Association mapping of morphological traits in wild and captive zebra finches: reliable within, but not between populations

Identifying causal genetic variants underlying heritable phenotypic variation is a long‐standing goal in evolutionary genetics. We previously identified several quantitative trait loci (QTL) for five morphological traits in a captive population of zebra finches (Taeniopygia guttata) by whole‐genome linkage mapping. We here follow up on these studies with the aim to narrow down on the quantitative trait variants (QTN) in one wild and three captive populations. First, we performed an association study using 672 single nucleotide polymorphisms (SNPs) within candidate genes located in the previously identified QTL regions in a sample of 939 wild‐caught zebra finches. Then, we validated the most promising SNP–phenotype associations (n = 25 SNPs) in 5228 birds from four populations. Genotype–phenotype associations were generally weak in the wild population, where linkage disequilibrium (LD) spans only short genomic distances. In contrast, in captive populations, where LD blocks are large, apparent SNP effects on morphological traits (i.e. associations) were highly repeatable with independent data from the same population. Most of those SNPs also showed significant associations with the same trait in other captive populations, but the direction and magnitude of these effects varied among populations. This suggests that the tested SNPs are not the causal QTN but rather physically linked to them, and that LD between SNPs and causal variants differs between populations due to founder effects. While the identification of QTN remains challenging in nonmodel organisms, we illustrate that it is indeed possible to confirm the location and magnitude of QTL in a population with stable linkage between markers and causal variants.

[1]  B. Kempenaers,et al.  Fitness consequences of polymorphic inversions in the zebra finch genome , 2016, Genome Biology.

[2]  J. Wolf,et al.  Disruptive selection without genome‐wide evolution across a migratory divide , 2016, Molecular ecology.

[3]  H. Ellegren,et al.  Whole‐genome resequencing of extreme phenotypes in collared flycatchers highlights the difficulty of detecting quantitative trait loci in natural populations , 2016, Molecular ecology resources.

[4]  J. Slate,et al.  Replicated analysis of the genetic architecture of quantitative traits in two wild great tit populations , 2015, Molecular ecology.

[5]  Judy H. Cho,et al.  Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations , 2015, Nature Genetics.

[6]  Gil McVean,et al.  Stable recombination hotspots in birds , 2015, Science.

[7]  H. Ellegren,et al.  Genome-wide association mapping in a wild avian population identifies a link between genetic and phenotypic variation in a life-history trait , 2015, Proceedings of the Royal Society B: Biological Sciences.

[8]  J. Pemberton,et al.  Heterogeneity of genetic architecture of body size traits in a free‐living population , 2015, Molecular ecology.

[9]  C. Jiggins,et al.  Towards the identification of the loci of adaptive evolution , 2015, Methods in ecology and evolution.

[10]  B. Kempenaers,et al.  Quantifying realized inbreeding in wild and captive animal populations , 2015, Heredity.

[11]  D. Gianola,et al.  Genomic Heritability: What Is It? , 2014, PLoS genetics.

[12]  D. Balding,et al.  Relatedness in the post-genomic era: is it still useful? , 2014, Nature Reviews Genetics.

[13]  Heather J. Cordell,et al.  Comparison of Methods to Account for Relatedness in Genome-Wide Association Studies with Family-Based Data , 2014, PLoS genetics.

[14]  H. Schielzeth,et al.  Challenges and prospects in genome‐wide quantitative trait loci mapping of standing genetic variation in natural populations , 2014, Annals of the New York Academy of Sciences.

[15]  Shaun M. Purcell,et al.  Statistical power and significance testing in large-scale genetic studies , 2014, Nature Reviews Genetics.

[16]  S. Kerje,et al.  The role of pleiotropy and linkage in genes affecting a sexual ornament and bone allocation in the chicken , 2014, Molecular ecology.

[17]  J. Slate,et al.  Molecular quantitative genetics , 2014 .

[18]  Peter M Visscher,et al.  Explaining additional genetic variation in complex traits. , 2014, Trends in genetics : TIG.

[19]  P. Visscher,et al.  Advantages and pitfalls in the application of mixed-model association methods , 2014, Nature Genetics.

[20]  Peggy Hall,et al.  The NHGRI GWAS Catalog, a curated resource of SNP-trait associations , 2013, Nucleic Acids Res..

[21]  K. Lohmueller The Impact of Population Demography and Selection on the Genetic Architecture of Complex Traits , 2013, PLoS genetics.

