Optimization of Genotype by Sequencing data for phylogenetic purposes

• Herein we propose a framework for assembling and analyzing Genotype by Sequencing (GBS) data to better understand evolutionary relationships within a group of closely related species using the mastiff bats (Molossus) as our model system. Many species within this genus have low-levels of genetic variation within and between morphologically distinct species, and the relationships among them remain unresolved using traditional Sanger sequencing methods. Given that both de novo and reference genome pipelines can be used to assemble next generation sequences, and that several tree inference methodologies have been proposed for single nucleotide polymorphism (SNP) data, we test whether different alignments and phylogenetic approaches produce similar results. We also examined how the process of SNP identification and mapping can affect the consistency of the analyses. Different alignments and phylogenetic inferences produced consistent results, supporting the GBS approach for answering evolutionary questions on a macroevolutionary scale when the genetic distance among phenotypically identifiable clades is low. We highlight the importance of exploring the relationships among groups using different assembly assumptions and also distinct phylogenetic inference methods, particularly when addressing phylogenetic questions in genetic and morphologically conservative taxa. • The method uses the comparison of several filter settings, alignments, and tree inference approaches on Genotype by Sequencing data. • Consistent results were found among several approaches. • The methodology successfully recovered well supported species boundaries and phylogenetic relationships among species of mastiff bats not hypothesized by previous methods.