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Mnafgui W, Jabri C, Jihnaoui N, Maiza N, Guerchi A, Zaidi N, Basson G, Keyster EM, Djébali N, Pecetti L, Hanana M, Annicchiarico P, Sakiroglu M, Ludidi N, Badri M. Discovering new genes for alfalfa ( Medicago sativa) growth and biomass resilience in combined salinity and Phoma medicaginis infection through GWAS. FRONTIERS IN PLANT SCIENCE 2024; 15:1348168. [PMID: 38756967 PMCID: PMC11096488 DOI: 10.3389/fpls.2024.1348168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 04/15/2024] [Indexed: 05/18/2024]
Abstract
Salinity and Phoma medicaginis infection represent significant challenges for alfalfa cultivation in South Africa, Europe, Australia, and, particularly, Tunisia. These constraints have a severe impact on both yield and quality. The primary aim of this study was to establish the genetic basis of traits associated with biomass and growth of 129 Medicago sativa genotypes through genome-wide association studies (GWAS) under combined salt and P. medicaginis infection stresses. The results of the analysis of variance (ANOVA) indicated that the variation in these traits could be primarily attributed to genotype effects. Among the test genotypes, the length of the main stem, the number of ramifications, the number of chlorotic leaves, and the aerial fresh weight exhibited the most significant variation. The broad-sense heritability (H²) was relatively high for most of the assessed traits, primarily due to genetic factors. Cluster analysis, applied to morpho-physiological traits under the combined stresses, revealed three major groups of accessions. Subsequently, a GWAS analysis was conducted to validate significant associations between 54,866 SNP-filtered single-nucleotide polymorphisms (SNPs) and seven traits. The study identified 27 SNPs that were significantly associated with the following traits: number of healthy leaves (two SNPs), number of chlorotic leaves (five SNPs), number of infected necrotic leaves (three SNPs), aerial fresh weight (six SNPs), aerial dry weight (nine SNPs), number of ramifications (one SNP), and length of the main stem (one SNP). Some of these markers are related to the ionic transporters, cell membrane rigidity (related to salinity tolerance), and the NBS_LRR gene family (associated with disease resistance). These findings underscore the potential for selecting alfalfa genotypes with tolerance to the combined constraints of salinity and P. medicaginis infection.
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Affiliation(s)
- Wiem Mnafgui
- Laboratory of Extremophile Plants, Centre of Biotechnology of Borj Cedria, Hammam-Lif, Tunisia
| | - Cheima Jabri
- Laboratory of Extremophile Plants, Centre of Biotechnology of Borj Cedria, Hammam-Lif, Tunisia
| | - Nada Jihnaoui
- Laboratory of Extremophile Plants, Centre of Biotechnology of Borj Cedria, Hammam-Lif, Tunisia
- Faculty of Sciences of Tunis, University of Tunis El Manar, El Manar Tunis, Tunisia
| | - Nourhene Maiza
- Laboratory of Extremophile Plants, Centre of Biotechnology of Borj Cedria, Hammam-Lif, Tunisia
- Faculty of Sciences of Tunis, University of Tunis El Manar, El Manar Tunis, Tunisia
| | - Amal Guerchi
- Laboratory of Extremophile Plants, Centre of Biotechnology of Borj Cedria, Hammam-Lif, Tunisia
- Faculty of Sciences of Tunis, University of Tunis El Manar, El Manar Tunis, Tunisia
| | - Nawres Zaidi
- Laboratory of Extremophile Plants, Centre of Biotechnology of Borj Cedria, Hammam-Lif, Tunisia
- Faculty of Sciences of Tunis, University of Tunis El Manar, El Manar Tunis, Tunisia
| | - Gerhard Basson
- Environmental Biotechnology Laboratory, Department of Biotechnology, University of the Western Cape, Bellville, South Africa
| | - Eden Maré Keyster
- Environmental Biotechnology Laboratory, Department of Biotechnology, University of the Western Cape, Bellville, South Africa
- Plant Stress Tolerance Laboratory, University of Mpumalanga, Mbombela, South Africa
| | - Naceur Djébali
- Laboratory of Bioactive Substances, Centre of Biotechnology of Borj Cedria, Hammam-Lif, Tunisia
| | - Luciano Pecetti
- Council for Agricultural Research and Economics, Research Centre for Animal Production and Aquaculture, Lodi, Italy
| | - Mohsen Hanana
- Laboratory of Extremophile Plants, Centre of Biotechnology of Borj Cedria, Hammam-Lif, Tunisia
| | - Paolo Annicchiarico
- Council for Agricultural Research and Economics, Research Centre for Animal Production and Aquaculture, Lodi, Italy
| | - Muhammet Sakiroglu
- Department of Bioengineering, Adana Alparslan Türkeş Science and Technology University, Adana, Türkiye
| | - Ndiko Ludidi
- Plant Stress Tolerance Laboratory, University of Mpumalanga, Mbombela, South Africa
- DSI-NRF Centre of Excellence in Food Security, University of the Western Cape, Bellville, South Africa
| | - Mounawer Badri
- Laboratory of Extremophile Plants, Centre of Biotechnology of Borj Cedria, Hammam-Lif, Tunisia
