Education
Graduation (B.Sc., 2002)
University of Allahabad University, U.P., India.
Major: Biology and chemistry
Post-Graduation (M.Sc. Bioinformatics, 2005),
University of Allahabad, U.P. India
Major: Bioinformatics
Thesis: Comparative Protein Modelling and Structural Analysis of Calmodulin Protein
Ph.D. (2012)
Maulana Azad National Institute of Technology (MANIT), Bhopal, M.P., India
Major: Computational Biology and Bioinformatics
Thesis: Computational Approach to Study Nucleotide and Peptide Sequences of Mycobacterium tuberculosis.
Postdoc (Jan 2012-June 2014),
Department of Biology, Lund University, Lund, Sweden
Major: Computational Biology and Bioinformatics
Project: Functional and Structural diversity of microbes for carbon recycling in agricultural soils.
Appointments
Scientist-E (31st October 2019- Present),
National Institute of Animal Biotechnology, Hyderabad, India
Job profile: Develop computational resources to explore molecular mechanism of animal disease resistance and susceptibility, reproduction, bioinformatics data analysis and support.
Researcher (March 2019- Sept 2019),
Department of Biology, Lund University, Sweden
Job profile: Bioinformatics data analysis and support for running collaborative projects
Researcher (Aug 2015- Feb 2019),
Plant breeding platform, Plant Breeding, SLU Alnarp, Sweden
Job profile: Bioinformatics data analysis and support for collaborative projects between departments and SLU campuses, bioinformatics services and training courses.
Research Engineer (July 2014 – July 2015),
PlantLink, Plant Protection, SLU Alnarp, Sweden
Job profile: Bioinformatics data analysis and support for collaborative projects between SLU Alnarp and Lund University, bioinformatics services and training courses.
Professional Trainings
1. Course in doctoral supervision (3 weeks), SLU, Sweden
2. Teaching in Higher Education, basic course (3 weeks), SLU, Sweden
3. Teaching in higher education, step two (2 weeks),SLU, Sweden
4. Active e-learning course: course design and development (2 weeks), SLU, Sweden
5. Attended GENeco Workshop on Genomic , 12-25 January, 2014, Cesky Krumlov, Czech Republic
6. Attended course “DNA Amplification Technology”, 21-25 October, 2013, Applied Microbiology, Lund University, Lund, Sweden.
7. Attended four weeks course “Large scale genome analysis”, 2013, Lund University, Lund, Sweden.
8. Attended course on “Statistics for Biologists” in 2012, Lund University, Lund, Sweden.
9. Attended ISTE Workshop “Entrepreneurship Awareness Camp 2010”, MANIT, Bhopal, India
1. Indian Society of Technical Education(ISTE)
2. Computer Society of India(CSI)
3. Gwalior Academy of Mathematical Sciences(GAMS)
4. Society of Applied Life Sciences(SALS)
Organized National and International Courses (Resource Person)
1. Short term course organised on “Next Generation Sequencing Data Analysis” at the Department of Biotechnology, MNNIT, India, December 17-23, 2018.
2. High Throughput Sequencing DNA and RNA-Seq Analysis for Plant Breeding (12-23 March 2018), SLU, Sweden.
3. Introduction using databases for data mining and storage, ( 3-7 November 2015), Lund University, Sweden
4. National Workshop on BIOINFORMATICS, 2007, at MANIT, Bhopal, M.P., India
5. Five-day training program on “Bioinformatics and Genomics” for the faculties of Maharashtra Animal and Fishery Sciences University (MAFSU) from 13th -17th June, 2023, sponsored by NAHEP.
6. Five-day workshop on “Next Generation Sequence (NGS) Data Analysis and its Applications in Livestock Research,” from 20th -24th May 2024, sponsored under the SERB Karyashala Scheme.
