Unraveling the Genomic Architecture of Gene Expression Regulation

Gene expression is a tightly controlled process crucial for cellular function and organismal development. This project will investigate the genomic regulators, specifically focusing on Transcription Factors (TFs) which regulate gene (target) expression. Using publicly available bulk RNA-Seq data from diverse tissues or conditions, the student will learn to integrate genomic information (e.g., DNA sequence and TF-target gene interaction data if available) with gene expression profiles to identify and characterize potential Regulators.

Expected Outcomes: The student will contribute to identifying potential transcription factors that play a role in regulating gene expression in the studied system. This project will provide valuable insights into the complex interplay between the genome and the transcriptome. The student will gain a strong foundation in analyzing large-scale genomic and transcriptomic datasets.

Name of research group, project, or lab
Computational Systems Biology Lab
Website
https://sites.google.com/view/csblab/home
Why join this research group or lab?
The Computational Systems Biology Lab (CSBLab) works on the intersection of biology and computation, with a focus on systems responses of diseases in plants and animal model systems. We utilize state-of-the-art systems biology frameworks to study transcriptomics changes at different scales (Bulk RNA-Seq, single-cell RNA-Seq, and spatial transcriptomics) and multi-omics profiles to delineate the factors underlying cellular functions.

We are looking for enthusiastic undergraduate students with interest to learn the necessary biological data science skills which will prepare them for upcoming research or educational challenges. Students will gain hands-on experience in processing and interpreting complex genomic datasets. The research experience emphasizes in the development of essential bioinformatics skills and the use of cutting-edge software tools to explore biological data. Throughout the research, students will apply their knowledge to real-world datasets, culminating in module-based projects that showcase their analytical and presentation skills. This research experience aims to equip students with the necessary tools and knowledge to tackle contemporary research questions in genomics, fostering critical thinking and data interpretation skills.

Note: If student want to continue their research in the CSBLab after Fall, they can do so. 

Logistics Information:
Project categories
Applied and Computational Mathematics and Statistics
Biological Sciences
Chemistry and Biochemistry
Student ranks applicable
Sophomore
Junior
Senior
Graduate Student
Student qualifications
  • Strong interest in genomics, molecular biology, and computational analysis.
  • Basic understanding of genetics and gene regulation.
  • Familiarity with command-line interfaces and basic programming concepts (e.g., Python or R) is a plus but not required. We will provide training.
  • Enthusiasm for learning new bioinformatic tools and techniques.
  • Should have access to a laptop and willing to work on cloud through ND CRC. 
Hours per week
1 credit / 3-6 hours
2 credits / 6-12 hours
Summer - Full Time
Summer - Part Time
Compensation
Research for Credit
Unpaid - Volunteer
Number of openings
1
Techniques learned

The student will gain hands-on experience in:

  • Data Acquisition and Processing: Downloading and quality control of bulk RNA-Seq data (FASTQ files) and corresponding genomic annotations (e.g., gene models, regulatory element databases).
  • Alignment and Quantification: Using command-line tools and bioinformatic pipelines to align RNA-Seq reads to the reference genome and quantify gene expression levels.
  • Differential Gene Expression Analysis: Applying statistical methods to identify genes that are significantly up- or down-regulated across different conditions.
  • Genomic Feature Annotation: Utilizing bioinformatic tools to map differentially expressed genes to TF target databases.
  • Motif Enrichment Analysis: Employing computational approaches to identify over-represented DNA sequence motifs within the regulatory regions of co-expressed genes, suggesting potential transcription factor binding sites.
  • Visualization and Interpretation: Generating informative plots and figures to present findings and interpret the relationship between genomic architecture and gene expression.
Contact Information:
Mentor
Bharat Mishra
bmishra2@nd.edu
Principal Investigator
Name of project director or principal investigator
Bharat Mishra
Email address of project director or principal investigator
bmishra2@nd.edu
1 sp. | 10 appl.
Hours per week
1 credit / 3-6 hours (+3)
1 credit / 3-6 hours2 credits / 6-12 hoursSummer - Full TimeSummer - Part Time
Project categories
Biological Sciences (+2)
Applied and Computational Mathematics and StatisticsBiological SciencesChemistry and Biochemistry