Population structure and genome-wide association studies in bread wheat for phosphorus efficiency traits using 35 K Wheat Breeder’s Affymetrix array

Soumya, P. R.; Burridge, Amanda J.; Singh, Nisha; Batra, Renu; Pandey, Renu; Kalia, Sanjay; Rai, Vandana; Edwards, Keith J.

doi:10.1038/s41598-021-87182-2

Cited by 11 publications

(3 citation statements)

References 77 publications

(54 reference statements)

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“… Pang et al (2020) reported 90 marker-trait associations (MTAs) and identified eight putative candidate genes for TKW, KL, KW, and KDR using GWAS with 768 wheat cultivars. In addition, several studies have used the GWAS method to identify MTAs for wheat kernel traits and to determine the underlying candidate genes and function markers ( Sun et al, 2017 ; Li et al, 2019 ; Alemu et al, 2020 ; Soumya et al, 2021 ). However, due to the complexity and large size of the wheat genome, the genetic basis of kernel traits is still poorly understood.…”

Section: Introductionmentioning

confidence: 99%

Genome-Wide Association Study of Kernel Traits Using a 35K SNP Array in Bread Wheat (Triticum aestivum L.)

Wang

Tian

et al. 2022

Front. Plant Sci.

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Kernel size and weight are crucial components of grain yield in wheat. Deciphering their genetic basis is essential for improving yield potential in wheat breeding. In this study, five kernel traits, including kernel length (KL), kernel width (KW), kernel diameter ratio (KDR), kernel perimeter (KP), and thousand-kernel weight (TKW), were evaluated in a panel consisting of 198 wheat accessions under six environments. Wheat accessions were genotyped using the 35K SNP iSelect chip array, resulting in a set of 13,228 polymorphic SNP markers that were used for genome-wide association study (GWAS). A total of 146 significant marker-trait associations (MTAs) were identified for five kernel traits on 21 chromosomes [–log10(P) ≥ 3], which explained 5.91–15.02% of the phenotypic variation. Of these, 12 stable MTAs were identified in multiple environments, and six superior alleles showed positive effects on KL, KP, and KDR. Four potential candidate genes underlying the associated SNP markers were predicted for encoding ML protein, F-box protein, ethylene-responsive transcription factor, and 1,4-α-glucan branching enzyme. These genes were strongly expressed in grain development at different growth stages. The results will provide new insights into the genetic basis of kernel traits in wheat. The associated SNP markers and predicted candidate genes will facilitate marker-assisted selection in wheat breeding.

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Section: Introductionmentioning

confidence: 99%

Genome-Wide Association Study of Kernel Traits Using a 35K SNP Array in Bread Wheat (Triticum aestivum L.)

Wang

Tian

et al. 2022

Front. Plant Sci.

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“…At least a dozen models are now available showing significant improvement in GWAS. In the recent past several genome wide association studies have been conducted, where several models have been used and the results compared ( Ayana et al., 2018 ; Ward et al., 2019 ; Chaurasia et al., 2020 ; Alemu et al., 2021 ; Malik et al., 2021a ; Sandhu et al., 2021 ; Soumya et al., 2021 ). In this study, we selected five models for identification of main effect MTAs and PLINK for epistatic interactions.…”

Section: Discussionmentioning

confidence: 99%

Genetics of spot blotch resistance in bread wheat (Triticum aestivum L.) using five models for GWAS

Singh

Gaurav²,

Vasistha³

et al. 2023

Front. Plant Sci.

