Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • lmbrutscher
    Junior Member
    • Sep 2016
    • 1

    Metagenomic Assembly from PacBio reads

    Hi everyone,

    I am trying to assemble a bacterial genome using PacBio reads and short illumina reads from a metagenomic pool of both eurkaryotic host and bacterial sequences.

    In an ideal world, I would have been able to culture the bacteria and obtain pure DNA to sequence and assemble from, but its cultivation has proved challenging. So, instead we have a ton of metagenomic data sequenced obtained from whole host DNA. We have roughly ~70 million Illumina MiSeq paired end reads (2x150) and ~120,000 PacBio reads (5-20 KB). I suspect that I have roughly 3x coverage of the bacterial genome with the PacBio reads and ~20-30x coverage with the illumina reads (with 80-90% of the reads likely being host). This project is further complicated by the fact that the host genome is not fully sequenced, so I cannot remove known host sequence to simplify analysis and de novo assembly.

    Could anyone recommend an appropriate set of programs/pipeline in order to isolate and assemble the bacterial genome? Thanks so much!
    Last edited by lmbrutscher; 04-03-2017, 12:21 PM.
  • rhall
    Senior Member
    • Aug 2012
    • 324

    #2
    Hi,
    There isn't one well developed approach to an experiment like this, I can think of a lot of things to try, but it is going to come down to a lot of manual assembly work.
    My first observation would be that the pacbio coverage is a little low if you want to go for a hybrid assembly approach. With only 3x of data a lot of the genome will not be covered at all and the chances of the reads within that 3x spanning the important repeats, that will not be resolved in the illumina data, is slim.
    I would concentrate on the illumina data, assemble with a standard metagenomic assembly algorithm, for a recent comparison http://journals.plos.org/plosone/art...l.pone.0169662. Then bin the microbial contigs by comparing with a database, using something like Kraken.
    3x of pacbio data is going to be all but useless, but you could try manually aligning the pacbio data to the binned microbial contigs to see if you can get any useful scaffold information. The problem at 3x is that even if you do see a single read join two illumina contigs it is impossible to tell if that is a real connection or not. There is always a none zero chance of a biological chimera being formed during sample prep, a random event, so normally you would always require at least two reads to corroborate a connection.

    Comment

    Latest Articles

    Collapse

    • SEQadmin2
      Proteomic Platforms: How to Choose the Right Analytical Strategy to Improve Detection and Clinical Applications
      by SEQadmin2


      Proteomics platforms are evolving rapidly, with advances in mass spectrometry and affinity-based approaches expanding what researchers can detect and at what scale. As the field moves toward deeper proteome coverage and clinical applications, scientists face an increasingly complex landscape of tools. This article will explore how researchers are navigating these choices to find the right platform for their work.

      The systematic characterization of the human proteome has
      ...
      07-20-2026, 11:48 AM
    • SEQadmin2
      Advanced Sequencing Platforms Tackle Neuroscience’s Toughest Genomics Problems
      by SEQadmin2



      Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
      ...
      07-09-2026, 11:10 AM
    • SEQadmin2
      Cancer Drug Resistance: The Lingering Barrier to Rising Survival
      by SEQadmin2



      Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.

      There is no single reason why many patients don’t respond to treatment as expected. Cancer is...
      07-08-2026, 05:17 AM

    ad_right_rmr

    Collapse

    News

    Collapse

    Topics Statistics Last Post
    Started by SEQadmin2, 07-20-2026, 11:10 AM
    0 responses
    21 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 07-13-2026, 10:26 AM
    0 responses
    34 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 07-09-2026, 10:04 AM
    0 responses
    44 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 07-08-2026, 10:08 AM
    0 responses
    30 views
    0 reactions
    Last Post SEQadmin2  
    Working...