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Carrillo-Perdomo E, Magnin-Robert JB, Raffiot B, Deulvot C, Floriot M, Lejeune-Hénaut I, Marget P, Burstin J, Tayeh N, Aubert G. A QTL approach in faba bean highlights the conservation of genetic control of frost tolerance among legume species. Front Plant Sci 2022; 13:970865. [PMID: 36340396 PMCID: PMC9627038 DOI: 10.3389/fpls.2022.970865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 09/28/2022] [Indexed: 06/16/2023]
Abstract
Frost is a major abiotic stress of winter type faba beans (Vica faba L.) and has adverse effects on crop yield. Climate change, far from reducing the incidence of frost events, is making these phenomena more and more common, severe, and prolonged. Despite the important interaction that the environment has in the tolerance of faba bean to frost, this trait seems to have good levels of heritability. Several QTLs for frost tolerance have already been reported, however, a more robust identification is needed to more precisely identify the genomic regions involved in faba bean tolerance to sub-zero temperatures. Several pea (Pisum sativum L.) and barrel medic (Medicago truncatula L.) frost tolerance QTLs appear to be conserved between these two species, furthering the hypothesis that the genetic control of frost tolerance in legume species might be more generally conserved. In this work, the QTL mapping in two faba bean recombinant inbred line (RIL) populations connected by a common winter-type parent has led to the identification of five genomic regions involved in the control of frost tolerance on linkage groups I, III, IV, and V. Among them, a major and robust QTL of great interest for marker-assisted selection was identified on the lower part of the long-arm of LGI. The synteny between the faba bean frost tolerance QTLs and those previously identified in other legume species such as barrel medic, pea or soybean highlighted at least partial conservation of the genetic control of frost tolerance among different faba bean genetic pools and legume species. Four novel RILs showing high and stable levels of tolerance and the ability to recover from freezing temperatures by accumulating frost tolerance QTLs are now available for breeding programs.
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Affiliation(s)
- Estefanía Carrillo-Perdomo
- Agroécologie, INRAE, Institut Agro, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, Dijon, France
- UMR AGAP Institut, Univ. Montpellier, CIRAD, INRAE, Institut Agro, San Giuliano, France
| | | | - Blandine Raffiot
- Agroécologie, INRAE, Institut Agro, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, Dijon, France
- Terres Inovia, Thiverval-Grignon, France
| | - Chrystel Deulvot
- Agroécologie, INRAE, Institut Agro, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, Dijon, France
| | | | - Isabelle Lejeune-Hénaut
- Département de génétique et protection des cultures, BioEcoAgro Joint Research Unit, INRAE, Université de Lille, Université de Liège, Université de Picardie Jules Verne, Estrées-Mons, France
| | - Pascal Marget
- Agroécologie, INRAE, Institut Agro, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, Dijon, France
- INRAE, UE115 Domaine Expérimental d’Epoisses, Dijon, France
| | - Judith Burstin
- Agroécologie, INRAE, Institut Agro, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, Dijon, France
| | - Nadim Tayeh
- Agroécologie, INRAE, Institut Agro, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, Dijon, France
| | - Grégoire Aubert
- Agroécologie, INRAE, Institut Agro, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, Dijon, France
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Dubois O, Allanic C, Charvet CL, Guégnard F, Février H, Théry-Koné I, Cortet J, Koch C, Bouvier F, Fassier T, Marcon D, Magnin-Robert JB, Peineau N, Courtot E, Huau C, Meynadier A, Enguehard-Gueiffier C, Neveu C, Boudesocque-Delaye L, Sallé G. Lupin (Lupinus spp.) seeds exert anthelmintic activity associated with their alkaloid content. Sci Rep 2019; 9:9070. [PMID: 31227784 PMCID: PMC6588613 DOI: 10.1038/s41598-019-45654-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 06/12/2019] [Indexed: 12/20/2022] Open
Abstract
The growing range of drug resistant parasitic nematode populations threatens the sustainability of ruminant farming worldwide. In this context, nutraceuticals, animal feed that provides necessary dietary requirements while ensuring parasite control, could contribute to increase farming sustainability in developed and low resource settings. In this study, we evaluated the anthelmintic potential of lupin seed extracts against the major ruminant trichostrongylids, Haemonchus contortus and Teladorsagia circumcincta. In vitro observations showed that seed extracts from commercially available lupin varieties could significantly but moderately inhibit larval migration. This anthelmintic effect was mediated by the seed alkaloid content and was potent against both fully susceptible and multidrug resistant H. contortus isolates as well as a susceptible T. circumcincta isolate. Analytical chemistry revealed a set of four lupanine and sparteine-derivatives with anthelmintic activity, and electrophysiology assays on recombinant nematode acetylcholine receptors suggested an antagonistic mode of action for lupin alkaloids. An in vivo trial in H. contortus infected lupin-fed ewes and goats failed to demonstrate any direct anthelmintic effect of crude lupin seeds but infected lupin-fed goats suffered significantly less parasite-mediated blood losses. Altogether, our findings suggest that the anthelmintic potential of lupin remains limited. However, the potent alkaloids identified could lead to the development of novel drugs or may be used in combination with current anthelmintics to improve their efficacy.
