Dr. Subha Srinivasan and team members use genomics and bioinformatics techniques to diverse application areas of biology including cancer biomarker discovery, plant genomics, root metagenomics, nutritional genomics and noninvasive diagnostics. Dr. Srinivasan is also involved in teaching both basic and advanced bioinformatics courses to Masters level students, which includes concepts/algorithms behind every major bioinformatics tools. She also provides training in big data analysis through interns programs. Her lectures are recorded and can be made available.
- Research Interest
Cancer: The large repository of NGS data in cancer, generated by NCI, is pregnant with molecular signatures unique to cancer tissues. Extracting cancer-specific signatures by profiling various molecular types from diverse NGS applications allows for systems level interrogation of cancer biology. Her group is currently focusing on prostate cancer.
Nutrition genomics: India has a unique major unmet need compared to the West; the malnutrition problem. To be more specific, India’s problem for the most part is lysine malnutrition. Lysine is the most limiting amino acid in rice and wheat. This lack is exaggerated by the fact that lysine is critical to maintain integrity of collagen structure, which is critical to prevent infection. Efforts to engineer high-lysine rice and wheat has mostly failed because of inherent inverse correlation between high-lysine and high-yield. The lack of correlation, however, is mitigated in grain amaranth, a Caryophylalles. Subha’s group is using genomics to crack this puzzle.
Plant genomics: The holy grail of plant genomics research is to make all the agronomic crop to be draught resistant, saline tolerant, high-yielding, healthy grains with long shelf life. This may sound like a tall order. But nature has achieved this in grain amaranth. As a C4 dicot, rare among edible dicot plant species, grain amaranth displays majority of the desirable traits. Subha’s group is using comparative genomics/transcriptomics to extract genotypes unique to grain amaranth that are responsible for these unique traits.
Root metagenomics: All organisms have evolved symbiotically along with other organisms. For example, plants have evolved symbiotically with soil microbes in and mammals have evolved with gut microbes, which play a critical role in extraction of nutrients from environment. Said that, it is not sufficient to just dissect the genome of an organism to explain all phenotypes displayed by a species. Roots of plants tender organic/amino acids in exchange for some metabolites from microbial species that help it stay healthy, defend against infection and produce healthy seeds. Subha’s group is actively involved in identifying and characterizing microbial species that are uniquely enriched by grain amaranths using metagenomics and comparative metagenomics.
Alternative splicing: It is now well established that alternative splicing is used to create protein diversity in higher eukaryotes. Besides, cancer tissues are reported to display differential splicing. Methods to identify differential splicing remain challenging despite the increased sensitivities in measurements from RNA sequencing technologies. Subha’s group is actively involved in developing novel methods and statistics that simplifies profiling of alternatively spliced forms across large number of tissues.
Big Data training/solutions: All the projects mentioned above rely on analysis of big sequence data where some files can be as large as 20-80 GB in size. Cloud computing is being embraced by genomics community to handle the elastic computing needs. Subha’s group routinely uses AWS cloud to analyze big data from public repositories. Her group is also involved in developing solutions that allows automated processing of data from 100-1000 samples simultaneously overnight on AWS cloud.
