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Journal articles on the topic 'Population genetics'

To see the other types of publications on this topic, follow the link: Population genetics.

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Published: 4 June 2021

Last updated: 29 July 2024

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1

Laporte, Valérie, and Brian Charlesworth. "Effective Population Size and Population Subdivision in Demographically Structured Populations." Genetics 162, no. 1 (September 1, 2002): 501–19. http://dx.doi.org/10.1093/genetics/162.1.501.

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AbstractA fast-timescale approximation is applied to the coalescent process in a single population, which is demographically structured by sex and/or age. This provides a general expression for the probability that a pair of alleles sampled from the population coalesce in the previous time interval. The effective population size is defined as the reciprocal of twice the product of generation time and the coalescence probability. Biologically explicit formulas for effective population size with discrete generations and separate sexes are derived for a variety of different modes of inheritance. The method is also applied to a nuclear gene in a population of partially self-fertilizing hermaphrodites. The effects of population subdivision on a demographically structured population are analyzed, using a matrix of net rates of movement of genes between different local populations. This involves weighting the migration probabilities of individuals of a given age/sex class by the contribution of this class to the leading left eigenvector of the matrix describing the movements of genes between age/sex classes. The effects of sex-specific migration and nonrandom distributions of offspring number on levels of genetic variability and among-population differentiation are described for different modes of inheritance in an island model. Data on DNA sequence variability in human and plant populations are discussed in the light of the results.

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2

Morin-Chassé, Alexandre. "Behavioral Genetics, Population Genetics, and Genetic Essentialism." Science & Education 29, no. 6 (November 4, 2020): 1595–619. http://dx.doi.org/10.1007/s11191-020-00166-y.

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3

Siegel, PB, and EA Dunnington. "Genetic selection strategies–population genetics." Poultry Science 76, no. 8 (August 1997): 1062–65. http://dx.doi.org/10.1093/ps/76.8.1062.

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4

Viney, M. E. "Nematode population genetics." Journal of Helminthology 72, no. 4 (December 1998): 281–83. http://dx.doi.org/10.1017/s0022149x00016606.

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Population genetics seeks to understand the genetic relationships within and between populations of a species and the processes that generate these patterns. Little is known about the population genetics of parasitic nematodes. This is a notable gap in our knowledge since understanding the population genetic patterns and processes of parasitic nematodes has profound implications for our ability to fully understand this important group of pathogens. For example, it is only possible to begin to understand how a parasite population will respond to an imposed selection pressure (such as an anthelmintic drug, a vaccine, or resistant hosts) when the population genetic structure and patterns of gene flow of that population is known. Equally, the epidemiology of many nematode parasites is well known empirically and theoretically, yet this epidemiological information is of limited use without a good understanding of the genetic structure of those populations (Anderson & May, 1992).

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5

Степанов, В. А. "Population Genomics of Russian populations." Nauchno-prakticheskii zhurnal «Medicinskaia genetika», no. 7(216) (July 30, 2020): 6–7. http://dx.doi.org/10.25557/2073-7998.2020.07.6-7.

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Популяционная геномика человека является мощным современным подходом в популяционной генетике, базирующемся на технологиях геномного секвенирования, биоинформатики и анализа больших данных. Геномный анализ генетической вариабельности в популяциях является фундаментальной основой генетики болезней и разработки путей их диагностики, терапии и профилактики. В работе представлены собственные данные о геномном анализе генетического разнообразия населения России. Показано, что генофонд современных народов России формировался на протяжении многих тысяч лет в ходе совокупного влияния миграций, изоляции расстоянием, эффектов основателя и естественного отбора. Сформировавшиеся в ходе микроэволюции геномные паттерны современных популяций в существенной мере определяют композицию генетических факторов как частых хронических, так и редких моногенных заболеваний. Human population genomics is a powerful modern approach in population genetics based on technologies of genomic sequencing, bioinformatics, and big data analysis. Genomic analysis of genetic variability in populations is a fundamental basis for the genetics of diseases and the development of ways for their diagnosis, therapy and prevention. The work presents the own data on the genomic analysis of the genetic diversity of the Russian populations. It is shown that the gene pool of modern populations of Russia was formed over many thousands of years by the combined effects of migrations, isolation by distance, founder effects and natural selection. The genomic patterns of modern populations formed during microevolution substantially determine the composition of genetic factors of both frequent chronic and rare monogenic diseases.

