American Journal of Plant Biology
Volume 3, Issue 4, December 2018, Pages: 33-40
Received: Feb. 23, 2019;
Accepted: Mar. 28, 2019;
Published: May 6, 2019
Views 676 Downloads 68
Al Amin, Plant Breeding Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh
KM Iftekharuddaula, Plant Breeding Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh
Animesh Sarker, Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh
Md. Abdul Kader, Plant Breeding Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh
Ashraf Hossain Talukder, Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh
Tamal Lata Aditya, Research Department, Bangladesh Rice Research Institute, Gazipur, Bangladesh
Md. Ansar Ali, Administration and Common Services Department, Bangladesh Rice Research Institute, Gazipur, Bangladesh
Md. Shahjahan Kabir, General Office, Bangladesh Rice Research Institute, Gazipur, Bangladesh
The molecular screening of deep water rice landraces showed that out of 21 landraces, 15 landraces possess the SNORKEL1 (SK1) and SNORKEL2 (SK2) genes conferring stem elongation of paddy plant survive in increased water level of deep water ecosystem. Both genes/Quantitative trait loci (QTLs) were subjected to study through in-silico approaches. The fasta sequences, secondary structure and 3D structure of those proteins were identified and verified using bioinformatics tools. The physico-chemical properties and functions were also predicted. The in-silico study of SNORKEL1 (SK1) and SNORKEL2 (SK2) QTL have also revealed the capacity and way of survival of deep water rice germplasm noticeably. This study illustrates the many deep water rice varieties having SNORKEL1 (SK1) and SNORKEL2 (SK2) QTL and others do not possess the these QTLs though they are cultivated in deep water ecosystem. The molecular screening and in-silico study output of deep water rice landraces can be applied for establishing morphological correlation that 15 landraces are more elongating type than others and more adapted in natural deep water condition.
Md. Abdul Kader,
Ashraf Hossain Talukder,
Tamal Lata Aditya,
Md. Ansar Ali,
Md. Shahjahan Kabir,
Exploration of SNORKEL1 (SK1) and SNORKEL2 (SK2) QTLs in Deep Water Rice Germplasm Through Genotyping and In-silico Approach, American Journal of Plant Biology.
Vol. 3, No. 4,
2018, pp. 33-40.
Catling, David. (1992). Rice in Deep Water. 10.1007/978-1-349-12309-4.
Iftekharuddaula K M, Newaz M A, Salam MA, Ahmed H U, Mahbub M A A, Septiningsih E M, Collard B C Y, Sanchez D L, Pamplona A M and Mackill D J. 2011. Rapid and High-Precision Marker Assisted Backcrossing to Introgress the SUB1 QTL into BR11, the Rainfed Lowland Rice Mega Variety of Bangladesh. Euphytica, 178, 83-97.
Xu K, Xia X, Fukao T, Canlas P, Maghirang-Rodriguez R, Heuer S, Ismail AM, Bailey-Serres J, Ronald PC, Mackill DJ. Sub1A is an ethylene response factor-like gene that confers submergence tolerance to rice. Nature. 2006; 442: 705–708. doi: 10.1038/nature04920.
Bailey-Serres J, Fukao T, Ronald P, Ismail A, Heuer S, Mackill D. Submergence Tolerant Rice: SUB1’s Journey from Landrace to Modern Cultivar. Rice. 2010; 3: 138–147. doi: 10.1007/s12284-010-9048-5.
Das KK, Panda D, Sarkar RK, Reddy JN, Ismail AM. Submergence tolerance in relation to variable floodwater conditions in rice. Environmental and Experimental Botany. 2009; 66: 425–434.
Catling D: Rice in Deepwater. London: Macmillan Press; 1992. This is a comprehensive and specialized book on deepwater rice, dealing with such topics as the phenotype of deepwater rice, local cultures, agroecosystem and climate.
