Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

RNA-seq03:21

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 Assembly03:36

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.
Next-generation Sequencing03:00

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...
Sanger Sequencing01:57

Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
Ribosome Profiling02:24

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...

You might also read

Related Articles

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

Sort by
Same author

Complete genome sequence of <i>Microbacterium</i> sp. strain UB-LE1, isolated from Teutoburger Forest soil in Germany.

Microbiology resource announcements·2026
Same author

Species-specific, accession-specific, and common responses of foliar phytohormones and morphological traits to drought and herbivory.

BMC plant biology·2026
Same author

Ecological role of emergent properties in the chemodiversity landscape.

Nature ecology & evolution·2026
Same author

Pre-anthesis light signaling of sheathed developing barley inflorescences defines floral fate.

Journal of experimental botany·2026
Same author

Dissecting the genetic basis of drought escape across multiple traits in colonizing Arabidopsis thaliana lineages.

The New phytologist·2026
Same author

Lysine Biosynthesis Defines a Metabolic Checkpoint for Gibberellin-Mediated Growth in Arabidopsis thaliana.

Plant, cell & environment·2026
Same journal

Machine-learning-assisted comparative analysis of rice growth and yield formation in field and plant factory systems.

Frontiers in plant science·2026
Same journal

TomatoweedDet: a real-field multi-class weed detection dataset and YOLO benchmark for tomato production systems.

Frontiers in plant science·2026
Same journal

Genomic advances in orphan and underutilized Brassicaceae crops and their wild relatives.

Frontiers in plant science·2026
Same journal

Delayed sowing limits grain number per spike in wheat by restricting young spike differentiation through reduced photothermal resources.

Frontiers in plant science·2026
Same journal

Deterministic assembly and centralized networks define the <i>Pinus massoniana</i> rhizosphere mycobiota.

Frontiers in plant science·2026
Same journal

Cover cropping enhances fruit quality in protected citrus cultivation by modulating rhizosphere microbiome and iron availability.

Frontiers in plant science·2026
See all related articles

Related Experiment Video

Updated: May 17, 2026

Novel Sequence Discovery by Subtractive Genomics
09:40

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

RNA-Seq Assembly - Are We There Yet?

Simon Schliesky1, Udo Gowik, Andreas P M Weber

  • 1Center of Excellence on Plant Sciences (CEPLAS), Institute for Plant Biochemistry, Heinrich Heine University Düsseldorf, Germany.

Frontiers in Plant Science
|October 12, 2012
PubMed
Summary
This summary is machine-generated.

Transcriptome sequence assembly is crucial for non-model plant species research. Current assembly methods using Next Generation Sequencing (NGS) data show limitations, necessitating improved strategies and quality control for accurate plant transcriptome representation.

Keywords:
NGSRNA-seqassemblynext generation sequencingplanttranscriptome

More Related Videos

AQRNA-seq for Quantifying Small RNAs
05:12

AQRNA-seq for Quantifying Small RNAs

Published on: February 2, 2024

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
11:52

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Related Experiment Videos

Last Updated: May 17, 2026

Novel Sequence Discovery by Subtractive Genomics
09:40

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

AQRNA-seq for Quantifying Small RNAs
05:12

AQRNA-seq for Quantifying Small RNAs

Published on: February 2, 2024

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
11:52

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Plant Genomics

Background:

  • Transcriptomic sequence data are vital for studying species lacking sequenced genomes.
  • Next Generation Sequencing (NGS) technologies like 454/Roche and Illumina have generated extensive plant transcriptome databases.
  • Existing transcriptome assemblies often fail to accurately represent the true plant transcriptome, limiting downstream applications like proteomics.

Purpose of the Study:

  • To review the challenges and solutions in transcriptome assembly for plant species.
  • To provide a framework for assessing the quality of transcriptome assemblies.
  • To offer practical tools and scripts for quality control in transcriptomic data analysis.

Main Methods:

  • Discussion of two primary assembly strategies: overlap-consensus for long reads and Eulerian path/de Bruijn graphs for short reads.
  • Analysis of assembly parameters and their impact on transcriptome accuracy.
  • Provision of a curated list of quality control parameters and associated scripts.

Main Results:

  • Identified limitations in current transcriptome assembly methods, particularly concerning accuracy.
  • Highlighted the differences in performance between long-read and short-read assembly approaches.
  • Demonstrated the need for robust quality control measures in transcriptomic data analysis.

Conclusions:

  • Accurate transcriptome assembly remains a significant challenge, especially for non-model organisms.
  • Improved assembly strategies and rigorous quality control are essential for reliable transcriptomic research.
  • The provided quality control parameters and scripts aim to enhance the utility of plant transcriptome sequence resources.