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6

Bedge, Kiran, and Pratima Salunkhe. "Population Genetics : A Review." International Journal of Scientific Research in Science and Technology 11, no. 2 (April 20, 2024): 746–48. http://dx.doi.org/10.32628/ijsrst24112109.

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Genetics is the study of genes and genetic variations alongwith the hereditary characteristics of an organism. Genetics is a central pillar of biology. It overlaps with other areas, such as: Agriculture, Medicine, Biotechnology. Genetics involves studying: Gene structure and function Gene variation and changes How genes affect health, appearance, and personality. Population genetics studies genetic variation within and among populations, based on the Hardy-Weinberg law, which remains constant in large populations with random mating and minimal mutation, selection, and migration.

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7

Nagylaki, T. "The inbreeding effective population number in dioecious populations." Genetics 139, no. 1 (January 1, 1995): 473–85. http://dx.doi.org/10.1093/genetics/139.1.473.

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Abstract The inbreeding effective population number in a dioecious population with discrete, nonoverlapping generations is investigated for both autosomal and X-linked loci. The recursion relations for the probabilities of genic identity, and the effective population numbers are analyzed and compared in two cases: (i) the offspring identified by sex in the calculation of the probability of common parentage and (ii) the offspring not so identified. Case i gives the correct evolution of the probabilities of identity, but case ii has been more widely studied and applied. A general symmetric framework that reduces the number of parameters is developed and used to examine a wide variety of models of panmixia and monogamy. Cases i and ii agree in many, but not all, models.

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8

Nagylaki, T. "The Inbreeding Effective Population Number in Dioecious Populations." Genetics 139, no. 3 (March 1, 1995): 1463d. http://dx.doi.org/10.1093/genetics/139.3.1463c.

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9

Russo, Eugene. "Population Genetics." Nature 413, no. 6855 (October 2001): 4–5. http://dx.doi.org/10.1038/35097203.

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10

Cavalli-Sforza, L. L. "Population genetics." Trends in Genetics 2 (January 1986): 220. http://dx.doi.org/10.1016/0168-9525(86)90234-9.

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11

Lewontin, R. C. "Population Genetics." Annual Review of Genetics 19, no. 1 (December 1985): 81–102. http://dx.doi.org/10.1146/annurev.ge.19.120185.000501.

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12

PROVINE, W. "Population genetics." Bulletin of Mathematical Biology 52, no. 1-2 (1990): 201–7. http://dx.doi.org/10.1016/s0092-8240(05)80009-6.

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13

Brookfield, John. "Population genetics." Current Biology 6, no. 4 (April 1996): 354–56. http://dx.doi.org/10.1016/s0960-9822(02)00493-1.

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14

Maruyama, Takeo, and Paul A. Fuerst. "POPULATION BOTTLENECKS AND NONEQUILIBRIUM MODELS IN POPULATION GENETICS. III. GENIC HOMOZYGOSITY IN POPULATIONS WHICH EXPERIENCE PERIODIC BOTTLENECKS." Genetics 111, no. 3 (November 1, 1985): 691–703. http://dx.doi.org/10.1093/genetics/111.3.691.

