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ORIGINAL RESEARCH
In-Silico Analysis of R-Genes in Rice for New
Insights of Partial and Complete Resistance
Against Bacterial Leaf Blight Disease
1
Nuclear Institute for Agriculture & Biology (NIAB-C), PIEAS, Pakistan
2
Department of Biochemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
3
EPCRS Excellence Center, Plant Pathology and Biotechnology Lab.; Agric. Botany Dept.;
Fac. Agric.; Kafrelsheikh University; 33516, Egypt
4
The University of Lahore, Department of Environmental Sciences, Lahore, 54590, Pakistan
5
National Key Laboratory of Green Pesticide, Key Laboratory of Green Pesticide and Agricultural Bioengineering,
Ministry of Education, Center for R&D of Fine Chemicals of Guizhou University, Guiyang 550025, China
6
Institute of Molecular Biology and Biotechnology, The University of Lahore, 54590 Lahore, Pakistan
Submission date: 2024-06-09
Final revision date: 2024-07-24
Acceptance date: 2024-11-08
Online publication date: 2025-04-09
Publication date: 2026-01-29
Corresponding author
Qamar Uz Zaman
The University of Lahore, Department of Environmental Sciences, Lahore, 54590, Pakistan
The University of Lahore, Department of Environmental Sciences, Lahore, 54590, Pakistan
Pol. J. Environ. Stud. 2026;35(1):265-275
KEYWORDS
TOPICS
ABSTRACT
Bacterial leaf blight (BLB) disease is a rice disease caused by Xanthomonas oryzae pv.oryzae (Xoo).
Under variable climate conditions, the new races of Xanthomonas oryzae pv. oryzae (Xoo) have a massive
impact on rice crop yield. The focus of the study has been finding disease-resistant genes that will provide
resistance against Xoo. Different strains of Xoo attack rice crops all over the world; the kinds that are
resistant to these strains can differ depending on where in the world you live.
Currently, 45 Xa-genes have been identified that possess resistance against the Xoo pathogen and are being used in screening rice-diverse cultivars. In this project, amino acid sequences of Xa23, Xa23Ni, Xa10, and X10Ni were mined and used for their motif, domain identification, and chromosome localization. Almost 113 amino acids in both the Xa23 and Xa23-Ni were observed. However, 126 and 134 amino acids were identified in XaXa10 and X10-Ni. The amino acid-conserved regions of Xa23 contribute 50% of the identity to the known executor R protein of Xa10. In addition, trans-membrane helices of Xa23 were also present in Xa10. However, the activation of transcription in Xa23 observed by AvrXa23 was distinct from that in Xa10. During in-silico analysis, two novel Xa10-like genes (Xa10-Ni and Xa23-Ni) were recognized. The structural analysis (physical and chemical characterization) of the Xa23, Xa23Ni, Xa10, and X10Ni proteins showed that, except for all the genes, Xa10-Ni has α-helix and was slightly acidic in nature. Due to their hydrophobic attributes, all were found to be stable proteins. In Ramachandran plot analysis, over 90% of amino acid residues fall in the favored regions. In homology modeling, except for Xa10-Ni, the predicted models of Xa23, Xa23-Ni, and Xa10 possess the ligands. During chromosomal localization, all the genes were found on Chromosome No. 11. It is concluded that the project study will be helpful for the selection of R-genes to build resistance in rice varieties against particular isolates of the Xoo strain to achieve sustainable rice crop production under variable climate conditions.
Currently, 45 Xa-genes have been identified that possess resistance against the Xoo pathogen and are being used in screening rice-diverse cultivars. In this project, amino acid sequences of Xa23, Xa23Ni, Xa10, and X10Ni were mined and used for their motif, domain identification, and chromosome localization. Almost 113 amino acids in both the Xa23 and Xa23-Ni were observed. However, 126 and 134 amino acids were identified in XaXa10 and X10-Ni. The amino acid-conserved regions of Xa23 contribute 50% of the identity to the known executor R protein of Xa10. In addition, trans-membrane helices of Xa23 were also present in Xa10. However, the activation of transcription in Xa23 observed by AvrXa23 was distinct from that in Xa10. During in-silico analysis, two novel Xa10-like genes (Xa10-Ni and Xa23-Ni) were recognized. The structural analysis (physical and chemical characterization) of the Xa23, Xa23Ni, Xa10, and X10Ni proteins showed that, except for all the genes, Xa10-Ni has α-helix and was slightly acidic in nature. Due to their hydrophobic attributes, all were found to be stable proteins. In Ramachandran plot analysis, over 90% of amino acid residues fall in the favored regions. In homology modeling, except for Xa10-Ni, the predicted models of Xa23, Xa23-Ni, and Xa10 possess the ligands. During chromosomal localization, all the genes were found on Chromosome No. 11. It is concluded that the project study will be helpful for the selection of R-genes to build resistance in rice varieties against particular isolates of the Xoo strain to achieve sustainable rice crop production under variable climate conditions.
