- Research article
- Open Access
Towards breed formation by island model divergence in Korean cattle
© Strucken et al. 2015
Received: 13 October 2015
Accepted: 8 December 2015
Published: 18 December 2015
The main cattle breed in Korea is the brown Hanwoo, which has been under artificial selection within a national breeding program for several decades. Varieties of the Hanwoo known as Jeju Black and Chikso were not included in the breeding program and remained isolated from the effects of recent artificial selection advancements. We analysed the Jeju Black and Chikso populations in regards to their genetic variability, state of inbreeding, as well as level of differentiation from the mainland Hanwoo population.
Jeju Black and Chikso were found to have small estimated effective population sizes (N e ) of only 11 and 7, respectively. Despite a small N e , higher than expected heterozygosity levels were observed (0.303 and 0.306), however, lower allelic richness was found for the two island populations (1.76 and 1.77) compared to the mainland population (1.81). The increase in heterozygosity could be due to environmental disease challenges that promoted maintenance of higher genetic variability; however, no direct proof exists. Increased heterozygosity due to a first generation crossing of genetically different populations is not recorded. The differentiation between the Korean populations had F ST values between 0.014 and 0.036 which is not as high as the differentiation within European beef or dairy cattle breeds (0.047–0.111). This suggests that the three populations have not separated into independent breeds.
Results agree with an island model of speciation where the brown Hanwoo represents the ancestral breed, whilst the Jeju Black and Chikso diverge from this common ancestor, following different evolutionary trajectories. Nevertheless, differences are minor and whether Jeju Black and Chikso cattle will develop into discrete breeds or reintegrate with the main population has to be seen in the future and will largely depend on human management decisions. This offers a rare opportunity to accompany the development of new breeds but also poses challenges on how to preserve these incipient breeds and ensure their long term viability.
Recent developments in genome-wide data collection have enabled researchers to construct world-wide patterns of ancestry and admixture in domesticated cattle [1, 2]. Whilst these studies provide an exceptional overview of diversity patterns, smaller sub-populations that are just on the verge of becoming a distinct new breed were not included. Genetic differentiation usually takes places when individuals of a population get separated and diverge from each other driven by natural selection, founder effects, genetic drift and the lack of intermixture between the populations. A classic example is Darwin’s finches with many different (sub) species inhabiting the multitude of islands in the Galapagos, each adapted to the specific environmental conditions of their island [3, 4]. A similar scenario can be found in Korea, where a large cattle population exists on the mainland (brown Hanwoo), kept for beef production purposes (carcass weight and marbling) and therefore undergoing artificial selection pressure , and two other cattle populations (Jeju Black and Chikso) inhabiting small areas on the mainland as well as two islands off the coast line. On the mainland, the brown Hanwoo dominate mainly due to their incorporation into the national breeding program since the 1970s. On Jeju Island in the South, black Hanwoo (Jeju Black) survived, whilst some small populations of brindle or tiger-striped Hanwoo (Chikso) can be found on the mainland and on Ulleung Island in the East. Up until now, these breeds have been treated as independent breeds, mainly due to their different coat colours (National Report on the State of Animal Genetic Resources of the Republic of Korea; 2004).
Cattle bones found on Jeju Island were most closely related to Jeju Black suggesting that the progenitors of these cattle inhabited the island already 1100–2000 years ago . This time span coincides with migration routes from North China to Japan via the Korean peninsula . Jeju Black were used as presents to the king and selected for their black coat colour during the Joseon Dynasty (1392–1897). In 1992, the population was on the brink of extinction and had been reduced to about only 30 animals. As a result of conservation efforts, the population of Jeju Black has increased, though current figures for population size vary widely. Most Jeju Black cattle are kept in two preservation centres on Jeju Island. In 2013 the population was designated a natural monument of Korea with the hope of drawing attention to the need of improving the lineage and disease control measures, as well as raising awareness about the historical significance of the breed (Jeju Special Self-Governing Province Community).
