Hello!
we are currently having mRNA libraries of non-model organisms prepped and have been running into some issues resulting in very broad fragment size distributions.
Neither of the two library construction protocols we have tried (standard Illumina protocols and covaris shearing, afaik) show distinct peaks; The first one produced a range in fragment sizes from about 200 to 700 bps at nearly equal concentrations accross the range. The second resulted in a distribution that is slightly skewed towards larger fragment sizes but is still showing considerable concentrations of shorter fragments.
Seeing that we will use those libraries for de-novo transcriptome assembly, I feel that it would be a bad idea to run the libraries as they are due to the compromises in accuracy of insert size information.
One of the other options we have would be subsampling from these libraries by performing an additional size selection step. Theoretically this should not bias the libraries if shearing was random. I was wondering whether any of you had an opinion on this? What is it that could be causing this broad distribution and can I realistically expect shearing to be (mostly) random?
Also, has anyone tried assembling a library that had similarly broad distributions?
Thanks very much for your help!
Jacky
we are currently having mRNA libraries of non-model organisms prepped and have been running into some issues resulting in very broad fragment size distributions.
Neither of the two library construction protocols we have tried (standard Illumina protocols and covaris shearing, afaik) show distinct peaks; The first one produced a range in fragment sizes from about 200 to 700 bps at nearly equal concentrations accross the range. The second resulted in a distribution that is slightly skewed towards larger fragment sizes but is still showing considerable concentrations of shorter fragments.
Seeing that we will use those libraries for de-novo transcriptome assembly, I feel that it would be a bad idea to run the libraries as they are due to the compromises in accuracy of insert size information.
One of the other options we have would be subsampling from these libraries by performing an additional size selection step. Theoretically this should not bias the libraries if shearing was random. I was wondering whether any of you had an opinion on this? What is it that could be causing this broad distribution and can I realistically expect shearing to be (mostly) random?
Also, has anyone tried assembling a library that had similarly broad distributions?
Thanks very much for your help!
Jacky
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