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RNA-seq03:21

RNA-seq

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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. 
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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: May 1, 2026

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

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EXONSAMPLER: a computer program for genome-wide and candidate gene exon sampling for targeted next-generation

Ted Cosart1, Albano Beja-Pereira, Gordon Luikart

  • 1Division of Biological Sciences, University of Montana, Missoula, MT, 59812, USA.

Molecular Ecology Resources
|April 23, 2014
PubMed
Summary

EXONSAMPLER is a Python program that automates exon sequence collection for exon capture sequencing. It efficiently samples thousands of exon sequences from reference genomes, aiding in gene sequencing and SNP discovery.

Keywords:
bioinformaticsexon captureexon sequencesnext-generation sequencing

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Next-generation sequencing methods like exon capture require targeted DNA sequences.
  • Efficiently obtaining these sequences from large genomes is a critical challenge.
  • Publicly available genome sequences and annotation databases are valuable resources.

Purpose of the Study:

  • To develop a computational tool, EXONSAMPLER, for automating the retrieval of exon sequences.
  • To facilitate the design of exon-capture arrays for efficient gene sequencing.
  • To enable the study of genetic variation and gene regulation.

Main Methods:

  • EXONSAMPLER automates the sampling of exon sequences from reference genomes and gene annotation databases.
  • It allows for user-defined parameters such as exon length, number of base pairs, and sampling strategy (e.g., 5' or 3' exons).
  • The program outputs genomic coordinates (BED file) and sequences (FASTA format).

Main Results:

  • EXONSAMPLER was used to collect approximately 10% of the bovine exome (~3 million bp), including 155 genes and ~16,000 exons.
  • The collected sequences were used to design an exon-capture microarray for sequencing related species like zebu cattle and bison.
  • Prioritization of 5' exons aided in identifying single nucleotide polymorphisms (SNPs) near regulatory DNA sequences.

Conclusions:

  • EXONSAMPLER is an effective tool for automating exon sequence collection for exon capture applications.
  • The program supports efficient genome-wide SNP discovery and genotyping.
  • This approach facilitates evolutionary and population genetics studies in diverse species.