Genetic architecture of agronomic and quality traits in a nested association mapping population of spring wheat

Abstract Germplasm collections are rich sources of genetic variation to improve crops for many valuable traits. Nested association mapping (NAM) populations can overcome the limitations of genome‐wide association studies (GWAS) in germplasm collections by reducing the effect of population structure....

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Main Authors: Ahmad H. Sallam, Fazal Manan, Prabin Bajgain, Matthew Martin, Tamas Szinyei, Emily Conley, Gina Brown‐Guedira, Gary J. Muehlbauer, James A. Anderson, Brian J. Steffenson
Format: Article
Language:English
Published: Wiley 2020-11-01
Series:The Plant Genome
Online Access:https://doi.org/10.1002/tpg2.20051
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spelling doaj-80c8eed0d264443e901cb4dbeb2abd9b2020-11-25T04:02:51ZengWileyThe Plant Genome1940-33722020-11-01133n/an/a10.1002/tpg2.20051Genetic architecture of agronomic and quality traits in a nested association mapping population of spring wheatAhmad H. Sallam0Fazal Manan1Prabin Bajgain2Matthew Martin3Tamas Szinyei4Emily Conley5Gina Brown‐Guedira6Gary J. Muehlbauer7James A. Anderson8Brian J. Steffenson9Department of Plant Pathology University of Minnesota St. Paul MN 55108 USADepartment of Plant Pathology University of Minnesota St. Paul MN 55108 USADepartment of Agronomy and Plant Genetics University of Minnesota St. Paul MN 55108 USADepartment of Plant Pathology University of Minnesota St. Paul MN 55108 USADepartment of Plant Pathology University of Minnesota St. Paul MN 55108 USADepartment of Agronomy and Plant Genetics University of Minnesota St. Paul MN 55108 USAPlant Science Research USDA‐ARS Raleigh NC 27695 USADepartment of Agronomy and Plant Genetics University of Minnesota St. Paul MN 55108 USADepartment of Agronomy and Plant Genetics University of Minnesota St. Paul MN 55108 USADepartment of Plant Pathology University of Minnesota St. Paul MN 55108 USAAbstract Germplasm collections are rich sources of genetic variation to improve crops for many valuable traits. Nested association mapping (NAM) populations can overcome the limitations of genome‐wide association studies (GWAS) in germplasm collections by reducing the effect of population structure. We exploited the genetic diversity of the USDA‐ARS wheat (Triticum aestivum L.) core collection by developing the Spring Wheat Multiparent Introgression Population (SWMIP). To develop this population, twenty‐five core parents were crossed and backcrossed to the Minnesota spring wheat cultivar RB07. The NAM population and 26 founder parents were genotyped using genotyping‐by‐sequencing and phenotyped for heading date, height, test weight, and grain protein content. After quality control, 20,312 markers with physical map positions were generated for 2,038 recombinant inbred lines (RILs). The number of RILs in each family varied between 58 and 96. Three GWAS models were utilized for quantitative trait loci (QTL) detection and accounted for known family stratification, genetic kinship, and both covariates. GWAS was performed on the whole population and also by bootstrap sampling of an equal number of RILs from each family. Greater power of QTL detection was achieved by treating families equally through bootstrapping. In total 16, 15, 12, and 13 marker‐trait associations (MTAs) were identified for heading date, height, test weight, and grain protein content, respectively. Some of these MTAs were coincident with major genes known to control the traits, but others were novel and contributed by the wheat core parents. The SWMIP will be a valuable source of genetic variation for spring wheat breeding.https://doi.org/10.1002/tpg2.20051
collection DOAJ
language English
format Article
sources DOAJ
author Ahmad H. Sallam
Fazal Manan
Prabin Bajgain
Matthew Martin
Tamas Szinyei
Emily Conley
Gina Brown‐Guedira
Gary J. Muehlbauer
James A. Anderson
Brian J. Steffenson
spellingShingle Ahmad H. Sallam
Fazal Manan
Prabin Bajgain
Matthew Martin
Tamas Szinyei
Emily Conley
Gina Brown‐Guedira
Gary J. Muehlbauer
James A. Anderson
Brian J. Steffenson
Genetic architecture of agronomic and quality traits in a nested association mapping population of spring wheat
The Plant Genome
author_facet Ahmad H. Sallam
Fazal Manan
Prabin Bajgain
Matthew Martin
Tamas Szinyei
Emily Conley
Gina Brown‐Guedira
Gary J. Muehlbauer
James A. Anderson
Brian J. Steffenson
author_sort Ahmad H. Sallam
title Genetic architecture of agronomic and quality traits in a nested association mapping population of spring wheat
title_short Genetic architecture of agronomic and quality traits in a nested association mapping population of spring wheat
title_full Genetic architecture of agronomic and quality traits in a nested association mapping population of spring wheat
title_fullStr Genetic architecture of agronomic and quality traits in a nested association mapping population of spring wheat
title_full_unstemmed Genetic architecture of agronomic and quality traits in a nested association mapping population of spring wheat
title_sort genetic architecture of agronomic and quality traits in a nested association mapping population of spring wheat
publisher Wiley
series The Plant Genome
issn 1940-3372
publishDate 2020-11-01
description Abstract Germplasm collections are rich sources of genetic variation to improve crops for many valuable traits. Nested association mapping (NAM) populations can overcome the limitations of genome‐wide association studies (GWAS) in germplasm collections by reducing the effect of population structure. We exploited the genetic diversity of the USDA‐ARS wheat (Triticum aestivum L.) core collection by developing the Spring Wheat Multiparent Introgression Population (SWMIP). To develop this population, twenty‐five core parents were crossed and backcrossed to the Minnesota spring wheat cultivar RB07. The NAM population and 26 founder parents were genotyped using genotyping‐by‐sequencing and phenotyped for heading date, height, test weight, and grain protein content. After quality control, 20,312 markers with physical map positions were generated for 2,038 recombinant inbred lines (RILs). The number of RILs in each family varied between 58 and 96. Three GWAS models were utilized for quantitative trait loci (QTL) detection and accounted for known family stratification, genetic kinship, and both covariates. GWAS was performed on the whole population and also by bootstrap sampling of an equal number of RILs from each family. Greater power of QTL detection was achieved by treating families equally through bootstrapping. In total 16, 15, 12, and 13 marker‐trait associations (MTAs) were identified for heading date, height, test weight, and grain protein content, respectively. Some of these MTAs were coincident with major genes known to control the traits, but others were novel and contributed by the wheat core parents. The SWMIP will be a valuable source of genetic variation for spring wheat breeding.
url https://doi.org/10.1002/tpg2.20051
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