SNP marker development in cassava for cassava mosaic disease resistance using bioinformatics tools

Abstract

Cassava (Manihot esculenta Crantz), originated in Latin America is one of the most important food cropswith a worldwide production of 314.81 million tonnes. The advancements in sequencing ability and lesscost involved allow for effective genome-wide discovery of SNPs. The present study was undertaken tocomputationally develop SNPs for cassava mosaic disease resistance and to understand the effectivenessof molecular markers in cassava for biotic stress response (cassava mosaic virus). The preliminary dataset for the work was obtained from the EST section of NCBI (http://www.ncbi.nlm.nih.gov/nucest).The draft cassava genome sequence and transcript sequences (variety AM560-2, JGI annotation v4.1)from the Phytozome website (http://phytozome.jgi.doe.gov/pz/portal.html) were also utilized. The SNPprediction tools, viz., Quality SNP and Auto SNP were used to predictthe SNPs. Quality SNP predictedabout 56 SNPs, in which 30 were non-synonymous and 26 were synonymous SNPs. Primers weredesigned for five selected SNPs associated with CMD resistant genes. These primers were validatedusing 5 resistant and 5 susceptible cassava genotypes. Among the primers, after validation one SNP(SNP896) primer was able to clearly differentiate between the resistant and susceptible genotypes. Thisis the first report of SNPs computationally identified and verified in wet lab. The results showed thatthe sequence with SNP1043 did not show any variation in the predicted SNP site, but SNP896 in thevariety, MNga showed SNP at the 1493th position with a variation in the base. The same SNP896 did notshow any variance in that position for the susceptible variety CI732.