Unexpected low genetic variation in the South American hystricognath rodent Lagostomus maximus (Rodentia: Chinchillidae)

Authors: María Constanza Gariboldi aff001;  Pablo Ignacio Felipe Inserra aff001;  Sergio Lucero aff002;  Mauricio Failla aff004;  Sergio Iván Perez aff002;  Alfredo Daniel Vitullo aff001
Authors place of work: Centro de Estudios Biomédicos, Biotecnológicos, Ambientales y Diagnóstico, Universidad Maimónides, Ciudad Autónoma de Buenos Aires, Argentina aff001;  Consejo Nacional de Investigaciones Científicas y Técnicas, Ciudad Autónoma de Buenos Aires, Argentina aff002;  División de Mastozoología, Museo Argentino de Ciencias Naturales "Bernardino Rivadavia", Ciudad Autónoma de Buenos Aires, Argentina aff003;  Proyecto Patagonia Noreste, Río Negro, Argentina aff004;  División Antropología, Facultad de Ciencias Naturales y Museo, Universidad Nacional de la Plata, Buenos Aires, Argentina aff005
Published in the journal: PLoS ONE 14(9)
Category: Research Article
doi: 10.1371/journal.pone.0221559


The South American plains vizcacha, Lagostomus maximus inhabits primarily the Pampean and adjoining Espinal, Monte and Chaquenean regions of Argentina. In order to study the population genetic structure of L. maximus, a fragment of 560 bp of the mitochondrial DNA hypervariable region 1from 90 individuals collected from the 3 subspecies and 8 groups along Argentina was amplified and analyzed. We found 9 haplotypes. The haplotype network did not show an apparent phylogeographical signal. Although low levels of genetic variation were found in all the subspecies and groups analyzed, a radiation of L. maximus would have occurred from the North and Center of the Pampean region toward the rest of its geographic range in Argentina. Low levels of genetic diversity, the existence of a single genetically distinct population in Argentina and changes of its effective size indicate that metapopulation processes and changes in human population dynamics during the late-Holocene were important factors shaping the population genetic structure of L. maximus in Argentina.


Biology and life sciences – Evolutionary biology – Genetic polymorphism – Genetics – Population genetics – Phylogeography – Heredity – Genetic mapping – Haplotypes – DNA – Conservation genetics – Population biology – Population metrics – Population size – Biogeography – Biochemistry – Nucleic acids – Forms of DNA – Mitochondrial DNA – Conservation biology – Ecology and environmental sciences – Conservation science – Earth sciences – Geography – People and places – Geographical locations – South America – Argentina


Studying the amount and the pattern of genetic diversity found within and between populations is one of the central aims of population genetics. Furthermore, elucidating the population genetic structure of a species provides ecological and evolutionary information that allows the identification of conservation units. Nevertheless, the population genetic structure of many species is currently poorly understood.

The South American plains vizcacha, Lagostomus maximus, is a hystricognath rodent belonging to the family Chinchillidae. The family also comprises the chinchillas (Chinchilla spp.) and mountain vizcachas (Lagidium spp.). L. maximus inhabits primarily the Pampean and adjoining Espinal, Monte and Chaquenean regions of Argentina, though it is also found in southeastern Bolivia and western Paraguay [1,2].

Based on morphological characteristics, three subspecies are recognized: L. m. petilidens Hollister, 1914, from southern Buenos Aires, La Pampa and Río Negro provinces (Argentina), L. m. maximus Desmarest, 1817, from central Argentina and L. m. immollis Thomas, 1910, from north-central Argentina, Paraguay and Bolivia [1,3].

L. maximus is highly social. One to three adult males, two to four times more females and immatures form a social group living in a communal burrow system called "vizcachera" [3,4]. Individuals from each vizcachera share a common home range, with an average size of 1.3 ha, with little overlap between neighboring vizcacheras [4]. Before breeding, young males disperse from their natal burrow system. While adult males move into and out of social groups, not being present in a social group for more than one breeding season, females and inmatures remain in the same group [4,5]. Moreover, L. maximus is considered an ecosystem engineer, playing important functional roles in grasslands and shrublands. By the construction of burrows and removing the understory vegetation, the species facilitates burrowing owls [6,7]; through grazing, the species changes fire regimen and intensity [8]; furthermore, L. maximus serves as an important resource for larger predators, such as pumas (Puma concolor) [9].

Although many ecological, physiological and anatomical characteristics of L. maximus have been analyzed (e.g. [1,4,1012]), no study has investigated the population genetic structure of the species. Considering that L. maximus presents an extensive distribution in Argentina, that three morphologically distinct subspecies of L. maximus has been recognized along Argentina [1,3], that females are philopatric and that the average size of the home range of the species is 1.3 ha [4,5], we hypothesize that through the definition of putative geographically distant populations the species in Argentina will display a pattern of population genetic structure showing a significant genetic differentiation among the defined putative populations. To test this hypothesis, we employed mitochondrial DNA (mtDNA) sequences and analyzed the population genetic structure of L. maximus in Argentina.

