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bioRxiv · 10.1101/047282

DiscoMark: Nuclear marker discovery from orthologous sequences using draft genome data

Abstract

High-throughput sequencing has laid the foundation for fast and cost-effective development of phylogenetic markers. Here we present the program DO_SCPCAPISCOC_SCPCAPMO_SCPCAPARKC_SCPCAP, which streamlines the development of nuclear DNA (nDNA) markers from whole-genome (or whole-transcriptome) sequencing data, combining local alignment, alignment trimming, reference mapping and primer design based on multiple sequence alignments in order to design primer pairs from input orthologous sequences. In order to demonstrate the suitability of DO_SCPCAPISCOC_SCPCAPMO_SCPCAPARKC_SCPCAP we designed markers for two groups of species, one consisting of closely related species and one group of distantly related species. For the closely related members of the species complex of Cloeon dipterum s.l. (Insecta, Ephemeroptera), the program discovered a total of 78 markers. Among these, we selected eight markers for amplification and Sanger sequencing. The exon sequence alignments (2,526 base pairs (bp)) were used to reconstruct a well supported phylogeny and to infer clearly structured haplotype networks. For the distantly related species we designed primers for several families in the insect order Ephemeroptera, using available genomic data from four sequenced species. We developed primer pairs for 23 markers that are designed to amplify across several families. The DO_SCPCAPISCOC_SCPCAPMO_SCPCAPARKC_SCPCAP program will enhance the development of new nDNA markersby providing a streamlined, automated approach to perform genome-scale scans for phylogenetic markers. The program is written in Python, released under a public license (GNU GPL v2), and together with a manual and example data set available at: https://github.com/hdetering/discomark.

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BibTeXRIS

Sereina Rutschmann, Harald Detering, Sabrina Simon, Jakob Fredslund, Michael T. Monaghan. 2016-04-07. DiscoMark: Nuclear marker discovery from orthologous sequences using draft genome data. https://doi.org/10.1101/047282

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