First records of Chikso cattle can be dated back to a picture on an ancient tomb mural from AD 357 (Domestic Animal Diversity Information System, DAD-IS, FAO). The Chikso cattle nowadays comprise about 4000 animals of which 3000 exist on the mainland and another 1000 animals on Ulleung Island.
Both Jeju Black and Chikso were classified as endangered by the National Report on the State of Animal Genetic Resources of the Republic of Korea (2004). However, exact numbers of total or effective population sizes are not recorded and studies on the genetic divergence of the breeds as well as their genetic variability and inbreeding are sparse [8–11]. Maintaining genetic diversity, especially in small populations, is of high importance to prevent a decline in health and fertility and to preserve the ability of a population to respond to environmental changes in the future . Preservation of Jeju Black and Chikso cattle is of cultural value because of their ancient origins and strong links to the history of Korea.
Besides the varieties of Hanwoo within Korea, Chinese Yanbian cattle have been shown to be genetically highly similar to Hanwoo  but have maintained a higher level of genetic diversity possibly due to the lack of artificial selection within an organized breeding program. The Yanbian region in China has a strong Korean influence  and the Yanbian cattle were probably fully connected to the brown Hanwoo until the split between North and South Korea in 1953. Therefore, the Yanbian can be seen to some extend as a proxy for the original Hanwoo population prior to the implementation of the national breeding scheme.
Here, we provide important information (based on genome-wide markers) about the state of the Jeju Black and Chikso populations in regards to their genetic variability, state of inbreeding, as well as level of differentiation from the mainland Hanwoo population. Results of this work should be of value for practical decision making on how to best conserve these populations.
Results and discussion
Variability and Isolation
Population metrics of 10 cattle breeds including effective population sizes (N e ), genetic variance, allelic richness, and inbreeding measures (±sd)
# Fixed markers
97 ± 31
0.23 ± 0.15
0.312 ± 0.17
1.81 ± 0.28a
0.0003 ± 0.006
11 ± 2
0.22 ± 0.16
0.303 ± 0.19
1.77 ± 0.34
0.0003 ± 0.005
7 ± 2
0.21 ± 0.16
0.306 ± 0.20
1.76 ± 0.35
0.0002 ± 0.004
227 ± 67
0.24 ± 0.15
0.326 ± 0.16
1.84 ± 0.25
0.0004 ± 0.006
14 ± 4
0.24 ± 0.15
0.329 ± 0.19
1.81 ± 0.32a
0.0027 ± 0.040
15 ± 15
0.20 ± 0.17
0.291 ± 0.25
1.73 ± 0.44
0.0004 ± 0.009
77 ± 45
0.24 ± 0.15
0.332 ± 0.20
1.83 ± 0.30b
0.0006 ± 0.011
26 ± 7
0.24 ± 0.15
0.334 ± 0.20
1.83 ± 0.31b
0.0034 ± 0.041
56 ± 16
0.25 ± 0.15
0.341 ± 0.18
1.86 ± 0.25
0.0020 ± 0.029
16 ± 5
0.14 ± 0.14
0.208 ± 0.19
1.61 ± 0.39
0.0061 ± 0.065
Further, we estimated the effective population size for five European taurine breeds as well as a Brahman population which were much lower than previously reported [17, 18]. Nevertheless, in comparative terms, the two island populations had the smallest effective population size within our study.
The relationship between population size and genetic variability has been extensively studied and with a reduction in population size it would be expected that the genetic variability also decreases and inbreeding increases, which is visible as a loss of heterozygosity [12, 19]. A first simplistic measure is to look at the number of markers that are fixed in a population, i.e. show no variability. Over all breeds in this study, 14,629 markers were fixed in at least one population. Within the Korean cattle breeds, the island populations had 2.5 to 3.0 times as many loci fixed compared to the Hanwoo, confirming a potential reduction in genetic variability between the Korean island and mainland populations (Table 1). Allelic richness (A R ) estimates also confirmed a reduction in genetic variability for the two island populations (Table 1), which were only undercut by the Brown Swiss and Brahman populations of this study. However, observed heterozygosities were 0.303 and 0.306 for Jeju Black and Chikso, respectively, and 0.312 for mainland Hanwoo, which were significantly higher than estimated expected heterozygosity levels for these breeds (Table 1). Edea et al.  reported a 0.1 higher expected heterozygosity for Hanwoo cattle which might be a result of differing quality control filtering criteria or the use of a lower density genotyping platform, resulting in different estimates of heterozygosity. Suh et al.  found higher expected heterozygosity levels for brown Hanwoo and Chikso, however, their study was based on 30 microsatellite markers which present a different data basis.
