Copy Number Variation: A Substrate for Plant Adaptation and Stress Response in Arabidopsis

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Abstract

Copy number variation (CNV) in gene families plays a crucial role in genome evolution and adaptation. However, the evolutionary forces shaping CNV and its ecological relevance remain a key question in evolutionary biology. Here, we investigated CNV across four Brassicaceae species, Arabidopsis thaliana, A. lyrata, A. halleri, and Arabis alpina, to identify gene families undergoing rapid expansion or contraction. Using annotated proteomes and a birth-death model of gene family evolution, we identified 231 rapidly evolving gene families, enriched in functions related to regulation, information processing, multifunctional domains, and defense and stress responses. Focusing on defense- and stress-related gene families, we assessed CNV within populations of A. thaliana and A. lyrata using long-read assemblies. We identified 29 gene families exhibiting CNV both within and between species. These families showed frequent pseudogenization in roughly two-thirds of cases and functional divergence among paralogs, yet retained signatures of strong purifying selection, highlighting ecological constraint despite structural variation. Population clustering based on CNV patterns revealed distinct geographic structuring. In A. thaliana, populations from Cape Verde, Madeira, and Japan formed divergent clusters, while A. lyrata showed separation between North American, Siberian, and European populations, mirroring patterns observed from SNP data. Ecological modeling further revealed significant associations between CNV and bioclimatic variables, particularly more temperature-derived-variables than precipitation-derived-variables in A. lyrata. Additionally, unexplained CNV divergence in A. thaliana suggests additional local environmental drivers, such as edaphic conditions or biotic interactions. Our findings demonstrate that CNV in gene families that experienced rapid expansion and contraction among Arabidopsis species, contribute to local adaptation across complex environmental gradients.

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