Dr. Jinliang Wang

Curriculum Vitae:

• 2004-present: Senior Research Fellow, Institute of Zoology.
• 2000-2004: Research Fellow, Institute of Zoology.
• 1997-2000: Post-doctoral research fellow, Institute of Cell, Animal and Population Biology, University of Edinburgh.
• 1991-1997: Associate Professor in College of Animal Sciences, Zhejiang Agricultural University (China).
• 1991: PhD, Department of Animal Sciences, Northwestern Agricultural University (China).

Editorial Positions:

2009-2012, Member of Editorial Board, Journal of Evolutionary Biology
2009-, Member of Editorial Board, Computational and Mathematical Methods in Medicine
2013-, Member of Editorial Board, Heredity

Research Interests:

I am interested in developing population/quantitative genetics models and methods on analysis of empirical data to address issues in evolutionary and conservation biology and in the selective improvement of domesticated species. I use both analytical and stochastic simulation models and methods in my studies, which fall mainly into the following four areas.

• The inbreeding and genetic drift processes in small populations, subdivided populations (metapopulations), and applications to conservation biology. The rates of inbreeding and drift were predicted for populations of various structures (e.g. age, sex, spatial and genetic structures) and new breeding systems aimed at minimizing inbreeding were proposed. Currently, I am involved in developing methods and software for the genetic management of group-breeding captive populations without pedigree.
• The accumulation of deleterious mutations in small populations, its population level consequences (e.g. inbreeding depression, associative overdominance, background selection), and implications to evolution, speciation and conservation biology. The mutation accumulation process, its consequences, and the effectiveness of different strategies for purging deleterious mutations from small populations were investigated through simulations.
• Application of genetic markers in conservation biology. I developed maximum likelihood methods to estimate the effective size and migration rate of natural populations from temporal and spatial changes in marker allele frequencies, and to estimate admixture proportions of a hybrid population and the divergence times (or effective sizes) of the parental and hybrid populations from marker data. I also developed a moment estimator for pairwise relatedness between individuals based on genetic marker information, and a maximum likelihood method for assigning individuals in a sample to full-sib families nested within half-sib families (colonies) using these individuals' multi-locus genotypes without parental information. The software that implements these parameter estimation methods is available from this web site. The optimal utilisation of marker and pedigree information simultaneously in maximising the maintenance of genetic diversity in a small captive population was proposed and its effectiveness investigated.
• The maintenance of polygenic variation and its response to a bottleneck in population size and to artificial selection. This is supported by a BBSRC grant jointly held with Prof. W. G. Hill (Edinburgh University). We use accumulated empirical information on new mutations and segregating alleles affecting metric traits from various experiments to construct an improved pleiotropic model for explaining the maintenance of polygenic variation.

Software resulting from my research work:

• MLNE : A program for calculating maximum likelihood estimates of effective population size (Ne) and migration rate from temporal and spatial differences in marker allele frequencies
• CoDiDi : A program for estimating Gst, Hs and their correlation coefficient from marker data. It can be used to detect the presence or absence of mutational effect on the marker based genetic differentiation statistic Gst.
• LEADMIX : A program implementing a likelihood method for estimating the admixture proportions and genetic drift using data on genetic markers.
• COLONY : A program implementing a maximum likelihood method to assign individuals in a sample into full-sib families nested within half-sib families (colonies) using these individuals' multi-locus genotypes without parental information.
• KinInfor : A program that calculates the informativeness of markers in inferring pairwise relatedness or relationships.
• COANCESTRY : A program that implements 7 methods to estimate the pairwise relatedness between individuals and 4 methods to estimate individual inbreeding coefficients, using individual genotypes at a set of marker loci.
• KFinder : A program that estimates the number of populations represented by a sample of individuals.
• AgeStructure : A program that estimates the generation interval, effective size, variances and covariance's of lifetime number of offspring of an age structured population with overlapping generations.
• MicroErrorAnalyzer : A program for analysing the genotyping errors of microsatellites in parentage exclusion analysis.
• PopCluster : A program for population genetic structure analysis from a sample of multilocus genotypes.

Google Scholar Profile

Representative Publications: 

• Wang J, Santiago E, Carballero A (2016) Prediction and estimation of effective population size. Heredity 117:193-206.
• Wang J. (2016) Pedigrees or markers: Which are better in estimating relatedness and inbreeding coefficient? Theoretical Population Biology 107, 4-13.
• Wang J. (2016) Individual identification from genetic marker data: developments and accuracy comparisons of methods. Molecular Ecology Resources 16, 163-175.
• Wang J. (2015) Does Gst underestimate genetic differentiation from marker data? Molecular Ecology 24, 3546-3558.
• Wang J. (2014) Estimation of migration rates from marker based parentage analysis. Molecular Ecology 23: 3191–3213.
• Wang J. (2013) On the measurements of genetic differentiation among populations. Genetics Research 94: 275-289.
• Wang J, El-Kassaby Y, Ritland K. (2012) Estimating selfing rates from reconstructed pedigrees using multilocus genotype data. Molecular Ecology 21: 100-116.
• Wang J. (2012) Computationally efficient sibship and parentage assignment from multilocus marker data. Genetics 191: 183-94.
• Ramilo S, Wang J. (2012) The effect of close relatives on unsupervised Bayesian clustering algorithms in population genetic structure analysis.Molecular Ecology Resources 12: 873-884.
• Wang, J. (2011) COANCESTRY: A program for simulating, estimating and analysing relatedness and inbreeding coefficients. Molecular Ecology Resources11: 141–145.
• Wang, J., Brekke, P., Huchard, E., Knapp, L. A., Cowlishaw, G. (2010) Estimation of parameters of inbreeding and genetic drift in populations with overlapping generations. Evolution 64: 1704 – 1718.
• Wang, J. (2009) A new method for estimating effective population sizes from a single sample of multilocus genotypes. Molecular Ecology 18: 2148-2164.
• Wang, J. and Santure, A. W. (2009) Parentage and sibship inference from multilocus genotype data under polygamy. Genetics 181: 1579–1594.
• Wang, J. (2003) Maximum likelihood estimation of admixture proportions from genetic data. Genetics 164: 747-765.
• Wang, J. and Whitlock, M. C. (2003) Estimating effective population size and migration rates from genetic samples over space and time. Genetics 163: 429-446.
• Wang, J. (2002) An estimator for pairwise relatedness using molecular markers. Genetics 160: 1203-1215.

Research Group Members:

Current PhD students:
Lisa Signorile (Oct. 2009-) 
David Stanton (Oct. 2010-)

Former post-doctoral fellows:
Xusheng Zhang (2000-2003)
Anna W Santure (2006-2008)
Owen Jones (2009-2010)

Former PhD students: 
Elizabeth Boakes (2003-2006)
Olutolani Oni (2008-2012)
Johanna Fønss Nielsen (2008-2012)

Collaborators & Links:

• W.G. Hill, ICAPB, University of Edinburgh.
• A. Caballero, Dept. Bioquímica, Genética e Inmunología, Vigo University, Spain.
• N. Ryman, Division of Population Genetics, Stockholm University, Sweden.
• M. Whitlock, Department of Zoology, University of British Columbia, Canada.
• Bill Amos, Dept. Zoology, University of Cambridge.
• R.C. Lacy, Dept. Conservation Biology, Chicago Zoological Society, USA.