Unlocking genetic insights: Evaluating wheat RILs for physiobiochemical traits under terminal heat stress conditions.

BACKGROUND: The increasing impacts of heat stress on wheat production due to climate change has entailed the development of heat-resilient crop varieties. To address this, two hundred recombinant inbred lines (RILs) derived from a cross between WH711/WH1021 were evaluated in a randomized block design (RBD) with two replications at CCSHAU, Hisar, during 2018-19 under heat stress and non-stress conditions. Heat stress was induced by altering the date of sowing so that the grain filling stage coincide with heat stress. RESULTS: Heat stress adversely affects RILs performance, as illustrated by alterations in phenotypic traits. Highest coefficients of variations were recorded for TAA, CTD 1, WUE, CTD 2, Cc and A under non-stress and heat stress conditions whereas gs, WUEi and GY under non-stress and SPAD 1, SPAD 2, GY and NDVI 2 under heat-stress conditions recorded moderate estimates of coefficient of variations. CTD 2, TAA, E, WUE and A displayed a significant occurrence of both high heritability and substantial genetic advance under non-stress. Similarly, CTD 2, NDVI 2, A, WUEi, SPAD 2, gs, E, Ci, MDA and WUE exhibited high heritability with high genetic advance under heat-stress conditions. CONCLUSIONS: Complementary and duplicate types of interactions with number of controlling genes were observed for different parameters depending on the traits and environments. RILs 41, 42, 59, 74, 75, 180 and 194 were categorized as heat tolerant RILs. Selection preferably for NDVI 1, RWC, TAA, A, E and WUEi to accumulate heat tolerance favorable alleles in the selected RILs is suggested for development of heat resilient genotypes for sustainable crop improvement. The results showed that traits such as such as NDVI, RWC, TAA, A, E, and WUEi, can be effective for developing heat-resilient wheat genotypes and ensuring sustainable crop improvement.

Genetic diversity and population structure analysis for morphological traits in upland cotton (Gossypium hirsutum L.).

A total of 96 different genotypes of upland cotton (Gossypium hirsutum) were selected from the breeding material and germplasm available at CCS HAU, India, to find the novel marker-trait associations for morphological traits used for registration of variety in upland cotton. Twenty-three morphological traits of the selected genotypes were recorded in field trials conducted in two replication of randomized block design during Kharif 2018 and 2019. A total of 11 traits showed sufficient variations in the screened germplasm and the same were further used for association mapping. A total of 168 SSRs were used for genotyping, of which 97 SSRs showed polymorphism amplifying 293 different alleles with an average of 3.02 alleles per SSR. Clustering, principal component analysis, and population structure analysis advocated that the current germplasm panel has enough diversity to be considered for association mapping. A total of 20 significant marker-trait associations were identified by the mixed linear model (MLM) and compressed mixed linear model (CMLM), of which 15 were common to both models, hence considered as promising associations. To the best of our knowledge, it is a first attempt to identify the linked markers in relation to morphological traits for the cotton crop. Results of the present study will be highly useful in speeding up variety registration programmes of upland cotton complementing to Distinctiveness, Uniformity, and Stability (DUS) testing.

Identification of Novel Marker-Trait Associations for Lint Yield Contributing Traits in Upland Cotton (Gossypium hirsutum L.) Using SSRs.

Improving the yield of lint is the main objective for most of the cotton crop improvement programs throughout the world as it meets the demand of fiber for textile industries. In the current study, 96 genotypes of Gossypium hirsutum were used to find novel simple sequence repeat marker-based associations for lint yield contributing traits by linkage disequilibrium. Extensive phenotyping of 96 genotypes for various agronomic traits was done for two consecutive years (2018 and 2019) in early, normal, and late sown environments. Out of 168 SSR markers screened over the 96 genotypes, a total of 97 polymorphic markers containing 293 alleles were used for analysis. Three different models, i.e., mixed linear model (MLM), compressed mixed linear model (CMLM), and multiple locus mixed linear model (MLMM), were used to detect the significant marker-trait associations for six different environments separately. A total of 38 significant marker-trait associations that were common to at least two environments were considered as promising associations and detailed annotation of the significant markers has been carried out. Twenty-two marker-trait associations were found to be novel in the current study. These results will be very useful for crop improvement programs using marker-assisted cotton breeding.