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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 microarray-based...

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.

Ribosome Profiling

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.
The technique helps...

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Related Experiment Video

Updated: May 16, 2026

AQRNA-seq for Quantifying Small RNAs

AQRNA-seq for Quantifying Small RNAs

Published on: February 2, 2024

Improved transcriptome quantification and reconstruction from RNA-Seq reads using partial annotations.

Serghei Mangul¹, Adrian Caciula, Olga Glebova

¹Department of Computer Science, Georgia State University, Atlanta, GA, USA. serghei@cs.gsu.edu

In Silico Biology

|December 4, 2012

Summary

This summary is machine-generated.

This study introduces a new framework, Discovery and Reconstruction of Unannotated Transcripts (DRUT), to improve RNA-Seq analysis for transcriptome reconstruction and discovery. DRUT enhances existing tools, leading to superior transcript reconstruction and frequency estimation.

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Area of Science:

Genomics
Bioinformatics
Transcriptomics

Background:

RNA-Seq data analysis is crucial for understanding gene expression.
Partially annotated genomes present challenges for accurate transcriptome reconstruction and novel transcript discovery.
Existing transcriptome assembly methods have limitations in handling incomplete genomic annotations.

Purpose of the Study:

To develop a novel annotation-guided framework for transcriptome discovery, reconstruction, and quantification in partially annotated genomes.
To compare the proposed framework with existing annotation-guided and genome-guided transcriptome assembly methods.
To enhance the performance of existing transcriptome assemblers like Cufflinks.

Main Methods:

The study presents a general framework named Discovery and Reconstruction of Unannotated Transcripts (DRUT).
DRUT is designed to work with RNA-Seq data and partially annotated genomes.
The method was integrated with Cufflinks and evaluated using synthetic datasets.

Main Results:

DRUT demonstrated superior quality in transcriptome reconstruction compared to existing methods.
The enhanced Cufflinks (with DRUT) showed improved accuracy in estimating transcript frequencies.
Empirical analysis confirmed the effectiveness of the DRUT framework.

Conclusions:

The DRUT framework offers a significant advancement in analyzing RNA-Seq data for transcriptome reconstruction and discovery.
Integrating DRUT with assemblers like Cufflinks enhances their performance, especially in partially annotated genomes.
This approach improves the accuracy of transcript identification and quantification, aiding genomic research.