# Revised phylogeny from complete mitochondrial genomes of phyllostomid bats resolves subfamilial classification

M Alejandra Camacho, Dániel Cadar, Balázs Horváth, Andrés Merino-Viteri, Jérôme Murienne

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## To cite this version:

M Alejandra Camacho, Dániel Cadar, Balázs Horváth, Andrés Merino-Viteri, Jérôme Murienne. Revised phylogeny from complete mitochondrial genomes of phyllostomid bats resolves subfamilial classification. Zoological Journal of the Linnean Society, 2022, 196 (4), pp.1591-1607. 10.1093/zoolinnean/zlac055. hal-04909550

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Submitted on 24 Jan 2025

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Abstract

Molecular phylogenies of Phyllostomidae have been classically inferred using a
combination of few mitochondrial and nuclear markers; however, there is still
uncertainty in the classification, especially among deep clades within the family. In
this study, we provide newly sequenced complete mitochondrial genomes from 26
bat species, including 23 species' genomes reported for the first time. By carefully
analyzing under Maximum Likelihood and Bayesian methods different ingroup and
outgroup samples, partition schemes, and data types, we investigated the
robustness and sensitivity of our phylogenetic results. The optimal topologies were
those inferred with the complete data matrix of nucleotides, with complex and
highly parameterized substitution models and partition schemes. Our results show
a statistically robust picture of the evolutionary relationships between phyllostomid
subfamilies and clarify hitherto uncertain relationships of Lonchorhininae and
Macrotinae.

KEYWORDS: Lonchorhininae - Macrotinae - mitochondrial genomes - phylogenetics Phyllostomidae
INTRODUCTION

The New World leaf-nosed bats, family Phyllostomidae Gray 1825, are found
ubiquitously in all regions of the Neotropics. The most recent classification
recognizes 227 species in 61 genera (Simmons y Cirranello, 2022), making it the
second most speciose chiropteran family after Vespertilionidae Gray 1821. This
group of bats is characterized by its rapid early radiation and recent speciation
events (Velazco, 2005; Solari et al., 2009; Larsen et al., 2013; Velazco & Patterson,
2013, 2019) that led to an unparalleled morphological, behavioral, and ecological
diversity (Freeman, 2000; Dumont et al., 2012; Dávalos et al., 2012; Dávalos et al.,
2014; Baker et al., 2016), and an exceptional diversification of feeding habits with
six different strategies: sanguivory, insectivory, frugivory, nectivory, carnivory, and
omnivory (Baker et al. 2012). According to Baker et al. (2016), Phyllostomidae is
divided into eleven subfamilies, twelve tribes and nine subtribes.

Several phylogenetic studies have examined the relationships among phyllostomid
bats using nuclear and mitochondrial loci obtained from classical Sanger sequencing
(Baker et al., 2003; Datzmann et al., 2010; Rojas et al., 2011; Dumont et al., 2012;
Dávalos et al., 2014; Rojas et al., 2016). Among these studies, Rojas et al. (2016)
inferred a phylogeny from seven nuclear and five mitochondrial genes, which has
been used as a backbone for evolutionary inferences in phyllostomids (Potter et al.,
2021). Despite these comprehensive analyses, there is still considerable debate
about the position of Lonchorhininae Gray 1866, Micronycterinae Van Den Bussche
1992, and Macrotinae Van Den Bussche 1992, at a deeper level. In addition, further
studies are required to solve the systematics of certain groups at the genera level;
specially those that have been traditionally underrepresented due to limited
taxonomic sampling, limited data sets, and incongruences among and within different data types, leading to conflicts when drawing taxonomic or systematic conclusions (Solari *et al.*, 2009; Baker *et al.*, 2016; Solari *et al.*, 2019b; Morales-Martínez *et al.*, 2021).

Botero-Castro *et al.* (2013) used high-throughput sequencing to obtain complete mitogenomes through a genome-skimming approach. Using shallow sequencing, this approach is able to fully recover repeated regions of the genome, typically organelles such as the mitochondria (Straub *et al.*, 2012; Trevisan *et al.*, 2019). In their study, Botero-Castro *et al.* (2013) sequenced the complete mitochondrial genome of eleven bat species, including representatives of seven phyllostomid subfamilies, and compared the phylogenies from mitochondrial genomes versus nuclear exons (*rag2* and *vWF*), and single-gene versus concatenation for both kinds of genes. They found that the phylogeny inferred from concatenated mitogenomic sequences was better resolved and well supported. Following their previous study, Botero-Castro *et al.* (2018) sequenced eight new chiropteran mitogenomes and added sequences from GenBank, consolidating a sample of 39 bat species including 19 phyllostomids representing each subfamily as defined by Baker *et al.* (2003).

Complete mitochondrial genomes in vertebrates may provide a better resolution of phylogenetic relationships on various taxonomic levels than short nuclear and mitochondrial fragments classically used with Sanger sequencing data (Meganathan *et al.*, 2012; Finstermeier *et al.*, 2013; Fabre *et al.*, 2017; Botero-Castro *et al.*, 2018; Pan *et al.*, 2020; Hassanin *et al.*, 2020). In addition, advances of high-throughput sequencing technologies in the last decade provide efficient access to mitochondrial
genome sequences (Springer *et al.*, 2004; Paijmans *et al.*, 2013; Morgan *et al.*, 2014; Phillips & Shazwani-Zakaria, 2021; Toussaint *et al.*, 2021).

The seminal work of Botero Castro *et al.* (2013, 2018) provided the foundation for phyllostomids mitochondrial phylogenomics. However, the results are based on a very limited dataset of bats, representing 2.6% of the order's diversity. In this study, using high-throughput sequencing, we have generated several complete bat mitogenomes to reconstruct a subfamily-level phylogeny of phyllostomids. We herein addressed the following questions: (i) does the newly sequenced mitogenomic data help to improve the phylogeny at the subfamily level? (ii) what is the influence of various analytical conditions on the results? In particular, we investigated the influence of partition schemes, choice of outgroups, data type and phylogenetic methods.

# MATERIAL AND METHODS

## TAXON SAMPLING, DNA EXTRACTION AND SEQUENCING

We newly sequenced 32 mitogenomes from 26 new species out of which 23 belong to Phyllostomidae, two to Vespertilionidae, and one to Molossidae Gervais 1856. The tissues used for DNA extraction belonged to specimens collected in various field trips from western provinces of Ecuador (Figure 1), as part of research projects of the Mammalogy Section of the Museum of Zoology of the Pontifical Catholic University of Ecuador (QCAZ). Additional information about these specimens can be retrieved from https://bioweb.bio/faunaweb/mammaliaweb/. In addition, we used 39 complete mitogenome sequences generated by Botero-Castro *et al.* (2013, 2018), composed of 37 sequences from eight chiropteran and two non-chiropteran
families. Our dataset was thus formed by 71 complete mitogenomes (Table 1). Only three species are represented by two mitogenome sequences: *Desmodus rotundus* Wied-Neuwied, 1826 (Desmodontinae J.A. Wagner, 1840), *Micronycteris megalotis* (Micronycterinae Van Den Bussche, 1992), and *Artibeus lituratus* Leach, 1821.

Bat tissue sections (heart, liver, lungs) were pooled per specimen and introduced in 2 mL safe-lock tubes (Eppendorf, Hamburg, Germany) with tungsten carbide beads (3 mm, Qiagen, Hilden, Germany) and 0.7 mL chilled high-glucose (4.5 g/L) Dulbecco's modified Eagle's medium (DMEM) (Sigma-Aldrich, St. Louis, MO, USA). Bats tissues were homogenized with a TissueLyser II (Qiagen, Hilden, Germany) for 2 min at 30-50 Hz. The suspension was clarified by centrifugation for 1 min at 8000 rpm at 4°C. DNA and RNA were extracted using the MagMAX CORE Nucleic Acid Purification Kit (ThermoFisher Scientific, Waltham, MA, USA) according to manufacturer's recommendations. The quality and quantity of extracted nucleic acids were measured using Qubit™ DNA/RNA HS Assay Kit (Thermo Fisher Scientific, Austin, TX, USA). The extracted DNA (120 ng starting concentration) was subjected to library preparation using a QIAseq FX DNA Library Kit (Qiagen, Hilden, Germany) according to the instructions of the manufacturer. Normalized samples were pooled and sequenced on an Illumina NextSeq550 sequencing platform using the 300-cycle (2 × 150 bp paired-end) NextSeq550 reagent kit (Illumina, San Diego, CA, USA).

## MITOGENOME ASSEMBLY AND ANNOTATIONS

The paired-end Illumina reads were quality checked, automatically trimmed, and merged using QIAGEN CLC Genomics Workbench 20.0 (https://digitalinsights.qiagen.com/). Additional adapter trimming and
deduplication was performed using the BBtools software package (https://sourceforge.net/projects/b&W/). The resulting high-quality reads were de novo assembled with Megahit, which in this case was found to give the best output (Li et al., 2015). We used reference guided mapping, circularization validation, manual curation, also using the CLC Genomics Workbench 20.0 software. All the assembled mitochondrial genomes were annotated using MITOS2 metazoan pipeline (Bernt et al., 2013; Al Arab et al., 2017; Donath et al., 2019), followed by manual adjustment in Geneious 9.0.5 (https://www.geneious.com). We relied on the publicly available mitochondrial sequences as reference (Botero-Castro et al., 2013, 2018). In order to validate the morphological identification of the bat species, we used the Barcoding of Life Database Identification Engine on the 5' region of the COI sequence using the BOLD web server (Ratnasingham & Hebert, 2007).

