Comparative transcriptome analysis of pigeonpea, Cajanus cajan (L.) and one of its wild relatives Cajanus platycarpus (Benth.) Maesen

Pigeonpea is a major source of dietary protein to the vegetarian population of the Indian sub-continent. Crop improvement to mitigate biotic and abiotic stresses for realization of its potential yield and bridging yield gap is the need of the hour. Availability of limited genomic resources in the cultivated germplasm, however, is a serious bottleneck towards successful molecular breeding for the development of superior genotypes in pigeonpea. In view of this, improvement of pigeonpea can be attempted through transgenesis or by exploiting genetic resources from its wild relatives. Pigeonpea wild relatives are known to be bestowed with agronomic traits of importance; discovery and deployment of genes from them can provide a lucrative option for crop improvement. Understanding molecular signatures of wild relatives would not only provide information about the mechanism behind desired traits but also enable us to extrapolate the information to cultivated pigeonpea. The present study deals with the characterization of leaf transcriptomes of Cajanus cajan and one of its wild relatives, Cajanus platycarpus. Illumina sequencing revealed 0.11 million transcripts in both the species with an annotation of 0.09 million (82%) transcripts using BLASTX. Comparative transcriptome analyses on the whole, divulged cues about the wild relative being vigilant and agile. Gene ontology and Mapman analysis depicted higher number of transcripts in the wild relative pertaining to signaling, transcription factors and stress responsive genes. Further, networking between the differentially expressed MapMan bins demonstrated conspicuous interactions between different bins through 535 nodes (512 Genes and 23 Pathways) and 1857 edges. The authenticity of RNA-seq analysis was confirmed by qRT-PCR. The information emanating from this study can provide valuable information and resource for future translational research including genome editing to alleviate varied stresses. Further, this learning can be a platform for in-depth investigations to decipher molecular mechanisms for mitigation of various stresses in the wild relative.