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Nazzicari N, Franguelli N, Ferrari B, Pecetti L, Annicchiarico P. The Effect of Genome Parametrization and SNP Marker Subsetting on Genomic Selection in Autotetraploid Alfalfa. Genes (Basel) 2024; 15:449. [PMID: 38674384 PMCID: PMC11050091 DOI: 10.3390/genes15040449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 03/21/2024] [Accepted: 03/27/2024] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND Alfalfa, the most economically important forage legume worldwide, features modest genetic progress due to long selection cycles and the extent of the non-additive genetic variance associated with its autotetraploid genome. METHODS To improve the efficiency of genomic selection in alfalfa, we explored the effects of genome parametrization (as tetraploid and diploid dosages, plus allele ratios) and SNP marker subsetting (all available SNPs, only genic regions, and only non-genic regions) on genomic regressions, together with various levels of filtering on reading depth and missing rates. We used genotyping by sequencing-generated data and focused on traits of different genetic complexity, i.e., dry biomass yield in moisture-favorable (FE) and drought stress (SE) environments, leaf size, and the onset of flowering, which were assessed in 143 genotyped plants from a genetically broad European reference population and their phenotyped half-sib progenies. RESULTS On average, the allele ratio improved the predictive ability compared with other genome parametrizations (+7.9% vs. tetraploid dosage, +12.6% vs. diploid dosage), while using all the SNPs offered an advantage compared with any specific SNP subsetting (+3.7% vs. genic regions, +7.6% vs. non-genic regions). However, when focusing on specific traits, different combinations of genome parametrization and subsetting achieved better performances. We also released Legpipe2, an SNP calling pipeline tailored for reduced representation (GBS, RAD) in medium-sized genotyping experiments.
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Affiliation(s)
- Nelson Nazzicari
- Council for Agricultural Research and Economics (CREA), Research Center for Animal Production and Aquaculture, Viale Piacenza 29, 26900 Lodi, Italy
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Wang H, Bai Y, Biligetu B. Effects of SNP marker density and training population size on prediction accuracy in alfalfa (Medicago sativa L.) genomic selection. THE PLANT GENOME 2024; 17:e20431. [PMID: 38263612 DOI: 10.1002/tpg2.20431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 11/29/2023] [Accepted: 01/04/2024] [Indexed: 01/25/2024]
Abstract
Effects of individual single-nucleotide polymorphism (SNP) markers and the size of "training" and "test" populations affect prediction accuracy in genomic selection (GS). This study evaluated 11 subsets of 4932 SNPs using six genetic additive methods to understand marker density in GS prediction in alfalfa (Medicago sativa L.). In the GS methods, the effect of "training" to "test" population size was also evaluated. Fourteen alfalfa populations sampled from long-term grazing sites were genotyped using genotyping by sequencing for the identification of SNPs. These populations were also phenotyped for six agromorphological and three nutritive traits from 2018 to 2020. The accuracy of GS prediction improved across six GS methods when the ratio of "training" to "test" population size increased. However, the prediction accuracy of the six GS methods reduced to a range of -0.27 to 0.11 when random, uninformative SNPs were used. In this study, five Bayesian methods and ridge-regression best linear unbiased prediction (rrBLUP) method had similar GS accuracies for "training" sets, but rrBLUP tended to outperform Bayesian methods in independent "test" sets when SNP subsets with high mean-squared-estimated-marker effect were used. These findings can enhance the application of GS in alfalfa genetic improvement.
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Affiliation(s)
- Hu Wang
- Department of Plant Sciences, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Yuguang Bai
- Department of Plant Sciences, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Bill Biligetu
- Department of Plant Sciences, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
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Afshari-Behbahanizadeh S, Puglisi D, Esposito S, De Vita P. Allelic Variations in Vernalization ( Vrn) Genes in Triticum spp. Genes (Basel) 2024; 15:251. [PMID: 38397240 PMCID: PMC10887697 DOI: 10.3390/genes15020251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Revised: 02/12/2024] [Accepted: 02/14/2024] [Indexed: 02/25/2024] Open
Abstract
Rapid climate changes, with higher warming rates during winter and spring seasons, dramatically affect the vernalization requirements, one of the most critical processes for the induction of wheat reproductive growth, with severe consequences on flowering time, grain filling, and grain yield. Specifically, the Vrn genes play a major role in the transition from vegetative to reproductive growth in wheat. Recent advances in wheat genomics have significantly improved the understanding of the molecular mechanisms of Vrn genes (Vrn-1, Vrn-2, Vrn-3, and Vrn-4), unveiling a diverse array of natural allelic variations. In this review, we have examined the current knowledge of Vrn genes from a functional and structural point of view, considering the studies conducted on Vrn alleles at different ploidy levels (diploid, tetraploid, and hexaploid). The molecular characterization of Vrn-1 alleles has been a focal point, revealing a diverse array of allelic forms with implications for flowering time. We have highlighted the structural complexity of the different allelic forms and the problems linked to the different nomenclature of some Vrn alleles. Addressing these issues will be crucial for harmonizing research efforts and enhancing our understanding of Vrn gene function and evolution. The increasing availability of genome and transcriptome sequences, along with the improvements in bioinformatics and computational biology, offers a versatile range of possibilities for enriching genomic regions surrounding the target sites of Vrn genes, paving the way for innovative approaches to manipulate flowering time and improve wheat productivity.
