Identifying the physiological traits associated with DNA marker using genome wide association in wheat under heat stress

Autor: Adeel Khan, Munir Ahmad, Muhammad Yousaf Shani, Muhammad Kashif Riaz Khan, Mehdi Rahimi, Daniel K. Y. Tan
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Druh dokumentu: article
ISSN: 2045-2322
DOI: 10.1038/s41598-024-70630-0
Popis: Abstract Heat stress poses a significant environmental challenge that profoundly impacts wheat productivity. It disrupts vital physiological processes such as photosynthesis, by impeding the functionality of the photosynthetic apparatus and compromising plasma membrane stability, thereby detrimentally affecting grain development in wheat. The scarcity of identified marker trait associations pertinent to thermotolerance presents a formidable obstacle in the development of marker-assisted selection strategies against heat stress. To address this, wheat accessions were systematically exposed to both normal and heat stress conditions and phenotypic data were collected on physiological traits including proline content, canopy temperature depression, cell membrane injury, photosynthetic rate, transpiration rate (at vegetative and reproductive stage and ‘stay-green’. Principal component analysis elucidated the most significant contributors being proline content, transpiration rate, and canopy temperature depression, which exhibited a synergistic relationship with grain yield. Remarkably, cluster analysis delineated the wheat accessions into four discrete groups based on physiological attributes. Moreover, to explore the relationship between physiological traits and DNA markers, 158 wheat accessions were genotyped with 186 SSRs. Allelic frequency and polymorphic information content value were found to be highest on genome A (4.94 and 0.688), chromosome 1A (5.00 and 0.712), and marker Xgwm44 (13.0 and 0.916). Population structure, principal coordinate analysis and cluster analysis also partitioned the wheat accessions into four subpopulations based on genotypic data, highlighting their genetic homogeneity. Population diversity and presence of linkage disequilibrium established the suitability of population for association mapping. Additionally, linkage disequilibrium decay was most pronounced within a 15–20 cM region on chromosome 1A. Association mapping revealed highly significant marker trait associations at Bonferroni correction P
Databáze: Directory of Open Access Journals
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