Population structure, genetic diversity, and GWAS analyses with GBS-derived SNPs and silicodart markers unveil genetic potential for breeding and candidate genes for agronomic and root quality traits in an international sugar beet germplasm collection
Background: Knowledge about the degree of genetic diversity and population structure is crucial as it facilitates novel variations that can be used in breeding programs. Similarly, genome-wide association studies (GWAS) can reveal candidate genes controlling traits of interest. Sugar beet is a major...
| Autores principales: | , , , , , , , , , , , , |
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| Formato: | info:ar-repo/semantics/artículo |
| Lenguaje: | Inglés |
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BMC
2025
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.12123/23808 https://bmcplantbiol.biomedcentral.com/articles/10.1186/s12870-025-06525-7 https://doi.org/10.1186/s12870-025-06525-7 |
| _version_ | 1855038823796310016 |
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| author | Bahjat, Noor Maiwan Yildiz, Mehtap Nadeem, Muhammad Azhar Morales Sanfurgo, Hugo Andres Wohlfeiler Altavilla, Josefina Baloch, Faheem Shehzad Tunçtürk, Murat Koçak, Metin Yong, Suk Chung Grzebelus, Dariusz Sadık, Gökhan Kuzğun, Cansu Cavagnaro, Pablo |
| author_browse | Bahjat, Noor Maiwan Baloch, Faheem Shehzad Cavagnaro, Pablo Grzebelus, Dariusz Koçak, Metin Kuzğun, Cansu Morales Sanfurgo, Hugo Andres Nadeem, Muhammad Azhar Sadık, Gökhan Tunçtürk, Murat Wohlfeiler Altavilla, Josefina Yildiz, Mehtap Yong, Suk Chung |
| author_facet | Bahjat, Noor Maiwan Yildiz, Mehtap Nadeem, Muhammad Azhar Morales Sanfurgo, Hugo Andres Wohlfeiler Altavilla, Josefina Baloch, Faheem Shehzad Tunçtürk, Murat Koçak, Metin Yong, Suk Chung Grzebelus, Dariusz Sadık, Gökhan Kuzğun, Cansu Cavagnaro, Pablo |
| author_sort | Bahjat, Noor Maiwan |
| collection | INTA Digital |
| description | Background: Knowledge about the degree of genetic diversity and population structure is crucial as it facilitates novel variations that can be used in breeding programs. Similarly, genome-wide association studies (GWAS) can reveal candidate genes controlling traits of interest. Sugar beet is a major industrial crops worldwide, generating 20% of the world’s total sugar production. In this work, using genotyping by sequencing (GBS)-derived SNP and silicoDArT markers, we present new insights into the genetic structure and level of genetic diversity in an international sugar beet germplasm (94 accessions from 16 countries). We also performed GWAS to identify candidate genes for agriculturally-relevant traits.
Results: After applying various filtering criteria, a total of 4,609 high-quality non-redundant SNPs and 6,950 silicoDArT markers were used for genetic analyses. Calculation of various diversity indices using the SNP (e.g., mean gene diversity: 0.31, MAF: 0.22) and silicoDArT (mean gene diversity: 0.21, MAF: 0.12) data sets revealed the existence of a good level of conserved genetic diversity. Cluster analysis by UPGMA revealed three and two distinct clusters for SNP and DArT data, respectively, with accessions being grouped in general agreement with their geographical origins and their tap root color. Coincidently, structure analysis indicated three (K = 3) and two (K = 2) subpopulations for SNP and DArT data, respectively, with accessions in each subpopulation sharing similar geographic origins and root color; and comparable clustering patterns were also found by principal component analysis. GWAS on 13 root and leaf phenotypic traits allowed the identification of 35 significant marker-trait associations for nine traits and, based on predicted functions of the genes in the genomic regions surrounding the significant markers, 25 candidate genes were identified for four root (fresh weight, width, length, and color) and three leaf traits (shape, blade color, and veins color).
