Towards the identification of the loci of adaptive evolution

Pardo‐Díaz, Carolina; Salazar, Camilo; Jiggins, Chris D.

doi:10.1111/2041-210x.12324

Cited by 121 publications

(114 citation statements)

References 282 publications

(477 reference statements)

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“…Of course, this is unless the biological characteristics (for example size, behaviour, generation time) prevent the applicability of this experiment. Common gardens could possibly even replace the field work required to obtain tissue samples for genotyping: as we mentioned, it would still allow for population genomics approaches, while guaranteeing independent validation through the study of phenotypes (Pardo-Diaz et al, 2014;Rellstab et al, 2015), hence saving the cost of another genotyping campaign. As emphasised by Lepais and Bacles (2014), deciphering the genetic basis of local adaptation will only be accomplished by combining all the information yielded by dense marker panels, careful experiments and in situ sampling and observations.…”

Section: Resultsmentioning

confidence: 99%

“…If a strong adaptive signal is detected both using both using genome scan methods (that is, using genotypic and possibly environmental data) and the phenotypic data from a common garden experiment, that will constitute two independent piece of evidence favouring the hypothesis of local adaptation (Holderegger et al, 2008). As stated above, genome scan results need to be validated anyhow (Pardo-Diaz et al, 2014;Rellstab et al, 2015), and performing a common garden experiment is an elegant way to do so. We suggested that, whenever possible, combining genome scan approaches with common garden experiments is an efficient approach to the study of local adaptation.…”

Section: What Is the Use Of Common Garden Experiments In The Genomic Era?mentioning

confidence: 99%

“…Although this method can be quite powerful, it has some limitations (for example, false positives, no information on the adaptive phenotype). Several calls have been made to independently validate the results of such analyses (see Buehler et al, 2014 for a striking example), possibly using common garden or reciprocal transplant experiments (Holderegger et al, 2008;Pardo-Diaz et al, 2014;Rellstab et al, 2015). Following these lines, this perspective paper addresses three main questions: where does the common garden experiment stand in the genomic era?…”

Section: Introductionmentioning

confidence: 99%

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Common garden experiments in the genomic era: new perspectives and opportunities

Villemereuil¹,

Gaggiotti²,

Mouterde³

et al. 2015

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308

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The study of local adaptation is rendered difficult by many evolutionary confounding phenomena (for example, genetic drift and demographic history). When complex traits are involved in local adaptation, phenomena such as phenotypic plasticity further hamper evolutionary biologists to study the complex relationships between phenotype, genotype and environment. In this perspective paper, we suggest that the common garden experiment, specifically designed to deal with phenotypic plasticity, has a clear role to play in the study of local adaptation, even (if not specifically) in the genomic era. After a quick review of some high-throughput genotyping protocols relevant in the context of a common garden, we explore how to improve common garden analyses with dense marker panel data and recent statistical methods. We then show how combining approaches from population genomics and genome-wide association studies with the settings of a common garden can yield to a very efficient, thorough and integrative study of local adaptation. Especially, evidence from genomic (for example, genome scan) and phenotypic origins constitute independent insights into the possibility of local adaptation scenarios, and genome-wide association studies in the context of a common garden experiment allow to decipher the genetic bases of adaptive traits.

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Section: Resultsmentioning

confidence: 99%

Section: What Is the Use Of Common Garden Experiments In The Genomic Era?mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Common garden experiments in the genomic era: new perspectives and opportunities

Villemereuil¹,

Gaggiotti²,

Mouterde³

et al. 2015

Heredity

308

242

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“…Field experimentation, linkage and association mapping, forward and reverse genetics, candidate gene approaches, functional molecular genetics and modelling are also crucial approaches for understanding the genetic basis of local adaptation (Kawecki & Ebert 2004;Hereford 2009;Anderson et al 2011;Savolainen et al 2013;Pardo-Diaz et al 2015).…”

Section: )mentioning

confidence: 99%

Breaking RAD: An evaluation of the utility of restriction site associated DNA sequencing for genome scans of adaptation

