Genome-Wide Association Study Reveals Novel Genomic Regions for Grain Yield and Yield-Related Traits in Drought-Stressed Synthetic Hexaploid Wheat

Bhatta, Madhav; Morgounov, Alexey; Belamkar, Vikas; Baenziger, P. S.

doi:10.3390/ijms19103011

Cited by 111 publications

(114 citation statements)

References 92 publications

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“…We also found MTAs associated with drought stress. Moreover, we found several other MTAs whose annotations suggest different roles including response to drought stress (TBC1 domain family member, SNF1-related protein kinase regulatory subunit beta-2) plant senescence (E3 ubiquitin-protein ligase ORTHRUS 2), salt stress (Glutamyl-tRNA (Gln) amidotransferase subunit A), disease resistance (Disease resistance protein (NBS-LRR class) family), metabolism (Adenosine kinase-like protein) and antioxidant defense (Telomere repeat-binding factor like-protein) [30][31][32][33][34][35][36]. Our study identified novel MTAs associated with SPAD measurements in US soft wheat under HT conditions which contributes to a better understanding of the genetic basis of SPAD traits in wheat.…”

Section: Discussionmentioning

confidence: 99%

Genetic dissection of heat-responsive physiological traits to improve adaptation and increase yield potential in soft winter wheat

et al. 2020

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Background: Climate change, including higher temperatures (HT) has a detrimental impact on wheat productivity and modeling studies predict more frequent heat waves in the future. Wheat growth can be impaired by high daytime and nighttime temperature at any developmental stage, especially during the grain filling stage. Leaf chlorophyll content, leaf greenness, cell membrane thermostability, and canopy temperature have been proposed as candidate traits to improve crop adaptation and yield potential of wheat under HT. Nonetheless, a significant gap exists in knowledge of genetic backgrounds associated with these physiological traits. Identifying genetic loci associated with these traits can facilitate physiological breeding for increased yield potential under high temperature stress condition in wheat. Results: We conducted genome-wide association study (GWAS) on a 236 elite soft wheat association mapping panel using 27,466 high quality single nucleotide polymorphism markers. The panel was phenotyped for three years in two locations where heat shock was common. GWAS identified 500 significant marker-trait associations (MTAs) (p ≤ 9.99 × 10 − 4). Ten MTAs with pleiotropic effects detected on chromosomes 1D, 2B, 3A, 3B, 6A, 7B, and 7D are potentially important targets for selection. Five MTAs associated with physiological traits had pleiotropic effects on grain yield and yield-related traits. Seventy-five MTAs were consistently expressed over several environments indicating stability and more than half of these stable MTAs were found in genes encoding different types of proteins associated with heat stress. Conclusions: We identified 500 significant MTAs in soft winter wheat under HT stress. We found several stable loci across environments and pleiotropic markers controlling physiological and agronomic traits. After further validation, these MTAs can be used in marker-assisted selection and breeding to develop varieties with high stability for grain yield under high temperature.

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Section: Discussionmentioning

confidence: 99%

Genetic dissection of heat-responsive physiological traits to improve adaptation and increase yield potential in soft winter wheat

et al. 2020

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“…One approach which can facilitate a more accurate estimation for the improvement of trait stability is through examining the genetic architecture underlying stability and implementing genomic-assisted breeding [4,5]. Genetic mapping through association studies and genomic selection has been widely used to dissect the architecture of important traits in wheat (Triticum aestivum L.) [6][7][8][9]. A genomewide association study (GWAS) identifies genetic loci linked to phenotypic values of trait variation through…”

Section: Introductionmentioning

confidence: 99%

Insights into the Genetic Architecture of Phenotypic Stability Traits in Winter Wheat

