Genetic differentiation among soybean parental lines of elite vegetable and grain types revealed by molecular markers

Introduction

Soybean (Glycine max (L.) Merrill), often referred to as the "Golden Crop" or "Miracle Crop," is one of the most versatile and globally significant legumes of the twentieth century.

Owing to its exceptionally high protein content and wide range of applications in food, animal feed, and industrial products, soybean has established itself as the leading oilseed crop worldwide, with a global production of 531 million metric tons in 2024 (USDA, 2024). Nutritionally, soybean seeds contain more than 36% protein, 30% carbohydrates, valuable dietary fiber, vitamins, and minerals, along with approximately 20% oil, making it the most important source of edible oil (IITA). The increasing global population demands enhanced crop productivity, yet the rate of yield improvement is slowing. To address this challenge, modern plant breeding must prioritize traits that ensure yield stability and sustainability, such as durable disease resistance, tolerance to abiotic stresses, and improved nutrient and water use efficiency. Marker-assisted selection (MAS), which employs DNA markers to accelerate breeding, has become a powerful tool in this context (Shinde et al., 2018) [12] . Soybean's high protein content and nutraceutical properties make it highly suitable for human consumption. However, its utilization is constrained by factors such as the off-flavors caused by lipoxygenase isozymes (Anshu et al., 2021) [1] and the presence of anti-nutritional factors (ANFs). Among these, trypsin inhibitors particularly the Kunitz Trypsin Inhibitor (KTI) and Bowman-Birk Inhibitor (BBI) can reduce growth performance in poultry and livestock, necessitating heat treatment to inactivate them. While effective, such processing often lowers the availability of essential amino acids and increases production costs (Patil et al., 2025; Gavande et al., 2024) [11,2] . Other ANFs, including non-starch polysaccharides (NSPs) and oligosaccharides, are resistant to heat treatment and may cause digestive disturbances, further complicating soybean's food and feed use.

Advances in molecular breeding have provided strategies to address these limitations. Marker-Assisted Backcross Selection (MABS) relies on a preliminary Parental Polymorphism Survey (PPS) to identify informative molecular markers, which enable the mapping of quantitative trait loci (QTLs) associated with desirable traits and facilitate efficient trait introgression (Kumar et al., 2022) [8] . Simple sequence repeats (SSRs), due to their reproducibility, codominant inheritance, and high polymorphism, are particularly effective in PPS and remain widely used despite the growing popularity of single nucleotide polymorphisms (SNPs) (Cregan et al., 1999; Jadhav et al., 2022; Zatybekov et al., 2023) [4,15,19] . While SNPs are powerful for genome-wide applications, SSRs continue to provide cost-effective and precise tools for assessing genetic diversity and supporting crop improvement. Harnessing genetic diversity is central to developing soybean cultivars that combine resilience with consumer-preferred traits. Breeding programs must integrate alleles for yield potential, stress tolerance, and nutritional enhancement while retaining key market-oriented characteristics such as seed quality, relative maturity, and processing suitability (Cargil et al., 2021) [18] . Importantly, despite modern tools such as MAS and genome editing, the incorporation of new diversity into elite cultivars remains a slow process, often spanning more than a decade, reflecting the complexity of plant breeding and the need for careful decision-making at each stage. Soybean cultivars are broadly classified into grain-type varieties, which are primarily used for oil extraction and animal feed, and foodtype varieties, which are used for traditional fermented (e.g., miso, tempeh, natto) and non-fermented (e.g., tofu, soy flour, soy milk) products (Liu, 1999). Improvement of traits such as protein composition, fatty acid profile (oleic, linoleic, and linolenic acids), sugar content, grain size, hilum color, absence of lipoxygenase enzymes, and cooking time is essential for developing food-type cultivars suitable for direct human consumption. These modifications require confirmation through integrated chemical, physical, and sensory analyses (Carrão-Panizzi, 2000; Meneguce et al., 2005) [16,17] .

Experimental Material

A total of eleven soybean genotypes were selected, comprising five grain types and three vegetable types. The details of the genotypes are as follows:

A set of SSR markers reported by Jadhav et al., 2025 were used for present study.