et al. 2016

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Understanding how and why populations evolve is of fundamental importance to molecular ecology. Restriction site-associated DNA sequencing (RADseq), a popular reduced representation method, has ushered in a new era of genome-scale research for assessing population structure, hybridization, demographic history, phylogeography and migration. RADseq has also been widely used to conduct genome scans to detect loci involved in adaptive divergence among natural Correspondence: David B. Lowry, Fax: 517-353-1926; dlowry@msu.edu. Correction noteThe original advance online paper contained two errors associated with the calculation of the median density of RAD-seq tags in the survey of recent RAD-seq genome scan studies (Table S1). The first error was in the size of the assembled stickleback genome, which was reported as 0.53 Gbp, but should have been 0.46 Gbp. The second error was an accidental inversion of terms. These two mistakes contributed to an erroneous statement in the original abstract that the median density of RAD-tags across recent studies "was one marker per 3.96 megabases." The statement has been revised to read: "was 4.08 RAD-tag markers per megabase." Following these corrections, changes were made in the abstract and elsewhere in the paper to reflect a modified interpretation of the results, though we note the main arguments in the article are unaffected. Other minor modifications to the paper were made based upon suggestions by the editors of Molecular Ecology Resources. This version of the article, published as an "accepted article" on 12 November 2016 under DOI 10.1111/1755-0998.12635 replaces the original version of the article published on 12 September 2016 under DOI 10.1111/1755-0998.12596.The idea for the manuscript was conceived collectively by all authors during an NSF National Institute for Mathematical and Biological Synthesis (NIMBioS) working group. All authors contributed to the writing of the manuscript.Supporting Information Additional Supporting Information may be found in the online version of this article: Appendix S1 Supplementary R scripts for Breaking RAD. Table S1 Recent (January 2015 to April 2016) genome scan studies, which used RAD-seq for genotyping. Andrews et al. (2016). Generally, RADseq methods produce DNA libraries for high-throughput sequencing using restriction enzymes that cut at specific motifs throughout the genome. RADseq markers come in the form of RAD-tags, which are short-read sequences adjacent to restriction enzyme cut sites. Because many polymorphic markers are produced by RADseq, it has frequently been used successfully for population genetic analyses, including assessment of population structure, hybridization, demographic history, phylogeography and migration (Catchen et al. 2013;Cavender-Bares et al. 2015;Combosch & Vollmer 2015;Qi et al. 2015). Markers generated by RADseq have also been quite useful for constructing linkage maps and identifying quantitative trait loci (QTL;Pfender et al. 2011;Houston et al. 2012;Weber et al. 2013;Laporte et al. 2015...

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“…We examine whether ligand-coding genes are preferential targets for the generation of morphological evolution. In addition, we confront existing data to predictions that the corresponding allelic variation should be (1) potentially adaptive (Barrett and Hoekstra 2011;Pardo-Diaz et al 2015), (2) replicated over various phylogenetic levels (Gompel and Prud'homme 2009;Kopp 2009;Martin and Orgogozo 2013), and (3) cis-regulatory rather than coding (Prud'homme et al 2007;Carroll 2008;Stern and Orgogozo 2008;Liao et al 2010). …”

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confidence: 99%

Morphological Evolution Repeatedly Caused by Mutations in Signaling Ligand Genes

Martin

Courtier‐Orgogozo

2017

Diversity and Evolution of Butterfly Wing Patterns

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What types of genetic changes underlie evolution? Secreted signaling molecules (syn. ligands) can induce cells to switch states and thus largely contribute to the emergence of complex forms in multicellular organisms. It has been proposed that morphological evolution should preferentially involve changes in developmental toolkit genes such as signaling pathway components or transcription factors. However, this hypothesis has never been formally confronted to the bulk of accumulated experimental evidence. Here we examine the importance of ligandcoding genes for morphological evolution in animals. We use Gephebase (http:// www.gephebase.org), a database of genotype-phenotype relationships for evolutionary changes, and survey the genetic studies that mapped signaling genes as causative loci of morphological variation. To date, 19 signaling genes represent 20% of the cases where an animal morphological change has been mapped to a gene (80/391). This includes the signaling gene Agouti, which harbors multiple cis-regulatory alleles linked to color variation in vertebrates, contrasting with the effects of coding variation in its target, the melanocortin receptor MC1R. In sticklebacks, genetic mapping approaches have identified 4 signaling genes out of 14 loci associated with lake adaptations. Finally, in butterflies, a total of 18 allelic variants of the WntA Wnt-family ligand cause color pattern adaptations related to wing mimicry, both within and between species. We discuss possible hypotheses explaining these cases of natural replication (genetic parallelism) and conclude that signaling ligand loci are an important source of sequence variation underlying morphological change in nature.

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Towards the identification of the loci of adaptive evolution

Cited by 121 publications

References 282 publications

Common garden experiments in the genomic era: new perspectives and opportunities

Common garden experiments in the genomic era: new perspectives and opportunities

Breaking RAD: An evaluation of the utility of restriction site associated DNA sequencing for genome scans of adaptation

Morphological Evolution Repeatedly Caused by Mutations in Signaling Ligand Genes

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