Comparison of array‐ and sequencing‐based markers for genome‐wide association mapping and genomic prediction in spring wheat

AbstractCassava (Manihot esculenta Crantz), a key carbohydrate dietary source for millions of people in Africa, faces severe yield loses due to two viral diseases: cassava brown streak disease (CBSD) and cassava mosaic disease (CMD). The completion of the cassava genome sequence and the whole genome marker profiling of clones from African breeding programs (www.nextgencassava.org) provides cassava breeders the opportunity to deploy additional breeding strategies and develop superior varieties with both farmer and industry preferred traits. Here the identification of genomic segments associated with resistance to CBSD foliar symptoms and root necrosis as measured in two breeding panels at different growth stages and locations is reported. Using genome-wide association mapping and genomic prediction models we describe the genetic architecture for CBSD severity and identify loci strongly associated on chromosomes 4 and 11. Moreover, the significantly associated region on chromosome 4 colocalises with a Manihot glaziovii introgression segment and the significant SNP markers on chromosome 11 are situated within a cluster of nucleotide-binding site leucine-rich repeat (NBS-LRR) genes previously described in cassava. Overall, predictive accuracy values found in this study varied between CBSD severity traits and across GS models with Random Forest and RKHS showing the highest predictive accuracies for foliar and root CBSD severity scores.

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Genome-Wide Association Studies and Genomic Selection for Grain Protein Content Stability in a Nested Association Mapping Population of Spring Wheat

10.1101/2021.04.15.440064 ◽

2021 ◽

Author(s):

Karansher S. Sandhu ◽

Paul D. Mihalyov ◽

Megan J. Lewien ◽

Michael O. Pumphrey ◽

Arron H Carter

Keyword(s):

Association Mapping ◽

Protein Content ◽

Genomic Selection ◽

Genetic Control ◽

Spring Wheat ◽

Grain Protein Content ◽

Genome Wide Association ◽

Grain Protein ◽

Nested Association Mapping ◽

Genome Wide

Grain protein content (GPC) is controlled by complex genetic systems and their interactions, and is an important quality determinant for hard spring wheat as it has a positive effect on bread and pasta quality. GPC is variable among genotypes and strongly influenced by environment. Thus, understanding the genetic control of wheat GPC and identifying genotypes with improved stability is an important breeding goal. The objectives of this research were to identify genetic backgrounds with less variation for GPC across environments and identify quantitative trait loci (QTLs) controlling the stability of GPC. A spring wheat nested association mapping (NAM) population of 650 recombinant inbred lines (RIL) derived from 26 diverse founder parents crossed to one common parent, 'Berkut', was phenotyped over three years of field trials (2014-2016). Genomic selection models were developed and compared based on prediction of GPC and GPC stability. After observing variable genetic control of GPC within the NAM population, seven RIL families displaying reduced marker-by-environment interaction were selected based on a stability index derived from Finlay-Wilkinson regression. A genome-wide association study identified seven significant QTLs for GPC stability with a Bonferroni-adjusted P value <0.05. This study also demonstrated that genome-wide prediction of GPC with ridge regression best linear unbiased estimates reached up to r = 0.69. Genomic selection can be used to apply selection pressure for GPC and improve genetic gain for GPC.

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Genomic Selection and Genome-Wide Association Studies for Grain Protein Content Stability in a Nested Association Mapping Population of Wheat

Agronomy ◽

10.3390/agronomy11122528 ◽

2021 ◽

Vol 11 (12) ◽

pp. 2528

Author(s):

Karansher S. Sandhu ◽

Paul D. Mihalyov ◽

Megan J. Lewien ◽

Michael O. Pumphrey ◽

Arron H. Carter

Keyword(s):

Association Mapping ◽

Protein Content ◽

Genomic Selection ◽

Genetic Control ◽

Spring Wheat ◽

Grain Protein Content ◽

Genome Wide Association ◽

Grain Protein ◽

Nested Association Mapping ◽

Genome Wide

Grain protein content (GPC) is controlled by complex genetic systems and their interactions and is an important quality determinant for hard spring wheat as it has a positive effect on bread and pasta quality. GPC is variable among genotypes and strongly influenced by the environment. Thus, understanding the genetic control of wheat GPC and identifying genotypes with improved stability is an important breeding goal. The objectives of this research were to identify genetic backgrounds with less variation for GPC across environments and identify quantitative trait loci (QTLs) controlling the stability of GPC. A spring wheat nested association mapping (NAM) population of 650 recombinant inbred lines (RIL) derived from 26 diverse founder parents crossed to one common parent, ‘Berkut’, was phenotyped over three years of field trials (2014–2016). Genomic selection models were developed and compared based on predictions of GPC and GPC stability. After observing variable genetic control of GPC within the NAM population, seven RIL families displaying reduced marker-by-environment interaction were selected based on a stability index derived from a Finlay–Wilkinson regression. A genome-wide association study identified eighteen significant QTLs for GPC stability with a Bonferroni-adjusted p-value < 0.05 using four different models and out of these eighteen QTLs eight were identified by two or more GWAS models simultaneously. This study also demonstrated that genome-wide prediction of GPC with ridge regression best linear unbiased estimates reached up to r = 0.69. Genomic selection can be used to apply selection pressure for GPC and improve genetic gain for GPC.

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