Using high-throughput phenotypes to enable genomic selection by inferring genotypes

Using high-throughput phenotypes to enable genomic selection by inferring genotypes
复制标题

使用高通量表型通过推断基因型来实现基因组选择

DOI:
10.1101/2020.02.28.969600
复制
发表时间:
2020
期刊:
--
影响因子:
--
通讯作者:
Whalen A
Whalen A
中科院分区:
--
文献类型:
--
作者:
Whalen A

文献摘要

参考文献

相似文献

在本文中,我们开发和测试的方法,使用高通量的表型来推断个体的基因型。然后可以使用推断的基因型进行基因组选择。以前的方法使用高通量表型数据来增加选择的准确性,假设高通量表型与选择靶相关。当不是这种情况下,我们表明,高通量表型可以用来确定哪些单倍型的个人从他们的父母继承,从而推断个人的基因型。我们在两个模拟中测试了这种方法。在第一次模拟中,我们探索了推断基因型的准确性如何取决于所使用的高通量表型和所分析物种的基因组。在第二个模拟中,我们探索了使用这种方法是否可以通过对非基因型个体进行基因组选择来增加植物育种计划的遗传增益。在第一次模拟中,我们发现,如果使用更多的高通量表型,如果这些表型具有更高的遗传力,基因型的准确性更高。我们还发现,基因型的准确性随着物种基因组大小的增加而降低。在第二次模拟中,我们发现推断的基因型可用于对非基因型个体进行基因组选择,并与随机选择或在某些情况下的表型选择相比增加遗传增益。该方法为在育种程序中使用高通量表型数据提供了一种新的方法。随着高通量表型质量的提高和成本的降低,这种方法可以使基因组选择在大量的非基因分型个体上的使用成为可能。
In this paper we develop and test a method which uses high-throughput phenotypes to infer the genotypes of an individual. The inferred genotypes can then be used to perform genomic selection. Previous methods which used high-throughput phenotype data to increase the accuracy of selection assumed that the high-throughput phenotypes correlate with selection targets. When this is not the case, we show that the high-throughput phenotypes can be used to determine which haplotypes an individual inherited from their parents, and thereby infer the individual’s genotypes. We tested this method in two simulations. In the first simulation, we explored, how the accuracy of the inferred genotypes depended on the high-throughput phenotypes used and the genome of the species analysed. In the second simulation we explored whether using this method could increase genetic gain a plant breeding program by enabling genomic selection on non-genotyped individuals. In the first simulation, we found that genotype accuracy was higher if more high-throughput phenotypes were used and if those phenotypes had higher heritability. We also found that genotype accuracy decreased with an increasing size of the species genome. In the second simulation, we found that the inferred genotypes could be used to enable genomic selection on non-genotyped individuals and increase genetic gain compared to random selection, or in some scenarios phenotypic selection. This method presents a novel way for using high-throughput phenotype data in breeding programs. As the quality of high-throughput phenotypes increases and the cost decreases, this method may enable the use of genomic selection on large numbers of non-genotyped individuals.
DOI: 10.1016/j.ajhg.2013.02.011
发表时间: 2013-04-04
影响因子: 9.8
作者:
Cheung, Charles Y. K.;Thompson, Elizabeth A.;Wijsman, Ellen M.
通讯作者: Wijsman, Ellen M.
DOI: 10.1186/s12711-018-0438-2
发表时间: 2018-12-18
影响因子: 4.1
作者:
Whalen, Andrew;Ros-Freixedes, Roger;Hickey, John M.
通讯作者: Hickey, John M.
DOI: 10.1534/genetics.118.300885
发表时间: 2018-09-01
期刊: GENETICS
影响因子: 3.3
作者:
Zheng, Chaozhi;Boer, Martin P.;van Eeuwijk, Fred A.
通讯作者: van Eeuwijk, Fred A.
丹麦荷斯坦牛和丹麦泽西牛的傅里叶变换红外牛奶光谱的遗传分析。
DOI: 10.3168/jds.2018-14464
发表时间: 2019
影响因子: 3.5
作者:
R. M. Zaalberg;N. Shetty;Luc Janss;A. Buitenhuis
通讯作者: A. Buitenhuis
DOI: 10.1016/j.ajhg.2009.01.005
发表时间: 2009-02-13
影响因子: 9.8
作者:
Browning, Brian L.;Browning, Sharon R.
通讯作者: Browning, Sharon R.