Exploring genetic variations within Gamma-Activated Sequence (GAS) motifs in the  Interferon/JAK/STAT signaling pathway to understand the genetics of autoimmune  diseases

Shreeti Chhatrala

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.