Data from: Genomic sequence capture of haemosporidian parasites: methods and prospects for enhanced study of host-parasite evolution
Barrow, Lisa N. et al. (2018), Data from: Genomic sequence capture of haemosporidian parasites: methods and prospects for enhanced study of host-parasite evolution, Dryad, Dataset, https://doi.org/10.5061/dryad.8030nq9
Avian malaria and related haemosporidians (Plasmodium, [Para]Haemoproteus, and Leucocytoozoon) represent an exciting multi-host, multi-parasite system in ecology and evolution. Global research in this field accelerated after 1) the publication in 2000 of PCR protocols to sequence a haemosporidian mitochondrial (mtDNA) barcode, and 2) the development in 2009 of an open-access database to document the geographic and host ranges of parasite mtDNA haplotypes. Isolating haemosporidian nuclear DNA from bird hosts, however, has been technically challenging, slowing the transition to genomic-scale sequencing techniques. We extend a recently-developed sequence capture method to obtain hundreds of haemosporidian nuclear loci from wild bird samples, which typically have low levels of infection, or parasitemia. We tested 51 infected birds from Peru and New Mexico and evaluated locus recovery in light of variation in parasitemia, divergence from reference sequences, and pooling strategies. Our method was successful for samples with parasitemia as low as ~0.02% (2 of 10,000 blood cells infected) and mtDNA divergence as high as 15.9% (one Leucocytozoon sample), and using the most cost-effective pooling strategy tested. Phylogenetic relationships estimated with >300 nuclear loci were well resolved, providing substantial improvement over the mtDNA barcode. We provide protocols for sample preparation and sequence capture including custom probe sequences, and describe our bioinformatics pipeline using aTRAM 2.0, PHYLUCE, and custom Perl/Python scripts. This approach can be applied to thousands of avian samples that have already been found to have haemosporidian infections of at least moderate intensity, greatly improving our understanding of parasite speciation, biogeography, and evolutionary dynamics.
National Science Foundation, Award: PRFB-1611710, DEB-1146491