Molecular Characterization and Genetic Diversity Assessment of Soybean Varieties using SSR Markers

Koutu, G. K.; Shrivastava, Arpita; Singh, Yogendra; Tiwari, Sharad

doi:10.20546/ijcmas.2019.804.018

Cited by 9 publications

(5 citation statements)

References 9 publications

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“…One of the ways to assess the genetic background behind this trait is through the application of informative types of DNA markers, including simple sequence repeats (SSR, also known as microsatellites) and single nucleotide polymorphism (SNP) markers. In the past decades, SSR and SNP markers have been widely used to study genetic diversity [15][16][17][18] and search for associations between markers and traits [19,20]. Both SSRs and SNPs are ubiquitous in the genome of most crops and, therefore, potentially useful to determine the genetic structure of a population and study the evolutionary history and phylogenetic relationships of species.…”

Section: Introductionmentioning

confidence: 99%

Genetic Diversity Analysis of Soybean Collection Using Simple Sequence Repeat Markers

Zatybekov,

Yermagambetova,

Genievskaya

et al. 2023

Plants

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Soybean [Glycine max (L.) Merr.] is a nutrient-rich crop that offers a sustainable source of dietary protein and edible oil. Determining the level of genetic diversity and relationships between various genetic resources involved in breeding programs is very important in crop improvement strategies. This study evaluated 100 soybean accessions with diverse origins for 10 important agronomic traits, including plant height (PH), an important plant adaptation-related trait impacting yield, in conditions in southeastern Kazakhstan for 2 years. The comparison of different groups of PH (tall, middle, and short) using a t-test suggested that the group of plants with the tallest PH provided a higher yield (p < 0.001) in relatively dry field conditions. The genetic diversity of the accessions was estimated using 25 simple sequence repeat (SSR) markers previously known to be associated with plant height. The results showed a significant variation among different groups of origin for all measured agronomic traits, as well as high genetic diversity, with the PIC (polymorphism information content) varying from 0.140 to 0.732, with an average of 0.524. Nei’s diversity index ranged between 0.152 and 0.747, with an average of 0.526. The principal coordinate analysis (PCoA) of the studied soybean collection showed that Kazakhstan accessions were genetically distant from European, East Asian, and North American cultivars. Twelve out of twenty-five SSR markers demonstrated significant associations with ten studied agronomic traits, including PH (p < 0.05). Six SSRs with pleiotropic effects for studied traits were selected, and their haplotypes with phenotypic effects were generated for each soybean accession. The obtained results can be used in soybean improvement programs, including molecular-assisted breeding projects.

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Section: Introductionmentioning

confidence: 99%

Genetic Diversity Analysis of Soybean Collection Using Simple Sequence Repeat Markers

Zatybekov,

Yermagambetova,

Genievskaya

et al. 2023

Plants

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“…For genetic diversity analysis and molecular characterization in soybean, SSR markers become very important because of their abundance, codominance, high reproducibility (Kujane et al, 2019;Koutu et al, 2019), high polymorphism compared to RFLPs, AFLPs, and RAPDs (Kumawat et al, 2015;Chakraborty et al, 2018;Moniruzzaman et al, 2019) and have a much greater ability to identify unique alleles in parental and elite soybean germplasm than any other markers (Tantasawat et al, 2011). Russel et al (2004) found that SSR markers are useful for the determination of genetic relationship and dissimilarity within a population.…”

Section: Introductionmentioning

confidence: 99%

Genetic Diversity Analysis of Soybean [Glycine max (L.) Merrill.] Germplasms in Bangladesh Using SSR Markers