ALIGNMENT AND PHYLOGENY

Ribosomal RNA and transfer RNA loci were aligned using MUSCLE (Edgar, 2004).
Sequences of protein-coding genes were aligned using TranslatorX (Abascal et al.,
2010) to preserve the reading frame. We used trimAl (Capella-Gutiérrez et al., 2009)
to remove poorly aligned regions. Following Botero Castro et al. (2018), the protein-
coding gene nd6 and the control region were excluded from the analyses. The nd6
gene has frequently been omitted because it is coded on the light strand, and its
properties differ from those of the other 12 protein-coding genes (Springer et al.,
2001; Gao et al., 2018); the control region is the most variable region because of a
faster rate of evolution as compared with the rRNA and protein-coding genes of the
mitochondrial genome (Gong et al., 2015), which may interfere in the phylogenetic
interpretation. The final data matrix consisted of 71 mitogenomes, each comprising 36 loci (two rRNA, 12 protein-coding and 22 tRNA genes) and averaging 16 kb.

In order to evaluate the impact of ingroup taxon sampling on the results, we performed a phylogenetic analysis using the same analytical parameters and the same outgroups as in Botero-Castro *et al.* (2018), but with an ingroup taxon sampling that significantly exceeds previous analyses. In their study, Botero-Castro *et al.* (2018) used sequences from 19 phyllostomid species while we here used 42 species. We consider this step as our “reference analysis” and the resulting topology as our “reference tree”.

To evaluate the influence of partitioning, we analyzed various *a priori* schemes as well as new estimated ones. For the *a priori* nucleotide partition schemes, following Botero-Castro *et al.* (2018), we used one partition, five partitions (two independent partitions for rRNAs and tRNAs combined with three partitions corresponding to each codon position), 14 partitions (two independent partitions for rRNAs and tRNAs plus one partition for each protein-coding gene), and 38 partitions (two independent partitions for rRNAs and for tRNAs plus 36 partitions, one partition for each codon for each gene). For each *a priori* partition scheme, we used a Generalized Time Reversible model of substitution rates along with a Gamma distribution and a fraction of invariable sites (GTR+G+I). In addition, we also estimated the optimal partition scheme and evolutionary model using PartitionFinder 2.1.1 (Lanfear *et al.*, 2012) and ModelFinder (Kalyaanamoorthy *et al.*, 2017) as implemented in IQ-TREE 2 (Minh *et al.*, 2020) (Table 2). The best partitioning schemes were chosen based on the Akaike Information Criterion (AIC) (Bozdogan, 1987).
To evaluate the impact of taxon sampling in the outgroups, we compared our reference analysis from the complete sample of 71 sequences (henceforth “Full outgroup dataset”) with a new dataset comprising a subset of 48 nucleotide sequences with only the mitochondrial genomes of Noctilionidae Gray, 1821 and Mormoopidae Saussure, 1860 as outgroups (“Reduced outgroup dataset”) (Table 2). We followed Baker *et al.* (2003) who repeatedly found these families as outgroups of Phyllostomidae in their higher-level classification analyses with both mitochondrial and nuclear markers. For each dataset, we estimated the best nucleotide substitution models and partitioning schemes (Table 2).

We also performed various analyses using our dataset as amino acids. We only considered the coding genes and evaluated the impact of outgroups and partitioning schemes as with the nucleotides. For amino acid data sets, we used one and twelve partitions (one for each protein-coding gene) as proposed by Botero-Castro *et al.* (2018), and the resulting best-fit schemes suggested by PartitionFinder and ModelFinder (Table 3). The *a priori* partitions were analyzed with a LG and mtMAM model of substitution rates, respectively, along with a Gamma distribution and a fraction of invariable sites (LG+G+I; mtMAM+G+I). The best partitioning schemes were chosen based on the Akaike Information Criterion (AIC). As with nucleotides, we evaluated the impact of outgroups by comparing our reference analysis (71 mitogenomes with full outgroups) with a dataset comprising a subset of 48 amino acids sequences with only Noctilionidae and Mormoopidae as outgroups.

We performed an additional analysis considering only the coding genes from our full nucleotide dataset using a 36-partition scheme (one partition for each codon for each gene, excluding *nd6*). This analysis was performed to examine the influence of
the data type (amino acid versus the nucleotide) using the exact same dataset (only the protein coding genes).

We performed Maximum Likelihood analyses using RAxML-NG (Kozlov *et al.*, 2019) starting from 10 parsimony trees and 10 random trees. Bootstrapping was performed with the bootstopping option ("bs-trees autoMRE{N}" command). Bootstrap support values were obtained using the classical Felsenstein metric (Felsenstein, 1985) and Transfer Bootstrap Expectation (Lemoine *et al.*, 2018). For comparative reasons, we also inferred the ML tree using IQ-TREE2 (Minh *et al.*, 2020) using the edge-linked partition model (Nguyen *et al.*, 2015; Chernomor *et al.*, 2016) and obtained node support with the ultrafast bootstrap (Hoang *et al.*, 2018) by performing 1000 replicates. Bayesian Inference analyses were performed using MrBayes 3.2.7 (Ronquist *et al.*, 2012). We partitioned the sequences in 38 sets corresponding to two independent partitions for rRNAs and for tRNAs plus 36 partitions, one partition for each codon for each gene, and used the best analytical scheme as evaluated by the Akaike information criterion (AIC). We ran eight MCMC chains for ten million generations with default heating values. The sampling frequency was set every 1000 generations and the first 25,000 samples were discarded as burn-in. A consensus tree was built under the majority rule consensus of all trees obtained in the eight runs after the burn-in period. We used the "sumt" command to produce summary statistics for trees sampled during a Bayesian MCMC analysis. Posterior probabilities of nodes were regarded as estimators of confidence. Finally, trees were visualized and edited in FigTree v1.4.4 (http://tree.bio.ed.ac.uk/software/figtree/). Only the optimal partitioning schemes found under ML, were evaluated using Bayesian inference.
## RESULTS

After DNA extraction and sequencing, we obtained a mean of 640,043 reads (SD 329,238) per library (Table 4). Among the 32 newly generated mitochondrial genomes, 23 species' genomes have not been published and are first reported here. All mitochondrial genomes show the typical circular structure with an average length of 16,690 pb (SD 152 pb; Table 4) and harbor the gene order found in other mammalian genomes (Pumo *et al.*, 1998; López-Wilchis *et al.*, 2017).

## REFERENCE ANALYSIS

We used as reference the phyllostomid phylogeny inferred from all genes under Maximum Likelihood (ML) using RAxML-NG (Kozlov *et al.*, 2019). Sequence evolution was modeled using a GTR+G+I model and a 38-partition scheme comprising two independent partitions for rRNAs and for tRNAs, plus one partition per gene and per codon position for each coding gene. We used 71 complete mitogenomes which included the “Full outgroup dataset” (Table 2). In essence, this analysis corresponds exactly to the one previously performed by Botero-Castro *et al.* (2018) except for the ingroup where we added 23 new phyllostomid species to the 19 previously used in 2018. As expected, Phyllostomidae is recovered as monophyletic and divided into eleven clades corresponding to all known subfamilies (Figure 1). At the level of deep nodes (subfamilies), we cannot observe differences between our reference topology and the best evaluated topology obtained by Botero-Castro *et al.* (2018), however, the addition of new mitogenomes shows genus-level relationships not presented by Botero-Castro *et al.* (2018) that help clarify the relationships between species, particularly those in nectar-feeding
subfamilies. When compared with the other analyses that combine mitochondrial and nuclear markers (Baker, 2000; Baker et al., 2003; Rojas et al., 2016), the main difference in our analysis lies in the position of Lonchorhininae as sister group to Phyllostominae Gray, 1825, not to a clade formed by Lonchophyllinae Griffiths, 1982 and the mainly frugivore subfamilies.

The phylogenetic relationships between the Stenodermatinae Gervais, 1856, Rhinophyllinae Baker, Solari, Cirranello & Simmons, 2016, Carolliinae and Glyphonycterinae Baker, Solari, Cirranello & Simmons, 2016 subfamilies are recovered with strong support. Stenodermatinae shares a common ancestry with Rhinophyllinae after diverging from a clade formed by Carolliinae and Glyphonycterinae. Regarding the nectar-feeding phyllostomids, Lonchophyllinae appears as sister to a lineage comprising the clades formed by Stenodermatinae + Rhinophyllinae and Carolliinae + Glyphonycterinae (Figure 2), with a strong nodal support (BS=91%, node not recovered with Bayesian inference) and in agreement with Baker et al. (2003), Rojas et al. (2011), and Rojas et al. (2016). Glossophaginae Bonaparte, 1845 is the nectar-feeding clade that diverged first and is composed of two major lineages: one containing Anoura Gray, 1838 and Choeroniscus, and the other containing Glossophaga E. Geoffroyi, 1818 and Brachypylla Gray, 1833. In addition, Phyllostominae appears as a sister group to Lonchorhininae with moderate bootstrap support and vampire bats are defined as a three-genus monophyletic clade (Desmodontinae), with well-resolved relationships. In our reference tree, Macrotinae is recovered as sister group to all remaining Phyllostomid subfamilies, and Mormoopidae appears as sister family to Phyllostomidae, also in concordance with previous phylogenetic reconstructions
(Baker *et al.*, 2003, 2016; Cirranello *et al.*, 2016). All phylogenetic relationships between non-Phyllostomid families remained consistent with the results obtained in previous studies with mitogenomes except that, for the first time, mitogenomes of the family Molossidae (*Molossus molossus* É. Geoffroy, 1805) are added and appear closely related to Vespertilionidae.

IMPACT OF PARTITIONING SCHEMES

We performed twelve different analyses with various *a priori* partition schemes as well as new estimated ones (Table 2). We did find that a GTR+G+I evolution model along with a 38-partitions scheme (thus corresponding to our “Reference analysis”) yielded the smallest AIC value (Table 2). This evolutionary model and partition scheme also yielded the best AIC value in the analysis performed by Botero-Castro *et al.* (2018). The eleven additional analytical schemes are thus sub-optimal in the sense that they yielded higher AIC values than with the optimal partitioning scheme, including those with IQ-TREE2 performed for comparative reasons. This evaluation is however particularly relevant as it provides a different view of the stability of our results compared to statistical resampling like bootstrap. The presence (or not) of key clades was thus evaluated with a sensitivity analysis of the various analytical conditions and is represented with a Navajo rug approach (Figure 2).

