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Data from: Finding stories in noise: mitochondrial portraits from RAD data

Cite this dataset

Stobie, C. S.; Cunningham, Michael J.; Oosthuizen, Carel J.; Bloomer, Paulette (2018). Data from: Finding stories in noise: mitochondrial portraits from RAD data [Dataset]. Dryad.


Mitochondrial DNA (mtDNA) has formed the backbone of phylogeographic research for many years, however, recent trends focus on genome-wide analyses. One method proposed for calibrating inferences from noisy Next-Generation data, such as RAD sequencing, is to compare these results with analyses of mitochondrial sequences. Most researchers using this approach appear to be unaware that many Single Nucleotide Polymorphisms (SNPs) identified from genome-wide sequence data are themselves mitochondrial, or assume that these are too few to bias analyses. Here we demonstrate two methods for mining mitochondrial markers using RAD sequence data from three South African species of yellowfish, Labeobarbus. First, we use a rigorous SNP discovery pipeline using the program STACKS, to identify variant sites in mtDNA, which we then combine into haplotypes. Secondly, we directly map sequence reads against a mitochondrial genome reference. This method allowed us to reconstruct up to 98% of the Labeobarbus mitogenome. We validated these mitogenome reconstructions through BLAST database searches and by comparisons with cytochrome b gene sequences obtained through Sanger sequencing. Finally, we investigate the organismal consequences of these data including ancient genetic exchange and a recent translocation among populations of L. natalensis, as well as interspecific hybridisation between L. aeneus and L. kimberleyensis.

Usage notes


South Africa
Orange River