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Old 12-27-2016, 06:46 PM   #241
Timer123
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Default Tn5 assemble and single cell sequence

I am a student from Huazhong Agricultural University,Wuhan,China.Now I am working with the single cell RNA-seq library preparation,because we have so many sample to operate, we could not afford this by use standard Nextera kit,so we have to produce in-house Tn5 transposase by reference the article of "Tn5 transposase and tagmentation procedures for massively scaled sequencing projects"Picelli et al.Genome Research.2014.
In the assemble protocol,where I can get a most suitable the phosphorylation primer:
Tn5MErev, 5'-[phos]CTGTCTCTTATACACATCT-3',and is there any detail protocol or notes about Tn5 transposase assemble and purification ?
And for the smart-seq2, how to order the TSO primer also a problem in China, I know the Exiqon have the patent for the LNA,and order is very difficult. So how to order it faster or is there any good alternative company I can get this?
Thank you for your generous help!
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Old 12-30-2016, 02:06 AM   #242
Simone78
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Quote:
Originally Posted by Timer123 View Post
I am a student from Huazhong Agricultural University,Wuhan,China.Now I am working with the single cell RNA-seq library preparation,because we have so many sample to operate, we could not afford this by use standard Nextera kit,so we have to produce in-house Tn5 transposase by reference the article of "Tn5 transposase and tagmentation procedures for massively scaled sequencing projects"Picelli et al.Genome Research.2014.
In the assemble protocol,where I can get a most suitable the phosphorylation primer:
Tn5MErev, 5'-[phos]CTGTCTCTTATACACATCT-3',and is there any detail protocol or notes about Tn5 transposase assemble and purification ?
And for the smart-seq2, how to order the TSO primer also a problem in China, I know the Exiqon have the patent for the LNA,and order is very difficult. So how to order it faster or is there any good alternative company I can get this?
Thank you for your generous help!
I replied you in a private message, take a look there!
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Old 01-02-2017, 12:03 AM   #243
Timer123
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Default Tn5 assemble and single cell sequence

I have read that,it's very useful for me, thank you very much!
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Old 01-18-2017, 11:45 PM   #244
rnaseqmonkey
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Did anyone solve the mystery of bacterial rRNA contaminations yet?
We're also seeing this pop up inversely correlated to the endogenous RNA amount. We use Maxima H- RT for our libraries, too!
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Old 04-03-2017, 12:20 AM   #245
RevTK
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Dear all,
I`m working with laser-capture microdissected cells (e.g. isolated a few hundred cell equivalents from frozen tissue sections) from mouse tissue. I`m using the single-cell lysis buffer from clontech to generate a lysate of my captured cells right after LCM and then use that lysate directly for the cDNA generation. According to this publication, SMART-Seq2 from this lysate should provide decent results: https://www.ncbi.nlm.nih.gov/pubmed/27387371

After 21 preamplification cycles I get the cDNA profiles seen in the attached .pdf.
The kit used is the SMART-Seq2 Ultra-low v3.

Instead of the expected peak at 1.5-2kb, I get a wide range of smaller peaks across the whole range.
Does this mean degraded RNA? Or possibly fragmented due to the UV laser?
Do these profiles look like too many preamp-cycles were used?
In the above mentioned publication, they also seem to get somewhat of a shift towards smaller cDNA fragments when directly lysing 50 to 120 cells.
But they still got good sequencing results.

If my RNA is fragmented, oligo-dT priming / the used kit won`t work properly I assume.

Is there any chance for a successful sequencing from these kinds of samples? Would switching to a totalRNA-kit that uses random priming improve my chances?