Across the analyses, we were able to identify very stable nodes. The phylogenetic relationships between the Stenodermatinae, Rhinophyllinae, Carolliinae and Glyphonycterinae subfamilies are recovered in all the analyses. Rhinophyllinae appears consistently as a sister clade to Stenodermatinae and both subfamilies form a sister clade to another formed by Carolliinae and Glyphonycterinae. Vampire bats (Desmodontinae) consistently appear in the same position in all the resulting
topologies, and the relationships between the three species were all well resolved. Interestingly, the subfamily Lonchorhininae whose position was poorly supported in previous studies (Rojas *et al.*, 2016) is very stable as sister to Phyllostominae in our analyses.

We identified unstable nodes formed by subfamilies whose phylogenetic relationships varied depending on the number of partitions. Lonchophyllinae as sister to the clade formed by Stenodermatinae + Rhinophyllinae and Carolliinae + Glyphonycterinae appear in only four out of the twelve analyses with bootstraps values ranging from 63% to 96%. Lonchophyllinae is found as sister to a clade comprised by Lonchorhininae, Phyllostominae, Glossophaginae, Glyphonycterinae, Carolliinae, Rhinophyllinae and Stenodermatinae, depicting even better bootstrap values in the corresponding analyses (BS = 91%-100%). The subfamily is also recovered as sister to Glossophaginae in several analytical schemes, with medium to strong support values (BS = 45%-97%). As the position of Lonchophyllinae change in the topologies, so does Glossophaginae and its phylogenetic placement. Macrotinae appears as a sister group of all remaining phyllostomids in fifty percent of the analyses performed, with absolute support (BS = 100%, PP = 1); however, Micronycterinae is also recovered as sister clade to all remaining phyllostomids (including Macrotinae) in the other fifty percent of the analyses, also with very high support (BS = 100%; PP = 1).

## IMPACT OF OUTGROUPS TAXON SAMPLING

By comparing the topologies obtained with the "Full outgroup dataset" and the "Reduced outgroup dataset" (Table 2) we observe an effect caused by the number of outgroups used. Although most of the phylogenetic relationships using less
outgroups are consistent with the reference tree obtained from the analysis of 71 sequences, some relationships are less stable. In most of the analyses with the "Full outgroup dataset", Lonchophyllinae appears as sister to the nodes formed by Stenodermatinae + Rhinophyllinae and Carolliinae + Glyphonycterinae; however, in almost all the analyses performed with the "Reduced outgroup dataset", Lonchophyllinae is recovered as sister to Glossophaginae, with medium to strong support values (BS = 45%-97%). Taking this parameter into account, here again, we observe that as the position of Lonchophyllinae changes in the topologies, so does Glossophaginae and its phylogenetic placement. Unlike what was observed in all the analyses with all the sequences, with the "Reduced outgroup dataset", we found Micronycterinae as sister clade to all remaining phyllostomids (including Macrotinae; BS = 75%-89%), although less supported than Macrotinae as the sister clade to all remaining phyllostomids found with the "Full outgroup dataset".

## IMPACT OF DATA TYPE

The phylogenetic resolution and associated nodal supports across analyses differ significantly according to the type of data (i.e., nucleotides vs. amino acids). For amino acids, we performed eight different analyses (Table 3). All resulting topologies were compared, and the presence (or not) of key clades is represented with a Navajo rug approach as well (Figure S1). For amino acid data sets, the best-evaluated topology is poorly supported and does not agree with the best-evaluated topology of the nucleotide analyses.

Phyllostomidae is recovered as monophyletic and divided into eleven clades corresponding to all known subfamilies; however, as a generality, we also found
more unstable nodes with lower support than with nucleotides. We found
Lonchophyllinae as sister to a clade comprised of Lonchorhininae, Phyllostominae,
Glossophaginae, Glyphonycterinae, Carolliinae, Rhinophyllinae, and
Stenodermatinae with strong bootstrap supports (BS = 98%, node not recovered
with Bayesian inference) (Figure S1); also, we found Lonchophyllinae as the nectar-
feeding clade that diverged first and as sister to a clade containing Glossophaginae
which then diverged from a lineage containing Glyphonycterinae, Carollinae,
Rhinophyllinae and Stenodermatinae, with poor to strong support values (BS =
40%-91%). Finally, we found Lonchophyllinae forming a monophyletic clade with
Glossophaginae. The position of Lonchorhininae appears unclear when amino acid
data sets were analyzed. As with nucleotides, we found Lonchorhininae as sister to
Phyllostominae in some analyses although mostly with poor bootstrap support. In
most of the amino acid analyses, Lonchorhininae appears as sister to clades
containing the subfamilies Phyllostominae, Lonchophyllinae, Glossophaginae,
Glyphonycterinae, Carolliinae, Rhinophyllinae, and Stenodermatinae. Another
important variation in relation to the results we obtained with nucleotide data sets
was the position of Micronycterinae: in all the analysis carried out with amino acids
Micronycterinae appears as the sister lineage to all the other phyllostomids with
strong support values (BS = 90%-100%). Our analysis considering only the coding
genes from our full nucleotide dataset using a 36-partition scheme yielded a
topology that mostly resembled the best-evaluated phylogeny from the amino acid
data set and also does not agree with the best-evaluated topology of the nucleotide
analyses (Figure S2).
IMPACT OF PHYLOGENETIC METHODS

For the Bayesian inference, we used the same analytical scheme as for Maximum
Likelihood. We observe that the phylogenetic resolution and associated nodal
supports differ depending on the inference method. Even with high bootstrap
values, some nodes are not recovered under Bayesian Inference. Figure 2 (for
nucleotides) and S1 (for amino acids) summarize and compare the support values
of the ML analyses and the BI posterior probabilities with a pattern of colored
semicircles. In the trees, it can be observed that the absence of a semicircle
represents the non-recovery of a particular node by ML or BI.

Under Bayesian Inference we observe relationships between subfamilies
(particularly in the less stable nodes) statistically less likely to occur due to posterior
probabilities lower than 0.5, for example a monophyletic relationship between
Lonchophyllinae and Phyllostominae (PP = 0.47). Additionally, the relationships
between Lonchorhininae with the rest of the subfamilies or those of
Micronycterinae or Macrotinae as basal clades of Phyllostomidae are neither clear
nor consistent under Bayesian analysis.

DISCUSSION

In this study, we provide newly sequenced complete mitogenomes for 26 bat
species, from 16 genera, and three families. Our phylogenomic analysis of
phylostomids confirmed the relationships so far agreed between the subfamilies,
with strong supports and highly congruent with those previously suggested by
Baker *et al.* (2016), Rojas *et al.* (2016), and Botero-Castro *et al.* (2018).
Phyllostomidae was monophyletic and divided into eleven subfamilies. The
phylogenetic relationships between Stenodermatinae, Rhinophyllinae, Carolliinae, and Glyphonycterinae, as well as the position of Desmodontinae were consistent and well supported. Lonchophyllinae evolved independently of Glossophaginae, although inconsistent results across different analyses were evident among nectar-eating subfamilies (see specific discussion hereafter). Unlike what was found by Rojas *et al.* (2016), Lonchorhininae appears consistently as the sister of Phyllostominae. Finally, in our reference tree, Macrotinae is retrieved as a sister group to all the remaining Phyllostomid subfamilies. Despite high support values both in the ML and BI analyses, our sensitivity analysis highlighted that some relationships were unstable when parameters related to the number of outgroup taxa, number of partitions, and data type (i.e., nucleotides vs. amino acids) were evaluated and we hereafter further discuss the stability of our results and their implication for evolutionary studies.

The choice of outgroup could have important consequences for the resulting phylogenetic tree (Graybeal, 1998; Schneider & Cannarozzi, 2009). From all possible outgroups, the closest one is the best choice to root a tree because shorter distances suffer less from statistical error and the expected number of homoplasies between any ingroup and the outgroup is minimized (Muse & Weir, 1992; Smith, 1994). We expected that by removing all other mammalian families and keeping the closest outgroups (Reduced outgroup dataset), the phylogeny of Phyllostomidae could be improved or at least would not be affected. On the contrary, our results showed discrepancy between phylogenies obtained with the full outgroup dataset and the reduced outgroup dataset. We found stronger phylogenetic congruence when all sequences, even those less phylogenetically related, were maintained as outgroups.
This is particularly true for the most basal nodes in phyllostomids, related to the phylogenetic placement of Macrotinae and Micronycterinae.

Early debates concentrated on the choice of the appropriate evolutionary model (Kelsey *et al.*, 1999), with the adequacy of the model potentially producing differences between topologies with short internal branches (Schneider & Cannarozzi, 2009). However, it is now well recognized that choosing the most adequate model is unimportant and that using the most complex model provides consistent topologies (Abadi *et al.*, 2019). However, variation in substitution patterns across genes and sites should still be accommodated and the partitioning of the dataset can have strong influence on the topology (Kainer & Lanfear, 2015). Likewise, some of our results proved to be sensitive to the choice of the partitioning scheme. This is particularly visible in the “intermediate” part of the tree (between the shallowest nodes and the deeper nodes) where branch lengths are noticeably shorts. The optimal results are however quite stable as they are retrieved in four out six partition schemes.

