Ashwini Sunkavalli
Tufts University School of Medicine
Boston,USA
15
years of professional experience
Cell and molecular biologist with extensive experience integrating wet-lab research and computational analysis to investigate complex biological systems. Experienced in experimental design, biological data analysis, and connecting molecular and phenotypic findings across bacterial, viral, and mammalian models.
Work History
Graduate Researcher
9 Years- Designed and executed multifactor, time-resolved RNA-seq experiments to investigate transcriptional regulation and stress adaptation in Neisseria gonorrhoeae under iron-replete and iron-depleted conditions.
- Analyzed transcriptomic datasets using differential expression, time-course analysis, and operon-level interpretation to characterize dynamic bacterial stress responses.
- Developed and applied gene regulatory network and module-level analyses to identify candidate regulators associated with iron homeostasis, oxidative stress, and metabolic adaptation.
- Integrated transcriptomic findings with phenotypic assays, including growth, viability, oxidative stress tolerance, and epithelial cell invasion experiments, to connect molecular regulation with bacterial behavior.
- Performed motif discovery and computational regulatory analysis to prioritize putative transcriptional regulators and biologically relevant targets.
- Generated publication-style visualizations and analytical summaries to communicate complex multi-layer datasets and support biological interpretation.
Research Associate II
2 Years- Investigated Influenza A virus replication, RNA biology, and viral fitness under antiviral pressure using molecular and cell-based assays.
- Performed viral mutagenesis, plaque assays, strand-specific quantitative PCR, and replication kinetics analyses to assess viral behavior across experimental conditions.
- Designed primers and quantitative assays to distinguish viral RNA species and support detailed analysis of infection dynamics.
- Contributed to experimental design, data interpretation, and project execution in virology and RNA biology studies.
Lead Research Technician - Cancer Genomics
4 Years- Supported large-scale whole-exome and whole-genome sequencing studies in cancer genomics through high-throughput sample processing and sequencing workflows.
- Managed next-generation sequencing library preparation, normalization, and quality control to maintain consistency across high-volume projects.
- Contributed to genomics studies published in Nature Genetics, JAMA Oncology, and The Lancet Oncology.
- Trained staff and collaborators on sequencing workflows, laboratory standards, and quality control practices.
Education
Master of Science (MS) - Genetics, Molecular & Cell Biology
- Thesis: Role of the Transcriptional Regulator MpeR in Neisseria gonorrhoeae Adaptation to Iron Limitation and Oxidative Stress
- Completed PhD-level dissertation research and successfully passed the doctoral thesis defense
Master of Science (MS) - Biotechnology
- Thesis: Study of RANTES and Klf13 in Sle3 mice
Bachelor of Science - Biotechnology
Skills
Programming / Quantitative Analysis: R programming for transcriptomic
statistical
and quantitative biological data analysis; Python for data visualization; reproducible computational workflows; high-performance computing (HPC) environments
Bioinformatics / Computational Biology: RNA-seq preprocessing
quality control
and differential expression analysis; DESeq2
edgeR
limma; FastQC
fastp
Rockhopper; time-course transcriptomic analysis; custom integrative analysis of gene expression and phenotypic datasets; gene regulatory network inference and module-level analysis; network topology analysis using igraph and Gephi; Bayesian network inference using bnlearn; motif discovery using MEME Suite and Tomtom; operon prediction and operon-level transcriptomic analysis; public biological dataset integration and analysis
Data Visualization / Scientific Communication: Biological data visualization in R and Python; scientific figure generation and interpretation; integration of transcriptomic
network
and phenotypic data for biological insight
Laboratory / Experimental Biology: DNA/RNA isolation and quality control; strand-specific RNA sequencing library preparation; PCR
primer design
and qPCR-based quantification; bacterial growth
viability
and colony assays; mammalian cell culture and viral infection assays; epithelial cell adherence and invasion assays; multifactor experimental design and phenotype-linked analysis
Timeline
Graduate Researcher
Tufts University School of Medicine
01.2016 - 01.2025Read More
Research Associate II
University of Massachusetts Medical School
01.2014 - 01.2016Read More
Lead Research Technician - Cancer Genomics
Dana-Farber Cancer Institute
01.2010 - 01.2014Read More
SRM University
Bachelor of Science from Biotechnology
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Tufts University School of Medicine
Master of Science (MS) from Genetics, Molecular & Cell Biology
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University of Texas At Dallas
Master of Science (MS) from Biotechnology
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SELECTED PUBLICATIONS
- Wang A, Fairhurst AM, Liu K, Wakeland B, Barnes S, Malladi VS, Viswanathan K, Arana C, Dozmorov I, Singhar A, Du Y, Imam M, Moses A, Chen C, Sunkavalli A, et al. Communications Biology. 2024.
- Sunkavalli A, McClure R, Genco CA. Molecular regulatory mechanisms drive emergent pathogenetic properties of Neisseria gonorrhoeae. Microorganisms. 2022.
- McClure RS, Sunkavalli A, Balzano PM, Massari P, Cho C, Nauseef WM, Apicella MA, Genco CA. Global network analysis of Neisseria gonorrhoeae identifies coordination between pathways, processes, and regulators expressed during human infection. mSystems. 2020.
- Campbell JD, Lathan C, Sholl L, Ducar M, Vega M, Sunkavalli A, et al. JAMA Oncology. 2017.
- Pastor-Garcia A, Gonzalez-Barca E, Colomo L, Domingo-Domenech E, Sunkavalli A, et al. The Lancet Oncology. 2015.
- Brastianos PK, Taylor-Weiner A, Manley PE, Jones RT, Dias-Santagata D, Thorner AR, Sunkavalli A, et al. Nature Genetics. 2014.