Canonical correlations reveal adaptive loci and phenotypic responses to climate in perennial ryegrass

Standard

Canonical correlations reveal adaptive loci and phenotypic responses to climate in perennial ryegrass. / Blanco-Pastor, José Luis; Barre, Philippe; Keep, Thomas; Ledauphin, Thomas; Escobar-Gutiérrez, Abraham; Roschanski, Anna Maria; Willner, Evelyn; Dehmer, Klaus J.; Hegarty, Matthew; Muylle, Hilde; Veeckman, Elisabeth; Vandepoele, Klaas; Ruttink, Tom; Roldán-Ruiz, Isabel; Manel, Stéphanie; Sampoux, Jean Paul.

In: Molecular Ecology Resources, 21.11.2020.

Research output: Contribution to journalArticlepeer-review

Harvard

Blanco-Pastor, JL, Barre, P, Keep, T, Ledauphin, T, Escobar-Gutiérrez, A, Roschanski, AM, Willner, E, Dehmer, KJ, Hegarty, M, Muylle, H, Veeckman, E, Vandepoele, K, Ruttink, T, Roldán-Ruiz, I, Manel, S & Sampoux, JP 2020, 'Canonical correlations reveal adaptive loci and phenotypic responses to climate in perennial ryegrass', Molecular Ecology Resources. https://doi.org/10.1111/1755-0998.13289

APA

Blanco-Pastor, J. L., Barre, P., Keep, T., Ledauphin, T., Escobar-Gutiérrez, A., Roschanski, A. M., Willner, E., Dehmer, K. J., Hegarty, M., Muylle, H., Veeckman, E., Vandepoele, K., Ruttink, T., Roldán-Ruiz, I., Manel, S., & Sampoux, J. P. (2020). Canonical correlations reveal adaptive loci and phenotypic responses to climate in perennial ryegrass. Molecular Ecology Resources. https://doi.org/10.1111/1755-0998.13289

Vancouver

Blanco-Pastor JL, Barre P, Keep T, Ledauphin T, Escobar-Gutiérrez A, Roschanski AM et al. Canonical correlations reveal adaptive loci and phenotypic responses to climate in perennial ryegrass. Molecular Ecology Resources. 2020 Nov 21. https://doi.org/10.1111/1755-0998.13289

Author

Blanco-Pastor, José Luis ; Barre, Philippe ; Keep, Thomas ; Ledauphin, Thomas ; Escobar-Gutiérrez, Abraham ; Roschanski, Anna Maria ; Willner, Evelyn ; Dehmer, Klaus J. ; Hegarty, Matthew ; Muylle, Hilde ; Veeckman, Elisabeth ; Vandepoele, Klaas ; Ruttink, Tom ; Roldán-Ruiz, Isabel ; Manel, Stéphanie ; Sampoux, Jean Paul. / Canonical correlations reveal adaptive loci and phenotypic responses to climate in perennial ryegrass. In: Molecular Ecology Resources. 2020.