Khatun¹,

Haque²,

Malek³

et al. 2021

JAS

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The purpose of the present study was to investigate the genetic diversity and molecular characterization of 50 soybean genotypes in Bangladesh with 20 SSR markers. Genomic DNA was isolated by modified standard cetyl tri-methyl ammonium bromide (CTAB) extraction protocol and alleles were amplified by polymerase chain reaction (PCR). Allele sizes were estimated in comparison with 50 bp DNA ladder. The software NTSYSpc version 2.2 and POPGENE version 1.31 were utilized for molecular data analysis and preparation of dendrogram. Polymorphic Information Content (PIC) values varied from 0.53 (Satt664) to 0.98 (Satt009, Satt330 and Satt522) with the mean value 0.897 and expected heterozygosity varied from 0.4059 (Satt685) to 0.1246 (Satt664) with the mean value 0.244. The dendrogram analysis depicted that the 50 genotypes were grouped in four (4) major clusters. The most diverse genotypes were SBG-1, PM-78-6-3-13, BS-3 and AGS-31, which suggest that the simple sequence repeat (SSR) markers are very efficient for genetic diversity analysis. The similarity matrix revealed the diversity among genotypes. The diverse genetic materials obtained from the present study on genetic diversity of soybean genotypes in Bangladesh may be utilized in the future breeding programme.

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“…Among the different DNA markers are; Amplified Fragment Length Polymorphisms (AFLPs), Single Nucleotide Polymorphisms (SNPs), Restriction Fragment Length Polymorphisms (RFLPs), Microsatellites/ Simple Sequence Repeats (SSRs) and Randomly Amplified Polymorphic DNAs (RAPDs) have been widely used in studying genetic diversity in soybeans, each with its own merits and demerits (Khare et al, 2013;Chakraborty et al, 2018). For molecular characterization and genetic diversity studies in soybean, SSR markers have been considered as the molecular markers of choice because of their abundance, codominance, high reproducibility (Kujane et al, 2019;Koutu et al, 2019), high polymorphism compared to RFLPs, AFLPs and RAPDs (Kumawat et al, 2015;Chakraborty et al, 2018;Moniruzzaman et al, 2019) and have much greater ability to identify unique alleles in parental and elite soybean germplasm than any other markers (Tantasawat et al, 2011). Therefore, the objective of this study was to determine the level genetic diversity that exists among released and elite soybean genotypes in Uganda based on the SSRs molecular markers.…”

Section: Introductionmentioning

confidence: 99%

Genetic diversity analysis among soybean genotypes using SSR markers in Uganda

Mukuze¹,

Tukamuhabwa²,

Maphosa³

et al. 2020

Afr. J. Biotechnol.

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The assessment of genetic diversity among improved crop germplasm can facilitate the expansion of the genetic base for crop improvement in breeding program. However, little effort has been made to assess the level of genetic relatedness among released varieties and elite soybean [Glycine max (L.) Merr.] genotypes. The objective of this study was to determine the degree of genetic diversity that exists among released and elite soybean genotypes in Uganda. In this study, 21 polymorphic simple sequence repeat (SSR) molecular markers were used to determine the degree of genetic diversity and varietal identification among 34 soybean genotypes. A total of 59 alleles with an average of 2.85 alleles per locus were detected. The polymorphic information content (PIC) values ranged from 0.208 on BE806308 to 0.741 on Satt411, with an average of 0.5870. The expected heterozygosity varied from 0.208 on BE806308 to 0.725 on Satt411, with an average of 0.548 per marker. The dendrogram constructed based on Jaccard's genetic similarities among 34 soybean genotypes identified three major clusters, with six of the released varieties belonging to cluster I. The majority of elite genotypes including three recently released cultivars; Maksoy 4N, Maksoy 5N and Maksoy 6N were grouped in cluster II and III. The results showed moderate genetic variation among the soybean genotypes, which could accelerate genetic vulnerability. Therefore, there is need to widen the genetic base of the working germplasm through the use of techniques such as pre-breeding and novel biotechnology techniques such as mutation breeding and CRISPR to create genetic variation necessary to cope with the dynamics of biotic and abiotic stresses that affect soybean production in Uganda.

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Molecular Characterization and Genetic Diversity Assessment of Soybean Varieties using SSR Markers

Cited by 9 publications

References 9 publications

Genetic Diversity Analysis of Soybean Collection Using Simple Sequence Repeat Markers

Genetic Diversity Analysis of Soybean Collection Using Simple Sequence Repeat Markers

Genetic Diversity Analysis of Soybean [Glycine max (L.) Merrill.] Germplasms in Bangladesh Using SSR Markers

Genetic diversity analysis among soybean genotypes using SSR markers in Uganda

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