Materials and methods

Sample collection and DNA extraction

Samples from 90 individuals were collected along Argentina (Fig 1). As we collected tissue samples from dead individuals or feces, an Institutional Animal Care and Use Committee or equivalent animal ethics committee was not necessary. Sampling permits were issued by Dirección Provincial de Fiscalización Agropecuaria, Alimentaria y de los Recursos Naturales (Buenos Aires Province) and Secretaría de Ambiente y Desarrollo Sustentable (Río Negro Province).

<h2>Geographical locations of the sampled sites along the distributional range of <i>L</i>. <i>maximus</i> in Argentina.</h2>
Fig. 1.

Geographical locations of the sampled sites along the distributional range of L. maximus in Argentina.

I, II and III correspond to L. m. petilidens, L. m. maximus and L. m. immollis, respectively; A-H corresponds to the defined groups in this study. For each group, the sample size is shown.

Since samples included bones, muscles and feces, genomic DNA was extracted using different methods. Briefly, bone surfaces were cleaned with 6% sodium hypochlorite and molecular grade water. In order to decalcify each bone, ~0.1g of bone powder was sampled and incubated overnight at room temperature with 1.5 mL 0.5M EDTA pH 8. After incubation, samples were centrifuged at 10,000 rpm for 10 min and the supernatant was removed. To extract DNA from the bone pellet, as well as from fresh muscle, standard proteinase K digestion, phenol-chloroform purification and ethanol DNA precipitation procedures were performed [13]. For stool samples, genomic DNA was extracted using a commercial kit (AccuPrep® Stool DNA Extraction Kit, Bioneer).

In order to perform the analyses, we studied a fragment of the mtDNA control region. This region has been extensively used to investigate the population genetic structure of many species due to its easy collection, lack of recombination and fast rates of base substitution; it has proved to be powerful for evolutionary and genealogical studies (e.g. [1418]). Moreover, due to the previous recognition of three morphologically distinct subspecies [1,3], the small home range of L. maximus relative to the extensive analyzed area in this study, the male-based dispersal pattern [4,5], the maternally inheritance of the mtDNA [14,19] and all the above-mentioned characteristics turn the mtDNA control region suitable for studying the population genetic structure of L. maximus. A fragment of 560 bp of the mtDNA hypervariable region 1 (HVR 1) was amplified by polymerase chain reaction (PCR) using species-specific primers designed for this study: LMF 5' CAA ATC CTG TGT ACT TTG TG and LMR 5' ATG CAT GAC ACC ACA GTT AT. Final concentrations used in PCRs of 25 μl were: 5 μg/ml of template DNA, Buffer 1X (Promega), 0.2 mmol/L of dNTPS, 0.2 μmol/L of each primer, 1.5 mmol/L of MgCl2, and 1.25 units of GoTaq polymerase (Promega). PCR cycling profile consisted of an initial denaturation at 94°C for 2 min, followed by thirty-five cycles of denaturation at 94°C for 40 s, anneling at 54°C for 40 s and polymerase extension at 72°C for 40 s, and a final extension at 72°C for 3 min. PCR products were purified with a commercial kit (AccuPrep PCR Purification Kit, Bioneer) and sequenced in both directions using an ABI 337 Automated DNA Prism Sequencer (Applied Biosystems, Inc.).

Data analysis

CLUSTALX 2.0.11 [20] was used to align DNA sequences and to identify polymorphic sites. Haplotypes were verified using DnaSP v5.10.01 [21].

To study patterns of geographical distribution and haplotype relationships we performed a Median-Joining network [22], as implemented in PopART v1.7 [23].

In order to further evaluate our data set, we grouped the samples by subspecies and geographical proximity (Fig 1). Subspecies division was based on previously published information [1,3] and considering geographical points that share the same elevation. Elevation and distance were assessed using a Geographic Information System (GIS) in ArcGIS software.

For each subspecies and defined group, haplotype (h) and nucleotide diversity (π) of the data set were assessed using Arlequin v3.5 [24]. Additionally, the program MDIV [25], that relies on Markov-chain Monte Carlo (MCMC) simulations, was used to estimate the migration rate per gene per generation between putative populations scaled by the effective population size (M = 2Nem). We used the finite sites (HKY) model. Ten independent runs of 2 x 106 iterations each and a burn-in of 5 x 105 iterations were performed. Likelihood values with the highest posterior probability were accepted as the best estimates.

An Analysis of Molecular Variance (AMOVA) was performed to analyze the population genetic structure among the sampling areas using Arlequin v3.5 [24]. Populations pairwise FST and ΦST statistics were computed in Arlequin v3.5 [24]. Significance levels (p = 0.05) were assessed using 8,000 nonparametric random permutations and corrected for multiple comparisons with a modified false discovery rate procedure [26] (p = 0.027 for 3 putative populations; p = 0.013 for 8 putative populations).

