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...

• Autores: 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
• Año de publicación: 2025
• Idioma: inglés
• Tipo de recurso: artículo
• Fuente: BMC Plant Biology 25 : Article number: 523. (2025)
• Materia: Remolacha Azucarera; Germoplasma; Variación Genética; Marcadores Genéticos; Genotipado; Gen Candidato; Sugar Beet; Beta vulgaris; Germplasm; Genetic Variation; Genetic Markers; Genotyping; Candidate Genes
• Institución: Instituto Nacional de Tecnología Agropecuaria

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