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Genetic architecture of resistance to spot blotch in wheat was examined using a Genome-Wide Association Study (GWAS) involving an association panel comprising 303 diverse genotypes. The association panel was evaluated at two different locations in India including Banaras Hindu University (BHU), Varanasi (Uttar Pradesh), and Borlaug Institute for South Asia (BISA), Pusa, Samastipur (Bihar) for two consecutive years (2017-2018 and 2018-2019), thus making four environments (E1, BHU 2017-18; E2, BHU 2018-19; E3, PUSA, 2017-18; E4, PUSA, 2018-19). The panel was genotyped for 12,196 SNPs based on DArT-seq (outsourced to DArT Ltd by CIMMYT); these SNPs included 5,400 SNPs, which could not be assigned to individual chromosomes and were therefore, described as unassigned by the vendor. Phenotypic data was recorded on the following three disease-related traits: (i) Area Under Disease Progress Curve (AUDPC), (ii) Incubation Period (IP), and (iii) Lesion Number (LN). GWAS was conducted using each of five different models, which included two single-locus models (CMLM and SUPER) and three multi-locus models (MLMM, FarmCPU, and BLINK). This exercise gave 306 MTAs, but only 89 MTAs (33 for AUDPC, 30 for IP and 26 for LN) including a solitary MTA detected using all the five models and 88 identified using four of the five models (barring SUPER) were considered to be important. These were used for further analysis, which included identification of candidate genes (CGs) and their annotation. A majority of these MTAs were novel. Only 70 of the 89 MTAs were assigned to individual chromosomes; the remaining 19 MTAs belonged to unassigned SNPs, for which chromosomes were not known. Seven MTAs were selected on the basis of minimum P value, number of models, number of environments and location on chromosomes with respect to QTLs reported earlier. These 7 MTAs, which included five main effect MTAs and two for epistatic interactions, were considered to be important for marker-assisted selection (MAS). The present study thus improved our understanding of the genetics of resistance against spot blotch in wheat and provided seven MTAs, which may be used for MAS after due validation.

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“…Thus, DArTseq based genotyping method has been used for association studies in macadamia (O'Connor et al, 2019(O'Connor et al, , 2020. Anchoring each SNP marker to the genome sequence and genetic mapping would improve its usefulness (Jia et al, 2016) as is used in platforms such as Illumina and Affymetrix (Bayer et al, 2017;Zhao et al, 2020;Soumya et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Discovery of Single Nucleotide Polymorphisms for Resistance to Abnormal Vertical Growth in Macadamia

et al. 2021

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Abnormal vertical growth (AVG) syndrome is a serious threat to the Australian macadamia industry as it decreases the yield of nuts by as much as 70% per annum. A lack of information on the cause of AVG has hindered the development of an effective disease management strategy. Discovery of genetic markers associated with disease resistance can be used as tool for rapid selection of elite cultivars, hence helps in efficient disease management. Differences in field susceptibility of macadamia cultivars provide an opportunity for discovery of genetic markers that are associated with host resistance. REML mixed model analysis was performed to estimate the AVG rating of 51 cultivars from multiple origins using phenotypic data from 359 trees planted in four sites. Most of the Hawaiian cultivars were found as susceptible, while selections from the Australian macadamia industry breeding program were predominantly resistant. All the cultivars were genotyped for 13,221 DArTseq-based single nucleotide polymorphism (SNP) markers. A bulked sample analysis was performed using 20 genotypes each at the extremes of AVG phenotypic ratings. Ten SNP markers were predicted to be associated with AVG resistance and two arbitrarily selected SNP markers were validated using PCR and Sanger sequencing. Our findings suggest that AVG resistance in the commercial cultivars may be derived from the genomic introgression of Macadamia tetraphylla through interspecific hybridization. The results may support marker-assisted selection for macadamia germplasm with AVG resistance.

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Population structure and genome-wide association studies in bread wheat for phosphorus efficiency traits using 35 K Wheat Breeder’s Affymetrix array

Cited by 11 publications

References 77 publications

Genome-Wide Association Study of Kernel Traits Using a 35K SNP Array in Bread Wheat (Triticum aestivum L.)

Genome-Wide Association Study of Kernel Traits Using a 35K SNP Array in Bread Wheat (Triticum aestivum L.)

Genetics of spot blotch resistance in bread wheat (Triticum aestivum L.) using five models for GWAS

Discovery of Single Nucleotide Polymorphisms for Resistance to Abnormal Vertical Growth in Macadamia

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