The historical demography was studied for each of the populations obtained from the population pairwise analysis (see above). A mismatch distribution analysis [27,28] was performed using Arlequin v3.5 [24]. The Harpending’s raggedness index (r) was used to assess the goodness of fit between the observed and expected mismatch [29]. Furthermore, to model L. maximus demography, and since no substitution rate for the mtDNA control region of the species or a phylogenetically close species has been previously reported, the substitution rate was estimated using BEAST 2.1 [30]. We used the estimated divergence date of Chinchillidae (12.3 million years ago, Mya, 9.3–15.9 Mya) [31]. The HKY model, as indicated by JModelTest [32], a lognormal relaxed clock model, and a Yule speciation model prior was used. The analysis was run for 200 million Markov Chain Monte Carlo (MCMC) steps and the first 10% of runs were discarded as burn-in. Results were checked for convergence to a stationary distribution using Tracer 1.6. Due to the time dependency of molecular evolutionary rates (e.g. [3335]), the estimated substitution rate was corrected and an order faster substitution rate (7.7 x 10−7 substitutions/site/year) was used in this study. A Bayesian skyline plot (BSP) reconstruction was conducted in BEAST 2.1 [30]. Coalescent reconstructions used a strict molecular clock with a substitution rate of 7.7 x 10−7 substitutions/site/year, the HKY model of mutation, as indicated by JModelTest [32], and four grouped intervals. Two independent replicates of 200 million MCMC steps each were run. The first 10% of each run was discarded as burn-in. Results were checked for convergence to a stationary distribution using Tracer 1.6 and combined in LogCombiner 1.6.


From the 560 bp of the HVR 1 analyzed in 90 individuals, 24 variable sites defining 9 haplotypes were found (GenBank accession numbers: MK780072-MK780080).

The phylogenetic analysis based on the Median-Joining network did not reveal a phylogeographic relationship among haplotypes. Haplotype H1 was the most common and widely distributed haplotype, and most other haplotypes connected to it in a star-like topology. However, haplotypes H3 and H4 were separated by 12 and 13 mutational steps, respectively, from their nearest haplotype (Fig 2).

<h2>Median-joining network displaying the mtDNA control region variation of <i>L</i>. <i>maximus</i> in Argentina.</h2>
Fig. 2.

Median-joining network displaying the mtDNA control region variation of L. maximus in Argentina.

Haplotypes are represented with discs and colors that indicate geographical locations. Mutational steps are indicated with stripes. A-H corresponds to the defined groups in this study (see Fig 1).

In general, L. maximus showed a low haplotype and nucleotide diversity (mean 0.200 ± 0.120 and 0.002 ± 0.002, respectively). At the subspecies level, the highest genetic variability was observed in L. m. maximus, while at group level it was observed in group C (Table 1).

Tab. 1.

Genetic diversity indexes for each subspecies and group.

<h2>Genetic diversity indexes for each subspecies and group.</h2>

The AMOVA indicated a non-significant differentiation between the three subspecies (FCT = 0.009, p = 0.255; ΦCT = 0.010, p = 0.256), among groups within each subspecies (FSC = 0.000, p = 0.615; ΦSC = 0.010, p = 0.620) and within groups (FST = 0.000, p = 0.456; ΦST = 0.000, p = 0.460). All pairwise comparisons were no significant (p > 0.300 in all cases) (Table 2).

Tab. 2.

Pairwise genetic differentiation between putative populations for the mtDNA control region.

<h2>Pairwise genetic differentiation between putative populations for the mtDNA control region.</h2>

In accordance with the population structure results, high levels of gene flow were observed between groups and subspecies (Table 3).

Tab. 3.

Estimates of migration rate between groups and subspecies.

<h2>Estimates of migration rate between groups and subspecies.</h2>

Considering a single population, the mismatch distribution tends to show an unimodal L-shaped pattern, suggesting a recent sudden population expansion (Fig 3). Furthermore, the adequacy of the sudden expansion model could not be rejected based on the r (r = 0.42; p = 0.62). The BSP results suggested that the population has kept a stable size until 1,400 years before present (YBP), when a moderately decline in female effective population size began, followed by a population expansion throughout the last 300 years (Fig 3).

<h2>Demographic history based on the mtDNA control region sequences of <i>Lagostomus maximus</i>.</h2>
Fig. 3.

Demographic history based on the mtDNA control region sequences of Lagostomus maximus.

(A) Mismatch distribution. Observed and expected distributions are shown with bars and lines, respectively. (B) Bayesian skyline plot. The black line is the media estimated and the blue lines show the 95% highest posterior density intervals.


Variability and phylogeography

Despite its extensive distribution along Argentina and neighboring countries, L. maximus exhibited a low diversity in the mtDNA (Table 1). Haplotype H1 was the most common and widespread along Argentina, occurring in 74 out of 90 individuals (82.22%), and many other haplotypes connected to it in a star-shaped topology (Fig 2). This pattern suggests that haplotype H1 would be an ancestral one from which the others have derived [36]. Moreover, since ancient demographic events usually allow a greater genetic diversification and given the close relationship between the majority of the haplotypes found along Argentina (Fig 2) [37], a relatively recent expansion event would have occurred. Furthermore, even though the genetic diversity levels found in this study were low, the haplotype and nucleotide diversity levels in L. m. maximus were higher, more specifically in groups C and D (i.e., the North and Center of the Pampean region; Table 1). Therefore, considering that older and expanding populations tend to present a higher genetic diversity [38,39], a radiation of L. maximus would have occurred from this area into the rest of its geographic range in Argentina.