- Institute of Bioinformatics and Applied Biotechnology (IBAB)
Faculty Scientist: April 2015-Present
- Institute of Bioinformatics and Applied Biotechnology (IBAB)
Faculty Scientist/DBT Fellow (DBT, GoI): July 2010-March 2015
- Jivan Biologics, Larkspur, CA (2001-2010) 9 years
Founder and Chief Scientific Officer
- Berlex Biosciences, Richmond, CA (1998-2001) 3.5 years
- Immunex Corporation, Seattle, WA (1994-1997) 4 years
- Immunex Corporation, Seattle, WA (1989-1994) 5 years
Head, Computational Chemistry
- IDEC Pharmaceutical, San Diego, CA (1987-1989)
- Roswell Park Memorial Institute, Buffalo, NY (1984-1987)
Post Doctoral Position
- Ph. D., Physics, Madras University, Chennai, India,
- Simulation of Biomolecular Structures in a Computer
- M.S., Physics, Ranchi University, Bihar, India
- Specialization in Crystallography
- B.S., Physics, Ranchi University, Bihar, India
|7,833,779||Jivan||Methods for designing oligonucleotides|
|7,340,349||Jivan||Method and system for identifying splice variants of a gene|
|6,410,711||Immunex||DNA encoding CD40 ligand, a cytokine that binds CD40|
|6,290,972||Immunex||Method of augmenting a vaccine response by administering CD40 ligand|
|6,264,951||Immunex||Methods of inhibiting CD40L binding to CD40 with soluble monomeric CD40L|
|5,981,724||Immunex||DNA encoding CD40 ligand, a cytokine that binds CD40|
|5,962,406||Immunex||Recombinant soluble CD40 ligand polypeptide and pharmaceutical composition containing the same|
|5,884,230||Immunex||Method and system for protein modeling|
|5,716,805||Immunex||Methods of preparing soluble, oligomeric proteins|
|5,557,535||Immunex||Method and system for protein modeling|
|5,453,937||Immunex||Method and system for protein modeling|
1) Bawa P., Zacharia S., Srivatsan R., and Srinivasan S. (2015) “Up-regulation is the norm for lincRNAs specific to prostate cancer”, PLoS One, 01 May 2015.
2) Sunil M., Nayak S., Hariharan A., Gupta RP., Panda B., Choudhury B., Srinivasan S. (2014) “The draft genome and transcriptome of Amaranthus hypochondriacus: A C4 dicot producing high-lysine edible pseudo- cereal”, DNA Research, Dec;21(6):585-602.
3) Srinivasan S., Patil AH, Verma M., Bingham JL., Srivatsan R. (2012) “Genome-wide profiling of RNA splicing in prostate tumor from RNA-seq data using virtual microarrays.” J. Clinical Bioinformatics, 2:21 (HIGHLY ACCESSED status by BioMed Central)
4) Patil, AH M., Deshmukh, M. Singh, NK., Srivastava, R., Verma, M., Gupta, S., Veeresh, S., Srivatsan, R., Srinivasan, S. (2012), “From data repositories to biomarker discovery: Application to prostate cancer.” Current Science, April 2012, 102 (08)
5) Johnson ED, Sudarsanam S, Bingham J, Srinivasan, S. (2012) “Translational biology approach to identify causative factors for rare toxicities in humans and animals.”Curr Drug DiscovTechnol,9(1):77-80.
6) Srinivasan, S. (2011) “Alternative Splicing in Eukaryotes: The Norm, Not an Anomaly”. Current Science, March 2011, 100 (06)
8) Srinivasan, S., Bingham, J., Johnson, D. (2009) “The ABC’s of Alternative Splicing: A Review of ATP-Binding Cassette Transporter Splicing”. CODD, 12, 149-158
9) Bingham, J.L, Carrigan, P.E., Miller, L.J., Srinivasan, S. (2008) “Extent and diversity of human alternative splicing established by complementary database annotation and microarray analysis”.Omics, 12, 1-6
10) Bingham, J., Sudarsanam, S., Srinivasan, S. (2006) “Profiling human phosphodiesterase genes and splice isoforms”. Biochemical and Biophysical Research Communications, Vol. 350, 25-32
11) Seto, M., Whitlow, M., McCarrick, MA., Srinivasan, S., Zhu, Y., Paglia, R., Mintzer, R., Light, D., Johns, A., Meurer-Ogden, JA., (2004) “A Model of Acid Sphingomyelnase Phosphoesterase Domain Based on its Remote Structural Homolog Purple Acid Phosphatase”. Protein Science, 13, 3172-3186
12) Srinivasan. S. (1998) “Homology Folding of Proteins: Application to Cytokine Engineering”. Springer-Verlog, Berlin
13) Black, R. A., Rauch, C. T., Kozlosky, C. J., Peschon, J. J., Slack, J. L., Wolfson, M. F., Castner, B. J., Stocking. K. L., Reddy, P., Srinivasan, S., Nelson, N., Boiani, N., Schooley, K. A., Gerhart, M., Davis, R., Fitzner, J. N., Johnson, R. S., Paxton, R. J., March, C. J., and Cerretti, D. P. (1997) “A Metalloproteinase Disintegrin that Releases Tumor Necrosis Factor- from Cells”. Nature 385, 729-733
14) Graddis, T. J., Brasel, K., Friend, D., Srinivasan, S., Wee, S., Lyman, S. D., March, C. J. and McGrew, J. T. (1998) “Struncture-function analysis of flt3 ligand-flt3 receptor interactions using a rapid functional screen”. J. Biol. Chemistry, Vol. 273 (28), 17626-17633.
