Analisis Keragaman Genetik dan Pembuatan DNA Barcoding pada Galur Kedelai Tropis Berdasarkan Marka SSR
Abstract
Soybean cultivation in tropical regions, such as Indonesia, is often constrained by photoperiod sensitivity, consequently resulting in low yield. The use of long juvenile trait in short photoperiod tropical areas resulted lines with late flowering time and high yield. Genetic diversity analysis of soybean lines using molecular markers are critical steps for breeding high yielding soybean lines. The aim of this study was to analyze genetic diversity and construct DNA barcodes for 44 tropical soybean advanced lines based on 17 SSR markers. Genetic materials used were the high yielding F5 soybean lines developed for their adaptation to short day-length of low latitude tropical regions. SSR markers used were those that distributed well across the soybean genome and proven their usefulness for soybean genetic diversity analyses. Results showed that the SSR used demonstrated distinctive polymorphism among the 44 lines. A total of 377 alleles was detected with an average of 22.8 alleles per SSR locus. Polymorphism information content (PIC) values varied from 0.77 to 0.96 with an average of 0.90. Phylogenetic analysis showed that the 44 soybean genotypes were divided into 2 main clusters. Five markers, i.e., satt009, satt646, satt147, satt431, and satt191, with a polymorphism information content value of ≥0.94, were found to be informative and suitable for DNA barcode construction. Each of the 44 lines was assigned with specific barcodes. The barcodes constructed from this study should be useful for DNA fingerprint as well as protection purposes of the specific superior soybean lines analyzed in this study.
Downloads
Download data is not yet available.
References
Amiteye S. 2021. Basic concepts and methodologies of DNA marker systems in plant molecular breeding. Heliyon. 7(10): e08093. https://doi.org/10.1016/j.heliyon.2021.e08093
Asadi A, Dewi N, Nugroho K, Terryana RT, Mastur, Lestari P. 2020. Evaluation of SSR and important agronomical characters of promising mutant lines of soybean. Biodiversitas. 21(1): 299–310. https://doi.org/10.13057/biodiv/d210137
Barcodes. 2021. Barcode marker online. Barcodes Inc, Chicago (USA). Tersedia pada: https://www.barcodesinc.com/generator/index.ph
Bisen A, Khare D, Nair P, Tripathi N. 2015. SSR analysis of 38 genotypes of soybean (Glycine max (L.) Merr.) genetic diversity in India. Physiology and Molecular Biology of Plants. 21: 109-115. https://doi.org/10.1007/s12298-014-0269-8
Botstein D, White RL, Skolnick M, Davis RW. 1980. Construction of a genetic linkage map in man using restriction fragment length polymorphisms. American Journal of Human Genetics. 32(3): 314-331.
Carpentieri-Pípolo V, Almeida LAD, Kiihl RADS. 2002. Inheritance of a long juvenile period under short-day conditions in soybean. Genetics and Molecular Biology. 25: 463-469. https://doi.org/10.1590/S1415-47572002000400016
Chinnappareddy LRD, Khandagale K, Reddy SHS, Kanupriya C, Chennareddy A, Singh TH. 2012. SSR-based DNA barcodes as a tool for identification of eggplant genotypes. International Journal of Vegetable Science. 18(3): 260-271. https://doi.org/10.1080/19315260.2011.633976
Chung JW, Lee GA, Lee SS, Bang KH, Park CB, Park YJ. 2009. Cultivar discrimination of Korean and Chinese Boxthorn (Lycium chinense Mill. and Lycium barbarum L.) using SSR markers. Korean Journal of Medicinal Crop Science. 17(6): 445-451.
