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Discovery and validation of genomic regions associated with resistance to maize lethal necrosis in four biparental populations
Authors:Manje?Gowda  author-information"  >  author-information__contact u-icon-before"  >  mailto:m.gowda@cgiar.org"   title="  m.gowda@cgiar.org"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author  author-information__orcid u-icon-before icon--orcid u-icon-no-repeat"  >  http://orcid.org/---"   itemprop="  url"   title="  View OrcID profile"   target="  _blank"   rel="  noopener"   data-track="  click"   data-track-action="  OrcID"   data-track-label="  "  >View author&#  s OrcID profile,Yoseph?Beyene,Dan?Makumbi,Kassa?Semagn,Michael?S.?Olsen,Jumbo?M.?Bright,Biswanath?Das,Stephen?Mugo,L.?M.?Suresh,Boddupalli?M.?Prasanna
Affiliation:1.International Maize and Wheat Improvement Center (CIMMYT),Nairobi,Kenya;2.Department of Agricultural, Food and Nutritional Science,University of Alberta,Edmonton,Canada;3.MRI-Syngenta,Lusaka,Zambia
Abstract:In sub-Saharan Africa, maize is the key determinant of food security for smallholder farmers. The sudden outbreak of maize lethal necrosis (MLN) disease is seriously threatening the maize production in the region. Understanding the genetic basis of MLN resistance is crucial. In this study, we used four biparental populations applied linkage mapping and joint linkage mapping approaches to identify and validate the MLN resistance-associated genomic regions. All populations were genotyped with low to high density markers and phenotyped in multiple environments against MLN under artificial inoculation. Phenotypic variation for MLN resistance was significant and heritability was moderate to high in all four populations for both early and late stages of disease infection. Linkage mapping revealed three major quantitative trait loci (QTL) on chromosomes 3, 6, and 9 that were consistently detected in at least two of the four populations. Phenotypic variance explained by a single QTL in each population ranged from 3.9% in population 1 to 43.8% in population 2. Joint linkage association mapping across three populations with three biometric models together revealed 16 and 10 main effect QTL for MLN-early and MLN-late, respectively. The QTL identified on chromosomes 3, 5, 6, and 9 were consistent with the QTL identified by linkage mapping. Ridge regression best linear unbiased prediction with five-fold cross-validation revealed high accuracy for prediction across populations for both MLN-early and MLN-late. Overall, the study discovered and validated the presence of major effect QTL on chromosomes 3, 6, and 9 which can be potential candidates for marker-assisted breeding to improve the MLN resistance.
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