Methodology Morphological Characterization

Morphological evaluation of soybean genotypes was carried out to assess variability in key agronomic traits. Traits including plant height, flower color, and days to maturity were recorded at appropriate growth stages.  Plant height was measured from the base of the plant to the tip of the main stem at physiological maturity.  Flower color was documented based on the predominant pigmentation observed during the flowering stage.  Days to maturity were determined as the number of days from sowing until 95% of the pods had reached physiological maturity.

Data were recorded with replication to minimize experimental error and to ensure accuracy in trait assessment.

Molecular Analysis

Genomic DNA Isolation: High-quality genomic DNA was extracted from young leaf tissues using a modified cetyltrimethylammonium bromide (CTAB) method (Murray and Thompson, 1980) [10] . Fresh leaf samples were ground into fine powder in liquid nitrogen and homogenized in CTAB extraction buffer (2% CTAB, 100 mM Tris-HCl pH 8.0, 20 mM EDTA, 1.4 M NaCl). The homogenate was incubated at 65 °C for 60 min to promote cell lysis and denaturation of nucleoprotein complexes. Phase separation was achieved through two sequential extractions with chloroform: isoamyl alcohol (24:1, v/v). The aqueous phase was then mixed with CTAB precipitation solution (0.5% CTAB, 0.04 M NaCl) and incubated at room temperature for 1 h, facilitating selective DNA precipitation. The DNA pellet obtained was resuspended in 1.2 M NaCl, subjected to a second chloroform extraction, and subsequently precipitated with isopropanol. The resulting DNA was washed with 70% ethanol, air-dried, and dissolved in nuclease-free water. DNA integrity was verified by electrophoresis on 0.8% agarose gel stained with ethidium bromide, while purity and concentration were assessed using a nanophotometer. Samples with an A260/A280 ratio of ~1.8 were considered of acceptable quality. DNA concentrations were standardized to 30-40 ng/μL for subsequent PCR amplification.

PCR Amplification

PCR reactions were prepared in sterile microcentrifuge tubes maintained on ice to prevent enzyme degradation. Each 10 µL reaction consisted of 3 µL nuclease-free water, 1 µL genomic DNA (30-40 ng/µL), and 6 µL of a master mix containing 5 µL of 2× PCR master mix, 0.5 µL forward primer (10 pmol), and 0.5 µL reverse primer (10 pmol). Reaction mixtures were briefly centrifuged to collect the contents at the tube base and then placed in a programmed thermal cycler for amplification as in fig. 1. After completion of PCR cycles, the amplified products were stored at -20 °C until electrophoresis.

Polyacrylamide Gel Electrophoresis (PAGE)

PCR-amplified fragments were resolved using 8% nondenaturing polyacrylamide gels prepared from a 40% acrylamide:bis-acrylamide stock solution (29:1) in 1× TBE buffer. Polymerization was initiated with 10% ammonium persulfate (APS) and TEMED. The gel solution was carefully poured between assembled glass plates with spacers to avoid bubble formation. After polymerization, the gels were pre-run for 10 min at 120 V to stabilize the matrix. Subsequently, 5 µL of each PCR product was loaded into the wells, and electrophoresis was carried out at 120 V until the tracking dye reached the gel base. Gels were removed, stained with 0.1% ethidium bromide, and visualized under UV transillumination using a gel documentation system. Clear and reproducible banding patterns were scored to assess allelic variation and polymorphism.

Genetic Diversity Analysis

Amplified fragments were scored as present (1) or absent (0) across all genotypes, and only distinct, reproducible bands were considered for analysis. The binary data matrix was used to calculate the Polymorphism Information Content (PIC) for each marker to assess marker informativeness. Pairwise genetic similarity among genotypes was estimated using the Jaccard similarity coefficient. Similarity matrices were generated and subjected to cluster analysis using the Unweighted Pair Group Method with Arithmetic Mean (UPGMA) algorithm to construct dendrograms representing genetic relationships. Principal Coordinate Analysis (PCoA) was also performed

Result and Discussion

The morphological characterization of eleven soybean genotypes revealed substantial genetic variation in key agronomic traits, namely plant height, flower color, and maturity period. Such variation is highly relevant for parental polymorphism surveys in breeding programs, as it reflects the potential of these genotypes to serve as diverse parental sources for trait introgression.