Of all the analytical schemes that we evaluated, a strong influence of the data type (nucleotides vs amino acids) has been observed. In general, the best-evaluated model for amino acids yielded a topology that was incongruent with the best-evaluated nucleotide topology. Our most well-supported result for amino acids (71 samples with a 7-partition scheme; Figure S1) contradicts most previous relevant molecular analyses (Baker, 2000; Baker *et al.*, 2003; Rojas *et al.*, 2011, 2016; Dávalos *et al.*, 2012; Cirranello *et al.*, 2016), although it is congruent with the best evaluated topology for amino acids by Botero-Castro *et al.* (2018). Both ML and BI analyses reconstructed a similar topology; however, more key clades showed lower support
values, if compared to nucleotides data sets. These low phylogenetic resolutions
may be due to the use of coding genes only and thus fewer characters. This was
demonstrated with the analysis we did using only coding genes from the nucleotide
data set (Figure S2).

In our reference tree, Lonchophyllinae and Glossophaginae were not sister clades.
Both ML and BI analyses strongly support the non-monophyly of these lineages.
However, the most notorious incongruities across analyses were those related to the
phylogenetic position of the nectar-eating subfamilies. In the case of nectarivores,
five out of twelve analyses carried out with nucleotides and one out of eight analyses
carried out with amino acids, depicted these two subfamilies as monophyletic.
Although these results may agree with morphological phylogenies such as Wetterer
et al.'s (2000) and some of the analyses made by Dávalos et al. (2012), our best-
supported results showed both groups as not sister taxa. The homoplasies observed
in the aforementioned morphological phylogenies may be the result of
morphological similarities associated with ecological adaptations to nectar feeding
(Gatesy et al., 1996; Sánchez-Villagra & Williams, 1998; Wiens et al., 2003).
However, profound examination of morphological characters such as the oral
muscle complexes (Griffiths, 1982; Datzmann et al., 2010) and recent extensive
molecular analyses (Baker et al., 2016; Rojas et al., 2016) strongly support that
Lonchophyllinae and Glossophaginae evolved nectarivory independently, a result
confirmed by our analyses.

Across most of our analyses, the position of Lonchorhininae is stable and well
supported as sister to Phyllostominae. Until the beginning of this century,
Lonchorhina was placed within Phyllostominae (Baker et al., 1989; Koopman, 1994;
Wetterer *et al.*, 2000; Jones *et al.*, 2002). Baker *et al.* (2003) included *Lonchorhina* *Tomes, 1863* within its own monogeneric subfamily, *Lonchorhininae*, using as evidence a Bayesian analysis that combined the nuclear gene *rag2*, the mitochondrial genes 12S rRNA, Val tRNA, and 16S rRNA. In this analysis, *Lonchorhina* diverged from the remainder of the phyllostomids after the divergence of vampires but before the common ancestor of the remaining subfamilies. Rojas *et al.* (2011), analyzed the same genes as Baker *et al.* (2003), although it resulted in another hypothesis in which *Lonchorhina* appeared as sister to a clade comprising Glossophaginae, Lonchophyllinae, Carolliinae, Glyphonycterinae, Rhinophyllinae and Stenodermatinae. Later, Rojas *et al.* (2016) in a comprehensive phylogenetic analysis using combinations of seven nuclear loci and five mitochondrial genes from phyllostomid species found *Lonchorhina* as sister to a clade that excluded Glossophaginae and Phyllostominae, although with poor support (i.e., bootstrap value < 50%). Our phylogenomic approach supports Lonchorhininae as a sister to Phyllostominae. We herein provide a better resolution of the phylogenetic relationships between these insectivore subfamilies; although we consider that this hypothesis could be *evaluated* by analyzing molecular data from all species in the genus. The six species included in *Lonchorhina* are essentially insectivores and are characterized by having highly developed and quite complex ears, tragi, and nasal leaves (Solari *et al.*, 2019a). Representatives of *Lonchorhina* depend on caves for roosting, which are, in general, difficult to access causing specimens to be very rare in museum collections (Mantilla-Meluk & Montenegro, 2016). The incomplete taxonomic coverage, both morphological and molecular, has historically prevented an accurate reconstruction of the relationships within *Lonchorhina* and among Lonchorhininae and other subfamilies.
CONCLUSION

Our mitogenomic analysis yielded a topology that was well supported and highly congruent with previous phylogenetic results. Despite variations across analyses, our optimal topology confirmed the known relationships among most subfamilies, nectarivores evolved independently, and Macrotinae is sister to all other subfamilies. We also propose the hypothesis that Lonchorhininae may be the sister subfamily of Phyllostominae. We found that deeper relationships were sensible to the outgroup and data type selection, and that the intermediate relationships characterized by short internal branches were sensible to the partitioning schemes. Under adequate analytical conditions, complete mitogenomes proved to be extremely useful for resolving patterns of phylogenetic relationships within phyllostomids. This is of particular interest considering that genome-skimming is probably the most efficient method to analyze museum specimens or highly degraded material, which in turn may be the only accessible evidence for solving taxonomic conundra. In addition, future improvements on the phylogeny of phyllostomid could come from inclusion of more species and the use of large nuclear datasets such as transcriptomics, gene capture or full genome sequencing (Tsagkogeorga et al., 2013; Lei & Dong, 2016; McCormack et al., 2016 2016; Potter et al., 2021).

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## LIST OF TABLES

**Table 1.** List of specimens used in the present study. Records include taxonomic information, voucher identification, GenBank accession number, and bibliographic reference.

**Table 2.** Nucleotide data set used in this study. "Full outgroup dataset" corresponds to the complete sample of 71 sequences, "Reduced outgroup dataset" corresponds to a sub-sample made up of 48 sequences. The partition schemes are described and the Akaike Information Criterion values are compared. The asterisks (*) denote the best-evaluated partition schemes by this criterion.

**Table 3.** Amino acids data set used in this study. "Full outgroup dataset" corresponds to the complete sample of 71 sequences, "Reduced outgroup dataset" corresponds to a sub-sample made up of 48 sequences. The partition schemes are described and the Akaike Information Criterion values are compared. The asterisks (*) denote the best-evaluated partition schemes by this criterion.

**Table 4.** General features of the 32 new bat mitogenome assemblies.

## SUPPLEMENTARY TABLE

**Table S1.** Taxonomic and collection data from Ecuadorian specimens analyzed in this study and whose mitogenome sequences were generated (see Table 1 for GenBank accession numbers). Altitude in meters above the see level. Weight in grams, standard external measures in mm. GPS coordinates in decimal degrees.
LIST OF FIGURES

**Figure 1.** Geographical distribution of specimens used in this work. Sampling localities: Pichincha: 1) Alambi (Lon: -78.680733, Lat: -0.030217); Santo Domingo de Los Tsáchilas: 2) Río Mulaute (Lon: -78.993183, Lat: -0.131917); 3) La Lorena (Lon: -79.139733, Lat: -0.2747998); 4) Hacienda Tinalandia (Lon: -79.054433, Lat: -0.2979668); 5) Reserva Otongachi (Lon: -78.9518828, Lat: -0.3212998); Cotopaxi: 6) Guasaganda (Lon: -79.1468667, Lat: -0.7798167); 7) Jardín de los Sueños (Lon: -79.2045668, Lat: -0.8372); 8) San Cristóbal (Lon: -79.1532668, Lat: -0.8607); 9) Manguilita El Triunfo (Lon: -79.20735, Lat: -0.9117498); Manabí: 10) Las Tunas (Lon: -80.8152861, Lat: -1.6621917)

**Figure 2:** Phylogeny of Phyllostomidae based on complete mitochondrial genomes (nucleotide sequences). The tree represents the best Maximum Likelihood phylogeny inferring Phyllostomidae and other chiropteran lineages' relationships. The tree was reconstructed in RAxML under the GTR+GAMMA+I model using the Full outgroup data set (71 taxa, 14,703 nucleotides). Color filled semicircles on the nodes indicate ML bootstrap support (percentage) and Bayesian posterior probabilities (see inserted caption). The absence of a semicircle on the node indicates that it was not recovered by ML or Bayesian inferences. Each Navajo's Rug shows if the specified node was retrieved (black square) or not (white square) in different analyses performed (see inserted caption).
LIST OF SUPPLEMENTARY FIGURES

**Figure S1:** Phylogeny of Phyllostomidae based on mitochondrial genomes (amino acid sequences). The tree represents the best Maximum Likelihood phylogeny inferring Phyllostomidae and other chiropteran lineages' relationships. The tree was reconstructed in RAxML under the mtMAM and mtREV +I+G+F models using the Full outgroup data set (71 taxa, 3,606 amino acids). Color filled semicircles on the nodes indicate ML bootstrap support (percentage) and Bayesian posterior probabilities (see inserted caption). The absence of a semicircle on the node indicates that it was not recovered by ML or Bayesian inferences. Each Navajo's Rug shows if the specified node was retrieved (black square) or not (white square) in different analyses performed (see inserted caption).

