Rice species (Oryza sativa, L. and Oryza glaberrima, Steud) provide 20% energy of world’s food. Knowledge of genetic variability is important to remove duplicate materials for gene bank management and conservation. In this study, 59 microsatellite markers were used to assess the genetic diversity of 54 intraspecific (Oryza sativa) and interspecific (Oryza sativa X Oryza glaberrima) irrigated rice varieties by PCR-SSR. A total of 250 alleles were detected with an average of 4.24 alleles per SSR. Genetic diversity was ranged from 0.0713 (RM333, RM3744) to 0.8937 (RM251) to with an average of 0.4325. Polymorphism Information Content (PIC) varied from 0.0688 (RM333, RM3744) to 0.8854 (RM251) with an average of 0.3940. Rice genotypes were shared between five Groups based on their similarity with majority of them (64.81%) under Group V. Variety SK 7-8 within Group III was highly dissimilar to other varieties. Malian varieties were shared out between Groups II, III, VI and V. Strong genetic variability was observed within cluster V2 of Group V among the most cultivated and appreciated rice varieties such as Kogoni 91-1, Adny11 and BG90-2. Allelic variability observed among rice varieties could help breeding programs to identify cultivars with good agronomic traits for crop improvement.
| Published in | International Journal of Genetics and Genomics (Volume 6, Issue 2) |
| DOI | 10.11648/j.ijgg.20180602.11 |
| Page(s) | 22-29 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2018. Published by Science Publishing Group |
Genetic Diversity, Irrigated Rice, PCR-SSR, Mali
| [1] | Dhar, P., Ashrafuzzaman, M., Begum, S. N., Islam, M. M., & Chowdhury, M. M. H. (2012). Identification of salt tolerant rice genotypes and their genetic diversity analysis using SSR markers. International Journal of Biological Science, 2(9), 45-50. |
| [2] | FAO (2004). Le riz et l’alimentation humaine Food and Agriculture Organization of the United Nations Viale delle Terme di Caracalla Rome 00100 Italy (Disponible à www.fao.org/rice2004/fr/f-sheet/fiche3.pdf). |
| [3] | Diarra S. B., Traoré P., & Keïta F. (2014). L’inclusion des femmes, des jeunes et des pauvres dans la chaine de valeur du riz au Mali. Bamako: Observatoire du marché agricole.p114. |
| [4] | Khush G. S. (2005). What it will take to feed 5.0 billion rice consumers in 2030. Plant molecular biology, 59(1), 1-6. |
| [5] | Somado E. A., Guei R. G., & Keya S. O. (2008). NERICA: The new rice for Africa–a compendium. Africa Rice Center (WARDA), 10-14. |
| [6] | Baumgartner A. (1998). Un aliment de base pour la moitié de l’humanité p4. |
| [7] | Dao K. (2014). Caractérisation moléculaire des lignées en disjonction issues de croisement de dix variétés de riz de fort potentiel de rendement pour leurs composantes de rendement. p. 77. |
| [8] | FAO (2008). West African Catalogue of Plant Species and Varieties Rome, pp 41-69. http://www.fao.org/docrep/010/i0062e/i0062e00.htm. |
| [9] | Chabrolin R. (1983) Amélioration génétique du riz à la station de Kogoni (mali) Institut de Recherches Agronomiques Tropicales et des Cultures Vivrières (IRAT) p1-9. |
| [10] | Jacquot M., Clément G., Ghesquière A., Glaszmann J. C., Guiderdoni E., Tharreau D. (2001). Tropical plant breeding. Montpellier: CIRAD, p. 425-454. |
| [11] | Seetharam K., Thirumeni S., Paramasivam K. (2009). Estimation of genetic diversity in rice (Oryza sativa L.) genotypes using SSR markers and morphological characters. African Journal of Biotechnology Vol. 8 (10), pp. 2050-2059. |
| [12] | Moukoumbi Y. D., Kolade O., Drame K. N., Sie M., & Ndjiondjop, M. N. (2015). Genetic relationships between interspecific lines derived from Oryza glaberrima and Oryza sativa crosses using microsatellites and agro-morphological markers. Spanish Journal of Agricultural Research, 13(2), 0701. |
| [13] | Zeng L, Kwon TR, Liu X, Wilson C, Grieve CM, Gregorio GB (2004). Genetic diversity analysed by microsatellite markers among rice (Oryza sativa L.) genotypes with different adaptation to saline soils. Plant Sci. 166: 1275-1285. |
| [14] | GOITA O. (2013). Genetic Improvement of Alkalinity Tolerance in Rice in Office Du Niger in Mali (Doctoral dissertation, University of Ghana). |
| [15] | Demol J. (2002). Amélioration des plantes: Application aux principales espèces cultivées en régions tropicales. Presses Agronomiques de Gembloux. |
| [16] | Pokhriyal B., Thorat K., Limaye D., Joshi Y., Kadam, V. J., & Dubey, R. (2012). Microsatellite Markers–A Novel Tool in Molecular Genetics. International Journal of Research in Pharmacy and Chemistry, 2, 397-412. |
