标志性针叶树英国红豆杉(Taxus baccata L.)气候驱动(Mal)适应的基因组特征

IF 3.2 2区 生物学 Q1 EVOLUTIONARY BIOLOGY
Thomas Francisco, Maria Mayol, Elia Vajana, Miquel Riba, Marjana Westergren, Stephen Cavers, Sara Pinosio, Francesca Bagnoli, Maurizio Marchi, Filippos A. Aravanopoulos, Anna-Maria Farsakoglou, Ivan Scotti, Bruno Fady, Giovanni G. Vendramin, Juliette Archambeau, Andrea Piotti, Santiago C. González-Martínez
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引用次数: 0

摘要

对包括树木在内的许多物种来说,气候不适应的风险正在增加。开发可靠的方法来评估种群适应不良仍然是一项重大挑战。基因组补偿方法旨在通过描述种群在气候变化下保持适应性所需的基因组变化来预测气候适应不良。在这项研究中,我们评估了英国红豆杉(Taxus baccata)欧洲种群的气候不适应风险。英国红豆杉是一种长寿的树木,分布在欧洲、阿特拉斯山脉和近东地区,那里的许多种群规模很小或受到威胁。通过分析来自29个欧洲巴卡塔种群的475棵树的8616个snp,我们发现了当地气候适应的证据,气候解释了18.1%的遗传变异,通过基因型-环境关联(GEA)鉴定了100个不相关的气候相关位点。然后,我们评估了种群与整体基因-气候关联的偏差,以评估种群在局部适应或不同适应轨迹上的变异性,并发现低纬度种群的偏差最大。此外,我们预测基因组偏移,并成功地验证了这些预测使用表型性状评估来自26个群体的植物生长在一个比较实验。最后,我们综合了当前的局部适应、基因组抵消、历史遗传分化和有效迁移率等信息,表明地中海和高海拔巴卡塔种群比低海拔大西洋和大陆种群更容易受到气候变化的影响。我们的研究展示了基因组偏移框架在保护遗传学中的实际应用,为其进一步发展提供了见解,并强调了以种群为中心的方法的必要性,该方法结合了额外的统计数据和数据来源,以可靠地评估野生植物种群的气候脆弱性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Genomic Signatures of Climate-Driven (Mal)Adaptation in an Iconic Conifer, the English Yew (Taxus baccata L.)

Genomic Signatures of Climate-Driven (Mal)Adaptation in an Iconic Conifer, the English Yew (Taxus baccata L.)

The risk of climate maladaptation is increasing for numerous species, including trees. Developing robust methods to assess population maladaptation remains a critical challenge. Genomic offset approaches aim to predict climate maladaptation by characterizing the genomic changes required for populations to maintain their fitness under changing climates. In this study, we assessed the risk of climate maladaptation in European populations of English yew (Taxus baccata), a long-lived tree with a patchy distribution across Europe, the Atlas Mountains, and the Near East, where many populations are small or threatened. We found evidence suggesting local climate adaptation by analyzing 8616 SNPs in 475 trees from 29 European T. baccata populations, with climate explaining 18.1% of genetic variance and 100 unlinked climate-associated loci identified via genotype-environment association (GEA). Then, we evaluated the deviation of populations from the overall gene-climate association to assess variability in local adaptation or different adaptation trajectories across populations and found the highest deviations in low latitude populations. Moreover, we predicted genomic offsets and successfully validated these predictions using phenotypic traits assessed in plants from 26 populations grown in a comparative experiment. Finally, we integrated information from current local adaptation, genomic offset, historical genetic differentiation, and effective migration rates to show that Mediterranean and high-elevation T. baccata populations face higher vulnerability to climate change than low-elevation Atlantic and continental populations. Our study demonstrates the practical use of the genomic offset framework in conservation genetics, offers insights for its further development, and highlights the need for a population-centered approach that incorporates additional statistics and data sources to credibly assess climate vulnerability in wild plant populations.

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来源期刊
Evolutionary Applications
Evolutionary Applications 生物-进化生物学
CiteScore
8.50
自引率
7.30%
发文量
175
审稿时长
6 months
期刊介绍: Evolutionary Applications is a fully peer reviewed open access journal. It publishes papers that utilize concepts from evolutionary biology to address biological questions of health, social and economic relevance. Papers are expected to employ evolutionary concepts or methods to make contributions to areas such as (but not limited to): medicine, agriculture, forestry, exploitation and management (fisheries and wildlife), aquaculture, conservation biology, environmental sciences (including climate change and invasion biology), microbiology, and toxicology. All taxonomic groups are covered from microbes, fungi, plants and animals. In order to better serve the community, we also now strongly encourage submissions of papers making use of modern molecular and genetic methods (population and functional genomics, transcriptomics, proteomics, epigenetics, quantitative genetics, association and linkage mapping) to address important questions in any of these disciplines and in an applied evolutionary framework. Theoretical, empirical, synthesis or perspective papers are welcome.
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