GWAS to identify genomic loci associated with early vigour in bread wheat under simulated water deficit complemented with QTL meta-analysis

Autor: Yousef, Rahimi, Bahman, Khahani, Ali, Jamali, Hadi, Alipour, Mohammad Reza, Bihamta, Pär K, Ingvarsson
Rok vydání: 2022
Zdroj: G3 (Bethesda, Md.).
ISSN: 2160-1836
Popis: A genome-wide association study (GWAS) was used to identify associated loci with early vigour under simulated water deficit and grain yield under field drought in a diverse collection of Iranian bread wheat landraces. In addition, a meta-quantitative trait loci (MQTL) analysis was used to further expand our approach by retrieving already published QTLs from recombinant inbred lines (RILs), double haploids (DH), back-crosses (BC), and F2 mapping populations. In the current study, around 16%, 14%, and 16% of SNPs were in significant linkage disequilibrium (LD) in the A, B, and D genomes, respectively, and varied between 5.44% (4A) and 21.85% (6A). Three main subgroups were identified among the landraces with different degrees of admixture, and population structure was further explored through principal component analysis (PCA). Our GWAS identified 54 marker-trait associations (MTAs) that were located across the wheat genome but with the highest number found in the B sub-genome. The gene ontology (GO) analysis of MTAs revealed that around 75 percent were located within or closed to protein-coding genes. In the MQTL analysis 23 MQTLs, from a total of 215 QTLs, were identified and successfully projected onto the reference map. MQT-YLD4, MQT-YLD9, MQT-YLD13, MQT-YLD17, MQT-YLD18, MQT-YLD19, and MQTL-RL1 contributed to the highest number of projected QTLs and were therefore regarded as the most reliable and stable QTLs under water deficit conditions. These MQTLs greatly facilitate the identification of putative candidate genes underlying at each MQTL interval due to the reduced confidence of intervals (CI) associated with MQTLs. These findings provide important information on the genetic basis of early vigour traits and grain yield under water deficit conditions and set the foundation for future investigations into adaptation to water deficit in bread wheat.
Databáze: OpenAIRE