**Figure S2:** Phylogeny of Phyllostomidae based on the protein coding genes (CDS) from our full nucleotide data set using a 36-partition scheme. The tree was reconstructed in RAxML under the GTR+GAMMA+I model. Color filled semicircles on the nodes indicate ML bootstrap support (percentage; see inserted caption).
TABLES

<table><caption>**Table 1.** List of specimens used in the present study. Records include taxonomic information, voucher identification, GenBank accession number, and bibliographic reference.</caption><thead><tr><th>Family</th><th>Subfamily</th><th>Species</th><th>Voucher<sup>a</sup></th><th>Accession Number</th><th>Reference</th></tr></thead><tbody><tr><td colspan="6"><strong>Chiroptera</strong></td></tr><tr><td>Hipposideridae</td><td>–</td><td>Hipposideros armiger</td><td>–</td><td>NC_018540</td><td>Xu et al. 2012</td></tr><tr><td>Molossidae</td><td>Molossinae</td><td>Molossus molossus</td><td>QCAZ18284</td><td>ON357729</td><td>This study</td></tr><tr><td>Molossidae</td><td>Molossinae</td><td>Molossus molossus</td><td>QCAZ18287</td><td>pending</td><td>This study</td></tr><tr><td>Mormoopidae</td><td>–</td><td>Pteronotus rubiginosus</td><td>ISEM-V-2322</td><td>NC_022425</td><td>Botero-Castro et al. 2013</td></tr><tr><td>Mystacinidae</td><td>–</td><td>Mystacinia tuberculata</td><td>–</td><td>NC_006925</td><td>Unpublished</td></tr><tr><td>Noctilionidae</td><td>–</td><td>Noctilio leporinus</td><td>ISEM-V-1890</td><td>KU743910</td><td>Botero-Castro et al. 2018</td></tr><tr><td>Phyllostomidae</td><td>Carollinae</td><td>Carollia brevicauda</td><td>QCAZ18221</td><td>pending</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Carollinae</td><td>Carollia castanea</td><td>QCAZ18219</td><td>pending</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Carollinae</td><td>Carollia perspicillata</td><td>MHNG1972-003</td><td>HG003309</td><td>Botero-Castro et al. 2013</td></tr><tr><td>Phyllostomidae</td><td>Carollinae</td><td>Carollia brevicauda</td><td>QCAZ18226</td><td>pending</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Desmodontinae</td><td>Desmodus rotundus</td><td>EBRG-L-1874</td><td>HG003310</td><td>Botero-Castro et al. 2013</td></tr><tr><td>Phyllostomidae</td><td>Desmodontinae</td><td>Desmodus rotundus</td><td>QCAZ18371</td><td>pending</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Desmodontinae</td><td>Diaemus youngii</td><td>MSB-56205</td><td>KU743906</td><td>Botero-Castro et al. 2018</td></tr><tr><td>Phyllostomidae</td><td>Desmodontinae</td><td>Diphylla ecaudata</td><td>MSB-211697</td><td>KU743911</td><td>Botero-Castro et al. 2018</td></tr><tr><td>Phyllostomidae</td><td>Glossophaginae</td><td>Anoura caudifer</td><td>ROM-113962</td><td>HG003307</td><td>Botero-Castro et al. 2013</td></tr><tr><td>Phyllostomidae</td><td>Glossophaginae</td><td>Anoura cultrata</td><td>QCAZ18217</td><td>ON310503</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Glossophaginae</td><td>Anoura geoffroyi</td><td>QCAZ18218</td><td>ON310504</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Glossophaginae</td><td>Brachyphylla cavernicum</td><td>ISEM-V-2350</td><td>NC_022421</td><td>Botero-Castro et al. 2013</td></tr><tr><td>Phyllostomidae</td><td>Glossophaginae</td><td>Choeroniscus godmani</td><td>QCAZ18233</td><td>ON357720</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Glossophaginae</td><td>Glossophaga soricina</td><td>QCAZ18230</td><td>ON321893</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Glyphonycterinae</td><td>Glyphonycteris daviesi</td><td>ROM-41125</td><td>KU743912</td><td>Botero-Castro et al. 2018</td></tr><tr><td>Phyllostomidae</td><td>Lonchophyllinae</td><td>Hsunycteris thomasi</td><td>ISEM-V-1646</td><td>KU743907</td><td>Botero-Castro et al. 2018</td></tr><tr><td>Phyllostomidae</td><td>Lonchophyllinae</td><td>Lonchophylla concava</td><td>QCAZ18274</td><td>ON357727</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Lonchophyllinae</td><td>Lonchophylla concava</td><td>QCAZ18273</td><td>pending</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Lonchophyllinae</td><td>Lonchophylla robusta</td><td>QCAZ18236</td><td>ON357721</td><td>This study</td></tr></tbody></table>
<table><tr><td>Phyllostomidae</td><td>Lonchorhininae</td><td>Lonchorhina aurita</td><td>MVZ-185587</td><td>KU743908</td><td>Botero-Castro et al. 2018</td></tr><tr><td>Phyllostomidae</td><td>Macrotinae</td><td>Macrotus californicus</td><td>MSB-140888</td><td>KU743909</td><td>Botero-Castro et al. 2018</td></tr><tr><td>Phyllostomidae</td><td>Micronycterinae</td><td>Micronycteris hirsuta</td><td>QCAZ18237</td><td>ON357722</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Micronycterinae</td><td>Micronycteris megalotis</td><td>ISEM-V-2620</td><td>HF947304</td><td>Botero-Castro et al. 2013</td></tr><tr><td>Phyllostomidae</td><td>Micronycterinae</td><td>Micronycteris megalotis</td><td>QCAZ18280</td><td>ON357728</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Phyllostominae</td><td>Chrotopterus auritus</td><td>AMNH-M-272843</td><td>KU743905</td><td>Botero-Castro et al. 2018</td></tr><tr><td>Phyllostomidae</td><td>Phyllostominae</td><td>Lophostoma brasiliense</td><td>QCAZ18085</td><td>ON310506</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Phyllostominae</td><td>Lophostoma silvicola</td><td>MNHN2004-352</td><td>NC_022424</td><td>Botero-Castro et al. 2013</td></tr><tr><td>Phyllostomidae</td><td>Phyllostominae</td><td>Phyllostomus discolor</td><td>QCAZ18297</td><td>ON357733</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Phyllostominae</td><td>Tonatia maresi</td><td>MNHN2004-376</td><td>NC_022428</td><td>Botero-Castro et al. 2013</td></tr><tr><td>Phyllostomidae</td><td>Phyllostominae</td><td>Vampyrum spectrum</td><td>EBRG-L-1896</td><td>NC_022429</td><td>Botero-Castro et al. 2013</td></tr><tr><td>Phyllostomidae</td><td>Rhinophyllinae</td><td>Rhinophylla pumilio</td><td>ISEM-V-1992</td><td>NC_022426</td><td>Botero-Castro et al. 2013</td></tr><tr><td>Phyllostomidae</td><td>Stenodermatinae</td><td>Artibeus aequatorialis</td><td>QCAZ18246</td><td>ON357726</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Stenodermatinae</td><td>Artibeus jamaincensis</td><td>–</td><td>NC_002009</td><td>Pumo et al. 1998</td></tr><tr><td>Phyllostomidae</td><td>Stenodermatinae</td><td>Artibeus literatus</td><td>QCAZ18245</td><td>ON357725</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Stenodermatinae</td><td>Artibeus lituratus</td><td>–</td><td>NC_016871</td><td>Meganathan et al. 2012</td></tr><tr><td>Phyllostomidae</td><td>Stenodermatinae</td><td>Artibeus ravus</td><td>QCAZ18228</td><td>ON321891</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Stenodermatinae</td><td>Chiroderma salvini</td><td>QCAZ18227</td><td>ON321890</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Stenodermatinae</td><td>Enchisthenes hartii</td><td>QCAZ18229</td><td>ON321892</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Stenodermatinae</td><td>Platyrrhinus matapalensis</td><td>QCAZ18238</td><td>ON357723</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Stenodermatinae</td><td>Platyrrhinus nigellus</td><td>QCAZ18299</td><td>ON357734</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Stenodermatinae</td><td>Sturnira bakeri</td><td>QCAZ18306</td><td>ON357735</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Stenodermatinae</td><td>Sturnira ludovici</td><td>QCAZ18312</td><td>ON357738</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Stenodermatinae</td><td>Sturnira luisi</td><td>QCAZ18241</td><td>ON357724</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Stenodermatinae</td><td>Sturnira bakeri</td><td>QCAZ18307</td><td>ON357736</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Stenodermatinae</td><td>Sturnira bakeri</td><td>QCAZ18308</td><td>ON357737</td><td>This study</td></tr><tr><td>Phyllostomidae</td><td>Stenodermatinae</td><td>Sturnira tildae</td><td>ISEM-V-2412</td><td>NC_022427</td><td>Botero-Castro et al. 2013</td></tr><tr><td>Pteropodidae</td><td>–</td><td>Pteropus dasymallus</td><td>–</td><td>NC_002612</td><td>Nikaido et al. 2000</td></tr><tr><td>Pteropodidae</td><td>–</td><td>Pteropus scapulatus</td><td>–</td><td>NC_002619</td><td>Lin & Penny, 2001</td></tr><tr><td>Pteropodidae</td><td>–</td><td>Rosetus aegyptiacus</td><td>–</td><td>NC_007393</td><td>Unpublished</td></tr><tr><td>Rhinolophidae</td><td>Rhinolophinae</td><td>Rhinolophus ferrumequinum</td><td>–</td><td>NC_016191</td><td>Yoon et al. 2011</td></tr><tr><td>Rhinolophidae</td><td>Rhinolophinae</td><td>Rhinolophus formosae</td><td>–</td><td>NC_011304</td><td>Unpublished</td></tr></table>
<table><tbody><tr><td>Rhinolophidae</td><td>Rhinolophinae</td><td>Rhinolophus luctus</td><td>–</td><td>NC_018539</td><td>Xu et al. 2012</td></tr><tr><td>Rhinolophidae</td><td>Rhinolophinae</td><td>Rhinolophus monoceros</td><td>–</td><td>NC_005433</td><td>Lin et al. 2002</td></tr><tr><td>Rhinolophidae</td><td>Rhinolophinae</td><td>Rhinolophus pumilus</td><td>–</td><td>NC_005434</td><td>Nikaido et al. 2001</td></tr><tr><td>Vespertilionidae</td><td>Vespertilioninae</td><td>Lasiurus borealis</td><td>LSUMZ (field number CSM 020)</td><td>NC_016873</td><td>Meganathan et al. 2012</td></tr><tr><td>Vespertilionidae</td><td>Vespertilioninae</td><td>Myotis albescens</td><td>QCAZ18292</td><td>ON357731</td><td>This study</td></tr><tr><td>Vespertilionidae</td><td>Vespertilioninae</td><td>Myotis formosus</td><td>–</td><td>NC_015828</td><td>Kim et al. 2011</td></tr><tr><td>Vespertilionidae</td><td>Vespertilioninae</td><td>Myotis riparius</td><td>QCAZ18293</td><td>ON357732</td><td>This study</td></tr><tr><td>Vespertilionidae</td><td>Vespertilioninae</td><td>Myotis riparius</td><td>QCAZ18288</td><td>ON357730</td><td>This study</td></tr><tr><td>Vespertilionidae</td><td>Vespertilioninae</td><td>Pipistrellus abramus</td><td>–</td><td>NC_005436</td><td>Nikaido et al. 2001</td></tr><tr><td>Vespertilionidae</td><td>Vespertilioninae</td><td>Plecotus auritus</td><td>–</td><td>NC_015484</td><td>Unpublished</td></tr><tr><td>Vespertilionidae</td><td>Vespertilioninae</td><td>Plecotus rafinesquii</td><td>LSUMZ (field number M8121)</td><td>NC_016872</td><td>Meganathan et al. 2012</td></tr><tr><td>Vespertilionidae</td><td>–</td><td>Chalinolobus tuberculatus</td><td>–</td><td>NC_002626</td><td>Lin & Penny, 2001</td></tr><tr><td colspan="6"><strong>Other mammals</strong></td></tr><tr><td>Bovidae</td><td>–</td><td>Bos taurus</td><td>–</td><td>NC_006853</td><td>Unpublished</td></tr><tr><td>Canidae</td><td>–</td><td>Canis lupus</td><td>–</td><td>NC_002008</td><td>Kim et al. 1998</td></tr></tbody></table>

