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  • Rfam for bacteria

    Hi

    Any one suggest me how to identify ncRNAs for bacteria (Deep sequencing data).

    I want to identify ncRNAs in Bacteria.

    Currently i am using Rfam along with Infernal. I want to know how to screen/separate bacteria from the Rfam database.

    * Any suggestions for software/databases.

    Thanks.
    Last edited by Krish_143; 07-18-2012, 05:25 AM.
    Krishna

  • #2
    If you have a particular bacteria in mind then you browse the genomes page. Alternatively, if you want a list of Rfam families that contain bacterial sequences, then you could email [email protected] and ask for it.
    Are your reads assembled or are they short fragments? If the latter, then CMs have a pretty major problem with truncated sequences. See the article by Kolbe & Eddy. The new release of Infernal may be more robust to truncations.

    Comment


    • #3
      1) Reads mapped to the genome (with out using annotation file) using Tophat, bwa, bowtie2 and bowtie and then cufflinks for assembly. Annotate the assembled transcripts.

      2) De-novo assembly using Trinity, Soap denovo. Annotate assembled transcripts.

      3) Gneome annotation by Rfam along with infernal-1.1rc1 using cmsearch and creating gff or GTF again reads are mapped to the genome genome (1) with annotation file.

      I have short reads as well as assembled data (1), (2) and Genome for annotation.

      Yeah i sent mail and requested looking eddys article, any more suggestions.

      Thanks.
      Krishna

      Comment


      • #4
        if you have your transcript assembled you could use something like RNAz to test the so far not annotated transcript if they are structural conserved, this might give you hint.

        Comment


        • #5
          Pole_sana @ I do not have any idea how to annotate using RNAz.Can you give me an outline or suggestion of articles . I will check it.

          Thanks.
          Krishna

          Comment


          • #6
            Originally posted by Krish_143 View Post
            Pole_sana @ I do not have any idea how to annotate using RNAz.Can you give me an outline or suggestion of articles . I will check it.

            Thanks.
            you have to choose related species; blast your putative ncRNA there, if you find homologues you align them; this alignment can be evaluated with RNAz whether there seems to be a structural conservation, which implies a function for the structure (and thus the conservation of this structure) which is often the case with ncRNA.

            what RNAz is doing you can see on the webserver version (there is of course also a stand alone version) http://rna.tbi.univie.ac.at/cgi-bin/RNAz.cgi

            If this seems to much work for you you can also compare your not annotated transcripts with other ncRNA prediction tools, such as SIPHT or NAPP (just google them).

            regards

            Comment


            • #7
              pole_sana@ Yeah i will go through with RNAz and i am using other prediction tools like. sRNAPredict2, NAPP and RNAspace(which Using internally all these Softwares) and few other softwares.

              SIPHT might be used only comparison of existing genomes but how can it work with new genomes which dosen't have close species. it might be possible to check only using reference genome data.

              Thanks.
              Krishna

              Comment


              • #8
                if you do not have cosely related species than sipht and RNAz can t be applied, since they are based on genome comparision;

                Comment


                • #9
                  pole_sana@
                  Ok, we have different genomes data. Where few doe's not have closely related (sRNAs annotation only genome annotation available) and for the rest i can use these tools(SIPHT, RNAz).

                  Rfam is one of the good option thats why i want to annotate only using bacterial families and then later with othere tools.

                  Any Suggestions,

                  Thanks.
                  Krishna

                  Comment

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