Ribonucleotide enrichment features in human genome
Study of ribonucleotide embedment in human CD4+T cell type derived from
patient blood and lab grown stem cell line (hESC-H9) and embryonic
kidney cells (HEK293T), the latter with and without RNase H2 enzyme. In
this study we discovered single embedded ribonucleotides (rNMPs) are
enriched near CpG islands and are associated with gene expression and
methylation around Transcription Start Sites (TSSs). In addition, we see
a gene template vs non-template strand bias for RNase H2 KO that is not
present in wild-type RNase H2 cell associated with removal of rG on
non-template strand, possibly by Top1 enzyme.
Ribonucleotide features in Aicardi-Goutières syndrome (AGS) orthologous mutants
Two mutant orthologs
of human AGS, namely RNaseH2A-G37S and RNaseH2C-R69W were experimentally
created in yeast as rnh201-G42S and rnh203-K46W, respectively. The
RNaseH2A mutant results in strong reduction of enzymes activity thereby
leading to massive ribonucleotide increament in the nuclear genome with
increase seen on leading strand of Autonomous Replicating Sequences. The
RNase H2C mutant was found to show no significant increase in nuclear
genome, but we observed change in sites of ribonucleotide embedment
suggesting structural effect of enzyme leading to change in
specificity.
Associations of RNASEH2A gene in cancer datasets
Determining
Expression correlation of RNASEH2A with cancer proliferation and cell cycle markers in large cancer cell lines and tissue datasets. This project has been recently a part of paper published in MDPI’s Biology journal and received US National Science Foundation Conference Award for a poster presentation in RNA 2021 Conference
Web App to Determine Susceptibility of Multiple infections
IGen is an app to help the consumer be aware of their genetic tendency for susceptibility to multiple infections and be proactive with their health during the time of Global Pandemic. All they need is a DNA test sequencing Results from Companies like 23andMe. [ Glimpse of the Science behind it ]
Use of Methylation data to determine Survival Risks in HIV cohort from Yale’s Veterans Aging Cohort Study
Discovery of Differentially methylated regions in smokers vs non-smokers validated the finding from several other research groups. We were able to see variation in the methylation status based on Race. For prognosis prediction on this this dataset, we used Veterans Aging Cohort (VACS) Index. Use of support Vector Machines gave the best accuracy. Used of different and more lineant thresholding to extract more features and more information could lead to good AUCs for the methylated regions to be used as Biomarkers or predictors. More info..
More Projects
Genome Assembly and
Comparative Genomic Study on CDC’s foodborn disease Outbreaks
Differential
gene expression in lung cancer cell lines between wildtype and
mutant/variant p53
Exome
Analysis of Utah Resident with Northern and Western European
Ancestry