Dataset Information

Haplotype-Based, Genome-Wide Association Study Reveals Stable Genomic Regions for Grain Yield in CIMMYT Spring Bread Wheat.

ABSTRACT: We untangled key regions of the genetic architecture of grain yield (GY) in CIMMYT spring bread wheat by conducting a haplotype-based, genome-wide association study (GWAS), together with an investigation of epistatic interactions using seven large sets of elite yield trials (EYTs) consisting of a total of 6,461 advanced breeding lines. These lines were phenotyped under irrigated and stress environments in seven growing seasons (2011-2018) and genotyped with genotyping-by-sequencing markers. Genome-wide 519 haplotype blocks were constructed, using a linkage disequilibrium-based approach covering 14,036 Mb in the wheat genome. Haplotype-based GWAS identified 7, 4, 10, and 15 stable (significant in three or more EYTs) associations in irrigated (I), mild drought (MD), severe drought (SD), and heat stress (HS) testing environments, respectively. Considering all EYTs and the four testing environments together, 30 stable associations were deciphered with seven hotspots identified on chromosomes 1A, 1B, 2B, 4A, 5B, 6B, and 7B, where multiple haplotype blocks were associated with GY. Epistatic interactions contributed significantly to the genetic architecture of GY, explaining variation of 3.5-21.1%, 3.7-14.7%, 3.5-20.6%, and 4.4- 23.1% in I, MD, SD, and HS environments, respectively. Our results revealed the intricate genetic architecture of GY, controlled by both main and epistatic effects. The importance of these results for practical applications in the CIMMYT breeding program is discussed.

SUBMITTER: Sehgal D

PROVIDER: S-EPMC7737720 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Haplotype-Based, Genome-Wide Association Study Reveals Stable Genomic Regions for Grain Yield in CIMMYT Spring Bread Wheat.

Sehgal Deepmala D Mondal Suchismita S Crespo-Herrera Leonardo L Velu Govindan G Juliana Philomin P Huerta-Espino Julio J Shrestha Sandesh S Poland Jesse J Singh Ravi R Dreisigacker Susanne S

Frontiers in genetics 20201203

We untangled key regions of the genetic architecture of grain yield (GY) in CIMMYT spring bread wheat by conducting a haplotype-based, genome-wide association study (GWAS), together with an investigation of epistatic interactions using seven large sets of elite yield trials (EYTs) consisting of a total of 6,461 advanced breeding lines. These lines were phenotyped under irrigated and stress environments in seven growing seasons (2011-2018) and genotyped with genotyping-by-sequencing markers. Geno ...[more]

PMID: 33335539

Similar Datasets

Project description:Genomic breeding technologies offer new opportunities for grain yield (GY) improvement in common wheat. In this study, we have evaluated the potential of genomic selection (GS) in breeding for GY in wheat by modeling a large dataset of 48,562 GY observations from the International Maize and Wheat Improvement Center (CIMMYT), including 36 yield trials evaluated between 2012 and 2019 in Obregón, Sonora, Mexico. Our key objective was to determine the value that GS can add to the current three-stage yield testing strategy at CIMMYT, and we draw inferences from predictive modeling of GY using 420 different populations, environments, cycles, and model combinations. First, we evaluated the potential of genomic predictions for minimizing the number of replications and lines tested within a site and year and obtained mean prediction accuracies (PAs) of 0.56, 0.5, and 0.42 in Stages 1, 2, and 3 of yield testing, respectively. However, these PAs were similar to the mean pedigree-based PAs indicating that genomic relationships added no value to pedigree relationships in the yield testing stages, characterized by small family-sizes. Second, we evaluated genomic predictions for minimizing GY testing across stages/years in Obregón and observed mean PAs of 0.41, 0.31, and 0.37, respectively when GY in the full irrigation bed planting (FI BP), drought stress (DS), and late-sown heat stress environments were predicted across years using genotype × environment (G × E) interaction models. Third, we evaluated genomic predictions for minimizing the number of yield testing environments and observed that in Stage 2, the FI BP, full irrigation flat planting and early-sown heat stress environments (mean PA of 0.37 ± 0.12) and the reduced irrigation and DS environments (mean PA of 0.45 ± 0.07) had moderate predictabilities among them. However, in both predictions across years and environments, the PAs were inconsistent across years and the G × E models had no advantage over the baseline model with environment and line effects. Overall, our results provide excellent insights into the predictability of a quantitative trait like GY and will have important implications on the future design of GS for GY in wheat breeding programs globally.

Project description:KEY MESSAGE:Simultaneous genomic selection for grain yield, protein content and dough rheological traits enables the development of resource-use efficient varieties that combine superior yield potential with comparably high end-use quality. Selecting simultaneously for grain yield and baking quality is a major challenge in wheat breeding, and several concepts like grain protein deviations have been developed for shifting the undesirable negative correlation between both traits. The protein quality is, however, not considered in these concepts, although it is an important aspect and might facilitate the selection of genotypes that use available resources more efficiently with respect to the quantity and quality of the final end products. A population of 480 lines from an applied wheat breeding programme that was phenotyped for grain yield, protein content, protein yield and dough rheological traits was thus used to assess the potential of using integrated genomic selection indices to ease selection decisions with regard to the plethora of quality traits. Additionally, the feasibility of achieving a simultaneous genetic improvement in grain yield, protein content and protein quality was investigated to develop more resource-use efficient varieties. Dough rheological traits related to either gluten strength or viscosity were combined in two separate indices, both of which showed a substantially smaller negative trade-off with grain yield than the protein content. Genomic selection indices based on regression deviations for the two latter traits were subsequently extended by the gluten strength or viscosity indices. They revealed a large merit for identifying resource-use efficient genotypes that combine both superior yield potential with comparably high end-use quality. Hence, genomic selection opens up the opportunity for multi-trait selection in early generations, which will most likely increase the efficiency when developing new and improved varieties.

Dataset Information

Haplotype-Based, Genome-Wide Association Study Reveals Stable Genomic Regions for Grain Yield in CIMMYT Spring Bread Wheat.

Publications

Haplotype-Based, Genome-Wide Association Study Reveals Stable Genomic Regions for Grain Yield in CIMMYT Spring Bread Wheat.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets