High-Throughput Genome-Wide Genotyping To Optimize the Use of Natural Genetic Resources in the Grassland Species Perennial Ryegrass (Lolium perenne L.)

Thomas Keep; Jean Paul Sampoux; José Luis Blanco-Pastor; Klaus J. Dehmer; Matthew J. Hegarty; Thomas Ledauphin; Isabelle Litrico; Hilde Muylle; Isabel Roldán-Ruiz; Anna M. Roschanski; Tom Ruttink; Fabien Surault; Evelin Willner; Philippe Barre

doi:10.1534/g3.120.401491

High-Throughput Genome-Wide Genotyping To Optimize the Use of Natural Genetic Resources in the Grassland Species Perennial Ryegrass (Lolium perenne L.)

Thomas Keep, Jean Paul Sampoux, José Luis Blanco-Pastor, Klaus J. Dehmer, Matthew J. Hegarty, Thomas Ledauphin, Isabelle Litrico, Hilde Muylle, Isabel Roldán-Ruiz, Anna M. Roschanski, Tom Ruttink, Fabien Surault, Evelin Willner, Philippe Barre

Department of Life Sciences

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Abstract

The natural genetic diversity of agricultural species is an essential genetic resource for breeding programs aiming to improve their ecosystem and production services. A large natural ecotype diversity is usually available for most grassland species. This could be used to recombine natural climatic adaptations and agronomic value to create improved populations of grassland species adapted to future regional climates. However describing natural genetic resources can be long and costly. Molecular markers may provide useful information to help this task. This opportunity was investigated for Lolium perenne L., using a set of 385 accessions from the natural diversity of this species collected right across Europe and provided by genebanks of several countries. For each of these populations, genotyping provided the allele frequencies of 189,781 SNP markers. GWAS were implemented for over 30 agronomic and/or putatively adaptive traits recorded in three climatically contrasted locations (France, Belgium, Germany). Significant associations were detected for hundreds of markers despite a strong confounding effect of the genetic background; most of them pertained to phenology traits. It is likely that genetic variability in these traits has had an important contribution to environmental adaptation and ecotype differentiation. Genomic prediction models calibrated using natural diversity were found to be highly effective to describe natural populations for almost all traits as well as commercial synthetic populations for some important traits such as disease resistance, spring growth or phenological traits. These results will certainly be valuable information to help the use of natural genetic resources of other species.

Original language	English
Pages (from-to)	3347-3364
Number of pages	18
Journal	G3 (Bethesda, Md.)
Volume	10
Issue number	9
Early online date	21 Jul 2020
DOIs	https://doi.org/10.1534/g3.120.401491
Publication status	Published - 01 Sept 2020

Keywords

association study
forage species
genebank
genomic prediction
GenPred
GWAS
natural diversity
Shared data resources
Forage species
Prediction
Association study
Genebank
Natural diversity
Resources
Genomic
Shared data
Grassland
Lolium/genetics
Europe
Plant Breeding
Genotype
Genetic Variation
Ecosystem
Germany

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1534/g3.120.401491Licence: CC BY

3347.fullFinal published version, 2.97 MBLicence: CC BY

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Keep, T., Sampoux, J. P., Blanco-Pastor, J. L., Dehmer, K. J., Hegarty, M. J., Ledauphin, T., Litrico, I., Muylle, H., Roldán-Ruiz, I., Roschanski, A. M., Ruttink, T., Surault, F., Willner, E., & Barre, P. (2020). High-Throughput Genome-Wide Genotyping To Optimize the Use of Natural Genetic Resources in the Grassland Species Perennial Ryegrass (Lolium perenne L.). G3 (Bethesda, Md.), 10(9), 3347-3364. https://doi.org/10.1534/g3.120.401491