Lozada

Carter

2020

Agronomy

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Examining the architecture of traits through genomics is necessary to gain a better understanding of the genetic loci affecting important traits to facilitate improvement. Genomewide association study (GWAS) and genomic selection (GS) were implemented for grain yield, heading date, and plant height to gain insights into the genetic complexity of phenotypic stability of traits in a diverse population of US Pacific Northwest winter wheat. Analysis of variance using the Additive Main Effect and Multiplicative Interaction (AMMI) approach revealed significant genotype and genotype by environment interactions. GWAS identified 12 SNP markers distributed across 10 chromosomes affecting variation for both trait and phenotypic stability, indicating potential pleiotropic effects and signifying that similar genetic loci could be associated with different aspects of stability. The lack of stable and major effect loci affecting phenotypic variation supports the complexity of stability of traits. Accuracy of GS was low to moderate, between 0.14 and 0.66, indicating that phenotypic stability is under genetic control. The moderate to high correlation between trait and trait stability suggests the potential of simultaneous selection for trait and trait stability. Our results demonstrate the complex genetic architecture of trait stability and show the potential for improving stability in winter wheat using genomic-assisted approaches.Agronomy 2020, 10, 368 2 of 15 the strength of linkage disequilibrium (i.e., the non-random association of alleles at multiple loci) between markers and functional polymorphism across diverse germplasm [10]. In wheat, GWAS has been conducted in different traits such as grain yield, yield components (thousand kernel weight and kernel number), Fusarium head blight resistance, snow mold tolerance, plant height, and heading date [11][12][13][14][15][16]. Compared with biparental mapping, GWAS results in a higher mapping resolution as it exploits the majority of the recombination histories of the individuals belonging to the diverse population used [17,18]. The main drawback of GWAS, nonetheless, is that it might not able to capture the causative and rare variants (loci) with small effects, and therefore would be a special case of missing heritability, i.e., the portion of genetic variance that cannot be explained by all significant loci [19]. In this case, genomic selection (GS) is seen as a complementary approach to GWAS.GS uses genomewide markers to estimate the marker effects and calculate genomic estimated breeding values (GEBV), which represents the genetic "worth" or merit of an individual. A high GEBV for grain yield, for example, would mean that a line is predicted to have better grain yield compared with others. In contrast to GWAS, GS does not test for significance but rather uses genomewide marker data to calculate the GEBV. More genetic variation could be captured in GS compared with marker-assisted selection as all markers are used in estimating breeding values [20]. In GS, a prediction model ...

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“…In case of exceeding the relative air humidity inside with respect to the relative air humidity outside, it is recommended to provide ventilation above the grain [4], otherwise the quality of the stored products will be reduced.…”

Section: Resultsmentioning

confidence: 99%

“…The main method of storage in metal containers, according to the instructions [1,2] and safety regulations is the storage of grain in a dry and purified state [3]. It is known that not only humidity and purity, but also the temperature of the grain put into storage affect the storage period [4]. The lower the temperature, the longer the storage time becomes.…”

Section: Introductionmentioning

confidence: 99%

Dependence of fat acidity value on wheat grain storage conditions

et al. 2020

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The article presents the dependence of the fat acidity value (FAV) on the values of humidity and temperature, the relationship between the storage duration for wheat grain and FAV. To establish the expiration date of wheat grain during long-term storage, the author of the article considered the fat acid value (FAV) in mg of KOH. Storage temperature and relative air humidity in a desiccator affect the change (growth) of fat acidity value. The greatest changes occurred at 6 th , 7 th and 8 th months of storage at a relative air humidity of more than 65 % and temperatures above 20 °C. At a storage temperature of 10 °C, in all cases the growth of FAV remained insignificant and was within the limits of determination accuracy. It is noted that when the relative humidity was below 60 %, while the temperature was the same as in the previous case, the FAV of wheat grain was practically unchanged through the 6-month storage period.

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Genome-Wide Association Study Reveals Novel Genomic Regions for Grain Yield and Yield-Related Traits in Drought-Stressed Synthetic Hexaploid Wheat

Cited by 111 publications

References 92 publications

Genetic dissection of heat-responsive physiological traits to improve adaptation and increase yield potential in soft winter wheat

Genetic dissection of heat-responsive physiological traits to improve adaptation and increase yield potential in soft winter wheat

Insights into the Genetic Architecture of Phenotypic Stability Traits in Winter Wheat

Dependence of fat acidity value on wheat grain storage conditions

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