Concept for gene conservation strategy for the endangered Chinese yellowhorn, Xanthoceras sorbifolium, based on simulation of pairwise kinship coefficients

Concept for gene conservation strategy for the endangered Chinese yellowhorn, Xanthoceras sorbifolium, based on simulation of pairwise kinship coefficients

https://ift.tt/2Q10ll3

Publication date: 15 January 2019

Source: Forest Ecology and Management, Volume 432

Author(s): Yousry A. El-Kassaby, Qing Wang, Tongli Wang, Blaise Ratcliffe, Quan-Xin Bi, Zhou Wang, Jian-Feng Mao, Wenbin Guan

Abstract

A molecular markers-based conservation strategy framework for the endemic endangered Chinese yellowhorn, Xanthoceras sorbifolium, is developed. The method utilizes pairwise kinship coefficients, a measure of genetic similarity/dissimilarity, between individuals and contrasts two simulated mating schemes that either promote “no co-ancestry” or “co-ancestry” through multiple matings of particular individuals as well as a “hybrid” scenario involving both “no co-ancestry” and “co-ancestry” mating schemes. Selection of mating individuals is focused on maximizing genetic dissimilarity, hence capturing maximum genetic diversity. These approaches were compared on a population of 79 ancient yellowhorn trees scattered across 13 populations. Simulated matings were evaluated based on their average pairwise kinship, effective population size, and average number of alleles/locus. In this regard, no co-ancestry has been proven to be superior to co-ancestry mating scheme; however, co-ancestry offered opportunities for increasing effective population size, a desirable attribute for combating the detrimental effect of genetic drift. The hybrid approach, with reduced number of crosses, produced acceptable condition with maximum genetic diversity and high effective population size and genetic dissimilarity among the produced offspring. The advantages and disadvantages of marker-based gene conservation are highlighted and discussed.

Subject area: Conservation genetics and biodiversity.

Superforest

via ScienceDirect Publication: Forest Ecology and Management https://ift.tt/2zaqiu8

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