Cregan PB, Jarvik T, Bush AL, Shoemaker RC, Lark KG, Kahler AL, Kaya N, VanToai TT, Lohnes DG, Chung J, Specht JE. 1999. An integrated genetic linkage map of the soybean genome. Crop Science. 39(5): 1464-1490. https://doi.org/10.2135/cropsci1999.3951464x
Das A, Kesari V, Satyanarayana VM, Parida A, Mitra S, Rangan L. 2015. Genetic diversity in ecotypes of the scarce wild medicinal crop Zingiber moran revealed by ISSR and AFLP marker analysis and chromosome number assessment. Plant Biosystems-An International Journal Dealing with all Aspects of Plant Biology. 149(1): 111-120. https://doi.org/10.1080/11263504.2013.795197
Denwar NN, Awuku FJ, Diers B, Addae-Frimpomaah F, Chigeza G, Oteng-Frimpong R, Puozaa DK, Barnor MT. 2009. Genetic diversity, population structure and key phenotypic traits driving variation within soyabean (Glycine max) collection in Ghana. Plant Breeding. 138(5): 577-587. https://doi.org/10.1111/pbr.12700
Diwan N, Cregan PB. 1997. Automated sizing of fluorescent-labeled simple sequence repeat (SSR) markers to assay genetic variation in soybean. Theoretical and Applied Genetics. 95: 723-733. https://doi.org/10.1007/s001220050618
Dong YS, Zhao LM, Liu B, Wang ZW, Jin ZQ, Sun H. 2004. The genetic diversity of cultivated soybean grown in China. Theoretical and Applied Genetics. 108: 931-936. https://doi.org/10.1007/s00122-003-1503-x
dos Santos Silva FC, Sediyama T, de Cássia Teixeira Oliveira R, Borém A, da Silva FL, Bezerra ARG, da Silva AF. 2017. Economic importance and evolution of breeding. In: Lopes da Silva F, Borém A, Sediyama T, Ludke W. (eds) Soybean Breeding. Springer, Cham. 1-16. https://doi.org/10.1007/978-3-319-57433-2_1
Doyle JJ, Doyle JL. 1990. A rapid total DNA preparation procedure for fresh plant tissue. Focus. 12: 13-15.
Epstein R, Sajai N, Zelkowski M, Zhou A, Robbins KR, Pawlowski WP. 2023. Exploring impact of recombination landscapes on breeding outcomes. Proceedings of the National Academy of Sciences. 120(14): e2205785119. https://doi.org/10.1073/pnas.220578511
[FAO] Food and Agriculture Organization. 2021. FAOSTAT. Tersedia pada: https://www.fao.org/faostat/en/#data
Gupta S, Agrawal N, Tripathi R, Kumawat G, Nataraj V, Maranna S, Satpute GK, Ratnaparkhe MB, Rajesh V, Chandra S, Jain M. 2021. Long juvenility trait: A vehicle for commercial utilization of soybean (Glycine max) in lower latitudes. Plant Breeding. 140(4): 543-560. https://doi.org/10.1111/pbr.12926
Harisha R, Bhadru D, Vanisri S, Gourishanakar V, Satish L. 2021. SSR and morphological traits based fingerprints and DNA barcodes for varietal identification in rice. Biotechnology & Biotechnological Equipment. 35(1): 1461-1473. https://doi.org/10.1080/13102818.2021.1987324
Hartwig EE, Kiihl RA. 1979. Identification and utilization of a delayed flowering character in soybeans for short-day conditions. Field Crops Research. 2: 145-151. https://doi.org/10.1016/0378-4290(79)90017-0
Hossain MA, Islam MM, Emon RM, Rana MS, Hossain MA, Uddin MI, Malek M A, Khan NA, Nuruzzaman M. 2020. Microsatellite-based DNA fingerprinting and genetic analysis of some selected aus rice (Oryza sativa L.) genotypes. Annals of Agricultural & Crop Sciences. 5(3): 1066.
