Combining experimental evolution with next-generation sequencing: a powerful tool to study adaptation from standing genetic variation

Evolve and resequence (E&R) is a new approach to investigate the genomic responses to selection during experimental evolution. By using whole genome sequencing of pools of individuals (Pool-Seq), this method can identify selected variants in controlled and replicable experimental settings. Reviewing the current state of the field, we show that E&R can be powerful enough to identify causative genes and possibly even single-nucleotide polymorphisms. We also discuss how the experimental design and the complexity of the trait could result in a large number of false positive candidates. We suggest experimental and analytical strategies to maximize the power of E&R to uncover the genotype–phenotype link and serve as an important research tool for a broad range of evolutionary questions.

[1]  F. Jiggins,et al.  Genome-Wide Association Studies Reveal a Simple Genetic Basis of Resistance to Naturally Coevolving Viruses in Drosophila melanogaster , 2012, PLoS genetics.

[2]  C. Schlötterer,et al.  Genome assembly and annotation of a Drosophila simulans strain from Madagascar , 2014, Molecular ecology resources.

[3]  John Novembre,et al.  Maximum Likelihood Estimation of Frequencies of Known Haplotypes from Pooled Sequence Data , 2012, Molecular biology and evolution.

[4]  A. Futschik,et al.  The Next Generation of Molecular Markers From Massively Parallel Sequencing of Pooled DNA Samples , 2010, Genetics.

[5]  B. Koseva,et al.  The Genomic Signal of Partial Sweeps in Mimulus guttatus , 2013, Genome biology and evolution.

[6]  L. Keller,et al.  Evolution under monogamy feminizes gene expression in Drosophila melanogaster , 2014, Nature Communications.

[7]  C. Schlötterer,et al.  Inference of chromosomal inversion dynamics from Pool-Seq data in natural and laboratory populations of Drosophila melanogaster , 2013, Molecular ecology.

[8]  Robert Kofler,et al.  Massive Habitat-Specific Genomic Response in D. melanogaster Populations during Experimental Evolution in Hot and Cold Environments , 2013, Molecular biology and evolution.

[9]  John Novembre,et al.  forqs: forward-in-time simulation of recombination, quantitative traits and selection , 2013, Bioinform..

[10]  Kevin R. Thornton,et al.  The Power to Detect Quantitative Trait Loci Using Resequenced, Experimentally Evolved Populations of Diploid, Sexual Organisms , 2014, Molecular biology and evolution.

[11]  Christopher J. R. Illingworth,et al.  Quantifying Selection Acting on a Complex Trait Using Allele Frequency Time Series Data , 2011, Molecular biology and evolution.

[12]  F. Hospital,et al.  Selective Sweep at a Quantitative Trait Locus in the Presence of Background Genetic Variation , 2008, Genetics.

[13]  Stefan Zoller,et al.  Validation of SNP Allele Frequencies Determined by Pooled Next-Generation Sequencing in Natural Populations of a Non-Model Plant Species , 2013, PloS one.

[14]  Antti Honkela,et al.  Gaussian process test for high-throughput sequencing time series: application to experimental evolution , 2014, Bioinform..

[15]  V. Hartenstein,et al.  Drosophila melanogaster , 2005 .

[16]  G. Bell.  Experimental evolution , 2008, Heredity.

[17]  C. Schlötterer,et al.  Adaptation of Drosophila to a novel laboratory environment reveals temporally heterogeneous trajectories of selected alleles , 2012, Molecular ecology.

[18]  Aaron M. Tarone,et al.  Population-Based Resequencing of Experimentally Evolved Populations Reveals the Genetic Basis of Body Size Variation in Drosophila melanogaster , 2011, PLoS genetics.

[19]  Ali Bashir,et al.  Experimental selection of hypoxia-tolerant Drosophila melanogaster , 2011, Proceedings of the National Academy of Sciences.

[20]  D. Charlesworth,et al.  High Nucleotide Polymorphism and Rapid Decay of Linkage Disequilibrium in Wild Populations of Caenorhabditis remanei , 2006, Genetics.

[21]  R. Terns,et al.  CRISPR-based technologies: prokaryotic defense weapons repurposed. , 2014, Trends in genetics : TIG.

[22]  Thomas L. Turner,et al.  Investigating Natural Variation in Drosophila Courtship Song by the Evolve and Resequence Approach , 2012, Genetics.

