Conservation Genetics

Beaumont, M. A.

doi:10.1002/9780470061619.ch30

Cited by 8 publications

(4 citation statements)

References 113 publications

(180 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While this effect has been known from a theoretical point of view (Wakeley 1999;Beaumont 2003bBeaumont , 2004; Nielsen and Beaumont 2009), it had not been quantified for data sets simulated with different levels of gene flow and diversity. We found that the effect was limited when genetic differentiation was low but that it could be observed for values of F ST that are typically reported in the literature (e.g., Gonc xalves et al 2009;Holsinger and Weir 2009;Quéméré et al 2009;Rosel et al 2009).…”

Section: Discussionmentioning

confidence: 99%

The Confounding Effects of Population Structure, Genetic Diversity and the Sampling Scheme on the Detection and Quantification of Population Size Changes

et al. 2010

View full text Add to dashboard Cite

The idea that molecular data should contain information on the recent evolutionary history of populations is rather old. However, much of the work carried out today owes to the work of the statisticians and theoreticians who demonstrated that it was possible to detect departures from equilibrium conditions (e.g., panmictic population/mutation-drift equilibrium) and interpret them in terms of deviations from neutrality or stationarity. During the last 20 years the detection of population size changes has usually been carried out under the assumption that samples were obtained from populations that can be approximated by a Wright-Fisher model (i.e., assuming panmixia, demographic stationarity, etc.). However, natural populations are usually part of spatial networks and are interconnected through gene flow. Here we simulated genetic data at mutation and migration-drift equilibrium under an n-island and a stepping-stone model. The simulated populations were thus stationary and not subject to any population size change. We varied the level of gene flow between populations and the scaled mutation rate. We also used several sampling schemes. We then analyzed the simulated samples using the Bayesian method implemented in MSVAR, the Markov Chain Monte Carlo simulation program, to detect and quantify putative population size changes using microsatellite data. Our results show that all three factors (genetic differentiation/gene flow, genetic diversity, and the sampling scheme) play a role in generating false bottleneck signals. We also suggest an ad hoc method to counter this effect. The confounding effect of population structure and of the sampling scheme has practical implications for many conservation studies. Indeed, if population structure is creating ''spurious'' bottleneck signals, the interpretation of bottleneck signals from genetic data might be less straightforward than it would seem, and several studies may have overestimated or incorrectly detected bottlenecks in endangered species.T HE idea that molecular data should contain information on the recent evolutionary history of populations is not new and traces back to the beginning of the 20th century (e.g., Hirschfeld and Hirschfeld 1919). However, much of the work carried out today owes to the seminal work of the statisticians and theoreticians who demonstrated that it was possible to detect departures from equilibrium conditions (e.g., panmictic population/mutation-drift equilibrium) and interpret them in terms of deviations from neutrality (Watterson 1975;Tajima 1989b) or stationarity (Nei et al. 1975;Tajima 1989a). Following this period most studies have primarily been concerned with the statistical properties of relatively simple models such as the Wright-Fisher (WF) or Moran models (Ewens 2004). During the last 20 years the detection of population size changes (e.g., Tajima 1989b;Slatkin and Hudson 1991;Rogers and Harpending 1992;Cornuet and Luikart 1996;Beaumont 1999;Garza and Williamson 2001;Storz and Beaumont 2002) has usually been carried ou...

show abstract

Section: Discussionmentioning

confidence: 99%

The Confounding Effects of Population Structure, Genetic Diversity and the Sampling Scheme on the Detection and Quantification of Population Size Changes

et al. 2010

View full text Add to dashboard Cite

show abstract

“…In general all models follow the same basic assumptions: the focal population is expected to be in panmixia, discrete generations exist and mutation, selection and migration are negligible compared to genetic drift, thus representing a simplified Wright-Fisher population [ 30 , 31 ]. Short-term N e estimators are based on the variance of allele frequency changes over time and hence provide a harmonic mean of N e for the time elapsed between the two sampling periods (for comprehensive reviews see [ 60 ]).…”

