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基于全基因组重测序的环境因子对佛手瓜种群遗传分化的影响。

The effect of environmental factors on the genetic differentiation of Cucurbita ficifolia populations based on whole-genome resequencing.

机构信息

College of Landscape and Horticulture, Yunnan Agricultural University, Kunming, 650201, Yunnan, China.

Key Laboratory of Vegetable Biology of Yunnan Province, College of Landscape and Horticulture, Yunnan Agricultural University, Kunming, 650201, Yunnan, China.

出版信息

BMC Plant Biol. 2023 Dec 15;23(1):647. doi: 10.1186/s12870-023-04602-3.

DOI:10.1186/s12870-023-04602-3
PMID:38102604
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10722772/
Abstract

BACKGROUND

Cucurbita ficifolia is one of the squash species most resistant to fungal pathogens, and has especially high resistance to melon Fusarium wilt. This species is therefore an important germplasm resource for the breeding of squash and melon cultivars.

RESULTS

Whole-genome resequencing of 223 individuals from 32 populations in Yunnan Province, the main cucurbit production area in China, was performed and 3,855,120 single-nucleotide polymorphisms (SNPs) and 1,361,000 InDels were obtained. SNP analysis suggested that levels of genetic diversity in C. ficifolia were high, but that different populations showed no significant genetic differentiation or geographical structure, and that individual C. ficifolia plants with fruit rinds of a similar color did not form independent clusters. A Mantel test conducted in combination with geographical distance and environmental factors suggested that genetic distance was not correlated with geographical distance, but had a significant correlation with environmental distance. Further associations between the genetic data and five environmental factors were analyzed using whole-genome association analysis. SNPs associated with each environmental factor were investigated and genes 250 kb upstream and downstream from associated SNPs were annotated. Overall, 15 marker-trait-associated SNPs (MTAs) and 293 genes under environmental selection were identified. The identified genes were involved in cell membrane lipid metabolism, macromolecular complexes, catalytic activity and other related aspects. Ecological niche modeling was used to simulate the distribution of C. ficifolia across time, from the present and into the future. We found that the area suitable for C. ficifolia changed with the changing climate in different periods.

CONCLUSIONS

Resequencing of the C. ficifolia accessions has allowed identification of genetic markers, such as SNPs and InDels. The SNPs identified in this study suggest that environmental factors mediated the formation of the population structure of C. ficifolia in China. These SNPs and Indels might also contribute to the variation in important pathways of genes for important agronomic traits such as yield, disease resistance and stress tolerance. Moreover, the genome resequencing data and the genetic markers identified from 223 accessions provide insight into the genetic variation of the C. ficifolia germplasm and will facilitate a broad range of genetic studies.

摘要

背景

佛手瓜是对真菌病原体最具抗性的南瓜品种之一,尤其对瓜枯萎病具有高抗性。因此,该物种是培育南瓜和瓜类品种的重要种质资源。

结果

对来自中国主要南瓜产区云南省 32 个种群的 223 个个体进行了全基因组重测序,获得了 385.512 个单核苷酸多态性(SNP)和 136.1000 个插入缺失(InDel)。SNP 分析表明,佛手瓜的遗传多样性水平较高,但不同种群之间没有显著的遗传分化或地理结构,并且果皮颜色相似的个体佛手瓜植物没有形成独立的聚类。与地理距离和环境因素相结合的 Mantel 检验表明,遗传距离与地理距离没有相关性,但与环境距离有显著相关性。进一步利用全基因组关联分析分析了遗传数据与五个环境因素之间的关联。研究了与每个环境因素相关的 SNP,并注释了与相关 SNP 上下游 250kb 的基因。总体上,鉴定了 15 个与标记性状相关的 SNP(MTAs)和 293 个受环境选择的基因。鉴定的基因涉及细胞膜脂质代谢、大分子复合物、催化活性等相关方面。生态位模型被用来模拟佛手瓜在不同时期的分布,从现在到未来。我们发现,适合佛手瓜的区域随着不同时期气候的变化而变化。

结论

对佛手瓜品系进行重测序,鉴定出了遗传标记,如 SNP 和 InDel。本研究鉴定的 SNP 表明,环境因素介导了中国佛手瓜种群结构的形成。这些 SNP 和 Indels 可能也有助于与产量、抗病性和抗逆性等重要农艺性状相关的重要基因途径的变异。此外,223 个品系的基因组重测序数据和鉴定的遗传标记为佛手瓜种质的遗传变异提供了深入了解,并将促进广泛的遗传研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b27/10722772/1f53b5784942/12870_2023_4602_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b27/10722772/ea522e012101/12870_2023_4602_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b27/10722772/ee4e13898a26/12870_2023_4602_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b27/10722772/8b50338afb23/12870_2023_4602_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b27/10722772/6505410c82da/12870_2023_4602_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b27/10722772/1f53b5784942/12870_2023_4602_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b27/10722772/ea522e012101/12870_2023_4602_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b27/10722772/9a1931be81e2/12870_2023_4602_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b27/10722772/ee4e13898a26/12870_2023_4602_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b27/10722772/8b50338afb23/12870_2023_4602_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b27/10722772/6505410c82da/12870_2023_4602_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b27/10722772/1f53b5784942/12870_2023_4602_Fig6_HTML.jpg

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