Similarly to our observed increased heterozygosity levels compared to expected frequencies, estimated inbreeding coefficients indicated an excess of heterozygous genotypes for the two island populations (Table 1). Variation in inbreeding was similar between chromosomes and showed only stronger deviations from 0 for the Brown Swiss population which is most likely due to the small sample size (Additional file 1: Figure S1). Even though the indication for an excess in heterozygous loci is marginal, it might point towards an advantage and selection for over-dominant gene expressions . Selection under environmental pressure can be observed in declining populations because survival or fecundity of heterozygous individuals is increased . It was shown that Jeju Black are more resistant to theileria infections  - a piroplasms parasite which causes anorexia, fever, anaemia and icterus -, and Hanwoo cattle showed a higher resistance to the bovine papillomavirus compared to Holstein cattle . Nevertheless, reports on different adaption due to environmental pressure within the Hanwoo varieties are sparse and do not allow for an in depth interpretation. Further, this interpretation warrants some caution as there is a possibility of gene flow between these populations which could also have led to the increased heterozygosity observed. Records for Chikso and Jeju Black are very sparse and in an attempt to preserve these populations, there may have been some undocumented crossing with brown Hanwoo at some point in time.
To get an indication about whether environmental selection pressure resulted in a higher variability for loci close to genes related to health and fertility traits, we performed a gene enrichment analysis in an area of one Mb in either direction of segregating markers that were unique for each Korean breed (93 markers for Chikso, 212 markers for Jeju Black, and 1104 markers for Hanwoo). In total, 1531 protein coding genes were found in Chikso, 2519 genes in Jeju Black, and 10,282 genes in Hanwoo cattle.
Biological process of significantly enriched gene sets in the three Korean cattle breeds
Homophilic cell adhesion
Defence response to bacteria
Amine metabolic process
G-protein coupled receptor
Positive regulation of transcription from RNA polymerase II promoter
Negative regulation of transcription from RNA polymerase II promoter
Response to virus
Intracellular signal transduction
Response to oxidative stress
Counterintuitively given the population sizes, inbreeding cannot currently be observed in the island populations. However, an excess of heterozygous loci possibly due to environmental selection pressure together with the small effective population sizes warrant close monitoring of the populations to prevent inbreeding depression in the future.
Differentiation between populations
Pairwise estimates of F ST after 100 bootstrapsa (upper diagonal) and Nei’s D (lower diagonal) between 10 cattle breeds
Analysis of molecular variance in Korean, and European dairy and beef cattle populations
Source of variance
Sum of square deviations
Mean of square deviations
Degrees of freedom
Variance components (%)
Both Chikso and particularly the Jeju Black have a long association with the history of Korea – they serve as a living link to the past and to the cultural traditions of the country; hence, there is strong interest in preserving these populations for the future. The effective population sizes are small and whilst heterozygosity and inbreeding are currently not a major concern, forward projections of heterozygosity decay are quite troubling. Conservation efforts should focus on monitoring and maximizing diversity as well as tracking the overall robustness of the populations across time. There is a possibility that the Chikso is fragmented into isolates; a priority should be to improve gene flow between the subpopulations. A challenging question that will need to be addressed in the near future is whether to fully close these populations and work with the available diversity or introduce new variation from mainland Hanwoo. The relatively low differentiation at this point suggests that some level of introgression with Hanwoo and careful phenotypic selection for the population’s distinguishing traits would not compromise the integrity of the breeds but it may be politically infeasible to implement.
