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ABOUT ME

My research focuses on Human Genomics, Transcriptomics, Metagenomics, and DNA Barcoding. The main activities of my project work are listed below:


Human Genomics – Genetic Variation


Project 1: Improve the diagnostic rate for undiagnosed rare disorders in pediatric cases by utilizing the Emedgene artificial intelligence approach within cohorts.
In the French et al., 2022 study, 176 (34%) patients received molecular diagnoses out of 521 children suspected of having an undiagnosed monogenic disease. Due to the continuous updates in the annotation databases and new machine learning approaches, reanalysis of prior WGS data of the remaining 345 undiagnosed patients may improve the diagnostic rate. The availability of updated databases and the Emedgene tool provides the opportunity to diagnose patients with rare disorders by reanalyzing their WGS data.

 

Project 2: The identification of rare genetic variants in highly multiplex autistic families and extremely talented mathematicians. 
In this study, I analyzed the whole genome sequencing data (WGS) of 112 samples (92 autistic and 20 controls) from 21 multiplex autism families. By using a combination of both autistic traits and clinical diagnosis of autism, we identified rare variants in genes associated with autism and related neurodevelopmental conditions in multiple families. I developed an automated PDVarFilter (Phenotype and Diagnosis level Variant filtering) tool for this purpose. We identified a total of 37 variants encoding 35 genes using this approach. Fifteen of these genes have previously been linked to either autism or severe undiagnosed developmental disorders. Some examples of these genes are CHD7, ANKRD11, and SON which are robustly associated with both autism and severe developmental disorders. Two genes (SETD2 and MACF1) were identified in two separate families. Both genes are associated with diagnosis and high autistic traits (NAP and MAP) and are classified as Tier 1 genes. It is commonly known that individuals with autism also tend to have strong mathematical abilities. Therefore, I analyzed the WGS data of 61 extremely talented mathematicians. We prioritized a total of 18 SNP variants in 14 candidate genes. The frequencies of these variants were further checked in 774 exome samples (83 math with autism, 451 math without autism, and 240 autism without math). The manuscript on this work is currently in preparation.

 

Project 3: Whole Exome Sequencing (WES) data analysis of Severe Mental Illnesses (SMI) patients and SeSAME syndrome.
In this study, I conducted a whole-exome sequence (WES) analysis and data mining of 32 ill subjects and 31 healthy individuals. The ill subjects had a diagnosis of Bipolar Disorder (n=26), schizophrenia (n=4), schizoaffective disorder (n=1), or schizophrenia-like psychosis (n=1). This study has been published in the Psychiatry Clin Neurosci Journal. Three-step filtering process to select prioritized variants that included assessing deleteriousness by in-silico algorithms (SIFT and PolyPhen), variant sharing within families, absence in the familial controls, and rarity in the ExAC South Asian population controls. Finally, genes were examined with previous reports to identify genes associated with diverse neuropsychiatric syndromes, Mendelian inheritance, and neurobiology. Additionally, I analyzed the WES data of a SeSAME syndrome family, which included four patients and two unaffected parents. Through this analysis, we identified a novel rare damaging missense mutation in KCNJ10 in the patients (Nadella et al., 2019).

 

Project 4: GenomicQC tool: Whole Genome Sequencing (WGS) based quality assessment of iPSC cell lines.
I am involved in the quality assessment of iPSC cell lines using WGS and creating a report specific to each sample. I developed an integrated WGS analysis pipeline, called GenomicQC, which includes various software for raw reads, alignment, SNP/INDEL QC, mitochondria, gene-specific coverage, HLA, STR, Dendrogram, SV analysis, and databases. These are integrated to produce a comprehensive report of the genomic profile of a cell line. This work was published in Cell & Gene Therapy Insights Journal, with me as the first author.

 

Bacterial genomics, DNA Barcoding metagenomics and Insect transcriptomics
In this project, I analyzed the whole transcriptome (RNA-Seq) data of agriculturally important insect pests and performed DNA barcoding using Bayesian inference and maximum likelihood methods. Additionally, I analyzed metagenomic NGS data from the active biomass of a Common Effluent Treatment Plant (CETP), where I performed taxonomic classification to identify the microbial community structure and function. The results of the study revealed the presence of different microbial communities, including Proteobacteria, Bacteroidetes, and Firmicutes, which were involved in various metabolic pathways such as carbohydrate metabolism, amino acid metabolism, and xenobiotics biodegradation. I was involved in two research articles published in the high impact factor Bioresource Technology Journal on this work, and a third research article published in the PLOS ONE Journal where I was the third author.

During my PhD thesis, I developed two software applications, DNA BarID and matK-QR Classifier, for identifying bacterial and plant species using Perl scripts. Specifically, I identified distinguishing patterns for bacteria (specifically Bacilli, Bacillales, Bacillaceae, and Bacillus taxa in 16S rRNA sequences) and plants, using composite vectors and multiple sequence alignment. My work on this project has been published in the Journal of Computational Biology, as well as in the BMC BioDataMining Journals as a first author.

RESEARCH INTERESTS

Human Genomics - Genetic variation (WGS/WES)

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Transcritpomics

Microbial Genomics 

Metagenomics

EDUCATION

  • Ph.D. in Bioinformatics (Faculty of Science), on thesis titled “DNA Barcoding: Pattern-Based Approach for Creating a Gene Specific Signature” under guidance of Dr. Hemant Purohit, CSIR-NEERI, Nagpur, India from Swami Ramanand Teerth Marathwada University (SRTM), Nanded, Maharashtra, India (Registration: 10-05-2011, Thesis Submitted: 26-06-2014, Awarded: 17-04-2015).

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  • M.Sc. in Bioinformatics, Swami Ramanand Teerth Marathwada University (SRTM), Nanded, Maharashtra, India (July 2009).

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  • B.Sc. in Microbiology, Chemistry, Botany, Dr Babasaheb Ambedkar Marathwada University, Aurangabad, MH, India (December 2006).

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  • H.S.C. (English, Pali, Psychology, Physics, Chemistry, Biology), MSBSHSE Board, Pune (June 2003).

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  • S.S.C. (Marathi, Hindi, English, Maths, Science, Social Sciences), MSBSHSE Board, Pune (June 2001).

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