Also, haplotypes H3 and H4 that were found in low frequency were separated from haplotypes H7 and H5 by 12 and 13 mutational steps, respectively (Fig 2). Two plausible explanations could be proposed for the existence of these phylogenetic discontinuities and the apparent lack of geographic separations between these haplotypes and the others found in this study. First, haplotypes H3 and H4 could correspond to nuclear mitochondrial translocations (Numts) (e.g. [40]). However, the use of different tissues, including a mtDNA rich tissue like muscle, and species-specific primers to perform the PCRs, the single band in the electrophoresis gels and the lack of ambiguities in the chromatograms (e.g. [4042]), turns this possibility less likely. Second, the observed pattern could have arisen from introgressive hybridization between the subspecies of L. maximus or genetically divergent populations of the species. In fact, introgressive hybridization has been previously observed during range expansions between genetically divergent subspecies or populations not fully isolated (e.g. [4346]). We have found that haplotype H3 is exclusive from the area where L. maximus maximus is described, whereas haplotype H4 is exclusive from the area where L. maximus inmollis is. Therefore, if genetically divergent subspecies or populations existed in those areas and population contractions and expansions occurred (see below), the observed pattern could have arisen.

Demographic history

During the mid-Holocene (which began 8,000–6,000 years before present, YBP), although some periods and areas of southeastern South America may have presented a humid climate, the climate was characterized by warmer and, primarily, drier conditions than the late-Holocene (that began 3,000–2,000 YBP), and marine transgression-regression that influenced the coastal landscape of several estuaries occurred (e.g. [4750]).

Climate fluctuations during the mid-Holocene apparently had no significant effect on the population size of L. maximus (Fig 3). Since L. maximus occurs in a variety of habitats (from semi-tropical grasslands to desert scrubs) along its range, it would be expected to have the potential to adapt to climate changes. However, this apparent population stability showed in the BSP should be regarded with caution as it could be an artifice of the analysis. Population local contractions and posterior increases can promote the disappearance of some haplotypes lineages, with the subsequent loss of genetic information. In turn, the BSP could display a flat portion preceding a population expansion even though changes in the population effective size of L. maximus occurred [51,52]. In this respect, during the late-Holocene, a slight population size decline, that started approximately 1,500 YBP, can be observed, followed by its increase after 300 YBP (Fig 3). During the late-Holocene, a change in the human occupation, population density and subsistence strategy began in Argentina (e.g. [47,53,54]). Particularly, the archaeological evidence suggests a rapid increase in the human population size after 1,500 YBP and the increment of human territoriality in several regions [16,5356]. As the human population size increased, L. maximus and other small-sized mammals began to be exploited and consumed with more intensity as part of a process of diet expansion or diversification, mainly in the Pampean region [5759]. This process probably caused a higher predation pressure that could have affected the population size of small-size mammal species. Because L. maximus and other small-sized mammals were incorporated as secondary preys at that time, the slightly pronounced population size decline of L. maximus could be directly related with this change in human population dynamics. In the same sense, our demographic results suggest a population size expansion of L. maximus that began approximately 300 YBP (Fig 3). This demographic expansion is directly related to the decrease in indigenous human population during the Hispanic-indigenous contact period and the changes in the subsistence strategies in Pampa and Patagonia linked to the horse adoption [60].

Population structure

Typically, phenotypic, behavior and/or genetic changes are often evident along most species range, as a result to their adaptation to heterogeneous environments [61]. Moreover, the genetic changes may vary across the genome as a result of the existence of loci under selection, and those linked to them, and neutral loci [62]. Furthermore, even though neutral regions of the genome may diverge as a consequence of mutation and genetic drift coupled with reduce levels of gene flow, if adaptive divergence increases, neutral gene flow may decrease and a correlation between differentiation at neutral loci and adaptive phenotypic divergence may appear at neutral loci [61,62]. In this study, although along L. maximus range three subspecies are recognized base on phenotypic changes [1,3], we did not find genetic differences between them (see Results). Factors such as a large population size, high levels of gene flow (but see below) or a recent time since divergence may be preventing us to find genetic differences. When population genetic structure was analyzed considering different groups, we also did not find genetic differences between them (Table 2); furthermore, high levels of gene flow were observed between groups (Table 3). Taking into account the known home range of L. maximus [4] and the extension of the analyzed area, ongoing gene flow between groups is unlikely. However, if local extinction processes existed in this widely distributed species before and after its population size decline during the late-Holocene that was followed by its expansion after the European contact, the genetic diversity and the genetic differentiation between groups of individuals along the range of this species would be low [38,63,64].