The brown Hanwoo cattle have been subjected to artificial selection within a national breeding program aimed at meat quality for several decades. Two other varieties, the Jeju Black and the Chikso cattle, were excluded from the national breeding program and remained insulated from recent artificial selection advancements. This led to a decline in population sizes due to a lack of commercial interest in the breeds. Even though effective population sizes are small, there is currently little evidence of loss of genetic diversity or inbreeding. Nevertheless, forward estimates of heterozygosity project a rapid loss of diversity which justifies measures aimed at preserving the Jeju Black and Chikso population due to their historical and cultural relevance to Korea. The Jeju Black and Chikso varieties show some level of breed divergence from the mainland Hanwoo cattle, though distinctly less than between other well characterized cattle breeds. From a purely genetic perspective there is limited value in managing these populations independently; but given their high social value for Korea, a separate breeding program aimed at maximizing diversity and improving fitness is warranted.
Sampling of the brown Hanwoo was carried out by veterinary practitioners in the Hanwoo Improvement Centre of the National Agricultural Cooperative Federation with the permission of the owners. The protocol was approved by the Committee on the Ethics of Animal Experiments of the National Institute of Animal Science (Permit Number: 2013–028). No ethics statement was required for the collection of other animal samples used in this study as data was provided by secondary sources.
Cattle were sampled from research stations on mainland Korea and Jeju Island. On Jeju Island, 20 Jeju Black cattle were sampled at the Subtropical Animal Experimental Station. Chikso cattle (n = 20) were collected from the Gyeonggi and Gyeonbuk provinces; and brown Hanwoo (n = 40) cattle were sampled from the Hanwoo Improvement Centre of the National Agricultural Cooperative Federation in Seosan (Chungnam province).
A further 39 animals from the Chinese Yanbian cattle breed were sampled from the Yanbian Prefecture in China. Finally, five originally European taurine breeds (n = 6 Brown Swiss, n = 19 Holstein, n = 15 Hereford, n = 19 Angus and n = 13 Limousine) and one indicine breed (n = 19 Brahman) were sampled from Australian populations and included in the analysis for comparison (Table 1). All animals were sampled at random and relationship statuses between animals of each population were confirmed using a genomic relationship matrix. The genomic relationship matrix was build according to Van Raden . Missing genotypes were replaced by the average allele count across all animals.
All animals were genotyped with the Illumina Bovine SNP 50 K Bead chip (Illumina, San Diego). Quality control was performed with snpQC  and the data was filtered based on call rates of markers and animals over 95 %, a median GC score for markers over 0.6, heterozygosity within three standard deviations from other SNPs and deviation from Hardy-Weinberg equilibrium for a cut-off P-value of 10−16. Markers on sex chromosomes or unmapped markers were excluded. Ascertainment bias of genotypes was checked by comparing results of segregating markers within populations versus results of markers segregating across populations. Bias was minor and therefore no further markers were excluded from the study. A total of 29,844 markers were used in the analyses.
Genetic variability and admixture
The effective population size (N e ) for each breed was estimated with the LDNe program . Effective population sizes were estimated based on calculated r 2 as linkage disequilibrium according to Hill  and Waples . Due to constraints on the size of the input files, N e was estimated per chromosome and then averaged across the entire genome. The mating system was chosen to be at random even though this is not fully realistic for livestock populations.
Allelic richness (A R ) and private allelic richness (pA R ) were estimated with the HP-Rare v1.0 program , which includes differences in sample sizes to provide an unbiased estimate. Distribution of genetic variability between breeds, inbreeding and population differentiation were assessed with Wright  F-statistics (F IS and F ST ), estimated according to Weir and Cockerham , and Nei’s genetic distance as implemented in the StAMPP package in R [38, 39]. Significance test for differences in F ST values were achieved by 100 bootstrapping replicas.
