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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...
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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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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Transcriptome genetics using second generation sequencing in a Caucasian population.

Stephen B Montgomery1, Micha Sammeth, Maria Gutierrez-Arcelus

  • 1Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, 1211 Switzerland. stephen.montgomery@unige.ch

Nature
|March 12, 2010
PubMed
Summary

High-throughput sequencing of the transcriptome reveals more genetic variants influencing gene expression (eQTLs) and alternative splicing than microarrays. This advanced technology enhances our understanding of genetic impacts on cellular processes.

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Area of Science:

  • Genomics
  • Transcriptomics
  • Bioinformatics

Background:

  • Gene expression is a key phenotype reflecting genetic and environmental influences on cellular states.
  • Microarrays have been used to identify genetic variants affecting gene expression, but offer limited resolution.
  • Second-generation sequencing technologies provide high-resolution transcriptome analysis.

Purpose of the Study:

  • To leverage high-throughput sequencing to identify genetic variants influencing gene expression and transcript structure.
  • To compare the discovery power of sequencing versus microarrays for expression quantitative trait loci (eQTLs).
  • To explore allele-specific expression and its role in transcript variation.

Main Methods:

  • Sequencing of the mRNA fraction of the transcriptome in 60 European descent individuals (HapMap).
  • Integration of sequencing data with genetic variants from the HapMap3 project.
  • Quantification of exon and whole transcript abundance using read depth.
  • Analysis of small nucleotide polymorphisms (SNPs) for eQTL discovery.
  • Assessment of allele-specific expression.

Main Results:

  • High-throughput sequencing offers a dynamic range comparable to arrays with superior quantification of alternative and abundant transcripts.
  • Sequencing-based SNP correlation identified significantly more eQTLs than array-based methods.
  • A substantial number of variants influencing mature transcript structure, indicating roles in alternative splicing, were detected.
  • Allele-specific expression analysis enabled the discovery of rare eQTLs and allelic differences in transcript structure.

Conclusions:

  • High-throughput sequencing technologies offer novel insights into genetic effects on the transcriptome.
  • These technologies surpass microarrays in identifying eQTLs and characterizing transcriptomic variation.
  • The study highlights the potential for exploring genetic influences on complex cellular processes through advanced sequencing.