bakshisayan Goto Github PK
Name: Sayan Bakshi
Type: User
Company: University of Alabama at Birmingham
Bio: Pursuing Ph.D. in Biomedical Sciences
Name: Sayan Bakshi
Type: User
Company: University of Alabama at Birmingham
Bio: Pursuing Ph.D. in Biomedical Sciences
Data and Methods Supplement: "Dysregulation of the Mitochondrial Proteome Occurs in Mice Lacking Adiponectin Receptor 1"
A toy programming language written in Typescript
Pancreatic β-cells undergo profound hyperplasia during pregnancy to maintain maternal euglycemia. Failure to reprogram β-cells into a more replicative state has been found to underlie susceptibility to gestational diabetes mellitus (GDM). We recently identified a requirement for prolactin receptor (PRLR) signaling in the metabolic adaptations to pregnancy, where mice lacking β-cell PRLR (βPRLRKO) exhibit a metabolic phenotype consistent with GDM. However, the underlying transcriptional program that is responsible for the PRLR-dependent metabolic adaptations during gestation remains incompletely understood. To identify PRLR signaling gene regulatory networks and target genes within β-cells during pregnancy, we performed a transcriptomic analysis of pancreatic islets isolated from either βPRLRKO mice or littermate controls in late gestation. Gene set enrichment analysis identified Forkhead box protein M1 (Foxm1) and polycomb repressor complex 2 (PRC2) subunits, Suz12 and Ezh2, as novel candidate regulators of PRLR-dependent β-cell adaptation. GO-term pathway enrichment revealed both established and novel PRLR signaling target genes that together describe a state of increased cellular metabolism and/or proliferation. In contrast to the requirement for β-cell PRLR signaling in maintaining euglycemia during pregnancy, PRLR target genes were not induced following high-fat-diet feeding. Altogether, the current study expands our understanding of which transcriptional regulators and networks mediate gene expression required for islet adaptation during pregnancy. The current work also supports the presence of pregnancy-specific adaptive mechanisms distinct from those activated by nutritional stress.
Circular visualization in R
The failing heart undergoes profound metabolic changes due to alterations in cardiac gene expression, reactivating glycolytic genes and suppressing oxidative metabolic genes. In this study, we discover that alterations in cardiac DNA methylation encode this fetal-like metabolic preference. We also identify epigenetic interference of NRF1 via hyper-methylation of its downstream promoter targets, further supporting a central role of DNA methylation in the metabolic reprogramming of heart failure.
This repository has teaching materials for a 2-day Introduction to RNA-sequencing data analysis workshop using the Orchestra Cluster.
A repository for setting up a RNAseq workflow
Notes and exercise attempts for "An Introduction to Statistical Learning"
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