@article{66badd79ef804a3fa7f1d033d22c9ac9,

title = "High-Throughput Genome-Wide Genotyping To Optimize the Use of Natural Genetic Resources in the Grassland Species Perennial Ryegrass (Lolium perenne L.)",

abstract = "The natural genetic diversity of agricultural species is an essential genetic resource for breeding programs aiming to improve their ecosystem and production services. A large natural ecotype diversity is usually available for most grassland species. This could be used to recombine natural climatic adaptations and agronomic value to create improved populations of grassland species adapted to future regional climates. However describing natural genetic resources can be long and costly. Molecular markers may provide useful information to help this task. This opportunity was investigated for Lolium perenne L., using a set of 385 accessions from the natural diversity of this species collected right across Europe and provided by genebanks of several countries. For each of these populations, genotyping provided the allele frequencies of 189,781 SNP markers. GWAS were implemented for over 30 agronomic and/or putatively adaptive traits recorded in three climatically contrasted locations (France, Belgium, Germany). Significant associations were detected for hundreds of markers despite a strong confounding effect of the genetic background; most of them pertained to phenology traits. It is likely that genetic variability in these traits has had an important contribution to environmental adaptation and ecotype differentiation. Genomic prediction models calibrated using natural diversity were found to be highly effective to describe natural populations for almost all traits as well as commercial synthetic populations for some important traits such as disease resistance, spring growth or phenological traits. These results will certainly be valuable information to help the use of natural genetic resources of other species.",

keywords = "association study, forage species, genebank, genomic prediction, GenPred, GWAS, natural diversity, Shared data resources, Forage species, Prediction, Association study, Genebank, Natural diversity, Resources, Genomic, Shared data, Grassland, Lolium/genetics, Europe, Plant Breeding, Genotype, Genetic Variation, Ecosystem, Germany",

author = "Thomas Keep and Sampoux, {Jean Paul} and Blanco-Pastor, {Jos{\'e} Luis} and Dehmer, {Klaus J.} and Hegarty, {Matthew J.} and Thomas Ledauphin and Isabelle Litrico and Hilde Muylle and Isabel Rold{\'a}n-Ruiz and Roschanski, {Anna M.} and Tom Ruttink and Fabien Surault and Evelin Willner and Philippe Barre",

note = "Funding Information: T.Keep has received the support from the Nouvelle-Aquitaine administrative region (50% of funding) and from the Institut National de la Recherche Agronomique (25%: INRA – m{\'e}taprogramme ACCAF; 25%: BAP – Plant Biology and Breeding research division) in France. This work was funded in the frame of the project GrassLandscape awarded by the 2014 FACCE‐JPI ERA‐NET+ call Climate Smart Agriculture. Funding was granted by the 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. 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 the curators from the genebanks that provided perennial ryegrass seed samples for the needs of the project and staff from European agronomic research institutes who contributed to in situ collections in 2015. Perennial ryegrass is one of the plant species covered under the Multilateral System of the International Treaty on Plant Genetic Resources for Food and Agriculture. All genetic materials used in this study were made available to the authors after signature of a Standard Material Transfer Agreement (SMTA) by the provider and the recipient. Implementation and signature of a SMTA provides compliance with the provisions of the Nagoya Protocol for parties wishing to provide and receive genetic material under the Multilateral System. The authors thank greatly all the technical staff involved in the project from IBERS, ILVO, INRAE and IPK. The authors declare no conflict of interest. Funding Information: T.Keep has received the support from the Nouvelle-Aquitaine administrative region (50% of funding) and from the Institut National de la Recherche Agronomique (25%: INRA - m{\'e}taprogramme ACCAF; 25%: BAP - Plant Biology and Breeding research division) in France. This work was funded in the frame of the project GrassLandscape awarded by the 2014 FACCE‐JPI ERA‐NET+ call Climate Smart Agriculture. Funding was granted by the EC (grant agreement nº618105), 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. 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 the curators from the genebanks that provided perennial ryegrass seed samples for the needs of the project and staff from European agronomic research institutes who contributed to in situ collections in 2015. Perennial ryegrass is one of the plant species covered under the Multilateral System of the International Treaty on Plant Genetic Resources for Food and Agriculture. All genetic materials used in this study were made available to the authors after signature of a Standard Material Transfer Agreement (SMTA) by the provider and the recipient. Implementation and signature of a SMTA provides compliance with the provisions of the Nagoya Protocol for parties wishing to provide and receive genetic material under the Multilateral System. The authors thank greatly all the technical staff involved in the project from IBERS, ILVO, INRAE and IPK. The authors declare no conflict of interest. Publisher Copyright: Copyright {\textcopyright} 2020 Keep et al.",

