scholarly journals Genome-wide association and genomic prediction of resistance to maize lethal necrosis disease in tropical maize germplasm

2015 ◽  
Vol 128 (10) ◽  
pp. 1957-1968 ◽  
Author(s):  
Manje Gowda ◽  
Biswanath Das ◽  
Dan Makumbi ◽  
Raman Babu ◽  
Kassa Semagn ◽  
...  
2020 ◽  
Vol 11 ◽  
Author(s):  
Berhanu Tadesse Ertiro ◽  
Maryke Labuschagne ◽  
Michael Olsen ◽  
Biswanath Das ◽  
Boddupalli M. Prasanna ◽  
...  

Author(s):  
Manje Gowda ◽  
Dan Makumbi ◽  
Biswanath Das ◽  
Christine Nyaga ◽  
Titus Kosgei ◽  
...  

Abstract Key message Genome-wide association revealed that resistance to Striga hermonthica is influenced by multiple genomic regions with moderate effects. It is possible to increase genetic gains from selection for Striga resistance using genomic prediction. Abstract Striga hermonthica (Del.) Benth., commonly known as the purple witchweed or giant witchweed, is a serious problem for maize-dependent smallholder farmers in sub-Saharan Africa. Breeding for Striga resistance in maize is complicated due to limited genetic variation, complexity of resistance and challenges with phenotyping. This study was conducted to (i) evaluate a set of diverse tropical maize lines for their responses to Striga under artificial infestation in three environments in Kenya; (ii) detect quantitative trait loci associated with Striga resistance through genome-wide association study (GWAS); and (iii) evaluate the effectiveness of genomic prediction (GP) of Striga-related traits. An association mapping panel of 380 inbred lines was evaluated in three environments under artificial Striga infestation in replicated trials and genotyped with 278,810 single-nucleotide polymorphism (SNP) markers. Genotypic and genotype x environment variations were significant for measured traits associated with Striga resistance. Heritability estimates were moderate (0.42) to high (0.92) for measured traits. GWAS revealed 57 SNPs significantly associated with Striga resistance indicator traits and grain yield (GY) under artificial Striga infestation with low to moderate effect. A set of 32 candidate genes physically near the significant SNPs with roles in plant defense against biotic stresses were identified. GP with different cross-validations revealed that prediction of performance of lines in new environments is better than prediction of performance of new lines for all traits. Predictions across environments revealed high accuracy for all the traits, while inclusion of GWAS-detected SNPs led to slight increase in the accuracy. The item-based collaborative filtering approach that incorporates related traits evaluated in different environments to predict GY and Striga-related traits outperformed GP for Striga resistance indicator traits. The results demonstrated the polygenic nature of resistance to S. hermonthica, and that implementation of GP in Striga resistance breeding could potentially aid in increasing genetic gain for this important trait.


Author(s):  
Chalermpol Phumichai ◽  
Pornsak Aiemnaka ◽  
Piyaporn Nathaisong ◽  
Sirikan Hunsawattanakul ◽  
Phasakorn Fungfoo ◽  
...  

2016 ◽  
Vol 6 (12) ◽  
pp. 3803-3815 ◽  
Author(s):  
Jiafa Chen ◽  
Rosemary Shrestha ◽  
Junqiang Ding ◽  
Hongjian Zheng ◽  
Chunhua Mu ◽  
...  

Abstract Fusarium ear rot (FER) incited by Fusarium verticillioides is a major disease of maize that reduces grain quality globally. Host resistance is the most suitable strategy for managing the disease. We report the results of genome-wide association study (GWAS) to detect alleles associated with increased resistance to FER in a set of 818 tropical maize inbred lines evaluated in three environments. Association tests performed using 43,424 single-nucleotide polymorphic (SNPs) markers identified 45 SNPs and 15 haplotypes that were significantly associated with FER resistance. Each associated SNP locus had relatively small additive effects on disease resistance and accounted for 1–4% of trait variation. These SNPs and haplotypes were located within or adjacent to 38 candidate genes, 21 of which were candidate genes associated with plant tolerance to stresses, including disease resistance. Linkage mapping in four biparental populations to validate GWAS results identified 15 quantitative trait loci (QTL) associated with F. verticillioides resistance. Integration of GWAS and QTL to the maize physical map showed eight colocated loci on chromosomes 2, 3, 4, 5, 9, and 10. QTL on chromosomes 2 and 9 are new. These results reveal that FER resistance is a complex trait that is conditioned by multiple genes with minor effects. The value of selection on identified markers for improving FER resistance is limited; rather, selection to combine small effect resistance alleles combined with genomic selection for polygenic background for both the target and general adaptation traits might be fruitful for increasing FER resistance in maize.


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