Jian C, Deyi Q, Qiaoyun Y, Jia H, Dexing L, Xiaoya W, Leiqing Z. 2014. A successful case of DNA barcoding used in an international trade dispute. DNA Barcodes. 2(1): 21-28. https://doi.org/10.2478/dna-2014-0004
Kachare S, Tiwari S, Tripathi N, Thakur VV. 2020. Assessment of genetic diversity of soybean (Glycine max) genotypes using qualitative traits and microsatellite markers. Agricultural Research. 9(1): 23-34. https://doi.org/10.1007/s40003-019-00412-y
Kanupriya, Latha PM, Aswath C, Reddy L, Padmakar B, Vasugi C, Dinesh MR. 2011. Cultivar identification and genetic fingerprinting of guava (Psidium guajava) using microsatellite markers. International Journal of Fruit Science. 11: 184-196. http://dx.doi.org/10.1080/15538362.2011.578521
Khanande AS, Jadhav PV, Kale PB, Madavi SM, Mohari MP, Nichal SS. 2016. Genetic diversity in vegetable and grain type soybean genotypes identified using morphological descriptor and EST-SSR markers. Vegetos-An International Journal of Plant Research. 29(3): 158–173. https://doi.org/10.4172/2229-4473.1000156
Kumar SJ, Susmita C, Sripathy KV, Agarwal DK, Pal G, Singh AN, Kumar S, Rai AK, Simal-Gandara J. 2022. Molecular characterization and genetic diversity studies of Indian soybean (Glycine max (L.) Merr.) cultivars using SSR markers. Molecular Biology Reports. 49: 2129–2140. https://doi.org/10.1007/s11033-021-07030-4
Lazer IJ, Horvath-Lazar E. 2010. Gel Analyzer 2010a: freeware 1D gel electrophoresis image analysis software. Tersedia pada: http://www.gelanalyzer.com/index.html
Lestari P, Putri RE, Rineksane IA, Handayani E, Nugroho K, Terryana RT. 2021. Keragaman genetik 27 aksesi Kedelai (Glycine max l. Merr.) introduksi subtropis berdasarkan marka SSR. Vegetalika. 10(1): 1-17. https://doi.org/10.22146/veg.58418
Li X, Yang Y, Henry R J, Rossetto M, Wang Y, Chen S. 2015. Plant DNA barcoding: from gene to genome. Biological Reviews. 90(1): 157-166. https://doi.org/10.1111/brv.12104
Liu J, Li M, Zhang Q, Wei X, Huang X. 2020. Exploring the molecular basis of heterosis for plant breeding. Journal of Integrative Plant Biology. 62(3): 287-298. https://doi.org/10.1111/jipb.12804
Liu K, Muse SV. 2005. PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics. 21(9): 2128-2129. https://doi.org/10.1093/bioinformatics/bti282
Liu Z, Li H, Wang X, Zhang Y, Gou Z, Zhao X, Ren H, Wen Z, Li Y, Yu L, Gao H, Wang D, Qi X, Qiu L. 2023. QTL for yield per plant under water deficit and well-watered conditions and drought susceptibility index in soybean (Glycine max (L.) Merr.). Biotechnology & Biotechnological Equipment. 37(1): 92-103. https://doi.org/10.1080/13102818.2022.2155569
Lu S, Zhao X, Hu Y, Liu S, Nan H, Li X, Fang C, Cao D, Shi X, Kong L, Su T, Zhang F, Li S, Wang Z, Yuan X, Cober ER, Weller JL, Liu B, Hou X, Tian Z, Kong F. 2017. Natural variation at the soybean J locus improves adaptation to the tropics and enhances yield. Nature Genetics. 49(5): 773-779. https://doi.org/10.1038/ng.3819
Manjarrez‐Sandoval P, Carter Jr TE, Webb DM, Burton JW. 1997. Heterosis in soybean and its prediction by genetic similarity measures. Crop Science: 37(5): 1443-1452. https://doi.org/10.2135/cropsci1997.0011183X003700050005x
Mukuze C, Tukamuhabwa P, Maphosa M, Dari S, Dramadri IO, Obua T, Kongai H, Rubaihayo P. 2020. Genetic diversity analysis among soybean genotypes using SSR markers in Uganda. African Journal of Biotechnology. 19(7): 439-448. https://doi.org/10.5897/AJB2020.17152
Pardeshi P, Jadhav P, Sakhare S, Zunjare R, Rathod D, Sonkamble P, Saroj R, Varghese P. 2023. Morphological and microsatellite marker-based characterization and diversity analysis of novel vegetable soybean [Glycine max (L.) Merrill]. Molecular Biology Reports. 50(5): 4049-4060. https://doi.org/10.1007/s11033-023-08328-1
Presello DA, Reid LM, Butler G, Mather DE. 2005. Pedigree selection for Gibberella ear rot resistance in maize. Euphytica. 143: 1-8. https://doi.org/10.1007/s10681-005-6149-0
Rani A, Kumar V. Shukla S, Jha P, Rawal R. 2016. DNA barcoding of Indian soybean varieties as constructed through SSR markers. Seed Science and Technology. 44(2): 357-369. https://doi.org/10.15258/sst.2016.44.2.18
Ray JD, Hinson K, Mankono JEB, Malo MF. 1995. Genetic control of a long‐juvenile trait in soybean. Crop Science. 35(4): 1001-1006. https://doi.org/10.2135/cropsci1995.0011183X003500040012x
Rohlf FJ. 2000. NTSYS-pc: Numerical taxonomy and multivariate analysis system, version 2.1. Exeter Publishing, Setauket (NY).