year = "2020",

month = sep,

day = "1",

doi = "10.1534/g3.120.401491",

language = "English",

volume = "10",

pages = "3347--3364",

journal = "G3 (Bethesda, Md.)",

issn = "2160-1836",

publisher = "Genetics Society of America",

number = "9",

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Keep, T, Sampoux, JP, Blanco-Pastor, JL, Dehmer, KJ, Hegarty, MJ, Ledauphin, T, Litrico, I, Muylle, H, Roldán-Ruiz, I, Roschanski, AM, Ruttink, T, Surault, F, Willner, E & Barre, P 2020, 'High-Throughput Genome-Wide Genotyping To Optimize the Use of Natural Genetic Resources in the Grassland Species Perennial Ryegrass (Lolium perenne L.)', G3 (Bethesda, Md.), vol. 10, no. 9, pp. 3347-3364. https://doi.org/10.1534/g3.120.401491

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T1 - High-Throughput Genome-Wide Genotyping To Optimize the Use of Natural Genetic Resources in the Grassland Species Perennial Ryegrass (Lolium perenne L.)

AU - Keep, Thomas

AU - Sampoux, Jean Paul

AU - Blanco-Pastor, José Luis

AU - Dehmer, Klaus J.

AU - Hegarty, Matthew J.

AU - Ledauphin, Thomas

AU - Litrico, Isabelle

AU - Muylle, Hilde

AU - Roldán-Ruiz, Isabel

AU - Roschanski, Anna M.

AU - Ruttink, Tom

AU - Surault, Fabien

AU - Willner, Evelin

AU - Barre, Philippe

N1 - Funding Information: T.Keep has received the support from the Nouvelle-Aquitaine administrative region (50% of funding) and from the Institut National de la Recherche Agronomique (25%: INRA – métaprogramme ACCAF; 25%: BAP – Plant Biology and Breeding research division) in France. This work was funded in the frame of the project GrassLandscape awarded by the 2014 FACCE‐JPI ERA‐NET+ call Climate Smart Agriculture. Funding was granted by the 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. 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 the curators from the genebanks that provided perennial ryegrass seed samples for the needs of the project and staff from European agronomic research institutes who contributed to in situ collections in 2015. Perennial ryegrass is one of the plant species covered under the Multilateral System of the International Treaty on Plant Genetic Resources for Food and Agriculture. All genetic materials used in this study were made available to the authors after signature of a Standard Material Transfer Agreement (SMTA) by the provider and the recipient. Implementation and signature of a SMTA provides compliance with the provisions of the Nagoya Protocol for parties wishing to provide and receive genetic material under the Multilateral System. The authors thank greatly all the technical staff involved in the project from IBERS, ILVO, INRAE and IPK. The authors declare no conflict of interest. Funding Information: T.Keep has received the support from the Nouvelle-Aquitaine administrative region (50% of funding) and from the Institut National de la Recherche Agronomique (25%: INRA - métaprogramme ACCAF; 25%: BAP - Plant Biology and Breeding research division) in France. This work was funded in the frame of the project GrassLandscape awarded by the 2014 FACCE‐JPI ERA‐NET+ call Climate Smart Agriculture. Funding was granted by the EC (grant agreement nº618105), 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. 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 the curators from the genebanks that provided perennial ryegrass seed samples for the needs of the project and staff from European agronomic research institutes who contributed to in situ collections in 2015. Perennial ryegrass is one of the plant species covered under the Multilateral System of the International Treaty on Plant Genetic Resources for Food and Agriculture. All genetic materials used in this study were made available to the authors after signature of a Standard Material Transfer Agreement (SMTA) by the provider and the recipient. Implementation and signature of a SMTA provides compliance with the provisions of the Nagoya Protocol for parties wishing to provide and receive genetic material under the Multilateral System. The authors thank greatly all the technical staff involved in the project from IBERS, ILVO, INRAE and IPK. The authors declare no conflict of interest. Publisher Copyright: Copyright © 2020 Keep et al.

