Temporal variation in genetic diversity during an outbreak of Oligoryzomys longicaudatus (Rodentia, Sigmodontinae) in a temperate forest of southern Chile
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(2) 384. D. Boric-Bargetto et al. / Biochemical Systematics and Ecology 44 (2012) 383–389. fluctuations regulated by intraspecific competition due to food and space limitations (Murúa et al., 2003). O. longicaudatus responds quickly to increased food availability during the mast seeding of Chusquea bamboo (Murúa et al., 1986; González et al., 1989; Murúa et al., 1996; González et al., 2000; Jaksic and Lima, 2003; Murúa et al., 2003), and displays several characteristics that affect its population dynamics: (1) It has high vagility and large home range (320–4800 m2; Murúa et al., 1986), (2) its diet is mainly granivorous (Meserve, 1981), and (3) its habitat occupation is determined by the abundance of food and shelter (Muñoz-Pedreros et al., 2007). The species shows a broad geographic distribution from 28 to 55 S, occupying forests, shrublands and ecotones and preferring mesic areas (Kelt et al., 1994; Palma et al., 2005; Belmar-Lucero et al., 2009). In southern Chile inhabits temperate forests and is among the most abundant small mammals (Kelt, 2000). In Chile, mouse outbreaks are triggered by two natural phenomena: in north-central of the country they are associated with above-normal rainfall during El Niño Southern Oscillation (ENSO; Meserve and Le Boulengé, 1987; Lima et al., 1999; Meserve et al., 2003; Murúa et al., 2003), whereas in southern Chile mouse outbreaks are associated with the mast seeding of bamboos of the genus Chusquea (Philippi, 1879; Hershkovitz, 1962; Murúa et al., 1986, 1996; Gallardo and Mercado, 1999; González et al., 2000; Jaksic and Lima, 2003). The Chusquea blooming occurs every 12 (Chusquea quila and/or Chusquea valdiviensis) or 14 years (Chusquea culeou) (Jaksic and Lima, 2003). The life cycle of Chusquea bamboos are characterized by flowering during spring of a given year, and mast seed during the summer of the next year (approximately 18 months later), with O. longicaudatus populations irrupting during autumn and winter of that same year (approximately 2 years after the bamboo blooming, or 3–6 months after the seeding) (Murúa et al., 1996; González et al., 2000; Jaksic and Lima, 2003). Chusquea spp. produce large seed crops stimated to be 51.3 million seeds/ha in San Martin Experimental Preserve (39 380 S, 73 030 W) in January 1994 (González and Donoso, 1999), and populations of O. longicaudatus reached their maximum density 3 months after the seeding in April 1994 (González et al., 2000). The microevolutionary consequences of mouse outbreaks have not been studied, except for some life history traits (Murúa et al., 1986; González et al., 1989; Wolf, 1996; Lambin and Yoccoz, 2001; Pearson, 2002; Sage et al., 2007). There are no studies focused on the genetic consequences of O. longicaudatus outbreaks, thus the genetic variability involved in their subsequent population irruptions remains unknown. It’s possible to formulate a hypothesis that a local scale, like our present study in one area of the temperate forest of the Villarrica National Park, southern Chile, the genetic drift will be intensified due to a bottleneck effect at the end of outbreak (breakdown phase), triggering the loss of alleles, as well as a decrease in the genetic variability of post-outbreak populations. To evaluate this hypothesis, we estimated population genetic parameters of the 2001–2002 outbreak of O. longicaudatus. We determined the nucleotide and haplotype variability of O. longicaudatus at localtemporal scale, in association with the last mast seeding event of C. culeou in Villarrica National Park. 2. Material and methods 2.1. Study site The study was conducted at local scale in a one point of the Villarrica National Park (VNP; 39 270 28.4400 S, 71490 33.0600 W), Araucanía region, Chile. Seventy-nine specimens of O. longicaudatus were captured and the trapping was conducted through a web sampling design with three webs using Sherman traps (8 9 23 cm; H. B. Sherman Traps, Inc., Tallahassee, FL). The web sampling was modified from Parmenter et al. (1998) and Abbott et al. (1999), originally designed to study the persistence of Hantavirus in rodent populations (Schmaljohn and Hjelle, 1997; Hart and