FUNCTIONAL GENOMICS – CUBI2548

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Dr. Polaki Suman

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Course Information

Course Code Course Name Credit Type
CUBI2548 FUNCTIONAL GENOMICS 2 + 1 + 1

Course Overview:

             This course provides a comprehensive exploration of functional genomics, focusing on theoretical principles and practical applications. Students will gain insights into computational approaches, experimental methodologies, and data analysis techniques essential for understanding gene function within a genome.

Prerequisites:

  • Basic knowledge of genetics and molecular biology.
  • Introductory programming skills (preferably in Python).
  • Understanding of bioinformatics concepts.

Course Objectives:

  1. Gain a comprehensive understanding of functional genomics, including theoretical principles and practical applications. (L2)
  2. Acquire insights into computational approaches, experimental methodologies, and data analysis techniques essential for understanding gene function within a genome. (L3)

Course Outcomes:

  1. Demonstrate a basic knowledge of genetics and molecular biology. (L2)
  2. Utilize introductory programming skills in bioinformatics. (L3)
  3. Apply bioinformatics concepts to functional genomics. (L3)

CO–PO Mapping:

CO \ PO PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12
CO1 3 2 2 - - - - - - - - -
CO2 3 3 2 2 2 2 - - - - - -
CO3 3 3 2 2 2 2 3 2 2 - - -

Theory Syllabus – Functional Genomics

Module I: Introduction to Functional Genomics

  • Definition and scope of functional genomics.
  • Historical context and relationship with genomics and molecular biology.
  • Bioinformatics Tools for Functional Genomics:
    • Overview of bioinformatics applications in genomics.
    • Utilizing databases and resources for functional genomics.
    • Using bioinformatics tools like BLAST, NCBI, and UCSC Genome Browser.

 

Module II: High-Throughput Sequencing Technologies

  • Next-generation sequencing (NGS) platforms and technologies.
  • Data generation, quality control, and pre-processing.
  • Case studies illustrating functional genomics applications using NGS data.
  • Transcriptomics and Gene Expression Analysis:
    • Fundamentals of transcriptomics.
    • RNA-Seq analysis: experimental design, data processing, differential expression.
    • Interpreting gene expression data in a functional context.

 

Module III: Proteomics and Functional Genomics Approaches

  • Introduction to proteomics and functional proteomics.
  • Proteomics Techniques:
    • Mass spectrometry and other proteomic techniques.
    • Analyzing protein-protein interactions and functional annotation.
  • Functional Genomics Approaches:
    • CRISPR-Cas9 and genome editing techniques.
    • siRNA and shRNA methodologies.
    • Designing and conducting functional screens.
  • Integration and Systems Biology:
    • Integrating multi-omics data for a holistic understanding.
    • Systems biology approaches to dissecting gene function.
    • Network analysis and pathway enrichment methods.

Practical Syllabus – Functional Genomics

Module I: Bioinformatics Hands-on Session

  • Guided exercises on bioinformatics tools and databases.
  • Troubleshooting common issues in data retrieval and analysis.

 

Module II: NGS Data Analysis Workshop

  • Practical sessions on handling and analyzing NGS data.
  • Differential expression analysis using popular tools.

 

Module III: Functional Genomics Techniques Lab

  • Hands-on experience with CRISPR-Cas9 genome editing.
  • Implementation of siRNA and shRNA methodologies.
  • Conducting and analyzing functional screens.

Projects – Functional Genomics

  1. Hands-on project work applying functional genomics techniques: Design and execute a functional genomics experiment.
  2. Integrating multi-omics data for a systems biology project: Combine data from genomics, transcriptomics, and proteomics to gain insights into a biological system.
  3. Network analysis and pathway enrichment: Perform network analysis and pathway enrichment to identify key regulators and pathways in a dataset.

