Zhang Chaoqiang, Tang Yiwei, Tian Defeng, Huang Yanyan, Yang Guanghui, Nan Peng, Wang Yuguo, Li Lingfeng, Song Zhiping, Yang Ji, Zhong Yang, Zhang Wenju
College of Life Sciences and Engineering, Hexi University, Zhangye, China.
Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai, China.
Front Plant Sci. 2022 Oct 7;13:962364. doi: 10.3389/fpls.2022.962364. eCollection 2022.
Population genetic structure can provide valuable insights for conserving genetic resources and understanding population evolution, but it is often underestimated when using the most popular method and software, STRUCTURE and delta K, to assess. Although the hierarchical STRUCTURE analysis has been proposed early to overcome the above potential problems, this method was just utilized in a few studies and its reliability needs to be further tested. In this study, the genetic structure of populations of was evaluated by sequencing 12 nuclear microsatellite loci of 905 individuals from 38 populations. The STRUCTURE analysis suggested the most likely number of clusters was two, but using multi-hierarchical structure analysis, almost every population was determined with an endemic genetic component. The latter result is consistent with the extremely low gene flow among populations and a large number of unique cpDNA haplotypes in this species, indicating one level of structure analysis would extremely underestimate its genetic component. The simulation analysis shows the number of populations and the genetic dispersion among populations are two key factors to affect the estimation of K value using the above tools. When the number of populations is more than a certain amount, K always is equal to 2, and when a simulation only includes few populations, the underestimation of K value also may occur only if these populations consist of two main types of significantly differentiated genetic components. Our results strongly support that the hierarchical STRUCTURE analysis is necessary and practicable for the species with lots of subdivisions.
种群遗传结构可为遗传资源保护和种群进化理解提供有价值的见解,但在使用最流行的方法和软件STRUCTURE及ΔK进行评估时,其往往被低估。尽管早期就已提出分层STRUCTURE分析以克服上述潜在问题,但该方法仅在少数研究中得到应用,其可靠性仍需进一步检验。在本研究中,通过对来自38个种群的905个个体的12个核微卫星位点进行测序,评估了[具体物种]种群的遗传结构。STRUCTURE分析表明最可能的聚类数为两个,但使用多分层结构分析时,几乎每个种群都被确定具有独特的遗传成分。后一结果与种群间极低的基因流以及该物种中大量独特的叶绿体DNA单倍型一致,表明单一水平的结构分析会极大低估其遗传成分。模拟分析表明,种群数量和种群间的遗传离散度是影响使用上述工具估计K值的两个关键因素。当种群数量超过一定数量时,K值总是等于2,而当模拟仅包含少数种群时,只有在这些种群由两种显著分化的主要遗传成分类型组成时,才可能出现K值被低估的情况。我们的结果有力地支持了对于具有大量细分的物种,分层STRUCTURE分析是必要且可行的。