-
Notifications
You must be signed in to change notification settings - Fork 1
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Transform and library prep fk8 DMS library #2
Comments
I was thinking about our conversation re replicates and I think it's worth doing 2 more biological replicates (aka two more transformations) so there are 3 total replicates. That will be 12 libraries total and ~60million reads, let me know if you don't think it's worth it @rasi |
@kychen37 Yes, that is a good idea if it is not too much work. |
Update@rasi |
Update@rasi |
@kychen37 I am not sure I understand the comment above. Does this mean you have more RNA going as input into RT, in which case you can get away with smaller PCR reactions? |
Update
|
Update@rasi final libraries:
I was initially concerned that the double band in the tapestation might be incomplete libraries, but even when I tried doing a final extension of 15m at 72C the double band persisted. The double bands are close enough in size that the actual tapestation quantification doesn't say there are two bands (which it did when there were incomplete libraries in my previous runs). So I don't think the double bands are incomplete libraries, they are likely the spike-ins I used, since the 48nt inserts in these spikeins were truncated they are slightly smaller than the real library. Because there are only 1024 variants in this library, I spiked in at higher concentration than I previously have (1/1024 vs 1/200,000), which is why I think they are showing up on tapestation. Overall I think these libraries are ready to sequence. https://github.com/rasilab/protocols_tutorials/issues/80#issuecomment-1569408268 |
GanttStart: 2023-04-20
Background
In #3 and https://github.com/rasilab/rqc_aggregation_aging/issues/101, we identified and validated FK as a stalling dipeptide.
In https://github.com/rasilab/rqc_aggregation_aging/issues/117 we identified other possible targets of RQC (FK and others) using the 8x dicodon (pHPSC1142) library in hel-del cells.
In https://github.com/rasilab/rqc_aggregation_aging/issues/119, we identified endogenous genes with FK/etc stalling type motifs.
In https://github.com/rasilab/rqc_aggregation_aging/issues/120 we designed libraries to test these endogenous motifs and DMS libraries
In https://github.com/rasilab/rqc_aggregation_aging/issues/121 we cloned these libraries as a pool and in https://github.com/rasilab/rqc_aggregation_aging/issues/122 I transformed/library prepped them.
In https://github.com/rasilab/rqc_aggregation_aging/issues/124 we analyzed the deepseq data and found that the FK8 DMS library had very little representation in the library.
In https://github.com/rasilab/rqc_aggregation_aging/issues/129 we re-cloned the fk8 library alone (oKC224) into the library reporter without barcodes (pHPSC1163). Colony PCR + sangseq indicates that only ~12.5% of this library can be expected to be correct, so 6-8K (over 1184 variants) while 40-60K are either parent or have an incorrect insert.
Here I will tranform into WT and Hel2-del yeast and prepare libraries to redo this sequencing experiment.
Strategy
Experiment Links
first replicate: https://github.com/rasilab/rqc_aggregation_aging/blob/master/experiments/kchen_exp74_redo_fk8_dms_deepseq.md
second replicate: https://github.com/rasilab/rqc_aggregation_aging/blob/master/experiments/kchen_exp75_redo_fk8_dms_deepseq_rep2.md
library prep: https://github.com/rasilab/rqc_aggregation_aging/blob/master/experiments/kchen_exp76_library_pre_fk8_dms_replicates.md
snapgene map: https://github.com/rasilab/snapgene_maps/blob/master/DNA%20Files/lab_database/kchen/illumina_amplicons/IKCSC12_R1_fk8_umi_R2.dna
Brief conclusion
In the analysis we felt there was evidence of RT/PCR bias because T/C containing codons were preferentially low in some of the conditions. Other conditions did not have this bias and looked good. I tried redoing the library prep using the correct primer (https://github.com/rasilab/rqc_aggregation_aging/issues/135#issuecomment-1597885161, https://github.com/rasilab/rqc_aggregation_aging/issues/135#issuecomment-1603766677), but the RT and noRT samples no longer separated for most samples. Since the mRNA and gRNA samples are prepped the exact same way with regards to RT and PCR, any bias should normalize out, so we decided not to redo and kept the data from this run.
Checklist before closing issue
lab_database
folder on Snapgene?The text was updated successfully, but these errors were encountered: