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  • Is 12.5M reads enough for transcript discovery in bacteria?

    Hello SeqAnswers and thanks for your time.

    I have a question about RNA-seq with sensitivity in mind. According to Genohub, 30+ M reads are suggested for transcript discovery in bacteria. However, Encode and Genohub both suggest 100-200M reads for the human transcriptome. For every megabasepair of the human transcriptome (conservative estimate of 140Mbp), between 0.71-1.43 million clusters should be sequenced (this ratio would decrease for a larger estimate of the transcriptome) to achieve suggested depth. For bacteria (with a considerably simpler transcriptome) with 4Mbp transcriptome, their suggestion (30-65M reads) yields a much larger ratio of 7.5-16.25M clusters/Mbp of transcriptome. In contrast, if ~12.5M clusters were sequenced per sample, the ratio would be closer to 3.125, still exceeding ENCODE best-practices for low-abundance/transcript discovery purposes.

    TLDR:

    For a bacteria with 4Mbp transcriptome, do you think is 12.5M clusters/sample sufficient for low-abundance transcript discovery?
    Last edited by Matt.Ralston; 03-30-2014, 12:51 PM.

  • #2
    The Genohub figures seem quite high for a bacteria, I would have said 10M reads would suffice (and I've worked with less).

    You may be interested in this paper:

    Background High-throughput sequencing of cDNA libraries (RNA-Seq) has proven to be a highly effective approach for studying bacterial transcriptomes. A central challenge in designing RNA-Seq-based experiments is estimating a priori the number of reads per sample needed to detect and quantify thousands of individual transcripts with a large dynamic range of abundance. Results We have conducted a systematic examination of how changes in the number of RNA-Seq reads per sample influences both profiling of a single bacterial transcriptome and the comparison of gene expression among samples. Our findings suggest that the number of reads typically produced in a single lane of the Illumina HiSeq sequencer far exceeds the number needed to saturate the annotated transcriptomes of diverse bacteria growing in monoculture. Moreover, as sequencing depth increases, so too does the detection of cDNAs that likely correspond to spurious transcripts or genomic DNA contamination. Finally, even when dozens of barcoded individual cDNA libraries are sequenced in a single lane, the vast majority of transcripts in each sample can be detected and numerous genes differentially expressed between samples can be identified. Conclusions Our analysis provides a guide for the many researchers seeking to determine the appropriate sequencing depth for RNA-Seq-based studies of diverse bacterial species.

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