Evidence map›Paper›PMID 31203476›Full record

ArticleMarine biotechnology (New York, N.Y.)2019

Adaptive Evolution Patterns in the Pacific Oyster Crassostrea gigas.

Kai Song, Shiyong Wen, Guofan Zhang

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In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Kai SongSchool of Mathematics and Statistics, Qingdao University, Qingdao, 266071, Shandong, China. songkai1987@126.com.
Shiyong WenCollege of Veterinary Medicine, Inner Mongolia Agricultural University, Huhhot, 010018, China.
Guofan ZhangKey Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, Shandong, China. gzhang@qdio.ac.cn.

Funding

National Natural Science Foundation of China 11701546National Natural Science Foundation of China 31530079
6 · The paper itself

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.

Indexed as

Evolution, MolecularTranscriptomeAdaptation, PhysiologicalAlternative SplicingAnimalsCrassostreaExonsGenomeImmunity, InnateIntronsSelection, GeneticAdaptive evolution ratesCrassostrea gigasGene expression pattern

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.