Identification of Genomic Regions Associated with Agronomical Traits of Bread Wheat Under Two Levels of Salinity Using GWAS

Alotaibi, Fahad S.; Al-Qthanin, Rahmah N.; Aljabri, Maha; Shehzad, Tariq; Albaqami, Mohammed; Abou‐Elwafa, Salah Fatouh

doi:10.1007/s11105-022-01341-x

Cited by 9 publications

(1 citation statement)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As many as 14 admixture genotypes carrying genomic regions from both the subpopulations were observed, which is due to the advanced breeding line developed from common founding parents used in their crossing plan. AM panels with subpopulations were used efficiently by using either PCA-based grouping (Odilbekov et al, 2019 ; Rathan et al, 2022 ) or with the uses of the Q matrix from the STRUCTURE analysis as covariates (Beyer et al, 2019 ; Luján Basile et al, 2019 ; Danakumara et al, 2021 ; Alotaibi et al, 2022 ). Apart from that, suitable diversity for GWAS study among the genotypes in AM panel was confirmed by neighbor-joining clustering from the distance matrix.…”

Section: Discussionmentioning

confidence: 99%

Genome-wide association mapping for component traits of drought and heat tolerance in wheat

et al. 2022

View full text Add to dashboard Cite

Identification of marker trait association is a prerequisite for marker-assisted breeding. To find markers linked with traits under heat and drought stress in bread wheat (Triticum aestivum L.), we performed a genome-wide association study (GWAS). GWAS mapping panel used in this study consists of advanced breeding lines from the IARI stress breeding programme produced by pairwise and complex crosses. Phenotyping was done at multi locations namely New Delhi, Karnal, Indore, Jharkhand and Pune with augmented-RCBD design under different moisture and heat stress regimes, namely timely sown irrigated (IR), timely sown restricted irrigated (RI) and late sown (LS) conditions. Yield and its component traits, viz., Days to Heading (DH), Days to Maturity (DM), Normalized Difference Vegetation Index (NDVI), Chlorophyll Content (SPAD), Canopy temperature (CT), Plant Height (PH), Thousand grain weight (TGW), Grain weight per spike (GWPS), Plot Yield (PLTY) and Biomass (BMS) were phenotyped. Analysis of variance and descriptive statistics revealed significant differences among the studied traits. Genotyping was done using the 35k SNP Wheat Breeder's Genotyping Array. Population structure and diversity analysis using filtered 10,546 markers revealed two subpopulations with sufficient diversity. A large whole genome LD block size of 7.15 MB was obtained at half LD decay value. Genome-wide association search identified 57 unique markers associated with various traits across the locations. Twenty-three markers were identified to be stable, among them nine pleiotropic markers were also identified. In silico search of the identified markers against the IWGSC ref genome revealed the presence of a majority of the SNPs at or near the gene coding region. These SNPs can be used for marker-assisted transfer of genes/QTLs after validation to develop climate-resilient cultivars.

show abstract