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Related Concept Videos

DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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.

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Related Experiment Video

Updated: Jun 18, 2026

Pyrosequencing: A Simple Method for Accurate Genotyping
13:06

Pyrosequencing: A Simple Method for Accurate Genotyping

Published on: January 8, 2008

Combining next-generation pyrosequencing with microarray for large scale expression analysis in non-model species.

Diana Bellin1, Alberto Ferrarini, Antonio Chimento

  • 1Department of Biotechnology, University of Verona, Strada le Grazie 15, 37134 Verona, Italy. diana.bellin@univr.it

BMC Genomics
|November 26, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method for creating a "virtual transcriptome" using next-generation sequencing, enabling gene expression analysis in non-model species without prior genomic data. The approach successfully generated a comprehensive transcript catalog for Vitis vinifera.

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Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform
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Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform

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Last Updated: Jun 18, 2026

Pyrosequencing: A Simple Method for Accurate Genotyping
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Published on: January 8, 2008

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis
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Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

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Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform
13:14

Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform

Published on: August 10, 2009

Area of Science:

  • Genomics
  • Functional Genomics
  • Bioinformatics

Background:

  • Next-generation sequencing (NGS) offers new avenues for transcriptome characterization and functional genomics.
  • Developing affordable tools for functional genomics is crucial for broader research applications.
  • This study addresses the need for transcriptome analysis in non-model species lacking extensive genomic resources.

Purpose of the Study:

  • To present an innovative approach for transcriptome characterization using NGS.
  • To demonstrate the method's utility for non-model organisms.
  • To enable the development of custom microarrays for gene expression analysis.

Main Methods:

  • Construction of a normalized cDNA library from pooled RNAs.
  • 454 sequencing of 3' cDNA fragments.
  • De novo assembly of reads to create a unique transcript catalog (virtual transcriptome).

Main Results:

  • Generated a large catalog of unique transcripts for Vitis vinifera without prior sequence information.
  • Developed a custom microarray that detected 19,609 genes, surpassing existing grape microarrays in informative capacity.
  • Demonstrated the method's effectiveness for gene expression analysis in a non-model species.

Conclusions:

  • The described approach is a powerful tool for rapidly building extensive transcript catalogs.
  • This method facilitates the development of custom microarrays for large-scale gene expression analysis in any species.
  • Prior sequence knowledge is not required, making it highly versatile for diverse organisms.