Large-scale genome-wide study reveals climate adaptive variability in a cosmopolitan pest

文献类型： 外文期刊

第一作者： Chen, Yanting

作者： Chen, Yanting;Liu, Zhaoxia;Vasseur, Liette;Ke, Fushi;Chen, Shaoping;Li, Jianyu;Huang, Jieling;Gurr, Geoff M.;You, Minsheng;You, Shijun;Chen, Yanting;Liu, Zhaoxia;Vasseur, Liette;Ke, Fushi;Chen, Shaoping;Li, Jianyu;Huang, Jieling;Gurr, Geoff M.;You, Minsheng;You, Shijun;Chen, Yanting;Liu, Zhaoxia;Ke, Fushi;Chen, Shaoping;Li, Jianyu;Huang, Jieling;You, Minsheng;You, Shijun;Chen, Yanting;Chen, Shaoping;Li, Jianyu;Liu, Zhaoxia;Regniere, Jacques;Vasseur, Liette;Lin, Jian;Huang, Shiguo;Ke, Fushi;Gurr, Geoff M.

作者机构：

期刊名称：NATURE COMMUNICATIONS （ 影响因子：17.694； 五年影响因子：17.763 ）

ISSN：

年卷期： 2021 年 12 卷 1 期

页码：

收录情况： SCI

摘要： The diamondback moth is a cosmopolitan pest of significant economic importance. Here the authors analyse globally distributed genomic data to find evidence of climate-associated adaptive variation, and use an ecogenetic index to predict that it will maintain a global pest status under climate change. Understanding the genetic basis of climatic adaptation is essential for predicting species' responses to climate change. However, intraspecific variation of these responses arising from local adaptation remains ambiguous for most species. Here, we analyze genomic data from diamondback moth (Plutella xylostella) collected from 75 sites spanning six continents to reveal that climate-associated adaptive variation exhibits a roughly latitudinal pattern. By developing an eco-genetic index that combines genetic variation and physiological responses, we predict that most P. xylostella populations have high tolerance to projected future climates. Using genome editing, a key gene, PxCad, emerged from our analysis as functionally temperature responsive. Our results demonstrate that P. xylostella is largely capable of tolerating future climates in most of the world and will remain a global pest beyond 2050. This work improves our understanding of adaptive variation along environmental gradients, and advances pest forecasting by highlighting the genetic basis for local climate adaptation.

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