National Institute of Plant Genome Research
Digital India   Azadi Ka Amrit Mahotsav     
    Dr. Shailesh Kumar, Ph.D.
    Staff Scientist III, Bioinformatics Laboratory #202
    National Institute of Plant Genome Research (NIPGR), New Delhi
    Tel:  91-11-26735217
    Fax:  91-11-26741658
 Research Area
Bioinformatics, Genomics, Big data analysis, Machine Learning (ML), Deep Learning, Artificial Intelligence (AI), and Plant Biotechnology
 Professional & Academic Background
Staff Scientist III (July 2020- Present): National Institute of Plant Genome Research (NIPGR), New Delhi, India
Staff Scientist II (May 2017- June 2020): National Institute of Plant Genome Research (NIPGR), New Delhi, India
Postdoctoral Research Associate (2015-2017): University Of Virginia, Charlottesville, VA, USA
Research Scientist (2014-2015): Sir Ganga Ram Hospital, New Delhi, India
Ph.D. Bioinformatics (2009-2014): Bioinformatics Centre, Institute of Microbial Technology (IMTECH), Chandigarh under Jawaharlal Nehru University (JNU), New Delhi, India
 Scientific Contributions/ Recognitions
Elected Member:  National Academy of Sciences India (NASI), 2022
Selected for SAKURA Exchange Program in Science for Indian Young officers, JAPAN (January 21-27, 2018) by Department of Biotechnology (DBT), India
Visiting scientist: Guangxi medical university and Guilin Medical University, China (October-November 2017).
Associate editor: PloS one and BMC Bioinformatics.
Editorial Board Member of Journal: Theoretical Biology and Medical Modelling.
 Research Interests
  • Identification and characterization of novel molecules in Plants

My research group is exploring several new areas in plant genome research including identification, characterization of novel molecules in plants. We are using Next Generation sequencing (NGS) datasets for the purpose, and our choice of molecules including Transfer RNA-derived fragments (tRFs), tRNA halves, ribosomal RNA-derived fragments (e.g. rRFs), and Fusion transcripts.

Transfer RNA-derived fragments (e.g. tRFs) in Plants

Transfer RNA-derived fragments or tRFs is a novel class of 15-28 nucleotide length small non-coding RNAs, generated by endonucleolytic cleavage of both mature and precursor tRNAs. Current understanding of the plant tRFs indicates that these small RNAs originate from 5' end (i.e. tRF-5) and 3' end (i.e. tRF-3) of mature tRNAs; and precursor tRNAs (i.e. tRF-1). In plants, there is an enhancement of tRFs generation in case of different biotic and abiotic stress conditions. Initial reports suggests that both Dicer-dependent and Dicer-independent pathways involved in tRFs generation. Reports also suggests that tRFs have role in both transcription and translation repression. In a nutshell, It is very important class of molecule to study in plants. Now, the key question is "when" and "where" to look for such events. We are trying to understand the role of tRFs, biogenesis and their mode of action. 

Fusion transcripts in Plants

We are also exploring the area of fusion transcripts in plants. Chimeric transcripts may either act as long non-coding RNAs or encode novel chimeric proteins. Advancement in the high-throughput technologies has led to the accumulation of enormous sequencing data, which has eased the understanding of the molecular mechanism behind this complex event, and its implications are being attempted to be elucidated in eukaryotic organisms including plants. Negligible information available for the chimeric transcripts in plants. We have to understand their role, mode of generation and functional mechanism in plants. 

  • Development of webservers, databases and computational pipelines for plant research

We are analysing the Big Data generated by genomics and proteomics techniques, for plant research. It is also necessary to compile and share the information with scientific community. For all those purposes, we are developing in silico tools, web-servers, computational pipelines, and useful databases for plant research community. We are also using Machine Learning, Deep Learning and Artificial Intelligence to decipher the biology of different biomolecules.

  • Plant Biotechnology  

It is very important to decipher the mechanism of generation and action of novel molecules for the plant genomics research. Here, we are performing different experiments to characterize and validate our in silico findings with the help of our colleagues.