<footnote>a Key to institutional abbreviations: **AMNH** – American Museum of Natural History, New York, USA; **EBRG** – Museum "Estación Biológica de Rancho Grande", Aragua, Venezuela; **ISEM** – University of Montpellier, Montpellier, France; **LSUMZ** – Louisiana State University Museum of Natural Science, Baton Rouge, USA; **MHNG** – Natural History Museum of Geneva, Geneva, Switzerland; **MNHN** – Museum National d'Histoire Naturelle, Paris, France; **MSB** – Museum of Southwestern Biology, Albuquerque, USA; **MVZ** – Museum of Vertebrate Zoology at the University of California, Berkeley, USA; **QCAZ** – Zoology Museum, Pontifical Catholic University of Ecuador, Quito, Ecuador; **ROM** – Royal Ontario Museum, Toronto, Canada.</footnote>
<table><caption>**Table 2.** Nucleotide data set used in this study. "Full outgroup dataset" corresponds to the complete sample of 71 sequences, "Reduced outgroup dataset" corresponds to a sub-sample made up of 48 sequences. The partition schemes are described and the Akaike Information Criterion values are compared. The asterisks (*) denote the best-evaluated partition schemes by this criterion.</caption><thead><tr><th></th><th>Bioinformatics software</th><th>Partition scheme</th><th>Number of partitions</th><th>Number of Parameters</th><th>-lnL</th><th>AIC</th></tr></thead><tbody><tr><td rowspan="6">Full outgroup dataset</td><td>RAxML-NG</td><td>A single partition</td><td>1</td><td>149</td><td>-334,497.3</td><td>669,292.6</td></tr><tr><td>RAxML-NG</td><td>rRNA + tRNA + protein-coding genes</td><td>14</td><td>292</td><td>-326,799.5</td><td>653,985.1</td></tr><tr><td>RAxML-NG</td><td>rRNA + tRNA + codon positions</td><td>5</td><td>193</td><td>-332,165.0</td><td>664,914.0</td></tr><tr><td>RAxML-NG</td><td>rRNA + tRNA + protein-coding genes + codon positions</td><td>38</td><td>556</td><td>-324,889.2</td><td>650,890.4*</td></tr><tr><td>PartitionFinder RAxML-NG</td><td>Partition by gene</td><td>31</td><td>436</td><td>-330,755.8</td><td>662,383.7</td></tr><tr><td>IQTREE2</td><td>Partition by gene</td><td>19</td><td>148</td><td>-339,430.8</td><td>679,157.6</td></tr><tr><td rowspan="6">Reduced outgroup dataset</td><td>RAxML-NG</td><td>A single partition</td><td>1</td><td>103</td><td>-219,193.7</td><td>438,593.4</td></tr><tr><td>RAxML-NG</td><td>rRNA + tRNA + protein-coding genes</td><td>14</td><td>246</td><td>-217,376.1</td><td>435,244.2</td></tr><tr><td>RAxML-NG</td><td>rRNA + tRNA + codon positions</td><td>5</td><td>147</td><td>-212,155.9</td><td>424,605.8</td></tr><tr><td>RAxML-NG</td><td>rRNA + tRNA + protein-coding genes + codon positions</td><td>38</td><td>510</td><td>-210,734.2</td><td>422,488.4*</td></tr><tr><td>PartitionFinder RAxML-NG</td><td>Partition by gene</td><td>28</td><td>358</td><td>-213,561.8</td><td>427,839.7</td></tr><tr><td>IQTREE2</td><td>Partition by gene</td><td>16</td><td>254</td><td>-211,257.2</td><td>423,022.5</td></tr></tbody></table>
<table><caption>**Table 3.** Amino acids data set used in this study. "Full outgroup dataset" corresponds to the complete sample of 71 sequences, "Reduced outgroup dataset" corresponds to a sub-sample made up of 48 sequences. The partition schemes are described and the Akaike Information Criterion values are compared. The asterisks (*) denote the best-evaluated partition schemes by this criterion.</caption><thead><tr><th></th><th>Bioinformatic software</th><th>Partition scheme</th><th>Number of partitions</th><th>Number of Parameters</th><th>-lnL</th><th>AIC</th></tr></thead><tbody><tr><td rowspan="4">Full outgroup dataset</td><td>RAxML-NG</td><td>A single partition</td><td>1</td><td>141</td><td>-75,293.4</td><td>150,868.7</td></tr><tr><td>RAxML-NG</td><td>Protein-coding genes</td><td>12</td><td>231</td><td>-70,132.27</td><td>140,726.5</td></tr><tr><td>PartitionFinder RAxML-NG</td><td>Partition by gene</td><td>7</td><td>178</td><td>-70,134.5</td><td>140,625.1*</td></tr><tr><td>IQTREE2</td><td>Partition by gene</td><td>4</td><td>159</td><td>-73617.015</td><td>147,552.03</td></tr><tr><td rowspan="4">Reduced outgroup dataset</td><td>RAxML-NG</td><td>Partition by gene</td><td>1</td><td>95</td><td>-50,664.04</td><td>101,518.09</td></tr><tr><td>RAxML-NG</td><td>Protein-coding genes</td><td>12</td><td>185</td><td>-46,991.45</td><td>94,352.90</td></tr><tr><td>PartitionFinder RAxML-NG</td><td>Partition by gene</td><td>6</td><td>147</td><td>-46,976.63</td><td>94,247.27*</td></tr><tr><td>IQTREE2</td><td>Partition by gene</td><td>4</td><td>113</td><td>-49,380.65</td><td>98,987.31</td></tr></tbody></table>
<table><caption>**Table 4.** General features of the 32 new bat mitogenome assemblies.</caption><thead><tr><th>QCAZ</th><th>Species</th><th>Total reads<sup>a</sup></th><th>Mean Coverage</th><th>mtDNA Reads</th><th>mtDNA Reads (%)</th><th>Mitogenome Length</th><th>G+C Content (%)<sup>b</sup></th></tr></thead><tbody><tr><td>18085</td><td>Lophostoma brasiliense</td><td>5,020,095</td><td>5,931</td><td>630,938</td><td>12.57</td><td>16,653</td><td>40.7</td></tr><tr><td>18217</td><td>Anoura cultrata</td><td>5,196,044</td><td>4,675</td><td>491,888</td><td>9.47</td><td>16,552</td><td>38.67</td></tr><tr><td>18218</td><td>Anoura geofroyi</td><td>5,387,000</td><td>4,910</td><td>513,801</td><td>9.54</td><td>16,605</td><td>39.87</td></tr><tr><td>18219</td><td>Carollia castanea</td><td>6,010,339</td><td>6,504</td><td>733,256</td><td>12.2</td><td>16,711</td><td>41.45</td></tr><tr><td>18221</td><td>Carollia brevicauda</td><td>714,6821</td><td>7,043</td><td>784,051</td><td>10.97</td><td>16,711</td><td>41.45</td></tr><tr><td>18226</td><td>Carollia brevicauda</td><td>7,153,480</td><td>6,414</td><td>770,227</td><td>10.77</td><td>16,711</td><td>41.45</td></tr><tr><td>18227</td><td>Chiroderma salvini</td><td>5,376,798</td><td>11,000</td><td>1,129,92</td><td>21.01</td><td>16,689</td><td>41.36</td></tr><tr><td>18228</td><td>Artibeus ravus</td><td>5,546,264</td><td>5,943</td><td>634,436</td><td>11.44</td><td>16,709</td><td>37.84</td></tr><tr><td>18229</td><td>Enchisthenes hartii</td><td>5,082,139</td><td>6,758</td><td>703,230</td><td>13.84</td><td>16,718</td><td>38.22</td></tr><tr><td>18230</td><td>Glossophaga soricina</td><td>5,389,214</td><td>3,055</td><td>347,814</td><td>6.45</td><td>16,529</td><td>37.35</td></tr><tr><td>18233</td><td>Choeroniscus minor</td><td>6,611,734</td><td>217</td><td>24,935</td><td>0.38</td><td>16,637</td><td>37.59</td></tr><tr><td>18236</td><td>Lonchophylla robusta</td><td>5,501,494</td><td>6,901</td><td>720,793</td><td>13.1</td><td>16,666</td><td>43.68</td></tr><tr><td>18237</td><td>Micronycteris hirsuta</td><td>5,244,058</td><td>10,723</td><td>1,109,69</td><td>21.16</td><td>16,589</td><td>42.85</td></tr><tr><td>18238</td><td>Platyrrhinus matapalensis</td><td>5,362,494</td><td>6,572</td><td>664,783</td><td>12.4</td><td>16,541</td><td>40.68</td></tr><tr><td>18241</td><td>Sturnira bakeri</td><td>5,818,828</td><td>6,939</td><td>787,240</td><td>13.53</td><td>16,637</td><td>43.27</td></tr><tr><td>18245</td><td>Artibeus literatus</td><td>4,412,371</td><td>943</td><td>104,092</td><td>2.36</td><td>16,709</td><td>37.84</td></tr><tr><td>18246</td><td>Artibeus aequatorialis</td><td>5,470,809</td><td>3,540</td><td>368,764</td><td>6.74</td><td>16,709</td><td>37.84</td></tr><tr><td>18273</td><td>Lonchophylla concava</td><td>4,421,729</td><td>2,306</td><td>232,980</td><td>5.27</td><td>16,691</td><td>39.65</td></tr><tr><td>18274</td><td>Lonchophylla concava</td><td>3,878,886</td><td>780</td><td>81,974</td><td>2.11</td><td>16,692</td><td>39.97</td></tr><tr><td>18280</td><td>Micronycteris megalotis</td><td>5,125,473</td><td>7,611</td><td>790,574</td><td>15.42</td><td>16,589</td><td>42.79</td></tr><tr><td>18284</td><td>Molossus molossus</td><td>4,834,631</td><td>3,731</td><td>385,460</td><td>7.97</td><td>16,612</td><td>36.26</td></tr><tr><td>18287</td><td>Molossus molossus</td><td>5,164,704</td><td>6,877</td><td>713,304</td><td>13.81</td><td>16,615</td><td>36.54</td></tr><tr><td>18288</td><td>Myotis riparius</td><td>5,610,421</td><td>8,940</td><td>994,147</td><td>17.72</td><td>17,052</td><td>35.57</td></tr><tr><td>18292</td><td>Myotis albescens</td><td>4,967,853</td><td>3,058</td><td>326,789</td><td>6.58</td><td>17,128</td><td>35.58</td></tr><tr><td>18293</td><td>Myotis riparius</td><td>4,441,706</td><td>2,722</td><td>318,278</td><td>7.17</td><td>17,186</td><td>35.81</td></tr><tr><td>18297</td><td>Phyllostomus discolor</td><td>4,216,226</td><td>3,482</td><td>359,346</td><td>8.52</td><td>16,692</td><td>41.74</td></tr><tr><td>18299</td><td>Platyrrhinus nigellus</td><td>5,369,804</td><td>5,302</td><td>553,748</td><td>10.31</td><td>16,541</td><td>40.68</td></tr><tr><td>18306</td><td>Sturnira bakeri</td><td>5,518,196</td><td>8,591</td><td>914,490</td><td>16.57</td><td>16,637</td><td>43.27</td></tr><tr><td>18307</td><td>Sturnira bakeri</td><td>5,365,597</td><td>9,504</td><td>995,712</td><td>18.56</td><td>16,637</td><td>43.27</td></tr><tr><td>18308</td><td>Sturnira bakeri</td><td>5,973,325</td><td>9,823</td><td>1,040,51</td><td>17.42</td><td>16,637</td><td>43.27</td></tr><tr><td>18312</td><td>Sturnira ludovici</td><td>4,528,183</td><td>8,222</td><td>864,316</td><td>19.09</td><td>16,646</td><td>43.61</td></tr><tr><td>18371</td><td>Desmodus rotundus</td><td>6,115,261</td><td>12,311</td><td>1,389,88</td><td>22.73</td><td>16,668</td><td>47.68</td></tr></tbody></table>