Conclusions: The present work unveiled conserved genetic diversity–evidenced both genetically (by SNP and silicoDArT markers) and phenotypically- exploitable in breeding programs and germplasm curation of sugar beet. Results from GWAS and candidate gene analyses provide a frame work for future studies aiming at deciphering the genetic basis underlying relevant traits for sugar beet and related crop types within Beta vulgaris subsp. vulgaris. |
| format | info:ar-repo/semantics/artículo |
| id | INTA23808 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | BMC |
| publisherStr | BMC |
| record_format | dspace |
| spelling | INTA238082025-09-15T13:13:26Z Population structure, genetic diversity, and GWAS analyses with GBS-derived SNPs and silicodart markers unveil genetic potential for breeding and candidate genes for agronomic and root quality traits in an international sugar beet germplasm collection Bahjat, Noor Maiwan Yildiz, Mehtap Nadeem, Muhammad Azhar Morales Sanfurgo, Hugo Andres Wohlfeiler Altavilla, Josefina Baloch, Faheem Shehzad Tunçtürk, Murat Koçak, Metin Yong, Suk Chung Grzebelus, Dariusz Sadık, Gökhan Kuzğun, Cansu Cavagnaro, Pablo Remolacha Azucarera Germoplasma Variación Genética Marcadores Genéticos Genotipado Gen Candidato Sugar Beet Beta vulgaris Germplasm Genetic Variation Genetic Markers Genotyping Candidate Genes Background: Knowledge about the degree of genetic diversity and population structure is crucial as it facilitates novel variations that can be used in breeding programs. Similarly, genome-wide association studies (GWAS) can reveal candidate genes controlling traits of interest. Sugar beet is a major industrial crops worldwide, generating 20% of the world’s total sugar production. In this work, using genotyping by sequencing (GBS)-derived SNP and silicoDArT markers, we present new insights into the genetic structure and level of genetic diversity in an international sugar beet germplasm (94 accessions from 16 countries). We also performed GWAS to identify candidate genes for agriculturally-relevant traits. Results: After applying various filtering criteria, a total of 4,609 high-quality non-redundant SNPs and 6,950 silicoDArT markers were used for genetic analyses. Calculation of various diversity indices using the SNP (e.g., mean gene diversity: 0.31, MAF: 0.22) and silicoDArT (mean gene diversity: 0.21, MAF: 0.12) data sets revealed the existence of a good level of conserved genetic diversity. Cluster analysis by UPGMA revealed three and two distinct clusters for SNP and DArT data, respectively, with accessions being grouped in general agreement with their geographical origins and their tap root color. Coincidently, structure analysis indicated three (K = 3) and two (K = 2) subpopulations for SNP and DArT data, respectively, with accessions in each subpopulation sharing similar geographic origins and root color; and comparable clustering patterns were also found by principal component analysis. GWAS on 13 root and leaf phenotypic traits allowed the identification of 35 significant marker-trait associations for nine traits and, based on predicted functions of the genes in the genomic regions surrounding the significant markers, 25 candidate genes were identified for four root (fresh weight, width, length, and color) and three leaf traits (shape, blade color, and veins color). Conclusions: The present work unveiled conserved genetic diversity–evidenced both genetically (by SNP and silicoDArT markers) and phenotypically- exploitable in breeding programs and germplasm curation of sugar beet. Results from GWAS and candidate gene analyses provide a frame work for future studies aiming at deciphering the genetic basis underlying relevant traits for sugar beet and related crop types within Beta vulgaris subsp. vulgaris. EEA La Consulta Fil: Bahjat, Noor Maiwan. Van Yuzuncu Yil University. Faculty of Agriculture. Department of Agricultural Biotechnology; Turquía Fil: Yıldız, Mehtap. Van Yuzuncu Yil University. Faculty of Agriculture. Department of Agricultural Biotechnology; Turquía Fil: Nadeem, Muhammad Azhar. Mersin University. Faculty of Sciences. Department of Biotechnology; Turquía Fil: Nadeem, Muhammad Azhar. Sivas University of Science and Technology. Faculty of Agricultural Sciences and Technologies. Department of Field Crops; Turquía Fil: Morales Sanfurgo, Hugo Andres. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria La Consulta; Argentina Fil: Morales Sanfurgo, Hugo Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Biología Agrícola de Mendoza; Argentina Fil: Morales Sanfurgo, Hugo Andres. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias. Instituto de Biología Agrícola de Mendoza; Argentina Fil: Morales Sanfurgo, Hugo Andres. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina Fil: Wohlfeiler, Josefina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria La Consulta; Argentina Fil: Wohlfeiler, Josefina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Baloch, Faheem Shehzad. Mersin University. Faculty of Sciences. Department of Biotechnology; Turquía Fil: Baloch, Faheem Shehzad. Jeju National University. Department of Plant Resources and Environment; República de Corea Fil: Tunçtürk, Murat. Van Yuzuncu Yil University. Faculty of Agriculture. Department of Field Crops; Turquía Fil: Koçak, Metin. Van Yuzuncu Yil University. Faculty of Agriculture. Department of Agricultural Biotechnology; Turquía Fil: Yong, Suk Chung. Jeju National University. Department of Plant Resources and Environment; República de Corea Fil: Grzebelus, Dariusz. University of Agriculture in Krakow. Faculty of Biotechnology and Horticulture. Department of Plant Biology and Biotechnology; Polonia Fil: Sadık, Gökhan. Van Yuzuncu Yil University. Faculty of Agriculture. Department of Agricultural Biotechnology; Turquía Fil: Kuzğun, Cansu. Van Yuzuncu Yil University. Faculty of Agriculture. Department of Agricultural Biotechnology; Turquía Fil: Cavagnaro, Pablo Federico. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; Argentina Fil: Cavagnaro, Pablo Federico. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Cavagnaro, Pablo Federico. University of Agriculture in Krakow. Faculty of Biotechnology and Horticulture. Department of Plant Biology, and Biotechnology; Polonia 2025-09-15T13:10:59Z 2025-09-15T13:10:59Z 2025-04 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/23808 https://bmcplantbiol.biomedcentral.com/articles/10.1186/s12870-025-06525-7 1471-2229 https://doi.org/10.1186/s12870-025-06525-7 eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf BMC BMC Plant Biology 25 : Article number: 523. (2025) |
| spellingShingle | Remolacha Azucarera Germoplasma Variación Genética Marcadores Genéticos Genotipado Gen Candidato Sugar Beet Beta vulgaris Germplasm Genetic Variation Genetic Markers Genotyping Candidate Genes Bahjat, Noor Maiwan Yildiz, Mehtap Nadeem, Muhammad Azhar Morales Sanfurgo, Hugo Andres Wohlfeiler Altavilla, Josefina Baloch, Faheem Shehzad Tunçtürk, Murat Koçak, Metin Yong, Suk Chung Grzebelus, Dariusz Sadık, Gökhan Kuzğun, Cansu Cavagnaro, Pablo Population structure, genetic diversity, and GWAS analyses with GBS-derived SNPs and silicodart markers unveil genetic potential for breeding and candidate genes for agronomic and root quality traits in an international sugar beet germplasm collection |
| title | Population structure, genetic diversity, and GWAS analyses with GBS-derived SNPs and silicodart markers unveil genetic potential for breeding and candidate genes for agronomic and root quality traits in an international sugar beet germplasm collection |
| title_full | Population structure, genetic diversity, and GWAS analyses with GBS-derived SNPs and silicodart markers unveil genetic potential for breeding and candidate genes for agronomic and root quality traits in an international sugar beet germplasm collection |
| title_fullStr | Population structure, genetic diversity, and GWAS analyses with GBS-derived SNPs and silicodart markers unveil genetic potential for breeding and candidate genes for agronomic and root quality traits in an international sugar beet germplasm collection |
| title_full_unstemmed | Population structure, genetic diversity, and GWAS analyses with GBS-derived SNPs and silicodart markers unveil genetic potential for breeding and candidate genes for agronomic and root quality traits in an international sugar beet germplasm collection |
| title_short | Population structure, genetic diversity, and GWAS analyses with GBS-derived SNPs and silicodart markers unveil genetic potential for breeding and candidate genes for agronomic and root quality traits in an international sugar beet germplasm collection |
| title_sort | population structure genetic diversity and gwas analyses with gbs derived snps and silicodart markers unveil genetic potential for breeding and candidate genes for agronomic and root quality traits in an international sugar beet germplasm collection |
| topic | Remolacha Azucarera Germoplasma Variación Genética Marcadores Genéticos Genotipado Gen Candidato Sugar Beet Beta vulgaris Germplasm Genetic Variation Genetic Markers Genotyping Candidate Genes |
| url | http://hdl.handle.net/20.500.12123/23808 https://bmcplantbiol.biomedcentral.com/articles/10.1186/s12870-025-06525-7 https://doi.org/10.1186/s12870-025-06525-7 |
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