Jackson, M. B. and Ram, P. C. (2003) Physiological and Molecular Basis of Susceptibility and Tolerance of Rice Plants to Complete Submergence. Annals of Botany, 91, 227-241. http://dx.doi.org/10.1093/aob/mcf242
Hattori Y, Nagai K, Furukawa S, Song XJ, Kawano R, Sakakibara H, Wu J, Matsumoto T, Yoshimura A, Kitano H, Matsuoka M, Mori H, Ashikari M. The ethylene response factors SNORKEL1 and SNORKEL2 allow rice to adapt to deep water. Nature. 2009; 460: 1026–1030. doi: 10.1038/nature08258.
Rupesh Deshmukh, Humira Sonah, Gunvant Patil, Wei Chen, Silvas Prince, Raymond Mutava, Tri Vuong, Babu Valliyodan and Henry T. Nguyen (2014) Integrating omic approaches for abiotic stress tolerance in soybean. Frontiers in plant science, doi: 10.3389/fpls.2014.00244.
Hattori Y, Miura K, Asano K, Yamamoto E, Mori H, Kitano H, Matsuoka M, Ashikari M: A major QTL confers rapid internode elongation in response to water rise in deepwater rice. Breed Sci 2007, 57: 305-314.
Hattori Y, Nagai K, Mori H, Kitano H, Matsuoka M, Ashikari M: Mapping of three QTL that regulate internode elongation in deepwater rice. Breed Sci 2008, 58: 39-46.
Hattori, Y., Nagai, K. and Ashikari, M. (2011) Rice Growth Adapting to Deep Water. Current Opinion in Plant Biology, 14, 100-105. http://dx.doi.org/10.1016/j.pbi.2010.09.008.
Allen G C, Flores-Vergara M A, Krasnyanksi S, Kumar S, Thompson W F. 2006. A modified protocol for rapid DNA isolation form plant tissues using cetyltrimethylammonium bromide. Nat. Protoc., 1 (5), pp. 2320–2325.
Chen X, Temnykh S, Xu Y, Cho Y G, and McCouch SR. 1997. Development of a microsatellite framework map providing genome-wide coverage in rice (Oryza sativa L.). Theor Appl Genet, 95, 553-567.
Neeraja C N, Rodriguez R M, Pamplona A, Heuer S, Collard B C Y, Septiningsih E M, Vergara G, Sanchez D, Xu K, Ismail A M and Mackill D J. 2007. A marker-assisted backcross approach for developing submergence-tolerant rice cultivars. Theor Appl Genet, 115 (6): 767-776.
Gasteiger E., Hoogland C., Gattiker A., Duvaud S., Wilkins M. R., Appel R. D., Bairoch A.; Protein Identification and Analysis Tools on the ExPASy Server.
John M. Walker (ed): The Proteomics Protocols Handbook, Humana Press (2005). pp. 571-607.
Xu K, Xia X, Fukao T, Canlas P, Maghirang-Rodriguez R, Heuer S, Ismail AM, Bailey-Serres J, Ronald P C and Mackill D J. 2006. Sub1A Is an Ethylene Response Factor-Like Gene That Confers Submergence Tolerance to Rice. Nature, 442, 705-708.
Y. H. Li, J. Y. Xu, L. Tao, X. F. Li, S. Li, X. Zeng, S. Y. Chen, P. Zhang, C. Qin, C. Zhang, Z. Chen, F. Zhu, Y. Z. Chen. (2016) SVM-Prot 2016: A Web-Server for Machine Learning Prediction of Protein Functional Families from Sequence Irrespective of Similarity. PLoS One. 11 (8): e0155290.
C. Z. Cai, L. Y. Han, Z. L. Ji, X. Chen, Y. Z. Chen. (2003) SVM-Prot: Web-Based Support Vector Machine Software for Functional Classification of a Protein from Its Primary Sequence. Nucleic Acids Res.. 31: 3692-3697.