MEANGS: an efficient seed-free tool for de novo assembling animal mitochondrial genome using whole genome NGS data.

Abstract

Advances in next-generation sequencing (NGS) technologies have led to an exponential increase in the number of whole genome sequences (WGS) in databases. This wealth of WGS data has greatly facilitated the recovery of full mitochondrial genomes (mitogenomes), which are vital for phylogenetic, evolutionary and ecological studies. Unfortunately, most existing software cannot easily assemble mitogenome reference sequences conveniently or efficiently. Therefore, we developed a seed-free de novo assembly tool, MEANGS, which applies the trie-search method to extend contigs from self-discovery seeds and assemble a mitogenome from animal WGS data. We then used data from 16 species with different qualities to compare the performance of MEANGS with three other available programs. MEANGS exhibited the best overall performance since it was the only one that completed all tests, and it assembled full or partial mitogenomes for all of the tested samples while the others failed. Furthermore, MEANGS selects superior assembly sequences and annotates protein-coding genes. Thus, MEANGS can be one of the most efficient software for generating high-quality mitogenomes so far, the further use of it will benefit the study on mitogenome based on whole genome NGS data. MEANGS is available at https://github.com/YanCCscu/meangs.