A resistant variety with high yielding potential is key for increasing crop production to
fulfill the food requirement of the ever increasing world populations. Consequently, the aim of plant
breeders is to develop high yielding varieties or cultivars that are resistant or tolerant to specific
diseases or insects. For developing a resistant variety, it is enormously indispensable to incorporate or
introgress the specific resistant genes of that particular disease into the recipient. Suppression
subtractive hybridization (SSH) is a powerful technique for the identification of disease specific
differentially expressed genes that are expressed in a resistant or susceptible variety. This paper
presents a brief review on the SSH technique with examples focusing on the identification of the
wheat disease specific differentially expressed genes and their defense mechanisms against fungal
pathogens in global wheat cultivars. This review is helpful for wheat researchers for the updated
information on the SSH technique for the identification of differentially expressed genes in the global
wheat cultivars and varieties. Eventually, the identified genes could be used to develop the disease
resistance variety through marker-assisted backcrossing programme or conventional breeding.
Upland rice is important for sustainable crop production to meet future food demands. The expansion in area of irrigated rice faces limitations due to water scarcity resulting from climate change. Therefore, this research aimed to identify potential genotypes and suitable traits of upland rice germplasm for breeding programmes. Forty-three genotypes were evaluated in a randomised complete block design with three replications. All genotypes exhibited a wide and significant variation for 22 traits. The highest phenotypic and genotypic coefficient of variation was recorded for the number of filled grains/panicle and yields/plant (g). The highest heritability was found for photosynthetic rate, transpiration rate, stomatal conductance, intercellular CO₂, and number of filled grains/panicle and yields/plant (g). Cluster analysis based on 22 traits grouped the 43 rice genotypes into five clusters. Cluster II was the largest and consisted of 20 genotypes mostly originating from the Philippines. The first four principle components of 22 traits accounted for about 72% of the total variation and indicated a wide variation among the genotypes. The selected best trait of the number of filled grains/panicle and yields/plant (g), which showed high heritability and high genetic advance, could be used as a selection criterion for hybridisation programmes in the future.