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Related Concept Videos

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.
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...
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.
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

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Related Experiment Video

Updated: May 11, 2026

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms
10:41

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms

Published on: May 9, 2017

Sequence comparative analysis using networks: software for evaluating de novo transcript assembly from

Ian Misner1, Cédric Bicep, Philippe Lopez

  • 1Department of Biological Sciences, University of Rhode Island, RI, USA.

Molecular Biology and Evolution
|May 14, 2013
PubMed
Summary
This summary is machine-generated.

Sequence Comparative Analysis using Networks (SCAN) software aids researchers in evaluating de novo transcriptome assemblies. It statistically identifies the most accurate assembly and transcripts, crucial for novel genome projects.

Keywords:
comparative genomicsde novo assemblynetworknext-generation sequencingoomycetetranscriptome

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High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

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Last Updated: May 11, 2026

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved (Non-model) Organisms
10:41

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Published on: May 9, 2017

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Novel Sequence Discovery by Subtractive Genomics

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High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)
09:06

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

Published on: October 5, 2018

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • DNA sequencing costs are decreasing, enabling more researchers to sequence novel transcriptomes.
  • De novo assembly is essential for transcriptomes lacking a reference genome.
  • Evaluating and comparing different assembly programs is challenging due to varying strengths and weaknesses.

Purpose of the Study:

  • To develop a software tool for statistically comparing distinct de novo transcriptome assemblies.
  • To identify the most accurate de novo assembly and high-quality transcripts within user data.
  • To provide a method for comparative evaluation of transcriptome assembly algorithms.

Main Methods:

  • Developed Sequence Comparative Analysis using Networks (SCAN) software in R.
  • Utilized a reference dataset to statistically compare transcripts from different assembly programs.
  • Tested SCAN on publicly available transcriptomes and a newly sequenced oomycete transcriptome (Achlya hypogyna).

Main Results:

  • SCAN statistically compared de novo assemblies from Velvet, ABySS, and CLC Genomics Workbench.
  • In the Achlya hypogyna transcriptome, 937 ABySS transcripts were statistically similar to the reference, compared to 1,128 CLC and 49 Velvet transcripts.
  • SCAN provides statistical support for transcript assemblies within a biological context.

Conclusions:

  • SCAN enables robust statistical comparison of de novo transcriptome assemblies.
  • The software aids researchers in selecting the most accurate assembly and identifying reliable transcripts.
  • SCAN's network-based approach is extensible for comparative analysis of various network graphs.