 Group Members
Dr. Rashmi GangwarProject Scientist-I
Ajeet SinghPh.D. Student
Shafaque ZahraPh.D. Student
A. T. VivekPh.D. Student
Mohini JaiswalPh.D. Student
Srija ChakrabortySenior Research Fellow (SRF)
Rohan BhardwajProject Associate- I
Pragya ChitkaraProject Associate- I
Akila S.Project Associate- I
 Web Resources, Databases and Tools (Developed/Contributed)
PtncRNAdb: Plant transfer RNA-derived non-coding RNAs (tncRNAs) database (
MedProDB: Mediator Protein Database (
AlnC: An extensive database of long non-coding RNAs (lncRNAs) in Angiosperms (
tncRNA: A pipeline for the identification of tRNA-derived small ncRNAs (tncRNAs) from high throughput sequencing data (
PlantPepDB: A database of plant peptides having different functions and therapeutic activities (
PtRNAdb: A database containing information of tRNA genes (
AtFusionDB: A Database of Fusion Transcripts in Arabidopsis thaliana (
PVsiRNAdb:Plant Virus siRNA Database (
PtRFdb: Plant transfer RNA-derived fragments database (
Cancertope: A Platform for Designing Genome-Based Personalized Immunotherapy or Vaccine against Cancer (
CancerDr: Cancer Drug Resistance Database. (
PCMDB: Pancreatic cancer methylation database. (
OSDDlinux: A Customized Operating System for Drug Discovery. (
MtbVeb: A Web-Based Platform for Designing Vaccines against Existing and Emerging Strains of Mycobacterium tuberculosis. (


