mInDel: an efficient pipeline for high-throughput InDel marker discovery

Abstract

BackgroundNext-Generation Sequencing (NGS) technologies have emerged as a powerful tool to reveal nucleotide polymorphisms in a high-throughput and cost-effective manner. However, it remains a daunting task to proficiently analyze the enormous volume of data generated from NGS and to identify length polymorphisms for molecular marker discovery. The development of insertion-deletion polymorphism (InDel) markers is in particular computationally intensive, calling for integrated high performance methods to identify InDels with high sensitivity and specificity, which would directly benefit areas from genomic studies to molecular breeding.\n\nResultsWe present here a NGS-based tool for InDel marker discovery (mInDel), a high-performance computing pipeline for the development of InDel markers between any two genotypes. The mInDel pipeline proficiently develops InDel markers by comparing shared region size using sliding alignments between assembled contigs or reference genomes. mInDel has successfully designed thousands of InDel markers from maize NGS data locally and genome-wide. The program needs less than 2 hours to run when using 20 threads on a high-performance computing server to implement 40G data.\n\nConclusionsmInDel is an efficient, integrated pipeline for a high-throughput design of InDel markers between genotypes. It will be particularly applicable to the crop species which require a sufficient amount of DNA markers for molecular breeding selection. mInDel is freely available for downloading at www.github.com/lyd0527/mInDel website.