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Related Concept Videos

RNA-seq03:21

RNA-seq

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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...
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Genome Annotation and Assembly03:36

Genome Annotation and Assembly

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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 Profiling02:24

Ribosome Profiling

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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...
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RACE - Rapid Amplification of cDNA Ends02:35

RACE - Rapid Amplification of cDNA Ends

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Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific...
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Related Experiment Video

Updated: Apr 16, 2026

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
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Bridger: a new framework for de novo transcriptome assembly using RNA-seq data.

Zheng Chang, Guojun Li, Juntao Liu

    Genome Biology
    |February 28, 2015
    PubMed
    Summary
    This summary is machine-generated.

    Bridger is a novel de novo transcriptome assembler that improves accuracy and efficiency for RNA-seq data analysis. This new tool assembles more full-length transcripts with fewer false positives, outperforming existing methods.

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    Novel Sequence Discovery by Subtractive Genomics
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    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Genomics

    Background:

    • De novo transcriptome assembly is crucial for analyzing RNA sequencing (RNA-seq) data, especially in non-model organisms.
    • Existing de novo assemblers face limitations in accuracy, efficiency, and the number of false positive transcripts generated.

    Purpose of the Study:

    • To introduce Bridger, a new de novo transcriptome assembler designed to overcome the limitations of current tools.
    • To evaluate Bridger's performance in terms of accuracy, sensitivity, speed, and memory usage.

    Main Methods:

    • Bridger employs techniques similar to Cufflinks to enhance assembly.
    • Performance was assessed using RNA-seq data from dog, human, and mouse.
    • Key metrics included the number of full-length transcripts, candidate transcripts, and overall accuracy.

    Main Results:

    • Bridger assembled a higher proportion of full-length reference transcripts compared to state-of-the-art assemblers.
    • It significantly reduced the number of false positive transcripts.
    • The assembler demonstrated substantially faster runtimes and lower memory requirements.

    Conclusions:

    • Bridger offers improved accuracy and efficiency for de novo transcriptome assembly.
    • It provides a valuable tool for RNA-seq data analysis, reducing computational burden and improving transcript identification.