Sambrook J, Fritch EF, Maniatis T. 1989. Molecular cloning: a laboratory manual. Cold Spring Harbor Laboratory Press, Cold Spring Harbor (NY).
Singh AK, Chaurasia S, Kumar S, Singh R, Kumari J, Yadav MC, Singh N, Gaba S, Jacob SR. 2018. Identification, analysis and development of salt responsive candidate gene based SSR markers in wheat. BMC Plant Biology. 18(1): 1-15. https://doi.org/10.1186/s12870-018-1476-1
Sohn HB, Kim SJ, Hwang TY, Park HM, Lee YY, Markkandan K, Lee D, Lee S, Hong S Y, Song YH, Koo BC, Kim YH. 2017. Barcode system for genetic identification of soybean [Glycine max (L.) Merrill] cultivars using InDel markers specific to dense variation blocks. Frontiers in Plant Science. 8: 520. https://doi.org/10.3389/fpls.2017.00520
Spehar CR. 1995. Impact of strategic genes in soybean on agricultural development in the Brazilian tropical savannahs. Field Crops Research. 41(3): 141-146. https://doi.org/10.1016/0378-4290(95)00007-D
Tasma IM, Lorenzen LL, Green DE, Shoemaker RC. 2001. Mapping genetic loci for flowering time, maturity, and photoperiod insensitivity in soybean. Molecular Breeding. 8: 25-35. https://doi.org/10.1023/A:1011998116037
Tasma IM, Shoemaker RC. 2003. Mapping flowering time gene homologs in soybean and their association with maturity (E) loci. Crop Science. 43(1): 319-328. https://doi.org/10.2135/cropsci2003.3190
Tasma IM, Yani NMG, Purwaningdyah R, Satyawan D, Nugroho K, Lestari P, Kurniawan R, Trijatmiko, Mastur. 2018. Genetic diversity analysis and F2 population development for breeding of long juvenile trait in soybean. Jurnal AgroBiogen. 14(1): 11-22.