Section: Methodsmentioning

confidence: 99%

Historical sampling reveals dramatic demographic changes in western gorilla populations

et al. 2011

View full text Add to dashboard Cite

BackgroundToday many large mammals live in small, fragmented populations, but it is often unclear whether this subdivision is the result of long-term or recent events. Demographic modeling using genetic data can estimate changes in long-term population sizes while temporal sampling provides a way to compare genetic variation present today with that sampled in the past. In order to better understand the dynamics associated with the divergences of great ape populations, these analytical approaches were applied to western gorillas (Gorilla gorilla) and in particular to the isolated and Critically Endangered Cross River gorilla subspecies (G. g. diehli).ResultsWe used microsatellite genotypes from museum specimens and contemporary samples of Cross River gorillas to infer both the long-term and recent population history. We find that Cross River gorillas diverged from the ancestral western gorilla population ~17,800 years ago (95% HDI: 760, 63,245 years). However, gene flow ceased only ~420 years ago (95% HDI: 200, 16,256 years), followed by a bottleneck beginning ~320 years ago (95% HDI: 200, 2,825 years) that caused a 60-fold decrease in the effective population size of Cross River gorillas. Direct comparison of heterozygosity estimates from museum and contemporary samples suggests a loss of genetic variation over the last 100 years.ConclusionsThe composite history of western gorillas could plausibly be explained by climatic oscillations inducing environmental changes in western equatorial Africa that would have allowed gorilla populations to expand over time but ultimately isolate the Cross River gorillas, which thereafter exhibited a dramatic population size reduction. The recent decrease in the Cross River population is accordingly most likely attributable to increasing anthropogenic pressure over the last several hundred years. Isolation of diverging populations with prolonged concomitant gene flow, but not secondary admixture, appears to be a typical characteristic of the population histories of African great apes, including gorillas, chimpanzees and bonobos.

show abstract

“…Microsatellite markers have been widely used to study individual identification, phylogeographic relationships, and genetic variation, as well as population structuring and genetic differentiation of various wildlife species (Beaumont and Bruford, 1999;Polziehn et al, 2000;Hu et al, 2007;Lee et al, 2011;Park et al, 2011). Although plentiful ecological studies and some phylogenetic research with mitochondrial DNA on raccoon dog have been conducted, there are no previous data on the population structure using microsatellite markers (Kahula and Saeki, 2004).…”

Section: Introductionmentioning

confidence: 99%

Population genetic study of the raccoon dog (<i>Nyctereutes procyonoides</i>) in South Korea using newly developed 12 microsatellite markers

et al. 2013

View full text Add to dashboard Cite

The raccoon dog (Nyctereutes procyonoides) is distributed from southeastern Siberia to northern Vietnam, including Korea and Japan, as well as Europe. In Korea, most of its predators and competitors are extinct, which has resulted in rapid growth of the raccoon dog population. This population increase has raised concerns about its role in the ecosystem and the zoonotic transfer of various contagious diseases, and thus an effective method of raccoon dog population control in Korea is required. To investigate the genetic diversity and structure of raccoon dog populations, 12 polymorphic microsatellite loci were identified and characterized. These novel microsatellite markers were employed to obtain basic population genetic parameters for 104 N. procyonoides specimens from five locations in South Korea. The mean allele number of 12 loci across samples was 8.7, and the number of alleles per locus ranged 2-13. Mean expected and observed heterozygosities were 0.723 and 0.619, respectively. Genetic differentiation, estimated by pairwise F ST , was significant for all population pairs excepting Seoul/Gyeonggi and Gangwon pair, with a moderate level of genetic differentiation for all the population pairs (mean F ST = 0.054), but little differentiation between Seoul/Gyeonggi and Gangwon (F ST = 0.024). Bayesian-based clustering analysis predicted that Korean raccoon dog population is composed of four distinct genetic subpopulations. These genetic information and structure of raccoon dog will be very useful to prevent spreading infectious diseases.

show abstract

Conservation Genetics

Cited by 8 publications

References 113 publications

The Confounding Effects of Population Structure, Genetic Diversity and the Sampling Scheme on the Detection and Quantification of Population Size Changes

The Confounding Effects of Population Structure, Genetic Diversity and the Sampling Scheme on the Detection and Quantification of Population Size Changes

Historical sampling reveals dramatic demographic changes in western gorilla populations

Population genetic study of the raccoon dog (<i>Nyctereutes procyonoides</i>) in South Korea using newly developed 12 microsatellite markers

Contact Info

Product

Resources

About