Scientific Reports (Jul 2024)

Discovering novel genomic regions explaining adaptation of bread wheat to conservation agriculture through GWAS

  • Amit Kumar Mazumder,
  • Rajbir Yadav,
  • Manjeet Kumar,
  • Prashanth Babu,
  • Naresh Kumar,
  • Sanjay Kumar Singh,
  • Amolkumar U. Solanke,
  • Shabir H. Wani,
  • Adel I. Alalawy,
  • Abdulrahman Alasmari,
  • Kiran B. Gaikwad

DOI
https://doi.org/10.1038/s41598-024-66903-3
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 21

Abstract

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Abstract To sustainably increase wheat yield to meet the growing world population’s food demand in the face of climate change, Conservation Agriculture (CA) is a promising approach. Still, there is a lack of genomic studies investigating the genetic basis of crop adaptation to CA. To dissect the genetic architecture of 19 morpho-physiological traits that could be involved in the enhanced adaptation and performance of genotypes under CA, we performed GWAS to identify MTAs under four contrasting production regimes viz., conventional tillage timely sown (CTTS), conservation agriculture timely sown (CATS), conventional tillage late sown (CTLS) and conservation agriculture late sown (CALS) using an association panel of 183 advanced wheat breeding lines along with 5 checks. Traits like Phi2 (Quantum yield of photosystem II; CATS:0.37, CALS: 0.31), RC (Relative chlorophyll content; CATS:55.51, CALS: 54.47) and PS1 (Active photosystem I centers; CATS:2.45, CALS: 2.23) have higher mean values in CA compared to CT under both sowing times. GWAS identified 80 MTAs for the studied traits across four production environments. The phenotypic variation explained (PVE) by these QTNs ranged from 2.15 to 40.22%. Gene annotation provided highly informative SNPs associated with Phi2, NPQ (Quantum yield of non-photochemical quenching), PS1, and RC which were linked with genes that play crucial roles in the physiological adaptation under both CA and CT. A highly significant SNP AX94651261 (9.43% PVE) was identified to be associated with Phi2, while two SNP markers AX94730536 (30.90% PVE) and AX94683305 (16.99% PVE) were associated with NPQ. Identified QTNs upon validation can be used in marker-assisted breeding programs to develop CA adaptive genotypes.

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