Finally, it is worth to note that although deeper evolutionary processes could have reduced mtDNA diversity and biparental markers variation might yet display a pattern of population structure, the mtDNA is maternally inherited (e.g. [14,19]) and L. maximus females are philopatric [4,5]. Therefore, it would be expected that the analysis of the mtDNA ought to be the one to allow us to distinguish genetically distant population along Argentina.

Management and conservation implications

Usually, genetic variation is considered to be critical for the long-term survival of a species. Low levels of genetic variation can affect the ability of a species to respond to stochastic factors (environmental, demographic and genetic stochasticity), as well as to deterministic factors (habitat loss, introduced species and over-exploitation, among others) [65,66]. Additionally, although L. maximus is classified as "Least Concern" by the International Union for Conservation of Nature [67] and the Sociedad Argentina para el Estudio de los Mamíferos [68], its presence from some areas of Argentina has been reduced mainly due to anthropogenic causes (e.g. [6972]). The unexpected low levels of genetic variation in L. maximus in Argentina reported in this study and the anthropogenic pressure to which the species is subjected to in some areas of Argentina should be a matter of concern.

Also, since we found a single genetically distinct population in this study, Argentina can be considered as a single management unit [73]. This provides important information for future reintroduction plans of the species into now-extinct but previously inhabited areas of Argentina. However, in order to assign populations to management units more properly, additional information should be considered, such as life history traits, morphology, habitat and demographic information, as well as genetic data provided by different molecular markers [74,75]. Considering the existence of three morphologically different subspecies, we recommend an averse-to-risk strategy and to consider the three subspecies of L. maximus as different management units. Furthermore, since the optimal definition of management units and the development of effective management and conservation plans need to be made upon reliable demographic data, demographic studies are crucial in order to ensure the long-term survival of L. maximus.


In this study we analyzed for the first time the population genetic structure of L. maximus along most of its geographic range employing mtDNA. Despite the existence of three morphological distinct subspecies and the wide geographic extension analyzed in this study, our results suggest low levels of genetic diversity in all the analyzed subspecies and groups and a single genetically distinct population along Argentina that displayed changes of its effective size during the last 1,500 YBP. Surprisingly, these results were found by analyzing a genetic marker that is inherited by the philopatric sex. This indicates that different factors, such as metapopulation processes and changes in human population dynamics during the late-Holocene, led to the lack of population genetic structure of L. maximus in Argentina. Furthermore, since L. maximus can be considered an ecosystem engineer, our results provide valuable information for future reintroduction plans, especially in degraded areas. Further analyses including highly polymorphic, biparentally inherited microsatellites, as well as ancient DNA from archaeological and paleontological samples, could help to enlarge the results showed herein and improve our knowledge of the population genetic structure at a fine scale and the recent population history of L. maximus.


1. Jackson JE, Branch LC, Villareal D. Lagostomus maximus. Mamm Species. 1996; 543: 1–6.

2. Spotorno AE, Patton JL. Superfamily Chinchilloidea Bennett, 1833. In: Patton JL, Pardiñas UFJ, D'Elia G, editors. Mammals of South America Vol 2: Rodents. Chicago: University of Chicago Press; 2015. pp. 762–783.

3. Llanos AC, Crespo JA. Ecología de la vizcacha (Lagostomus maximus maximus Blainv.) en el nordeste de la Provincia de Entre Ríos. Rev Invest Agr. 1952; 6: 289–378.

4. Branch LC. Intergroup and intragroup spacing in the plains vizcacha (Lagostomus maximus). J Mammal. 1993; 74: 890–900.

5. Branch LC, Villarreal D, Fowler GS. Recruitment, dispersal, and group fusion in a declining population of the plains vizcacha (Lagostomus maximus; Chinchillidae). J Mammal. 1993; 74: 9–20.

6. Branch L, Villarreal D, Machicote M. Conservation challenges of ecosystem engineers: case studies from grasslands and shrublands of North and South America. The Open Country. 2002; 4: 37–48.

7. Machicote M, Branch LC, Villarreal D. Burrowing owls and burrowing mammals: are ecosystem engineers interchangeable as facilitators? OIKOS. 2004; 106: 527–535.

8. Hierro JL, Clark KL, Branch LC, Villarreal D. Native herbivore exerts contrasting effects on fire regime and vegetation structure. Oecologia. 2011; 166: 1121–1129. doi: 10.1007/s00442-011-1954-8 21384177

9. Branch LC, Pessino M, Villarreal D. Response of pumas to a population decline of the plains vizcacha. J Mammal. 1996; 77, 1132–1140.

