Multi-omics Approach in Biology

(previously called "Proteomics in practice")

BC207

Course link and additional details can be found here.

Important: Register for the course here.

Course Level: 200


Credits: 2:0


Semester: January

 

Instructors: Kartik Sunagar (CES) and Utpal Tatu (Biochemistry)


Target students: PhD, Int-PhD, MSc and UG

Timing:

 

Monday: 10 to 11 AM

 

Friday: 10 to 11 AM

Course code: BC207


Proposed course structure
Historically, data collection, particularly at the molecular level, has presented the major bottleneck for the advancement of science. For example, in the early years of DNA sequencing technologies, human genome sequencing incurred expenses in billion US dollars and took more than a decade to complete. In contrast, in the modern era of ‘omics’ technologies, sequencing of a human genome costs less than a thousand dollars and a single day for the completion of sequencing to assembly. The advent of high-throughput technologies has, similarly, revolutionized numerous fields of biology. The ‘big data’ generated by these approaches offers various opportunities and challenges alike.


The aim of the course is to provide an in-depth introduction to “omics” technologies (Proteomics, Transcriptomics, Genomics, and Metabolomics), and how they can be implemented for understanding interesting aspects in various fields of biology, including genetics, molecular biology, ecology, evolutionary biology and biomedical research. This course will consist of lectures, discussions and hands-on bioinformatics and experimental practical sessions. Practical sessions will introduce students to various aspects of data acquisition, processing, and analyses, while theory classes will provide in-depth knowledge of principles and state-of-the-art practices in ‘omics’ approaches. At the end of the course, a final examination (a written/online test) will be conducted to evaluate student performances.

Syllabus


Part 1.
Transcriptomics: evolution of sequencing technologies; de novo assembly to study non-model organisms; genome or reference-based assembly to study model organisms; quantification of the gene, transcript and isoform expression; gene and transcript annotation; single-cell transcriptomics; the entire RNA-seq workflow: sample preparation to data analysis.


Genomics: introduction to genomics and genome sequencing technologies; annotating genomes; detecting common genetic variation; comparative genomics and organismal adaptations; single nucleotide polymorphisms (SNPs) and complex diseases; cancer genomics.
 

Practicals: Basic NGS practices

  • Basic computational skills in Unix/Linux OS

  • NGS data acquisition, processing raw data, quality assessment, quality filtering and analysis.

  • Only if time permits (this part further requires physical access to computer labs and, hence, may not be possible during the pandemic/online teaching mode): construction of de novo assembly, assembly quality statistics, transcript annotation, and transcript quantification.
     

Part 2.
Introduction to Proteomics and Metabolomics: Definition, need for these approaches, challenges and potential applications.


Experimental approaches in Proteomics: Methods of protein resolution from complex mixtures: Cell lysates, Serum proteins using 2D GE. Concept of Multidimensional chromatography. Biomarker identification from Cells, Tissue as well as Biological fluids. Tear, Sweat, Urine and Serum proteomics with case studies.


Mass spectrometry: Principles and applications. Protein identification by Mass spectrometry: Peptide Mass Fingerprinting, MSMS fragmentation and sequencing. Study of post-translational modifications by 2D GE and MS. Glycoprotein analysis by MS. metabolome analysis.
Databases and their uses: software for analysis.

 

Practicals: 2D-Gel electrophoresis and mass spectrometry 

 

Reading material

  • Bioinformatics and Functional Genomics, Pevsner (3rd edition)

  • Practical Computing for Biologists, Haddock and Dunn

  • Primrose SB, Twyman RM (2006). Principles of gene manipulation and genomics. Blackwell Publishing

  • Simpson R (2002). Proteins and proteomics: A laboratory manual. Cold Spring Harbor Laboratory Press.

Frequently Asked Questions

  • Can UG students attend this course?

       Yes

  • Which NGS software/tools will be demonstrated/familiarised?

       Basic NGS tools (FASTQc, Trimmomatic, Trinity, and, if time permits, others)

  • Where can I find the TEAMS link to the class?

      A summary of the aforementioned information and the link to the course can be found here.

  • I am a student at IISc. Can I audit the course?

You can audit the course but you will have to attend all classes, submit assignments and take the exams.

  • Do I need to have prior experience in programming or scripting?

While prior experience in programming, scripting and/or using Linux operating systems can be advantageous, this is not mandatory for the course.​