Museomics of tree squirrels: a dense taxon sampling of mitogenomes reveals hidden diversity, phenotypic convergence, and the need of a taxonomic overhaul

Abstract

Background: Tree squirrels (Sciuridae, Sciurini), in particular the highly diverse Neotropical lineages, are amongst the most rapidly diversifying branches of the mammal tree of life but also some of the least known. Negligence of this group by systematists is likely a product of the difficulties in assessing morphological informative traits and of the scarcity or unavailability of fresh tissue samples for DNA sequencing. The highly discrepant taxonomic arrangements are a consequence of the lack of phylogenies and the exclusive phenotypic-based classifications, which can be misleading in a group with conservative morphology. Here we used high-throughput sequencing and an unprecedented sampling of museum specimens to provide the first comprehensive phylogeny of tree squirrels, with a special emphasis on Neotropical taxa.

Results: We obtained complete or partial mitochondrial genomes from 232 historical and modern samples, representing 40 of the 43 currently recognized species of Sciurini. Our phylogenetic analyses-performed with datasets differing on levels of missing data and taxa under distinct analytical methods-strongly support the monophyly of Sciurini and consistently recovered 12 major clades within the tribe. We found evidence that the diversity of Neotropical tree squirrels is underestimated, with at least six lineages that represent taxa to be named or revalidated. Ancestral state reconstructions of number of upper premolars and number of mammae indicated that alternative conditions of both characters must have evolved multiple times throughout the evolutionary history of tree squirrels.

Conclusions: Complete mitogenomes were obtained from museum specimens as old as 120 years, reinforcing the potential of historical samples for phylogenetic inferences of elusive lineages of the tree of life. None of the taxonomic arrangements ever proposed for tree squirrels fully corresponded to our phylogenetic reconstruction, with only a few of the currently recognized genera recovered as monophyletic. By investigating the evolution of two morphological traits widely employed in the taxonomy of the group, we revealed that their homoplastic nature can help explain the incongruence between phylogenetic results and the classification schemes presented so far. Based on our phylogenetic results we suggest a tentative supraspecific taxonomic arrangement for Sciurini, employing 13 generic names used in previous taxonomic classifications.

Keywords: Historical DNA; Morphology; Neotropical region; Phylogeny; Sciuridae; Systematics.

Fig. 1

Relationship between specimen age and mitochondrial genome completeness recovered from historical samples of Sciurini. Open circles represent osteocrusts from the National Museum of Natural History (USNM; N = 44), while gray circles represent osteocrusts from the American Museum of Natural History (AMNH; N = 20). Dashed black line represents linear regression based on samples from USNM and dashed gray line from ANMH, while the solid line represents the linear regression based on the samples from both collections. None of the linear regressions performed were significant (P > 0.05)

Fig. 2

Circular mitochondrial genome map of Guerlinguetus brasiliensis depicting the gene organization in tree squirrels. The inner circle shows the GC content along the mitogenome. Photograph of G. brasiliensis by Pedro Peloso

Fig. 3

Simplified ML trees of Sciurini based on analyses of five distinct datasets. a Dataset 1—92 specimens with no missing data, b Dataset 2—162 specimens with < 20% of missing data per sample, c Dataset 3—186 specimens with < 40% of missing data per sample, d Dataset 4—210 specimens with < 60% of missing data per sample, and e Dataset 5—232 specimens with < 80% of missing data per sample. Additional details of each dataset are provided in Table 2. Numbers above branches indicate support values for all nodes that presented bootstrap frequencies below 100%

Fig. 4

(parts a, b, and c). Mitochondrial phylogenomic inference of Sciurini recovered by ML analysis of 232 specimens (Dataset 5). Nodal support from the ML bootstrap pseudo-replicates are indicated at each node along with Bayesian posterior probabilities (BI). White wedges indicate bootstrap values ≤ 50%, grey indicates bootstrap frequencies between 50 and 75%, and black indicates bootstrap frequencies ≥ 75%. For BI, white indicates PP < 0.95, whereas black indicates PP ≥ 0.95. Scale at the bottom represents substitutions per site. Letters A–L identify species groups discussed in the text. Except by putative unnamed species (“species 1–3”), terminals are named with specific epithets following [1, 2], and [24] (see methods for details), accompanied by museum voucher numbers and geographic information (country code and state/department). The first column represents Operacional Taxonomic Units (OTUs), recognized with base on original identifications and monophyly. The second to fourth columns correspond to the status of the delimitation of OTUs by different species delimitation methods: generalized mixed Yule-coalescent models using ultrametric trees generated with strict molecular clock (GMYC 1) and relaxed log-normal clock (GMYC 2); and Bayesian Phylogenetics and Phylogeography (BPP) analyses

Fig. 5

Collecting localities of samples composing Neotropical Sciurini lineages. Maps were generated using QGIS 3.4.4 (http://qgis.org)

Fig. 6

Ancestral state reconstructions of morphological characters and comparison between phylogeny and classification schemes of Sciurini. The first column identifies species groups (a–l) discussed in the text, the second to fifth columns show previous classifications of Sciurini at genus level, and the last column depicts the tentative generic classification suggested by this study. Morphological characters are number of premolars (character 1) and number of pairs of mammae (character 2). See text for character definitions and scoring details. Pie diagrams at internal nodes represent estimated probabilities of alternative states