Arlequin (version 3.0)

更新时间:2023-06-12 01:46:00 阅读: 评论:0

A P P L I C A T I O N N O T E Arlequin (version 3.0): An integrated software package for population genetics data analysis
Laurent Excoffier, Guillaume Laval, Stefan Schneider
Computational and Molecular Population Genetics Lab, , Zoological Institute, University of Berne, Baltzerstras 6, 3012 Berne, Switzerland
Introduction
Most genetic studies on non-model organisms require a description of the pattern of diversity within and be-tween populations, bad on a variety of markers often including mitochondrial DNA (mtDNA) quences and microsatellites. The genetic data are procesd to extract information on the mating sy
stem, the extent of popu-lation subdivision, the past demography of the population, or on departure from lective neutrality at some loci. A ries of computer packages have been developed in the last 10 years to assist rearchers in performing basic population genetics analys like Arlequin2 (Schneider et al. 2000), DNASP (Rozas et al. 2003), FSTAT (Goudet 1995), GENEPOP (Raymond and Roust 1995b), or GENETIX (Belkhir et al. 2004). The programs have been widely ud in the molecular ecology and conrvation genetics community (Labate 2000; Luikart and England 1999; Schnabel et al. 1998). Among the, Arlequin is a very versatile (though not universal) pro-gram, and complements the other programs listed above. It can handle veral data types like RFLPs, DNA -quences, microsatellite data, allele frequencies, or standard multi-locus genotypes, while allowing the ur to carry out the same types of analys irrespective of the data types.
We prent here the version 3 of Arlequin with additional methods extending its capacities for the handling of unphad multi-locus genotypes and for the estimation of parameters of a spatial expansion. Note that the new developments are mainly implementations of new methodologies developed in our lab. We believe the methods will be uful to the rearch community, but we do not claim that alternative methods implemented by other groups in other programs are inadequate. A new graphical interface has been developed to provide a better integration of the different analys i
nto a common framework, and an easier exploration of the data by performing a wide variety of analys with different ttings. The tight coupling of Arlequin with the simula-tion programs SIMCOAL2 (Laval and Excoffier 2004) and SPLATCHE (Currat et al. 2004) should also make it uful to describe patterns of genetic diversity under complex evolutionary scenarios.
Methods implemented in Arlequin
Arlequin provides methods to analy patterns of genetic diversity within and between population samples.
Intra-population methods
• Computation of different standard genetic indices, like the number of gregating sites, the number of dif-
Excoffier et al
ferent alleles, the heterozygosity, the ba
composition of DNA quences, gene diver-
sity, or the population effective size N e scaled
by the mutation rate μ as θ=4N e u.
• Maximum-likelihood estimation of allele and haplotype frequencies via the EM algorithm
六级英语报名(Excoffier and Slatkin 1995).
• Estimation of the gametic pha from multi-locus genotypes via the Excoffier-Laval-
Balding (ELB) algorithm (Excoffier et al.
2003).
• Estimation of the parameters of a demographic (Rogers and Harpending 1992; Schneider and
Excoffier 1999) or a spatial (Excoffier 2004;
Ray et al. 2003) expansion, from the mismatch
distribution computed on DNA quences.
• Calculation of veral measures of linkage dis-equilibrium (LD) like D, D', or r2(Hedrick
1987), and test of non-random association of
alleles at different loci when the gametic pha
is known (Weir 1996) or unknown (Slatkin
and Excoffier 1996).
• Exact test of departure from Hardy-Weinberg equilibrium (Guo and Thompson 1992).
• Computation of Tajima’s D (Tajima 1989) and Fu's F S(Fu 1997) statistics, and test of their
significance by coalescent simulations
(Hudson 1990; Nordborg 2003) under the infi-
nite-site model.