Omics data provides a comprehensive structural and functional understanding of the whole cell, tissue or organism by simultaneous identification, characterization and quantification of biological molecules. Recent advancement of omics technologies has revolutionized the biological sciences and provided a platform to understand molecular mechanisms of biological systems. Nowadays, trends of multi-omics based research investigation are also quite popular in animal sciences. However, different scientists have different opinions about the merits and appropriateness of omics technologies for the identification of disease-causing genes, drug targets, biomarkers, host-pathogen interaction, personalized genomic predictions etc. But, integration of multi-omics data for system modelling and analyses are very powerful and accurate to develop holistic understanding of animal biology such as disease resistance and susceptibility, physiology, reproduction etc.
Figure 1: Omics data integration for system level studies.
Unprecedented growth and availability of omics data resources in the public domain are the key motivation of our data-driven research investigations in the field of animal science. Broad research themes of our lab at NIAB are a) to develop computational resources to support livestock research in India, b) explore the potential role of microbiome for animal health and welfare, and c) develop methods for the identification of new and emerging pathogens in livestock animals.
Presently, our lab is engaged in following projects:
1. IndiGau, the high-density SNPchip (DBT-NIAB_HDchip) developed by NIAB, envisions to identify the pure breed and segregating indigenous pure cattle breeds from crossbreds. This project aims to conduct Genome-wide association studies (GWAS) studies to explore the genetic potential of breeds for milk traits. GWAS is a method to identify genes associated with a particular trait by utilising an entire set of DNA of a large population of animals. In this project, four thousand samples of Five breeds, i.e. Gir, Sahiwal, Tharparkar, Kankrej and Ongole have been selected for the GWAS study.
2. Implementation of omics approaches to identify broad spectrum vaccine candidates against Bovine Mastitis
Bovine mastitis (BM), mammary gland inflammation caused by a multitude of pathogens, is one of the oldest known diseases of the dairy industry. A plethora of studies have been performed to explore mastitis causing pathogens for disease diagnosis and treatment and these studies have led to the identification of a large number of mastitis associated pathogens. Due to the large number of bacteria associated with this disease, it is extremely difficult to develop a vaccine for each and every pathogen associated with these bacteria. Thus, a strategic research approach is required for the identification of vaccine candidates representing a wide range of bacteria. Here, we are exploring multi-omics data to enlist the pathogenic bacteria found in mastitis milk samples to identify broad spectrum vaccine candidates or multi-epitope vaccines for experimental validation and application.
Figure 3: Schematic representation of used workflow for the study.
3. Potential role of bovine microbiome in non-obstructive infertility
Figure 4: Metagenomic approach to understand non-obstructive cyclic infertility in cows.
Bovine infertility is a pervasive problem in livestock production systems worldwide. Various research studies were performed and identified a range of factors associated with bovine infertility such as reproductive disturbance or disorder (ovarian aplasia and atrophy), physiological and hormonal imbalance, uterine infection and nutritional deficiency, which may work separately or in combination. In recent host-associated microbiome studies, significant influences of microbiome on host health, physiology, development, regulation of digestion and reproductive system were shown. Currently, the studies to explore the potential of bovine microbiome causing infertility are very limited due to associated biological complexity with infertility. However, a system level understanding of host microbiome-organelles association, pervasive and non-pervasive microbial communities, physiological and hormonal interplay of digestive and reproductive system can help us to understand bovine non-obstructive infertility. Here, we developed a strategic research approach to explore the bovine non-obstructive infertility. In this study, repeat breeding infertility cases will be investigated in farm settings and association of host microbiome will be evaluated for bovine infertility.