Bennet, 1999). Each web included 148 Sherman traps per night during 4 nights, and each trap was baited with rolled oats and vanilla. The first four trap stations were at 5 m intervals from the center, and the last eight stations were at 10 m intervals. Total web diameter was 200 m covering an area of 3.14 ha (Parmenter et al., 1998; Abbott et al., 1999). Each web was separated from each other by 500 m approximately, and we conducted 30 trapping events from January 2000 to January 2005 (Fig. 1). The geographic locations of each web were: Web 1 (39 270 28.4400 S, 71490 33.0600 W); Web2 (39 270 35.171400 S, 71490 28.498800 W) and Web3 (39 270 19.918800 S, 71490 11.038200 W). The handling of small mammals followed the guidelines and biosafety procedures of The American Society of Mammalogists and the Center for Disease Control and Prevention, CDC (Mills et al., 1995; Sikes et al., 2011). To report population abundance of O. longicaudatus at local scale in a one point of VNP, we used the Minimum Number Known Alive (MNKA; Krebs, 1966). The mouse outbreak of summer 2001–2002 showed an MNKA peaking at 63 in November 2001 (Fig. 1). Trapping seasons were classified in three major periods: pre-outbreak (all individuals trapped before the population irruption), outbreak (individuals trapped during the irruption phase until the breakdown phase), and postoutbreak (individuals trapped after the breakdown phase; Fig. 1).. 2.2. Molecular analyses DNA was extracted from liver and blood tissues from capture-recaptured and dead individuals, totalizing 79 adult specimens trapped throughout the three outbreak phases. Voucher specimens were stored in the Colección de Flora y Fauna “Profesor Patricio Sánchez Reyes” (SSUC), Departamento de Ecología, Pontificia Universidad Católica de Chile, Santiago, Chile, and in the Museum of Southwestern Biology (MSB), Department of Biology, University of New Mexico, Albuquerque, New.
(3) D. Boric-Bargetto et al. / Biochemical Systematics and Ecology 44 (2012) 383–389. 385. Captures of Oligoryzomys longicaudatus in Villarrica National Park. 70. Outbreak. Pre-Outbreak. 60. Post-Outbreak. 50. 40. 30. 20. jan-05. nov-04. jun-04. sep-04. may-04. jan-04. apr-04. nov-03. jun-03. sep-03. jan-03. mar-03. nov-02. jul-02. sep-02. may-02. jan-02. mar-02. nov-01. jul-01. sep-01. may-01. jan-01. mar-01. nov-00. jul-00. sep-00. may-00. jan-00. 0. mar-00. 10. Fig. 1. Number of individuals (Minimum Number Known Alive - MNKA) of O. longicaudatus during the trapping events between January 2000 to January 2005 at the study site in Villarrica National Park (VNP), southern Chile. The gray zone depicts the outbreak period. The maximum MNKA was during November 2001 (63 individuals).. Mexico. Tissues and other data associated with each specimen were cross-referenced directly to each voucher specimen and stored in the collection using a special field catalog number, the NK number used by the SSUC and MSB. Through the polymerase chain reaction (PCR) we amplified a segment of 500 nucleotides of the mitochondrial DNA (mtDNA) control region (hypervariable subunit I [HVI] and part of the conservative domain) in all 79 individuals. Primers used for PCR were DLO-L (50 CGG AGG CCA ACC AGT AGA 30 ) and DLO-H (50 TAA GGC CAG GAC CAA ACC 30 ) with the following thermal profile (25 cycles): denaturation for 30 s at 94 C, annealing for 25 s at 57 C, and extension for 90 s at 72 C. Doublestranded PCR products were purified with QIAquik (Qiagen). Cycle sequencing (Murray, 1989) was performed using primer DLO-L labeled and with the Big Dye Terminator kit (Perkin Elmer, Norwalk, Connecticut). The sequencing reactions were analyzed on an Applied Biosystems Prism 3100 (Foster City, California) automated sequencer. Sequences were aligned using ClustalW (Thompson et al., 1994) available in the BioEdit v7.0.9 program (Hall, 1999). In pre-outbreak, 27 individuals were sequenced between March 2000 and July 2001 (16 months); in outbreak phase we sequenced 25 specimens between September 2001 and March 2002 (6 months). In post-outbreak other 27 specimens were sequenced between May 2002 and January 2005 (32 months; Fig. 1). All 79 HVI sequences were stored in GenBank and access numbers are shown in Appendix 1. To evaluate if the breakdown phase (Fig. 1) caused a bottleneck that increased the genetic drift effect over post-outbreak populations, we tested