A) Corresponding Author / First Author Publications
Deepika, D., Poddar, N., Kumar, S*., and Singh A.* Molecular characterization reveals the involvement of calcium dependent protein kinases in abiotic stress signaling and development in chickpea (Cicer arietinum). Front. Plant Sci. (In Press)
Zahra, S., Bhardwaj, R., Sharma, S., Singh, S., and Kumar, S.* PtncRNAdb: Plant transfer RNA-derived non-coding RNAs (tncRNAs) database. 3 Biotech, 12, 105 (2022). PMID: 35462956
Chitkara, P., Poddar, N., Singh, A., and Kumar, S.* BURP domain-containing genes in legumes: genome-wide identification, structure, and expression analysis under stresses and development. Plant Biotechnol Rep (2022). (In Press)
Singh, A., Zahra S., Poddar N. and Kumar S.* Transfer RNA-derived non-coding RNAs (tncRNAs): hidden regulation of plants transcriptional regulatory circuits. Computational and Structural Biotechnology Journal. Volume 19, 2021, Pages 5278-5291. PMID: 34630945
Bhardwaj R, Thakur JK* and Kumar S*.  MedProDB: A database of Mediator proteins. Computational and Structural Biotechnology Journal Volume 19, 2021, Pages 4165-4176. PMID: 34527190
Singh A, Vivek AT and Kumar S*.(2021)  AlnC: An extensive database of long non-coding RNAs in angiosperms. PLoS ONE 16(4): e0247215. PMID: 33852582
Vivek AT and Shailesh Kumar*. Computational methods for annotation of plant regulatory non-coding RNAs using RNA-seq. Briefings in Bioinformatics, Volume 22, Issue 4, July 2021, bbaa322, PMID: 33333550
Das D, Jaiswal M, Khan F N, Ahamad S and Kumar S*. PlantPepDB: A manually curated plant peptide database. Scientific reports 10:2194(2020) PMID: 32042035
Vivek AT, Zahra S, and Kumar S*. From current knowledge to best practice: A primer on Viral diagnostics using deep sequencing of virus-derived small interfering RNAs (vsiRNAs) in infected plants. Methods; 2020 Nov 1;183:30-37. PMID: 31669354
Singh, A., Zahra S., Das D. and Kumar S.* AtFusionDB: A Database of Fusion Transcripts in Arabidopsis thaliana. Database (2018). Database (Oxford).Volume 2018 Jan 1. PMID: 30624648
Gupta, N., Zahra, S., Singh. A. and Kumar S.* PVsiRNAdb: A Database for Plant Exclusive Viral-derived small interfering RNAs. Database (2018). Database (Oxford).Volume 2018 Jan 1. PMID: 30307523
Gupta, N., Singh, A., Zahra, S. and Kumar S.* PtRFdb: a database for plant transfer RNA-derived fragments. Database (2018). Database (Oxford). 2018 Jan 1;2018. doi: 10.1093/database/bay063 PMID: 29939244
Kumar S, Razzaq SK, Vo AD, Gautam M, Li H: Identifying fusion transcripts using next generation sequencing. Wiley Interdisciplinary Reviews: RNA 2016, 7:811–823. (Cover Image) PMID: 27485475
Kumar S, Vo AD, Qin F, Li H: Comparative assessment of methods for the fusion transcripts detection from RNA-Seq data. Scientific reports 2016, 6:21597. PMID: 26862001
Kumar S, Vikram S, Raghava GPS: Genome Annotation of Burkholderia sp. SJ98 with Special Focus on Chemotaxis Genes. PLoS ONE 2013, 8:e70624. PMID: 23940608
Kumar S, Kushwaha H, Bachhawat AK, Raghava GPS, Ganesan K: Genome sequence of the oleaginous red yeast Rhodosporidium toruloides MTCC 457. Eukaryotic cell 2012,11:1083–4. PMID: 22858828
Kumar S, Randhawa A, Ganesan K, Raghava GPS, Mondal AK: Draft genome sequence of salt-tolerant yeast Debaryomyces hansenii var. hansenii MTCC 234. Eukaryotic cell 2012,11:961–2. PMID: 22744717
Kumar S, Subramanian S, Raghava GPS, Pinnaka AK: Genome sequence of the marine bacterium Marinilabilia salmonicolor JCM 21150T. Journal of bacteriology 2012, 194:3746. PMID: 22740671
Kumar S, Vikram S, Subramanian S, Raghava GPS, Pinnaka AK: Genome sequence of the halotolerant bacterium Imtechella halotolerans K1T. Journal of bacteriology 2012, 194:3731. PMID: 22740661
