Genome-wide association mapping for grain manganese in rice (Oryza sativa L.) using a multi-experiment approach

被引:0
|
作者
Panthita Ruang-areerate
Anthony J. Travis
Shannon R. M. Pinson
Lee Tarpley
Georgia C. Eizenga
Mary Lou Guerinot
David E. Salt
Alex Douglas
Adam H. Price
Gareth J. Norton
机构
[1] University of Aberdeen,Institute of Biological and Environmental Sciences
[2] National Science and Technology Development Agency (NSTDA),National Omics Center
[3] USDA-ARS Dale Bumpers National Rice Research Center,Department of Biological Sciences
[4] Texas A&M System AgriLife Research Center,Future Food Beacon of Excellence and the School of Biosciences
[5] Dartmouth College,undefined
[6] University of Nottingham,undefined
来源
Heredity | 2021年 / 126卷
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摘要
Manganese (Mn) is an essential trace element for plants and commonly contributes to human health; however, the understanding of the genes controlling natural variation in Mn in crop plants is limited. Here, the integration of two of genome-wide association study approaches was used to increase the identification of valuable quantitative trait loci (QTL) and candidate genes responsible for the concentration of grain Mn across 389 diverse rice cultivars grown in Arkansas and Texas, USA, in multiple years. Single-trait analysis was initially performed using three different SNP datasets. As a result, significant loci could be detected using the high-density SNP dataset. Based on the 5.2 M SNP dataset, major QTLs were located on chromosomes 3 and 7 for Mn containing six candidate genes. In addition, the phenotypic data of grain Mn concentration were combined from three flooded-field experiments from the two sites and 3 years using multi-experiment analysis based on the 5.2 M SNP dataset. Two previous QTLs on chromosome 3 were identified across experiments, whereas new Mn QTLs were identified that were not found in individual experiments, on chromosomes 3, 4, 9 and 11. OsMTP8.1 was identified in both approaches and is a good candidate gene that could be controlling grain Mn concentration. This work demonstrates the utilisation of multi-experiment analysis to identify constitutive QTLs and candidate genes associated with the grain Mn concentration. Hence, the approach should be advantageous to facilitate genomic breeding programmes in rice and other crops considering QTLs and genes associated with complex traits in natural populations.
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页码:505 / 520
页数:15
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