five

Detail informations of T. sinense samples.

收藏
Figshare2025-05-20 更新2026-04-28 收录
下载链接:
https://figshare.com/articles/dataset/Detail_informations_of_i_T_sinense_i_samples_/29111984
下载链接
链接失效反馈
官方服务:
资源简介:
Tetracentron sinense Oliv. (T. sinense), as a tertiary living fossil, has experienced a significant decline in population numbers. Currently, genetic resources depletion and human activities have led to habitat fragmentation of relict and endangered plants, despite the abundant evidence of its medicinal, economic, and ecological value. Conservation strategies were clarified and evaluated based on the genetic structure characteristics and diversity patterns among 25 wild populations using Restriction site-associated DNA sequencing (RAD-seq) technology. Through SNP calling, filtering, genetic diversity analysis, discriminant analysis of principal components (DAPC), maximum-likelihood phylogenetic tree, and ADMIXTURE clustering, significant population structure and differentiation were identified. The results revealed a total of 2,169 single nucleotide polymorphisms (SNPs), indicating lower genetic variation but higher genetic differentiation (He: 0.10, I: 0.16, Fst: 0.33). Analysis of molecular variance (AMOVA) showed that genetic variation within populations accounted for 77% of the total variance. DAPC, maximum-likelihood phylogenetic tree, and ADMIXTURE clustering analysis grouped the 25 populations into five distinct clades influenced by isolation, restricted gene flow, and complex topography. To preserve the genetic integrity of T. sinense, it is recommended to establish conservation units corresponding to different geographic clades, with a focus on populations with low/high genetic diversity by implementing artificial reproduction and germplasm resource nurseries. Given the species' vulnerable conservation status, urgent implementation of the aforementioned conservation strategies is necessary to safeguard the remaining genetic resources.
创建时间:
2025-05-20
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作