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Genetic diversity and trait genomic prediction in a pea diversity panel
BACKGROUND: Pea (Pisum sativum L.), a major pulse crop grown for its protein-rich seeds, is an important component of agroecological cropping systems in diverse regions of the world. New breeding challenges imposed by global climate change and new regulations urge pea breeders to undertake more effi...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4355348/ https://www.ncbi.nlm.nih.gov/pubmed/25765216 http://dx.doi.org/10.1186/s12864-015-1266-1 |
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author | Burstin, Judith Salloignon, Pauline Chabert-Martinello, Marianne Magnin-Robert, Jean-Bernard Siol, Mathieu Jacquin, Françoise Chauveau, Aurélie Pont, Caroline Aubert, Grégoire Delaitre, Catherine Truntzer, Caroline Duc, Gérard |
author_facet | Burstin, Judith Salloignon, Pauline Chabert-Martinello, Marianne Magnin-Robert, Jean-Bernard Siol, Mathieu Jacquin, Françoise Chauveau, Aurélie Pont, Caroline Aubert, Grégoire Delaitre, Catherine Truntzer, Caroline Duc, Gérard |
author_sort | Burstin, Judith |
collection | PubMed |
description | BACKGROUND: Pea (Pisum sativum L.), a major pulse crop grown for its protein-rich seeds, is an important component of agroecological cropping systems in diverse regions of the world. New breeding challenges imposed by global climate change and new regulations urge pea breeders to undertake more efficient methods of selection and better take advantage of the large genetic diversity present in the Pisum sativum genepool. Diversity studies conducted so far in pea used Simple Sequence Repeat (SSR) and Retrotransposon Based Insertion Polymorphism (RBIP) markers. Recently, SNP marker panels have been developed that will be useful for genetic diversity assessment and marker-assisted selection. RESULTS: A collection of diverse pea accessions, including landraces and cultivars of garden, field or fodder peas as well as wild peas was characterised at the molecular level using newly developed SNP markers, as well as SSR markers and RBIP markers. The three types of markers were used to describe the structure of the collection and revealed different pictures of the genetic diversity among the collection. SSR showed the fastest rate of evolution and RBIP the slowest rate of evolution, pointing to their contrasted mode of evolution. SNP markers were then used to predict phenotypes -the date of flowering (BegFlo), the number of seeds per plant (Nseed) and thousand seed weight (TSW)- that were recorded for the collection. Different statistical methods were tested including the LASSO (Least Absolute Shrinkage ans Selection Operator), PLS (Partial Least Squares), SPLS (Sparse Partial Least Squares), Bayes A, Bayes B and GBLUP (Genomic Best Linear Unbiased Prediction) methods and the structure of the collection was taken into account in the prediction. Despite a limited number of 331 markers used for prediction, TSW was reliably predicted. CONCLUSION: The development of marker assisted selection has not reached its full potential in pea until now. This paper shows that the high-throughput SNP arrays that are being developed will most probably allow for a more efficient selection in this species. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1266-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4355348 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43553482015-03-12 Genetic diversity and trait genomic prediction in a pea diversity panel Burstin, Judith Salloignon, Pauline Chabert-Martinello, Marianne Magnin-Robert, Jean-Bernard Siol, Mathieu Jacquin, Françoise Chauveau, Aurélie Pont, Caroline Aubert, Grégoire Delaitre, Catherine Truntzer, Caroline Duc, Gérard BMC Genomics Research Article BACKGROUND: Pea (Pisum sativum L.), a major pulse crop grown for its protein-rich seeds, is an important component of agroecological cropping systems in diverse regions of the world. New breeding challenges imposed by global climate change and new regulations urge pea breeders to undertake more efficient methods of selection and better take advantage of the large genetic diversity present in the Pisum sativum genepool. Diversity studies conducted so far in pea used Simple Sequence Repeat (SSR) and Retrotransposon Based Insertion Polymorphism (RBIP) markers. Recently, SNP marker panels have been developed that will be useful for genetic diversity assessment and marker-assisted selection. RESULTS: A collection of diverse pea accessions, including landraces and cultivars of garden, field or fodder peas as well as wild peas was characterised at the molecular level using newly developed SNP markers, as well as SSR markers and RBIP markers. The three types of markers were used to describe the structure of the collection and revealed different pictures of the genetic diversity among the collection. SSR showed the fastest rate of evolution and RBIP the slowest rate of evolution, pointing to their contrasted mode of evolution. SNP markers were then used to predict phenotypes -the date of flowering (BegFlo), the number of seeds per plant (Nseed) and thousand seed weight (TSW)- that were recorded for the collection. Different statistical methods were tested including the LASSO (Least Absolute Shrinkage ans Selection Operator), PLS (Partial Least Squares), SPLS (Sparse Partial Least Squares), Bayes A, Bayes B and GBLUP (Genomic Best Linear Unbiased Prediction) methods and the structure of the collection was taken into account in the prediction. Despite a limited number of 331 markers used for prediction, TSW was reliably predicted. CONCLUSION: The development of marker assisted selection has not reached its full potential in pea until now. This paper shows that the high-throughput SNP arrays that are being developed will most probably allow for a more efficient selection in this species. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1266-1) contains supplementary material, which is available to authorized users. BioMed Central 2015-02-21 /pmc/articles/PMC4355348/ /pubmed/25765216 http://dx.doi.org/10.1186/s12864-015-1266-1 Text en © Burstin et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Burstin, Judith Salloignon, Pauline Chabert-Martinello, Marianne Magnin-Robert, Jean-Bernard Siol, Mathieu Jacquin, Françoise Chauveau, Aurélie Pont, Caroline Aubert, Grégoire Delaitre, Catherine Truntzer, Caroline Duc, Gérard Genetic diversity and trait genomic prediction in a pea diversity panel |
title | Genetic diversity and trait genomic prediction in a pea diversity panel |
title_full | Genetic diversity and trait genomic prediction in a pea diversity panel |
title_fullStr | Genetic diversity and trait genomic prediction in a pea diversity panel |
title_full_unstemmed | Genetic diversity and trait genomic prediction in a pea diversity panel |
title_short | Genetic diversity and trait genomic prediction in a pea diversity panel |
title_sort | genetic diversity and trait genomic prediction in a pea diversity panel |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4355348/ https://www.ncbi.nlm.nih.gov/pubmed/25765216 http://dx.doi.org/10.1186/s12864-015-1266-1 |
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