Genetic diversity and trait genomic prediction in a pea diversity panel

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 method...

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Veröffentlicht in:BMC genomics 2015-02, Vol.16 (1), p.105-105, Article 105
Hauptverfasser: 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
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container_issue 1
container_start_page 105
container_title BMC genomics
container_volume 16
creator 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
description 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. 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. 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.
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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.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>25765216</pmid><doi>10.1186/s12864-015-1266-1</doi><tpages>1</tpages><orcidid>https://orcid.org/0009-0006-0302-0842</orcidid><orcidid>https://orcid.org/0000-0002-1867-5730</orcidid><orcidid>https://orcid.org/0000-0002-4125-3499</orcidid><oa>free_for_read</oa></addata></record>
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source MEDLINE; DOAJ Directory of Open Access Journals; SpringerLink Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central Open Access; Springer Nature OA Free Journals; PubMed Central
subjects Bayes Theorem
Discriminant Analysis
Environmental Sciences
Genetic Markers
Genetic Variation
Genome, Plant
Genotype
Least-Squares Analysis
Life Sciences
Linear Models
Microsatellite Repeats - genetics
Phenotype
Pisum sativum - genetics
Polymorphism, Single Nucleotide
Principal Component Analysis
Vegetal Biology
title Genetic diversity and trait genomic prediction in a pea diversity panel
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