whether the pattern of observed polymorphism within populations was consistent with a neutral equilibrium Wright-Fisher model, using the Tajima’s D (Tajima, 1989) and Fu’s Fs (Fu, 1997) neutrality tests. These tests were applied to the complete data set of 79 sequences for each mouse outbreak period. We evaluated for mutation-drift and population equilibrium deviations caused by population expansions or bottlenecks (Aris-Brosou and Excoffier, 1996; Tajima, 1996; Fu, 1997; Ray et al., 2003). These neutrality tests were calculated to distinguish between a DNA sequence evolving neutral, versus one evolving under a non-ramdom proccess such as selection, demographic expansion-contraction or introgession (Tajima, 1989). Significant negative values of Tajima’s D and Fu’s indicate an excess of rare alleles relative to expectations under the standard neutral model. Such a finding may occurr under scenarios of background selection, selective sweeps or population expansions, suggesting populations that have undergone recent demographic expansion or show departures from neutrality (Tajima, 1989). Significant positive values occur if rare alleles are eliminated from populations following genetic bottlenecks or show departures from neutrality (Tajima, 1989).. Table 1 Two-tailed Paired Student’s t test for nucleotide (Pi) and haplotype diversity (Hd). The values in bold are significant (p < 0.001) between periods. We used a Bonferroni correction for p values. Neither Tajima’s D or Fu’s Fs values were significant (p > 0.1). Attributes and tests. Pre outbreak. Outbreak. Post outbreak. Nucleotide diversity (Pi) Haplotype diversity (Hd) Tajima’s D Fu’s Fs. 0.0123 0.952 0.67479 3.829. 0.0153 0.953 0.40174 3.208. 0.011 0.934 0.71253 2.784.
(4) 386. D. Boric-Bargetto et al. / Biochemical Systematics and Ecology 44 (2012) 383–389. Fig. 2. Frequency histogram for 30 haplotypes from 79 sequences (pre ¼ pre-outbreak; out ¼ outbreak; post ¼ post-outbreak) at the study site in southern Chile. Gray bars depict the initial haplotypes of pre-outbreak. Black bars show the new haplotypes of outbreak, and white bars the new haplotypes post-outbreak. The haplotype richness was 16 for pre-outbreak and 14 for outbreak and post-outbreak periods.. 3. Results The Tajima D and Fu’s Fs neutrality tests for the 79 sequences (D ¼ 0.75570; F ¼ 2.85325; p > 0.1) and among temporal phases (pre-outbreak D ¼ 0.67479, F ¼ 3.829, p > 0.1; outbreak D ¼ 0.40174, F ¼ 3.208, p 0.1; post-outbreak D ¼ 0.71253, F ¼ 2.784, p 0.1; Table 1), did not show significant deviation from mutation-drift or demographic equilibrium. Haplotypic diversity (Hd) values were high, whereas those of nucleotide diversity (Pi) were low (Table 1). The genetic variability indexes per period showed a statistically significant decrease (Paired Student’s t test; p < 0.001) of nucleotide diversity (Pi; Appendix 2) and.
(5) D. Boric-Bargetto et al. / Biochemical Systematics and Ecology 44 (2012) 383–389. 387. haplotypic diversity (Hd; Table 1) post-outbreak. The nucleotide diversity was significantly different (p < 0.001) among the three phases, increasing during outbreak and decreasing post-outbreak (Table 1). Haplotype richness was almost constant for the three periods (pre-outbreak ¼ 16, outbreak and post-outbreak ¼ 14; Fig. 2). Of the 16 pre-outbreak haplotypes, 7 remained during the outbreak and 4 persisted into post-outbreak. During outbreak and post-outbreak a constant rate of haplotype replacement was observed, with the addition of 7 new haplotypes during outbreak and post-outbreak (Fig. 2). With respect to outbreak, this resulted in an equal proportion of initial and new haplotypes. During post-outbreak, 4 initial haplotypes remained and 7 new arrived, yielding a higher proportion of new haplotypes. Thus, during outbreak and post-outbreak 50% and 70% of the pre-outbreak haplotypes might have been replaced by new haplotypes, respectively (Fig. 2). 