<footnote>a trim / merge / duplicate</footnote>

<footnote>b Approximate values on draft genomes</footnote>
<table><caption>**Table S1.** Taxonomic and collection data from Ecuadorian specimens analyzed in this study and whose mitogenome sequences were generated (see Table 1 for GenBank accession numbers). Altitude in meters above the sea level. Weight in grams, standard external measures in mm. GPS coordinates in decimal degrees.</caption><thead><tr><th>Museum number</th><th>Field number</th><th>Genus</th><th>Species</th><th>Sex</th><th>Age</th><th>Province</th><th>Precise locality</th><th>Longitude</th><th>Latitude</th><th>Altitude</th><th>Weight</th><th>Forearm</th><th>Head-body length</th><th>Tail length</th><th>Ear length</th><th>Hind foot length</th></tr></thead><tbody><tr><td>QCAZ18085</td><td>NK298731</td><td>Lophostoma</td><td>brasiliense</td><td>F</td><td>Adult</td><td>Santo Domingo de los Tsáchilas</td><td>La Lorena</td><td>-79.139733</td><td>-0.2747998</td><td>577</td><td>8</td><td>34</td><td>53.7</td><td>8</td><td>20.2</td><td>8.6</td></tr><tr><td>QCAZ18217</td><td>QKM54786</td><td>Anoura</td><td>cultrata</td><td>F</td><td>Adult</td><td>Cotopaxi</td><td>San Cristóbal</td><td>-79.1532668</td><td>-0.8607</td><td>517</td><td>18.5</td><td>41.9</td><td>53.7</td><td>-</td><td>10.8</td><td>10.3</td></tr><tr><td>QCAZ18218</td><td>QKM54793</td><td>Anoura</td><td>geoffroyi</td><td>M</td><td>Adult</td><td>Cotopaxi</td><td>Jardín de los sueños</td><td>-79.2045668</td><td>-0.8372</td><td>621</td><td>13</td><td>41.7</td><td>68.8</td><td>-</td><td>17.3</td><td>11.4</td></tr><tr><td>QCAZ18219</td><td>QKM54798</td><td>Carollia</td><td>castanea</td><td>M</td><td>Adult</td><td>Cotopaxi</td><td>San Cristóbal</td><td>-79.1532668</td><td>-0.8607</td><td>460</td><td>10.5</td><td>34.4</td><td>47.5</td><td>12</td><td>16.5</td><td>11</td></tr><tr><td>QCAZ18221</td><td>QKM54776</td><td>Carollia</td><td>brevicauda</td><td>M</td><td>Adult</td><td>Cotopaxi</td><td>Jardín de los sueños</td><td>-79.2045668</td><td>-0.8372</td><td>400</td><td>14.5</td><td>39.2</td><td>47.3</td><td>10.2</td><td>17.2</td><td>10.7</td></tr><tr><td>QCAZ18226</td><td>QKM54797</td><td>Carollia</td><td>brevicauda</td><td>F</td><td>Adult</td><td>Cotopaxi</td><td>San Cristóbal</td><td>-79.1532668</td><td>-0.8607</td><td>462</td><td>14</td><td>41.6</td><td>62</td><td>10.2</td><td>9</td><td>12</td></tr><tr><td>QCAZ18227</td><td>QKM54794</td><td>Chiroderma</td><td>salvini</td><td>F</td><td>Adult</td><td>Cotopaxi</td><td>Jardín de los sueños</td><td>-79.2045668</td><td>-0.8372</td><td>621</td><td>27</td><td>49.5</td><td>65.5</td><td>-</td><td>14.8</td><td>12.8</td></tr><tr><td>QCAZ18228</td><td>QKM54800</td><td>Artibeus</td><td>javus</td><td>M</td><td>Subadult</td><td>Cotopaxi</td><td>Manguilita El Triunfo</td><td>-79.20735</td><td>-0.9117498</td><td>312</td><td>10.5</td><td>38.5</td><td>45.9</td><td>-</td><td>15.7</td><td>11</td></tr><tr><td>QCAZ18229</td><td>QKM54795</td><td>Enchisthenes</td><td>hartii</td><td>F</td><td>Adult</td><td>Cotopaxi</td><td>Jardín de los sueños</td><td>-79.2045668</td><td>-0.8372</td><td>573</td><td>18</td><td>40.5</td><td>51.3</td><td>-</td><td>15.4</td><td>9.3</td></tr><tr><td>QCAZ18230</td><td>QKM54777</td><td>Glossophaga</td><td>soricina</td><td>F</td><td>Adult</td><td>Cotopaxi</td><td>Jardín de los sueños</td><td>-79.2045668</td><td>-0.8372</td><td>395</td><td>9</td><td>35</td><td>44</td><td>5.4</td><td>13.1</td><td>9</td></tr><tr><td>QCAZ18233</td><td>QKM54807</td><td>Choeroniscus</td><td>minor</td><td>F</td><td>Adult</td><td>Cotopaxi</td><td>Jardín de los sueños</td><td>-79.2045668</td><td>-0.8372</td><td>495</td><td>8</td><td>35.1</td><td>41.4</td><td>5.5</td><td>10.5</td><td>9.3</td></tr></tbody></table>
<table><tr><td>QCAZ18236</td><td>QKM54804</td><td>Lonchophylla robusta</td><td>M</td><td>Adult</td><td>Cotopaxi</td><td>Manguilita El Triunfo</td><td>-79.20735</td><td>-0.9117498</td><td>285</td><td>15</td><td>43.7</td><td>52.5</td><td>12.8</td><td>17</td><td>13.7</td></tr><tr><td>QCAZ18237</td><td>QKM54805</td><td>Micronycteris hirsuta</td><td>F</td><td>Adult</td><td>Cotopaxi</td><td>Jardín de los sueños</td><td>-79.2045668</td><td>-0.8372</td><td>473</td><td>13.5</td><td>43.2</td><td>51</td><td>13.2</td><td>22.7</td><td>12.9</td></tr><tr><td>QCAZ18238</td><td>QKM54801</td><td>Platyrrhinus matapalensis</td><td>M</td><td>Adult</td><td>Cotopaxi</td><td>Manguilita El Triunfo</td><td>-79.20735</td><td>-0.9117498</td><td>285</td><td>14</td><td>32.9</td><td>52.3</td><td>-</td><td>17</td><td>11.7</td></tr><tr><td>QCAZ18241</td><td>QKM54792</td><td>Sturnira luisi</td><td>M</td><td>Adult</td><td>Cotopaxi</td><td>Guasaganda</td><td>-79.1468667</td><td>-0.7798167</td><td>481</td><td>21.5</td><td>41.8</td><td>56.6</td><td>-</td><td>15.9</td><td>10.8</td></tr><tr><td>QCAZ18245</td><td>NK298728</td><td>Artibeus literatus</td><td>F</td><td>Adult</td><td>Santo Domingo de los Tsáchilas</td><td>La Lorena</td><td>-79.139733</td><td>-0.2747998</td><td>577</td><td>80</td><td>74.2</td><td>105.5</td><td>-</td><td>20.4</td><td>17.8</td></tr><tr><td>QCAZ18246</td><td>NK298686</td><td>Artibeus aequatorialis</td><td>M</td><td>Adult</td><td>Santo Domingo de los Tsáchilas</td><td>Reserva Otongachi</td><td>-78.9518828</td><td>-0.3212998</td><td>856</td><td>46</td><td>65</td><td>89</td><td>-</td><td>22</td><td>14</td></tr><tr><td>QCAZ18273</td><td>NK298727</td><td>Lonchophylla concava</td><td>F</td><td>Adult</td><td>Santo Domingo de los Tsáchilas</td><td>La Lorena</td><td>-79.139733</td><td>-0.2747998</td><td>577</td><td>6.5</td><td>33.2</td><td>56.9</td><td>9.5</td><td>11.5</td><td>8.2</td></tr><tr><td>QCAZ18274</td><td>NK298732</td><td>Lonchophylla concava</td><td>F</td><td>Adult</td><td>Santo Domingo de los Tsáchilas</td><td>La Lorena</td><td>-79.139733</td><td>-0.2747998</td><td>577</td><td>7</td><td>34</td><td>58.6</td><td>11.3</td><td>14.4</td><td>10.4</td></tr><tr><td>QCAZ18280</td><td>NK298706</td><td>Micronycteris megalotis</td><td>M</td><td>Adult</td><td>Santo Domingo de los Tsáchilas</td><td>La Lorena</td><td>-79.139733</td><td>-0.2747998</td><td>577</td><td>5.5</td><td>36</td><td>49</td><td>12</td><td>20</td><td>10</td></tr><tr><td>QCAZ18284</td><td>NK298713</td><td>Molossus