Peer-reviewed research papers
2024
1. Panchariya DC, Dutta P, Ananya , Mishra A, Chawade A, Nayee N, Azam S, Gandham RK, Majumdar S and Kushwaha SK (2024) Genetic marker: a genome mapping tool to decode genetic diversity of livestock animals. Front. Genet. 15:1463474. doi: 10.3389/fgene.2024.1463474
2. Gupta D, Sarkar A, Pal Y, Suthar V, Chawade A and Kushwaha SK (2024) Bovine reproductive tract and microbiome dynamics: current knowledge, challenges, and its potential to enhance fertility in dairy cows. Front. Microbiomes 3:1473076. doi: 10.3389/frmbi.2024.1473076
3. Ananya, Panchariya, D.C., Karthic, A., Singh, S.P., Mani, A., Chawade, A. and Kushwaha, S., 2024. Vaccine design and development: Exploring the interface with computational biology and AI. International Reviews of Immunology, pp.1-20.doi: 10.1080/08830185.2024.2374546.
2023
4. Maurya, N.S.; Kushwaha, S.; Vetukuri, R.R.; Mani, A. Unlocking the Potential of the CA2, CA7, and ITM2C Gene Signatures for the Early Detection of Colorectal Cancer: A Comprehensive Analysis of RNA-Seq Data by Utilizing Machine Learning Algorithms. Genes 2023, 14, 1836. https://doi.org/10.3390/genes1410183
5. Roy A, Houot B, Kushwaha S and Anderson P (2023) Impact of transgenerational host switch on gut bacterial assemblage in generalist pest, Spodoptera littoralis (Lepidoptera: Noctuidae). Front. Microbiol. 14:1172601. doi: 10.3389/fmicb.2023.1172601
2022
10. B. Rathi, S. Gupta, P. Kumar, V. Kesarwani, RS Dhanda, SK Kushwaha & M Yadav. Anti-biofilm activity of caffeine against uropathogenic E. coli is mediated by curli biogenesis. Sci Rep 12, 18903 (2022). https://doi.org/10.1038/s41598-022-23647-2
11. A. Chaudhary, P. K. Chaurasia, S Kushwaha, P Chauhan, A Chawade, A Mani,Correlating multi-functional role of cold shock domain proteins with intrinsically disordered regions, International Journal of Biological Macromolecules, 2022, 220:743-753,https://doi.org/
12. Piombo E, Vetukuri RR, Sundararajan P, Kushwaha S, Funck Jensen D, Karlsson M, Dubey M. Comparative Small RNA and Degradome Sequencing Provides Insights into Antagonistic Interactions in the Biocontrol Fungus Clonostachys rosea. Appl Environ Microbiol. 2022 Jun 13:e0064322. doi: 10.1128/aem.00643-22. Epub ahead of print. PMID: 35695572.
13. Karthic A, Kesarwani V, Singh RK, Yadav PK, Chaturvedi N, Chauhan P, Yadav BS, Kushwaha SK. Computational Analysis Reveals Monomethylated Triazolopyrimidine as a Novel Inhibitor of SARS-CoV-2 RNA-Dependent RNA Polymerase (RdRp). Molecules. 2022 Jan 26;27(3):801. doi: 10.3390/molecules27030801. PMID: 35164069
14. Barin, M., Asadzadeh, F., Hashemnejad, F., Vetukuri RR., and Kushwaha SK. Optimization of Culture Conditions for Zinc Phosphate Solubilization by Aspergillus sp. Using Response Surface Methodology. J Soil Sci Plant Nutr (2022). https://doi.org/10.1007/s42729-021-00709-4
2021
15. Sandeep K Kushwaha, Inger Åhman, Therése Bengtsson, ResCap: plant resistance gene prediction and probe generation pipeline for resistance gene sequence capture, Bioinformatics Advances, Volume 1, Issue 1, 2021, vbab033, https://doi.org/10.
16. Rouydel, Z.; Barin, M.; Rasouli-Sadaghiani, M.H.; Khezri, M.; Vetukuri, R.R.; Kushwaha, S.: Harnessing the Potential of Symbiotic Endophytic Fungi and Plant Growth-Promoting Rhizobacteria to Enhance Soil Quality in Saline Soils. Processes 2021, 9, 1810.