15) Pettit, D. K., Bonnert, T. P., Eisenman, J., Srinivasan, S., Paxton, R., Beers, C., Lynch, D., Miller, B., Yost, J., Grabstein, K. H., Gombotz, W. R. (1997) “Structure-function studies of interleukin15 using site-specific mutagenesis, polyethylene glycol conjugation, and homology modeling”. J. Biol. Chem. 272, 2312-2318.
16) Sudarsanam, S. and Srinivasan S. (1997) “Sequence dependent conformational sampling using a database of i+1, i angles for predicting polypeptide backbone conformations”. Protein Engineering Vol. 10, 1155-1162.
17) Srinivasan, S. and Sudarsanam, S. (1996) “Homology Guided Protein Folding: Application to Protein Therapeutic Design, Biomolecules: From 3D Structures to application”. Proceedings of the Thirty-Fourth Hanford Symposium on health and the Environment, Edited by Rick L. Ornstein, 67-81.
18) Sudarsanam, S., DuBose, R., March, C. J., and Srinivasan S. (1995) “Modeling Protein Loops Using a i+1, i dimer database”. Protein Science 4, 1412-1420.
19) Sudarsanam, S., March, C. J., and Srinivasan, S. (1994) “Homology Modeling of Divergent Proteins”. J. Mol. Biol. 241, 143-149.
20) Sudarsanam, S.. and Srinivasan, S. (1995) “Searching for Protein Loop Conformations in Parallel”. CABIOS 11, 591-593.
21) Baum, P., Gayle, R. B., Ramsdell, F., Srinivasan, S., Sorensen, R., Watson, M., Seldin. M., Baker, E., Sutherland, G., Clifford, K., Anderson, M., Goodwin, R., and Fanslow, W. (1994) “Molecular Characterization of Murine and Human OX40/OX40 ligand systems: Identification of Human OX40 Ligand as the HTLV-1 Regulated Protein gp34″. EMBO J, 13, 3992.
22) Peter Baum, Gayle, R. B., Ramsdell, F., Srinivasan, S., Sorensen, R., Watson, M., Seldin. M., Baker, E., Sutherland, G., Clifford, K., Anderson, M., Goodwin, R., and Fanslow, W. (1994) “Identification of OX40 ligand and preliminary characterization of its activities on OX40 receptor”. Circ. Shock 44, 30.
23) Fanslow, W. C., Srinivasan, S., Paxton, R., Gibson, M., Spriggs, M. K., and Armitage, R. J. (1994) “Structural Characteristics of CD40 ligand that Determine Biological Function”. Seminars in Immunology 6, 267-278.
24) Beckmann, P. M., Gayle, R. B., Crrretti, D. P., March, C. J., Srinivasan, S., and Sleath P. R. (1993) “Structural and Functional Charaterization of the Interleukin-8 Receptors”. The Chemokines,Edited by I. J. D. Lindley et al., Plenum Press New York, 155-169.
25) Kozlosky, C. J., Maraskovsky, E., McGrew, J. T., Vandenbos, T., Teepe, M., Lynman, S. D., Srinivasan, S., Fletcher, F. A., Gayle, R. B., Cerretti, D. P., and Beckmann, P. (1995) “Ligands for the Receptor Tyrosine Kinases Hek and Elk: Isolation and cDNAs Encoding a Family of Proteins”. Oncogene, 10, 299.