molossus</td><td>M</td><td>Adult</td><td>Santo Domingo de los Tsáchilas</td><td>La Lorena</td><td>-79.139733</td><td>-0.2747998</td><td>577</td><td>17</td><td>39</td><td>65</td><td>44</td><td>14</td><td>11</td></tr><tr><td>QCAZ18287</td><td>NK298712</td><td>Molossus molossus</td><td>F</td><td>Adult</td><td>Santo Domingo de los Tsáchilas</td><td>La Lorena</td><td>-79.139733</td><td>-0.2747998</td><td>577</td><td>22</td><td>42</td><td>69</td><td>44</td><td>15</td><td>12</td></tr><tr><td>QCAZ18288</td><td>NK298683</td><td>Myotis riparius</td><td>M</td><td>Adult</td><td>Santo Domingo de los Tsáchilas</td><td>Reserva Otongachi</td><td>-78.9518828</td><td>-0.3212998</td><td>856</td><td>4.5</td><td>35</td><td>46</td><td>35</td><td>14</td><td>7</td></tr><tr><td>QCAZ18292</td><td>NK298716</td><td>Myotis albescens</td><td>F</td><td>Adult</td><td>Santo Domingo de los Tsáchilas</td><td>Río Mulaute</td><td>-78.993183</td><td>-0.131917</td><td>549</td><td>5</td><td>37</td><td>52</td><td>33</td><td>15</td><td>9</td></tr><tr><td>QCAZ18293</td><td>NK298651</td><td>Myotis riparius</td><td>F</td><td>Adult</td><td>Pichincha</td><td>Alambi</td><td>-78.680733</td><td>-0.030217</td><td>1479</td><td>5</td><td>36</td><td>46</td><td>37</td><td>14</td><td>7</td></tr></table>
<table><tr><td>QCAZ18297</td><td>NK298644</td><td>Phyllostomus</td><td>discolor</td><td>M</td><td>Adult</td><td>Pichincha</td><td>Alambi</td><td>-78.680733</td><td>-0.030217</td><td>1496</td><td>45</td><td>64</td><td>94</td><td>10</td><td>24</td><td>19</td></tr><tr><td>QCAZ18299</td><td>NK298679</td><td>Platyrrhinus</td><td>nigellus</td><td>M</td><td>Adult</td><td>Pichincha</td><td>Alambi</td><td>-78.680733</td><td>-0.030217</td><td>1492</td><td>28.5</td><td>79</td><td>75</td><td>-</td><td>18</td><td>14</td></tr><tr><td>QCAZ18306</td><td>NK298688</td><td>Sturnira</td><td>bakeri</td><td>F</td><td>Adult</td><td>Santo Domingo de los Tsáchilas</td><td>Reserva Otongachi</td><td>-78.9518828</td><td>-0.3212998</td><td>856</td><td>14.5</td><td>42</td><td>61</td><td>-</td><td>16</td><td>13</td></tr><tr><td>QCAZ18307</td><td>NK298689</td><td>Sturnira</td><td>bakeri</td><td>M</td><td>Adult</td><td>Santo Domingo de los Tsáchilas</td><td>Reserva Otongachi</td><td>-78.9518828</td><td>-0.3212998</td><td>856</td><td>22</td><td>43</td><td>66</td><td>-</td><td>18</td><td>12</td></tr><tr><td>QCAZ18308</td><td>NK298692</td><td>Sturnira</td><td>bakeri</td><td>M</td><td>Adult</td><td>Santo Domingo de los Tsáchilas</td><td>Hacienda Tinalandia</td><td>-79.054433</td><td>-0.2979668</td><td>685</td><td>21.5</td><td>44</td><td>64</td><td>-</td><td>17</td><td>12</td></tr><tr><td>QCAZ18312</td><td>NK298640</td><td>Sturnira</td><td>ludovici</td><td>M</td><td>Adult</td><td>Pichincha</td><td>Alambi</td><td>-78.680733</td><td>-0.030217</td><td>1496</td><td>25</td><td>47</td><td>75</td><td>-</td><td>19</td><td>15</td></tr><tr><td>QCAZ18371</td><td>QKM54671</td><td>Desmodus</td><td>rotundus</td><td>F</td><td>Adult</td><td>Manabí</td><td>Las Tunas</td><td>-80.8152861</td><td>-1.6621917</td><td>11</td><td>36</td><td>60.5</td><td>68.8</td><td>-</td><td>20.3</td><td>15.6</td></tr></table>
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<figure><img src="image_3.png" /><figcaption>Figure 1. Geographical distribution of specimens used in this work. Sampling localities: Pichincha: 1) Alambi (Lon: -78.680733, Lat: -0.030217); Santo Domingo de Los Tsáchilas: 2) Río Mulaute (Lon: -78.993183, Lat: -0.131917); 3) La Lorena (Lon: -79.139733, Lat: -0.2747998); 4) Hacienda Tinalandia (Lon: -79.054433, Lat: -0.2979668); 5) Reserva Otongachi (Lon: -78.9518828, Lat: -0.3212998); Cotopaxi: 6) Guasaganda (Lon: -79.1468667, Lat: -0.7798167); 7) Jardín de los Sueños (Lon: -79.2045668, Lat: -0.8372); 8) San Cristóbal (Lon: -79.1532668, Lat: -0.8607); 9) Manguilita El Triunfo (Lon: -79.20735, Lat: -0.9117498); Manabí: 10) Las Tunas (Lon: -80.8152861, Lat: -1.6621917)</figcaption></figure>

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<figure><img src="image_4.png" /><figcaption>Figure 2: Phylogeny of Phyllostomidae based on complete mitochondrial genomes (nucleotide sequences). The tree represents the best Maximum Likelihood phylogeny inferring Phyllostomidae and other chiropteran lineages' relationships. The tree was reconstructed in RAxML under the GTR+GAMMA+I model using the Full outgroup data set (71 taxa, 14,703 nucleotides). Color filled semicircles on the nodes indicate ML bootstrap support (percentage) and Bayesian posterior probabilities (see inserted caption). The absence of a semicircle on the node indicates that it was not recovered by ML or Bayesian inferences. Each Navajo's Rug shows if the specified node was retrieved (black square) or not (white square) in different analyses performed (see inserted caption).</figcaption></figure>

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<figure><img src="image_5.png" /></figure>

Figure S1: Phylogeny of Phyllostomidae based on mitochondrial genomes (amino acid sequences). The tree represents the best Maximum Likelihood phylogeny inferring Phyllostomidae and other chiropteran lineages' relationships. The tree was reconstructed in RAxML under the mtMAM and mtREV +I+G+F models using the Full outgroup data set (71 taxa, 3,606 amino acids). Color filled semicircles on the nodes indicate ML bootstrap support (percentage) and Bayesian posterior probabilities (see inserted caption). The absence of a semicircle on the node indicates that it was not recovered by ML or Bayesian inferences. Each Navajo's Rug shows if the specified node was retrieved (black square) or not (white square) in different analyses performed (see inserted caption).

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<figure><img src="image_6.png" /><figcaption>Figure S2: Phylogeny of Phyllostomidae based on the protein coding genes (CDS) from our full nucleotide data set using a 36-partition scheme. The tree was reconstructed in RAxML under the GTR+GAMMA+I model. Color filled semicircles on the nodes indicate ML bootstrap support (percentage; see inserted caption).</figcaption></figure>

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