10. Jensen F, Willis MA, Leopardo NP, Espinosa MB, Vitullo AD. The ovary of the gestating South American plains vizcacha (Lagostomus maximus): suppressed apoptosis and corpora lutea persistence. Biol Reprod. 2008; 79: 240–246. doi: 10.1095/biolreprod.107.065326 18448845

11. Inserra PIF, Leopardo NP, Willis MA, Freysselinard AL, Vitullo AD. Quantification of healthy and atretic germ cells and follicles in the developing and post-natal ovary of the South American plains vizcacha, Lagostomus maximus: evidence of continuous rise of the germinal reserve. Reproduction. 2014; 147: 199–209. doi: 10.1530/REP-13-0455 24231369

12. Fraunhoffer NA, Jensen F, Leopardo N, Inserra PIF, Abuelafia AM, Espinosa MB, et al. Hormonal behavior correlates with follicular recruitment at mid-gestation in the South American plains vizcacha, Lagostomus maximus (Rodentia, Caviomorpha). Gen Comp Endocr. 2017; 250: 162–174. doi: 10.1016/j.ygcen.2017.06.010 28645634

13. Sambrook J, Fritsch EF, Maniatis T. Molecular Cloning: a Laboratory Manual. New York: Cold Spring Harbor Laboratory Press; 1989.

14. Avise JC. Molecular markers. Natural history and evolution. New York: Chapman & Hall; 1994.

15. Pope LC, Sharp A, Moritz C. Population structure of the yellow-footed rock-wallaby Petrogale xanthopus (Gray, 1854) inferred from mtDNA sequences and microsatellite loci. Mol Ecol. 1996; 5: 629–640. 8873466

16. Perez SI, Postillone MB, Rindel D, Gobbo D, Gonzalez PN, Bernal V. Peopling time, spatial occupation and demography of Late Pleistocene–Holocene human population from Patagonia. Quatern Int. 2016; 425: 214–223.

17. Rivera DS, Vianna JA, Ebensperger LA, Palma RE. Phylogeography and demographic history of the Andean degu, Octodontomys gliroides (Rodentia: Octodontidae). Zool J Linn Soc-Lond. 2016; 178: 410–430.

18. Diringer B, Pretell K, Avellan R, Chanta C, Cedeño V, Gentile G. Genetic structure, phylogeography, and demography of Anadara tuberculosa (Bivalvia) from East Pacific as revealed by mtDNA: Implications to conservarion. Ecol Evol. 2019; 9: 4392–4402. doi: 10.1002/ece3.4937 31031914

19. Birky CW Jr, Maruyama T, Fuerst P. An approach to population genetic and evolutionary genetic theory for genes in mitochondrial and chloroplasts, and some results. Genetics. 1983; 103: 513–527. 6840539

20. Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, et al. Clustal W and Clustal X version 2.0. Bioinformatics. 2007; 23: 2947–2948. doi: 10.1093/bioinformatics/btm404 17846036

21. Librado P, Rozas J. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics. 2009; 25: 1451–1452. doi: 10.1093/bioinformatics/btp187 19346325

22. Bandelt HJ, Forster P, Röhl A. Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol. 1999; 16: 37–48. doi: 10.1093/oxfordjournals.molbev.a026036 10331250

23. Leigh JW, Bryant D. PopART: Full-feature software for haplotype network construction. Methods Ecol Evol. 2015; 6:1110–1116.

24. Excoffier L, Lischer HEL. ARLEQUIN suite ver 3.5: A new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour. 2010; 10: 564–567. doi: 10.1111/j.1755-0998.2010.02847.x 21565059

25. Nielsen R, Wakeley JW. Distinguishing migration from isolation: An MCMC approach. Genetics. 2001; 158: 885–896. 11404349

26. Benjamini Y, Yekutieli D. The control of false discovery rate under dependency. Ann Stat. 2001; 29: 1165–1188.

27. Rogers AR, Harpending H. Population growth makes waves in the distribution of pairwise genetic differences. Mol Biol Evol. 1992; 9: 552–569. doi: 10.1093/oxfordjournals.molbev.a040727 1316531

28. Schneider S, Excoffier L. Estimation of the past demographic parameters from the distribution of pairwise differences when the mutation rates vary among sites: application to human mitochondrial DNA. Genetics, 1999; 152: 1079–1089. 10388826

29. Harpending HC. Signature of ancient population growth in a low-resolution mitochondrial DNA mismatch distribution. Hum Biol. 1994; 66: 591–600. 8088750

30. Bouckaert R, Heled J, Kühnert D, Vaughan T, Wu CH, Xie D, et al. BEAST 2: A software platform for Bayesian Evolutionary Analysis. PLOS Comput Biol. 2014; 10: e1003537. doi: 10.1371/journal.pcbi.1003537 24722319

31. Upham NS, Patterson BD. Evolution of caviomorph rodents: a complete phylogeny and timetree for living genera. In: Vasallo AI, Antenucci D, editors. Biology of caviomorph rodents: diversity and evolution. Buenos Aires: SAREM; 2015. pp. 63–120.