26) Srinivasan, S., March, C.J. and Sudarsanam, S. (1993) “Sequence into Structure: A Holistic Approach To Protein Modeling”. Bio/Technology magazine, December, 1579-1580.
27) Grabstein, K.H., Shanebeck, K., Rauch, C., Srinivasan, S., Fung, V., Beer. C., Richardson, J., Schoenborn, M., King, J., Johnson, L., Anderson, M., Watson, James., Anderson, D.M. and Eisenman J. (1994) “Cloning of the T-cell growth factor that interacts with the b Chain of the Interleukin-2 Receptor”. Science 264, 965-968.
28) Gayle, R. B., Sleath, P. R., Srinivasan, S., Birk, C. W., Weerawarna, K. S., Cerretti, D. P., Kozlosky, C. J., Nelson, N., VandenBos, T. and Beckmann, M. P. (1993) “Importance of the amino terminus of the interleikin-8 receptor in ligand interactions”. J. Biol. Chem., 268, 7283.
29) Srinivasan, S., Deeley, M. M., Park, C. J., Sassenfeld, H. and Sudarsanam, S. (1993) “A Model od IL-7 and the Extra-cellular Domains of its Receptor Complex using Distance Geometry and Structure-Function Data”. Protein Engineering, 6 Supp., 107.
30) Gayle, R. B., Cosman, D., Dower, S., Hopp, T., Jerzy, R., Kronheim, S., March, C. J., Poindexter, K. and Srinivasan S. (1993) “Identification of Regions in Interleukin-1 Important for Activity”. J. Biol. Chem. 268, 22105-22111.
31) Srinivasan, S., March, C. J. and Sudarsanam, S. (1993) “An Automated Method for Modeling Proteins on known Templates using Distance Geometry”. Protein Sciences, 2, 277-289.
32) Sudarsanam, S., Virca, G. D., March, C. J. and Srinivasan, S. (1992) “An Approach to Computer-Aided Inhibitor Design: Application to Cathepsin-L”. J. Computer Aided Molecular Design, 6, 223-233.
33) Curtis, B., Presnell, S. R., Srinivasan, S., Sassenfeld, H., Klinke, R., Jeffery, E., Cosman, D., March, C. J. and Cohen, F. (1991) “Experimental and Theoretical Studies of the Three-Dimensional Structure of Human Interleukin-4”. Proteins: Structure, Function and Genetics 11, 111-119.
34) Subhashini Srinivasan, Mihir Rayshowdhury, Masayuki Shibata, Robert Rein (1987), “Multistep modeling of protein structure: Application towards refinement of tyr-tRNAsynthetase”, International Journal of Quantum Chemistry”, International Journal of Quantum Chemistry, volume 32, Issue Supplement 14, pages 281–288
35) Srinivasan, S.,Raghunathan, G.; Shibata, M.; Rein, R., (1986) “Multistep modeling (MSM) of biomolecular structure application to the A-G mispair in the B-DNA environment”, International journal of quantum chemistry (QBS), Volume 12; 217-27
36) Srinivasan S., Masayuki Shibata,Robert Rein (1986), “Multistep modeling of protein structure: Application to bungarotoxi”, International Journal of Quantum Chemistry”, volume 30, Issue Supplement S13, pages 167–174
37) S. Srinivasan and K. Sundaram, (1983)“Molecular structure by the constrained damped least-squares (CDLS) method”, Biopolymers, Volume 22, Issue 5, pages 1373–1381
- Video Lectures/PPT slides
- Basic Bioinformatics (2nd Semester)
- Dynamic Programming Algorithms
- Hidden Markov Model
- Multiple Sequence Alignment
- Data Analysis Theory (3rd Semester)
- Genome Assembly
- RNA analysis
- Gene prediction
- Signal Transduction
- Data Analysis Practical (3rd Semester)
- Genome assembly
- RNA-seq analysis
- SNP detection and annotation
- Gene prediction
- Other NGS applications
- Basic Bioinformatics (2nd Semester)
- Material from NGS Workshop