Exploring genetic variations within Gamma-Activated Sequence (GAS) motifs in the Interferon/JAK/STAT signaling pathway to understand the genetics of autoimmune diseases
Mentor: Markus Hoffman, PhD student and Pre-Doctoral Fellow at NIH
Date/Time: August 22nd, 2023 at 1pm.
Abstract: Autoimmune diseases pose a significant threat to public health, impacting millions of lives worldwide. Autoimmune disorders happen when the body’s natural defense system can’t tell the difference between your own cells and foreign cells, causing the body to mistakenly attack normal cells. A lot of factors are responsible for the development of autoimmune diseases such as genetic factors, environmental factors and immune system factors.
Central to these diseases is the Interferon/JAK/STAT signaling pathway that plays an important role in the immune response. The Interferon/JAK/STAT pathway is activated by cytokines, particularly interferons, in response to viral infections and immune stimulation. Key components of the pathway include interferons, Janus kinases (JAKs), and signal transducer and activator of transcription (STAT) proteins. In this project, we are focusing on the STAT5 protein. STAT5 dimers bind to specific DNA sequences called Gamma Activated Sequence (GAS) motifs in gene promoters or enhancers. GAS motifs have the consensus sequence 5′-TTCNNNGAA-3′. Upon binding to GAS motifs, STAT5 acts as a transcription factor, regulating the expression of target genes. The goal of this project is to gain deeper insights into the genetic architecture of the Interferon/JAK/STAT signaling pathway, with a particular focus on Gamma-Activated Sequence (GAS) motifs. These motifs play a crucial role in modulating gene expression in response to extracellular signals (e.g., immune system activation). Our project will investigate the presence and impact of single nucleotide polymorphisms (SNPs) on GAS motifs and their potential consequences on the function of the immune system.
Comprehensive literature review was conducted to analyse the different motif detection tools available and identify those that might be helpful in the project. The dbSNP database and UCSC genome browser consists of all SNPs for the human genome. Direct data about the SNPs was taken from these websites and used as the input for the project. Using the human genome sequence and the SNP data, a pipeline was created in Python to identify GAS motifs in the sequence and also identify SNPs using the sliding window approach. The output was then visualized on a genome browser to visualize the SNPs where the GAS motif matches and can include mutations that might destroy the GAS motif thus inhibiting it’s function. Genes were identified that might have functional consequences on the immune system and the corresponding SNPs were reports for further experimental evaluation.
- Summer 2023