干旱区生态环境知识资源中心(Arid): A classic approach for determining genomic prediction accuracy under terminal drought stress and well-watered conditions in wheat landraces and cultivars

Arid

DOI	10.1371/journal.pone.0247824
	A classic approach for determining genomic prediction accuracy under terminal drought stress and well-watered conditions in wheat landraces and cultivars
	Shabannejad, Morteza; Bihamta, Mohammad-Reza; Majidi-Hervan, Eslam; Alipour, Hadi; Ebrahimi, Asa
通讯作者	Bihamta, MR (corresponding author), Univ Tehran, Coll Agr & Nat Resources, Fac Agr Sci & Engn, Dept Agron & Plant Breeding, Tehran, Iran.
来源期刊	PLOS ONE
ISSN	1932-6203
出版年	2021
卷号	16 期号:3
英文摘要	The present study aimed to improve the accuracy of genomic prediction of 16 agronomic traits in a diverse bread wheat (Triticum aestivum L.) germplasm under terminal drought stress and well-watered conditions in semi-arid environments. An association panel including 87 bread wheat cultivars and 199 landraces from Iran bread wheat germplasm was planted under two irrigation systems in semi-arid climate zones. The whole association panel was genotyped with 9047 single nucleotide polymorphism markers using the genotyping-by-sequencing method. A number of 23 marker-trait associations were selected for traits under each condition, whereas 17 marker-trait associations were common between terminal drought stress and well-watered conditions. The identified marker-trait associations were mostly single nucleotide polymorphisms with minor allele effects. This study examined the effect of population structure, genomic selection method (ridge regression-best linear unbiased prediction, genomic best-linear unbiased predictions, and Bayesian ridge regression), training set size, and type of marker set on genomic prediction accuracy. The prediction accuracies were low (-0.32) to moderate (0.52). A marker set including 93 significant markers identified through genome-wide association studies with P values <= 0.001 increased the genomic prediction accuracy for all traits under both conditions. This study concluded that obtaining the highest genomic prediction accuracy depends on the extent of linkage disequilibrium, the genetic architecture of trait, genetic diversity of the population, and the genomic selection method. The results encouraged the integration of genome-wide association study and genomic selection to enhance genomic prediction accuracy in applied breeding programs.
类型	Article
语种	英语
开放获取类型	gold, Green Published
收录类别	SCI-E
WOS记录号	WOS:000626604300002
WOS类目	Multidisciplinary Sciences
WOS研究方向	Science & Technology - Other Topics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/368952
作者单位	[Shabannejad, Morteza; Majidi-Hervan, Eslam; Ebrahimi, Asa] Islamic Azad Univ, Fac Agr Sci & Food Ind, Dept Plant Breeding & Biotechnol, Sci & Res Branch, Tehran, Iran; [Bihamta, Mohammad-Reza] Univ Tehran, Coll Agr & Nat Resources, Fac Agr Sci & Engn, Dept Agron & Plant Breeding, Tehran, Iran; [Alipour, Hadi] Urmia Univ, Fac Agr & Nat Resources, Dept Plant Prod & Genet, Orumiyeh, Iran
推荐引用方式 GB/T 7714	Shabannejad, Morteza,Bihamta, Mohammad-Reza,Majidi-Hervan, Eslam,et al. A classic approach for determining genomic prediction accuracy under terminal drought stress and well-watered conditions in wheat landraces and cultivars[J],2021,16(3).
APA	Shabannejad, Morteza,Bihamta, Mohammad-Reza,Majidi-Hervan, Eslam,Alipour, Hadi,&Ebrahimi, Asa.(2021).A classic approach for determining genomic prediction accuracy under terminal drought stress and well-watered conditions in wheat landraces and cultivars.PLOS ONE,16(3).
MLA	Shabannejad, Morteza,et al."A classic approach for determining genomic prediction accuracy under terminal drought stress and well-watered conditions in wheat landraces and cultivars".PLOS ONE 16.3(2021).