[22]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[23]  Robert L. Wolpert,et al.  Statistical Inference , 2019, Encyclopedia of Social Network Analysis and Mining.

[24]  T. Clutton‐Brock,et al.  Life history trade-offs at a single locus maintain sexually selected genetic variation , 2013, Nature.

[25]  J. Slate,et al.  Partitioning of genetic variation across the genome using multimarker methods in a wild bird population , 2013, Molecular ecology.

[26]  J. Slate FROM BEAVIS TO BEAK COLOR: A SIMULATION STUDY TO EXAMINE HOW MUCH QTL MAPPING CAN REVEAL ABOUT THE GENETIC ARCHITECTURE OF QUANTITATIVE TRAITS , 2013, Evolution; international journal of organic evolution.

[27]  David Levine,et al.  GWASTools: an R/Bioconductor package for quality control and analysis of genome-wide association studies , 2012, Bioinform..

[28]  David Levine,et al.  A high-performance computing toolset for relatedness and principal component analysis of SNP data , 2012, Bioinform..

[29]  M. Wolak nadiv : an R package to create relatedness matrices for estimating non‐additive genetic variances in animal models , 2012 .

[30]  B. Kempenaers,et al.  QTL and quantitative genetic analysis of beak morphology reveals patterns of standing genetic variation in an Estrildid finch , 2012, Molecular ecology.

[31]  S. Griffith,et al.  Conspecific attraction and nest site selection in a nomadic species, the zebra finch , 2012 .

[32]  Eleazar Eskin,et al.  Improved linear mixed models for genome-wide association studies , 2012, Nature Methods.

[33]  B. Kempenaers,et al.  QTL linkage mapping of wing length in zebra finch using genome‐wide single nucleotide polymorphisms markers , 2012, Molecular ecology.

[34]  B. Kempenaers,et al.  QTL LINKAGE MAPPING OF ZEBRA FINCH BEAK COLOR SHOWS AN OLIGOGENIC CONTROL OF A SEXUALLY SELECTED TRAIT , 2012, Evolution; international journal of organic evolution.

[35]  M. Rockman THE QTN PROGRAM AND THE ALLELES THAT MATTER FOR EVOLUTION: ALL THAT'S GOLD DOES NOT GLITTER , 2012, Evolution; international journal of organic evolution.

[36]  Wolfgang Forstmeier,et al.  Women have Relatively Larger Brains than Men: A Comment on the Misuse of General Linear Models in the Study of Sexual Dimorphism , 2011, Anatomical record.

[37]  J. Slate,et al.  Genome‐wide association mapping identifies the genetic basis of discrete and quantitative variation in sexual weaponry in a wild sheep population , 2011, Molecular ecology.

[38]  M. Morgante,et al.  Nucleotide diversity and linkage disequilibrium in Populus nigra cinnamyl alcohol dehydrogenase (CAD4) gene , 2011, Tree Genetics & Genomes.

[39]  B. Kempenaers,et al.  A polymorphism in the oestrogen receptor gene explains covariance between digit ratio and mating behaviour , 2010, Proceedings of the Royal Society B: Biological Sciences.

[40]  M. DePristo,et al.  The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. , 2010, Genome research.

[41]  P. Visscher,et al.  Common SNPs explain a large proportion of heritability for human height , 2011 .

[42]  Nilanjan Chatterjee,et al.  Estimation of effect size distribution from genome-wide association studies and implications for future discoveries , 2010, Nature Genetics.

[43]  J. Slate,et al.  Genome mapping in intensively studied wild vertebrate populations. , 2010, Trends in genetics : TIG.

[44]  Albert J. Vilella,et al.  The genome of a songbird , 2010, Nature.

[45]  B. Kempenaers,et al.  The recombination landscape of the zebra finch Taeniopygia guttata genome. , 2010, Genome research.

[46]  Andreas Ziegler,et al.  A Statistical Approach to Genetic Epidemiology: With Access to E-Learning Platform by Friedrich Pahlke , 2010 .

[47]  H. Schielzeth Simple means to improve the interpretability of regression coefficients , 2010 .

[48]  D Gianola,et al.  Technical note: an R package for fitting generalized linear mixed models in animal breeding. , 2010, Journal of animal science.

[49]  Erik Matthysen,et al.  Association between DRD4 gene polymorphism and personality variation in great tits: a test across four wild populations , 2010, Molecular ecology.

