Literature DB >> 16928801

Simultaneous estimation of mixing rates and genetic drift under successive sampling of genetic markers with application to the mud crab (Scylla paramamosain) in Japan.

Toshihide Kitakado1, Shuichi Kitada, Yasuhiro Obata, Hirohisa Kishino.   

Abstract

In stock enhancement programs, it is important to assess mixing rates of released individuals in stocks. For this purpose, genetic stock identification has been applied. The allele frequencies in a composite population are expressed as a mixture of the allele frequencies in the natural and released populations. The estimation of mixing rates is possible, under successive sampling from the composite population, on the basis of temporal changes in allele frequencies. The allele frequencies in the natural population may be estimated from those of the composite population in the preceding year. However, it should be noted that these frequencies can vary between generations due to genetic drift. In this article, we develop a new method for simultaneous estimation of mixing rates and genetic drift in a stock enhancement program. Numerical simulation shows that our procedure estimates the mixing rate with little bias. Although the genetic drift is underestimated when the amount of information is small, reduction of the bias is possible by analyzing multiple unlinked loci. The method was applied to real data on mud crab stocking, and the result showed a yearly variation in the mixing rate.

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Year:  2006        PMID: 16928801      PMCID: PMC1569702          DOI: 10.1534/genetics.106.056424

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  10 in total

1.  Monte Carlo evaluation of the likelihood for N(e) from temporally spaced samples.

Authors:  E C Anderson; E G Williamson; E A Thompson
Journal:  Genetics       Date:  2000-12       Impact factor: 4.562

2.  Using maximum likelihood to estimate population size from temporal changes in allele frequencies.

Authors:  E G Williamson; M Slatkin
Journal:  Genetics       Date:  1999-06       Impact factor: 4.562

Review 3.  Towards sustainability in world fisheries.

Authors:  Daniel Pauly; Villy Christensen; Sylvie Guénette; Tony J Pitcher; U Rashid Sumaila; Carl J Walters; R Watson; Dirk Zeller
Journal:  Nature       Date:  2002-08-08       Impact factor: 49.962

4.  Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies.

Authors:  Daniel Falush; Matthew Stephens; Jonathan K Pritchard
Journal:  Genetics       Date:  2003-08       Impact factor: 4.562

5.  Simultaneous detection of linkage disequilibrium and genetic differentiation of subdivided populations.

Authors:  Shuichi Kitada; Hirohisa Kishino
Journal:  Genetics       Date:  2004-08       Impact factor: 4.562

6.  An efficient Monte Carlo method for estimating Ne from temporally spaced samples using a coalescent-based likelihood.

Authors:  Eric C Anderson
Journal:  Genetics       Date:  2005-04-16       Impact factor: 4.562

7.  An integrated-likelihood method for estimating genetic differentiation between populations.

Authors:  Toshihide Kitakado; Shuichi Kitada; Hirohisa Kishino; Hans Julius Skaug
Journal:  Genetics       Date:  2006-06-04       Impact factor: 4.562

8.  Genetic drift and estimation of effective population size.

Authors:  M Nei; F Tajima
Journal:  Genetics       Date:  1981-07       Impact factor: 4.562

9.  A generalized approach for estimating effective population size from temporal changes in allele frequency.

Authors:  R S Waples
Journal:  Genetics       Date:  1989-02       Impact factor: 4.562

10.  Genetic effective size is three orders of magnitude smaller than adult census size in an abundant, Estuarine-dependent marine fish (Sciaenops ocellatus).

Authors:  Thomas F Turner; John P Wares; John R Gold
Journal:  Genetics       Date:  2002-11       Impact factor: 4.562

  10 in total
  3 in total

1.  The complete mitochondrial genome of the black mud crab, Scylla serrata (Crustacea: Brachyura: Portunidae) and its phylogenetic position among (pan)crustaceans.

Authors:  Amnuay Jondeung; Wirangrong Karinthanyakit; Jitlada Kaewkhumsan
Journal:  Mol Biol Rep       Date:  2012-10-11       Impact factor: 2.316

2.  Estimating effective population size from temporally spaced samples with a novel, efficient maximum-likelihood algorithm.

Authors:  Tin-Yu J Hui; Austin Burt
Journal:  Genetics       Date:  2015-03-05       Impact factor: 4.562

3.  Transcriptome analysis of the mud crab (Scylla paramamosain) by 454 deep sequencing: assembly, annotation, and marker discovery.

Authors:  Hongyu Ma; Chunyan Ma; Shujuan Li; Wei Jiang; Xincang Li; Yuexing Liu; Lingbo Ma
Journal:  PLoS One       Date:  2014-07-23       Impact factor: 3.240

  3 in total

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