Congenital muscular dystrophies (CMD) and congenital myopathies (CM) are a group of rare genetically and clinically heterogeneous degenerative primary muscle disorders with onset at birth or during infancy. Due to vast heterogeneity, clinical examination and protein-based analyses often fail to identify the genetic causes of these diseases making it challenging for the clinician to make an
accurate diagnosis. My research therefore focuses on investigating the genomic signatures causal to CMD and CM in Indian patients. I analyse whole exome sequence data using variant calling and stringent variant filtration process to identify pathogenic mutations and achieve a genetic diagnosis.
I'm also interested in functionally characterizing the candidate variants in an in vivo zebrafish model and do a mechanistic evaluation in primary muscle cells using the efficient CRISPR-Cas genome editing tools.
Genome wide association studies (GWAS) are used to discover association of genetic variants with various complex diseases and traits. However, testing markers across the genome in an unbiased manner leads to loss of power for such studies. My research project deals with increasing the power of such genome wide studies by incorporating information from other sources. Knowledge from pathways, gene expression/eQTL studies and transcriptional regulation can be integrated with the information from GWAS to help in identifying variants that could be otherwise missed in an unbiased genome-wise search. My work emphasizes on building a pipeline for integrative statistical analysis of such multi-omics data. The pipeline will enable investigators to discover novel genetic variants and understand their mode of action, thus helping to elucidate the underlying genetic makeup of complex diseases.
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Human oral squamous cell carcinoma (OSCC) is the eighth most common cancer worldwide; and, the most prevalent cancer among men and fourth most common among women in India. Owing to the highly heterogeneous nature of oral carcinoma at both cellular and molecular levels, it is important to investigate the functions of altered pathways with respect to distinct cancer cell-types present wi thin the tumor as well as in its microenvironment. In the context of cell-cell interactions, NOTCH related signaling is intriguing because of its juxtacrine mode of action. Therefore, I am interested in studying the functional consequences of altered NOTCH related genes and its regulation within oral tumors. My focus is to examine the mechanisms of reciprocal interactions between diverse cell-types and its significance in oral cancer initiation and progression.
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Intratumor heterogeneity is among the greatest challenges in treatment of cancer. In spite of disruptive advances in sequencing technologies achieved over the last decade, high resolution comprehension of such heterogeneity has been beyond our reach until recently. Developments in high-throughput Single Cell RNA-Seq (SC-RNASEQ) may now enable us to dissect the diverse cellular populations o f tumors. In the future these technologies might inform the selection of targeted combination therapies and enrollment criteria for clinical trials. I am working on single cell RNA-Seq approaches to investigate the role of intratumour heterogeneity in tumour recurrence in Oral squamous cell carcinoma gingivo-buccal (OSCC-GB). My objective is to excavate the landscape of intratumor heterogeneity at single cell resolution and identify important clues on how cell type diversity relates to cancer recurrence.
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An individual is provided medication, whether vaccine or drug, without taking into account the genomic background of the individual; i.e., a one-size-fits-all approach is used. However, it is known that genetic differences strongly account for inter-individual variability in treatment response, leading to huge wastage of funds and resources. This economic burden can be drastically minimiz ed by genomic technologies. Very little is known in India about drug-response in relation to the genomic background of medication-recipient. The investigation of genetic backgrounds of recipients of medication can unfold key mechanisms associated with medication efficacy, which could be harnessed to design better medications for overcoming failure and poor response of current therapies.
Aim of the current study is to identify the genomic correlates of medication response to design a well represented panel of pharmacogenetic markers which will enable screening of individuals. These will help clinicians in selection of appropriate drug and genotype-specific dose. With plummeting cost of DNA sequencing technologies, genetic testing using such a panel will augment clinical decision making to meet personalized needs of each patient providing quality health care, while preventing adverse events and improve many lives.
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