Related Experiment Video
Updated: Nov 24, 2025
07:09
A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
Published on: May 28, 2021
10.1K
A primer for generating and using transcriptome data and gene sets
Chad Cockrum1, Kiyomi R Kaneshiro1, Andreas Rechtsteiner1
1Department of Molecular, Cell, and Developmental Biology, University of California Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA.
Development (Cambridge, England)
|December 28, 2020
Summary
This primer explores transcriptomic methods for analyzing gene expression patterns across tissues and single cells. It covers RNA collection, sequencing data analysis, and identifying tissue-specific genes.
Area of Science:
- Molecular Biology
- Genomics
- Bioinformatics
Background:
- Transcriptomics offers powerful tools for studying genome-wide gene expression patterns.
- Advancements in technology allow for detailed analysis of transcript abundance in specific tissues and single cells.
Purpose of the Study:
- To discuss methods for collecting and profiling RNA from specific biological samples.
- To explain the processing and analysis of high-throughput RNA sequencing data.
- To define strategies for identifying gene sets representing tissue-enriched or tissue-specific expression.
Main Methods:
- RNA collection and profiling from targeted tissues or single cells.
- High-throughput RNA sequencing data processing and analysis pipelines.
- Bioinformatic approaches for gene set definition and categorization.
Main Results:
- Established methodologies for comprehensive transcriptomic analysis.
- Framework for accurate identification of tissue-specific gene expression profiles.
- Insights into the application of transcriptomics for cell and tissue characterization.
Conclusions:
- Transcriptomic techniques are essential for understanding gene expression at a granular level.
- This primer provides a guide to leveraging these methods for biological discovery.
- Accurate analysis enables the identification of genes critical to specific cellular functions and tissue identities.
More Related Videos
Related Concept Videos
03:36Genome Annotation and Assembly
19.9K
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
19.9K
03:21Genome Size and the Evolution of New Genes
3.0K
3.0K
02:24Ribosome Profiling
3.9K
Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
3.9K
03:21RNA-seq
11.2K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
11.2K