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克隆繁殖作物的基因组选择策略。

Genomic selection strategies for clonally propagated crops.

机构信息

The Roslin Institute and Royal (Dick) School of Veterinary Studies, Easter Bush Research Centre, University of Edinburgh, Midlothian, EH25 9RG, UK.

NIAB EMR, New Road, East Malling, Kent, ME19 6BJ, UK.

出版信息

Theor Appl Genet. 2023 Mar 23;136(4):74. doi: 10.1007/s00122-023-04300-6.

Abstract

For genomic selection in clonally propagated crops with diploid (-like) meiotic behavior to be effective, crossing parents should be selected based on genomic predicted cross-performance unless dominance is negligible. For genomic selection (GS) in clonal breeding programs to be effective, parents should be selected based on genomic predicted cross-performance unless dominance is negligible. Genomic prediction of cross-performance enables efficient exploitation of the additive and dominance value simultaneously. Here, we compared different GS strategies for clonally propagated crops with diploid (-like) meiotic behavior, using strawberry as an example. We used stochastic simulation to evaluate six combinations of three breeding programs and two parent selection methods. The three breeding programs included (1) a breeding program that introduced GS in the first clonal stage, and (2) two variations of a two-part breeding program with one and three crossing cycles per year, respectively. The two parent selection methods were (1) parent selection based on genomic estimated breeding values (GEBVs) and (2) parent selection based on genomic predicted cross-performance (GPCP). Selection of parents based on GPCP produced faster genetic gain than selection of parents based on GEBVs because it reduced inbreeding when the dominance degree increased. The two-part breeding programs with one and three crossing cycles per year using GPCP always produced the most genetic gain unless dominance was negligible. We conclude that (1) in clonal breeding programs with GS, parents should be selected based on GPCP, and (2) a two-part breeding program with parent selection based on GPCP to rapidly drive population improvement has great potential to improve breeding clonally propagated crops.

摘要

为了使具有二倍体(类似)减数分裂行为的克隆繁殖作物的基因组选择有效,除非显性作用可以忽略不计,否则应该根据基因组预测的杂交表现选择杂交亲本。为了使克隆繁殖计划中的基因组选择有效,除非显性作用可以忽略不计,否则应该根据基因组预测的杂交表现选择亲本。杂交表现的基因组预测可以同时有效地利用加性和显性值。在这里,我们以草莓为例,比较了具有二倍体(类似)减数分裂行为的克隆繁殖作物的不同基因组选择策略。我们使用随机模拟来评估三种繁殖计划和两种亲本选择方法的六种组合。三种繁殖计划包括:(1)在第一个克隆阶段引入 GS 的繁殖计划;(2)每年有一个和三个杂交周期的两部分繁殖计划的两种变体。两种亲本选择方法是:(1)基于基因组估计育种值(GEBV)的亲本选择;(2)基于基因组预测杂交表现(GPCP)的亲本选择。基于 GPCP 的亲本选择比基于 GEBV 的亲本选择产生更快的遗传增益,因为当显性程度增加时,它减少了近交。使用 GPCP 的每年有一个和三个杂交周期的两部分繁殖计划总是产生最多的遗传增益,除非显性作用可以忽略不计。我们得出结论:(1)在具有 GS 的克隆繁殖计划中,应该根据 GPCP 选择亲本;(2)基于 GPCP 的两部分繁殖计划,通过选择亲本来快速推动群体改良,具有很大的潜力来改良克隆繁殖作物的繁殖。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b51c/10036424/ac1fceb295d0/122_2023_4300_Fig1_HTML.jpg

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