Originally posted by HESmith
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Yep, exactly. Sadly my boss insisted on having a library that we can do single read OR paired end on (a money saving move potentially), so I had to design the junction on the first read side. And the samples are just about finished being prepped :/
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I agree with you that hybridization is unlikely, but if it does happen it will be indistinguishable from an actual integration. Among other things, we are interested in mapping low-abundance integrations, so if we aren't able to get the verification sequence on every read, we will likely need to go in and verify a subset of integrations manually, which may not be possible if an integration is present in only one cell for example.Originally posted by HESmith View PostSimcom: Judicious primer design coupled with the appropriate annealing temperature will virtually assure that the primer does not hybridize inappropriately.
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There's an alternative approach, assuming that you have not yet constructed the libraries. Design them so the junction is at the opposite end of the insert, and perform paired-end sequencing. Cluster calling is based only on the first five cycles of read one, so you'll avoid the low-complexity issue.
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I think you are misunderstanding the problem. The issue is, because the first 5nt of read #1 are going to be all identical among clusters, and the machine uses these 5nt to call clusters, the machine has a hard time identifying/differentiating between different clusters (especially close overlapping clusters). So the reason for the gDNA is to add diversity to the sequence, allowing clusters to be called. Hence the reason it needs to be included in the same lane as the sample.Originally posted by GenoMax View PostCan your core not run your samples by specifying a different lane (which is expected to have "normal" DNA) as the "control" lane for that run?
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Simcom: Judicious primer design coupled with the appropriate annealing temperature will virtually assure that the primer does not hybridize inappropriately.
Genomax: the designation of a normal complexity sample as the control lane does not solve the problem (sadly). While it allows the signal thresholds to be set appropriately, it doesn't address the problem of cluster resolution in the low complexity lanes.
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Can your core not run your samples by specifying a different lane (which is expected to have "normal" DNA) as the "control" lane for that run?
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I am sequencing viral DNA/gDNA integration junctions, so I am using that 5 nucleotides of viral DNA as a type of 'verification', that indeed a read contains the junction between viral DNA and gDNA, essentially showing that the sequencing primer is not mis-hybridizing to a similar (non-viral) sequence elsewhere in the genome. We are using a custom sequencing primer, but we prefer that it not hybridize up the the very edge of the viral DNA for reason described above.
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Sequencing a Low diversity library on the HiSeq
I am preparing a custom multiplexed library that will fall into the "low diversity" category. Low diversity meaning the first 5 nucleotides of read 1 will be identical among all clusters. There is a well known and well documented problem with cluster identification for low diversity libraries (outlined here: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3030592/ ).
The above paper and many of the comments on these forums refer specifically to the GAII, and suggest that spiking the library with 40-50% phiX control resolves the cluster calling issue.
Now that the GAIIx has been all but phased out, I need to run my low diversity library on the HiSeq. The problem is that I don't know of anyone that has successfully run a low diversity library on a HiSeq, and my core informed me today that they have tried several times to run low diversity libraries but got awful results on the HiSeq, even after spiking with phiX %50.
My question is, has anyone had success running low a diversity library on the HiSeq? If so, how did you manage to get it to work. Because my study does not require a massive number of reads, I am considering spiking my sample with up to 90-95% gDNA, hopefully drastically increasing the diversity and resolving cluster identification problems. Does anyone have experience running low diversity libraries on the HiSeq that could give me some advice?
Thanks so much!Tags: None
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