The Unexpected Depths of Genome-Skimming Data: A Case Study Examining Goodeniaceae Floral Symmetry Genes

Premise of the study: The use of genome skimming allows systematists to quickly generate large data sets, particularly of sequences in high abundance (e.g., plastomes); however, researchers may be overlooking data in low abundance that could be used for phylogenetic or evo-devo studies. Here, we present a bioinformatics approach that explores the low-abundance portion of genome-skimming next-generation sequencing libraries in the fan-flowered Goodeniaceae. Methods: Twenty-four previously constructed Goodeniaceae genome-skimming Illumina libraries were examined for their utility in mining low-copy nuclear genes involved in floral symmetry, specifically the CYCLOIDEA (CYC)-like genes. De novo assemblies were generated using multiple assemblers, and BLAST searches were performed for CYC1, CYC2, and CYC3 genes. Results: Overall Trinity, SOAPdenovo-Trans, and SOAPdenovo implementing lower k-mer values uncovered the most data, although no assembler consistently outperformed the others. Using SOAPdenovo-Trans across all 24 data sets, we recovered four CYC-like gene groups (CYC1, CYC2, CYC3A, and CYC3B) from a majority of the species. Alignments of the fragments included the entire coding sequence as well as upstream and downstream regions. Discussion: Genome-skimming data sets can provide a significant source of low-copy nuclear gene sequence data that may be used for multiple downstream applications.