GENETIC VARIABILITY AMONG DIVERSE BRASSICA NAPUS GERMPLASM USING MOLECULAR MARKERS

Sohail Ahmad Jan; Syed Muhammad Owum Haider

Sohail Ahmad Jan capital university of science and technology
Syed Muhammad Owum Haider

Keywords: B. napus, Genetic similarity, Genetic variability, Polymorphism, Punjab

Abstract

Brassica napus is the third most preferable source of edible oil after soybean and palm oil, and an emerging alternative of fossil fuel renown as green energy or biodiesel. The current study was designed to investigate the genetic diversity among 31 distinct genotypes of Brassica napus. Reliable and accurate Simple Sequence Repeats (SSRs) were used for this purpose. 10 SSRs primers unique to B. napus genotypes were used to identify genomic diversity. Out of 10 SSRs used for 31 genotypes of B. napus a total of 12 alleles were generated. The amplified fragments ranged from 100-480 bp in length and almost all the primers showed maximum polymorphic banding patterns. Out of 10 primers used 9 detected one allele each while the primer PBCESSRNA3 amplified 3 alleles. Almost, a low to high level of genetic similarity was observed among all the genotypes with values ranged from 0-100% however, maximum level (100%) of genetic similarity was among DerBn217 and DerBn215 only, that revealed the genotypes of same origin may share common ancestors. But all other genotypes showed low level or medium level similarity. Genetic similarity values of 0% was observed among ChaBn249 / FaiBn201, SheBn250 / MuzBn211 etc. The cluster analysis based on UPGMA divided all the genotypes into 5 diverse groups comprised of 6, 6, 9, 5 and 5 genotypes, respectively. Group 5 was highly diverse genotypes containing group. The 2D and 3D (Principal Coordinate Analysis) analysis further identified promising genotypes. The observations recorded with 2D analysis indicated 5 diverse genotypes LayBn222, MuzBn211, LhrBn258, OkaBn260 and LhrBn255 on the outskirts, while 3D analysis showed MulBn241, LayBn220 and SheBn250 genotypes. These results could be used as a baseline for future Brassica napus research, evaluation, and breeding selection programs.