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Affiliation(s)
- O Dubois
- UMR1282 Infectiologie et Santé Publique, INRA, Université de Tours, F-37380, Nouzilly, France.,EA 7502 SIMBA, Université de Tours, Faculté de Pharmacie, F-37000, Tours, France
| | - C Allanic
- UMR1282 Infectiologie et Santé Publique, INRA, Université de Tours, F-37380, Nouzilly, France
| | - C L Charvet
- UMR1282 Infectiologie et Santé Publique, INRA, Université de Tours, F-37380, Nouzilly, France
| | - F Guégnard
- UMR1282 Infectiologie et Santé Publique, INRA, Université de Tours, F-37380, Nouzilly, France
| | - H Février
- UMR1282 Infectiologie et Santé Publique, INRA, Université de Tours, F-37380, Nouzilly, France
| | - I Théry-Koné
- EA 7502 SIMBA, Université de Tours, Faculté de Pharmacie, F-37000, Tours, France
| | - J Cortet
- UMR1282 Infectiologie et Santé Publique, INRA, Université de Tours, F-37380, Nouzilly, France
| | - C Koch
- UMR1282 Infectiologie et Santé Publique, INRA, Université de Tours, F-37380, Nouzilly, France
| | - F Bouvier
- UE332 La Sapinière, INRA, F-18174, Osmoy, France
| | - T Fassier
- UE332 La Sapinière, INRA, F-18174, Osmoy, France
| | - D Marcon
- UE332 La Sapinière, INRA, F-18174, Osmoy, France
| | - J B Magnin-Robert
- Agroécologie, AgroSup Dijon, INRA, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, F-21000, Dijon, France
| | - N Peineau
- Département Physiologie Animale, Université de Tours, Faculté des Sciences et Techniques, F-37000, Tours, France
| | - E Courtot
- UMR1282 Infectiologie et Santé Publique, INRA, Université de Tours, F-37380, Nouzilly, France
| | - C Huau
- GenPhySE, INRA, Université de Toulouse, INPT, ENVT, F-31326, Castanet-Tolosan, France
| | - A Meynadier
- GenPhySE, INRA, Université de Toulouse, INPT, ENVT, F-31326, Castanet-Tolosan, France
| | | | - C Neveu
- UMR1282 Infectiologie et Santé Publique, INRA, Université de Tours, F-37380, Nouzilly, France
| | - L Boudesocque-Delaye
- EA 7502 SIMBA, Université de Tours, Faculté de Pharmacie, F-37000, Tours, France
| | - G Sallé
- UMR1282 Infectiologie et Santé Publique, INRA, Université de Tours, F-37380, Nouzilly, France.
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Carrillo-Perdomo E, Raffiot B, Ollivier D, Deulvot C, Magnin-Robert JB, Tayeh N, Marget P. Identification of Novel Sources of Resistance to Seed Weevils ( Bruchus spp.) in a Faba Bean Germplasm Collection. Front Plant Sci 2018; 9:1914. [PMID: 30687341 PMCID: PMC6333698 DOI: 10.3389/fpls.2018.01914] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Accepted: 12/10/2018] [Indexed: 05/20/2023]
Abstract
Seed weevils (Bruchus spp.) are major pests of faba bean, causing yield losses, and affecting marketability. Our objective was to identify stable sources of resistance to seed weevil attacks, determine the climatic factors that most influenced its incidence and its relationship with some phenological and agronomic traits. The accessions "BOBICK ROD115," "CÔTE D'OR," "221516," and "NOVA GRADISKA" showed increased resistance to penetration and development of larvae. Other accessions such as "QUASAR," "109.669," and "223303" exhibited resistance to larval development. The results of this work suggest the presence of different defense mechanisms to seed weevils in faba bean, which in the future could be introgressed in elite cultivars to create resistant varieties and contribute to more sustainable agriculture with less need for pesticides. The temperature, rainfall, and humidity seemed to be the climatic factors most influencing faba bean seed weevil attack while the precocity and the small weight of the seeds were correlated with lower infestation rates in the different experiments.