32. Posada D. JModelTest Phylogenetic model averaging. Mol Biol Evol. 2008; 25: 1253–1256. doi: 10.1093/molbev/msn083 18397919

33. Ho SYW, Shapiro B, Phillips M, Cooper A, Drummond AJ. Evidence for time dependency of molecular rate estimates. Syst Biol, 2007; 56: 515–522. doi: 10.1080/10635150701435401 17562475

34. Ho SYW, Lanfear R, Bromham L, Phillips MJ, Soubrier J, Rodrigo AG, et al. Time‐dependent rates of molecular evolution. Mol Ecol. 2011; 20: 3087–3101. doi: 10.1111/j.1365-294X.2011.05178.x 21740474

35. Molak M, Ho SYW. Prolonged decay of molecular rate estimates of metazoan mitochondrial DNA. PeerJ 2015; 3: e821. doi: 10.7717/peerj.821 25780773

36. Posada D, Crandall KA. Intraspecific gene genealogies: trees grafting into networks. Trends Ecol Evol. 2001; 16: 37–45. 11146143

37. Avise JC. Phylogeography: The History and Formation of Species. Massachusetts: Harvard University Press; 2000.

38. Grant WS, Bowen BW. Shallow population histories in deep evolutionary lineages of marine fishes: insights from sardines and anchovies and lessons for conservation. J Hered. 1998; 89: 415–426.

39. Ray N, Currat M, Excoffier L. Intra-deme molecular diversity in spatially expanding populations. Mol Biol Evol. 2003; 20: 76–86. doi: 10.1093/molbev/msg009 12519909

40. Triant DA, DeWoody JA. The occurrence, detection, and avoidance of mitochondrial DNA translocations in mammalian systematics and phylogeography. J Mammal. 2007; 88: 908–920.

41. Leite LAR. Mitochondrial pseudogenes in insect DNA barcoding: differing points of view on the same issue. Biota Neotrop. 2012; 12: 301–308.

42. Mao X, Dong J, Hua P, He G, Zhang S, Rossiter SJ. Heteroplasmy and ancient translocation of mitochondrial DNA to the nucleus in the chinese horseshoe bat (Rhinolophus sinicus) complex. PLoS ONE. 2014; 9: e98035. doi: 10.1371/journal.pone.0098035 24842827

43. Mallet J. Hybridization as an invasion of the genome. Trends Ecol Evol. 2005; 20: 229–237. doi: 10.1016/j.tree.2005.02.010 16701374

44. Harrison RG, Larson EL. Hybridization, introgression, and the nature of species boundaries. J Hered; 2014: 795–809. doi: 10.1093/jhered/esu033 25149255

45. Pons JM, Sonsthagen S, Dove C, Crochet PA. Extensive mitochondrial introgression in North American Herring Gull (Larus smithsonianus) with little nuclear DNA impact. Heredity. 2014; 112: 226–239. doi: 10.1038/hdy.2013.98 24105440

46. Mastrantonio V, Porretta D, Urbanelli S, Crasta G, Nascetti G. Dynamics of mtDNA introgression during species range expansion: insights from an experimental longitudinal study. Sci Rep. 2016; 6: 30355. doi: 10.1038/srep30355 27460445

47. Barrientos G, Perez SI. Was there a population replacement during the Late mid-Holocene in the southeastern Pampas of Argentina? Archaeological evidence and paleoecological basis. Quatern Int. 2005; 132: 95–105.

48. Quattrocchio ME, Borromei AM, Deschamps CM, Grill SC, Zavala CA. Landscape evolution and climate changes in the Late Pleistocene-Holocene, southern Pampa (Argentina): Evidence from palynology, mammals and sedimentology. Quatern Int. 2008; 181: 123–138.

49. Prado LF, Wainer J, Chiessi CM, Ledru MP, Turcq B. A mid-Holocene climate reconstruction for eastern South America. Clim Past. 2013; 9: 2117–2133.

50. Patrolongo P, Piovan MJ, Cuadrado DG, Gómez EA. Coastal landscape evolution on the western margin of the Bahía Blanca Estuary (Argentina) mirrors a non-uniform sea-level fall after the mid-Holocene highstand. Geo-Mar Lett. 2017; 37: 373–384.

51. Karl SA, Toonen RJ, Grant WS, Bowen BW. Common misconceptions in molecular ecology: echoes of the modern synthesis. Mol Ecol. 2012; 21: 4171–4189. doi: 10.1111/j.1365-294X.2012.05576.x 22574714

52. Grant WS. Problems and Cautions With Sequence Mismatch Analysis and Bayesian Skyline Plots to Infer Historical Demography. J Hered. 2015; 106: 333–346. doi: 10.1093/jhered/esv020 25926628

53. Martínez G, Flensborg G, Bayala PD. Chronology and human settlement in northeastern Patagonia (Argentina): Patterns of site destruction, intensity of archaeological signal, and population dynamics. Quatern Int. 2013; 301: 123–134.

54. Martínez G, Prates L, Flensborg G, Stoessel L, Alcaráz AP, Bayala P. Radiocarbon trends in the Pampean region (Argentina). Biases and demographic patterns during the final Late Pleistocene and Holocene. Quatern Int. 2015; 356: 89–110.

55. Muscio HJ, Lopez GEJ. Radiocarbon dates and anthropogenic signal in the South-Central Andes (12,500–600 cal. years BP). J Archaeol Sci. 2016; 65: 93–102.

56. Nores R, Fabra M, García A, Demarchi DA. Diversidad genética en restos humanos arqueológicos del sitio El Diquecito (costa sur, Laguna de Mar Chiquita, Provincia de Córdoba). Rev Arg Antrop Biol. 2017; 19: 1–12.