[50]  A. McRae,et al.  Horn type and horn length genes map to the same chromosomal region in Soay sheep , 2010, Heredity.

[51]  Aaron R. Quinlan,et al.  Bioinformatics Applications Note Genome Analysis Bedtools: a Flexible Suite of Utilities for Comparing Genomic Features , 2022 .

[52]  Peter Kraft,et al.  Replication in genome-wide association studies. , 2009, Statistical science : a review journal of the Institute of Mathematical Statistics.

[53]  Vivian G. Cheung,et al.  Genetics of human gene expression: mapping DNA variants that influence gene expression , 2009, Nature Reviews Genetics.

[54]  E. Stone,et al.  The genetics of quantitative traits: challenges and prospects , 2009, Nature Reviews Genetics.

[55]  Jules Hernández-Sánchez,et al.  A web application to perform linkage disequilibrium and linkage analyses on a computational grid , 2009, Bioinform..

[56]  Richard Durbin,et al.  Sequence analysis Fast and accurate short read alignment with Burrows – Wheeler transform , 2009 .

[57]  Jonathan Flint,et al.  Genetic architecture of quantitative traits in mice, flies, and humans. , 2009, Genome research.

[58]  S. Edwards,et al.  Nucleotide Variation, Linkage Disequilibrium and Founder-Facilitated Speciation in Wild Populations of the Zebra Finch (Taeniopygia guttata) , 2009, Genetics.

[59]  Liuda Ziaugra,et al.  SNP Genotyping Using the Sequenom MassARRAY iPLEX Platform , 2009, Current protocols in human genetics.

[60]  J. Slate,et al.  Gene mapping in the wild with SNPs: guidelines and future directions , 2009, Genetica.

[61]  A. Ziegler,et al.  A Genotype-Based Approach to Assessing the Association between Single Nucleotide Polymorphisms , 2008, Human Heredity.

[62]  S. Griffith,et al.  Use of nest-boxes by the Zebra Finch (Taeniopygia guttata): implications for reproductive success and research , 2008 .

[63]  P. VanRaden,et al.  Efficient methods to compute genomic predictions. , 2008, Journal of dairy science.

[64]  David L Stern,et al.  The Loci of Evolution: How Predictable is Genetic Evolution? , 2008, Evolution; international journal of organic evolution.

[65]  Eden R Martin,et al.  A multiple testing correction method for genetic association studies using correlated single nucleotide polymorphisms , 2008, Genetic epidemiology.

[66]  J. Slate,et al.  A Linkage Map of the Zebra Finch Taeniopygia guttata Provides New Insights Into Avian Genome Evolution , 2008, Genetics.

[67]  W. G. Hill,et al.  Heritability in the genomics era — concepts and misconceptions , 2008, Nature Reviews Genetics.

[68]  D. Heckerman,et al.  Efficient Control of Population Structure in Model Organism Association Mapping , 2008, Genetics.

[69]  Shuhong Zhao,et al.  Candidate Gene Identification Approach: Progress and Challenges , 2007, International journal of biological sciences.

[70]  B. Kempenaers,et al.  Genetic variation and differentiation in captive and wild zebra finches (Taeniopygia guttata) , 2007, Molecular ecology.

[71]  H. Schielzeth,et al.  Intrasexual competition in zebra finches, the role of beak colour and body size , 2007, Animal Behaviour.

[72]  J. Haines,et al.  SNPs in Multi-Species Conserved Sequences (MCS) as useful markers in association studies: a practical approach , 2007, BMC Genomics.

[73]  P. Donnelly,et al.  Replicating genotype–phenotype associations , 2007, Nature.

[74]  Simon C. Potter,et al.  Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls , 2007, Nature.

[75]  Kees van Oers,et al.  Drd4 gene polymorphisms are associated with personality variation in a passerine bird , 2007, Proceedings of the Royal Society B: Biological Sciences.

[76]  D. Balding A tutorial on statistical methods for population association studies , 2006, Nature Reviews Genetics.

[77]  I. König,et al.  A Statistical Approach to Genetic Epidemiology: Concepts and Applications , 2006 .

[78]  W. Forstmeier Quantitative genetics and behavioural correlates of digit ratio in the zebra finch , 2005, Proceedings of the Royal Society B: Biological Sciences.

[79]  R W Doerge,et al.  Biased estimators of quantitative trait locus heritability and location in interval mapping , 2005, Heredity.

