Background: Verticillium wilt, caused by the fungal pathogen Verticillium dahliae, is the most severe disease in cotton (Gossypium spp.), causing great lint losses worldwide. Disease management could be achieved in the field if genetically improved, resistant plants were used. However, the interaction between V. dahliae and cotton is a complicated process, and its molecular mechanism remains obscure. To understand better the defense response to this pathogen as a means for obtaining more tolerant cultivars, we monitored the transcriptome profiles of roots from resistant plants of G. barbadense cv. Pima90-53 that were challenged with V. dahliae.
Results: In all, 46,192 high-quality expressed sequence tags (ESTs) were generated from a full-length cDNA library of G. barbadense. They were clustered and assembled into 23126 unigenes that comprised 2661 contigs and 20465 singletons. Those unigenes were assigned Gene Ontology terms and mapped to 289 KEGG pathways. A total of 3027 unigenes were found to be homologous to known defense-related genes in other plants. They were assigned to the functional classification of plant-pathogen interactions, including disease defenses and signal transduction. The branch of "SA→NPR1→TGA→PR-1→Disease resistance" was first discovered in the interaction of cotton-V. dahliae, indicating that this wilt process includes both biotrophic and necrotrophic stages. In all, 4936 genes coding for putative transcription factors (TF) were identified in our library. The most abundant TF family was the NAC group (527), followed by G2-like (440), MYB (372), BHLH (331), bZIP (271) ERF, C3H, and WRKY. We also analyzed the expression of genes involved in pathogen-associated molecular pattern (PAMP) recognition, the activation of effector-triggered immunity, TFs, and hormone biosynthesis, as well as genes that are pathogenesis-related, or have roles in signaling/regulatory functions and cell wall modification. Their differential expression patterns were compared among mock-/inoculated- and resistant/susceptible cotton. Our results suggest that the cotton defense response has significant transcriptional complexity and that large accumulations of defense-related transcripts may contribute to V. dahliae resistance in cotton. Therefore, these data provide a resource for cotton improvement through molecular breeding approaches.
Conclusions: This study generated a substantial amount of cotton transcript sequences that are related to defense responses against V. dahliae. These genomics resources and knowledge of important related genes contribute to our understanding of host-pathogen interactions and the defense mechanisms utilized by G. barbadense, a non-model plant system. These tools can be applied in establishing a modern breeding program that uses marker-assisted selections and oligonucleotide arrays to identify candidate genes that can be linked to valuable agronomic traits in cotton, including disease resistance.