| [17] | Zhang L. N., Cao G. L., & Han L. Z. (2013). Genetic diversity of rice landraces from lowland and upland accessions of China. Rice Science, 20(4), 259-266. |
| [18] | Ma H., Yin Y., Guo Z. F., Cheng L. J., Zhang L., Zhong M., & Shao G. J. (2011). Establishment of DNA fingerprinting of Liaojing series of japonica rice. Middle-East J. Sci. Res, 8(2), 384-392. |
| [19] | Powell W., Morgante M., Andre C., Hanafey M., Vogel J., Tingey S., & Rafalski A. (1996). The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis. Molecular breeding, 2(3), 225-238. |
| [20] | Sajib A. M., Hossain M., Mosnaz A. T. M. J., Hossain H., Islam M., Ali M., & Prodhan S. H. (2012). SSR marker-based molecular characterization and genetic diversity analysis of aromatic landreces of rice (Oryza sativa L.). Journal of BioScience & Biotechnology, 1(2):107-116. |
| [21] | Zhang S. B., Zhu Z., Zhao L., Zhang Y. D., Chen T., Lin J., & Wang C. L. (2007). Identification of SSR markers closely linked to gene in rice. Yi chuan= Hereditas, 29(3), 365-370. |
| [22] | Peng S., Zhuang J., Yan Q., & Zheng K. (2003). SSR markers selection and purity detection of major hybrid rice combinations and their parents in China. Zhongguo shuidao kexue, 17(1), 1-5. |
| [23] | McCouch S. R., Teytelman L., Xu Y., Lobos K. B., Clare K., Walton M., & Zhang Q. (2002). Development and mapping of 2240 new SSR markers for rice (Oryza sativa L.) (supplement). DNA research: an international journal for rapid publication of reports on genes and genomes, 9(6), 257. |
| [24] | IRGSP, International Rice Genome Sequencing Project (2005). The map-based sequence of the rice genome. Nature 436: 793-800. |
| [25] | Seetharam K., Thirumeni S., & Paramasivam K. (2009). Estimation of genetic diversity in rice (Oryza sativa L.) genotypes using SSR markers and morphological characters. African journal of Biotechnology, 8(10). |
| [26] | Lin H. Y., Wu Y. P., Hour A. L., Ho S. W., Wei F. J., C Hsing Y. I., & Lin Y. R. (2012). Genetic diversity of rice germplasm used in Taiwan breeding programs. Botanical Studies, 53(3), 363-376 |
| [27] | Zhang P., Li J., Li X., Liu X., Zhao X., & Lu Y. (2011). Population structure and genetic diversity in a rice core collection (Oryza sativa L.) investigated with SSR markers. PloS one, 6(12), e27565. |
| [28] | Watanabe, K. N., Ohsawa, R., Obara, M., Yanagihara, S., Aung, P. P., & Fukuta, Y. (2016). Genetic variation of rice (Oryza sativa L.) germplasm in Myanmar based on genomic compositions of DNA markers. Breeding science, 66(5), 762-767. |
| [29] | Vazirzanjani, M., Kawai, S., Korrani, H. M., Ossivand, A., & Ookawa, T. (2017). Genetic diversity of rice from Iran region assessed by simple sequence repeat (SSR) markers. African Journal of Agricultural Research, 12(36), 2765-2772. |
| [30] | Shakil S. K., Sultana S., Hasan Md M., Hossain Md M., Ali Md S., Prodhan S. H. (2015) SSR marker based genetic diversity analysis of modern rice varieties and coastral landraces in Bangladesh. Indian Journal of Biotechnology 14: 33-41. |
| [31] | Liu J., & Muse S. V. (2005). PowerMarker V3. 0 Manual. |
| [32] | Botstein D., White R. L., Skolnick M., & Davis R. W. (1980). Construction of a genetic linkage map in man using restriction fragment length polymorphisms. American journal of human genetics, 32(3), 314-331. |
| [33] | Fukunaga K., Hill J., Vigouroux Y., Matsuoka Y., Sanchez J., Liu K., & Doebley J. (2005). Genetic diversity and population structure of teosinte. Genetics, 169(4), 2241-2254. |
| [34] | Kumar, S., Stecher, G., & Tamura, K. (2016). MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Molecular biology and evolution, 33(7), 1870-1874. |
| [35] | Kanawapee N., Sanitchon J., Srihaban P., & Theerakulpisut P. (2011). Genetic diversity analysis of rice cultivars (Oryza sativa L.) differing in salinity tolerance based on RAPD and SSR markers. Electronic Journal of Biotechnology, 14(6), 2-2. |
| [36] | Zhu Y. F., Qin G. C., Hu J., Wang Y., Wang J. C., & Zhu S. J. (2012). Fingerprinting and variety identification of rice (Oryza sativa L.) based on simple sequence repeat markers. Plant Omics, 5(4), 421-426. |
| [37] | Pervaiz Z. H., Rabbani M. A., Khaliq I., Pearce S. R., & Malik S. A. (2010). Genetic diversity associated with agronomic traits using microsatellite markers in Pakistani rice landraces. Electronic Journal of Biotechnology, 13(3), 4-5. |
APA Style