[80]  J. Slate,et al.  INVITED REVIEW: Quantitative trait locus mapping in natural populations: progress, caveats and future directions , 2004, Molecular ecology.

[81]  Colin N. Dewey,et al.  Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution , 2004, Nature.

[82]  Dmitri V Zaykin,et al.  Bounds and normalization of the composite linkage disequilibrium coefficient , 2004, Genetic epidemiology.

[83]  M. Feder,et al.  Evolutionary and ecological functional genomics , 2003, Nature Reviews Genetics.

[84]  D Bentley,et al.  Highly parallel SNP genotyping. , 2003, Cold Spring Harbor symposia on quantitative biology.

[85]  J. Nadeau,et al.  Finding Genes That Underlie Complex Traits , 2002, Science.

[86]  R. Myers,et al.  Candidate-gene approaches for studying complex genetic traits: practical considerations , 2002, Nature Reviews Genetics.

[87]  B. Grant,et al.  Unpredictable Evolution in a 30-Year Study of Darwin's Finches , 2002, Science.

[88]  W. J. Kent,et al.  BLAT--the BLAST-like alignment tool. , 2002, Genome research.

[89]  Jeffrey Ross-Ibarra,et al.  Genetic Data Analysis II. Methods for Discrete Population Genentic Data , 2002 .

[90]  L. Kruglyak,et al.  Patterns of linkage disequilibrium in the human genome , 2002, Nature Reviews Genetics.

[91]  Robin Thompson,et al.  ASREML user guide release 1.0 , 2002 .

[92]  J Blangero,et al.  Large upward bias in estimation of locus-specific effects from genomewide scans. , 2001, American journal of human genetics.

[93]  T. Mackay The genetic architecture of quantitative traits. , 2001, Annual review of genetics.

[94]  E S Buckler,et al.  Structure of linkage disequilibrium and phenotypic associations in the maize genome , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[95]  J. Pritchard,et al.  Linkage disequilibrium in humans: models and data. , 2001, American journal of human genetics.

[96]  L. Cardon,et al.  Association study designs for complex diseases , 2001, Nature Reviews Genetics.

[97]  B. Sheldon,et al.  Avian Quantitative Genetics , 2001 .

[98]  Kenneth Lange,et al.  Use of population isolates for mapping complex traits , 2000, Nature Reviews Genetics.

[99]  P M Visscher,et al.  Mapping quantitative trait loci in complex pedigrees: a two-step variance component approach. , 2000, Genetics.

[100]  F. Pirchner Genetics and Analysis of Quantitative Traits. , 2000 .

[101]  K. Roeder,et al.  Genomic Control for Association Studies , 1999, Biometrics.

[102]  W. Ewens Genetics and analysis of quantitative traits , 1999 .

[103]  L. Kruglyak Prospects for whole-genome linkage disequilibrium mapping of common disease genes , 1999, Nature Genetics.

[104]  J R O'Connell,et al.  PedCheck: a program for identification of genotype incompatibilities in linkage analysis. , 1998, American journal of human genetics.

[105]  R. Zann The Zebra Finch: A Synthesis of Field and Laboratory Studies , 1996 .

[106]  J. Witte,et al.  Genetic dissection of complex traits , 1996, Nature Genetics.

[107]  J. Witte,et al.  Genetic dissection of complex traits. , 1994, Nature genetics.

[108]  E. Lander,et al.  Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results , 1995, Nature Genetics.

[109]  R. Abramson,et al.  Detection of specific polymerase chain reaction product by utilizing the 5'----3' exonuclease activity of Thermus aquaticus DNA polymerase. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[110]  B S Weir,et al.  Variances and covariances of squared linkage disequilibria in finite populations. , 1988, Theoretical population biology.

[111]  K. Liang,et al.  Asymptotic Properties of Maximum Likelihood Estimators and Likelihood Ratio Tests under Nonstandard Conditions , 1987 .

[112]  W. G. Hill,et al.  Nonuniform recombination within the human beta-globin gene cluster. , 1986, American journal of human genetics.

[113]  W. D. Stirling,et al.  Enhancements to Aid Interpretation of Probability Plots , 1982 .

[114]  B. Weir Inferences about linkage disequilibrium. , 1979, Biometrics.

[115]  H. Grüneberg,et al.  Introduction to quantitative genetics , 1960 .