sppIDer: A Species Identification Tool to Investigate Hybrid Genomes with High-Throughput Sequencing

• Published in: Molecular biology and evolution Vol. 35; no. 11; pp. 2835 - 2849
• Main Authors: Langdon, Quinn K, Peris, David, Kyle, Brian, Hittinger, Chris Todd
• Format: Journal Article
• Language: English
• Published: United States Oxford University Press 01-09-2018
• Subjects: allopolyploidization; Animals; Arabidopsis; BASIC BIOLOGICAL SCIENCES; bioinformatic software; Biological Evolution; Drosophila; Genetic Techniques; Genome; High-Throughput Nucleotide Sequencing; hybrid; Hybridization, Genetic; next-generation DNA sequencing; Phylogeny; Resources; Saccharomyces; Software; species identification; yeasts
• ISSN: 0737-4038; 1537-1719
• DOI: 10.1093/molbev/msy166

The genomics era has expanded our knowledge about the diversity of the living world, yet harnessing high-throughput sequencing data to investigate alternative evolutionary trajectories, such as hybridization, is still challenging. Here we present sppIDer, a pipeline for the characterization of interspecies hybrids and pure species, that illuminates the complete composition of genomes. sppIDer maps short-read sequencing data to a combination genome built from reference genomes of several species of interest and assesses the genomic contribution and relative ploidy of each parental species, producing a series of colorful graphical outputs ready for publication. As a proof-of-concept, we use the genus Saccharomyces to detect and visualize both interspecies hybrids and pure strains, even with missing parental reference genomes. Through simulation, we show that sppIDer is robust to variable reference genome qualities and performs well with low-coverage data. We further demonstrate the power of this approach in plants, animals, and other fungi. sppIDer is robust to many different inputs and provides visually intuitive insight into genome composition that enables the rapid identification of species and their interspecies hybrids. sppIDer exists as a Docker image, which is a reusable, reproducible, transparent, and simple-to-run package that automates the pipeline and installation of the required dependencies (https://github.com/GLBRC/sppIDer; last accessed September 6, 2018).