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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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Finding Pathogenic Nucleic Acid Sequences in Next Generation Sequencing Data.

Michael Parfenov1, J G Seidman1

  • 1Department of Genetics, Harvard Medical School, Boston, Massachusetts.

Current Protocols in Human Genetics
|July 2, 2015
PubMed
Summary
This summary is machine-generated.

This protocol introduces a fast and simple method for detecting pathogenic DNA or RNA in next-generation sequencing data. It also identifies potential pathogen genome integration into the host genome, aiding disease research.

Keywords:
bacteriadetectionintegrationnext generation sequencingpathogensviruses

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Area of Science:

  • Microbiology
  • Genomics
  • Bioinformatics

Background:

  • Viruses and bacteria are significant causes of human diseases, including hepatitis and cancer.
  • Next-generation sequencing (NGS) is increasingly used to study pathogen presence in human samples.
  • Current NGS methods for pathogen detection are time-consuming and computationally intensive.

Purpose of the Study:

  • To present a simplified and rapid protocol for pathogen detection using NGS data.
  • To enable the identification of pathogenic DNA or RNA.
  • To detect the integration of pathogen genomes within the host genome.

Main Methods:

  • Development of a straightforward computational protocol.
  • Application to human whole genome and transcriptome sequencing data.
  • Focus on efficiency and reduced resource utilization.

Main Results:

  • Successful detection of pathogenic DNA and RNA.
  • Identification of integrated pathogen genomes in host DNA.
  • Demonstration of a time- and resource-efficient approach.

Conclusions:

  • The protocol offers a practical solution for pathogen detection in NGS data.
  • This method facilitates the study of host-pathogen interactions and disease mechanisms.
  • The approach is valuable for clinical and research settings requiring rapid pathogen identification.