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RNA-seq

RNA-seq

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...

Genome Annotation and Assembly

Genome Annotation and Assembly

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.

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Ribosome Profiling

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.
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Related Experiment Video

Updated: Mar 16, 2026

Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes

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The Effect of Human Genome Annotation Complexity on RNA-Seq Gene Expression Quantification.

Po-Yen Wu¹, John H Phan², May D Wang³

¹Department of Electrical and Computer Engineering, Georgia Tech, Atlanta, GA, U.S.A, pwu33@gatech.edu.

IEEE International Conference on Bioinformatics and Biomedicine Workshops. IEEE International Conference on Bioinformatics and Biomedicine

|August 18, 2016

Summary

This summary is machine-generated.

The choice of human genome annotation impacts RNA-Seq gene expression quantification. More complex annotations increase quantification variation, as validated by qRT-PCR, affecting gene expression analysis.

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Area of Science:

Genomics
Transcriptomics
Bioinformatics

Background:

Next-generation sequencing (NGS) revolutionized human genomic research.
RNA-Seq quantifies gene expression, relying on accurate human genome annotation.
Existing genome annotations vary in complexity, creating uncertainty.

Purpose of the Study:

To evaluate the influence of different human genome annotations on RNA-Seq gene expression quantification.
To assess the impact on mapping quality, quantification variation, and accuracy.

Main Methods:

Compared multiple human genome annotations for RNA-Seq analysis.
Assessed mapping quality and quantification variation.
Validated quantification accuracy using quantitative reverse transcription PCR (qRT-PCR) data.
Evaluated concordance in detecting differentially expressed genes.

Main Results:

Different genome annotations led to variations in mapping quality and gene expression quantification.
External validation with qRT-PCR indicated that more complex genome annotations correlate with higher quantification variation.
The choice of annotation influenced the detection of differentially expressed genes.

Conclusions:

Genome annotation is a critical factor influencing RNA-Seq-based gene expression studies.
Researchers must carefully consider the chosen genome annotation for accurate and reproducible RNA-Seq results.
Further investigation into annotation-specific biases is warranted.