4. Discussion Our results did not show deviations of the mutation-drift and demographic equilibrium, suggesting that the breakdown phase did not cause a bottleneck that had increased the effect of genetic drift over post-outbreak populations. We found high Hd and low Pi during the three periods, although these values were significantly lower during post-outbreak. There was a change of haplotype composition during outbreak and post-outbreak, with a large proportion of replaced pre-outbreak haplotypes. These results support that species with highly variable population sizes, such as O. longicaudatus, may show striking effects on its genetic variability (Wright, 1978). Our data show that the genetic pool of O. longicaudatus maintains several haplotypes with low nucleotide variability (Pi; 0.011 to 0.0153, Appendix 2), suggesting a recent geographical expansion (Grant and Bowen, 1998), proccess that was recently confirmed by Palma et al. (2012) in an extensive population genetic analysis of O. longicaudatus. Further, as concluded by Palma et al. (2005), a high haplotypic and low nucleotide variability suggests that O. longicaudatus has a large gene pool. The increase of Pi during outbreaks may be caused by the arrival of newcomers to the site due to high food availability (Table 1). The haplotype loss may be due to low survival rates and short residence time (Murúa et al., 1986). The lowering of haplotype composition during post-outbreak may be attributable to: (1) a greater effect of genetic drift post-outbreak, and/or (2) a greater effect of immigration during outbreak, and emigration post-outbreak. The decrease in nucleotide and haplotype variability may owe to the higher effect of genetic drift, because of the abrupt decrease in population size post-outbreak (bottleneck). Nevertheless, we did not find evidence of a bias in the neutral evolution of nucleotide sequences (Table 1). It is possible that the reduction in haplotype and nucleotide variability post-outbreak could have occurred due to local extinction of individuals caused by food shortage after bamboo mast seeding, or a massive emigration to nearby areas searching for new food sources at local scale (Hershkovitz, 1962; Gallardo and Mercado, 1999; Pearson, 2002; Jaksic and Lima, 2003; Sage et al., 2007). This hypothesis allows us to emphasize the strong effect of migration or gene flow on the temporal genetic variability of O. longicaudatus at local scale in VNP. The high food availability due to the blooming of C. culeou during the outbreak may have triggered the immigration of mice from nearby populations, bringing new haplotypes from adjacent areas. Complementarily, the low food availability during the post-outbreak may have triggered the emigration of mice to nearby populations, decreasing the haplotypes and nucleotide variability in VNP. These local scale population processes that produce local change on the genetic variability of O. longicaudatus in VNP, probably as part of a population process at regional scale influenced by migration of individuals between subpopulations. Our results suggest that at regional scale gene flow is the main mechanism underlying changes in genetic variability at local scale, that in the study area maintain genetically structured the temperate forest population of O. longicaudatus (Palma et al., 2012). We suggest that at regional scale the high connectivity among subpopulations favors gene flow and leads to constant exchange of haplotype composition at local scale in the VNP, reducing the importance of stochastic proccess at local scale, such as genetic drift. Acknowledgments We thank the comments of Pedro Victoriano and Alvaro Zúñiga on an early version of this manuscript. We also thank the laboratory work of Ricardo Cancino. The funding support of grants FONDECYT 1070331, FONDECYT-FONDAP-CASEB #15010001, NIH-ICIDR 1 U19 AI45452-0 and FONDECYT-11080110 to CEH for the use of the computational platform is also acknowledged. Dusan Boric Bargetto was supported by Escuela de Graduados of the Universidad de Concepción (2008–2010) and a CONICYT Doctoral Fellowship (2011). Finally, we thank the Servicio Agrícola y Ganadero (SAG) and Corporación Nacional Forestal (CONAF) for collecting permits. This study is part of the requirements of the graduate program of the Universidad de Concepción in order to obtain the doctoral degree on Sistemática y Biodiversidad. We thank two anonymous reviewers for their valuable suggestions that greatly improved this work. Appendix Appendix 1. Specimens of O. longicaudatus analyzed by temporal window (Voucher number – GenBank access number) 1. Pre-outbreak (27): NK95044–HM856827; NK95048–EU593133; NK95060–EU593025; NK95070–HM856831; NK95072– HM856832; NK95073–HM856833; NK95083–HM856834; NK95093–HM856835; NK95095–HM856836; NK95097–.