References

Ali, N., Ali, S., Khan, N.U., Jan, S.A., Rabbani, M. A., Hussain, I., 2019. Genetic diversity of Brassica rapa germplasm of Khyber Pakhtunkhwa Pakistan revealed by molecular markers. Acta Sci. Pol. Hortorum Cultus., 18: 57-65.
Barr, D.B., Angerer, J., 2006. Potential uses of biomonitoring data: a case study using the Organophosphorus pesticides Chlorpyrifos and Malathion. Environ. Health Perspect., 114: 1763-1769.
Bhandari, H.R., Bhanu, A.N., Srivastava, K., Singh, M.N., Shreya., Hemantaranjan, A., 2017. Assessment of genetic diversity in crop plants, an overview. Adv. Plants Agric. Res., 7: 279-286.
Bird, K.A., An, H., Gazave, E., Gore, M.A., Pires, J.C., Robertson, L.D., Labate, J.A., 2017. Population structure and phylogenetic relationships in a diverse panel of Brassica rapa L. Front. Plant Sci., 8: 1-12.
Bus, A., Korber, N., Snowdon, R.J., Stich, B., 2011. Patterns of molecular variation in a species-wide germplasm set of Brassica napus. Theor. Appl. Genet., 123: 1413-1423.
Cartea, M.E., Soengas, P., Picoaga, A., Ordas, A., 2005. Relationship among Brassica napus (L.) germplasm from Spain and Great Britain as determined by RAPD markers. Genet. Resour. Crop Evol., 52: 655-662.
Channa, S.A., Tian, H., Wu, H.Q., Hu, S.W., 2016. Analysis of genetic diversity among rapseed cultivars and breeding lines by SRAP and SSR molecular markers. Pak. J. Bot., 48: 2409-2422.
El-Esawi, M.A., 2015. Genetic diversity and phylogenetic relationships of Brassica napus L. as revealed by protein profiling and SSR markers. Egypt. J. Exp. Biol. (Bot.)., 11: 245-256.
Gulden, R.H., Warwick, S.I., Thomas, A.G., 2008. The biology of Canadian weeds, 137. Brassica napus L. and Brassica rapa L. Can. J. Plant Sci., 88: 951-966.
Guzman, F.A., Moore, S., de Vicente, M.C., Jahn, M.M., 2020. Microsatellites enhance characterization, conservation, and breeding value of Capsicum germplasm. Genet. Resour. Crop Evol., 67: 569-585.
Jat, R.S., Singh, V.V., Sharma, P., Rai, P.K., 2019. Gobhi mustard (B. napus) and Ethiopian mustard Karan rai (B. carinata) are the new emerging oilseed crops having a limited area under cultivation in northern India. Sci. Rep., 26: 2-8.
Klyachenko, O.L., Prysiazhniuk, L.M., Shofolova, N.V., Piskova, O.V., 2018. Polymorphism in spring and winter rapeseed varieties (Brassica napus L.) identified by SSR markers. Plant Var. Stud. Prot., 14: 366-374.
Kumar, A., Sharma, P., Thomas, L., Agnihotri, A., Banga, S.S., 2009. Canola cultivation in India: Scenario and Future Strategy. 16th Australian Research Assembly on Brassica. Ballarat, VIC, Australia. 2009.
Li, L., Wanapu, C., Huang, X., Huang, T., Li, Q., Peng, Y., Huang, G., 2011. Comparison of AFLP and SSR for genetic diversity analysis of Brassica napus hybrids. J. Agric. Sci., 3: 101-110.
Meeghakumbura, M.K., Wambulwa, M.C., Thapa, K.K., Li, M.M., Moller, M., Xu, J.C., Yang, J.B., Liu, B.Y., Ranjitkar, S., Liu, J., Li, D.Z., Gao, L.H., 2016. Indications for three independent domestication events for the Tea plant (Camellia sinensis (L.) O. Kuntze) and new insight into the origin of Tea germplasm in China and India revealed by Nuclear Microsatellites. PloS one., 11.
Nei, M., Li, W.H., 1979. Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc. Natl. Acad. Sci. U.S.A., 76: 5269-5273.
Ofori, A., Becker, H.C., Kopisch-Obuch, F.J., 2008. Effect of crop improvement on genetic diversity in oilseed Brassica rapa (turnip-rape) cultivars, detected by SSR markers. J. Appl. Genet., 49: 207-212.
Raboanatahiry, N., Li, H., Yu, L., Li, M., 2021. Rapeseed (Brassica napus): Processing, utilization, and genetic improvement. Agron., 2021, 11: 1776.
Ramirez, D., Victorio, A.A., Beretta, V., Camargo, A., Moreno, D.A., 2020. Functional ingredients from Brassicaceae species: Overview and perspective. Int. J. Mol. Sci., 21: 1998-2006.
Rathore, S.S., Babu, S., Shekhawat, K., Singh, V.K., Upadhyay, P.K., Singh, R.K., Raj, R., Singh, H., Zaki, F.M., 2020. Oilseed Brassica species diversification and crop geometry influence and productivity, economics, and environmental footprints under semi-arid regions. Sustain. Sci., 14: 22-30.
Rohlf, F.J., 2002. NTSYS-pc numerical taxonomy system version 2.1. Setauket, Newyork: Exeter Publishing Limited.
Sika, K.C., Kefela, T., Sagbadja, H.A., Ahoton, L., Saidou, A., Moussa, L.B., Gachomo, E.W., 2015. A simple and efficient genomic DNA extraction protocol for large scale genetic analyses of plant biological systems. Plant Gene. 1: 43-45.
Sneath, P.H., Sokal, R.R., 1973. Numerical taxonomy: The principles and practice of numerical classification. Am. Stat. Assoc., 70: 962.
Turi, N.A., Farhatullah., Rabbani, M.A., Shinwari, Z.K., 2012. Genetic diversity in the locally collected Brassica species of Pakistan based on Microsatellite markers. Pak. J. Bot., 44: 1029-1035.
Verma, K., Tripathi, M.K., Tiwari, S., Tripathi, N., 2021. Analysis of genetic diversity among Brassica juncea genotypes using morpho-physiological and SSR markers. Int. J. Curr. Microbiol. Appl. Sci., 10: 1108-1117.
Vinu, V., Singh, N., Vasudev, S., Yadava, D.K., Kumar, S., Naresh, S., Bhat, S.R., Prabhu, K.V., 2013. Assessment of genetic diversity in Brassica juncea (Brassicaceae) genotypes using phenotypic differences and SSR markers. Rev. Biol. Trop., 61: 1919-1934.
Wang, X., Chatwin, W., Hilton, A., Kubenka, K., 2022. Genetic diversity revealed by microsatellites in genus Carya. Forests., 13: 188.
Yao, Q.L., Chen, F.B., Fang, P., Zhou, G.F., Fan, Y.H., Zhang, Z.R., 2012. Genetic diversity of Chinese vegetable mustard (Brassica juncea Coss) landraces based on SSR data. Biochem. Syst. Ecol., 45: 41-48.
Yu, S., Zhang, F., Wang, X., Zhao, X., Zhang, D., Yu, Y., Xu, J., 2010. Genetic diversity, and marker-trait associations in a collection of Pak-choi (Brassica rapa L. ssp. chinensis Makino) accessions. Mol. Genet. Genom., 32: 419-428.