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ABSTRACT The amount of variability in a population that experiences repeated restrictions in population size has been calculated. The restrictions in size occur cyclically with a fixed cycle length. Analytical formulas for describing the gene identity at any specific time in the expanded and restricted phases of the cycle, and for the average and second moment of the gene identity, have been derived. It is shown that the level of genetic diversity depends critically on the two parameters that account for the population size, mutation rate and the time of duration for each of the two phases in the cycle. If one or both of these composite parameters are small, the gene diversity will be much reduced, and population gene diversity will then be predictable from knowledge of the harmonic mean population size over the entire cycle. If these parameters take on intermediate values, diversity changes constantly during the cycle, fluctuating steadily from a high to a low value and back again. If these parameters are large, gene diversity will fluctuate rapidly between extreme values and will stay at the extremes for long periods of time.

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15

Bulaeva, K. B. (Kazima Bagdadovna), Lynn B. Jorde, Christopher Ostler, Scott Watkins, Oleg Bulayev, and Henry Harpending. "Genetics and Population History of Caucasus Populations." Human Biology 75, no. 6 (2003): 837–53. http://dx.doi.org/10.1353/hub.2004.0003.

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16

Goodnight, C. J. "Population genetics: Peak shifts in large populations." Heredity 96, no. 1 (October 12, 2005): 5–6. http://dx.doi.org/10.1038/sj.hdy.6800746.

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17

WERTH, Silke. "Population genetics of lichen-forming fungi – a review." Lichenologist 42, no. 5 (August 3, 2010): 499–519. http://dx.doi.org/10.1017/s0024282910000125.

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AbstractPopulation genetics investigates the distribution of genetic variation in natural populations and the genetic differentiation among populations. Lichen-forming fungi are exciting subjects for population genetic studies due to their obligate symbiosis with a green-algal and/or cyanobacterial photobiont, and because their different reproductive strategies could influence fungal genetic structures in various ways. In this review, first, I briefly summarize the results from studies of chemotype variation in populations of lichen-forming fungi. Second, I compare and evaluate the DNA-based molecular tools available for population genetics of lichen-forming fungi. Third, I review the literature available on the genetic structure of lichen fungi to show general trends. I discuss some fascinating examples, and point out directions for future research.

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18

Curnow, R. N., A. H. D. Brown, M. T. Clegg, A. L. Kahler, and B. S. Weir. "Plant Population Genetics, Breeding, and Genetic Resources." Biometrics 46, no. 4 (December 1990): 1241. http://dx.doi.org/10.2307/2532478.

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19

Olivieri, Isabelle. "Plant population genetics, breeding, and genetic resources." Trends in Ecology & Evolution 6, no. 8 (August 1991): 265–66. http://dx.doi.org/10.1016/0169-5347(91)90078-c.

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20

McDonald, B. A., R. E. Pettway, R. S. Chen, J. M. Boeger, and J. P. Martinez. "The population genetics of Septoria tritici (teleomorph Mycosphaerella graminicola)." Canadian Journal of Botany 73, S1 (December 31, 1995): 292–301. http://dx.doi.org/10.1139/b95-259.

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The DNA-based markers of molecular genetics were combined with the analytical tools of population genetics to learn about the population biology of the wheat pathogen Mycosphaerella graminicola. DNA-based genetic markers, including restriction fragment length polymorphisms in nuclear and mitochondrial DNA, DNA fingerprints, and electrophoretic karyotypes were used in combination to show that the amount and distribution of genetic variation within and among field populations of M. graminicola is similar around the world. Measures of gametic disequilibrium suggested that the sexual stage of reproduction has a more significant impact on the genetic structure of M. graminicola populations than asexual reproduction. A field experiment conducted over a 3-year period showed that populations had a high degree of genetic stability over time. The potential effects of selection were quantified in a cultivar mixture experiment with four wheat cultivars that varied in resistance to M. graminicola. In combination, these experiments demonstrated the utility of selectively neutral genetic markers to elucidate the population genetics of fungi. Key words: genetic diversity, wheat, gene flow, RFLPs, DNA fingerprinting.

