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Dryad

Foraging shifts and visual preadaptation in ecologically diverse bats

Cite this dataset

Davies, Kalina T. J. et al. (2020). Foraging shifts and visual preadaptation in ecologically diverse bats [Dataset]. Dryad. https://doi.org/10.5061/dryad.00000001g

Abstract

Changes in behaviour may initiate shifts to new adaptive zones, with physical adaptations for novel environments evolving later. While new mutations are commonly considered engines of adaptive change, sensory evolution enabling access to new resources might also arise from standing genetic diversity, and even gene loss. We examine the relative contribution of molecular adaptations, measured by positive and relaxed selection, acting on eye expressed genes associated with shifts to new adaptive zones in ecologically diverse bats from the superfamily Noctilionoidea. Collectively, noctilionoids display remarkable ecological breadth, from highly divergent echolocation to flight strategies linked to specialized insectivory, the parallel evolution of diverse plant-based diets (e.g., nectar, pollen, and fruit) from ancestral insectivory, and –unusually for echolocating bats– often have large, well-developed eyes. We report contrasting levels of positive selection in genes associated with the development, maintenance, and scope of visual function, tracing back to the origins of noctilionoids and Phyllostomidae (the bat family with most dietary diversity), instead of during shifts to novel diets. Generalized plant visiting was not associated with exceptional molecular adaptation, and exploration of these novel niches took place in an ancestral phyllostomid genetic background. In contrast, evidence for positive selection in vision genes was found at subsequent shifts to either nectarivory or frugivory. Thus, neotropical noctilionoids that use visual cues for identifying food and roosts, as well as for orientation, were effectively preadapted, with subsequent molecular adaptations in nectar-feeding lineages and the Stenodermatinae subfamily of fig-eating bats fine-tuning pre-existing visual adaptations for specialized purposes.

Methods

Multiple sequence alignments for protein-coding gene coding sequences in bat species, including sequences from the Noctilionoidea superfamily and out-group taxa. Genes were identified with best hit reciprocal blast (blast+/2.2.29) using the longest representative sequences of human proteins (Ensembl 86), applying an e-value cut-off <1e-6. Multiple sequence alignments were generated with GUIDANCEv.2.02 using the PRANKv.170427 algorithm, with 10 bootstrap replicates and codons enforced. For 10 genes encoding proteins of ≥5000 amino acids, alignments were constructed with MAFFTv.7.310 instead of PRANK, due to computational limits of run-time. Low confidence sites (below default score of 0.93) and/or low quality sequences (below default score of 0.6), were removed. Genes for which low quality sequences were detected were re-aligned with these removed. All alignments sites containing >50 % gaps and sequences <50 codons were removed using a Perl script which kept codons intact. Alignments were retained if they contained >100 codons and at least six species, with at least one of these being a focal species (i.e. a noctilionoid).

Usage notes

Multiple sequence alignments (in fasta format) for protein-coding gene coding sequences obtained from RNA-Seq data collected from bats representing the Noctilionoidea superfamily and out-group taxa.

Funding

European Research Council, Award: 310482 EVOGENO

University of Michigan–Ann Arbor, Award: ECR bridging fund

National Science Foundation, Award: DEB-1442142

National Science Foundation, Award: DEB-1442314

National Science Foundation, Award: DEB-1701414

National Science Foundation, Award: DBI-1812035