Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

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...

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...

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.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

AIEdit: Alignment-free genome assembly polisher trained on spaced seed match patterns.

PLoS computational biology·2026

Same author

ntStat: k-mer characterization using occurrence statistics in raw sequencing data.

PLoS computational biology·2026

Same author

A comprehensive tandem repeat catalog of the human genome.

Nature communications·2026

Same author

ntRoot: computational inference of human ancestry at scale from genomic data.

Bioinformatics advances·2025

Same author

Streaming Long-Read Sequence Alignments for HLA Predictions Using HLAminer.

Current protocols·2025

Same author

Rearrangements of viral and human genomes at human papillomavirus integration events and their allele-specific impacts on cancer genome regulation.

Genome research·2024

Same journal

A unified analysis of cell type- and trajectory-associated pathways in single-cell data using Phoenix.

Genome research·2026

Same journal

Resf1 is required for proper placental development and configuration of trophoblast cell-specific heterochromatin.

Genome research·2026

Same journal

Telomere-driven replicative crisis is driven by large-scale changes in genomic architecture.

Genome research·2026

Same journal

Spatially informed reference-free cell-type deconvolution for spatial transcriptomics with SpatialCD.

Genome research·2026

Same journal

Spatially resolved profiling of steroid nuclear receptors reveals a role for the disordered N-terminal domains in genome targeting and AP-1 interaction.

Genome research·2026

Same journal

Flexible and scalable inference of spatially varying correlation in spatial transcriptomics with spCorr.

Genome research·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Dec 11, 2025

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

RNA-Bloom enables reference-free and reference-guided sequence assembly for single-cell transcriptomes.

Ka Ming Nip¹, Readman Chiu¹, Chen Yang¹

¹Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, British Columbia, Canada V5Z 4S6.

Genome Research

|August 21, 2020

Summary

This summary is machine-generated.

RNA-Bloom is a new algorithm for single-cell transcriptome analysis. It reconstructs cell-specific isoforms from single-cell RNA sequencing data, improving isoform discovery compared to existing methods.

More Related Videos

RNA-seq Analysis of Transcriptomes in Thrombin-treated and Control Human Pulmonary Microvascular Endothelial Cells

RNA-seq Analysis of Transcriptomes in Thrombin-treated and Control Human Pulmonary Microvascular Endothelial Cells

Published on: February 13, 2013

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Related Experiment Videos

Last Updated: Dec 11, 2025

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

RNA-seq Analysis of Transcriptomes in Thrombin-treated and Control Human Pulmonary Microvascular Endothelial Cells

RNA-seq Analysis of Transcriptomes in Thrombin-treated and Control Human Pulmonary Microvascular Endothelial Cells

Published on: February 13, 2013

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Single-cell RNA sequencing (scRNA-seq) has advanced rapidly, but isoform analysis remains limited.
Existing transcriptome assembly methods are designed for bulk RNA, not single cells.
Technical limitations of scRNA-seq data hinder isoform detection in individual cells.

Purpose of the Study:

To develop an algorithm for reconstructing cell-specific isoforms from scRNA-seq data.
To enable unbiased discovery of novel isoforms and foreign transcripts.
To improve the utility of scRNA-seq data beyond gene expression analysis.

Main Methods:

Developed RNA-Bloom, an assembly algorithm leveraging aggregated single-cell transcriptome data.
Implemented both reference-guided and reference-free assembly strategies.
Benchmarked RNA-Bloom against five state-of-the-art transcriptome assembly methods.

Main Results:

RNA-Bloom significantly outperformed existing methods in isoform reconstruction on both simulated and real datasets.
Reference-free RNA-Bloom identified 37.9%-38.3% more isoforms than the best reference-free assembler.
Reference-guided RNA-Bloom identified 4.1%-11.6% more isoforms than reference-based assemblers.
On a large real dataset, RNA-Bloom reconstructed 9.7%-25.0% more isoforms than competing approaches.

Conclusions:

RNA-Bloom effectively reconstructs cell-specific isoforms from scRNA-seq data.
The algorithm enhances isoform discovery, enabling analysis beyond gene expression.
RNA-Bloom expands the informatic accessibility of scRNA-seq data for isoform analysis.