RNA-seq: What is the transcriptome and why study it?
Molecular biologists study a broad spectrum of topics relating to the molecular regulation of cell biology, from DNA and RNA, to protein expression and protein-protein interactions. A dominant theme in molecular biology is how variation in nucleic acids (genotype) affects the biology of organisms (phenotype). A second major theme is the study of gene expression and the resulting change(s) in observed transcriptomics features of a studied sample.
Next Generation Sequencing (NGS) is a key technology enabling an unprecedented level of precision, and efficacy in understanding genomic and transcriptomic regulation. A Next Generation sequencer creates a digital file representing sequenced DNA or RNA. This file contains information where nucleotides are represented by letters corresponding to their “bases”.
Next Generation Sequencing data analysis is often referred to as “RNA-seq”. The purpose of this analysis is to map the short reads from raw sequence files to the reference genome, and then study the abundance of RNA mapped to a particular region. The abundance can represent levels of gene or isoform expression, and can be compared between samples or groups of samples.
Transcriptomics 1: Course objectives and methodology
The goal of this course is to prepare a student for real-world applications of RNA-seq. We will review methods of both quantitative and qualitative analysis of RNA in a sample, how data is generated using Next Generation Sequencing, and use a sample project “Patient Derived Xenograft: Transcriptomic Biomarkers of Breast Cancer” to practice generating a table of expression from raw FASTq files. We will also learn to preview and visualize the resulting data using Principal Component Analysis (PCA). To perform the example analysis detailed in the course, students will need access to the T-BioInfo platform. Account information can be requested by filling out the form on server.t-bio.info site. Microsoft Excel is also used for plotting results.
We would like to thank the following people who helped to prepare the projects, develop the tools, and compile the the learning resources for this course:
Dr. Leonid Brodsky and the Tauber Bioinformatics Research Center, Dr. Claudia Copeland, Dr. Ron Ferrucci, Julia Panov, Jaclyn Williams and Jo Calihan.
- Lectures 9
- Quizzes 2
- Duration 6 hours
- Skill level All levels
- Language English
- Students 2215
- Certificate Yes
- Assessments Yes
1. Biology of RNA and Next Generation Sequencing
Learn about the process of gene expression, alternative splicing and assays for mRNA detection and quantification
2. Processing RNA-seq data and generating a table of expression
Learn about Next Generation Sequencing and the steps to analyze and interpret RNA-seq data
3. Understanding The Table of Expression
Learn about working with the table of expression to get a high-level view of RNA-seq data
4. Conclusion and Additional Resources
Additional resources for reading to review what we learned in Transcriptomics 1
This course is very much informative and very helpful to understand each step very easily. I have learned a lot of things from basic.
Transcriptomics 1: Your First Step Towards RNA Sequencing
Transcriptomics 1 is surely the best way to start off when you are curious about RNA sequencing. It starts from the basic concept of transcription in the central dogma of life to the quantification of mRNA and analysis of RNA raw data. The course provides you with extensive content to brood over and then hands-on experience of the same which is extremely helpful to the point you understand the theoretical concept behind each topic. It is circumstantial but succinct and is a great continuation after Introduction to Bioinformatics course.
The first time learning this course was a bit difficult...but with thorough reading it was much clear.
A wonderful start to Transcriptomics
The course is well written and quite informative,it makes the concept easy to understand.
Excellent!! to start with Transcriptomics
It’s really a very enlightening course on the topic of transcriptomics . It has awesome content on the concepts with excellent examples on the data analysis and nice guiding videos. I really loved to go through this course.