DNA barcoding of the tidal swamp rice (Oryza sativa) landraces from South Kalimantan, Indonesia
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Abstract. Mursyidin DH, Nazari YA, Badruzsaufari, Masmitra MRD. 2021. DNA barcoding of the tidal swamp rice (Oryza sativa) landraces from South Kalimantan, Indonesia. Biodiversitas 22: 1593-1599. The tidal swamp rice (Oryza sativa L.) landraces of the South Kalimantan, Indonesia, has been known for hundred years ago with a better adaptation to the local conditions, such as acidity, salinity, and metals contamination. However, the genetic insight of these landraces has not fully understood. Here, the rbcL region of tidal swamp rice from this region was successfully sequenced, aligned, analyzed, and deposited into the GenBank with accession numbers of MT818188–MT818201. The multiple alignments of these sequences showing a barcoding motif with eight mutation or polymorphic sites with both substitutions (transition-transversion) and indels (insertion-deletion). Based on this marker, the tidal swamp rice has a low genetic diversity, only 0.086. However, the UPGMA and maximum likelihood (ML) analyses revealed that this germplasm was grouped into five and twoclusters or clades, respectively. In this case, Bayar Putih is closely related to Siam Panangah and farthest from Lemo. This information might help to develop conservation and breeding programs of the tidal swamp rice landraces in the future.
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References
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Thanukos A. 2008. Bringing homologies into focus. Evol Educ Outreach 1(4): 498–504.
Wei X, Huang X. 2019. Origin, taxonomy, and phylogenetics of rice. In: Rice. AACCI. Published by Elsevier Inc. in cooperation with AACC International, p. 1–29.
Wilberg E. 2015. What’s in an outgroup? The impact of outgroup choice on the phylogenetic position of Thalattosuchia (Crocodylomorpha) and the origin of Crocodyliformes. Syst Biol 64(4): 621–637.
Yu Y, Santat LA, Choi S. 2006. Bioinformatics packages for sequence analysis. Appl Mycol Biotechnol 6: 143–160.
Ajala AS, Gana A. 2015. Analysis of challenges facing rice Processing in Nigeria. J Food Process 2015: 1–6.
Anumalla M, Roychowdhury R, Geda CK, Mazid M, Rathoure AK. 2015. Utilization of plant genetic resources and diversity analysis tools for sustainable crop improvement with special emphasis on rice. Int J Adv Res 3(3): 1155–75.
Bern M, Goldberg D, Lyashenko E. 2006. Data mining for proteins characteristic of clades. Nucleic Acids Res 34(16): 4342–53.
Bhandari HR, Bhanu AN, Srivastava K, Singh MN, Shreya, Hemantaranjan A. 2017. Assessment of genetic diversity in crop plants - an overview. Adv Plants Agric Res 7(3): 279–86.
Bousquet J, Strauss SH, Doerksen AH, Price RA. 1992. Extensive variation in evolutionary rate of rbcL gene sequences among seed plants. Proc Natl Acad Sci 89: 7844–7848.
CBOL. 2009. A DNA barcode for land plants. PNAS 106(31): 12794–12797.
Clegg MT. 1993. Review and the study of plant evolution. Proc Natl Acad Sci 90: 363–367.
Corpet F. 1988. Multiple sequence alignment with hierarchical clustering. Nucleic Acids Res 16(22): 10881–10890.
Dong Z, Fan X, Sha L, Zeng J, Wang Y, Chen Q, Kang H-Y, Zhang H-Q, Zhou Y-H. 2013. Phylogeny and molecular evolution of the rbcL gene of St genome in Elymus sensu lato (Poaceae: Triticeae). Biochem Syst Ecol 50: 322–330.
Felsenstein J. 1985. Confidence-Limits on phylogenies - an approach using the bootstrap. Evol 39: 783–791.
Frankham R, Ballou JD, Briscoe DA. 2002. Introduction to conservation genetics. Cambridge University Press, Cambridge, UK.
Gholave AR, Pawar KD, Yadav SR, Bapat VA, Jadhav JP. 2017. Reconstruction of molecular phylogeny of closely related Amorphophallus species of India using plastid DNA marker and fingerprinting approaches. Physiol Mol Biol Plants 23(1): 155–167.
Govindaraj M, Vetriventhan M, Srinivasan M. 2015. Importance of genetic diversity assessment in crop plants and its recent advances: an overview of its analytical perspectives. Genet Res Int 2015: 1–14.
Hollingsworth PM, Graham SW, Little DP. 2015. Choosing and using a plant DNA barcode. PLoS One 6(5): 1–13.