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
REFERENCES (41)
1.
ZHOU X., SHAFIQUE K., SAJID M., ALI Q., KHALILI E., JAVED M., HAIDER M., ZHOU G., ZHU G. Era-like GTP protein gene expression in rice. Brazilian Journal of Biology, 82, e250700, 2021. https://doi.org/10.1590/1519-6... PMid:34259718.
2.
BONNAVE M., BERTIN P. Evaluation of nitrogen use efficiency (NUE) of rice (O. sativa) under saline conditions, 2018.
3.
EL ARJA S. Neuromorphic perception for greenhouse technology using event-based sensors, 2022.
4.
KUMAR A., KUMAR V., RODRÍGUEZ-SEIJO A., SETIA R., SINGH S., KUMAR A., SETH C.S., SOMMA R. Appraisal of heavy metal(loid)s contamination in rice grain and associated health risks. Journal of Food Composition and Analysis, 106215, 2024. https://doi.org/10.1016/j.jfca....
5.
RUBIN B., MAGLASANG R., MAYO F. Modeling the Rice Production and Consumption in the Philippines: A System Dynamics Approach. SSRN 4247739, 2022. https://doi.org/10.2139/ssrn.4....
6.
KRISHNAN S.G., VINOD K., BHOWMICK P.K., BOLLINEDI H., ELLUR R.K., SETH R., SINGH A. Rice Breeding. Fundamentals of Field Crop Breeding, 192 (966.88), 113, 2022. https://doi.org/10.1007/978-98....
7.
SIMKHADA K., THAPA R. Rice blast, a major threat to the rice production and its various management techniques. Turkish Journal of Agriculture-Food Science and Technology, 10 (2), 147, 2022. https://doi.org/10.24925/turja....
8.
IQBAL S. Insect, pest and disease management in rice. Austin Publication, Irving, TX, 85, 2020.
9.
KUMAR A., KUMAR R., SENGUPTA D., DAS S.N., PANDEY M.K., BOHRA A., SHARMA N.K., SINHA P., SK H., GHAZI I.A. Deployment of genetic and genomic tools toward gaining a better understanding of rice-Xanthomonas oryzae pv. oryzae interactions for development of durable bacterial blight resistant rice. Frontiers in Plant Science, 11, 1152, 2020. https://doi.org/10.3389/fpls.2... PMid:32849710 PMCid:PMC7417518.
10.
SANYA D.R.A., SYED-AB-RAHMAN S.F., JIA A., ONÉSIME D., KIM K.-M., AHOHUENDO B.C., ROHR J.R. A review of approaches to control bacterial leaf blight in rice. World Journal of Microbiology and Biotechnology, 38 (7), 113, 2022. https://doi.org/10.1007/s11274... PMid:35578069.
11.
KHARAYAT B.S. Diseases of Field and Horticultural Crops and their Management Volume-I. PHI Learning Pvt. Ltd., 2023.
12.
TEPER D., WHITE F.F., WANG N. The dynamic transcription activator-like effector family of Xanthomonas. Phytopathology®, 113 (4), 651, 2023. https://doi.org/10.1094/PHYTO-... PMid:36449529.
13.
MONDAL R., KUMAR A., GNANESH B.N. Crop germplasm: Current challenges, physiological-molecular perspective, and advance strategies towards development of climate-resilient crops. Heliyon, 9 (1), 2023. https://doi.org/10.1016/j.heli... PMid:36711267 PMCid:PMC9880400.
14.
