A Bioinformatics Tool Searching for Genome-Wide SSR Markers by Using High-Throughput Sequencing Data

In plant breeding, simple sequence repeats (SSRs) have been widely used as genetic markers. SSR markers are important to perform positional cloning, construction of genetic maps and so on. Generally, SSR markers were developed by some methods based on PCR such as random amplified hybridization microsatellites (RAHM), 5’ anchored PCR in non-model species. To developing SSR markers economically in non-model species, we developed a bioinformatics tool. This tool detects polymorphic SSR markers among samples (e.g. lines and individuals) by using high-throughput sequencing data. For developing SSR markers, this tool performs follow steps (i) finding SSRs in each high-throughput sequencing read by pattern matching with regular expressions of Java computer programing language, (ii) extracting reads containing SSRs, (iii) clustering the extracted reads by SSRs and both flanking sequences of SSRs, (iv) determining consensus sequences of SSR loci in each sample, (v) finding polymorphisms in each SSR locus among multiple samples. In this presentation, we demonstrate a performance of the tool through discovering SSR markers of rice by using high-throughput sequencing data of The 3,000 rice genomes project.

This research was partially supported by Research Promotion Projects by Meiji University (Research by Young Researchers) to M.K., MEXT-Supported Program for the Strategic Research Foundation at Private Universities (2014-2018); and Research Funding for Computational Software Supporting Program from Meiji University to K.Y.. Computations were partially performed on the NIG supercomputer at ROIS National Institute of Genetics.