Data Production and Analysis in Population Genomics

Landscape genomics, based on the sampling of individuals genotyped for a large number of markers, may lead to the identi fi cation of regions of the genome correlated to selection pressures caused by the environment. In this chapter, we discuss sampling strategies to be used in a landscape genomics approach. We suggest that designs based on model-based strati fi cation using the climatic and/or biological spaces are in general more ef fi cient than designs based on the geographic space. More work is needed to identify designs that allow disentangling environmental selection pressures versus other processes such as range expansions or hierarchical population structure.

[1]  Pardis C Sabeti,et al.  Detecting recent positive selection in the human genome from haplotype structure , 2002, Nature.

[2]  Jean-François Zagury,et al.  Computation of haplotypes on SNPs subsets: advantage of the "global method" , 2006, BMC Genetics.

[3]  Michael Lynch,et al.  Estimation of Allele Frequencies From High-Coverage Genome-Sequencing Projects , 2009, Genetics.

[4]  B. Charlesworth,et al.  The effects of local selection, balanced polymorphism and background selection on equilibrium patterns of genetic diversity in subdivided populations. , 1997, Genetical research.

[5]  Pardis C Sabeti,et al.  Genome-wide detection and characterization of positive selection in human populations , 2007, Nature.

[6]  P. Donnelly,et al.  A Fine-Scale Map of Recombination Rates and Hotspots Across the Human Genome , 2005, Science.

[7]  Zhaoxia Yu,et al.  Simultaneous genotype calling and haplotype phasing improves genotype accuracy and reduces false-positive associations for genome-wide association studies. , 2009, American journal of human genetics.

[8]  M. Metzker.  Sequencing technologies — the next generation , 2010, Nature Reviews Genetics.

[9]  B. Weir,et al.  ESTIMATING F‐STATISTICS FOR THE ANALYSIS OF POPULATION STRUCTURE , 1984, Evolution; international journal of organic evolution.

[10]  Sharon R. Browning,et al.  Missing data imputation and haplotype phase inference for genome-wide association studies , 2008, Human Genetics.

[11]  B. Browning,et al.  Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. , 2007, American journal of human genetics.

[12]  A. Clark,et al.  Inference of haplotypes from PCR-amplified samples of diploid populations. , 1990, Molecular biology and evolution.

[13]  Mark Daly,et al.  Haploview: analysis and visualization of LD and haplotype maps , 2005, Bioinform..

[14]  Eran Halperin,et al.  Haplotype reconstruction from genotype data using Imperfect Phylogeny , 2004, Bioinform..

[15]  M. Beaumont.  Adaptation and speciation: what can F(st) tell us? , 2005, Trends in ecology & evolution.

[16]  R. Adkins,et al.  Comparison of the accuracy of methods of computational haplotype inference using a large empirical dataset , 2004, BMC Genetics.

[17]  Christian Schlötterer,et al.  Allele excess at neutrally evolving microsatellites and the implications for tests of neutrality , 2004, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[18]  P. Donnelly,et al.  A new statistical method for haplotype reconstruction from population data. , 2001, American journal of human genetics.

[19]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[20]  Nancy F. Hansen,et al.  Accurate Whole Human Genome Sequencing using Reversible Terminator Chemistry , 2008, Nature.

[21]  P. Donnelly,et al.  A Flexible and Accurate Genotype Imputation Method for the Next Generation of Genome-Wide Association Studies , 2009, PLoS genetics.

[22]  J. Kelly.  Geographical Variation in Selection, from Phenotypes to Molecules , 2006, The American Naturalist.

[23]  F. Tajima.  Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. , 1989, Genetics.

[24]  Zhaohui S. Qin,et al.  A comparison of phasing algorithms for trios and unrelated individuals. , 2006, American journal of human genetics.

[25]  John D. Storey,et al.  Statistical significance for genomewide studies , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[26]  Geoffrey B. Nilsen,et al.  Whole-Genome Patterns of Common DNA Variation in Three Human Populations , 2005, Science.