• Tests of lective neutrality under the infinite-alleles model, like the Ewens-Watterson test
(Slatkin 1996; Watterson 1978), and Chak-
raborty’s amalgamation test (Chakraborty
1990).
Inter-population methods
• Search for shared haplotypes between popula-tions
• Analysis of population subdivision under the AMOVA framework (Excoffier 2003; Excof-
fier et al. 1992), with three hierarchical levels:
genes within individuals, individuals within
demes, demes within groups of demes. Com-
putation of F-statistics like the local inbreed-
ing coefficient F IS or the index of population
differentiation F ST.
• Computation of genetic distances between populations related to the pairwi F ST index
(Gaggiotti and Excoffier 2000; Reynolds et al.
1983; Slatkin 1995).
• Exact test of population differentiation (Goudet et al. 1996; Raymond and Roust
1995a).
收据怎么写•    A simple assignment test of individual geno-types to populations according to their likeli-
hood (Paetkau et al. 1997).
• Computation of correlations or partial correla-tions between a t of 2 or 3 distance matrices
(Mantel test: Smou et al. 1986)
扇枕温衾的故事
New features in Arlequin 3
• Version 3 of Arlequin integrates the core com-putational routines and the interface in a single
program written in C++ for the Windows envi-
ronment. The interface has been entirely redes-
igned to provide better usability.
• Incorporation of two new methods to estimate gametic pha and haplotype frequencies:
◊ The ELB algorithm (Excoffier et al.
2003) is a pudo-Bayesian approach
aiming at reconstructing the gametic
pha of multi-locus genotypes, and the
estimation of the haplotype frequencies
are a by-product of this process. Pha
updates are made on the basis of a win-
dow of neighbouring loci, and the win-
dow size varies according to the local
level of linkage diquilibrium.
◊ The EM zipper algorithm, which is an extension of the EM algorithm for esti-
mating haplotype frequencies (Excoffier
and Slatkin 1995), aims at estimating the
haplotype frequencies in unphad
multi-locus genotypes. The estimation of
the gametic phas are a by-product of
this process. It proceeds by adding loci
one at a time and progressively extend-
ing the length of the reconstructed haplo-
Arlequin 3.0
Excoffier et al小型犬品种
References
Adkins RM. 2004. Comparison of the accuracy of methods of computational haplotype inference using a large empirical datat. BMC Genet. 5:
22.
Belkhir K, Borsa P, Chikhi L et al. 2004. GENETIX 4.05, logiciel sous Win-dows pour la génétique des populations. Laboratoire Génome, Popula-
tions, Interactions, CNRS UMR 5000, Université de Montpellier II,
Montpellier.
Chakraborty R. 1990. Mitochondrial DNA polymorphism reveals hidden het-erogeneity within some Asian populations. Am J Hum Genet. 47: 87-
94.
Currat M, Ray N and Excoffier L. 2004. SPLATCHE: a program to simulate genetic diversity taking into account environmental heterogeneity.
Mol Ecol. 4: 139-142.
Excoffier L. 2003. Analysis of Population Subdivision. In Balding D Bishop M, and Cannings C, eds. Handbook of Statistical Genetics, 2nd Edi-
tion. New York: John Wiley & Sons, Ltd. p 713-750.
Excoffier L. 2004. Patterns of DNA quence diversity and genetic structure after a range expansion: lessons from the infinite-island model. Mol
Ecol. 13: 853-864.
Excoffier L, Laval G and Balding D. 2003. Gametic pha estimation over large genomic regions using an adaptive window approach. Mol Ecol.
1: 7-19.
Excoffier L and Slatkin M. 1995. Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population. Mol Biol Evol. 12: 921-
927.
Excoffier L, Smou P and Quattro J. 1992. Analysis of molecular variance inferred from metric distances among DNA haplotypes: Application to
human mitochondrial DNA restriction data. Genetics. 131: 479-491.  Fu Y-X. 1997. Statistical tests of neutrality of mutations against population growth, hitchhiking and backgroud lection. Genetics. 147: 915-925.  Gaggiotti O and Excoffier L. 2000. A simple method of removing the effect of
a bottleneck and unequal population sizes on pairwi genetic dis-