17. Piombo E, Vetukuri RR, Broberg A, Kalyandurg PB, Kushwaha S, Funck Jensen D, Karlsson M, Dubey M: Role of Dicer-Dependent RNA Interference in Regulating Mycoparasitic Interactions. Microbiology Spectrum 2021, 9(2):e01099-01021.
18. Kesarwani V, Gupta R, Vetukuri RR, Kushwaha SK, Gandhi S: Identification of Unique Peptides for SARS-CoV-2 Diagnostics and Vaccine Development by an In Silico Proteomics Approach. Front Immunol 12: 725240 doi: 103389/fimmu 2021.
19. Wang S, Vetukuri RR, Kushwaha SK, Hedley PE, Morris J, Studholme DJ, Welsh LR, Boevink PC, Birch PR, Whisson SC: Haustorium formation and a distinct biotrophic transcriptome characterize infection of Nicotiana benthamiana by the tree pathogen Phytophthora kernoviae. Molecular Plant Pathology
20. Maurya NS, Kushwaha S, Chawade A, Mani A: Transcriptome profiling by combined machine learning and statistical R analysis identifies TMEM236 as a potential novel diagnostic biomarker for colorectal cancer. Scientific Reports 2021, 11(1):14304.
21. Katja Kozjek DK, Sandeep K. Kushwaha, Pål Axel Olsson, Dag Ahrén, Andreas Fliessbach, Klaus Birkhofer, Katarina Hedlund: Long-term agricultural management impacts arbuscular mycorrhizal fungi more than short-term experimental drought. Applied Soil Ecology 2021, 168:104140
2020
22. Kushwaha SK*, Kesarwani V, Choudhury S, Gandhi S, Sharma S: SARS-CoV-2 transcriptome analysis and molecular cataloguing of immunodominant epitopes for multi-epitope based vaccine design. Genomics 2020, 112(6):5044-5054.
23. Kumar Kushwaha S*, Vetukuri RR, Odilbekov F, Pareek N, Henriksson T, Chawade A: Differential Gene Expression Analysis of Wheat Breeding Lines Reveal Molecular Insights in Yellow Rust Resistance under Field Conditions. Agronomy 2020, 10(12):1888.
24. Kumar D, Kushwaha S, Delvento C, Liatukas Ž, Vivekanand V, Svensson JT, Henriksson T, Brazauskas G, Chawade A: Affordable phenotyping of winter wheat under field and controlled conditions for drought tolerance. Agronomy 2020, 10(6):882.
25. Alexandersson E, Kushwaha S, Subedi A, Weighill D, Climer S, Jacobson D, Andreasson E: Linking crop traits to transcriptome differences in a progeny population of tetraploid potato. BMC plant biology 2020, 20(1):1-14.
2019
26. Kushwaha SK*, Grimberg Å, Carlsson AS, Hofvander P: Charting oat (Avena sativa) embryo and endosperm transcription factor expression reveals differential expression of potential importance for seed development. Molecular Genetics and Genomics 2019, 294(5):1183-1197.
27. Kalyandurg PB, Tahmasebi A, Vetukuri RR, Kushwaha SK, Lezzhov AA, Solovyev AG, Grenville-Briggs LJ, Savenkov EI: Efficient RNA silencing suppression activity of Potato Mop-Top Virus 8K protein is driven by variability and positive selection. Virology 2019, 535:111-121.
28. Desta ZA, Kolano B, Shamim Z, Armstrong SJ, Rewers M, Sliwinska E, Kushwaha SK, Parkin IA, Ortiz R, De Koning D-J: Field cress genome mapping: integrating linkage and comparative maps with cytogenetic analysis for rDNA carrying chromosomes. Scientific reports 2019, 9(1):1-14.
2018
29. Vetukuri RR, Tripathy S, Malar C M, Panda A, Kushwaha SK, Chawade A, Andreasson E, Grenville-Briggs LJ, Whisson SC: Draft genome sequence for the tree pathogen Phytophthora plurivora. Genome biology and evolution 2018, 10(9):2432-2442.
