We have perennial issues with obtaining sane/consistent library concentrations prior to clustering. Those of you with a HiSeq will probably have this same problem, intermittently, if not persistently.
We had a particularly vexing set recently.
These all were TruSeq RNA prep libraries with a few protocol changes. Briefly, since we often do 2x101 PE de novo RNA seq, we usually back off on the fragmentation time to generate longer inserts. Then, to compensate we also use 0.8x Ampures in most places in the protocol. Just this batch we added a single, "hi-cut" Ampure, where we precipitated that part of the library that came down with a 0.5x Ampure cut and then recovered the molecules left in the supernatant (with more Ampure).
Also, we do 1/2 reactions. Pretty much just cut the volume of everything in half. (We started doing this because the multi-month back-orders for these kits made them too precious to waste.) Also, 15 cycles of enrichment PCR is way too high. We always cut that back. In this case to 10 cycles.
Anyway, the TruSeq RNA kit is a champ and almost always delivers a large library. We did per-library qPCRs and made pools based on the concentrations we obtained. I'll spare you the gory details. (And they are gory.) Each pool has (ostensibly) equal contribution of anywhere from 8 to 14 libraries. So this post goes into a little detail about 4 pools, their titrations and final cluster densities.
Here are the Agilent DNA High Sensitivity chip results for the 4 pools:
![](http://www.genomics.purdue.edu/~pmiguel/technical/2012Posts/Pool1.png)
![](http://www.genomics.purdue.edu/~pmiguel/technical/2012Posts/Pool4.png)
![](http://www.genomics.purdue.edu/~pmiguel/technical/2012Posts/Pool5.png)
![](http://www.genomics.purdue.edu/~pmiguel/technical/2012Posts/Pool6.png)
Here is a table of results:
![](http://www.genomics.purdue.edu/~pmiguel/technical/2012Posts/Run155_conc_table.png)
"len" is just the length as called by the Agilent Chip. (But you can see from the images that most of the library is in the 250-550 bp range.) Since all the assays we use are "mass" assays we do a correction for size, based on this number.
The next 3 columns are 3 different methods of estimating the concentration of the libraries. The first is just what the Agilent chip estimates. "qPCR nM" is what we calculate using a KAPA kit, but with an Illumina phiX library as the standard. Our high standard is 1 nM just to give you an idea of where we are in the concentration scale. For fluorimetry we take an aliquot of the sample and denature it (95 oC for 3 minutes, followed by chilling on ice) and then use the ribo-green fluor with its included rRNA standard. This is weird, I know, but the idea is that lots of your library might be single stranded, so you want that counted. Double-stranded (pico-green) fluorimetry will not show the single stranded stuff. Alas, pico-green's reading for double-stranded molecules is not the same as for single-stranded molecules. But I think this assay will be less confounded by mixtures of single-stranded and double-stranded molecules.
Distressing that both qPCR and fluorimetry give higher estimates of the concentration. Anyway, we decided to go with the fluorimetry values for making what we called "presumptive 2 nM" stocks. Our experience is that the larger the dilutions necessary to read 2 nM, the further from 2 nM they end up being upon re-quantification.
Then we take the "2 nM" stocks and do a final qPCR on them. They are all high. Then we dilute them again to what will hopefully be 2 nM based on those values. (We use 0.1% Tween as a surfactant in our dilutant.) Then fire up a run, loading a single pool per lane in the flow cell at 14 pM. 750-850 is spec for v3 chemistry. But our HiSeq seems to give excellent results even when the cluster density is above 1000. So we would rather be higher -- especially for the last 2 pools. Still, nothing to complain about. Except for the enormous time and effort it took to dial the concentrations in.
As I mention above, I left out details about the initial qPCR to create the pools. Also, the early qPCR results were so wacky I decided to "buy a vowel" by doing a 50 cycle MiSeq run on 2 of the pools (pools 2 and 3). Using the result of those we ended up at 907 and 1050 K/mm^2 cluster densities -- exactly where we wanted to be. I only did 2 of the pools on the MiSeq because any other combination of pools resulted in index overlaps.
Since we routinely have >50 libraries per flow cell, doing a MiSeq run for titration is probably not in the cards until we switch to dual indexing -- which would give us at least 96 unique index pairs.