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Affiliation(s)
- Sanaz Afshari-Behbahanizadeh
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA—Council for Agricultural Research and Economics, SS 673 Meters 25 200, 71122 Foggia, Italy; (S.A.-B.); (D.P.)
- Department of Agriculture, Food, Natural Science, Engineering, University of Foggia, Via Napoli 25, 71122 Foggia, Italy
| | - Damiano Puglisi
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA—Council for Agricultural Research and Economics, SS 673 Meters 25 200, 71122 Foggia, Italy; (S.A.-B.); (D.P.)
| | - Salvatore Esposito
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA—Council for Agricultural Research and Economics, SS 673 Meters 25 200, 71122 Foggia, Italy; (S.A.-B.); (D.P.)
- National Research Council of Italy, Institute of Biosciences and BioResources, Research Division Portici (CNR-IBBR), 80055 Portici, Italy
| | - Pasquale De Vita
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA—Council for Agricultural Research and Economics, SS 673 Meters 25 200, 71122 Foggia, Italy; (S.A.-B.); (D.P.)
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Esposito S, Vitale P, Taranto F, Saia S, Pecorella I, D'Agostino N, Rodriguez M, Natoli V, De Vita P. Simultaneous improvement of grain yield and grain protein concentration in durum wheat by using association tests and weighted GBLUP. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:242. [PMID: 37947927 DOI: 10.1007/s00122-023-04487-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 10/16/2023] [Indexed: 11/12/2023]
Abstract
KEY MESSAGE Simultaneous improvement for GY and GPC by using GWAS and GBLUP suggested a significant application in durum wheat breeding. Despite the importance of grain protein concentration (GPC) in determining wheat quality, its negative correlation with grain yield (GY) is still one of the major challenges for breeders. Here, a durum wheat panel of 200 genotypes was evaluated for GY, GPC, and their derived indices (GPD and GYD), under eight different agronomic conditions. The plant material was genotyped with the Illumina 25 k iSelect array, and a genome-wide association study was performed. Two statistical models revealed dozens of marker-trait associations (MTAs), each explaining up to 30%. phenotypic variance. Two markers on chromosomes 2A and 6B were consistently identified by both models and were found to be significantly associated with GY and GPC. MTAs identified for phenological traits co-mapped to well-known genes (i.e., Ppd-1, Vrn-1). The significance values (p-values) that measure the strength of the association of each single nucleotide polymorphism marker with the target traits were used to perform genomic prediction by using a weighted genomic best linear unbiased prediction model. The trained models were ultimately used to predict the agronomic performances of an independent durum wheat panel, confirming the utility of genomic prediction, although environmental conditions and genetic backgrounds may still be a challenge to overcome. The results generated through our study confirmed the utility of GPD and GYD to mitigate the inverse GY and GPC relationship in wheat, provided novel markers for marker-assisted selection and opened new ways to develop cultivars through genomic prediction approaches.
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Affiliation(s)
- Salvatore Esposito
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA - Council for Agricultural Research and Economics, SS 673 Meters 25200, 71122, Foggia, Italy
| | - Paolo Vitale
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA - Council for Agricultural Research and Economics, SS 673 Meters 25200, 71122, Foggia, Italy
- Department of Agriculture, Food, Natural Science, Engineering, University of Foggia, Via Napoli 25, 71122, Foggia, Italy
| | - Francesca Taranto
- Institute of Biosciences and Bioresources (CNR-IBBR), Via Amendola 165/A, 70126, Bari, Italy
| | - Sergio Saia
- Department of Veterinary Sciences, University of Pisa, 56129, Pisa, Italy
| | - Ivano Pecorella
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA - Council for Agricultural Research and Economics, SS 673 Meters 25200, 71122, Foggia, Italy
| | - Nunzio D'Agostino
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy
| | - Monica Rodriguez
- Department of Agriculture, University of Sassari, Viale Italia, 39, 07100, Sassari, Italy
| | - Vincenzo Natoli
- Genetic Services SRL, Contrada Catenaccio, snc, 71026, Deliceto, FG, Italy
| | - Pasquale De Vita
- Research Centre for Cereal and Industrial Crops (CREA-CI), CREA - Council for Agricultural Research and Economics, SS 673 Meters 25200, 71122, Foggia, Italy.
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