(6) 388. D. Boric-Bargetto et al. / Biochemical Systematics and Ecology 44 (2012) 383–389. EU593032; NK95366–EU593108; NK95367–EU593148; NK95379–EU593014; NK95380–EU593017; NK95388–EU593043; NK95395–EU593119; NK95396–HM856828; NK95399–EU593091; NK95400–HM856829; NK95405–HM856837; NK95411–HM856838; NK95421–EU593029; NK95427–EU593124; NK96401–EU593088; NK96403–EU593143; NK96420– EU593035; NK96421–HM856830. 2. Outbreak (25): NK104737–HM856839; NK104743–HM856840; NK104754–EU593033; NK104758–HM856841; NK104759– EU593127; NK104761–EU593046; NK104763–EU593045; NK104764–EU593036; NK104765–EU593039; NK104766– EU593010; NK104775–EU593120; NK104776–HM856842; NK104779–EU593052; NK104789–HM856843; NK104790– HM856844; NK104794–HM856845; NK104795–EU593116; NK105014–EU593121; NK105015–EU593147; NK105030– EU593007; NK105044–EU593138; NK105137–EU593139; NK105144–EU593135; NK105147–EU593040; NK105148– EU593082. 3. Post-outbreak (27): NK106497–EU593131; NK108827–EU593129; NK109042–HM856848; NK109044–HM856846; NK109059–HM856847; NK109445–HM856849; NK109447–HM856850; NK109459–HM856851; NK109466–HM856852; NK109467–HM856853; NK109470–HM856854; NK120438–HM856855; NK120451–HM856856; NK120463–HM856857; NK120465–HM856870; NK120469–HM856858; NK120470–HM856859; NK120484–HM856860; NK120485–HM856869; NK120486–HM856861; NK120688–HM856862; NK120696–HM856863; NK120706–HM856864; NK120707–HM856865; NK120710–HM856866; NK120715–HM856867; NK120716–HM856868.. Appendix 2 HVI mitochondrial DNA haplotypes consisted of 37 variable sites within a 500 bp region that was sequenced for every adult rice-rat (n [ 79) at the study site Villarrica National Park (VNP) in southern Chile. Nucleotide 9 14 57 58 76 81 83 86 89 97 106 107 109 110 112 113 114 145 146 163 168 171 174 176 212 221 222 229 234 237 243 248 251 288 371 372 460 position (bp) Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap Hap. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30. A T C C C. T. A. T C C. T C C C. A. T. T. C. A. A. C. C. T. C T T T. A. C A A A. C. A. T. A. T. A. C. G. G. T. T. C. T. T. C C. C. T C C C. C. C. C. G. A. A. G. A. C C. C C. C C. C. C T T C T C C. C T. C C C C T. C. C C C C C C C C C C C C C C C C C C C C C C C C. G. T. T. A A A A A A A. T T T T. T T T. T T. T. C C T. A. C C. T T. T. A A. C C T. T. T. A A A A A A A A A A A. T. C. T T T. T T T. T T. C. T T T T T T T T. T. T T. T. T. T. C T. T T. C. A G. A C. C. T C C C. C C C C C C C C. T C T C. A. C C C. G T. A. T C C C C C. G. A C. C C C C C C C. A. G. References Abbott, K.D., Ksiasek, T.G., Mills, J.N., 1999. Long-term hantavirus persistence in rodents populations in central Arizona. Emerg. Infect. Dis. 5 (1), 102–112. Aris-Brosou, S., Excoffier, L., 1996. The impact of population expansion and mutation rate heterogeneity on DNA sequence polymorphism. Mol. Biol. Evol. 13, 494–504. Belmar-Lucero, S., Godoy, P., Ferrés, M., Vial, P., Palma, R.E., 2009. Range expansion of Oligoryzomys longicaudatus (Rodentia, Sigmodontinae) in Patagonian Chile, and first record of hantavirus in the region. Rev. Chil. Hist. Nat. 82, 265–275. Fu, Y.X., 1997. Statistical test of neutrality mutations against population growth, kitchhiking and background selection. Genetics 147, 915–925. Gallardo, M.H., Mercado, C., 1999. Mast seeding of bamboo shrubs and mouse outbreaks in southern Chile. Mastozool. Neotrop. 6, 103–111. González, M.E., Donoso, C., 1999. Producción de semillas y hojarasca en Chusquea quila (Poaceae: Bambusoideae), posterior a su floración sincrónica en la zona centro-sur de Chile. Rev. Chil. Hist. Nat. 72, 169–180. González, L.A., Murúa, R., Jofré, C., 1989. The effect of seed availability on population density of Oligoryzomys longicaudatus in southern Chile. J. Mammal. 70, 401–403. González, L.A., Murúa, R., Jofré, C., 2000. Habitat utilization of two muroid species in relation to population outbreaks in southern temperate forest of Chile. Rev. Chil. Hist. Nat. 73, 489–495. Grant, W.S., Bowen, B.W., 1998. Shallow population histories in deep evolutionary lineages of marine fishes: insights froms sardines and anchovies and lessons for conservation. J. Hered. 89, 415–426..
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