Kumar S, Vikram S, Raghava GPS: Genome sequence of the nitroaromatic compounddegrading Bacterium Burkholderia sp. strain SJ98. Journal of bacteriology 2012, 194:3286. PMID: 22628512
Vikram S, Kumar S, Subramanian S, Raghava GPS: Draft genome sequence of the nitrophenol-degrading actinomycete Rhodococcus imtechensis RKJ300. Journal of bacteriology 2012, 194:3543. PMID: 22689233
Kumar S, Kaur N, Singh NK, Raghava GPS, Mayilraj S: Draft Genome Sequence of Streptomyces gancidicus Strain BKS 13-15. Genome announcements, 1:e0015013. PMID: 23599292
Kumar S, Bala M, Raghava GPS, Mayilraj S: Draft Genome Sequence of Rhodococcus triatomae Strain BKS 15-14. Genome announcements, 1:e0012913. PMID: 23538907
Kumar S, Kaur C, Kimura K, Takeo M, Raghava GPS, Mayilraj S: Draft Genome Sequence of the Type Species of the Genus Citrobacter, Citrobacter freundii MTCC 1658. Genome announcements 2013, 1. PMID: 23405287
Bala M, Kumar S, Raghava GPS, Mayilraj S: Draft Genome Sequence of Rhodococcus ruber Strain BKS 20-38. Genome announcements, 1:e0013913. (Equal Contribution) PMID: 23558535
Kaur N, Kumar S, Bala M, Raghava GPS, Mayilraj S: Draft Genome Sequence of Amycolatopsis decaplanina Strain DSM 44594T. Genome announcements, 1:e0013813. (Equal Contribution) PMID: 23558534
Singh NK, Kumar S, Raghava GPS, Mayilraj S: Draft Genome Sequence of Acinetobacter baumannii Strain MSP4-16. Genome announcements, 1:e0013713. (Equal Contribution) PMID: 23558533
Bala M, Kumar S, Raghava GPS, Mayilraj S: Draft Genome Sequence of Rhodococcus qingshengii Strain BKS 20-40. Genome announcements, 1:e0012813. (Equal Contribution) PMID: 23538906
Vikram S, Kumar S, Vaidya B, Pinnaka AK, Raghava GPS: Draft Genome Sequence of the 2-Chloro-4-Nitrophenol-Degrading Bacterium Arthrobacter sp. Strain SJCon. Genome announcements, 1:e0005813. (Equal Contribution) PMID: 23516196
Kaur N, Kumar S, Mayilraj S: Genome sequencing and annotation of Amycolatopsis vancoresmycina strain DSM 44592T. Genomics Data 2014, 2:16–17. (Equal Contribution) PMID: 26484057
Kimura K, Kumar S, Takeo M, Mayilraj S: Genome sequencing, annotation of Citrobacter freundii strain GTC 09479. Genomics Data 2014, Dec; 2: 40–41 . (Equal Contribution) PMID: 26484065
B) As Collaborator / Contributor / Co-author
Raul B, Bhattacharjee O, Ghosh A, Upadhyay P, Tembhare K, Singh A, Shaheen T, Ghosh AK, Torres-Jerez I, Krom N, Clevenger J, Udvardi M, E Scheffler B, Ozias Akins P, Dutta Sharma R, Bandyopadhyay K, Gaur V, Kumar S, Sinharoy S. Microscopic and transcriptomic analyses of Dalbergoid legume peanut reveal a divergent evolution leading to Nod Factor dependent epidermal crack-entry and terminal bacteroid differentiation. Mol Plant Microbe Interact. 35(2):131-145. PMID: 34689599
Singh S, Qin F, Kumar S, Elfman J, Lin E, Pham L, Yang A and Li H (2019) The Landscape of Chimeric RNAs in Non-Diseased Tissues and Cells.  Nucleic acids research 2020; 48(4):1764-1778 PMID: 31965184
Wu P, Yang S, Singh S, Qin F, Kumar S, Wang L, Ma D and Li H: The Landscape and Implications of Chimeric RNAs in Cervical Cancer. EBioMedicine 2018 Oct 31. pii: S2352-3964(18)30477-8. doi: 10.1016/j.ebiom.2018.10.059. PMID: 30389505
Huang R, Kumar S, Li H: Absence of Correlation between Chimeric RNA and Aging. Genes 2017, 8: 386. PMID: 29240691
Xie Z, Babiceanu M, Kumar S, Jia Y, Qin F, Barr FG, Li H: Fusion transcriptome profiling provides insights into alveolar rhabdomyosarcoma. Proceedings of the National Academy of Sciences (PNAS) of the United States of America 2016, 113:13126–13131. PMID: 27799565
Dhanda SK, Vir P, Singla D, Gupta S, Kumar S, Raghava GPS: A Web-Based Platform for Designing Vaccines against Existing and Emerging Strains of Mycobacterium tuberculosis. PLOS ONE 2016, 11:e0153771. PMID: 27096425