Ullah A, Akram Z, Malik SI, Khan KSU. 2021. Assessment of phenotypic and molecular diversity in soybean [Glycine max (L.) Merr.] germplasm using morpho-biochemical attributes and SSR markers. Genetic Resources and Crop Evolution. 68: 2827-2847. https://doi.org/10.1007/s10722-021-01157-w
Valentini A, Pompanon F, Taberlet P. 2009. DNA barcoding for ecologists. Trends in Ecology & Evolution. 24(2): 110-117. https://doi.org/10.1016/j.tree.2008.09.011
Wang L, Guan R, Zhang XL, Chang R, Qiu L. 2006. Genetic diversity of Chinese cultivated soybean revealed by SSR markers. Crop Science. 46(3): 1032-1038. https://doi.org/10.2135/cropsci2005.0051
Wibisono K, Aisyah SI, Nurcholis W, Suhesti S. 2022. Sensitivity in callus tissue of Plectranthus amboinicus (L.) through mutation induction with colchicine. Agrivita Journal of Agricultural Science. 44(1): 82-95. http://doi.org/10.17503/agrivita.v44i1.3058
Widaningsih NA, Purwanto E, Nandariyah N, Reflinur R. 2014. The use of DNA microsatellite markers for genetic diversity identification of soybean (Glycine max (L) Meriil.) as a supplementary method in reference collections management. Indonesian Journal of Biotechnology. 19(2): 136-145. https://doi.org/10.22146/ijbiotech.9306
Asadi A, Dewi N, Nugroho K, Terryana RT, Mastur, Lestari P. 2020. Evaluation of SSR and important agronomical characters of promising mutant lines of soybean. Biodiversitas. 21(1): 299–310. https://doi.org/10.13057/biodiv/d210137
Barcodes. 2021. Barcode marker online. Barcodes Inc, Chicago (USA). Tersedia pada: https://www.barcodesinc.com/generator/index.ph
Bisen A, Khare D, Nair P, Tripathi N. 2015. SSR analysis of 38 genotypes of soybean (Glycine max (L.) Merr.) genetic diversity in India. Physiology and Molecular Biology of Plants. 21: 109-115. https://doi.org/10.1007/s12298-014-0269-8
Botstein D, White RL, Skolnick M, Davis RW. 1980. Construction of a genetic linkage map in man using restriction fragment length polymorphisms. American Journal of Human Genetics. 32(3): 314-331.
Carpentieri-Pípolo V, Almeida LAD, Kiihl RADS. 2002. Inheritance of a long juvenile period under short-day conditions in soybean. Genetics and Molecular Biology. 25: 463-469. https://doi.org/10.1590/S1415-47572002000400016
Chinnappareddy LRD, Khandagale K, Reddy SHS, Kanupriya C, Chennareddy A, Singh TH. 2012. SSR-based DNA barcodes as a tool for identification of eggplant genotypes. International Journal of Vegetable Science. 18(3): 260-271. https://doi.org/10.1080/19315260.2011.633976
Chung JW, Lee GA, Lee SS, Bang KH, Park CB, Park YJ. 2009. Cultivar discrimination of Korean and Chinese Boxthorn (Lycium chinense Mill. and Lycium barbarum L.) using SSR markers. Korean Journal of Medicinal Crop Science. 17(6): 445-451.
Cregan PB, Jarvik T, Bush AL, Shoemaker RC, Lark KG, Kahler AL, Kaya N, VanToai TT, Lohnes DG, Chung J, Specht JE. 1999. An integrated genetic linkage map of the soybean genome. Crop Science. 39(5): 1464-1490. https://doi.org/10.2135/cropsci1999.3951464x
Das A, Kesari V, Satyanarayana VM, Parida A, Mitra S, Rangan L. 2015. Genetic diversity in ecotypes of the scarce wild medicinal crop Zingiber moran revealed by ISSR and AFLP marker analysis and chromosome number assessment. Plant Biosystems-An International Journal Dealing with all Aspects of Plant Biology. 149(1): 111-120. https://doi.org/10.1080/11263504.2013.795197
Denwar NN, Awuku FJ, Diers B, Addae-Frimpomaah F, Chigeza G, Oteng-Frimpong R, Puozaa DK, Barnor MT. 2009. Genetic diversity, population structure and key phenotypic traits driving variation within soyabean (Glycine max) collection in Ghana. Plant Breeding. 138(5): 577-587. https://doi.org/10.1111/pbr.12700
Diwan N, Cregan PB. 1997. Automated sizing of fluorescent-labeled simple sequence repeat (SSR) markers to assay genetic variation in soybean. Theoretical and Applied Genetics. 95: 723-733. https://doi.org/10.1007/s001220050618
Dong YS, Zhao LM, Liu B, Wang ZW, Jin ZQ, Sun H. 2004. The genetic diversity of cultivated soybean grown in China. Theoretical and Applied Genetics. 108: 931-936. https://doi.org/10.1007/s00122-003-1503-x
dos Santos Silva FC, Sediyama T, de Cássia Teixeira Oliveira R, Borém A, da Silva FL, Bezerra ARG, da Silva AF. 2017. Economic importance and evolution of breeding. In: Lopes da Silva F, Borém A, Sediyama T, Ludke W. (eds) Soybean Breeding. Springer, Cham. 1-16. https://doi.org/10.1007/978-3-319-57433-2_1
Doyle JJ, Doyle JL. 1990. A rapid total DNA preparation procedure for fresh plant tissue. Focus. 12: 13-15.