Theory Session Plan – Functional Genomics (40 Hours)

Session No. Module Topic Sub-Topics
1 Module I Introduction to Functional Genomics Definition, Scope
2 Module I History & Evolution Relation with genomics & molecular biology
3 Module I Central Dogma Refresher DNA–RNA–Protein concepts
4 Module I Bioinformatics Tools Overview Genomics applications
5 Module I Databases for Functional Genomics NCBI, Ensembl, UCSC
6 Module I BLAST & Sequence Retrieval Types, Scoring, Use cases
7 Module I Genome Browsers UCSC Browser deep dive
8 Module I Annotation & Feature Interpretation Genes, CDS, Promoters
9 Module I Comparative Genomics Basics Orthologs, Paralogs
10 Module I Genomic Data Formats FASTA, GFF, BED, VCF
11 Module II Introduction to NGS Platforms: Illumina, Nanopore, PacBio
12 Module II NGS Workflow Library prep, Sequencing chemistry
13 Module II Quality Control FastQC, Phred scores
14 Module II Data Preprocessing Trimming, Filtering, Adaptor removal
15 Module II Alignment Algorithms BWA, HISAT2, STAR
16 Module II Assembly Concepts Reference vs De Novo assembly
17 Module II NGS Case Studies Agriculture & Disease genomics
18 Module II Introduction to Transcriptomics Gene expression basics
19 Module II RNA-Seq Experimental Design Controls, Replicates, Biases
20 Module II RNA-Seq Data Processing Alignment, Counting Reads
21 Module II Differential Gene Expression DESeq2, EdgeR
22 Module II Interpreting DEGs Biological significance
23 Module II Pathway Analysis GO, KEGG, Reactome
24 Module II Data Visualization Heatmaps, PCA, Volcano
25 Module II Transcriptome Case Study Interpreting real datasets
26 Module III Introduction to Proteomics Concepts, Types, Applications
27 Module III Mass Spectrometry Principles, Workflow
28 Module III Protein Identification Mascot, Sequest, MS Databases
29 Module III Protein-Protein Interactions STRING, BioGRID
30 Module III CRISPR-Cas9 Mechanism, Design, Applications
31 Module III Genome Editing Off-target effects, Validation
32 Module III siRNA & shRNA Knockdown strategies
33 Module III Functional Screens Guide Libraries, Hit Discovery
34 Module III Multi-Omics Integration Genomics + Transcriptomics + Proteomics
35 Module III Systems Biology Network modelling, Dynamic systems
36 Module III Pathway Enrichment GSEA, DAVID Analysis
37 Module III Signal Transduction Key regulators, Pathway cascades
38 Module III Disease Genomics Cancer, Neurogenomics
39 Module III Multiomics Case Study Interpretation of real datasets
40 Module III Revision & Integration Final summary + Q&A

Practical Session Plan – Functional Genomics

Practical No. Module Title / Experiment Activities / Tasks
P1 Module I Bioinformatics Hands-on Tool usage, Database searching
P2 Module I Data Retrieval Troubleshooting Handling errors, fixing missing fields
P3 Module II NGS Data Handling FASTQ files, Quality checks
P4 Module II Differential Expression DESeq2 / EdgeR workflow
P5 Module III CRISPR-Cas9 Editing Design, Target selection, Editing
P6 Module III siRNA / shRNA Activity Gene silencing hands-on
P7 Module III Functional Screens Guide libraries, Hit identification

Project Session Plan – Functional Genomics

Project No. Project Title Description
1 Functional Genomics Experiment Design & conduct a functional genomics experiment using real datasets.
2 Systems Biology Integration Integrate genomics, transcriptomics, and proteomics for systems-level insights.
3 Network & Pathway Analysis Perform network analysis and enrichment to identify key regulators.

References

  1. Przybyla, L., Gilbert, L.A. A new era in functional genomics screens.
    Nature Reviews Genetics 23, 89–103 (2022). https://doi.org/10.1038/s41576-021-00409-w
  2. Michael Mannstadt, Marc N. Wein, Chapter 6 – Functional Genomics. In: Rajesh V. Thakker, Michael P. Whyte, John A. Eisman, Takashi Igarashi (Eds.), Genetics of Bone Biology and Skeletal Disease (Second Edition), Academic Press, 2018, pp. 77–88. https://doi.org/10.1016/B978-0-12-804182-6.00006-X
  3. Bunnik EM, Le Roch KG. An Introduction to Functional Genomics and Systems Biology. Advances in Wound Care. 2013 Nov; 2(9): 490–498. doi: 10.1089/wound.2012.0379. PMID: 24527360; PMCID: PMC3816999.
  4. Konopka, G., Bhaduri, A. Functional genomics and systems biology in human neuroscience. Nature 623, 274–282 (2023). https://doi.org/10.1038/s41586-023-06686-1

📚 Online Resource – Functional Genomics


➤ Open Functional Genomics Resource

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