RNA-Seq transcriptome analysis of Jatropha curcas L. accessions after salt stimulus and unigene-derived microsatellite mining

Abstract The small oleaginous tree of Jatropha curcas L. (physic nut) is an excellent biodiesel source whose crop could represent a good income source for farmers in tropical and semi-arid zones. However, in some areas in particular, salinity, such as many other abiotic stresses, can compromise productivity. We analyzed the root RNA-Seq transcriptome of two Brazilian J. curcas accessions after a three-hour NaCl exposition (150 mM) aiming at identifying differentially expressed genes (DEGs) useful for breeding programs. The de novo transcriptome covered 145,422 assembled transcripts (126,343 unigenes), out of which 84,589 showed at least one significant alignment to the GenBank reference genome. Differentially expressed unigenes (DEGs) of the salt-sensitive Jc171 accession (4,646) suppressed those of the salt-tolerant Jc183 (57) one. A MapMan analysis of the DEGs using Manihot esculenta Crantz genes as reference (Euphorbiaceae family) highlighted the metabolism of phytohormone, carbohydrate (CHO), lipid, amino acid, redox, and secondary metabolite in the salt-responses. RT-qPCR results of nine selected Jc183 DEGs [phenylalanine ammonia-lyase (PAL), S-adenosylmethionine-dependent methyltransferase (SAMe), S-adenosylmethionine synthase (SAM), carboxylesterase (CXE), homeobox-leucine zipper gene (HD-Zip), NAC transcription factor gene (NAC), methionine-gamma lyase (MGL), peroxidase (PX), and xyloglucan endotransglucosylase (XTH)] evaluated in 36 combinations accession/treatments validated 86.11 % of the in silico results. The data generated improved the J. curcas transcriptome based on Illumina-21 bp tags as reported before, which can benefit breeders in the improvement of salt-tolerance in J. curcas. Additionally, primer pairs successfully designed for 1,423 DEGs presenting microsatellite motifs can contribute to the development of co-dominant molecular markers, a very useful marker applied to genetic analysis.