Thank you for your help.
Attached Files
File Type: pdf 21preamp_samples.pdf (211.5 KB, 47 views)

Last edited by RevTK; 04-03-2017 at 12:22 AM.
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Old 08-16-2017, 10:14 AM   #246
lmw.bio
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Arrow Sequencing small cDNA libraries

Hi RevTK, wondering if you found a way to sequence your small cDNA samples? Or if you figured out why you got the shorter reads in the first place?
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Old 08-16-2017, 11:54 PM   #247
RevTK
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We tried to make another library with the mammalian pico kit, but the single-stranded DNA in my samples served as template for the RT used in that kit and we got mostly amplification of that.
We just went with the Smart-Seq2 anyways and we got sequencing results. I got about 9 Million reads per sample, out of which between 3 to 6 Million reads were mappable.
Thus I had the libraries sequenced on a second lane, to increase the amount of reads I got per sample.
Now I've around 9-11 Million reads for each sample that were mapped successfully and my results show that I was successful in capturing my target tissue.

There's just some difficulties with a lot of targets that have very low amounts of reads (< 10 reads), of course for these you get gigantic fold-changes if you conduct differential expression analysis using e.g. DESeq2.
I got quite a bit of PolyT contamination in my reads, explaining why a decent amount of the raw reads ended up being unmappable.

I think the data I generated in this way is not of the highest quality, but it can be used for its intended purpose.
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Old 11-21-2017, 08:49 PM   #248
shilpij01
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Default rRNA depletion solution

Hey,
I was just wondering if there is any way to make the rRNA depletion solution on our own?
Thanks
SJ
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Old 11-21-2017, 11:20 PM   #249
nucacidhunter
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Quote:
Originally Posted by shilpij01 View Post
Hey,
I was just wondering if there is any way to make the rRNA depletion solution on our own?
Thanks
SJ
Look at this RNAseH based method: http://journals.plos.org/plosone/art...one.0042882#s4
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Old 11-22-2017, 04:54 AM   #250
Simone78
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Quote:
Originally Posted by shilpij01 View Post
Hey,
I was just wondering if there is any way to make the rRNA depletion solution on our own?
Thanks
SJ
Hi,
there are multiple options. It mostly depends on which method you want to use for depletion: RNAse H, DSN method post-amplification, bead capture. HEre´s a quick summary but let me know if you need more details:
- US Pat 9,428,794: Ribogone from Takara/Clontech
- US Pat 20150299771: Morlan and Sincropi oligos, SDRNA method (see also the 2012 PLoS One paper mentioned below)
- modified SDRNA from Adiconis et al. (Nature Methods 2013, sequences in the Supplementary)
- Probe-directed Degradation, PDD as in Archer et al. (BMC Genomics 2014). They used DSN (Duplex Specific Nuclease), an enzyme also present in Illumina library prep kits and used for normalization. Plenty of papers on the subject are available.
- US Pat 20090137415: method from Euclid Diagnostics (company doesn´t exist anymore, as far as I know)
- EU Patent WO 2011/019993: method used by Epicentre
- US Pat 20160362680: method used by Nugen Technologies (AnyDeplete kit)
- EU Pat WO 2014044724: method used by Qiagen (GeneRead rRNA depletion kit)

Have fun!
/Simone
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Old 12-07-2017, 07:14 AM   #251
skannan4
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Default ERCC stability

Sorry if this has been addressed before on this thread or elsewhere, but for those using ERCC spike-ins, how stable are they? Say, for example, we are using 1:100,000 dilution - how stable is this at -80C?
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Old 12-09-2017, 06:29 AM   #252
Simone78
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Quote:
Originally Posted by skannan4 View Post
Sorry if this has been addressed before on this thread or elsewhere, but for those using ERCC spike-ins, how stable are they? Say, for example, we are using 1:100,000 dilution - how stable is this at -80C?
it is not recommended to freeze and thaw them more than 4 times, according to Ambion. Upon arrival we generate hundreds of tubes with 15 ul of our final dilution (1:4M or 1:40M). 15 ul is the volume necessary for a 384-w plate in our settings, so every tube is enough for 1 plate or 10 plates if using the lower dilution. In this way we can take a single vial when we need it and throw away any leftover.
However, even this is apparently not enough to make experiments very comparable, according to a recent paper where they saw that every freeze and thaw cycle decreases the amount of ERCC by 20%: https://www.ncbi.nlm.nih.gov/pubmed/28263961

...just the last of the many issues of using ERCC!

Best,
Simone
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