Senior Research Fellow
Area of work
Bringing threatened species back from the brink of extinction
Monitoring genetic management of endangered species
Contact details

Institute of Zoology
Zoological Society of London
Regent's Park
United Kingdom

Google Scholar

Dr Jinliang Wang's work aims to address the global conservation challenge 'Bringing threatened species back from the brink of extinction'. 

Work Specialisms

As a population geneticist, Jinliang is interested in modelling the genetic processes (e.g. drift, inbreeding and their associated impacts on fitness, survival and adaptation) in small fragmented populations; in designing, evaluating and monitoring genetic management of in situ or ex situ populations of endangered species for conserving the genetic diversity; in developing rigorous statistical methods and software to analyse genetic marker data for understanding the historical and current population demography; and in the conservation genetics studies of various endangered species (e.g. Sumatra tigers, giant pandas) and the population genetics and evolutionary genetics studies of invasive species (e.g. grey squirrels in Europe, and alpine newts in the UK). 

What global conservation challenge does Dr Jinliang Wang's work aim to address? 

In modelling the genetic processes in small or fragmented populations, we are interested, for example, in the accumulation by genetic drift and the purging by natural selection of deleterious mutations and the consequences on the fitness and survival of populations in the short term and in the long run. The modelling work has direct implications for conservation management of endangered species, especially for the minimum population size suitable for population survival. 

In designing, evaluating and monitoring genetic management of endangered species, we are interested, for example, in the impact of population fragmentation on the maintenance of genetic diversity and fitness. We have investigated the optimal level of gene flow among fragmented populations, evaluated the impact of supportive breeding on maintaining the genetic variation in wild populations, and investigated the genetic managements of group breeding populations in captivity without individual pedigrees.

In developing statistical methods and software for genetic marker data analyses, we proposed novel methods to infer the historical and current effective population size, migration rates, relatedness and relationship among individuals, and the admixture and hybridisation of populations. These methods were implemented in software packages posted on ZSL websites for free download and use.

In the conservation genetics studies of endangered species such as Sumatra tigers, Okapis and giant pandas, we used non-invasive samples (faeces or confiscated skins) to investigate the population densities, migration and structure. 

Professional history

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).
Representative Publications
  • Wang J (2022) Fast and accurate population admixture inference from genotype data from a few microsatellites to millions of SNPs. Heredity 129: 79–92.
  • Wang J (2022) A joint likelihood estimator of relatedness and allele frequencies from a small sample of individuals. Methods in Ecology and Evolution 13: 2443-2462.
  • Trask AE, Ferrie GM, Wang J, Newland S, Canessa S, Moehrenschlager A, Laut M, Barnhart Duenas L, Ewen JG (2021) Multiple life-stage inbreeding depression impacts demography and extinction risk in an extinct-in-the-wild species. Scientific Reports 11: 1-10.
  • Santiago E, Novo I, Pardiñas AF, Saura M, Wang J, Caballero A (2020) Recent demographic history inferred by high-resolution analysis of linkage disequilibrium. Molecular Biology and Evolution 37: 3642-3653.
  • Hunter RD, Roseman EF, Sard NM, DeBruyne RL, Wang J, Scribner KT (2020) Genetic family reconstruction characterizes Lake Sturgeon use of newly constructed spawning habitat and larval dispersal. Transactions of the American Fisheries Society 149: 266-283.
  • 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 Resources 11: 141–145.
  • Wang J, Brekke P, Huchard E, Knapp LA, 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, Santure AW (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, Whitlock MC (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.
Software resulting from Jinliang Wang's 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 GstHs 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.
  • AuntExcPrb : A program calculating or simulating the probability of excluding N aunts from the maternity of a male by using L codominant marker data. 
  • 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.
  • EMIBD9 : A program for estimating the 9 IBD coefficients of each dyad in a sample from their genotype data.
  • PopCluster : A program for population genetic structure analysis from a sample of multilocus genotypes.