KHANNETAH K., RAMCHANDER S., LEON M.A.P., SHOBA D., SARAVANAN S., KANNAN R., YASIN J.K., PILLAI M.A. Genetic diversity analysis in indigenous rice (Oryza sativa L.) germplasm for bacterial leaf blight (Xanthomonas oryzae pv. oryzae) using resistance genes-linked markers. Euphytica, 217 (7), 145, 2021. https://doi.org/10.1007/s10681....
15.
WANG S., LIU W., LU D., LU Z., WANG X., XUE J., HE X. Distribution of bacterial blight resistance genes in the main cultivars and application of Xa23 in rice breeding. Frontiers in Plant Science, 11, 555228, 2020. https://doi.org/10.3389/fpls.2... PMid:32983213 PMCid:PMC7488846.
16.
SINGH B.K., DELGADO-BAQUERIZO M., EGIDI E., GUIRADO E., LEACH J.E., LIU H., TRIVEDI P. Climate change impacts on plant pathogens, food security and paths forward. Nature Reviews Microbiology, 21 (10), 640, 2023. https://doi.org/10.1038/s41579... PMid:37131070 PMCid:PMC10153038.
17.
JI Z., GUO W., CHEN X., WANG C., ZHAO K. Plant executor genes. International Journal of Molecular Sciences, 23 (3), 1524, 2022. https://doi.org/10.3390/ijms23... PMid:35163443 PMCid:PMC8835739.
18.
NGUYEN M.H.R. Host-induced adaptation of Xanthomonas oryzae pv. oryzae. University of Southern Queensland, 2021.
19.
YANG Y., ZHOU Y., SUN J., LIANG W., CHEN X., WANG X., ZHOU J., YU C., WANG J., WU S. Research progress on cloning and function of Xa genes against rice bacterial blight. Frontiers in Plant Science, 13, 847199, 2022. https://doi.org/10.3389/fpls.2... PMid:35386667 PMCid:PMC8978965.
20.
AFTAB U., ALI S., GHANI M.U., SAJID M., ZESHAN M.A., AHMED N., MAHMOOD R. Epidemiological Studies of Bacterial Leaf Blight of Rice and its Management. Basrah Journal of Agricultural Sciences, 35 (1), 106, 2022. https://doi.org/10.37077/25200....
21.
RAMASETTY B.T., KUMAR R.M., UDAYSHANKAR A.C., PRAKASH H.S. Chapter-2 Phyto-Endophytes for the Sustainable Management of Bacterial Blight Disease in Rice Caused by Xanthomonas oryzae pv. oryzae (Xoo); Recent Advances and Future Challenges.
22.
ISNAINI I., NUGRAHA Y., BAISAKH N., CARSONO N. Toward Food Security in 2050: Gene Pyramiding for Climate-Smart Rice. Sustainability, 15 (19), 14253, 2023. https://doi.org/10.3390/su1519....
23.
SCHNEIBLE J.D. A Material Toolbox for Advanced Therapeutics. North Carolina State University, 2020.
24.
ALTWAIJRY N., ALMASOUD M., ALMALKI A., AL-TURAIKI I. Multiple sequence alignment using a multiobjective artificial bee colony algorithm. IEEE, 2020. https://doi.org/10.1109/ICCAIS....
25.
SHAMSHAD A., RASHID M., ZAMAN Q.U. In-silico analysis of heat shock transcription factor (OsHSF) gene family in rice (Oryza sativa L.). BMC Plant Biology, 23 (1), 395, 2023. https://doi.org/10.1186/s12870... PMid:37592226 PMCid:PMC10433574.
26.
YANG M., DERBYSHIRE M.K., YAMASHITA R.A., MARCHLER-BAUER A. NCBI's conserved domain database and tools for protein domain analysis. Current Protocols in Bioinformatics, 69 (1), e90, 2020. https://doi.org/10.1002/cpbi.9... PMid:31851420 PMCid:PMC7378889.
27.
HAVLIK L.P., DAS A., MIETZSCH M., OH D.K., ARK J., MCKENNA R., AGBANDJE-MCKENNA M., ASOKAN A. Receptor switching in newly evolved adeno-associated viruses. Journal of Virology, 95 (19), e00587, 2021. https://doi.org/10.1128/JVI.00... PMid:34232726 PMCid:PMC8428401.
28.
SINGH A., PANDEY A.K., DUBEY S.K. Genome sequencing and in silico analysis of isoprene degrading monooxygenase enzymes of Sphingobium sp. BHU LFT2. Journal of Biomolecular Structure and Dynamics, 41 (9), 3821, 2023. https://doi.org/10.1080/073911... PMid:35380094.