Plant Height

Plant height showed considerable variability, ranging from 37.40 cm in AMS-MB-5-18 to 73.23 cm in AMS-100-39. Vegetable-type genotypes such as AGS-457, AGS-465, and Swarna Vasundhara exhibited moderate stature (55-58 cm), which is desirable for ease of pod picking and suitability for mechanized harvesting. In contrast, taller grain-type cultivars such as JS 93-05 and NRC-109 may offer advantages in terms of higher biomass production and potential yield contributions. These findings highlight the differential breeding potential of vegetable-type versus grain-type lines, supporting targeted parental selection for both yield optimization and harvest efficiency (table 3 and fig. 2).

Molecular Diversity

The electrophoresis profiles generated from the parental polymorphism survey of eight soybean genotypes using 50 SSR markers revealed considerable genetic variability. These markers, distributed across different genomic regions, were highly effective in differentiating the genotypes.

Discussion and Conclusion

The present study demonstrated clear morphological and molecular diversity among the evaluated soybean genotypes, reaffirming their potential as valuable parental lines in breeding programs. Morphological traits such as plant height, flower colour, and maturity duration revealed substantial variation, with vegetable-type lines showing moderate plant height and early maturity, favourable for vegetable soybean production and mechanized harvesting, whereas grain-type varieties exhibited taller stature and later maturity, contributing to higher biomass and yield potential. Such variation underscores the genetic richness of the studied germplasm and provides an accessible basis for varietal differentiation and preliminary parental selection. Complementing morphological observations, molecular characterization using 50 SSR markers further revealed significant genetic diversity. Out of the 50 markers tested, 44 produced clear amplification, of which 18 showed high levels of polymorphism. The Polymorphism Information Content (PIC) values ranged widely from 0.14 to 0.99, with markers such as Satt558 proving highly informative. These markers not only validated the genetic distinctiveness observed morphologically but also provided higher resolution in distinguishing allelic variation. Cluster analysis based on SSR profiles separated grain and vegetable types into distinct clades, mirroring their morphological divergence. This concordance between morphological and molecular datasets highlights the reliability of an integrated approach for parental polymorphism surveys. The identification of polymorphic SSR markers holds direct application in marker-assisted backcross breeding (MABB). These markers are particularly useful for hybridity testing, background genome analysis, and estimation of Recurrent Parent Genome Contribution (RPGC). By enabling precise monitoring of recurrent parent genome recovery while introgressing donor traits, breeders can accelerate the development of improved cultivars. This approach is especially relevant for enhancing traits such as resistance to charcoal rot, tolerance to Yellow Mosaic Virus, and nutritional quality improvement (e.g., Kunitz trypsin inhibitor-free soybean lines).

Integrating morphological characterization with molecular polymorphism thus provides a comprehensive and practical framework for breeding. While morphological traits assist in preliminary classification and selection of contrasting parents, SSR markers refine this process by offering precise genetic resolution. Together, they enhance the efficiency of parental selection, support genetic diversity conservation, and ensure targeted genome recovery in MABB pipelines.

Overall, this study establishes a robust methodological framework where the combined evaluation of morphology and molecular markers strengthens parental polymorphism surveys and facilitates the development of soybean varieties tailored to diverse agro-climatic conditions and end-use preferences whether for vegetable soybean production with desirable quality traits or for grain-type cultivars optimized for yield and resilience.

Acknowledgement

AcknowledgmentThe work was carried out under the research project (Sanction number BT/PR 30841/AGIII/103/1112/2019; dated August 27, 2019) financed by Department of Biotechnology, Ministry of Science and Technology, India. and "Establishment of Centre of Excellence for Enhancing Crop Productivity under Climate Resilience of Vidarbha Region" (Sanction No. BBA/2023/880; dated 27.06.2023), funded by the State Government of Maharashtra. Also, we acknowledge ICAR-IISR, Indore for providing the donors NRC-101 and NRC-127 for the introgression research work.

