Research Projects

My doctoral research focused on the Vandiemenella viatica species complex, a powerful model for studying neo-sex chromosome evolution. This system exhibits multiple independent X-chromosome–autosome fusion events, providing a unique opportunity to investigate how such rearrangements arise and how they influence genome regulation, particularly dosage compensation mechanisms.

I leveraged PacBio long-read sequencing alongside complementary short-read data to generate high-quality genome assemblies across multiple chromosomal races. My work spanned genome assembly, variant calling, and differential gene expression analyses across several tissues, enabling an integrated view of structural evolution and its functional consequences.

Throughout my research, I designed and implemented robust, reproducible data-analysis pipelines that supported large-scale comparative genomics and transcriptomics. This work resulted in multiple publications in peer-reviewed journals. All publications are available on the Publications page, and the full thesis can be accessed via the homepage.

I worked with large-scale single-cell RNA sequencing datasets from human and mouse cortical tissue to investigate cell-type–specific gene expression patterns in the brain. By integrating and comparing data across species, I identified key transcriptional signatures relevant to cortical organization and function.

This work contributed to a deeper understanding of gene expression dynamics in the cortex and provided insights valuable for neurological and neurodevelopmental research. The analyses emphasized data quality, biological interpretation, and cross-species relevance, strengthening the translational potential of single-cell transcriptomics.

I analysed repeat elements and cyanobacterial content in Amaranthus hypochondriacus using integrated genomic and metagenomic datasets. Metagenomic data were specifically leveraged to characterize the microbial content of soils from different geographic regions where the plant was cultivated, enabling insights into region-specific metagenomic composition and its potential influence on genome assembly and annotation.

Building on an existing chromosome-level reference, I generated an improved Amaranthus hypochondriacus genome through multiple rounds of iterative assembly refinement. This work involved the development of robust, fully reproducible analysis pipelines spanning repeat analysis, metagenomic profiling, and assembly improvement. These efforts, along with additional supporting analyses, culminated in a peer-reviewed publication, which is available on the Publications page.

I generated and refined high-quality genome assemblies for multiple strains of Anopheles stephensi, a key malaria vector species. I was primarily responsible for assembling strain-specific genomes using diverse genomic markers, followed by manual curation and chromosome-level scaffolding to accurately stitch and orient chromosomal sequences.

This work resulted in two peer-reviewed publications, with detailed methodology described in the corresponding manuscripts. Additional insights and intermediate analyses from this project were also presented in multiple scientific posters, all of which are available on the Publications and Posters pages.

Seven strains of Dictyostelium giganteum were sequenced and assembled using multiple genome assemblers, including Velvet and SPAdes. After comparative evaluation, SPAdes produced the highest-quality assemblies and was selected for downstream analyses. Each of the seven strain assemblies was subsequently refined through an iterative improvement process to enhance scaffold length and overall assembly quality.

The primary goal of the project was to identify genes involved in self and non-self recognition within and between Dictyostelium strains. To achieve this, improved assemblies were used for homology-based analyses against well-annotated reference species, including Dictyostelium discoideum and Dictyostelium purpureum. Gene sequences of interest from these reference genomes were compared against the seven D. giganteum strains to identify conserved and strain-specific candidates associated with social recognition mechanisms.

I performed comparative genomics on Saccharomyces species using three genomic sequences for trio-based assembly and haplotype phasing. The analysis leveraged long- and short-read sequencing data and employed state-of-the-art assemblers and phasing tools such as SPAdes, Canu, and HapCUT2 to generate high-quality, phased genome assemblies. This approach enabled accurate resolution of haplotypes, improved structural variant detection, and provided insights into genome organization and inheritance patterns in yeast.

I contributed to the study by carrying out the library preparation of Exome-seq and sequencing data processing and variant calling workflow. My work involved handling raw high-throughput sequencing data, performing quality control, read alignment, and variant detection using standard bioinformatics pipelines and best-practice tools. The resulting variant datasets formed a core input for downstream analyses and interpretation in the study. The publication from this study can be found on the Publications page.

During my tenure as a Project Assistant at Shivaprasad Lab in National Center for Biological Sciences (NCBS), I spearheaded a comprehensive transcriptomic study focused on the genetic determinants of phenotypic diversity in Vitis vinifera. By leveraging high-throughput bulk RNA-Seq datasets, I conducted rigorous differential expression analyses to map the complex regulatory networks governing fruit pigmentation. My work successfully identified key candidate genes and metabolic pathways associated with anthocyanin biosynthesis, providing a statistically validated framework for understanding color variation in grapes. These insights not only advanced our fundamental knowledge of plant secondary metabolism but also established a reliable baseline for targeted experimental follow-up and precision breeding strategies.