GWAS and genomic selection for marker-assisted development of sucrose enriched soybean cultivars
Abstract Sucrose concentration in soy-derived foods is becoming a seminal trait for the production of food-grade soybeans. However, limited scientific knowledge is reported on this increasingly important breeding objective. In this study, 473 genetically diverse soybean germplasm accessions and 8477 high-quality single nucleotide polymorphisms (SNPs) were utilized to pinpoint genomic regions associated with seed sucrose contents through a genome-wide association study (GWAS). A total of 75 significant SNPs (LOD ≥ 6.0) were identified across GLM, FarmCPU and BLINK models, including four stable and novel SNPs (Gm03_45385087_ss715586641, Gm06_10919443_ss715592728, Gm09_45335932_ss715604570 and Gm14_10470463_ss715617454). Gene mining near 20 kb flanking genomic regions of the four stable SNP markers identified 23 candidate genes with the majority of them highly expressed in soybean seeds and pod shells. A sugar transporter encoding major facilitator superfamily gene (Glyma.06G132500) showing the highest expression in pod shells was also identified. Moreover, selection accuracy, efficiency and favorable alleles of 75 significantly associated SNPs were estimated for their utilization in soybean breeding programs. Furthermore, genomic predictions with three different scenarios revealed better feasibility of GWAS-derived SNPs for selection and improvement of seed sucrose concentration. These results could facilitate plant breeders in marker-assisted breeding and genomic selection of sucrose-enriched food-grade soybean cultivars for the global soy-food industry..
| Medienart: |
Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:219 |
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| Enthalten in: |
Euphytica - 219(2023), 9 vom: 26. Aug. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Riaz, Awais [VerfasserIn] |
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| Links: |
Volltext [lizenzpflichtig] |
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| Themen: |
Food-grade soybean |
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| Anmerkungen: |
© The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| doi: |
10.1007/s10681-023-03224-y |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Abstract Sucrose concentration in soy-derived foods is becoming a seminal trait for the production of food-grade soybeans. However, limited scientific knowledge is reported on this increasingly important breeding objective. In this study, 473 genetically diverse soybean germplasm accessions and 8477 high-quality single nucleotide polymorphisms (SNPs) were utilized to pinpoint genomic regions associated with seed sucrose contents through a genome-wide association study (GWAS). A total of 75 significant SNPs (LOD ≥ 6.0) were identified across GLM, FarmCPU and BLINK models, including four stable and novel SNPs (Gm03_45385087_ss715586641, Gm06_10919443_ss715592728, Gm09_45335932_ss715604570 and Gm14_10470463_ss715617454). Gene mining near 20 kb flanking genomic regions of the four stable SNP markers identified 23 candidate genes with the majority of them highly expressed in soybean seeds and pod shells. A sugar transporter encoding major facilitator superfamily gene (Glyma.06G132500) showing the highest expression in pod shells was also identified. Moreover, selection accuracy, efficiency and favorable alleles of 75 significantly associated SNPs were estimated for their utilization in soybean breeding programs. Furthermore, genomic predictions with three different scenarios revealed better feasibility of GWAS-derived SNPs for selection and improvement of seed sucrose concentration. These results could facilitate plant breeders in marker-assisted breeding and genomic selection of sucrose-enriched food-grade soybean cultivars for the global soy-food industry. | ||
| 650 | 4 | |a Food-grade soybean | |
| 650 | 4 | |a Genomic prediction | |
| 650 | 4 | |a Population genetics | |
| 650 | 4 | |a Quantitative genetics | |
| 650 | 4 | |a Seed sucrose concentration | |
| 650 | 4 | |a Single nucleotide polymorphism (SNP) | |
| 650 | 4 | |a Soluble sugars | |
| 700 | 1 | |a Raza, Qasim |4 aut | |
| 700 | 1 | |a Kumar, Anuj |4 aut | |
| 700 | 1 | |a Dean, Derek |4 aut | |
| 700 | 1 | |a Chiwina, Kenani |4 aut | |
| 700 | 1 | |a Phiri, Theresa Makawa |4 aut | |
| 700 | 1 | |a Thomas, Julie |4 aut | |
| 700 | 1 | |a Shi, Ainong |4 aut | |
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