Euclidean distances and Ward’s clustering method as implemented in the Ape package in R were used to establish a phylogenetic tree [40, 41] based on allele frequencies. The phylogeny analysis was complemented with 10,000 bootstrapping replicas on the entire marker data with random replacements. Further, principal components based on a genomic relationship matrix  were assessed, and an analysis of molecular variance (AMOVA ) carried out to establish within and between population variation.
Finally, we used ADMIXTURE 1.23  to predict ancestral populations and estimate breed proportions. The best number of ancestral populations (K) was inferred through cross-validation of 1 to 10 assumed populations.
The numbers of fixed and segregating markers were assessed and the overlap of markers between breeds calculated. A gene enrichment analysis for segregating markers that were unique for each of the Korean breeds was carried out. Genes including a direct marker or genes within one Mb in either direction of a marker (to minimize the possibility of recombination between marker and causal mutation) were regarded as adaptive variation whereas all other markers were regarded as neutral variation. The GeneCodis program (release 3) [44–46] was used to filter whether gene groups with similar functions occurred more frequently than expected between breeds. A Chi2 test was used to compute P-values which were corrected for multiple testing through false-discovery rate .
Availability of supporting data
Datasets will be made available upon acceptance of this paper and before publication. Genotypic data of the Korean cattle breeds are deposited with Dryad: http://0-dx.doi.org.brum.beds.ac.uk/10.5061/dryad.p2b3b.
This work was supported by a grant from the Next-Generation BioGreen 21 Program (No. PJ01134906), Rural Development Administration, Republic of Korea.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Decker JE, McKay SD, Rolf MM, Kim J, Molina Alcala A, Sonstegard TS, et al. Worldwide patterns of ancestry, divergence, and admixture in domesticated cattle. PLoS Genet. 2014;10:e1004254.PubMed CentralPubMedView ArticleGoogle Scholar
- Bovine HapMap C, Gibbs RA, Taylor JF, Van Tassell CP, Barendse W, Eversole KA, et al. Genome-wide survey of SNP variation uncovers the genetic structure of cattle breeds. Science. 2009;324:528–32.View ArticleGoogle Scholar
- McKay BD, Zink RM. Sisyphean evolution in Darwin’s finches. Biol Rev Camb Philos Soc. 2014.Google Scholar
- Farrington HL, Lawson LP, Clark CM, Petren K. The evolutionary history of darwin’s finches: speciation, gene flow, and introgression in a fragmented landscape. Evolution. 2014;68:2932–44.PubMedView ArticleGoogle Scholar
- Kim HC, Lee SH, Cho YM, Kim SW, Lim D, Park EW, et al. Genomic information and its application in hanwoo (Korean native cattle) breeding program - a mini review. Ann Anim Resour Sci. 2011;22:125–33.Google Scholar
- Kim JH, Oh SJ, Song JH, Jeon JT, Han SH, Jung YH, et al. Molecular genetic analysis of ancient cattle bones excavated from archaeological sites in jeju, Korea. Mol Cells. 2005;20:325–30.PubMedView ArticleGoogle Scholar
- Mannen H, Tsuji S, Loftus RT, Bradley DG. Mitochondrial DNA variation and evolution of Japanese black cattle (Bos taurus). Genetics. 1998;150:1169–75.PubMed CentralPubMedGoogle Scholar
- Lee SH, Cho YM, Lim D, Kim HC, Choi BH, Park HS, et al. Linkage disequilibrium and effective population size in hanwoo Korean cattle. Asian-Aust J Anim Sci. 2011;24:1660–5.View ArticleGoogle Scholar
