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Whole-genome resequencing of Japanese whiting (Sillago japonica) provide insights into local adaptations

Zhi-Qiang Han Xin-Yu Guo Qun Liu Shan-Shan Liu Zhi-Xin Zhang Shi-Jun Xiao Tian-Xiang Gao

Zhi-Qiang Han, Xin-Yu Guo, Qun Liu, Shan-Shan Liu, Zhi-Xin Zhang, Shi-Jun Xiao, Tian-Xiang Gao. Whole-genome resequencing of Japanese whiting (Sillago japonica) provide insights into local adaptations. Zoological Research, 2021, 42(5): 548-561. doi: 10.24272/j.issn.2095-8137.2021.116
Citation: Zhi-Qiang Han, Xin-Yu Guo, Qun Liu, Shan-Shan Liu, Zhi-Xin Zhang, Shi-Jun Xiao, Tian-Xiang Gao. Whole-genome resequencing of Japanese whiting (Sillago japonica) provide insights into local adaptations. Zoological Research, 2021, 42(5): 548-561. doi: 10.24272/j.issn.2095-8137.2021.116

基于全基因组重测序的少鳞鱚(Sillago japonica)地理群体本地适应进化研究

doi: 10.24272/j.issn.2095-8137.2021.116

Whole-genome resequencing of Japanese whiting (Sillago japonica) provide insights into local adaptations

Funds: The study was supported by the National Natural Science Foundation of China (41976083, 41776171 and 32072980)
More Information
  • 摘要: 西北太平洋地区海洋生物对不同环境的适应进化研究尚未系统开展。种群之间的基因组差异能够反映环境选择作用。开展海洋生物群体对温度适应进化研究对于理解生物对气候变化的适应机制以及预测生物对全球变暖的未来适应潜力非常重要。我们采集了少鳞鱚(Sillago japonica)中国和日本近海不同纬度的地理群体样品,利用全基因组重测序检测研究温度适应机制。我们对5个群体基因组重测序,获得548万个单核苷酸多态位点(SNPs),可以将中国和日本群体完全区分开。这种遗传结局形成主要是归因于地理隔离和本地适应性。两个隔离的种群(舟山和伊势湾/东京湾)之间共享大量受选择基因,这表明两种群间存在温度驱动的平行进化现象。这也表明温度对不同种群的选择过程可能是可重复的。此外,我们观察到冷适应的受选择基因在功能上主要跟细胞膜的流动性相关。物种分布预测模型表明,少鳞鱚中国和日本群体可能对未来的气候变化有不同的响应,在未来前者分布区将扩大,后者分布区将收缩。该研究的结果促进了对鱼类群体本地温度适应的遗传机制的理解,扩大了我们对群体遗传分化和群体如何适应温度变化的新认知。
  • Figure  1.  Map of sampling locations and population genomic analyses of Sillago japonica

    A: Map of sampling locations. Annual sea surface temperature is indicated. B: Genome-wide distribution of nucleotide diversity in 40 kb non-overlapping windows. C: Admixture analysis of five S. japonica populations. Length of each colored segment represents proportion of individual genome inferred from ancestral populations (K=2–6). D: Principal components 1 (27.80%) and 2 (16.95%) for 49 S. japonica individuals. E: Neighbor-joining tree constructed using p-distances of 49 S. japonica individuals. For abbreviations, see Table 1.

    Figure  2.  Isolation by distance, demographic history, and pattern of population splits

    A, B: Plot of pairwise estimates of FST/(1−FST) versus two types of geographic distance (i.e., coastal and oceanic distances) between populations. C: Demographic history for each population inferred from PSMC analysis. D, E: Pattern of population splits and mixture between five S. japonica populations. Drift parameter is proportional to Ne generations, where Ne is effective population size. Scale bar shows average standard error of estimated entries in sample covariance matrix.

    Figure  3.  Genomic regions with strong selective signals in populations of S. japonica

    A: Distribution of log2(θπ ratios) and FST values calculated in 40 kb sliding windows with 20 kb increments between RS/ZS populations (ZS as control group). Data points in red (corresponding to top 5% of empirical log2[θπ ratio] distributions with values of >0.1204 and top 5% of FST distributions with values of >0.0904) are genomic regions under selection in RS population. B: Overlapping candidate genes in RS/ZS and RS/ST pairs based on Venn diagram. C: Overlapping candidate genes in ZS/RS and Japan/RS pairs based on Venn diagram. D: Allele frequency of one SNP within cold-temperature adaptation gene Picalm across five S. japonica populations, red and blue represent two types of bases at this locus. E: Allele frequencies of one SNP within warm-temperature adaptation gene SORCS3 across five S. japonica populations, red and blue represent two types of bases at this locus.

    Figure  4.  PCA based on SNPs located in candidate genes and top 20 enriched KEGG pathways in candidate genes

    A: PCA based on cold-temperature adaptation genes. B: PCA based on warm-temperature adaptation genes. C: KEGG enrichment for cold-temperature adaptation genes. D: KEGG enrichment for warm-temperature adaptation genes.

    Figure  5.  Predicted potential distribution (A, B), changes in habitat suitability (C) of Chinese group under RCP45 scenarios, and response curves of predicted occurrence probability (D) of Chinese group against temperature. Predicted potential distribution (E, F), changes in habitat suitability (G) of Japanese group under RCP45 scenarios, and response curves of predicted occurrence probability (H) of Japanese group against temperature

    Table  1.   Population samples of Sillago japonica used in this study

    Sample locationSample IDDate of collectionSample size (n)Nucleotide diversityJanuary
    temperature (°C)
    Mean
    temperature (°C)
    July
    temperature (°C)
    Range (°C)
    RushanRSAugust 2016100.0246±0.01387.0114.925.818.79
    ZhoushanZSJune 201690.0212±0.012012.719.128.115.43
    SantouSTJuly 2016100.02150±0.011324.525.229.14.62
    Ise BayIBJanuary 2009100.0208±0.010813.521.327.313.75
    Tokyo BayTBOctober 2009100.0213±0.010713.020.427.214.14
    Total49
    下载: 导出CSV

    Table  2.   Pairwise FST values for five populations

    SampleRSZSSTIB
    ZS0.0159*
    ST0.0214*0.0177*
    IB0.0237*0.0344*0.0325*
    TB0.0255*0.0377*0.0359*–0.0001
    *: P<0.05. For abbreviations, see Table 1.
    下载: 导出CSV
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  • 收稿日期:  2021-04-06
  • 录用日期:  2021-07-28
  • 网络出版日期:  2021-07-29
  • 刊出日期:  2021-09-18

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