RESUMEN
High molecular weight glutenin subunit composition and variation in 95 Elite-1 synthetic hexaploid (SH) wheats (Triticum turgidum/Aegilops tauschii; 2n = 6× = 42; AABBDD) were determined by sodium dodecyl sulphate polyacrylamide gel electrophoresis method (SDS-PAGE). Twenty two different alleles at Glu-1 loci in SHs were observed. Forty four different patterns of HMW-GS in synthetics were found. This higher HMW glutenin composition was due to higher proportion of D-genome encoded subunits in these SHs. 8% urea/SDS-PAGE better discriminated subunit 2* than 12% gels. However 12% urea/SDS-PAGE allowed differentiated mobility of Glu-D(t)1 subunits. Genetic variability at Glu-D(t)1 locus was greater than Glu-A1 and Glu-B1 loci. The relative high frequency of superior alleles, Glu-B1b and Glu-D(t)1d indicated the superior bread making quality attributes embedded in these synthetic hexaploid wheats. Of the 95 Elite-1 SHs 27.1% possessed superior alleles at Glu-A1 and 51% had superior alleles at Glu-B1 locus. At Glu-D(t)1 frequency of inferior allele 1Dx2 + 1Dy12 was very low (5.26%) and nine different rare alleles along with the higher frequency (22.1%) of D-genome encoded subunit, 1Dx5 + 1Dy10, were observed. These superior alleles shall form the priority selective sieve for their usage in wheat improvement efforts.
RESUMEN
Drought is a major and constantly increasing abiotic stress factor, thus limiting chickpea production. Like other crops, Kabuli Chickpea genotypes are screened for drought stress through Multi-environment trials (METs). Although, METs analysis is generally executed taking into account only one trait, which provides less significant reliability for the recommendation of genotypes as compared to multi trait-based analysis. Multi trait-based analysis could be used to recommend genotypes across diverse environments. Hence, current research was conducted for selection of superior genotypes through multi-trait stability index (MTSI) by using mixed and fixed effect models under six diverse environments. The genotypic stability was computed for all traits individually using the weighted average of absolute scores from the singular value decomposition of the matrix of best linear unbiased predictions for the genotype vs environment interaction (GEI) effects produced by a linear mixed-effect model index. A superiority index, WAASBY was measured to reflect the MPS (Mean performance and stability). The selection differential for the WAASBY index was 11.2%, 18.49% and 23.30% for grain yield (GY), primary branches per plant (PBP) and Stomatal Conductance (STOMA) respectively. Positive selection differential (0.80% ≤ selection differential ≤ 13.00%) were examined for traits averaged desired to be increased and negative (-0.57% ≤ selection differential ≤ -0.23%) for those traits desired to be reduced. The MTSI may be valuable to the plant breeders for the selection of genotypes based on many characters as being strong and simple selection process. Analysis of MTSI for multiple environments revealed that, the genotypes G20, G86, G31, G28, G116, G12, G105, G45, G50, G10, G30, G117, G81, G48, G85, G17, G32, G4, and G37 were the most stable and high yielding out of 120 chickpea genotypes, probably due to high MPS of selected traits under various environments. It is concluded that identified traits can be utilized as genitors in hybridization programs for the development of drought tolerant Kabuli Chickpea breeding material.
RESUMEN
Terminal heat stress causes irreversible damage to wheat crop productivity. It reduces the vegetative growth and flowering period that consequently declines the efficiency to capture available stem reserves (carbohydrates) in grains. Markers associated with thermotolerant traits ease in marker assisted selection (MAS) for crop improvement. It identifies the genomic regions associated with thermotolerant traits in wheat, but the scarcity of markers is the major hindrance in crop improvement. Therefore, 158 wheat genotypes were subjected to genotyping with 165 simple sequence repeat markers dispersed on three genomes (A, B and D). Allelic frequency and polymorphic information content values were highest on genome A (5.34 (14% greater than the lowest value at genome D) and 0.715 (3% greater than the lowest value at genome D)), chromosome 4 (5.40 (16% greater than the lowest value at chromosome 2) and 0.725 (5% greater than the lowest value at chromosome 6)) and marker xgwm44 (13.0 (84% greater than the lowest value at marker xbarc148) and 0.916 (46% greater than the lowest value at marker xbarc148)). Bayesian based population structure discriminated the wheat genotypes into seven groups based on genetic similarity indicating their ancestral origin and geographical ecotype. Linkage disequilibrium pattern had highest significant (P < 0.001) linked loci pairs 732 on genome A at r2 > 0.1 whereas, 58 on genome B at r2 > 0.5. Linkage disequilibrium decay (P < 0.01 and r2 > 0.1) had larger LD block (5-10 cM) on genome A. Highly significant MTAs (P < 0.000061) under heat stress conditions were identified for flag leaf area (xwmc336), spikelet per spike (xwmc553), grains per spike (cxfa2147, xwmc418 and xwmc121), biomass (xbarc7) and grain yield (xcfa2147 and xwmc671). The identified markers in this study could facilitate in MAS and gene pyramiding against heat stress in wheat.
RESUMEN
The study was carried out to investigate the nature of gene action determining the inheritance pattern of protein, lysine, gluten and flour yield in eight wheat varieties (Pak 81, Pothowar 93, Parwaz 94, Shahkar 95, Suleiman 96, Chakwal 97, Kohistan 97 and MH 97) selected on the basis of phenotypic diversity. In order to ascertain the gene action involved in the inheritance of these characters, the techniques like analysis of variance of Hayman model and genetic component analysis were employed. The estimates of components of genetic variation showed that additive genetic effects controlled the expression of traits like protein contents and flour yield, however, non-additive gene effects were more important for lysine contents and gluten contents. Directional dominance was observed in case of protein contents, which indicated the possibility of further improvement in this particular trait. Protein contents and flour yield being controlled by additive genetic effects with partial dominance suggested that selection could be practiced in early segregating generations for improvement in these traits.