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21

Harrison, S. P., D. G. Jones, and J. P. W. Young. "Rhizobium Population Genetics: Genetic Variation Within and Between Populations from Diverse Locations." Microbiology 135, no. 5 (May 1, 1989): 1061–69. http://dx.doi.org/10.1099/00221287-135-5-1061.

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22

Casillas, Sònia, and Antonio Barbadilla. "Molecular Population Genetics." Genetics 205, no. 3 (March 2017): 1003–35. http://dx.doi.org/10.1534/genetics.116.196493.

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23

Beaumont, Mark A. "Estimation of Population Growth or Decline in Genetically Monitored Populations." Genetics 164, no. 3 (July 1, 2003): 1139–60. http://dx.doi.org/10.1093/genetics/164.3.1139.

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AbstractThis article introduces a new general method for genealogical inference that samples independent genealogical histories using importance sampling (IS) and then samples other parameters with Markov chain Monte Carlo (MCMC). It is then possible to more easily utilize the advantages of importance sampling in a fully Bayesian framework. The method is applied to the problem of estimating recent changes in effective population size from temporally spaced gene frequency data. The method gives the posterior distribution of effective population size at the time of the oldest sample and at the time of the most recent sample, assuming a model of exponential growth or decline during the interval. The effect of changes in number of alleles, number of loci, and sample size on the accuracy of the method is described using test simulations, and it is concluded that these have an approximately equivalent effect. The method is used on three example data sets and problems in interpreting the posterior densities are highlighted and discussed.

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24

Fearnhead, Paul. "Perfect Simulation From Nonneutral Population Genetic Models: Variable Population Size and Population Subdivision." Genetics 174, no. 3 (September 1, 2006): 1397–406. http://dx.doi.org/10.1534/genetics.106.060681.

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25

Legarra, Andres, Ole F. Christensen, Zulma G. Vitezica, Ignacio Aguilar, and Ignacy Misztal. "Ancestral Relationships Using Metafounders: Finite Ancestral Populations and Across Population Relationships." Genetics 200, no. 2 (April 14, 2015): 455–68. http://dx.doi.org/10.1534/genetics.115.177014.

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26

McHugh, Caitlin, Lisa Brown, and Timothy A. Thornton. "Detecting Heterogeneity in Population Structure Across the Genome in Admixed Populations." Genetics 204, no. 1 (July 20, 2016): 43–56. http://dx.doi.org/10.1534/genetics.115.184184.

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27

Sherwin, WB, and ND Murray. "Population and Conservation Genetics of Marsupials." Australian Journal of Zoology 37, no. 3 (1989): 161. http://dx.doi.org/10.1071/zo9890161.

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This article summarises current knowledge of marsupial population genetics, and discusses its relevance to the conservation of marsupial species. It has been suggested that there is much lower genetic variation within marsupial populations than in eutherian mammals. This trend is not evident in the electrophoretic data summarised here. However, genetic differentiation between populations, subspecies, and species of marsupials appears to be slightly lower than comparable values for eutherians. Genetic estimates of migration between populations are scarce at present, but show values that are comparable with eutherians. Some studies of marsupial population genetics have used non-electrophoretic characteristics, or have addressed the possibility of selection on the characters analysed. Although few, these studies indicate the suitability of marsupials for such investigations. Recent debate over the theories and applications of conservation genetics has made it clear that more research is required on individual species. Given the record of extinction of marsupials in the last 200 years, it is important to test the applicability of these theories to individual marsupial species. Several examples are discussed emphasising the need for ecological studies that estimate the effective number of reproducing individuals per generation. This figure, called the effective size, is the corner- stone of conservation genetics theory, being an important determinant of both the rate of loss of variation between individuals, and the rate of inbreeding. The effective size of the mainland population of the eastern barred bandicoot, Perameles gunnii, appears to be only about one-tenth of its census number. This result is comparable with estimates made in other vertebrates, and demonstrates that many marsupial species which appear to have an adequate census size on ecological grounds may face genetic problems resulting from small effective size.

