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Old 04-21-2016, 08:59 AM   #1
chris11
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Location: texas, us

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Post nextera xt library prep for bulk RNA-Seq of mouse

Hi All,

We purchased an illumina nextera xt DNA library prep kit and accompanying 96 index kit with the goal of doing single cell RNA-seq on mouse cells following single cell sorting on a fluidigm C1.

For a number of reasons, we put the single cell RNA-Seq project on hold, but still want to use up the nextera xt kit and indexes in our lab.

Has anyone ever used the xt kit to perform any type of bulk RNA-Seq (i.e. not single cell) using eukaryotic cells before? If not does anyone have any tips or suggestions on how to try this?

In the past, we have used the standard nextera kit (not the xt) for bulk RNA-seq of mouse cells, but that is not currently an option.

Thanks

Last edited by chris11; 04-21-2016 at 09:01 AM. Reason: typo
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Old 04-21-2016, 09:09 AM   #2
fanli
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We just did a bulk cell (mouse) RNA-seq using a Clontech kit and Nextera XT. Client wanted to keep the protocol similar to the Fluidigm C1 prep in case they go and do single cell later.

The only issue we encountered was in getting the right cluster density on a NextSeq 500 (see thread here). You might want to use qPCR quantification as suggested by @pmiguel instead of Qubit/Bioanalyzer.

My thinking is that you should be really careful about quantification/purity of your input DNA to the XT kit as it is easy for the fragment sizes to be larger than you'd like.
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Old 04-21-2016, 04:48 PM   #3
nucacidhunter
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You only can only use 1 ng of ds-cDNA in each reaction and you would obtain good yield for libraries as well. The issues I see are:

1- If you are looking for differential expression, sampling might be erratic at that input level for reproducible results. Some expressed genes even might not be converted to library and missed. You may try preparing 3 XT and 3 higher input library libraries (by shearing ds-cDNA) from the same cDNA to check reproducibility and gene representation in different inputs.

2-In single-cells only a fraction of genes are expressed so 1 ng or less input would have good representation of transcripts.
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