Sognan Dao, Halimatou Timbine, Oumarou Goita, Diakaridia Traore. (2018). Genetic Variability Assessment in Irrigated Rice (Oryza sativa and Oryza glaberrima) by PCR-SSR in Mali. International Journal of Genetics and Genomics, 6(2), 22-29. https://doi.org/10.11648/j.ijgg.20180602.11
ACS Style
Sognan Dao; Halimatou Timbine; Oumarou Goita; Diakaridia Traore. Genetic Variability Assessment in Irrigated Rice (Oryza sativa and Oryza glaberrima) by PCR-SSR in Mali. Int. J. Genet. Genomics 2018, 6(2), 22-29. doi: 10.11648/j.ijgg.20180602.11
AMA Style
Sognan Dao, Halimatou Timbine, Oumarou Goita, Diakaridia Traore. Genetic Variability Assessment in Irrigated Rice (Oryza sativa and Oryza glaberrima) by PCR-SSR in Mali. Int J Genet Genomics. 2018;6(2):22-29. doi: 10.11648/j.ijgg.20180602.11
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Download@article{10.11648/j.ijgg.20180602.11,
author = {Sognan Dao and Halimatou Timbine and Oumarou Goita and Diakaridia Traore},
title = {Genetic Variability Assessment in Irrigated Rice (Oryza sativa and Oryza glaberrima) by PCR-SSR in Mali},
journal = {International Journal of Genetics and Genomics},
volume = {6},
number = {2},
pages = {22-29},
doi = {10.11648/j.ijgg.20180602.11},
url = {https://doi.org/10.11648/j.ijgg.20180602.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijgg.20180602.11},
abstract = {Rice species (Oryza sativa, L. and Oryza glaberrima, Steud) provide 20% energy of world’s food. Knowledge of genetic variability is important to remove duplicate materials for gene bank management and conservation. In this study, 59 microsatellite markers were used to assess the genetic diversity of 54 intraspecific (Oryza sativa) and interspecific (Oryza sativa X Oryza glaberrima) irrigated rice varieties by PCR-SSR. A total of 250 alleles were detected with an average of 4.24 alleles per SSR. Genetic diversity was ranged from 0.0713 (RM333, RM3744) to 0.8937 (RM251) to with an average of 0.4325. Polymorphism Information Content (PIC) varied from 0.0688 (RM333, RM3744) to 0.8854 (RM251) with an average of 0.3940. Rice genotypes were shared between five Groups based on their similarity with majority of them (64.81%) under Group V. Variety SK 7-8 within Group III was highly dissimilar to other varieties. Malian varieties were shared out between Groups II, III, VI and V. Strong genetic variability was observed within cluster V2 of Group V among the most cultivated and appreciated rice varieties such as Kogoni 91-1, Adny11 and BG90-2. Allelic variability observed among rice varieties could help breeding programs to identify cultivars with good agronomic traits for crop improvement.},
year = {2018}
}
TY - JOUR T1 - Genetic Variability Assessment in Irrigated Rice (Oryza sativa and Oryza glaberrima) by PCR-SSR in Mali AU - Sognan Dao AU - Halimatou Timbine AU - Oumarou Goita AU - Diakaridia Traore Y1 - 2018/05/22 PY - 2018 N1 - https://doi.org/10.11648/j.ijgg.20180602.11 DO - 10.11648/j.ijgg.20180602.11 T2 - International Journal of Genetics and Genomics JF - International Journal of Genetics and Genomics JO - International Journal of Genetics and Genomics SP - 22 EP - 29 PB - Science Publishing Group SN - 2376-7359 UR - https://doi.org/10.11648/j.ijgg.20180602.11 AB - Rice species (Oryza sativa, L. and Oryza glaberrima, Steud) provide 20% energy of world’s food. Knowledge of genetic variability is important to remove duplicate materials for gene bank management and conservation. In this study, 59 microsatellite markers were used to assess the genetic diversity of 54 intraspecific (Oryza sativa) and interspecific (Oryza sativa X Oryza glaberrima) irrigated rice varieties by PCR-SSR. A total of 250 alleles were detected with an average of 4.24 alleles per SSR. Genetic diversity was ranged from 0.0713 (RM333, RM3744) to 0.8937 (RM251) to with an average of 0.4325. Polymorphism Information Content (PIC) varied from 0.0688 (RM333, RM3744) to 0.8854 (RM251) with an average of 0.3940. Rice genotypes were shared between five Groups based on their similarity with majority of them (64.81%) under Group V. Variety SK 7-8 within Group III was highly dissimilar to other varieties. Malian varieties were shared out between Groups II, III, VI and V. Strong genetic variability was observed within cluster V2 of Group V among the most cultivated and appreciated rice varieties such as Kogoni 91-1, Adny11 and BG90-2. Allelic variability observed among rice varieties could help breeding programs to identify cultivars with good agronomic traits for crop improvement. VL - 6 IS - 2 ER -
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