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28

Xia, Longjie, Fengna Cai, Shasha Chen, Yao Cai, Kaiya Zhou, Jie Yan, and Peng Li. "Phylogenetic Analysis and Genetic Structure of Schlegel’s Japanese Gecko (Gekko japonicus) from China Based on Mitochondrial DNA Sequences." Genes 14, no. 1 (December 21, 2022): 18. http://dx.doi.org/10.3390/genes14010018.

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Gekko japonicus, i.e., Schlegel’s Japanese Gecko, is an important species which is widely distributed in East Asia. However, the information about population genetics of this species from China remains unclear. To address this issue, we used sequences from a fragment of the mitochondrial protein-coding gene cytochrome c oxidase I to estimate genetic diversity, genetic structure, and historical demography of G. japonicus populations from China. Phylogenetic analysis indicated that G. japonicus had a close relationship with Gekko wenxianensis. A total of 14 haplotypes were obtained, of which haplotype 1 was the most common and widely distributed. The genetic diversity of G. japonicus was comparatively low across different geographic populations. The populations of G. japonicus were divided into four groups which exhibited low levels of genetic differentiation, and expressed an unclear pattern of population structuring. In addition, potential population expansion of G. japonicus has occurred as well. Overall, these results demonstrate that the populations of G. japonicus reveal low genetic diversity in China, which is attributed to the founder and bottleneck events among populations. Our results will provide meaningful information on the population genetics of G. japonicus and will provide some insights into the study of origin of populations.

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29

Borowsky, Richard. "Basic Population Genetics." BioScience 37, no. 7 (July 1987): 518–19. http://dx.doi.org/10.2307/1310428.

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30

HUDSON, RICHARD R. "Population genetics text." Journal of Heredity 77, no. 2 (March 1986): 141–42. http://dx.doi.org/10.1093/oxfordjournals.jhered.a110199.

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31

Ewens, W. J. "Theoretical population genetics." Genome 31, no. 2 (January 15, 1989): 1088–89. http://dx.doi.org/10.1139/g89-188.

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32

Smith, John Maynard. "Population genetics revisited." Nature 403, no. 6770 (February 2000): 594–95. http://dx.doi.org/10.1038/35001127.

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33

Wilson, Ian. "Spatial population genetics." Trends in Ecology & Evolution 19, no. 5 (May 2004): 229–30. http://dx.doi.org/10.1016/j.tree.2004.01.007.

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34

Nordborg, Magnus, and Hideki Innan. "Molecular population genetics." Current Opinion in Plant Biology 5, no. 1 (February 2002): 69–73. http://dx.doi.org/10.1016/s1369-5266(01)00230-8.

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35

Quardokus, E. "Modeling Population Genetics." Science 288, no. 5465 (April 21, 2000): 458. http://dx.doi.org/10.1126/science.288.5465.458.

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36

Höss, Matthias. "Neanderthal population genetics." Nature 404, no. 6777 (March 2000): 453–54. http://dx.doi.org/10.1038/35006551.

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37

Dorey, Emma. "Population genetics deal." Nature Biotechnology 18, no. 4 (April 2000): 366. http://dx.doi.org/10.1038/74348.

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38

Chakraborty, Ranajit. "Theoretical Population Genetics." Trends in Ecology & Evolution 6, no. 2 (February 1991): 68. http://dx.doi.org/10.1016/0169-5347(91)90132-h.

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39

Provine, William B. "Discussion: Population genetics." Bulletin of Mathematical Biology 52, no. 1-2 (January 1990): 199–207. http://dx.doi.org/10.1007/bf02459573.

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40

Lambert, Amaury. "Population genetics, ecology and the size of populations." Journal of Mathematical Biology 60, no. 3 (August 6, 2009): 469–72. http://dx.doi.org/10.1007/s00285-009-0286-3.

