Mate selection: A useful approach to maximize genetic gain and control inbreeding in genomic and conventional oil palm (Elaeis guineensis Jacq.) hybrid breeding.

IF 4.3 2区 生物学
PLoS Computational Biology Pub Date : 2023-09-11 eCollection Date: 2023-09-01 DOI:10.1371/journal.pcbi.1010290
Billy Tchounke, Leopoldo Sanchez, Joseph Martin Bell, David Cros
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引用次数: 0

Abstract

Genomic selection (GS) is an effective method for the genetic improvement of complex traits in plants and animals. Optimization approaches could be used in conjunction with GS to further increase its efficiency and to limit inbreeding, which can increase faster with GS. Mate selection (MS) typically uses a metaheuristic optimization algorithm, simulated annealing, to optimize the selection of individuals and their matings. However, in species with long breeding cycles, this cannot be studied empirically. Here, we investigated this aspect with forward genetic simulations on a high-performance computing cluster and massively parallel computing, considering the oil palm hybrid breeding example. We compared MS and simple methods of inbreeding management (limitation of the number of individuals selected per family, prohibition of self-fertilization and combination of these two methods), in terms of parental inbreeding and genetic progress over four generations of genomic selection and phenotypic selection. The results showed that, compared to the conventional method without optimization, MS could lead to significant decreases in inbreeding and increases in annual genetic progress, with the magnitude of the effect depending on MS parameters and breeding scenarios. The optimal solution retained by MS differed by five breeding characteristics from the conventional solution: selected individuals covering a broader range of genetic values, fewer individuals selected per full-sib family, decreased percentage of selfings, selfings preferentially made on the best individuals and unbalanced number of crosses among selected individuals, with the better an individual, the higher the number of times he is mated. Stronger slowing-down in inbreeding could be achieved with other methods but they were associated with a decreased genetic progress. We recommend that breeders use MS, with preliminary analyses to identify the proper parameters to reach the goals of the breeding program in terms of inbreeding and genetic gain.

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配偶选择:在基因组和传统油棕(Elaeis guineensis Jacq.)杂交育种中,最大限度地提高遗传增益和控制近亲繁殖的一种有用方法。
基因组选择是对动植物复杂性状进行遗传改良的有效方法。优化方法可以与GS结合使用,以进一步提高其效率并限制近亲繁殖,近亲繁殖可以与GS一起更快地增加。配偶选择(MS)通常使用元启发式优化算法,即模拟退火,来优化个体的选择及其配对。然而,在繁殖周期长的物种中,这无法进行实证研究。在这里,我们通过高性能计算集群上的正向遗传模拟和大规模并行计算,考虑到油棕榈杂交育种的例子,研究了这一方面。我们比较了MS和简单的近亲繁殖管理方法(限制每个家族选择的个体数量,禁止自我受精和这两种方法的结合),从亲本近亲繁殖和四代基因组选择和表型选择的遗传进展方面进行了比较。结果表明,与未经优化的传统方法相比,MS可以显著减少近交,增加年度遗传进展,其影响程度取决于MS参数和育种场景。MS保留的最佳解决方案与传统解决方案有五个育种特征不同:选择的个体覆盖了更广泛的遗传值,每个全同胞家族选择的个体更少,自交百分比降低,优先在最好的个体上进行自交,以及选择的个体之间的杂交数量不平衡,个体越优秀,交配次数就越高。近亲繁殖中更强的减缓可以通过其他方法实现,但它们与遗传进步的减少有关。我们建议育种家使用MS,并进行初步分析,以确定适当的参数,从而在近亲繁殖和遗传增益方面达到育种计划的目标。
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来源期刊
PLoS Computational Biology
PLoS Computational Biology 生物-生化研究方法
CiteScore
7.10
自引率
4.70%
发文量
820
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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