Drought stress restricts plant growth and development by altering metabolic activity and biological functions. However, plants have evolved several cellular and molecular mechanisms to overcome drought stress. Drought tolerance is a multiplex trait involving the activation of signaling mechanisms and differentially expressed molecular responses. Broadly, drought tolerance comprises two steps: stress sensing/signaling and activation of various parallel stress responses (including physiological, molecular, and biochemical mechanisms) in plants. At the cellular level, drought induces oxidative stress by overproduction of reactive oxygen species (ROS), ultimately causing the cell membrane to rupture and stimulating various stress signaling pathways (ROS, mitogen-activated-protein-kinase, Ca²⁺, and hormone-mediated signaling). Drought-induced transcription factors activation and abscisic acid concentration co-ordinate the stress signaling and responses in cotton. The key responses against drought stress, are root development, stomatal closure, photosynthesis, hormone production, and ROS scavenging. The genetic basis, quantitative trait loci and genes of cotton drought tolerance are presented as examples of genetic resources in plants. Sustainable genetic improvements could be achieved through functional genomic approaches and genome modification techniques such as the CRISPR/Cas9 system aid the characterization of genes, sorted out from stress-related candidate single nucleotide polymorphisms, quantitative trait loci, and genes. Exploration of the genetic basis for superior candidate genes linked to stress physiology can be facilitated by integrated functional genomic approaches. We propose a third-generation sequencing approach coupled with genome-wide studies and functional genomic tools, including a comparative sequenced data (transcriptomics, proteomics, and epigenomic) analysis, which offer a platform to identify and characterize novel genes. This will provide information for better understanding the complex stress cellular biology of plants.

Wheat is a cool seasoned crop requiring low temperature during grain filling duration and therefore increased temperature causes significant yield reduction. A set of 125 spring wheat genotypes from International Maize and Wheat Improvement Centre (CIMMYT-Mexico) was evaluated for phenological and yield related traits at three locations in Pakistan under normal sowing time and late sowing time for expose to prolonged high temperature. With the help of genome-wide association study using genotyping-by-sequencing, marker trait associations (MTAs) were observed separately for the traits under normal and late sown conditions. Significant reduction ranging from 9 to 74% was observed in all traits under high temperature. Especially 30, 25, 41 and 66% reduction was observed for days to heading (DH), plant height (PH), spikes per plant (SPP) and yield respectively. We identified 55,954 single nucleotide polymorphisms (SNPs) using genotyping by sequencing of these 125 hexaploid spring wheat genotypes and conducted genome-wide association studies (GWAS) for days to heading (DH), grain filled duration (GFD), plant height (PH), spikes per plant (SPP), grain number per spike (GNS), thousand kernel weight (TKW) and grain yield per plot (GY). Genomic regions identified through GWAS explained up to 13% of the phenotypic variance, on average. A total of 139 marker-trait associations (MTAs) across three wheat genomes (56 on genome A, 55 on B and 28 on D) were identified for all the seven traits studied. For days to heading, 20; grain filled duration, 21; plant height, 23; spikes per plant, 13; grain numbers per spike, 8; thousand kernel weight, 21 and for grain yield, 33 MTAs were detected under normal and late sown conditions. This study identifies the essential resource of genetics research and underpins the chromosomal regions of seven agronomic traits under normal and high temperature. Significant relationship was observed between the number of favored alleles and trait observations. Fourteen protein coding genes with their respective annotations have been searched with the sequence of seven MTAs which were identified in this study. These findings will be helpful in the development of a breeder friendly platform for the selection of high yielding wheat lines at high temperature areas.

Interrogations of local germplasm and landraces can offer a foundation and genetic basis for drought tolerance in wheat. Potential of drought tolerance in a panel of 30 wheat genotypes including varieties, local landraces, and wild crosses were explored under drought stress (DS) and well-watered (WW) conditions. Considerable variation for an osmotic adjustment (OA) and yield components, coupled with genotype and environment interaction was observed, which indicates the differential potential of wheat genotypes under both conditions. Reduction in yield per plant (YP), thousand kernel weight (TKW), and induction of OA was detected. Correlation analysis revealed a strong positive association of YP with directly contributing yield components under both environments, indicating the impotence of these traits as a selection-criteria for the screening of drought-tolerant genotypes for drylands worldwide. Subsequently, the association of OA with TKW which contributes directly to YP, indicates that wheat attains OA to extract more water from the soil under low water-potential. Genotypes including WC-4, WC-8 and LLR-29 showed more TKW under both conditions, among them; LLR-29 also has maximum OA and batter yield comparatively. Result provides insight into the role of OA in plant yield sustainability under DS. In this study, we figure out the concept of OA and its incredible role in sustainable plant yield in wheat.

Lentil is an important food legume throughout the world and Pakistan stands at 18^th position with 8,610 tons production from 17,457 hectares. It is rich in protein, carbohydrates, fat, fiber, and minerals that can potentially meet food security and malnutrition issues, particularly in South Asia. Two hundred and twenty lentil genotypes representing Pakistan (178), Syria (14), and the USA (22) including 6 from unknown origins were studied for yield, yield contributing traits, and cooking time (CT). Genotype 6122 (Pakistan) performed the best during both years with seed yield per plant (SY) 68±1.7 g, biological yield per plant (BY) 264±2.8 g, pod size (PS) 0.61±0.01 cm, number of seeds per pod (NSP) 2, cooking time (CT) 11 minutes, with no hard seed (HS). The genotypes 6122 (Pakistan) and 6042 (Syria) produced the highest BY, hence these have the potential to be an efficient source of fodder, particularly during extreme winter months. The genotypes 5698 (Pakistan) and 6015 (USA) were late in maturity during 2018–19 while 24783 and 5561 matured early in 2019. A minimum CT of 10 minutes was taken by the genotypes 6074 and 5745 of Pakistani origin. The lowest CT saves energy, time, and resources, keeps flavor, texture, and improves protein digestibility, hence the genotypes with minimum CT are recommended for developing better lentil cultivars. Pearson correlation matrix revealed significant association among several traits, especially SY with BY, PS, and NSP which suggests their use for the future crop improvement program. The PCA revealed a considerable reduction in components for the selection of suitable genotypes with desired traits that could be utilized for future lentil breeding. Structural Equational Model (SEM) for SY based on covariance studies indicated the perfect relationship among variables. Further, hierarchical cluster analysis establishes four clusters for 2017–18, whereas seven clusters for 2018–19. Cluster 4 of 2017–18 and cluster 5 of 2018–19 exhibited the genotypes with the best performance for most of the traits (SY, BY, PS, NSP, CT, and HS). Based on heritability; HSW, SY, BY, NSP were highly heritable, hence these traits are expected for selecting genotypes with genes of interest and for future lentil cultivars. In conclusion, 10 genotypes (5664, 5687, 6084, 6062, 6122, 6058, 6087, 5689, 6042 and 6074) have been suggested to evaluate under multi-location environments for selection of the best one/s or could be utilized in hybridization in future lentil breeding programs.