29.
CHEN X., QIU Q., CHEN K., LI D., LIANG L. Water-soluble myofibrillar protein-pectin complex for enhanced physical stability near the isoelectric point: Fabrication, rheology and thermal property. International Journal of Biological Macromolecules, 142, 615, 2020. https://doi.org/10.1016/j.ijbi... PMid:31622714.
30.
YD M., DS M., KANNARATH A. In Silico Drug Search for Better Treatment for Cancer: L-Asparaginase. International Journal of Research, 2 (11), 75, 2014.
31.
BEVACQUA A., BAKSHI S., XIA Y. Principal component analysis of alpha-helix deformations in transmembrane proteins. PLoS One, 16 (9), e0257318, 2021. https://doi.org/10.1371/journa... PMid:34525125 PMCid:PMC8443038.
32.
WEBB B., SALI A. Comparative protein structure modeling using MODELLER. Current Protocols in Bioinformatics, 54 (1), 5.6.1, 2016. https://doi.org/10.1002/cpbi.3 PMid:27322406 PMCid:PMC5031415.
33.
ORBÁN-NÉMETH Z., BEVERIDGE R., HOLLENSTEIN D.M., RAMPLER E., STRANZL T., HUDECZ O., DOBLMANN J., SCHLÖGELHOFER P., MECHTLER K. Structural prediction of protein models using distance restraints derived from cross-linking mass spectrometry data. Nature Protocols, 13 (3), 478, 2018. https://doi.org/10.1038/nprot.... PMid:29419816 PMCid:PMC5999019.
34.
HASHEMZADEH P., GHORBANZADEH V., LASHGARIAN H.E., KHEIRANDISH F., DARIUSHNEJAD H. Harnessing bioinformatic approaches to design novel multi-epitope subunit vaccine against Leishmania infantum. International Journal of Peptide Research and Therapeutics, 26 (3), 1417, 2020. https://doi.org/10.1007/s10989....
35.
SHAMSHAD A., RASHID M., HAMEED A., IMRAN ARSHAD H.M. Identification of biochemical indices for brown spot (Bipolaris oryzae) disease resistance in rice mutants and hybrids. PLoS One, 19 (4), e0300760, 2024. https://doi.org/10.1371/journa... PMid:38635807 PMCid:PMC11025958.
36.
HAN X., YANG Y., WANG X., ZHOU J., ZHANG W., YU C., CHENG C., CHENG Y., YAN C., CHEN J. Quantitative trait loci mapping for bacterial blight resistance in rice using bulked segregant analysis. International Journal of Molecular Sciences, 15 (7), 11847, 2014. https://doi.org/10.3390/ijms15... PMid:24995697 PMCid:PMC4139818.
37.
PANDA S., BUSATTO N., HUSSAIN K., KAMBLE A. Piriformospora indica-primed transcriptional reprogramming induces defense response against early blight in tomato. Scientia Horticulturae, 255, 209, 2019. https://doi.org/10.1016/j.scie....
38.
RAMASARMA T. Transmembrane domains participate in functions of integral membrane proteins. Indian Journal of Biochemistry & Biophysics, 33 (1), 20, 1996.
39.
TIRINCSI A., SICKING M., HADZIBEGANOVIC D., HAßDENTEUFEL S., LANG S. The molecular biodiversity of protein targeting and protein transport related to the endoplasmic reticulum. International Journal of Molecular Sciences, 23 (1), 143, 2021. https://doi.org/10.3390/ijms23... PMid:35008565 PMCid:PMC8745461.
40.
SAINI P., YASHVEER S., REDHU N.S., CHAUDHARY S., KAMBOJ A., HEMBADE V., SHARMA K., SANGWAN S. Opportunities for Bioinformatics Tools for the Management of Rice Bacterial Diseases. Apple Academic Press, 2023. https://doi.org/10.1201/978100....
41.
TONG X., CAO J., SUN M., LIAO P., DAI S., CUI W., CHENG X., LI Y., JIANG L., WANG H. Physical and oxidative stability of oil-in-water (O/W) emulsions in the presence of protein (peptide): Characteristics analysis and bioinformatics prediction. LWT, 149, 111782, 2021. https://doi.org/10.1016/j.lwt.....
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