Assessing Population Genetic Structure and Diversity and Their Driving Factors in Phoebe Zhennan Populations

Overview

Journal BMC Plant Biol

Publisher Biomed Central

Specialty Biology

Date 2024 Nov 17

PMID 39551749

Authors

Jian Peng

Jiaxin Xie

Yunjie Gu

Hongying Guo

Shuaiying Zhang

Xin Huang

Xiandan Luo

Jianghong Qian

Minhao Liu

Xueqin Wan

Lianghua Chen

Xiong Huang

Fan Zhang

Fang He

Peng Zhu

Yu Zhong

Hanbo Yang

Affiliations

Soon will be listed here.

Abstract

Background: Phoebe zhennan, commonly known as "golden-thread nanmu," is one of the most valuable and protected tree species in China. An accurate understanding of the population genetic structure and its environmental factors is of significance for the protection and selection of new P. zhennan varieties.

Results: Sixteen nSSR and six cpSSR markers were used to determine the genetic diversity and population structure of P. zhennan and the effect of environmental factors on the genetic structure. The nSSR markers identified a total of 451 number of alleles (Na), while cpSSR markers detected 20 Na. A relative high level of genetic diversity was observed in the P. zhennan population evidenced by high Shannon's information index (I) of 0.671 and 2.294 based on cpSSR and nSSR datasets. The low value of fixation index (F) observed from the nSSR dataset indicated low breeding within the population. The genetic differentiation was mainly detected within populations (only 28% and 13% of the variance being between populations according to the nSSR and cpSSR datasets). Among them, the HNSZX (H = 0.469) and SCSZZ (I = 1.943) populations exhibited the highest level of genetic diversity, while the HNXXT (H = 0.041) and SCLJS (I = 0.943) populations exhibited the lowest level of genetic diversity. The average genetic differentiation coefficient (Fst) and gene flow (Nm) were 0.022-0.128 and 1.698-11.373, respectively, which indicated a moderate level of genetic differentiation and a high level of gene flow. STRUCTURE, neighbor-joining clustering, and principal coordinate analysis divided 543 individuals into two or three categories based on the nSSR or cpSSR datasets. Four temperature, three precipitation, five chemical, five physical, and one soil texture variable showed significant effects on the genetic structure and distribution of P. zhennan populations. Compared to nSSR, the genetic differentiation among populations based on cpSSR datasets conformed to the geographic isolation model, suggesting that geographic and genetic distances should be considered for further genetic conservation and breeding utilization. The importance of in situ conservation units, such as populations with a high level of genetic diversity, more private alleles, and haplotypes (e.g., population SCGTS, SCYFS, and YNYJX), should be emphasized. Additionally, breeding, along with artificially assisted population regeneration and restoration, should also be carefully planned, taking into account climate and soil properties at the same time.

Conclusions: In conclusion, this study provided genetic background information for the genetic conservation, management, and utilization of P. zhennan.

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