57. Quintana CA, Mazzanti DL. Las vizcachas pampeanas (Lagostomus maximus, Rodentia) en la subsistencia indígena del Holoceno Tardío de las sierras de Tandilia Oriental (Argentina). Lat Am Antiq. 2011; 22: 253–270.

58. Stoessel L, Martínez G. El proceso de intensificación en la transición pampeano-patagónica oriental. Discusión y perspectivas comparativas con regiones aledañas. Comechingonia. 2014; 18: 65–94.

59. Rafuse DJ, Kaufmann CA, Gutiérrez MA, González ME, Scheifler NA, Álvarez MC, et al. Taphonomy of modern communal burrow systems of the Plains vizcacha (Lagostomus maximus, Chinchillidae) in the Pampas region of Argentina: implications for the fossil record. Hist Biol. 2017; 31: 517–534.

60. Mitchell P. Horse Nations: The worldwide impact of the horse on indigenous societies post-1492. Oxford: Oxford University Press; 2015.

61. Schmid M, Guillaume F. The role of phenotypic plasticity on population differentiation. Heredity. 2017; 119: 214–225. doi: 10.1038/hdy.2017.36 28745716

62. Nosil P, Egan SP, Funk DJ. Heterogeneous genomic differentiation between walking-stick ecotypes: “isolation by adaptation” and multiple roles for divergent selection. Evolution. 2008; 62: 316–336. doi: 10.1111/j.1558-5646.2007.00299.x 17999721

63. Pannell JR, Charlesworth B. Effects of metapopulation processes on measures of genetic diversity. Philos T R Soc B. 2000; 355: 1851–64.

64. Tero N, Aspi J, Siikamäki P, Jäkäläniemi A, Tuomi J. Genetic structure and gene flow in a metapopulation of an endangered plant species, Silene tatarica. Mol Ecol. 2003; 12: 2073–2085. 12859630

65. Lande R. Anthropogenic, ecological and genetic factors in extinction and conservation. Res Popul Ecol. 1998; 40: 259–269.

66. Frankham R, Ballou JD, Briscoe DA, editors. Introduction to conservation genetics. Cambridge: Cambridge University Press; 2010.

67. Roach N. Lagostomus maximus; 2016. Database: The IUCN Red List of Threatened Species. Available from: https://www.iucnredlist.org/species/11170/78320596.

68. Ojeda RA, Chillo V, Díaz Isenrath GB. Libro rojo de mamíferos amenazados de la Argentina. Buenos Aires: SAREM; 2012.

69. Muzzachiodi N, Sabattini RA. La mastofauna como indicador de conservación del bosque nativo en un área protegida de Entre Ríos. Revista Científica Agropecuaria. 2002; 6: 5–15.

70. Mérida E, Ahot J. Talares bonaerenses y su conservación. Buenos Aires: Fundación de Historia Natural "Félix de Azara"; 2006.

71. Berduc A, Bierig PL, Donello AV, Walker CH. Lista actualizada y análisis preliminar del uso del hábitat de medianos y grandes mamíferos en un área natural protegida del espinal con invasión de leñosas exóticas, Entre Ríos, Argentina. FABICIB. 2010; 14: 9–27.

72. Barberis IM, Romano M, Montani E, Cordini C, Derlindati EJ. Registro de vizcachas (Lagostomus maximus) en Pampa de las Lagunas, sur de Santa Fe, Argentina. Nótulas Faunísticas. 2015; 182: 1–6.

73. Moritz C. Defining ‘Evolutionarily Significant Units’ for conservation. Trends Ecol Evol. 1994; 9: 373–375. doi: 10.1016/0169-5347(94)90057-4 21236896

74. Crandall KA, Bininda Emonds ORP, Mace GM, Wayne RK. Considering evolutionary processes in conservation biology. Trends Ecol Evol. 2000; 15: 290–295. 10856956

75. Witzenberger KA, Hochkirch A. Ex situ conservation genetics: a review of molecular studies on the genetic consequences of captive breeding programmes for endangered animal species. Biodivers Conserv. 2011; 20: 1843–1861.

Článok vyšiel v časopise


2019 Číslo 9

Najčítanejšie v tomto čísle

Tejto téme sa ďalej venujú…


Zvýšte si kvalifikáciu online z pohodlia domova

Zánětlivá bolest zad a axiální spondylartritida – Diagnostika a referenční strategie
nový kurz
Autori: MUDr. Monika Gregová, Ph.D., MUDr. Kristýna Bubová

Příběh jedlé sody
Autori: MUDr. Ladislav Korábek, CSc., MBA

Mnohočetný myelom: Úvodní léčba netransplantovatelných pacientů

Hypersenzitivita dentinu jako příznak poškození tvrdých zubních tkání
Autori: MUDr. Erika Lenčová, Ph.D.

Všetky kurzy
Zabudnuté heslo

Nemáte účet?  Registrujte sa

Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.


Nemáte účet?  Registrujte sa