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...

You might also read

Related Articles

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

Sort by

Same author

HsClpP-Engaging Selective Mitochondrial Pan-PDK Degraders for Cancer Therapy.

Journal of medicinal chemistry·2026

Same author

Cross-Domain Fire Detection Across Indoor and Outdoor Scenes.

Sensors (Basel, Switzerland)·2026

Same author

Adaptive strategies of the harmful alga Heterosigma akashiwo to low salinity: rapid stress responses and long-term metabolic remodeling.

Harmful algae·2026

Same author

Dual Metabolic Blockade in Pancreatic Cancer: Potent Anticancer Activity of Mitochondria-Targeted Glycolysis and OXPHOS Inhibitors.

Journal of medicinal chemistry·2026

Same author

Electron-Deficient Single-Molecule-Junction Sites in COFs Enable H<sub>2</sub>O<sub>2</sub> Photosynthesis via Precision Charge Delivery and Oxygen Adsorption.

Advanced materials (Deerfield Beach, Fla.)·2026

Same author

Boosting Built-in Electric Field via COF Molecular Quadrupole Gradients for Efficient H<sub>2</sub>O<sub>2</sub> Photosynthesis.

Angewandte Chemie (International ed. in English)·2026

Search research articles

Related Experiment Video

Updated: Aug 8, 2025

Transcriptome Analysis of Single Cells

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

Full-Length Transcriptome Analysis of the Ichthyotoxic Harmful Alga Heterosigma akashiwo (Raphidophyceae) Using

Nanjing Ji^1,2, Xueyao Yin^1,2, Yujiao Chen^1,2

¹Jiangsu Key Laboratory of Marine Bioresources and Environment/Jiangsu Key Laboratory of Marine Biotechnology, Jiangsu Ocean University, Lianyungang 222005, China.

|February 25, 2023

Summary

Harmful algal blooms of Heterosigma akashiwo cause fish kills. Researchers generated a reference transcriptome to understand the molecular basis of these blooms, identifying key metabolism and regulatory genes.

Keywords:

Heterosigma akashiwo SMRT sequencing harmful alga reference transcriptome

More Related Videos

Simultaneous DNA-RNA Extraction from Coastal Sediments and Quantification of 16S rRNA Genes and Transcripts by Real-time PCR

Simultaneous DNA-RNA Extraction from Coastal Sediments and Quantification of 16S rRNA Genes and Transcripts by Real-time PCR

Published on: June 11, 2016

Analyzing Gene Expression from Marine Microbial Communities using Environmental Transcriptomics

Analyzing Gene Expression from Marine Microbial Communities using Environmental Transcriptomics

Published on: February 18, 2009

Related Experiment Videos

Last Updated: Aug 8, 2025

Transcriptome Analysis of Single Cells

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

Simultaneous DNA-RNA Extraction from Coastal Sediments and Quantification of 16S rRNA Genes and Transcripts by Real-time PCR

Simultaneous DNA-RNA Extraction from Coastal Sediments and Quantification of 16S rRNA Genes and Transcripts by Real-time PCR

Published on: June 11, 2016

Analyzing Gene Expression from Marine Microbial Communities using Environmental Transcriptomics

Analyzing Gene Expression from Marine Microbial Communities using Environmental Transcriptomics

Published on: February 18, 2009

Area of Science:

Marine Biology
Phycology
Molecular Biology

Background:

Harmful algal blooms (HABs) caused by the raphidophyte Heterosigma akashiwo are linked to significant fish mortality in coastal ecosystems.
Understanding the molecular mechanisms driving H. akashiwo blooms is crucial for predicting and mitigating their ecological impact.

Purpose of the Study:

To generate a high-quality, full-length reference transcriptome for Heterosigma akashiwo.
To identify genes and molecular pathways involved in H. akashiwo bloom formation and its ecological effects.

Main Methods:

Single-molecule real-time (SMRT) sequencing was employed to obtain the full-length transcriptome of H. akashiwo.
Bioinformatic analyses were performed to process sequencing data, assemble unigenes, and annotate gene functions using public databases.

Main Results:

A total of 16,668 unigenes were obtained, with 52% successfully annotated.
Key genes related to phosphorus and nitrogen metabolism were identified.
The transcriptome analysis predicted 300 transcription factors, 4392 long non-coding RNAs, and 7851 simple sequence repeats.

Conclusions:

This study provides a valuable genomic resource for Heterosigma akashiwo.
The generated transcriptome data offers insights into the molecular underpinnings of H. akashiwo blooms.
Further research can utilize this reference to investigate the ecological dynamics and harmful potential of this species.