Bibtex - Download

@article{917d431dd7f64bf8af4460aab171b8fb,
title = "Canonical correlations reveal adaptive loci and phenotypic responses to climate in perennial ryegrass",
abstract = "Germplasm from perennial ryegrass (Lolium perenne L.) natural populations is useful for breeding because of its adaptation to a wide range of climates. Climate-adaptive genes can be detected from associations between genotype, phenotype and climate but an integrated framework for the analysis of these three sources of information is lacking. We used two approaches to identify adaptive loci in perennial ryegrass and their effect on phenotypic traits. First, we combined Genome-Environment Association (GEA) and GWAS analyses. Then, we implemented a new test based on a Canonical Correlation Analysis (CANCOR) to detect adaptive loci. Furthermore, we improved the previous perennial ryegrass gene set by de novo gene prediction and functional annotation of 39,967 genes. GEA-GWAS revealed eight outlier loci associated with both environmental variables and phenotypic traits. CANCOR retrieved 633 outlier loci associated with two climatic gradients, characterized by cold-dry winter versus mild-wet winter and long rainy season versus long summer, and pointed out traits putatively conferring adaptation at the extremes of these gradients. Our CANCOR test also revealed the presence of both polygenic and oligogenic climatic adaptations. Our gene annotation revealed that 374 of the CANCOR outlier loci were positioned within or close to a gene. Co-association networks of outlier loci revealed a potential utility of CANCOR for investigating the interaction of genes involved in polygenic adaptations. The CANCOR test provides an integrated framework to analyse adaptive genomic diversity and phenotypic responses to environmental selection pressures that could be used to facilitate the adaptation of plant species to climate change.",
keywords = "adaptation, agriculture, climate change, ecological genetics, landscape genetics, quantitative genetics",
author = "Blanco-Pastor, {Jos{\'e} Luis} and Philippe Barre and Thomas Keep and Thomas Ledauphin and Abraham Escobar-Guti{\'e}rrez and Roschanski, {Anna Maria} and Evelyn Willner and Dehmer, {Klaus J.} and Matthew Hegarty and Hilde Muylle and Elisabeth Veeckman and Klaas Vandepoele and Tom Ruttink and Isabel Rold{\'a}n-Ruiz and St{\'e}phanie Manel and Sampoux, {Jean Paul}",
note = "Funding Information: This work was funded in the frame of the project awarded by the 2014 FACCE‐JPI ERA‐NET + call . Funding was granted by the European Commission (EC) (grant agreement nº 618105), by the Agence Nationale de la Recherche (ANR) and the Institut National de la Recherche Agronomique (INRA – m{\'e}taprogramme ACCAF) in France, the Biotechnology and Biological Sciences Research Council (BBSRC) in the United‐Kingdom, the Bundesantalt f{\"u}r Landwirtschaft und Ern{\"a}hrung (BLE) in Germany. J. L. Blanco‐Pastor has received the support of the EC in the framework of the Marie‐Curie FP7 COFUND People Program, through the award of an AgreenSkills + fellowship (grant agreement nº 609398). Support to J. L. Blanco‐Pastor came partially from R{\'e}G{\`a}Te, a project funded by the French Ministry of Agriculture through the 2015 CASDAR program. The computational resources (Stevin Supercomputer Infrastructure) and services used for genotype calling were provided by the VSC (Flemish Supercomputer Center), funded by Ghent University in Belgium, FWO and the Flemish Government – department EWI. The authors thank Michiel van Bel (VIB) for building the new PLAZA4.5 monocots instance that includes the novel gene set of perennial ryegrass and its functional annotations. We also thank two anonymous reviewers for their insightful comments that improved the quality of the manuscript. Climate data was processed by Milka Radojevik and Christian Pag{\'e} (CECI, Universit{\'e} de Toulouse, CNRS CERFACS http://cerfacs.fr ) from EURO4M‐MESAN and EUMETSAT CM SAF grids. GrassLandscape Climate Smart Agriculture Publisher Copyright: {\textcopyright} 2020 John Wiley & Sons Ltd",
year = "2020",
month = nov,
day = "21",
doi = "10.1111/1755-0998.13289",
language = "English",
journal = "Molecular Ecology Resources",
issn = "1755-098X",
publisher = "Wiley",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Canonical correlations reveal adaptive loci and phenotypic responses to climate in perennial ryegrass

AU - Blanco-Pastor, José Luis

AU - Barre, Philippe

AU - Keep, Thomas

AU - Ledauphin, Thomas

AU - Escobar-Gutiérrez, Abraham

AU - Roschanski, Anna Maria

AU - Willner, Evelyn

AU - Dehmer, Klaus J.

