (Nibea albiflora).Marine biotechnology (New York, N.Y.) · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Estimation of adaptive evolution rates at the molecular level is important in evolutionary genomics. However, knowledge of adaptive evolutionary patterns in Mollusca is very scarce, especially for oysters. Such information would help clarify how oysters adapt to pathogen-rich and dynamically changing intertidal environments. In this study, we characterized the patterns of adaptive evolution in the Crassostrea gigas genome, using population diversity analysis and congeneric comparison. Our analysis revealed that gene expression patterns were positively associated with adaptive evolution rates, which suggested that positive selection played an important role in gene evolution. The genes with more exons and alternative splicing events had higher adaptive evolution rates. The rates of adaptive evolution in immune-related and stress-response genes were higher than those in other genes, suggesting that these groups of genes experienced strong positive selection. This study represents the first analysis of adaptive evolution rates in oysters and the first comprehensive study of a Mollusca species. These results provide a system-level investigation of association between adaptive evolution rates with some intrinsic genetic factors. They also suggest that adaptation to pathogens and environmental stressors are important forces driving the adaptive evolution of genes.
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Registered trials
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