Any comments?
--
Phillip
We had a particularly vexing set recently.
These all were TruSeq RNA prep libraries with a few protocol changes. Briefly, since we often do 2x101 PE de novo RNA seq, we usually back off on the fragmentation time to generate longer inserts. Then, to compensate we also use 0.8x Ampures in most places in the protocol. Just this batch we added a single, "hi-cut" Ampure, where we precipitated that part of the library that came down with a 0.5x Ampure cut and then recovered the molecules left in the supernatant (with more Ampure).
Also, we do 1/2 reactions. Pretty much just cut the volume of everything in half. (We started doing this because the multi-month back-orders for these kits made them too precious to waste.) Also, 15 cycles of enrichment PCR is way too high. We always cut that back. In this case to 10 cycles.
Anyway, the TruSeq RNA kit is a champ and almost always delivers a large library. We did per-library qPCRs and made pools based on the concentrations we obtained. I'll spare you the gory details. (And they are gory.) Each pool has (ostensibly) equal contribution of anywhere from 8 to 14 libraries. So this post goes into a little detail about 4 pools, their titrations and final cluster densities.
Here are the Agilent DNA High Sensitivity chip results for the 4 pools:
![](http://www.genomics.purdue.edu/~pmiguel/technical/2012Posts/Pool1.png)
![](http://www.genomics.purdue.edu/~pmiguel/technical/2012Posts/Pool4.png)
![](http://www.genomics.purdue.edu/~pmiguel/technical/2012Posts/Pool5.png)
![](http://www.genomics.purdue.edu/~pmiguel/technical/2012Posts/Pool6.png)
Here is a table of results:
![](http://www.genomics.purdue.edu/~pmiguel/technical/2012Posts/Run155_conc_table.png)
"len" is just the length as called by the Agilent Chip. (But you can see from the images that most of the library is in the 250-550 bp range.) Since all the assays we use are "mass" assays we do a correction for size, based on this number.
The next 3 columns are 3 different methods of estimating the concentration of the libraries. The first is just what the Agilent chip estimates. "qPCR nM" is what we calculate using a KAPA kit, but with an Illumina phiX library as the standard. Our high standard is 1 nM just to give you an idea of where we are in the concentration scale. For fluorimetry we take an aliquot of the sample and denature it (95 oC for 3 minutes, followed by chilling on ice) and then use the ribo-green fluor with its included rRNA standard. This is weird, I know, but the idea is that lots of your library might be single stranded, so you want that counted. Double-stranded (pico-green) fluorimetry will not show the single stranded stuff. Alas, pico-green's reading for double-stranded molecules is not the same as for single-stranded molecules. But I think this assay will be less confounded by mixtures of single-stranded and double-stranded molecules.
Distressing that both qPCR and fluorimetry give higher estimates of the concentration. Anyway, we decided to go with the fluorimetry values for making what we called "presumptive 2 nM" stocks. Our experience is that the larger the dilutions necessary to read 2 nM, the further from 2 nM they end up being upon re-quantification.
Then we take the "2 nM" stocks and do a final qPCR on them. They are all high. Then we dilute them again to what will hopefully be 2 nM based on those values. (We use 0.1% Tween as a surfactant in our dilutant.) Then fire up a run, loading a single pool per lane in the flow cell at 14 pM. 750-850 is spec for v3 chemistry. But our HiSeq seems to give excellent results even when the cluster density is above 1000. So we would rather be higher -- especially for the last 2 pools. Still, nothing to complain about. Except for the enormous time and effort it took to dial the concentrations in.
As I mention above, I left out details about the initial qPCR to create the pools. Also, the early qPCR results were so wacky I decided to "buy a vowel" by doing a 50 cycle MiSeq run on 2 of the pools (pools 2 and 3). Using the result of those we ended up at 907 and 1050 K/mm^2 cluster densities -- exactly where we wanted to be. I only did 2 of the pools on the MiSeq because any other combination of pools resulted in index overlaps.
Since we routinely have >50 libraries per flow cell, doing a MiSeq run for titration is probably not in the cards until we switch to dual indexing -- which would give us at least 96 unique index pairs.
Any comments?
--
Phillip
Comment