Impact of mixing between parallel year groups on genomic prediction in Atlantic salmon breeding programmes under random selection
Impact of mixing between parallel year groups on genomic prediction in Atlantic salmon breeding programmes under random selection
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随机选择下平行年份组之间的混合对大西洋鲑鱼育种计划基因组预测的影响
DOI：
10.1016/j.aquaculture.2023.739497
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发表时间：
2023
期刊：
影响因子：
4.5
通讯作者：
Kokkinias P
中科院分区：
文献类型：
--
作者：
Kokkinias P
大西洋鲑鱼的商业繁殖计划利用四个平行繁殖种群的四年一代间隔。在这项研究中，我们开发了一个鲑鱼繁殖计划的计算机模拟，并探讨了平行年组之间的基因流动对育种系内部和之间基因组预测准确性的影响。我们模拟了4条平行线，10代离散，随机选择，平行年份组之间的混合率不同。鱼类之间的遗传距离（作为多样性的衡量标准）和估计的基因组育种值的准确性被用作比较标准。在不混合的情况下，群体间遗传距离增加，群体内遗传变异减小，跨群体组合数据的准确性没有提高。即使是低比例的混合也会减少种群间的遗传距离，增加种群内的遗传变异。混合比例越高，谱线变得越相似的速度越快。随着混合比例的增加，预测的准确性也随之提高。与内部评估方法相比，组合评估方法的准确性增加随着混合百分比的增加而增加。总之，如果群体间没有基因流动，株系就会渐行渐远，组合群体间的信息对基因组育种价值预测没有价值。株系之间只有少量的混合才能使株系之间的距离更近，并有助于利用跨株系的信息来提高育种价值预测。优化品系之间的基因流动应该是鲑鱼育种计划设计的一个组成部分。
A commercial breeding programme in Atlantic salmon utilises a four-year generation interval with four parallel breeding populations. In this study, we develop a computer simulation of a salmon breeding programme and explore the impact of gene flow between the parallel year groups on the accuracy of genomic prediction within and between breeding lines. We simulated four parallel lines for 10 discrete generations with random selection and different mixing rates between parallel year groups. The genetic distance between fish (as a measure of diversity) and the accuracy of estimated genomic breeding values were used as criteria of comparison. With no mixing the genetic distance increased between populations, the genetic variation within populations decreased and there was no increase in accuracy when combining data across populations. Even a low percentage of mixing decreased the genetic distance between populations and increased the genetic variation within populations. The higher the percentage of mixing the faster the lines became more similar. The accuracy of prediction climbed as the percentage of mixing increased. The increase in accuracy from the combined evaluation approach compared to the within evaluation approach was greater with an increased percentage of mixing. In conclusion, if there is no gene flow between populations the lines drift apart and there is no value in combining information across populations for genomic breeding value prediction. Only a low amount of mixing between lines brings the lines closer together and facilitates the use of information across lines to improve breeding value prediction. Optimising gene flow between lines should be an integral part of salmon breeding programme design.
影响因子：
3.3
作者：
Gjoen, HM;Bentsen, HB
通讯作者：
Bentsen, HB