- Kim JH, Byun MJ, Kim MJ, Suh SW, Ko YG, Lee CW, et al. MtDNA diversity and phylogenetic state of Korean cattle breed, chikso. Asian-Aust J Anim Sci. 2013;26:163–70.View ArticleGoogle Scholar
- Choi JW, Liao X, Park S, Jeon HJ, Chung WH, Stothard P, et al. Massively parallel sequencing of Chikso (Korean brindle cattle) to discover genome-wide SNPs and InDels. Mol Cells. 2013.Google Scholar
- Dadi H, Lee SH, Jung KS, Choi JW, Ko MS, Han YJ, et al. Effect of population reduction on mtDNA diversity and demographic history of Korean cattle populations. Asian-Aust J Anim Sci. 2012;25:1223–8.View ArticleGoogle Scholar
- Amos W, Balmford A. When does conservation genetics matter? Heredity (Edinb). 2001;87:257–65.View ArticleGoogle Scholar
- Strucken EM, Piper EK, Lee HK, Song KD, Gibson JP, Lee SH, et al. Fat cows - selection signatures in Korean hanwoo and Australian wagyu cattle. Vancouver: 10th World Congress of Genetics Applied to Livestock Production; 2014. p. 1–4.Google Scholar
- Min PG. A comparison of the Korean minorities in China and Japan. Int Migr Rev. 1992;26:4–21.PubMedView ArticleGoogle Scholar
- Han SH, Cho IC, Kim JH, Ko MS, Kim YH, Kim EY, et al. Coat color patterns and genotypes of extension and agouti in hanwoo and Jeju black cattle. J Life Sci. 2011;21:494–501.View ArticleGoogle Scholar
- Suh S, Kim YS, Cho CY, Byun MJ, Choi SB, Ko YG, et al. Assessment of genetic diversity, relationships and structure among Korean native cattle breeds using microsatellite markers. Asian-Aust J Anim Sci. 2014;27:1548–53.View ArticleGoogle Scholar
- Leroy G, Mary-Huard T, Verrier E, Danvy S, Charvolin E, Danchin-Burge C. Methods to estimate effective population size using pedigree data: examples in dog, sheep, cattle and horse. Genet Sel Evol. 2013;45:1.PubMed CentralPubMedView ArticleGoogle Scholar
- de Roos AP, Hayes BJ, Spelman RJ, Goddard ME. Linkage disequilibrium and persistence of phase in Holstein-Friesian, Jersey and Angus cattle. Genetics. 2008;179:1503–12.PubMed CentralPubMedView ArticleGoogle Scholar
- Amos W, Harwood J. Factors affecting levels of genetic diversity in natural populations. Philos Trans R Soc Lond B Biol Sci. 1998;353:177–86.PubMed CentralPubMedView ArticleGoogle Scholar
- Edea Z, Dadi H, Kim SW, Dessie T, Lee T, Kim H, et al. Genetic diversity, population structure and relationships in indigenous cattle populations of Ethiopia and Korean Hanwoo breeds using SNP markers. Front Genet. 2013;4:35.PubMed CentralPubMedView ArticleGoogle Scholar
- Tregenza T, Wedell N. Genetic compatibility, mate choice and patterns of parentage: invited review. Mol Ecol. 2000;9:1013–27.PubMedView ArticleGoogle Scholar
- Gulland FM, Albon SD, Pemberton JM, Moorcroft PR, Clutton-Brock TH. Parasite-associated polymorphism in a cyclic ungulate population. Proc Biol Sci. 1993;254:7–13.PubMedView ArticleGoogle Scholar
- Ko MS, Lee KK, Hwang KK, Kim BS, Choi GC, Yun YM. Antigenic diversity of Theileria major piroplasm surface protein gene in Jeju black cattle. J Vet Sci. 2008;9:155–60.PubMed CentralPubMedView ArticleGoogle Scholar
- Bae YC, Lee CS, Kang MI, Yoon SS, Park JW, Jean YH. Bovine papillomavirus detection from bovine teats using immunohistochemistry and electronmicroscopy. Korean J Vet Res. 2005;45:233–8.Google Scholar
- Selsted ME, Tang YQ, Morris WL, McGuire PA, Novotny MJ, Smith W, et al. Purification, primary structures, and antibacterial activities of beta-defensins, a new family of antimicrobial peptides from bovine neutrophils. J Biol Chem. 1993;268:6641–8.PubMedGoogle Scholar