[27]  Paul Scheet,et al.  A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase. , 2006, American journal of human genetics.

[28]  M. Stephens,et al.  Accounting for Decay of Linkage Disequilibrium in Haplotype Inference and Missing-data Imputation , 2022 .

[29]  Radford M. Neal,et al.  Haplotype inference using a Bayesian Hidden Markov model , 2007, Genetic epidemiology.

[30]  Jean-François Zagury,et al.  Shape-IT: new rapid and accurate algorithm for haplotype inference , 2008, BMC Bioinformatics.

[31]  Jade Buchanan-Carter,et al.  Sequencing and de novo analysis of a coral larval transcriptome using 454 GSFlx , 2009, BMC Genomics.

[32]  J. Marden,et al.  Rapid transcriptome characterization for a nonmodel organism using 454 pyrosequencing , 2008, Molecular ecology.

[33]  K K Kidd,et al.  The accuracy of statistical methods for estimation of haplotype frequencies: an example from the CD4 locus. , 2000, American journal of human genetics.

[34]  Ron Shamir,et al.  A Block-Free Hidden Markov Model for Genotypes and Its Application to Disease Association , 2005, J. Comput. Biol..

[35]  Kevin R. Thornton,et al.  Recombination and the Properties of Tajima's D in the Context of Approximate-Likelihood Calculation , 2005, Genetics.

[36]  J. Kelly,et al.  Effects of Spatially Varying Selection on Nucleotide Diversity and Linkage Disequilibrium: Insights From Deer Mouse Globin Genes , 2008, Genetics.

[37]  K. Holsinger,et al.  Genetics in geographically structured populations: defining, estimating and interpreting FST , 2009, Nature Reviews Genetics.

[38]  Richard Durbin,et al.  A large genome center's improvements to the Illumina sequencing system , 2008, Nature Methods.

[39]  M. Pascual,et al.  Global Migration Dynamics Underlie Evolution and Persistence of Human Influenza A (H3N2) , 2010, PLoS pathogens.

[40]  A. Long,et al.  A wing expressed sequence tag resource for Bicyclus anynana butterflies, an evo-devo model , 2006, BMC Genomics.

[41]  W. Rice.  ANALYZING TABLES OF STATISTICAL TESTS , 1989, Evolution; international journal of organic evolution.

[42]  N. Schork,et al.  Accuracy of haplotype frequency estimation for biallelic loci, via the expectation-maximization algorithm for unphased diploid genotype data. , 2000, American journal of human genetics.

[43]  S. Narum.  Beyond Bonferroni: less conservative analyses for conservation genetics , 2006, Conservation Genetics.

[44]  Timothy T. Harkins,et al.  Transcriptome sequencing with the Genome Sequencer FLX system , 2008 .

[45]  Marta Matvienko,et al.  Genomics of Compositae weeds: EST libraries, microarrays, and evidence of introgression. , 2012, American journal of botany.

[46]  Ron Shamir,et al.  The Incomplete Perfect Phylogeny Haplotype Problem , 2005, J. Bioinform. Comput. Biol..

[47]  J. Marchini,et al.  Genotype imputation for genome-wide association studies , 2010, Nature Reviews Genetics.

[48]  Ryan D. Hernandez,et al.  Inferring the Joint Demographic History of Multiple Populations from Multidimensional SNP Frequency Data , 2009, PLoS genetics.

[49]  Peter Beerli,et al.  Unified Framework to Evaluate Panmixia and Migration Direction Among Multiple Sampling Locations , 2010, Genetics.

[50]  L. Excoffier,et al.  Detecting loci under selection in a hierarchically structured population , 2009, Heredity.

[51]  M. Slatkin.  Inbreeding coefficients and coalescence times. , 2007, Genetical research.

[52]  M. Stephens,et al.  Modeling linkage disequilibrium and identifying recombination hotspots using single-nucleotide polymorphism data. , 2003, Genetics.

[53]  P. Donnelly,et al.  A new multipoint method for genome-wide association studies by imputation of genotypes , 2007, Nature Genetics.