Epstein R, Sajai N, Zelkowski M, Zhou A, Robbins KR, Pawlowski WP. 2023. Exploring impact of recombination landscapes on breeding outcomes. Proceedings of the National Academy of Sciences. 120(14): e2205785119. https://doi.org/10.1073/pnas.220578511
[FAO] Food and Agriculture Organization. 2021. FAOSTAT. Tersedia pada: https://www.fao.org/faostat/en/#data
Gupta S, Agrawal N, Tripathi R, Kumawat G, Nataraj V, Maranna S, Satpute GK, Ratnaparkhe MB, Rajesh V, Chandra S, Jain M. 2021. Long juvenility trait: A vehicle for commercial utilization of soybean (Glycine max) in lower latitudes. Plant Breeding. 140(4): 543-560. https://doi.org/10.1111/pbr.12926
Harisha R, Bhadru D, Vanisri S, Gourishanakar V, Satish L. 2021. SSR and morphological traits based fingerprints and DNA barcodes for varietal identification in rice. Biotechnology & Biotechnological Equipment. 35(1): 1461-1473. https://doi.org/10.1080/13102818.2021.1987324
Hartwig EE, Kiihl RA. 1979. Identification and utilization of a delayed flowering character in soybeans for short-day conditions. Field Crops Research. 2: 145-151. https://doi.org/10.1016/0378-4290(79)90017-0
Hossain MA, Islam MM, Emon RM, Rana MS, Hossain MA, Uddin MI, Malek M A, Khan NA, Nuruzzaman M. 2020. Microsatellite-based DNA fingerprinting and genetic analysis of some selected aus rice (Oryza sativa L.) genotypes. Annals of Agricultural & Crop Sciences. 5(3): 1066.
Jian C, Deyi Q, Qiaoyun Y, Jia H, Dexing L, Xiaoya W, Leiqing Z. 2014. A successful case of DNA barcoding used in an international trade dispute. DNA Barcodes. 2(1): 21-28. https://doi.org/10.2478/dna-2014-0004
Kachare S, Tiwari S, Tripathi N, Thakur VV. 2020. Assessment of genetic diversity of soybean (Glycine max) genotypes using qualitative traits and microsatellite markers. Agricultural Research. 9(1): 23-34. https://doi.org/10.1007/s40003-019-00412-y
Kanupriya, Latha PM, Aswath C, Reddy L, Padmakar B, Vasugi C, Dinesh MR. 2011. Cultivar identification and genetic fingerprinting of guava (Psidium guajava) using microsatellite markers. International Journal of Fruit Science. 11: 184-196. http://dx.doi.org/10.1080/15538362.2011.578521
Khanande AS, Jadhav PV, Kale PB, Madavi SM, Mohari MP, Nichal SS. 2016. Genetic diversity in vegetable and grain type soybean genotypes identified using morphological descriptor and EST-SSR markers. Vegetos-An International Journal of Plant Research. 29(3): 158–173. https://doi.org/10.4172/2229-4473.1000156
Kumar SJ, Susmita C, Sripathy KV, Agarwal DK, Pal G, Singh AN, Kumar S, Rai AK, Simal-Gandara J. 2022. Molecular characterization and genetic diversity studies of Indian soybean (Glycine max (L.) Merr.) cultivars using SSR markers. Molecular Biology Reports. 49: 2129–2140. https://doi.org/10.1007/s11033-021-07030-4
Lazer IJ, Horvath-Lazar E. 2010. Gel Analyzer 2010a: freeware 1D gel electrophoresis image analysis software. Tersedia pada: http://www.gelanalyzer.com/index.html
