Transcript-level gene regulation | Circadian biology | Alternative splicing
I am a bioinformatician and molecular biologist studying transcript-level gene regulation. My work focuses on circadian biology, alternative splicing, and isoform dynamics, using RNA-seq, computational genomics, and integrative analysis to uncover regulatory mechanisms that are not visible at the gene level.
Developed a transcript-resolved circadian RNA-seq workflow in adipocytes using SortMeRNA, STAR, and RSEM, followed by LIMBR batch correction of TPM values. Transcripts were filtered to average CPM > 10 and restricted to protein-coding isoforms from protein-coding genes to identify rhythmic transcripts with ECHO.
RNA-seq reads were processed with SortMeRNA, aligned to the mouse genome with STAR, and quantified at the transcript level using RSEM with reverse-stranded settings. TPM values were batch-corrected with LIMBR, filtered to protein-coding transcripts with average CPM > 10, and analyzed with ECHO to identify rhythmic transcripts.
Integrated rhythmic chromatin accessibility data with transcription factor motif analysis to predict circadian TF binding near rhythmic ATAC-seq peaks. motifmatchr was used to identify enriched motifs in rhythmic adipocyte chromatin and nominate candidate regulators of circadian transcriptional programs.
Extended transcript-level circadian analysis to alternative splicing and isoform usage to define how temporal regulation shapes RNA processing. This work focuses on identifying rhythmic splicing events, isoform-specific dynamics, and downstream regulatory mechanisms involving RNA-binding proteins.