30. Vetukuri RR, Kushwaha SK, Sen D, Whisson SC, Lamour KH, Grenville-Briggs LJ: Genome sequence resource for the oomycete Taro pathogen Phytophthora colocasiae. Molecular Plant-Microbe Interactions 2018, 31(9):903-905.
2017
31. Kushwaha SK, Vetukuri RR, Grenville-Briggs LJ: Draft genome sequence of the mycoparasitic oomycete Pythium oligandrum strain CBS 530.74. Genome announcements 2017, 5(21):e00346-00317.
32. Manoharan L, Kushwaha SK, Ahren D, Hedlund K: Agricultural land use determines functional genetic diversity of soil microbial communities. Soil Biology & Biochemistry 2017, 115(December 2017):423-432.
33. Kushwaha SK, Vetukuri RR, Grenville-Briggs LJ: Draft genome sequence of the mycoparasitic oomycete Pythium periplocum strain CBS 532.74. Genome announcements 2017, 5(12):e00057-00017.
34. Grenville-Briggs LJ, Kushwaha SK, Cleary MR, Witzell J, Savenkov EI, Whisson SC, Chawade A, Vetukuri RR: Draft genome of the oomycete pathogen Phytophthora cactorum strain LV007 isolated from European beech (Fagus sylvatica). Genomics data 2017, 12:155-156.
2016
35. Roy A, Walker III WB, Vogel H, Kushwaha S, Chattington S, Larsson M, Anderson P, Heckel DG, Schlyter F: Data set for diet specific differential gene expression analysis in three Spodoptera moths. Data in brief 2016, 8:448-455.
36. Kushwaha SK*, Chauhan P, Hedlund K, Ahrén D: NBSPred: a support vector machine-based high-throughput pipeline for plant resistance protein NBSLRR prediction. Bioinformatics 2016, 32(8):1223-1225.
37. Hofvander P, Ischebeck T, Turesson H, Kushwaha SK*, Feussner I, Carlsson AS, Andersson M: Potato tuber expression of Arabidopsis WRINKLED1 increase triacylglycerol and membrane lipids while affecting central carbohydrate metabolism. Plant Biotechnology Journal 2016, 14(9):1883-1898.
2015
38. Manoharan L, Kushwaha SK, Hedlund K, Ahrén D: Captured metagenomics: large-scale targeting of genes based on ‘sequence capture’reveals functional diversity in soils. DNA Research 2015, 22(6):451-460.
39. Kushwaha SK*, Manoharan L, Meerupati T, Hedlund K, Ahrén D: MetCap: a bioinformatics probe design pipeline for large-scale targeted metagenomics. BMC bioinformatics 2015, 16(1):1-11.
2011
40. Biswas S. Kushwaha, Rahul S. Mandal, Saugata Roy, Das HR: Structural Model Based Designing of Inhibitors for Glial Fibrillary Acidic Protein. Annals of Biological Research 2011, 2(1):40-50.
2010
41. Kushwaha SK*, Shakya M: Protein interaction network analysis—approach for potential drug target identification in Mycobacterium tuberculosis. Journal of theoretical biology 2010, 262(2):284-294.
42. Kushwaha S*, Chauhan P, Jha M, Shrivastava S: Rational drug designing for drug target alanine racemase (Alr) of mycobacterium tuberculosis. The Internet Journal of Infectious Diseases 2010, 8(1).
2009
43. Kushwaha SK*, Shakya M: Molecular modelling and dynamics studies of Mycobacterium tuberculosis protein RelA (Rv2583c). International Journal of Integrative Biology 2009, 7(3):135.
44. Kushwaha SK*, Shakya M: PINAT: protein interaction network analysis tool. Bioinformation 2009, 3(10):419.
45. Sharma N, Kushwaha SK, Chauhan P, Shakya M: Development of Efficient Drug Analogs for Dutasteride through Insilico Modeling. Internet Journal of Medical Informatics 2009, 5(1):p2.
