Development and Proof-of-Concept Application of Genome-Enabled Selection for Pea Grain Yield under Severe Terminal Drought

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Wider pea (Pisum sativum L.) cultivation has great interest for European agriculture, owing to its favorable environmental impact and provision of high-protein feedstuff. This work aimed to investigate the extent of genotype × environment interaction (GEI), genetically based trade-offs and polygenic control for crude protein content and grain yield of pea targeted to Italian environments, and to assess the efficiency of genomic selection (GS) as an alternative to phenotypic selection (PS) to increase protein yield per unit area. Some 306 genotypes belonging to three connected recombinant inbred line (RIL) populations derived from paired crosses between elite cultivars were genotyped through genotyping-by-sequencing and phenotyped for grain yield and protein content on a dry matter basis in three autumn-sown environments of northern or central Italy. Line variation for mean protein content ranged from 21.7 to 26.6%. Purely genetic effects, compared with GEI effects, were over two-fold larger for protein content, and over 2-fold smaller for grain and protein yield per unit area. Grain yield and protein content exhibited no inverse genetic correlation. A genome-wide association study revealed a definite polygenic control not only for grain yield but also for protein content, with small amounts of trait variation accounted for by individual loci. On average, the GS predictive ability for individual RIL populations based on the rrBLUP model (which was selected out of four tested models) using by turns two environments for selection and one for validation was moderately high for protein content (0.53) and moderate for grain yield (0.40) and protein yield (0.41). These values were about halved for inter-environment, inter-population predictions using one RIL population for model construction to predict data of the other populations. The comparison between GS and PS for protein yield based on predicted gains per unit time and similar evaluation costs indicated an advantage of GS for model construction including the target RIL population and, in case of multi-year PS, even for model training based on data of a non-target population. In conclusion, protein content is less challenging than grain yield for phenotypic or genome-enabled improvement, and GS is promising for the simultaneous improvement of both traits.

Section: Genomic Regression Models and Data Configurationsmentioning

confidence: 99%

Pea Grain Protein Content Across Italian Environments: Genetic Relationship With Grain Yield, and Opportunities for Genome-Enabled Selection for Protein Yield

Crosta¹,

N.²,

Ferrari³

et al. 2022

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“…Its cost-efficient application to plant breeding has greatly been enhanced by recent sequencing techniques, such as genotyping-by-sequencing (GBS; Elshire et al, 2011 ), that allow large germplasm sets to be genotyped by thousands of single nucleotide polymorphism (SNP) markers at a relatively low cost. Pioneer studies for pea suggested greater genetic gain per unit time of genomic over phenotypic selection for improving grain yield under PS conditions in moisture-favorable (Annicchiarico et al, 2019b ) and severely drought-prone target regions (Annicchiarico et al, 2020 ). Genomic selection out-performed phenotypic selection in breeding for intercropping in a study based on stochastic simulation data (Bančič et al, 2021 ), but no experimental assessment of the value of genomic selection for intercropping is available.…”

Section: Introductionmentioning

confidence: 99%

Pea Breeding for Intercropping With Cereals: Variation for Competitive Ability and Associated Traits, and Assessment of Phenotypic and Genomic Selection Strategies

Annicchiarico¹,

N.²,

Notario³

et al. 2021

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Mixed stand (MS) cropping of pea with small-grain cereals can produce more productive and environment-friendly grain crops relative to pure stand (PS) crops but may require selection to alleviate the pea competitive disadvantage. This study aimed to assess the pea variation for competitive ability and its associated traits and the efficiency of four phenotypic or genomic selection strategies. A set of 138 semi-leafless, semi-dwarf pea lines belonging to six recombinant inbred line populations and six parent lines were genotyped using genotyping-by-sequencing and grown in PS and in MS simultaneously with one barley and one bread wheat cultivar in two autumn-sown trials in Northern Italy. Cereal companions were selected in a preliminary study that highlighted the paucity of cultivars with sufficient earliness for association. Pea was severely outcompeted in both years albeit with variation for pea proportion ranging from nearly complete suppression (<3%) to values approaching a balanced mixture. Greater pea proportion in MS was associated with greater total yield of the mixture (r ≥ 0.46). The genetic correlation for pea yield across MS and PS conditions slightly exceeded 0.40 in both years. Later onset of flowering and taller plant height at flowering onset displayed a definite correlation with pea yield in MS (r ≥ 0.46) but not in PS, whereas tolerance to ascochyta blight exhibited the opposite pattern. Comparisons of phenotypic selection strategies within or across populations based on predicted or actual yield gains for independent years indicated an efficiency of 52–64% for indirect selection based on pea yield in PS relative to pea yield selection in MS. The efficiency of an indirect selection index including onset of flowering, plant height, and grain yield in PS was comparable to that of pea yield selection in MS. A genome-wide association study based on 5,909 SNP markers revealed the substantial diversity of genomic areas associated with pea yield in MS and PS. Genomic selection for pea yield in MS displayed an efficiency close to that of phenotypic selection for pea yield in MS, and nearly two-fold greater efficiency when also taking into account its shorter selection cycle and smaller evaluation cost.

“…Pioneer studies highlighted greater predicted yield gain per unit time or unit cost for alfalfa ( Annicchiarico et al, 2015b ), soybean ( Matei et al, 2018 ), and pea ( Annicchiarico et al, 2019b ). In legumes, GS displayed convenient predictive ability also for key grain quality ( Stewart-Brown et al, 2019 ) or forage quality traits ( Biazzi et al, 2017 ; Pégard et al, 2021 ) and emerging complex traits, such as drought tolerance ( Li et al, 2019 ; Annicchiarico et al, 2020 ), performance in intercropping ( Annicchiarico et al, 2021 ), and tolerance to some biotic stresses ( Carpenter et al, 2018 ). However, research work is crucially needed to fully assess the potential of GS for different legume species and target traits, explore the transferability of its models to different breeding populations, and optimize its adoption within the breeding schemes.…”

Section: Novel Techniques To Enhance the Selection Efficiency And Ease The Complexity Of Selectionmentioning

confidence: 99%

Legume Breeding for the Agroecological Transition of Global Agri-Food Systems: A European Perspective

Rubiales

Annicchiarico²,

Patto

et al. 2021

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Wider and more profitable legume crop cultivation is an indispensable step for the agroecological transition of global agri-food systems but represents a challenge especially in Europe. Plant breeding is pivotal in this context. Research areas of key interest are represented by innovative phenotypic and genome-based selection procedures for crop yield, tolerance to abiotic and biotic stresses enhanced by the changing climate, intercropping, and emerging crop quality traits. We see outmost priority in the exploration of genomic selection (GS) opportunities and limitations, to ease genetic gains and to limit the costs of multi-trait selection. Reducing the profitability gap of legumes relative to major cereals will not be possible in Europe without public funding devoted to crop improvement research, pre-breeding, and, in various circumstances, public breeding. While most of these activities may profit of significant public-private partnerships, all of them can provide substantial benefits to seed companies. A favorable institutional context may comprise some changes to variety registration tests and procedures.