alexa Target capture and massively parallel sequencing of ultraconserved elements for comparative studies at shallow evolutionary time scales.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Phylogenetics & Evolutionary Biology

Author(s): Smith BT, Harvey MG, Faircloth BC, Glenn TC, Brumfield RT, Smith BT, Harvey MG, Faircloth BC, Glenn TC, Brumfield RT

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Abstract Comparative genetic studies of non-model organisms are transforming rapidly due to major advances in sequencing technology. A limiting factor in these studies has been the identification and screening of orthologous loci across an evolutionarily distant set of taxa. Here, we evaluate the efficacy of genomic markers targeting ultraconserved DNA elements (UCEs) for analyses at shallow evolutionary timescales. Using sequence capture and massively parallel sequencing to generate UCE data for five co-distributed Neotropical rainforest bird species, we recovered 776-1516 UCE loci across the five species. Across species, 53-77\% of the loci were polymorphic, containing between 2.0 and 3.2 variable sites per polymorphic locus, on average. We performed species tree construction, coalescent modeling, and species delimitation, and we found that the five co-distributed species exhibited discordant phylogeographic histories. We also found that species trees and divergence times estimated from UCEs were similar to the parameters obtained from mtDNA. The species that inhabit the understory had older divergence times across barriers, contained a higher number of cryptic species, and exhibited larger effective population sizes relative to the species inhabiting the canopy. Because orthologous UCEs can be obtained from a wide array of taxa, are polymorphic at shallow evolutionary timescales, and can be generated rapidly at low cost, they are an effective genetic marker for studies investigating evolutionary patterns and processes at shallow timescales. This article was published in Syst Biol and referenced in Journal of Phylogenetics & Evolutionary Biology

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