Inference of genealogical relationships among individuals from genetic markers
Lead Research Organisation:
Zoological Society of London
Department Name: Institute of Zoology
Abstract
Individuals in a population may have among themselves various genealogical relationships (such as sib and parent-offspring relationships). Knowledge of these relationships is essential in many areas of research in behavioural, ecological and evolutionary genetics and in conservation biology. Although pedigree or ecological data can be used to determine relationships, such data are rarely available from most natural populations. In such cases, we can genotype individuals at a number of marker loci and infer their genealogical relationships from the pattern of similarity (allele sharing) among the multi-locus genotypes of the individuals. Powerful likelihood methods have been developed to partition a sample of individuals into distinctive genetic groups (defined by structured relationships) of variable sizes by maximising the likelihood of marker data. However, these methods are limited in application to either small problems in which the number of sampled individuals is small, or simple problems in which only sibships are inferred in a one-generation sample of individuals. Built on my previous work, this project aims to develop statistical methods for inferring parentage and sibships jointly in a large two-generation sample of individuals from marker data, and for assessing the uncertainties of the inferences. Typing errors and mutations in marker data will be accounted for in inferring relationships and be identified simultaneously by the methods. These extensions will make the group likelihood methods more flexible, robust and powerful in inferring relationships among individuals from marker data in practice. We will first develop the methodology, and then use extensive simulations to investigate the statistical properties of the method and its robustness when some assumptions are violated. Some empirical data sets with known relationships will be analysed by the proposed methods to further check their performance in realistic situations and to demonstrate their usefulness. The final goal is to develop a software package implementing the proposed group likelihood methods and to make it available free on the World Wide Web to the scientific community.
Technical Summary
Using genetic markers to infer the genealogical relationships (e.g. sibship) among individuals in a population is becoming an important tool in ecology and evolutionary and conservation biology. Powerful group likelihood methods have been developed to partition a sample of individuals into distinctive genetic groups (defined by one or more types of relationships organised in a specific structure) of variable sizes by maximising the likelihood of marker data. However, these methods are limited in application to either small problems in which the number of sampled individuals is small, or simple problems in which only sibships are inferred in a one-generation sample of individuals. Built on my previous work, this project aims to develop statistical methods for inferring parentage and sibships jointly in a large two-generation sample of individuals from marker data, and for assessing the uncertainties of the inferences. Typing errors and mutations in marker data will be accounted for in inferring relationships and be identified simultaneously by the methods. These extensions will make the group likelihood methods more flexible, robust and powerful in inferring relationships among individuals from marker data in practice. We will first develop the methodology, and then use extensive simulations to investigate the statistical properties of the method and its robustness when some assumptions are violated. Some empirical data sets with known relationships will be analysed by the proposed methods to further check their performance in realistic situations and to demonstrate their usefulness. The final goal is to develop a software package implementing the proposed group likelihood methods and to make it available free on the World Wide Web to the scientific community.
People |
ORCID iD |
Jinliang Wang (Principal Investigator) |
Publications
Jones O
(2010)
Molecular marker-based pedigrees for animal conservation biologists
in Animal Conservation
Jones OR
(2010)
COLONY: a program for parentage and sibship inference from multilocus genotype data.
in Molecular ecology resources
Jones OR
(2012)
A comparison of four methods for detecting weak genetic structure from marker data.
in Ecology and evolution
Wang J
(2009)
A new method for estimating effective population sizes from a single sample of multilocus genotypes.
in Molecular ecology
Wang J
(2012)
Estimating selfing rates from reconstructed pedigrees using multilocus genotype data.
in Molecular ecology
Wang J
(2013)
A simulation module in the computer program COLONY for sibship and parentage analysis.
in Molecular ecology resources
Wang J
(2012)
Computationally efficient sibship and parentage assignment from multilocus marker data.
in Genetics
Wang J
(2013)
An improvement on the maximum likelihood reconstruction of pedigrees from marker data.
in Heredity
Wang J
(2014)
Parentage and sibship inference from markers in polyploids.
in Molecular ecology resources
Wang J
(2007)
Parentage and sibship exclusions: higher statistical power with more family members.
in Heredity
Wang J
(2009)
Parentage and sibship inference from multilocus genotype data under polygamy.
in Genetics
Description | Knowledge of the familial relationships among individuals in a population is essential in many areas of research in behavioural, ecological and evolutionary genetics and in conservation biology. It is valuable, for example, in studies of the social behaviour/organization, mating systems, dispersal, isolation by distance and spatial genetic structure in natural populations. Unfortunately, familial relationships among individuals in most natural (wild) populations are unknown, and have to be inferred from genetic marker data. Previous marker based methods have strong assumptions (e.g. males and females cannot be both polygamous) and thus have limited applications in practice. The present project has developed a rigorous statistical population genetic method with fewer limiting assumptions. The power and statistical behaviour of the method has been checked by numerous simulations considering various scenarios of parameter combinations, and by some empirical datasets. The method has also been implemented in computer programs for all 3 major platforms (Windows, Linux, Mac) which are freely downloadable from our website http://www.zsl.org/science/software/colony. Two postdoc working on this project received training in population genetics, computer programming, data analysis, and others. |
Exploitation Route | The findings were summarized in a number of scientific papers published in mainstream genetic and ecology journals. The total citations of these papers are over 1000 times now. The software was published in our institute's website for free download. |
Sectors | Agriculture, Food and Drink,Environment |
URL | http://www.zsl.org/science/software/colony |
Description | Papers summarising our findings have been read and cited by the scientific research community. The software of the method developed in the project have been used by numerous researchers in analysing their data. |
First Year Of Impact | 2009 |
Sector | Agriculture, Food and Drink,Environment |
Impact Types | Economic,Policy & public services |
Description | estimating selfing rate from sibship analysis |
Organisation | University of British Columbia |
Country | Canada |
Sector | Academic/University |
PI Contribution | Conceived the original idea, writing simulation programs, conducting simulations |
Collaborator Contribution | providing several empirical datasets |
Impact | Wang, J., ELKASSABY, Y. A., & Ritland, K. (2012). Estimating selfing rates from reconstructed pedigrees using multilocus genotype data. Molecular ecology, 21(1), 100-116. |
Start Year | 2010 |
Description | parentage and sibship analysis in polyploid species |
Organisation | Michigan State University |
Country | United States |
Sector | Academic/University |
PI Contribution | Extended our analysis method to the case of polyploids, conducted simulations to check the accuracy of the extended method, analysed an empirical dataset provided by the collaborators |
Collaborator Contribution | Our partners contacted us requesting to extend our method, genotyped a sample of sturgeons with known relationships. |
Impact | Wang J & Scribner KT. (2014) Parentage and sibship inference from markers in polyploids. Molecular Ecology Resources 14: 541-553. |
Start Year | 2012 |
Title | COLONY |
Description | The software implements the statistical method developed in the project to infer parentage and sibship among individuals using their multilocus genotype data. |
Type Of Technology | Software |
Year Produced | 2009 |
Impact | the software has been widely applied by the ecologists and other biologists to infer parentage and sibship from marker data |
URL | http://www.zsl.org/science/software/colony |