AU - Hegarty, Matthew

AU - Muylle, Hilde

AU - Veeckman, Elisabeth

AU - Vandepoele, Klaas

AU - Ruttink, Tom

AU - Roldán-Ruiz, Isabel

AU - Manel, Stéphanie

AU - Sampoux, Jean Paul

N1 - Funding Information: This work was funded in the frame of the project awarded by the 2014 FACCE‐JPI ERA‐NET + call . Funding was granted by the European Commission (EC) (grant agreement nº 618105), by the Agence Nationale de la Recherche (ANR) and the Institut National de la Recherche Agronomique (INRA – métaprogramme ACCAF) in France, the Biotechnology and Biological Sciences Research Council (BBSRC) in the United‐Kingdom, the Bundesantalt für Landwirtschaft und Ernährung (BLE) in Germany. J. L. Blanco‐Pastor has received the support of the EC in the framework of the Marie‐Curie FP7 COFUND People Program, through the award of an AgreenSkills + fellowship (grant agreement nº 609398). Support to J. L. Blanco‐Pastor came partially from RéGàTe, a project funded by the French Ministry of Agriculture through the 2015 CASDAR program. The computational resources (Stevin Supercomputer Infrastructure) and services used for genotype calling were provided by the VSC (Flemish Supercomputer Center), funded by Ghent University in Belgium, FWO and the Flemish Government – department EWI. The authors thank Michiel van Bel (VIB) for building the new PLAZA4.5 monocots instance that includes the novel gene set of perennial ryegrass and its functional annotations. We also thank two anonymous reviewers for their insightful comments that improved the quality of the manuscript. Climate data was processed by Milka Radojevik and Christian Pagé (CECI, Université de Toulouse, CNRS CERFACS http://cerfacs.fr ) from EURO4M‐MESAN and EUMETSAT CM SAF grids. GrassLandscape Climate Smart Agriculture Publisher Copyright: © 2020 John Wiley & Sons Ltd

PY - 2020/11/21

Y1 - 2020/11/21

N2 - Germplasm from perennial ryegrass (Lolium perenne L.) natural populations is useful for breeding because of its adaptation to a wide range of climates. Climate-adaptive genes can be detected from associations between genotype, phenotype and climate but an integrated framework for the analysis of these three sources of information is lacking. We used two approaches to identify adaptive loci in perennial ryegrass and their effect on phenotypic traits. First, we combined Genome-Environment Association (GEA) and GWAS analyses. Then, we implemented a new test based on a Canonical Correlation Analysis (CANCOR) to detect adaptive loci. Furthermore, we improved the previous perennial ryegrass gene set by de novo gene prediction and functional annotation of 39,967 genes. GEA-GWAS revealed eight outlier loci associated with both environmental variables and phenotypic traits. CANCOR retrieved 633 outlier loci associated with two climatic gradients, characterized by cold-dry winter versus mild-wet winter and long rainy season versus long summer, and pointed out traits putatively conferring adaptation at the extremes of these gradients. Our CANCOR test also revealed the presence of both polygenic and oligogenic climatic adaptations. Our gene annotation revealed that 374 of the CANCOR outlier loci were positioned within or close to a gene. Co-association networks of outlier loci revealed a potential utility of CANCOR for investigating the interaction of genes involved in polygenic adaptations. The CANCOR test provides an integrated framework to analyse adaptive genomic diversity and phenotypic responses to environmental selection pressures that could be used to facilitate the adaptation of plant species to climate change.

AB - Germplasm from perennial ryegrass (Lolium perenne L.) natural populations is useful for breeding because of its adaptation to a wide range of climates. Climate-adaptive genes can be detected from associations between genotype, phenotype and climate but an integrated framework for the analysis of these three sources of information is lacking. We used two approaches to identify adaptive loci in perennial ryegrass and their effect on phenotypic traits. First, we combined Genome-Environment Association (GEA) and GWAS analyses. Then, we implemented a new test based on a Canonical Correlation Analysis (CANCOR) to detect adaptive loci. Furthermore, we improved the previous perennial ryegrass gene set by de novo gene prediction and functional annotation of 39,967 genes. GEA-GWAS revealed eight outlier loci associated with both environmental variables and phenotypic traits. CANCOR retrieved 633 outlier loci associated with two climatic gradients, characterized by cold-dry winter versus mild-wet winter and long rainy season versus long summer, and pointed out traits putatively conferring adaptation at the extremes of these gradients. Our CANCOR test also revealed the presence of both polygenic and oligogenic climatic adaptations. Our gene annotation revealed that 374 of the CANCOR outlier loci were positioned within or close to a gene. Co-association networks of outlier loci revealed a potential utility of CANCOR for investigating the interaction of genes involved in polygenic adaptations. The CANCOR test provides an integrated framework to analyse adaptive genomic diversity and phenotypic responses to environmental selection pressures that could be used to facilitate the adaptation of plant species to climate change.

KW - adaptation

KW - agriculture

KW - climate change

KW - ecological genetics

KW - landscape genetics

KW - quantitative genetics

UR - http://www.scopus.com/inward/record.url?scp=85096749789&partnerID=8YFLogxK

U2 - 10.1111/1755-0998.13289

DO - 10.1111/1755-0998.13289

M3 - Article

C2 - 33098268

AN - SCOPUS:85096749789

JO - Molecular Ecology Resources

JF - Molecular Ecology Resources

SN - 1755-098X

ER -

Show download statistics
View graph of relations
Citation formats