tances. Proceedings of the Royal Society London B. 267: 81-87.  Goudet J. 1995. Fstat version 1.2: a computer program to calculate F-statistics.
J Heredity. 86: 485-486.
Goudet J, Raymond M, de Meeüs T et al. 1996. Testing differentiation in dip-loid populations. Genetics. 144: 1933-1940.
Guo S and Thompson E. 1992. Performing the exact test of Hardy-Weinberg proportion for multiple alleles. Biometrics. 48: 361-372.
Hedrick P. 1987. Gametic diquilibrium measures: proceed with caution.
Genetics. 117: 331-3412.
Hudson RR. 1990. Gene genealogies and the coalescent process. In Futuyma DJ and Antonovics JD, eds. Oxford Surveys in Evolutionary Biology.
New York: Oxford University Press. p 1-44.
小说家排名Labate JA. 2000. Software for Population Genetic Analys of Molecular Marker Data. Crop Sci. 40: 1521-1528.
Laval G and Excoffier L. 2004. SIMCOAL 2.0: a program to simulate genomic diversity over large recombining regions in a subdivided population
with a complex history. Bioinformatics. 20: 2485-2487.
Luikart G and England PR. 1999. Statistical analysis of microsatellite DNA data. Trends Ecol Evol. 14: 253-256.
Nordborg M. 2003. Coalescent Theory. In Balding D Bishop M, and Cannings C, eds. Handbook of Statistical Genetics, 2nd edition. New York: John
Wiley & Sons Ltd. p 602-635.
Paetkau D, Waits LP, Clarkson PL et al. 1997. An empirical evaluation of genetic distance statistics using microsatellite data from bear (Ursidae)
populations. Genetics. 147: 1943-1957.
Ray N, Currat M and Excoffier L. 2003. Intra-Deme Molecular Diversity in Spatially Expanding Populations. Mol. Biol. Evol. 20: 76-86.  Raymond M and Roust F. 1995a. An exact test for population differentiation.
Evolution. 49: 1280-1283.
Raymond M and Roust F. 1995b. GENEPOP Version 1.2: Population genet-ics software for exat t
ests and ecumenicism. J Heredity. 248-249.  Reynolds J, Weir BS and Cockerham CC. 1983. Estimation for the coancestry coefficient: basis for a short-term genetic distance. Genetics. 105:
感恩节的小故事767-779.
Rogers AR and Harpending H. 1992. Population growth makes waves in the distribution of pairwi genetic differences. Mol Biol Evol. 9: 552-
569.
Rozas J, Sanchez-DelBarrio JC, Mesguer X et al. 2003. DnaSP, DNA poly-morphism analys by the coalescent and other methods. Bioinformat-
道路交通事故处理办法ics. 19: 2496-2497.
Schnabel A, Beerli P, Estoup A et al. 1998. A guide to software packages for data analysis in molecular ecology. In Carvalho G, eds. Advances in
Molecular Ecology. Amsterdam: IOS Press. pp 291-303.
Schneider S and Excoffier L. 1999. Estimation of demographic parameters from the distribution of pairwi differences when the mutation rates
vary among sites: Application to human mitochondrial DNA. Genet-
ics. 152: 1079-1089.
Schneider S, Roessli D and Excoffier L. 2000. Arlequin: a software for popula-tion genetics data analysis. Ur manual ver 2.000. Genetics and Bi-
ometry Lab, Dept. of Anthropology, University of Geneva, Geneva.  Slatkin M. 1995. A measure of population subdivision bad on microsatellite allele frequencies. Genetics. 139: 457-462.
你人生的第一次
Slatkin M. 1996. A correction to the exact test bad on the Ewens sampling distribution. Genet Res. 68: 259-260.
Slatkin M and Excoffier L. 1996. Testing for linkage diquilibrium in geno-typic data using the EM algorithm. Heredity. 76: 377-383.
Smou PE, Long JC and Sokal RR. 1986. Multiple regression and correlation extensions of the Mantel Test of matrix correspondence. Syst Zool. 35:
627-632.
Tajima F. 1989. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics. 123: 585-595.
Watterson G. 1978. The homozygosity test of neutrality. Genetics. 88: 405-417.
Weir BS. 1996. Genetic Data Analysis II: Methods for Discrete Population Genetic Data. Sinauer Assoc., Inc.: Sunderland, MA, USA.

本文发布于:2023-06-12 01:46:00,感谢您对本站的认可!

本文链接:https://www.wtabcd.cn/fanwen/fan/82/933793.html

版权声明:本站内容均来自互联网,仅供演示用,请勿用于商业和其他非法用途。如果侵犯了您的权益请与我们联系,我们将在24小时内删除。

标签:道路   枕温   排名   处理   办法   故事
相关文章
留言与评论(共有 0 条评论)
   
验证码:
推荐文章
排行榜
Copyright ©2019-2022 Comsenz Inc.Powered by © 专利检索| 网站地图