Ismail AM. 2013. Flooding and submergence tolerance. Genomics Breed Clim Crop 2: 269–90.
Kirwan ML, Megonigal JP. 2013. Tidal wetland stability in the face of human impacts and sea-level rise. Nature 504(7478): 53–60.
Kück P, Wägele JW. 2016. Plesiomorphic character states cause systematic errors in molecular phylogenetic analyses: a simulation study. Cladistics. 32(4): 461–78.
Kumar S, Stecher G, Tamura K. 2018. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 35(6): 1547-1549.
Lemey P, Salemi M, Vandamme A-M. 2009. The phylogenetic handbook: A practical approach to phylogenetic analysis and hypothesis testing. Second Edit. Cambridge, UK: Cambridge University Press.
Lenaerts B, Collard BCY, Demont M. 2019. Review: Improving global food security through accelerated plant breeding. Plant Sci 287(110207): 1–8.
Liu L, Zhao B, Zhang Y, Wang J. 2012. Adaptive evolution of the rbcL gene in Brassicaceae. Biochem Syst Ecol 44: 13–19.
Moghal A, Mohler K, Ibba M. 2014. Mistranslation of the genetic code. FEBS Lett 588(23): 4305–4310.
Mursyidin DH, Nazari YA, Daryono BS. 2017. Tidal swamp rice cultivars of South Kalimantan Province, Indonesia: A case study of diversity and local culture. Biodiversitas 18(1): 427–432.
Mursyidin DH, Purnomo P, Sumardi I, Daryono BS. 2008a. Molecular diversity of tidal swamp rice (Oryza sativa L.) in South Kalimantan, Indonesia. Diversity 10(22): 1–10.
Mursyidin DH, Sumardi I, Purnomo, Daryono BS. 2018b. Pollen diversity of the tidal swamp rice (Oryza sativa L.) cultivars collected from South Kalimantan, Indonesia. Aust J Crop Sci 12(03): 380–385.
Mursyidin DH, Purnomo, Sumardi I, Daryono BS. 2019. Phenotypic diversity of the tidal swamp rice (Oryza sativa L.) germplasm from South Kalimantan, Indonesia. Aust J Crop Sci 13(03): 386–94.
Nadeem MA, Nawaz MA, Shahid MQ, Do?an Y, Comertpay G, Y?ld?z M, et al. 2018. DNA molecular markers in plant breeding: current status and recent advancements in genomic selection and genome editing. Biotechnol Biotechnol Equip 32(2): 261–85.
Nei M. 2007. The new mutation theory of phenotypic evolution. PNAS 104(30): 12235–12242.
Panesar PS, Kaur S. 2016. Rice: types and composition. In: Encyclopedia of Food and Health. 1st ed. Elsevier Ltd. p. 646–652.
Ripley LS. 2013. Mutation. In: Brenner’s Encyclopedia of Genetics: Second Edit. Elsevier Inc., p. 534–539.
Robinson SW, Afzal AM, Leader DP. 2014. Bioinformatics?: concepts, methods, and data. Elsevier Inc., Amsterdam, Netherlands.
Sereno PC. 2005. The logical basis of phylogenetic taxonomy. Syst Biol 54(4): 595–619.
Sharif MK, Butt MS, Anjum FM, Khan SH. 2014. Rice bran: a novel functional ingredient. Crit Rev Food Sci Nutr 54(6): 807–816.
Sinaga PH, Trikoesoemaningtyas, Sopandie D, Aswidinnoor H. 2014. Screening of rice genotypes and evaluation of their ratooning ability in tidal swamp area. Asian J Agric Res 8(5): 218–233.
Singh J, Banerjee S. 2018. Utility of DNA barcoding tool for conservation and molecular identification of intraspecies of rice genotypes belonging to Chhattisgarh using rbcL and matK gene sequences. Plant Arch 18: 69–75.
Thanukos A. 2008. Bringing homologies into focus. Evol Educ Outreach 1(4): 498–504.
Wei X, Huang X. 2019. Origin, taxonomy, and phylogenetics of rice. In: Rice. AACCI. Published by Elsevier Inc. in cooperation with AACC International, p. 1–29.
Wilberg E. 2015. What’s in an outgroup? The impact of outgroup choice on the phylogenetic position of Thalattosuchia (Crocodylomorpha) and the origin of Crocodyliformes. Syst Biol 64(4): 621–637.
Yu Y, Santat LA, Choi S. 2006. Bioinformatics packages for sequence analysis. Appl Mycol Biotechnol 6: 143–160.
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