High-Density Linkage Mapping of Agronomic Trait QTLs in Wheat under Water Deficit Condition using Genotyping by Sequencing (GBS)

Heat Stress-Tolerant Quantitative Trait Loci Identified Using Backcrossed Recombinant Inbred Lines Derived from Intra-Specifically Diverse Aegilops tauschii Accessions

In the face of climate change, bringing more useful alleles and genes from wild relatives of wheat is crucial to develop climate-resilient varieties. We used two populations of backcrossed recombinant inbred lines (BIL1 and BIL2), developed by crossing and backcrossing two intra-specifically diverse Aegilops tauschii accessions from lineage 1 and lineage 2, respectively, with the common wheat cultivar 'Norin 61'. This study aimed to identify quantitative trait loci (QTLs) associated with heat stress (HS) tolerance. The two BILs were evaluated under heat stress environments in Sudan for phenology, plant height (PH), grain yield (GY), biomass (BIO), harvest index (HI), and thousand-kernel weight (TKW). Grain yield was significantly correlated with BIO and TKW under HS; therefore, the stress tolerance index (STI) was calculated for these traits as well as for GY. A total of 16 heat-tolerant lines were identified based on GY and STI-GY. The QTL analysis performed using inclusive composite interval mapping identified a total of 40 QTLs in BIL1 and 153 QTLs in BIL2 across all environments. We detected 39 QTLs associated with GY-STI, BIO-STI, and TKW-STI in both populations (14 in BIL1 and 25 in BIL2). The QTLs associated with STI were detected on chromosomes 1A, 3A, 5A, 2B, 4B, and all the D-subgenomes. We found that QTLs were detected only under HS for GY on chromosome 5A, TKW on 3B and 5B, PH on 3B and 4B, and grain filling duration on 2B. The higher number of QTLs identified in BIL2 for heat stress tolerance suggests the importance of assessing the effects of intraspecific variation of Ae. tauschii in wheat breeding as it could modulate the heat stress responses/adaptation. Our study provides useful genetic resources for uncovering heat-tolerant QTLs for wheat improvement for heat stress environments.

Mapping of the QTLs governing grain micronutrients and thousand kernel weight in wheat (Triticum aestivum L.) using high density SNP markers

Biofortification is gaining importance globally to improve human nutrition through enhancing the micronutrient content, such as vitamin A, iron, and zinc, in staple food crops. The present study aims to identify the chromosomal regions governing the grain iron concentration (GFeC), grain zinc concentration (GZnC), and thousand kernel weight (TKW) using recombinant inbred lines (RILs) in wheat, developed from a cross between HD3086 and HI1500. The experiment was conducted in four different production conditions at Delhi viz., control, drought, heat, and combined heat and drought stress and at Indore under drought stress. Grain iron and zinc content increased under heat and combined stress conditions, while thousand kernel weight decreased. Medium to high heritability with a moderate correlation between grain iron and zinc was observed. Out of 4,106 polymorphic markers between the parents, 3,407 SNP markers were used for linkage map construction which spanned over a length of 14791.18 cm. QTL analysis identified a total of 32 chromosomal regions governing the traits under study, which includes 9, 11, and 12 QTLs for GFeC, GZnC, and TKW, respectively. A QTL hotspot was identified on chromosome 4B which is associated with grain iron, grain zinc, and thousand kernel weight explaining the phenotypic variance of 29.28, 10.98, and 17.53%, respectively. Similarly, common loci were identified on chromosomes 4B and 4D for grain iron, zinc, and thousand kernel weight. In silico analysis of these chromosomal regions identified putative candidate genes that code for proteins such as Inositol 1,3,4-trisphosphate 5/6-kinase, P-loop containing nucleoside triphosphate hydrolase, Pleckstrin homology (PH) domains, Serine-threonine/tyrosine-protein kinase and F-box-like domain superfamily proteins which play role in many important biochemical or physiological process. The identified markers linked to QTLs can be used in MAS once successfully validated.