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Genetic–geographic correlation revealed across a broad European ecotypic sample of perennial ryegrass (Lolium perenne) using array-based SNP genotyping

KEY MESSAGE: Publically available SNP array increases the marker density for genotyping of forage crop,Lolium perenne. Applied to 90 European ecotypes composed of 716 individuals identifies a significant genetic–geographic correlation. ABSTRACT: Grassland ecosystems are ubiquitous across temperate a...

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Detalles Bibliográficos
Autores principales: Blackmore, T., Thomas, I., McMahon, R., Powell, W., Hegarty, M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4572065/
https://www.ncbi.nlm.nih.gov/pubmed/26093611
http://dx.doi.org/10.1007/s00122-015-2556-3
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author Blackmore, T.
Thomas, I.
McMahon, R.
Powell, W.
Hegarty, M
author_facet Blackmore, T.
Thomas, I.
McMahon, R.
Powell, W.
Hegarty, M
author_sort Blackmore, T.
collection PubMed
description KEY MESSAGE: Publically available SNP array increases the marker density for genotyping of forage crop,Lolium perenne. Applied to 90 European ecotypes composed of 716 individuals identifies a significant genetic–geographic correlation. ABSTRACT: Grassland ecosystems are ubiquitous across temperate and tropical regions, totalling 37 % of the terrestrial land cover of the planet, and thus represent a global resource for understanding local adaptations to environment. However, genomic resources for grass species (outside cereals) are relatively poor. The advent of next-generation DNA sequencing and high-density SNP genotyping platforms enables the development of dense marker assays for population genetics analyses and genome-wide association studies. A high-density SNP marker resource (Illumina Infinium assay) for perennial ryegrass (Lolium perenne) was created and validated in a broad ecotype collection of 716 individuals sampled from 90 sites across Europe. Genetic diversity within and between populations was assessed. A strong correlation of geographic origin to genetic structure was found using principal component analysis, with significant correlation to longitude and latitude (P < 0.001). The potential of this array as a resource for studies of germplasm diversity and identifying traits underpinning adaptive variation is highlighted. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00122-015-2556-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-45720652015-09-23 Genetic–geographic correlation revealed across a broad European ecotypic sample of perennial ryegrass (Lolium perenne) using array-based SNP genotyping Blackmore, T. Thomas, I. McMahon, R. Powell, W. Hegarty, M Theor Appl Genet Original Paper KEY MESSAGE: Publically available SNP array increases the marker density for genotyping of forage crop,Lolium perenne. Applied to 90 European ecotypes composed of 716 individuals identifies a significant genetic–geographic correlation. ABSTRACT: Grassland ecosystems are ubiquitous across temperate and tropical regions, totalling 37 % of the terrestrial land cover of the planet, and thus represent a global resource for understanding local adaptations to environment. However, genomic resources for grass species (outside cereals) are relatively poor. The advent of next-generation DNA sequencing and high-density SNP genotyping platforms enables the development of dense marker assays for population genetics analyses and genome-wide association studies. A high-density SNP marker resource (Illumina Infinium assay) for perennial ryegrass (Lolium perenne) was created and validated in a broad ecotype collection of 716 individuals sampled from 90 sites across Europe. Genetic diversity within and between populations was assessed. A strong correlation of geographic origin to genetic structure was found using principal component analysis, with significant correlation to longitude and latitude (P < 0.001). The potential of this array as a resource for studies of germplasm diversity and identifying traits underpinning adaptive variation is highlighted. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00122-015-2556-3) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2015-06-21 2015 /pmc/articles/PMC4572065/ /pubmed/26093611 http://dx.doi.org/10.1007/s00122-015-2556-3 Text en © The Author(s) 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Paper
Blackmore, T.
Thomas, I.
McMahon, R.
Powell, W.
Hegarty, M
Genetic–geographic correlation revealed across a broad European ecotypic sample of perennial ryegrass (Lolium perenne) using array-based SNP genotyping
title Genetic–geographic correlation revealed across a broad European ecotypic sample of perennial ryegrass (Lolium perenne) using array-based SNP genotyping
title_full Genetic–geographic correlation revealed across a broad European ecotypic sample of perennial ryegrass (Lolium perenne) using array-based SNP genotyping
title_fullStr Genetic–geographic correlation revealed across a broad European ecotypic sample of perennial ryegrass (Lolium perenne) using array-based SNP genotyping
title_full_unstemmed Genetic–geographic correlation revealed across a broad European ecotypic sample of perennial ryegrass (Lolium perenne) using array-based SNP genotyping
title_short Genetic–geographic correlation revealed across a broad European ecotypic sample of perennial ryegrass (Lolium perenne) using array-based SNP genotyping
title_sort genetic–geographic correlation revealed across a broad european ecotypic sample of perennial ryegrass (lolium perenne) using array-based snp genotyping
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4572065/
https://www.ncbi.nlm.nih.gov/pubmed/26093611
http://dx.doi.org/10.1007/s00122-015-2556-3
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