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41

Brugman, E., A. Widiastuti, and A. Wibowo. "Population genetics of Phytophthora species based on short sequence repeat (SSR) marker: a review of its importance and recent studies." IOP Conference Series: Earth and Environmental Science 1230, no. 1 (September 1, 2023): 012102. http://dx.doi.org/10.1088/1755-1315/1230/1/012102.

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Abstract Phytophthora is a genus of oomycete (water molds) whose member species mostly live as plant pathogens and have been reported to cause enormous economic losses on crops worldwide. In recent years, population genetics of Phytophthora pathogens have been broadly studied to evaluate their adaptive evolution. Population genetic studies focus on analyzing the level of genetic diversity and the structure of the pathogen population. A population’s genetic diversity is proportional to its evolutionary potential. The generation and maintenance of genetic variation in pathogen populations are influenced by the biology of the pathogen and its host, environments, agricultural practices, and human activities. Understanding the population genetics of plant pathogens allows us to track the dynamic of the pathogen population and their adaptive ability, assisting the development of sustainable disease management strategies. This review presents the importance of population genetics, short sequence repeat (SSR) marker utilization in population genetic studies, and recent population genetics studies of Phytophthora pathogens related to agricultural practices.

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42

Bollmer, Jennifer L., Noah K. Whiteman, Michelle D. Cannon, James C. Bednarz, Tjitte de Vries, and Patricia G. Parker. "POPULATION GENETICS OF THE GALÁPAGOS HAWK (BUTEO GALAPAGOENSIS): GENETIC MONOMORPHISM WITHIN ISOLATED POPULATIONS." Auk 122, no. 4 (2005): 1210. http://dx.doi.org/10.1642/0004-8038(2005)122[1210:pgotgh]2.0.co;2.

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43

Bollmer, Jennifer L., Noah K. Whiteman, Michelle D. Cannon, James C. Bednarz, Tjitte de Vries, and Patricia G. Parker. "Population Genetics of the Galápagos Hawk (Buteo Galapagoensis): Genetic Monomorphism Within Isolated Populations." Auk 122, no. 4 (October 1, 2005): 1210–24. http://dx.doi.org/10.1093/auk/122.4.1210.

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Abstract Because of their smaller size and isolation, island populations tend to be more divergent and less genetically variable than mainland populations. We collected DNA samples from nine Galápagos Hawk (Buteo galapagoensis) island populations, covering the species’ entire range. Neutral minisatellite DNA markers were used to calculate within-island genetic diversity and between-island genetic differentiation (FST). Typically, these markers mutate too quickly to be informative in such studies. However, in very small, isolated populations, concerns about high mutational rate are obviated by the relative force of genetic drift. Individuals within islands had the highest levels of reported genetic uniformity of any natural bird population, with mean within-population band-sharing similarity values ranging from 0.693 to 0.956, increasing with decreasing island size. Galápagos Hawks exhibit cooperative polyandry to varying degrees across islands; however, we did not find an association between degree of polyandry and genetic variability. Between-island FST values ranged from 0.017 to 0.896, with an overall archipelago value of 0.538; thus, most populations were genetically distinct. Also, we documented higher levels of genetic similarity between nearby populations. Our results indicated negligible gene flow among most Galápagos Hawk populations, and genetic drift has played a strong role in determining structure at these minisatellite loci. Genética de Poblaciones de Buteo galapagoensis: Monomorfismo Genético dentro de Poblaciones Aisladas

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44

Frank, Steven A. "Genetic predisposition to cancer — insights from population genetics." Nature Reviews Genetics 5, no. 10 (October 2004): 764–72. http://dx.doi.org/10.1038/nrg1450.

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45

Futuyma, Douglas J. "Interface: Population Ecology and Population Genetics." Ecology 73, no. 6 (December 1992): 2340–41. http://dx.doi.org/10.2307/1941486.

