Genic codominant multiallelic markers are essential to identify the genetic variation, population diversity and evolutionary history of a species. Soybean (Glycine max) is a major legume crop having importance in both a protein-rich pulse as well as a high recovery oilseed crop. To date, no genome-wide genic SSR markers have been elucidated in this crop of high importance. This article aims to identify and validate regulatory gene-derived SSR markers in soybean. The coding sequences of Glycine max were downloaded from PlantTFDB and used for the identification, followed by the localization of SSRs by using a Perl 5 script (MISA, MIcroSAtellite identification tool). The flanking primers to SSRs were designed and chromosomal distribution and Gene ontology searches were performed using BLAST2GO. Twenty random SSR markers were validated to check cross-species transferability and genetic diversity study was performed. A set of 1138 simple sequence repeat markers from transcription factor coding genes were designed and designated as TF-derived SSR markers. They were anchored on 20 G. max chromosomes, and the SSR motif frequency was one per 4.64 kb. Trinucleotide repeats were found abundant and tetra, as well as pentanucleotide frequency, was least in soybean. Gene Ontology search revealed the diverse role of SSR-containing TFs in soybean. Eight soybean accessions were analyzed for identified twenty candidates for genic SSR diversification, and a principal co-ordinate analysis, a genic dissimilarity-based unweighted neighbour-joining tree, was constructed. Our findings will serve as a potential functional marker resource for marker-assisted selection and genomic characterization of soybean.
Keywords: Transcription Factor (TFs), SSR, Genic Marker, Gene Ontology, Genetic Diversity
Full text and supplemented materials
References
Bandelj, D. and Jakše, J., Assessment of genetic variability of olive varieties by microsatellite and AFLP markers, Euphytica, 2004, vol. 136, pp. 93–102. https://doi.org/10.1023/B:EUPH.0000019552.42066.10
Beier, S., Thiel, T., Münch, T., et al., MISA-web: A web server for microsatellite prediction, Bioinformatics, 2017, vol. 33, pp. 2583–2585. https://doi.org/10.1093/BIOINFORMATICS/BTX198
Bosamia, T.C., Mishra, G.P., Thankappan, R., and Dobaria, J.R., Novel and stress relevant EST derived SSR markers developed and validated in peanut, PLoS One, 2015, vol. 10, p. e0129127. https://doi.org/10.1371/JOURNAL.PONE.0129127
Conesa, A., Götz, S., García-Gómez, J., et al., Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. academic.oup.com
Fredslund, J., Madsen, L.H., Hougaard, B.K., et al., A general pipeline for the development of anchor markers for comparative genomics in plants, BMC Genomics, 2006, vol. 7, no. 1, p. 207. https://doi.org/10.1186/1471-2164-7-207
Gepts, P., Beavis, W., Brummer, E., and Shoemaker, R., Legumes as a model plant family, Genomics for food and feed report of the cross-legume advances through genomics conference, Plant Physiol., 2005, vol. 137, no. 4, pp. 1228–1235.
Hisano, H., Sato, S., Isobe, S., et al., Characterization of the soybean genome using EST-derived microsatellite markers, DNA Res., 2007, vol. 14, pp. 271–281. https://doi.org/10.1093/DNARES/DSM025
Jin, J., Zhang, H., Kong, L., et al., PlantTFDB 3.0: A portal for the functional and evolutionary study of plant transcription factors, Nucleic Acids Res., 2014, vol. 42, pp. D1182–D1187. https://doi.org/10.1093/NAR/GKT1016
Kujur, A., Bajaj, D., Saxena, M.S., et al., Functionally relevant microsatellite markers from chickpea transcription factor genes for efficient genotyping applications and trait association mapping, DNA Res., 2013, vol. 20, pp. 355–374. https://doi.org/10.1093/DNARES/DST015
Kumar Biswas, M., Kumar Nath, U., Howlader, J., et al., Exploration and exploitation of novel SSR markers for candidate transcription factor genes in Lilium species, Genes, 2018, vol. 9, no. 2, p. 97. https://doi.org/10.3390/genes9020097
Liu, Y.L., Li, Y.H., Zhou, G.A., et al., Development of soybean EST-SSR markers and their use to assess genetic diversity in the subgenus Soja, Agric. Sci. China, 2010, vol. 9, pp. 1423–1429. https://doi.org/10.1016/S1671-2927(09)60233-9
Liu, W., Jia, X., Liu, Z., et al., Development and characterization of Transcription Factor Gene-Derived Microsatellite (TFGM) Markers in Medicago truncatula and their transferability in leguminous and non-leguminous species, Molecules, 2015, vol. 20, pp. 8759–8771. https://doi.org/10.3390/molecules20058759
Liu, N., Cheng, F.Yun., Guo, X., and Zhong, Y., Development and application of microsatellite markers within transcription factors in flare tree peony (Paeonia rockii) based on next-generation and single-molecule long-read RNA-seq, J. Integr. Agric., 2021, vol. 20, pp. 1832–1848. https://doi.org/10.1016/S2095-3119(20)63402-5
Parmar, R., Seth, R., and Sharma, R.K., Genome-wide identification and characterization of functionally relevant microsatellite markers from transcription factor genes of Tea (Camellia sinensis (L.) O. Kuntze), Sci. Rep., 2022, vol. 12, pp. 1–14. https://doi.org/10.1038/s41598-021-03848-x
Saha, D., Rana, R.S., Das, S., et al., Genome-wide regulatory gene-derived SSRs reveal genetic differentiation and population structure in fiber flax genotypes, J. Ap-pl. Genet, 2019, vol. 60, pp. 13–25. https://doi.org/10.1007/S13353-018-0476-Z
Spitz, F., Genetics EF-N reviews, Transcription factors: from enhancer binding to developmental control, Nat. Rev. Genet., 2012, vol. 13, p. 613–626. https://doi.org/10.1038/nrg3207
Stefanova, P., Taseva, M., Georgieva, T., et al., A modified CTAB method for DNA extraction from soybean and meat products, Biotechnol. Biotechnol. Equip., 2013, vol. 27, pp. 3803–3810. https://doi.org/10.5504/BBEQ.2013.0026
Varshney, R.K., Thiel, T., and Stein, N., In silico analysis on frequency and distribution of microsatellites in ESTs of some cereal species, Cell Mol. Biol. Lett., 2002, vol. 7, no. 2A, pp. 537–546.
Ye, J., Fang, L., Zheng, H., et al., WEGO: a web tool for plotting GO annotations, Nucleic Acids Res., 2006, vol. 34, pp. 293–297. https://doi.org/10.1093/NAR/GKL031