Cotton (Gossypium. Spp.) is an agroeconomically significant crop worldwide involved in textile, oil, and feedstock production. Identifying genetic targets involved with disease resistance in cotton remains a critical objective for the scientific community. There remains much to be elucidated about how plant cells communicate and recognize biotic and abiotic environmental cues. Cell-surface-associated pattern recognition receptors (PRR) play a critical role in pathogen recognition. In plants, PRRs are receptor-like kinases (RLKs) and receptor-like proteins (RLPs). In particular, leucine-rich repeat containing RLPs (LRR-RLPs) have been indicated to play an important role in disease resistance against Fusarium infection in Arabidopsis. My thesis research is to genome-wide identify cotton RLPs with a bioinformatics approach and characterize their potential involvement in cotton disease resistance using virus-induced gene silencing (VIGS) approach. The 57 Arabidopsis RLPs were used to identify the cotton RLPs via sequence homology. Analysis of the cotton genome has identified 86 LRR-RLPs in G arboreum, 107 LRR-RLPs in G raimondii, and 151 LRR-RLPs in G. hirsutum. Phylogenic tree analysis with other plant LRR-RLPs suggested that cotton LRR-RLPs are likely evolved independently and clustered together. LRR-RLPs appear to be evolved rapidly as the homology between cotton and Arabidopsis LRR-RLPs is often below 40%. The number of LRRs varies among different LRR-RLP members. Using the VIGS approach, we silenced a set of cotton RLPs. My preliminary assays suggested that GhRLPGSO1-like, GhRLP44, GhRLP6, and GhRLP34 might be required for defense against Fusarium oxysporum. Additional infection assays and evaluation of silencing efficiency will further evaluate their involvement in disease resistance.
