A comprehensive understanding of host–pathogen interactions requires a knowledge of the associated gene expression changes in both the pathogen and the host. Traditional, probe-dependent approaches using microarrays or reverse transcription PCR typically require the pathogen and host cells to be physically separated before gene expression analysis. However, the development of the probe-independent RNA sequencing (RNA-seq) approach has begun to revolutionize transcriptomics.

Researchers at the University of Würzburg, Germany have assessed the feasibility of taking transcriptomics one step further by performing ‘dual RNA-Seq’, in which gene expression changes in both the pathogen and the host are analysed simultaneously.

They found that dual RNA-Seq will require high sequencing depth in order to provide accurate representations of the host and pathogen genomes and propose that this is highly likely to be attainable in the future given the potential for near-infinite sequencing power. However, current dual RNA-Seq on the population level appears to be costly but feasible. The latest sequencing platforms can generate an output of up to several hundred gigabases per experimental run, suggesting that the ~200–2,000 million reads required for dual RNA-Seq can be achieved.

  • Westermann AJ, Gorski SA, Vogel J. (2012) Dual RNA-seq of pathogen and host. Nat Rev Microbiol 10(9), 618-30. [article]

Incoming search terms:

  • dual rna seq
  • Dual RNA-seq of pathogen and host
  • host pathogen interaction rna seq
  • dual seq
  • host pathogen interactions rna seq

Comments

One Response to “Dual RNA-Seq of Pathogen and Host”

  1. Dual RNA-Seq of Pathogen and Host | RNA-Seq Blog | Roberts Lab on August 22nd, 2012 6:09 pm

    [...] Dual RNA-Seq of Pathogen and Host | RNA-Seq Blog [...]

Leave a Reply




  • Social Networking Pages

    Linkedin Group

  • Follow Me on Pinterest
  • RSS SEQanswers – RNA Sequencing

    • CuffDiff strange output May 23, 2013
      Hi, I hope that someone can be so gentle to help me. I'm analizing some data from RNA-Seq with TopHat and Cufflinks and I focus my attention on... […]
      Pruexel
    • cannot away with cuffdiff,incredible May 23, 2013
      Hi,all I have 4(A,B,C,D) sample in 4 times(increasing time),I got diff result in 3 different cuffdiff 1.cuffdiff 3(A,B,C) individual... […]
      upper
    • TopHat extremely low paired mapping rate. PLS HELP! May 22, 2013
      Hey guys, I have some problems with my paried-end RNA seq analysis on Galaxy. As you can see in the bam flagstat output, my tophat alignment rate is... […]
      Felix.Lee
    • Identifying small RNA sequence within whole genome sequence May 21, 2013
      Hi all, I want to know if there are any useful bioinformatic tool to find small RNA sequence within a whole bacteria genome. Thank you in... […]
      Inma
    • standard of clean data May 21, 2013
      Hi all I recently got my prokaryotes RNA-seq data report back. the standard filter steps of the raw data set by our local sequencing center is as... […]
      Pengfei Liu
    • Problem with cummeRbund diffData() May 20, 2013
      Hi all, I'm running Tophat/cufflinks/cuffdiff for differential gene expression and analysis with cummeRbund (v 2.0.0). I'm having an issue with... […]
      Enrique Zudaire
  • RSS Biostar – RNA-Seq

    • Why am I getting so many unmapped reads in STAR, classified as "too short"?
      I am currently using STAR to map several Hi-SEQ mRNA runs. I'm having trouble getting a decent amount of reads to map, but I don't really understand why. I'm hoping you can shed some light :) In the final log, only about 50% (or less) of the reads map to the reference. I'm using a GTF in addition to the genome. The unmapped bin that most […]
    • What are the best practices for SNP identification in RNA seq transcriptome data
      I have 20 RICE RNA seq tranascriptome data hiseq 2000 platform paired end reads. I aligned fasta reads with BWA and remove PCR duplicates with PICARD. Later I call SNP with samtools using various parameters. I would like to clarify what parameters should I used while alinging to reference rice genome for looking SNP location 100 bp upstream and 250 bp downst […]
    • How do TopHat options -g , --supress-hits, and Bowtie options interplay?
      Hi, I am currently using TopHat2 to map RNA-seq runs. I think there have been some changes pertaining the -g option. Does anyone know how it works now? I used to think that setting -g would look for n alignments for a given read, report them [if top-scoring] and discard those reads that had more than g [top scoring] alignments. Now, the description sounds mo […]
    • What happened to -k in TopHat for multiple-mapping reads?
      Selecting -g n in tophat does not discard reads mapping more than n, but instead only reports n alignments for those out all all their TOP scoring alignments. I think there used to be an option -k that would allow one to discard reads that topped x alignments -- whatever happened to that? I only see -g in the tophat 2 manual, no reporting options like before […]
    • Does tophat use the library-type information for mapping, or just for the XS flag?
      When I specify library-type to TopHat, i.e., first-strand, second-strand, unstranded, TopHat appends a value + or - to the XS:A flag, which is useful for subsequent analyses, such as annotation. However, does this information actually influence the "mappability" of reads, or is this unaffected? My thinking is that the information would be considere […]
    • Purpose of Y-shaped adapters in Illumina Sequencing?
      Hi all, Y adapters different sequences to be annealed to the 5' and 3' ends of each molecule in a library. The arms of the Y are unique, and the middle part, connected to the DNA fragment, is complementary. What are the advantages of this? My take of this over having fully-complementary adapters (ADAPTER1 - - - - - ADAPTER1) is that: -Upon primer a […]