PY - 2020/9/1

Y1 - 2020/9/1

N2 - The natural genetic diversity of agricultural species is an essential genetic resource for breeding programs aiming to improve their ecosystem and production services. A large natural ecotype diversity is usually available for most grassland species. This could be used to recombine natural climatic adaptations and agronomic value to create improved populations of grassland species adapted to future regional climates. However describing natural genetic resources can be long and costly. Molecular markers may provide useful information to help this task. This opportunity was investigated for Lolium perenne L., using a set of 385 accessions from the natural diversity of this species collected right across Europe and provided by genebanks of several countries. For each of these populations, genotyping provided the allele frequencies of 189,781 SNP markers. GWAS were implemented for over 30 agronomic and/or putatively adaptive traits recorded in three climatically contrasted locations (France, Belgium, Germany). Significant associations were detected for hundreds of markers despite a strong confounding effect of the genetic background; most of them pertained to phenology traits. It is likely that genetic variability in these traits has had an important contribution to environmental adaptation and ecotype differentiation. Genomic prediction models calibrated using natural diversity were found to be highly effective to describe natural populations for almost all traits as well as commercial synthetic populations for some important traits such as disease resistance, spring growth or phenological traits. These results will certainly be valuable information to help the use of natural genetic resources of other species.

AB - The natural genetic diversity of agricultural species is an essential genetic resource for breeding programs aiming to improve their ecosystem and production services. A large natural ecotype diversity is usually available for most grassland species. This could be used to recombine natural climatic adaptations and agronomic value to create improved populations of grassland species adapted to future regional climates. However describing natural genetic resources can be long and costly. Molecular markers may provide useful information to help this task. This opportunity was investigated for Lolium perenne L., using a set of 385 accessions from the natural diversity of this species collected right across Europe and provided by genebanks of several countries. For each of these populations, genotyping provided the allele frequencies of 189,781 SNP markers. GWAS were implemented for over 30 agronomic and/or putatively adaptive traits recorded in three climatically contrasted locations (France, Belgium, Germany). Significant associations were detected for hundreds of markers despite a strong confounding effect of the genetic background; most of them pertained to phenology traits. It is likely that genetic variability in these traits has had an important contribution to environmental adaptation and ecotype differentiation. Genomic prediction models calibrated using natural diversity were found to be highly effective to describe natural populations for almost all traits as well as commercial synthetic populations for some important traits such as disease resistance, spring growth or phenological traits. These results will certainly be valuable information to help the use of natural genetic resources of other species.

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KW - forage species

KW - genebank

KW - genomic prediction

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KW - Shared data resources

KW - Forage species

KW - Prediction

KW - Association study

KW - Genebank

KW - Natural diversity

KW - Resources

KW - Genomic

KW - Shared data

KW - Grassland

KW - Lolium/genetics

KW - Europe

KW - Plant Breeding

KW - Genotype

KW - Genetic Variation

KW - Ecosystem

KW - Germany

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SN - 2160-1836

VL - 10

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EP - 3364

JO - G3 (Bethesda, Md.)

JF - G3 (Bethesda, Md.)

IS - 9

ER -

High-Throughput Genome-Wide Genotyping To Optimize the Use of Natural Genetic Resources in the Grassland Species Perennial Ryegrass (Lolium perenne L.)

Abstract

Keywords

UN SDGs

Access to Document

Permanent link

Other files and links

Fingerprint

Matthew Hegarty

FACCE ERA-NET+ GrassLandscape (Project Leader: Jean-Paul Sampoux, INRA, France)

C3G: Lolium and Trifolium genetics, genomics and germplasm development

Bioinformatics and genomic and phenomic platform development

Cite this

High-Throughput Genome-Wide Genotyping To Optimize the Use of Natural Genetic Resources in the Grassland Species Perennial Ryegrass (Lolium perenne L.)

Abstract

Keywords

UN SDGs

Access to Document

Permanent link

Other files and links

Fingerprint

Profiles

Matthew Hegarty

Projects

FACCE ERA-NET+ GrassLandscape (Project Leader: Jean-Paul Sampoux, INRA, France)

C3G: Lolium and Trifolium genetics, genomics and germplasm development

Bioinformatics and genomic and phenomic platform development

Cite this