Babiceanu M, Qin F, Xie Z, Jia Y, Lopez K, Janus N, Facemire L, Kumar S, Pang Y, Qi Y, Lazar IM, Li H: Recurrent chimeric fusion RNAs in non-cancer tissues and cells. Nucleic acids research 2016, 44:2859–72. PMID: 26837576
Gupta S, Chaudhary K, Dhanda SK, Kumar R, Kumar S, Sehgal M, Nagpal G, Raghava GPS: A Platform for Designing Genome-Based Personalized Immunotherapy or Vaccine against Cancer. PLOS ONE 2016, 11:e0166372. PMID: 27832200
Nagpal G, Sharma M, Kumar S, Chaudhary K, Gupta S, Gautam A, Raghava GPS: PCMdb: Pancreatic Cancer Methylation Database. Scientific reports 2014, 4:4197. PMID: 24569397
Kumar R, Chaudhary K, Gupta S, Singh H, Kumar S, Gautam A, Kapoor P, Raghava GPS: CancerDR: cancer drug resistance database. Scientific reports 2013, 3:1445. PMID: 23486013
Vikram S, Pandey J, Kumar S, Raghava GPS: Genes involved in degradation of paranitrophenol are differentially arranged in form of non-contiguous gene clusters in Burkholderia sp. strain SJ98. PloS one 2013, 8:e84766. PMID: 24376843
Singh SV, Kumar N, Singh SN, Bhattacharya T, Sohal JS, Singh PK, Singh AV, Singh B, Chaubey KK, Gupta S, Sharma N, Kumar S, Raghava GPS: Genome Sequence of the “Indian Bison Type” Biotype of Mycobacterium avium subsp. paratuberculosis Strain S5. Genome announcements 2013, 1. PMID: 23469332
C) Book Chapters
Narayan A and Kumar S*. (2022) Identification of novel RNAs in plants with the help of next-generation sequencing technologies. Bioinformatics in Agriculture, Academic Press, 177-189, doi:
Narayan A, Zahra S, Singh A, Kumar S*. In Silico Methods for the Identification of Viral-Derived Small Interfering RNAs (vsiRNAs) and Their Application in Plant Genomics. Methods Mol Biol. 2022;2408:71-84. doi: 10.1007/978-1-0716-1875-2_4. PMID:35325416.
Mandal M, Poddar N, Kumar S.* (2022) Identification of Novel Noncoding RNAs in Plants by Big Data Analysis. In: Singh S. (eds) Machine Learning and Systems Biology in Genomics and Health. Springer, Singapore.
Narayan A, Singh A, and Kumar S.* Understanding Microbiome Science through Big Data analysis. (eds). In: Singh S. (eds). Metagenomics Systems Biology. Springer, Singapore.
Vivek A.T., and Kumar S.* (2020). Genomics approaches in Plant Stress Research. In. Khan, Singh, and Poor (eds). Improving Abiotic Stress Tolerance in Plants. CRC Press/Taylor & Francis Group DOI: 10.1201/9780429027505-16.
Jaiswal M, Zahra S and Kumar S.* (2020). Bioinformatics tools for Epitope Prediction. In: Singh S. (eds). Systems and Synthetic Immunology. Springer, Singapore
Singh A and Kumar S.* (2019). Study of Plant Exclusive Virus-Derived Small Interfering RNAs. In: Kumar S., Egbuna C. (eds) Phytochemistry: An in-silico and in-vitro Update. Springer,Singapore.
Zahra S and Kumar S.* (2019). PtRFdb: Plant tRNA-Derived Fragments Database. In: Kumar S., Egbuna C. (eds) Phytochemistry: An in-silico and in-vitro Update. Springer,Singapore.
Singh A, Zahra S, and Kumar S.* (2019). In-Silico Tools in Phytochemical Research. In: Kumar S., Egbuna C. (eds) Phytochemistry: An in-silico and in-vitro Update. Springer,Singapore.
Narayan A, Singh A, and Kumar S.* (2019). Protein Homology Modeling in Phytochemical Research. In: Kumar S., Egbuna C. (eds) Phytochemistry: An in-silico and in-vitro Update. Springer, Singapore.
Zahra S, Singh A and Kumar S.* (2018). Synthetic Probes, Their Applications and Designing. In: Singh S. (eds) Synthetic Biology (Omics Tools and Their Applications). Springer, Singapore
Kumar S and Li H. (2017)  In silico designing of Anticancer Peptides.  In: Lazar I., Kontoyianni M., Lazar A. (eds) Proteomics for Drug Discovery. Methods in Molecular Biology, vol 1647. Humana Press, New York, NY

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