46. Kushwaha S*, Shakya M: Protocol of Rice Genome Annotation through Comparative Functional Genomics Approach. Internet Journal of Genomics & Proteomics; 2009, 4(1).
47. Kushwaha S*, Chauhan P, Shakya M: Comparative Phylogenetics Approach for Discovering Alternative Source of Taxol. The Internet Journal of Bioengineering 2008, 3(2).
Peer-reviewed Review papers
1. Maurya NS, Kushwaha S, Mani A: Recent Advances and Computational Approaches in Peptide Drug Discovery. Current pharmaceutical design 2019, 25(31):3358-3366.
2. Paritosh K, Kushwaha SK, Yadav M, Pareek N, Chawade A, Vivekanand V: Food waste to energy: an overview of sustainable approaches for food waste management and nutrient recycling. BioMed research international 2017, 2017.
Peer-reviewed Conference papers
1. Kushwaha SK, Shakya M: Neural Network: A Machine Learning Technique for Tertiary Structure Prediction of Proteins from Peptide Sequences. In: 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies: 2009. IEEE: 98-101.
2. Kushwaha SK, Shakya M: Multi-layer perceptron architecture for tertiary structure prediction of helical content of proteins from peptide sequences. In: 2009 International Conference on Advances in Recent Technologies in Communication and Computing: 2009. IEEE: 465-467.
3. Rathore B, Kushwaha SK, Shakya M: Identification of Melanoma (Skin Cancer) Proteins through Support Vector Machine. In: International Conference on Advances in Information and Communication Technologies: 2010. Springer, Berlin, Heidelberg: 571-575.
Book:
1. Mani, A., & Kushwaha, S. (Eds.). (2023). Genomics of Plant–Pathogen Interaction and the Stress Response (1st ed.). CRC Press. https://doi.org/10.1201/9781003153481
Book availability.
Book Chapters
1. Birendra Singh Yadav, Sandeep Kushwaha, Saurabh Yadav, Ashutosh Mani: Meta-Analysis of Arabidopsis thaliana Gene Expression Data Identifies Heavy Metal Stress Responsive Genes, Genomics of Plant-Pathogen Interaction and the Stress Response, Edition 1st Edition, 2023, CRC Press, Pages 12, eBook ISBN : 9781003153481
2. Yadev BS, Chauhan P, Kushwaha S: Bioinformatics Resources for Microbial Research in Biological Systems. In: Microbial Genomics in Sustainable Agroecosystems. Springer, Singapore; 2019: 45-60.
3. Yadav BS, Singh AK, Kushwaha SK: Systems-Based Approach to the Analyses of Plant Functions: Conceptual Understanding, Implementation, and Analysis. In: Plant Bioinformatics. Springer, Cham; 2017: 107-133.
Posters
1. Vetukuri RR, Kalyandurg PB, Sen D, Kushwaha S, Brus-Szkalej M, Boevink P, Whisson SC, Savenkov EI, Grenville-Briggs LJ: The role of viral and oomycete suppressors of silencing in modulating plant defense. In: 2019 IS-MPMI XVIII Congress: 2019. ISMPMI.
2. Sen D, Kushwaha S, Lamour K, Tripathy S, Grenville-Briggs L, Vetukuri R: New insights into pathogenicity of the emerging tropical pathogen: Phytophthora colocasiae on taro, molecular plant-microbe interactions: 2019
3. Kushwaha SK, Manoharan L, Hedlund K, Ahren D, Protein interaction analysis approach for the investigation of lignin degradation pathways, Lund University, May 2015, Sweden, London
Current Lab Members:
DBT – RA:Deepshikha Gupta,
Ph. D., University of Hyderabad
Current Research Interest: Metagenomics interrogation of bovine reproductive tract of non obstructive cyclic infertile cows
PhD Students:
Naveen Prasath
Current Research Interest: Bovine infertility is a severe problem in the livestock production system. A large number of indigenous and crossbred cattle reside in India, which do not have single calving during their lifetime. The causes of infertility are not known because these animals look normal clinically. The primary focus of my research is to explore the microbial prospect of bovine infertility in non-obstructive cyclic infertile cows and association of mastitis to reproduction performance.
