Genetic structure and diversity of a soybean germplasm considering biological nitrogen fixation and protein content

Grunvald, Anna Karolina; Martins, Talita Busulini; Santos, Maria Aparecida dos; Lemos, N. G.; Silva, Luis Antônio Stabile; Hungría, Mariangela

doi:10.1590/0103-9016-2014-0039

Cited by 12 publications

(7 citation statements)

References 26 publications

(29 reference statements)

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“…The mean gene diversity of 0.55 recorded in this study is similar to that of Huang et al () who reported a mean gene diversity of 0.59 using 24 SSR markers to screen 150 soybean accessions. Similarly, the PIC of 0.51 observed in this study is similar to the mean PIC of 0.49 obtained by Torres et al () in a study that involves genotyping 191 soybean accessions with 22 SSR markers. Bisen et al, () recorded lower diversity parameters on soybean including mean gene diversity of 0.2339, heterozygosity of 0.0469 and polymorphic information content of 0.1998 as compared to this study.…”

Section: Discussionsupporting

confidence: 91%

Genetic diversity, population structure and key phenotypic traits driving variation within soyabean (Glycine max) collection in Ghana

Denwar¹,

Awuku²,

Diers

et al. 2019

Plant Breeding

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Soybean [Glycine max (L.) Merrill] is an important oilseed crop worldwide and it has recently become the crop of interest in Ghana. In this study, 142 soybean accessions were genotyped with 34 SSR markers and concurrently evaluated for five quantitative and two qualitative phenotypic traits. Twenty‐nine of the SSR markers were polymorphic with mean allele number of 5.3, polymorphic information content (PIC) of 0.51 and gene diversity of 0.55. Molecular analysis based on unweighted paired group arithmetic mean (UPGMA) clustering and principal coordinate analysis (PCoA) was similar in explaining the extent of diversity within the accessions. Structure analysis placed most of the accessions into two subpopulations with 18 (12.7%) as admixtures. Principal component analysis (PCA) based on phenotypic traits revealed two clusters. Both UPGMA clustering‐based SSR data and PCA from phenotypic data showed similar results. The assembled germplasm is genetically diverse with high variation in flowering and maturity period, and key yield components which could be exploited in developing superior varieties well adapted to Ghana and West Africa.

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Section: Discussionsupporting

confidence: 91%

Genetic diversity, population structure and key phenotypic traits driving variation within soyabean (Glycine max) collection in Ghana

Denwar¹,

Awuku²,

Diers

et al. 2019

Plant Breeding

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“…In the current study, population structure analysis using STRUCTURE software revealed the same results as the PCA. Several studies indicated PCA and Bayesian model-based STRUCTURE analysis showed the same results in different plants, e.g., Persian walnut (Mohsenipoor et al 2010;Bernard et al 2018), coconut (Odong et al 2011), soybean (Torres et al 2015), sweet cherry (Campoy et al 2016), maize (Vigouroux et al 2008), coffee (Cubry et al 2013) and apples (Liang et al 2015).…”

Section: Discussionmentioning

confidence: 89%

Genetic Diversity and Structure Analysis of a Worldwide Collection of Faba bean (Vicia faba) Genotypes using ISSR Markers

Qahtan¹

2021

IJAB

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The success of breeding programs depends on the extent of genetic variability. Inter-simple sequence repeats (ISSR) have been widely utilized in investigations, including the characterization of many plant species genetically. This research aimed to examine both the genetic diversity and relationships of 92 faba bean (Vicia faba L.) genotypes from different geographical areas using ISSR markers. Eleven ISSR primers generated a total of 189 repeatable amplified bands, of which 109 were polymorphic. Values of polymorphism information content (PIC) and gene diversity averaged 0.3484 and 0.1438 and ranged 0.089–0.715 and 0.0742–0.2065, respectively. The studied accessions of faba bean plant differentiated into four main clusters, prevalently based on geographical origin through UPGMA clustering analysis and principal component analysis (PCA), deriving four major groupings based on pedigree and origin relationships. The STRUCTURE software analysis results were significantly aligned with the PCA and showed five main clusters; each one represents one continent. AMOVA showed high variation and differentiation among nations from different continents. The discrimination power of ISSR markers obtained in this study suggests that they could be used to examine the diversity of faba bean genotypes efficiently and precisely and encourage targeted crossing strategies. © 2021 Friends Science Publishers

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“…Identification of dissimilar genotypes with molecular markers is helpful over the conventional breeding. SSRs molecular markers find its application in analysis of genetic diversity, identification of genotypes and population structure assessment in soybean (Bisen et al 2015;Torres et al 2015).…”

Section: Resultsmentioning

confidence: 99%

Genetic diversity and population structure of Indian soybean (Glycine max (L.) Merr.) as revealed by microsatellite markers

Tiwari

Tripathi

Tsuji

et al. 2019

Physiol Mol Biol Plants

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The genetic structure and diversity of 148 soybean genotypes were analyzed using 26 simple sequence repeat (SSR) markers. SSR analysis showed distinctive polymorphism among the 148 lines. A total of 71 alleles were detected with an average of 2.8 alleles per SSR locus. Polymorphism information content varied from 0.118 to 0.699 with an average of 0.369. These soybean genotypes were divided into 3 subgroups based on STRUCTURE analysis. Further comparison showed that the arithmetic average (UPGMA) and STRUCTURE subgroups in fact were highly coherent, as genotypes in their subsequent classified group exhibited consistency with their origins or pedigree. This analysis provided a deep insight into the genetic structure of soybeans in India and will help us to improve the breeding strategies.

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Genetic structure and diversity of a soybean germplasm considering biological nitrogen fixation and protein content

Cited by 12 publications

References 26 publications

Genetic diversity, population structure and key phenotypic traits driving variation within soyabean (Glycine max) collection in Ghana

Genetic diversity, population structure and key phenotypic traits driving variation within soyabean (Glycine max) collection in Ghana

Genetic Diversity and Structure Analysis of a Worldwide Collection of Faba bean (Vicia faba) Genotypes using ISSR Markers

Genetic diversity and population structure of Indian soybean (Glycine max (L.) Merr.) as revealed by microsatellite markers

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