Lestari P, Putri RE, Rineksane IA, Handayani E, Nugroho K, Terryana RT. 2021. Keragaman genetik 27 aksesi Kedelai (Glycine max l. Merr.) introduksi subtropis berdasarkan marka SSR. Vegetalika. 10(1): 1-17. https://doi.org/10.22146/veg.58418
Li X, Yang Y, Henry R J, Rossetto M, Wang Y, Chen S. 2015. Plant DNA barcoding: from gene to genome. Biological Reviews. 90(1): 157-166. https://doi.org/10.1111/brv.12104
Liu J, Li M, Zhang Q, Wei X, Huang X. 2020. Exploring the molecular basis of heterosis for plant breeding. Journal of Integrative Plant Biology. 62(3): 287-298. https://doi.org/10.1111/jipb.12804
Liu K, Muse SV. 2005. PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics. 21(9): 2128-2129. https://doi.org/10.1093/bioinformatics/bti282
Liu Z, Li H, Wang X, Zhang Y, Gou Z, Zhao X, Ren H, Wen Z, Li Y, Yu L, Gao H, Wang D, Qi X, Qiu L. 2023. QTL for yield per plant under water deficit and well-watered conditions and drought susceptibility index in soybean (Glycine max (L.) Merr.). Biotechnology & Biotechnological Equipment. 37(1): 92-103. https://doi.org/10.1080/13102818.2022.2155569
Lu S, Zhao X, Hu Y, Liu S, Nan H, Li X, Fang C, Cao D, Shi X, Kong L, Su T, Zhang F, Li S, Wang Z, Yuan X, Cober ER, Weller JL, Liu B, Hou X, Tian Z, Kong F. 2017. Natural variation at the soybean J locus improves adaptation to the tropics and enhances yield. Nature Genetics. 49(5): 773-779. https://doi.org/10.1038/ng.3819
Manjarrez‐Sandoval P, Carter Jr TE, Webb DM, Burton JW. 1997. Heterosis in soybean and its prediction by genetic similarity measures. Crop Science: 37(5): 1443-1452. https://doi.org/10.2135/cropsci1997.0011183X003700050005x
Mukuze C, Tukamuhabwa P, Maphosa M, Dari S, Dramadri IO, Obua T, Kongai H, Rubaihayo P. 2020. Genetic diversity analysis among soybean genotypes using SSR markers in Uganda. African Journal of Biotechnology. 19(7): 439-448. https://doi.org/10.5897/AJB2020.17152
Pardeshi P, Jadhav P, Sakhare S, Zunjare R, Rathod D, Sonkamble P, Saroj R, Varghese P. 2023. Morphological and microsatellite marker-based characterization and diversity analysis of novel vegetable soybean [Glycine max (L.) Merrill]. Molecular Biology Reports. 50(5): 4049-4060. https://doi.org/10.1007/s11033-023-08328-1
Presello DA, Reid LM, Butler G, Mather DE. 2005. Pedigree selection for Gibberella ear rot resistance in maize. Euphytica. 143: 1-8. https://doi.org/10.1007/s10681-005-6149-0
Rani A, Kumar V. Shukla S, Jha P, Rawal R. 2016. DNA barcoding of Indian soybean varieties as constructed through SSR markers. Seed Science and Technology. 44(2): 357-369. https://doi.org/10.15258/sst.2016.44.2.18
Ray JD, Hinson K, Mankono JEB, Malo MF. 1995. Genetic control of a long‐juvenile trait in soybean. Crop Science. 35(4): 1001-1006. https://doi.org/10.2135/cropsci1995.0011183X003500040012x
Rohlf FJ. 2000. NTSYS-pc: Numerical taxonomy and multivariate analysis system, version 2.1. Exeter Publishing, Setauket (NY).
Sambrook J, Fritch EF, Maniatis T. 1989. Molecular cloning: a laboratory manual. Cold Spring Harbor Laboratory Press, Cold Spring Harbor (NY).