[23]  C. Schlötterer,et al.  Sequencing pools of individuals — mining genome-wide polymorphism data without big funding , 2014, Nature Reviews Genetics.

[24]  C. Schlötterer,et al.  Host adaptation to viruses relies on few genes with different cross-resistance properties , 2014, Proceedings of the National Academy of Sciences.

[25]  P. Keightley,et al.  The use of retrotransposons as markers for mapping genes responsible for fitness differences between related Drosophila melanogaster strains. , 1993, Genetical research.

[26]  K. Lindblad-Toh,et al.  Whole-genome resequencing reveals loci under selection during chicken domestication , 2010, Nature.

[27]  G. Glazko,et al.  Evolution of gene expression and expression plasticity in long‐term experimental populations of Drosophila melanogaster maintained under constant and variable ethanol stress , 2012, Molecular ecology.

[28]  F. Lemeunier,et al.  Mitotic and Polytene Chromosomes: Comparisons Between Drosophila Melanogaster and Drosophila Simulans , 2004, Genetica.

[29]  R. Lenski,et al.  Microbial genetics: Evolution experiments with microorganisms: the dynamics and genetic bases of adaptation , 2003, Nature Reviews Genetics.

[30]  I. Chelo,et al.  Evolution of Outcrossing in Experimental Populations of Caenorhabditis elegans , 2012, PloS one.

[31]  J. Novembre,et al.  Power Analysis of Artificial Selection Experiments Using Efficient Whole Genome Simulation of Quantitative Traits , 2014, Genetics.

[32]  C. Schlötterer,et al.  A Guide for the Design of Evolve and Resequencing Studies , 2013, Molecular biology and evolution.

[33]  T. Garland,et al.  Experimental Evolution: Concepts, Methods, and Applications of Selection Experiments , 2009 .

[34]  S. Nuzhdin,et al.  Promises and limitations of hitchhiking mapping. , 2013, Current opinion in genetics & development.

[35]  Thomas L. Turner,et al.  Combining genome-wide methods to investigate the genetic complexity of courtship song variation in Drosophila melanogaster. , 2013, Molecular biology and evolution.

[36]  J. M. Smith,et al.  “Haldane's Dilemma” and the Rate of Evolution , 1968, Nature.

[37]  Christian Schlötterer,et al.  Multi-locus Analysis of Genomic Time Series Data from Experimental Evolution , 2014, bioRxiv.

[38]  Mats E. Pettersson,et al.  Genome-Wide Effects of Long-Term Divergent Selection , 2010, PLoS genetics.

[39]  V. Bafna,et al.  Learning Natural Selection from the Site Frequency Spectrum , 2013, Genetics.

[40]  Kevin R. Thornton,et al.  A second-generation assembly of the Drosophila simulans genome provides new insights into patterns of lineage-specific divergence , 2013, Genome research.

[41]  C. Schlötterer,et al.  Experimental evolution reveals habitat-specific fitness dynamics among Wolbachia clades in Drosophila melanogaster , 2014, Molecular ecology.

[42]  K. Hughes,et al.  GENOMIC BASIS OF AGING AND LIFE‐HISTORY EVOLUTION IN DROSOPHILA MELANOGASTER , 2012, Evolution; international journal of organic evolution.

[43]  Kevin R. Thornton,et al.  Genome-wide analysis of a long-term evolution experiment with Drosophila , 2010, Nature.

[44]  Wusheng Liu,et al.  Advanced genetic tools for plant biotechnology , 2013, Nature Reviews Genetics.

[45]  P. L. Chang,et al.  Genomic changes under rapid evolution: selection for parasitoid resistance , 2014, Proceedings of the Royal Society B: Biological Sciences.

[46]  A. Long,et al.  Experimental evolution reveals natural selection on standing genetic variation , 2009, Nature Genetics.

[47]  Alan M. Moses,et al.  Revealing the genetic structure of a trait by sequencing a population under selection. , 2011, Genome research.

[48]  K. Weber.  Large genetic change at small fitness cost in large populations of Drosophila melanogaster selected for wind tunnel flight: rethinking fitness surfaces. , 1996, Genetics.

[49]  D. Gianola,et al.  A Genome-Wide Scan for Evidence of Selection in a Maize Population Under Long-Term Artificial Selection for Ear Number , 2013, Genetics.