References

1. Anshu AK, Tayalkar T, Rani A, Kumar V, Parmar HS. Genetic polymorphism of soybean genotypes with contrasting levels of phosphatidylcholine, protein, and lipoxygenase-2. Journal of Applied Biology & Biotechnology. 2022;10:1-5.
2. Gavande BS, Jadhav PV, Shinde UD, Jadhav A, Zanjal SL, Moharil MP, et al. Genetic and molecular characterization of Null KTI allele in backcrossed soybean populations. International Journal of Advanced Biochemistry Research. 2024;8(11):686-690. doi:10.33545/26174693.2024.v8.i11i.2939.
3. Bisen A, Khare D, Nair P, Tripathi N. SSR analysis of 38 genotypes of soybean (Glycine max (L.) Merr.) genetic diversity in India. Physiology and Molecular Biology of Plants. 2014;21:109-115. doi:10.1007/s12298-014-0269-8.
4. Cregan PB, Mudge J, Fickus EW, Marek LF, Danesh D, Denny R, et al. Targeted isolation of simple sequence repeat markers through the use of bacterial artificial chromosomes. Theoretical and Applied Genetics. 1999;98:919-928.
5. Jadhav BC, Dudhare MS, More K, Malge DP, Ghodke MK. Genetic diversity and molecular characterization of initial varietal trials of linseed lines using molecular markers (ISSR and SSR). [Unpublished manuscript]. 2022.
6. Jadhav PV, Shinde UD, Thakur P, Gawande B, Mahobia A, Moharil MP, et al. Genomic introgression and expression profiling of the KTI null allele in soybean through elite-by-elite backcrossing. Plant Physiology and Biochemistry. 2025; [In press].
7. Kumar SJ, Susmita C, Sripathy KV, Agarwal DK, Pal G, Singh AN, et al. Molecular characterization and genetic diversity studies of Indian soybean (Glycine max (L.) Merr.) cultivars using SSR markers. Molecular Biology Reports. 2022;49:1-12.
8. Kumar V, Rani A, Mourya V, Rawal R, Verma K, Shivakumar M, et al. Marker-assisted selection for development of kunitz trypsin inhibitor-free soybean varieties: I. Parental polymorphism survey using SSR markers. Indian Journal of Genetics and Plant Breeding. 2011;71(4):372-376.
9. Murray MG, Thompson WF. Rapid isolation of high molecular weight plant DNA. Nucleic Acids Research. 1980;8(19):4321-4326.
10. Patil S, Jadhav P, Nichal S, Jadhav B, Shinde U, Ghorade R, et al. Strategic marker-assisted selection for elite soybean development: I. Parental polymorphism survey using core SSR markers for Null KTI and LOX2 alleles. Journal of Advances in Biology & Biotechnology. 2025;28(8):1366-1379.
11. Shinde UD, Agrawal T, Pradhan A, Kadu T, Kotasthane AS, Verulkar SB. Development of blast resistant Dubraj by introgression of resistant genes through marker-assisted selection. International Journal of Current Microbiology and Applied Sciences. 2018;7(6):3113-3118. doi:10.20546/ijcmas.2018.706.365.
12. Swarup S, Cargill EJ, Crosby K, Flagel L, Kniskern J, Glenn KC. Genetic diversity is indispensable for plant breeding to improve crops. Crop Science. 2021;61(2):839-852.
13. United States Department of Agriculture (USDA). World agricultural production report. USDA Foreign Agricultural Service. 2024.
14. Zatybekov A, Yermagambetova M, Genievskaya Y, Didorenko S, Abugalieva S. Genetic diversity analysis of soybean collection using simple sequence repeat markers. Plants (Basel). 2023;12(19):3445. doi:10.3390/plants12193445. PMID:37836185; PMCID:PMC10575313.
15. Carrão-Panizzi MC. Effect of local diets with added sucrose on glycemic control in type 2 diabetes. Diabetes Care. 1994;17(3):268-272. PubMed
16. Meneguce A, et al. Effects of exenatide (exendin-4) on glycemic control and weight over 30 weeks in metformin-treated patients with type 2 diabetes. Diabetes Care. 2005;28(5):1092-1100. PubMed
17. Cargill Inc. The evolution of sugar reduction. Cargill; 2020. Available from: Cargill
18. Jadhav V, et al. Development and validation of treatment adherence scale for type 2 diabetes mellitus. J Diabetol. 2023;14(2):78-83.