Singh AK, Chaurasia S, Kumar S, Singh R, Kumari J, Yadav MC, Singh N, Gaba S, Jacob SR. 2018. Identification, analysis and development of salt responsive candidate gene based SSR markers in wheat. BMC Plant Biology. 18(1): 1-15. https://doi.org/10.1186/s12870-018-1476-1
Sohn HB, Kim SJ, Hwang TY, Park HM, Lee YY, Markkandan K, Lee D, Lee S, Hong S Y, Song YH, Koo BC, Kim YH. 2017. Barcode system for genetic identification of soybean [Glycine max (L.) Merrill] cultivars using InDel markers specific to dense variation blocks. Frontiers in Plant Science. 8: 520. https://doi.org/10.3389/fpls.2017.00520
Spehar CR. 1995. Impact of strategic genes in soybean on agricultural development in the Brazilian tropical savannahs. Field Crops Research. 41(3): 141-146. https://doi.org/10.1016/0378-4290(95)00007-D
Tasma IM, Lorenzen LL, Green DE, Shoemaker RC. 2001. Mapping genetic loci for flowering time, maturity, and photoperiod insensitivity in soybean. Molecular Breeding. 8: 25-35. https://doi.org/10.1023/A:1011998116037
Tasma IM, Shoemaker RC. 2003. Mapping flowering time gene homologs in soybean and their association with maturity (E) loci. Crop Science. 43(1): 319-328. https://doi.org/10.2135/cropsci2003.3190
Tasma IM, Yani NMG, Purwaningdyah R, Satyawan D, Nugroho K, Lestari P, Kurniawan R, Trijatmiko, Mastur. 2018. Genetic diversity analysis and F2 population development for breeding of long juvenile trait in soybean. Jurnal AgroBiogen. 14(1): 11-22.
Ullah A, Akram Z, Malik SI, Khan KSU. 2021. Assessment of phenotypic and molecular diversity in soybean [Glycine max (L.) Merr.] germplasm using morpho-biochemical attributes and SSR markers. Genetic Resources and Crop Evolution. 68: 2827-2847. https://doi.org/10.1007/s10722-021-01157-w
Valentini A, Pompanon F, Taberlet P. 2009. DNA barcoding for ecologists. Trends in Ecology & Evolution. 24(2): 110-117. https://doi.org/10.1016/j.tree.2008.09.011
Wang L, Guan R, Zhang XL, Chang R, Qiu L. 2006. Genetic diversity of Chinese cultivated soybean revealed by SSR markers. Crop Science. 46(3): 1032-1038. https://doi.org/10.2135/cropsci2005.0051
Wibisono K, Aisyah SI, Nurcholis W, Suhesti S. 2022. Sensitivity in callus tissue of Plectranthus amboinicus (L.) through mutation induction with colchicine. Agrivita Journal of Agricultural Science. 44(1): 82-95. http://doi.org/10.17503/agrivita.v44i1.3058
Widaningsih NA, Purwanto E, Nandariyah N, Reflinur R. 2014. The use of DNA microsatellite markers for genetic diversity identification of soybean (Glycine max (L) Meriil.) as a supplementary method in reference collections management. Indonesian Journal of Biotechnology. 19(2): 136-145. https://doi.org/10.22146/ijbiotech.9306
Published
2024-12-30
How to Cite
WibisonoK., DyahR. P., UtariR., Suparjo, Umar, RijzaaniH., HakimL., SuhendarA., PurwantoO. D., SatyawanD., Witjaksono, Mastur, LestariP., & TasmaI. M. (2024). Analisis Keragaman Genetik dan Pembuatan DNA Barcoding pada Galur Kedelai Tropis Berdasarkan Marka SSR. Jurnal Ilmu Pertanian Indonesia, (00). Retrieved from https://journal.ipb.ac.id/index.php/JIPI/article/view/54304
Section
Articles
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This journal is published under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License. Authors who publish with this journal agree to the following terms: Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. NonCommercial — You may not use the material for commercial purposes.
View JIPI StatsCounter