- Cormican P, Meade KG, Cahalane S, Narciandi F, Chapwanya A, Lloyd AT, et al. Evolution, expression and effectiveness in a cluster of novel bovine beta-defensins. Immunogenetics. 2008;60:147–56.PubMedView ArticleGoogle Scholar
- Porto-Neto LR, Lee S-H, Sonstegard T, Van Tassell CP, Lee HK, Gondro C. Genome-wide detection of signatures of selection in Korean hanwoo cattle. Anim Genet. 2012.Google Scholar
- Van Raden PM. Efficient methods to compute genomic predictions. J Dairy Sci. 2008;91:4414–23.View ArticleGoogle Scholar
- Gondro C, Porto-Neto LR, Lee SH. snpqc - an R pipeline for quality control of Illumina SNP genotyping array data. Anim Genet. 2014;45:758–61.PubMedView ArticleGoogle Scholar
- Waples RS, Do C. ldne: a program for estimating effective population size from data on linkage disequilibrium. Mol Ecol Resour. 2008;8:753–6.PubMedView ArticleGoogle Scholar
- Hill WG. Estimation of effective population size from data on linkage disequilibrium. Genet Res. 1981;38:209–16.View ArticleGoogle Scholar
- Waples RS. A bias correction for estimates of effective population size based on linkage disequilibrium at unlinked gene loci. Conserv Genet. 2006;7:167–84.View ArticleGoogle Scholar
- Kimura M, Ohta T. The average number of generations until fixation of a mutant gene in a finite population. Genetics. 1969;61:763–71.PubMed CentralPubMedGoogle Scholar
- Kliman R, Sheehy B, Schultz J. Genetic drift and effective population size. Nat Educ. 2008;1:3.Google Scholar
- Kalinowski ST. hp-rare 1.0: a computer program for performing rarefaction on measures of allelic richness. Mol Ecol Resour. 2004;5:187–9.Google Scholar
- Wright S. The genetical structure of populations. Ann Eugenics. 1951;15:323–54.View ArticleGoogle Scholar
- Weir BS, Cockerham CC. Estimating F-statistics for the analysis of population structure. Evolution. 1984;38:1358–70.View ArticleGoogle Scholar
- Nei M. Genetic distance between populations. Am Nat. 1972;106:283–92.View ArticleGoogle Scholar
- Pembleton LW, Cogan NO, Forster JW. StAMPP: an R package for calculation of genetic differentiation and structure of mixed-ploidy level populations. Mol Ecol Resour. 2013;13:946–52.PubMedView ArticleGoogle Scholar
- Ward Jr JH. Hierarchical grouping to optimize an objective function. J Am Stat Assoc. 1963;58:236–44.View ArticleGoogle Scholar
- Paradis E, Claude J, Strimmer K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics. 2004;20:289–90.PubMedView ArticleGoogle Scholar
- Excoffier L, Smouse PE, Quattro JM. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics. 1992;131:479–91.PubMed CentralPubMedGoogle Scholar
- Alexander DH, Novembre J, Lange K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 2009;19:1655–64.PubMed CentralPubMedView ArticleGoogle Scholar
- Tabas-Madrid D, Nogales-Cadenas R, Pascual-Montano A. GeneCodis3: a non-redundant and modular enrichment analysis tool for functional genomics. Nucleic Acids Res. 2012;40:W478–83.PubMed CentralPubMedView ArticleGoogle Scholar
- Nogales-Cadenas R, Carmona-Saez P, Vazquez M, Vicente C, Yang X, Tirado F, et al. GeneCodis: interpreting gene lists through enrichment analysis and integration of diverse biological information. Nucleic Acids Res. 2009;37:W317–22.PubMed CentralPubMedView ArticleGoogle Scholar
- Carmona-Saez P, Chagoyen M, Tirado F, Carazo JM, Pascual-Montano A. GENECODIS: a web-based tool for finding significant concurrent annotations in gene lists. Genome Biol. 2007;8:R3.PubMed CentralPubMedView ArticleGoogle Scholar
- Benjamin Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multilpe testing. J R Stat Soc. 1995;57:289–300.Google Scholar