title: Genetic diversity and trait genomic prediction in a pea diversity panel.
abstract: 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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France. judith.burstin@dijon.inra.fr.
authors.forename: Judith
authors.initials: J
authors.lastname: Burstin
authors.affiliation: Clinical and Innovation Proteomic Platform (CLIPP), CHU Dijon, Université de Bourgogne, 1 rue du Professeur Marion, Dijon, 21000, France. pauline.salloignon@clipproteomic.fr.
authors.forename: Pauline
authors.initials: P
authors.lastname: Salloignon
authors.affiliation: UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France. marianne.martinello@dijon.inra.fr.
authors.forename: Marianne
authors.initials: M
authors.lastname: Chabert-Martinello
authors.affiliation: UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France. magninro@dijon.inra.fr.
authors.forename: Jean-Bernard
authors.initials: JB
authors.lastname: Magnin-Robert
authors.affiliation: UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France. mathieu.siol@dijon.inra.fr.
authors.forename: Mathieu
authors.initials: M
authors.lastname: Siol
authors.affiliation: UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France. francoise.jacquin@dijon.inra.fr.
authors.forename: Françoise
authors.initials: F
authors.lastname: Jacquin
authors.affiliation: UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France. chauveau@cng.fr.|Present address: US EPGV, IG-CEA, Centre National de Génotypage, 2 rue Gaston Crémieux, Evry Cedex, 91057, France. chauveau@cng.fr.
authors.forename: Aurélie
authors.initials: A
authors.lastname: Chauveau
authors.affiliation: UMR GDEC, Plateforme Gentyane, Clermont Ferrand, 63100, France. caroline.pont@clermont.inra.fr.
authors.forename: Caroline
authors.initials: C
authors.lastname: Pont
authors.affiliation: UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France. gregoire.aubert@dijon.inra.fr.
authors.forename: Grégoire
authors.initials: G
authors.lastname: Aubert
authors.affiliation: UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France. catherine.delaitre@dijon.inra.fr.
authors.forename: Catherine
authors.initials: C
authors.lastname: Delaitre
authors.affiliation: Clinical and Innovation Proteomic Platform (CLIPP), CHU Dijon, Université de Bourgogne, 1 rue du Professeur Marion, Dijon, 21000, France. caroline.truntzer@clipproteomic.fr.
authors.forename: Caroline
authors.initials: C
authors.lastname: Truntzer
authors.affiliation: UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France. gerard.Duc@dijon.inra.fr.
authors.forename: Gérard
authors.initials: G
authors.lastname: Duc
mesh_terms: D001499:Bayes Theorem; D016002:Discriminant Analysis; D005819:Genetic Markers; D014644:Genetic Variation; D018745:Genome, Plant; D005838:Genotype; D016018:Least-Squares Analysis; D016014:Linear Models; D018895:Microsatellite Repeats / Q000235:genetics; D018532:Pisum sativum / Q000235:genetics*; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D025341:Principal Component Analysis
chemical_list: D005819:Genetic Markers