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46

Cano, Pedro, Manuela Testi, Marco Andreani, Evelyne Khoriaty, Jad Bou Monsef, Tiziana Galluccio, Maria Troiano, Marcelo Fernandez-Vina, and Adlette Inati. "HLA population genetics: a Lebanese population." Tissue Antigens 80, no. 4 (September 20, 2012): 341–55. http://dx.doi.org/10.1111/j.1399-0039.2012.01936.x.

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47

Chotibut, Thiparat, and David R. Nelson. "Population Genetics with Fluctuating Population Sizes." Journal of Statistical Physics 167, no. 3-4 (February 13, 2017): 777–91. http://dx.doi.org/10.1007/s10955-017-1741-y.

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48

Priyono, Dwi Sendi, Dedy Duryadi Solihin, Achmad Farajallah, and Bambang Purwantara. "Genetic Diversity of the Endangered Endemic Anoa (Bubalus spp): Implication for Conservation." HAYATI Journal of Biosciences 29, no. 5 (May 17, 2022): 586–96. http://dx.doi.org/10.4308/hjb.29.5.586-596.

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Anoa is an endemic ungulate in Sulawesi and its status now is endangered because the population continues to decline. Conservation genetics is one of the crucial issues in the anoa conservation strategy and action plan 2013-2022 document, but this genetic data is not yet available. To investigate and provide valuable information for conservation genetics measures, thirteen polymorphic microsatellites were used to analyze 20 adult anoa. Anoa has relatively low genetic diversity within populations (HO = 0.58), and high genetic differentiation among populations (FST = 0157). Although the anoa population has a bottleneck signal (T.P.M: 0.019; P0.05), the bottleneck simulation results show that the loss of genetic diversity is being slow over the next 100 years (9.5%). We provide some recommendations for conservation genetics based on the findings in this paper, including monitoring and genetically mapping for other anoa populations due to bottleneck signals, establishing the founder of the ex-situ population by examining their genetic diversity status, maintaining and increasing the number of individuals in the ex-situ population to genetically safe population size, and managing anoa populations by avoiding inbreeding. In-situ and ex-situ conservation programs should be combined to maintain the genetic diversity of anoa.

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Takahata, N. "Gene genealogy in three related populations: consistency probability between gene and population trees." Genetics 122, no. 4 (August 1, 1989): 957–66. http://dx.doi.org/10.1093/genetics/122.4.957.

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Abstract A genealogical relationship among genes at a locus (gene tree) sampled from three related populations was examined with special reference to population relatedness (population tree). A phylogenetically informative event in a gene tree constructed from nucleotide differences consists of interspecific coalescences of genes in each of which two genes sampled from different populations are descended from a common ancestor. The consistency probability between gene and population trees in which they are topologically identical was formulated in terms of interspecific coalescences. It was found that the consistency probability thus derived substantially increases as the sample size of genes increases, unless the divergence time of populations is very long compared to population sizes. Hence, there are cases where large samples at a locus are very useful in inferring a population tree.

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Wakeley, John, and Jody Hey. "Estimating Ancestral Population Parameters." Genetics 145, no. 3 (March 1, 1997): 847–55. http://dx.doi.org/10.1093/genetics/145.3.847.

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Abstract:

The expected numbers of different categories of polymorphic sites are derived for two related models of population history: the isolation model, in which an ancestral population splits into two descendents, and the size-change model, in which a single population undergoes an instantaneous change in size. For the isolation model, the observed numbers of shared, fixed, and exclusive polymorphic sites are used to estimate the relative sizes of the three populations, ancestral plus two descendent, as well as the time of the split. For the size-change model, the numbers of sites segregating at particular frequencies in the sample are used to estimate the relative sizes of the ancestral and descendent populations plus the time the change took place. Parameters are estimated by choosing values that most closely equate expectations with observations. Computer simulations show that current and historical population parameters can be estimated accurately. The methods are applied to DNA data from two species of Drosophila and to some human mitochondrial DNA sequences.

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