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Affiliation(s)
- Estefanía Carrillo-Perdomo
- Agroécologie, AgroSup Dijon, INRA, Université Bourgogne Franche-Comté, Dijon, France
- *Correspondence: Estefanía Carrillo-Perdomo, ;
| | - Blandine Raffiot
- Agroécologie, AgroSup Dijon, INRA, Université Bourgogne Franche-Comté, Dijon, France
- Terres Inovia, Thierval-Grignon, France
| | - Damien Ollivier
- Agroécologie, AgroSup Dijon, INRA, Université Bourgogne Franche-Comté, Dijon, France
| | - Chrystel Deulvot
- Agroécologie, AgroSup Dijon, INRA, Université Bourgogne Franche-Comté, Dijon, France
| | | | - Nadim Tayeh
- Agroécologie, AgroSup Dijon, INRA, Université Bourgogne Franche-Comté, Dijon, France
| | - Pascal Marget
- Agroécologie, AgroSup Dijon, INRA, Université Bourgogne Franche-Comté, Dijon, France
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Burstin J, Salloignon P, Chabert-Martinello M, Magnin-Robert JB, Siol M, Jacquin F, Chauveau A, Pont C, Aubert G, Delaitre C, Truntzer C, Duc G. Genetic diversity and trait genomic prediction in a pea diversity panel. BMC Genomics 2015; 16:105. [PMID: 25765216 PMCID: PMC4355348 DOI: 10.1186/s12864-015-1266-1] [Citation(s) in RCA: 68] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2014] [Accepted: 01/22/2015] [Indexed: 11/10/2022] Open
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. 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.
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Affiliation(s)
- Judith Burstin
- UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France.
| | - Pauline Salloignon
- Clinical and Innovation Proteomic Platform (CLIPP), CHU Dijon, Université de Bourgogne, 1 rue du Professeur Marion, Dijon, 21000, France.
| | | | | | - Mathieu Siol
- UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France.
| | - Françoise Jacquin
- UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France.
| | - Aurélie Chauveau
- UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France.
- Present address: US EPGV, IG-CEA, Centre National de Génotypage, 2 rue Gaston Crémieux, Evry Cedex, 91057, France.
| | - Caroline Pont
- UMR GDEC, Plateforme Gentyane, Clermont Ferrand, 63100, France.
| | - Grégoire Aubert
- UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France.
| | - Catherine Delaitre
- UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France.
| | - Caroline Truntzer
- Clinical and Innovation Proteomic Platform (CLIPP), CHU Dijon, Université de Bourgogne, 1 rue du Professeur Marion, Dijon, 21000, France.
| | - Gérard Duc
- UMR1347, Agroecology, INRA, 17 rue de Sully, Dijon Cedex, 21065, France.
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Tayeh N, Klein A, Le Paslier MC, Jacquin F, Houtin H, Rond C, Chabert-Martinello M, Magnin-Robert JB, Marget P, Aubert G, Burstin J. Genomic Prediction in Pea: Effect of Marker Density and Training Population Size and Composition on Prediction Accuracy. Front Plant Sci 2015; 6:941. [PMID: 26635819 PMCID: PMC4648083 DOI: 10.3389/fpls.2015.00941] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2015] [Accepted: 10/16/2015] [Indexed: 05/18/2023]
Abstract
Pea is an important food and feed crop and a valuable component of low-input farming systems. Improving resistance to biotic and abiotic stresses is a major breeding target to enhance yield potential and regularity. Genomic selection (GS) has lately emerged as a promising technique to increase the accuracy and gain of marker-based selection. It uses genome-wide molecular marker data to predict the breeding values of candidate lines to selection. A collection of 339 genetic resource accessions (CRB339) was subjected to high-density genotyping using the GenoPea 13.2K SNP Array. Genomic prediction accuracy was evaluated for thousand seed weight (TSW), the number of seeds per plant (NSeed), and the date of flowering (BegFlo). Mean cross-environment prediction accuracies reached 0.83 for TSW, 0.68 for NSeed, and 0.65 for BegFlo. For each trait, the statistical method, the marker density, and/or the training population size and composition used for prediction were varied to investigate their effects on prediction accuracy: the effect was large for the size and composition of the training population but limited for the statistical method and marker density. Maximizing the relatedness between individuals in the training and test sets, through the CDmean-based method, significantly improved prediction accuracies. A cross-population cross-validation experiment was further conducted using the CRB339 collection as a training population set and nine recombinant inbred lines populations as test set. Prediction quality was high with mean Q (2) of 0.44 for TSW and 0.59 for BegFlo. Results are discussed in the light of current efforts to develop GS strategies in pea.
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Affiliation(s)
- Nadim Tayeh
- INRA, UMR1347 AgroécologieDijon, France
- *Correspondence: Nadim Tayeh
| | | | - Marie-Christine Le Paslier
- INRA, US1279 Etude du Polymorphisme des Génomes Végétaux, CEA-IG/Centre National de GénotypageEvry, France
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