Project Associates:Darshan C Panchariya
MSc. Animal Biology and Biotechnology
University of Hyderabad
Position: Project Associate-I
Project: Validation of DBT-NIAB SNP chip for breed identification and preliminary genome-wide association studies of milk yield
Ananya
M.Sc. Bioinformatics, Central University of South Bihar
Position: Project Associate-I
Project: Validation of DBT-NIAB SNP chip for breed identification and preliminary genome-wide association studies of milk yield
Former Lab Members:
Priyanka Dutta
M.Sc Zoology, Gurudas College, University of Calcutta
Badeer Hassan U
BSMS in Biology, IISER Pune
A Karthic
B.Tech. + M. Tech. Biotechnology, Amity University Maharashtra
Veerbhan Kesarwani
M.Sc. Bioinformatics, University of Allahabad, Prayagraj
Adyasha Mishra
Msc in Biotechnology, RamaDevi Women’s University, Odisha
Ongoing Research Projects:
1. Validationof DBT-NIAB SNP chip for breed identification and preliminary genome-wide association studies of milk yield (PI)
2. Identification of key molecular players specially lncRNAs involved in response to NDV challenge in indigenous and exotic chicken breeds using RNA-seq analysis (Co-PI)
3. “Genomics assisted pathobiology to identify novel targets for diagnosis and therapeutic intervention(s) of Japanese encephalitis and Leptospirosis” (Co-PI)
Previously Completed Research Projects:
4. 2016-2017: Computational Infrastructure: To drive the plant breeding education and research front at SLU, Kungliga Fysiografiska Sällskapets, Sweden.
5. 2016-2018: The microbiome of the invasive pest Drosophila suzukii and its impact on the fly’s sexual communication, behavior and reproduction, Crafoord foundation, Sweden.
6. 2016-2018: Transcriptional regulation of oil in wheat, Crafoord foundation, Sweden.
7. 2017-2018: Molecular Biology to Support Oat Breeding for Seed Development and Oil Storage, Kungliga Fysiografiska Sällskapets, Sweden.
8. 2018-2020: Resistance Gene Array: a targeted approach to capture plant resistance genes, FORMAS, Sweden.
9. 2018-2019: Targeted transcriptomics approach for the capturing of plant resistance genes at large scale Kungliga Fysiografiska Sällskapets, Sweden.
10. 2019-2020: Promotion of Decoko (Pisum sativum ssp. Abyssinicum) for a food security in Ethiopia, VR network grant, Sweden.
National Institute of Animal Biotechnology
Survey No. 37, Opp. Journalist Colony
Extended Q City Road, Near Gowlidoddy
Gachibowli, Hyderabad
Telangana – 500032
Email: sandeep[at]niab[dot]org[dot]in
Tel: +91-(0)40-2312-0150
Our lab is actively looking for talented and motivated research scholars at all levels (Postdocs, SRF, JRF etc.) who have basic understanding of genetics, functional genomics, computational biology or similar and deep desire to learn new expertise to excel in his/her research career.
PhD: Applicants with valid NET-JRF can contact to PI for PhD admission or hosting of PhD. grant proposals.
Postdoc: Applicants can contact to PI to discuss some of the opportunities:
1. SERB-National Post-Doctoral Fellowship (N-PDF)
2. DBT Research Associateship
3. INSPIRE Fellowship
4. UGC postdoctoral fellowship
5. SERB Women Scientist Fellowship
If interested, please send me an e-mail (sandeep [at]niab[dot]org[dot]in) with your detailed CV and a brief statement of research interest.
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