Hi all! Wondering if anyone is familiar with a Cre-inducible transgenic line where the nucleus of neurons could be marked with a reporter (GFP, Tdtomato, not picky…). Going to try single-nuc on a subpopulation of cells
Hi @ShanTan. @achamess has uses this strategy previously: Transcriptional Profiling of Somatostatin Interneurons in the Spinal Dorsal Horn | Scientific Reports.
Wow, so helpful. Thank you for sharing @thicunha. @achamess, hoping to ask you a couple of questions about your protocol. Mostly, did you find there was lots of debris (i.e. fat cells) when sorting your nuclei? I don’t see any gradient steps - does the fat separate from other cells when forming a pellet? Thanks!
No gradient. Just FACS. It cleans up the nuclei better than anything else, including gradients.
Thanks very much @achamess. The mice are ordered! 
Did you find there was lots of debris when you brought your sample for sorting?
Yes. Lots of debris. That’s why FACS. If you just try to run that through 10x or whatever, it’ll get all that gunk and diminish the quality of your results.
I have a detailed protocol here
Good luck!
I wanted to touch base with you on this @achamess! I’ve had pretty great success so far with this protocol. However, I am working with a very low number of nuclei due to the nature of the experiement and the cell pop. I’m trying to look at (around 6000 after sorting is complete, before capture on 10x).
The main issue is this; The sort takes hours to get the correct number of nuclei I need, and my sample is packed with debris. If I can clean up my sample a bit before going to the sorter, I think I’d get the amount of nuclei I needed at a quicker rate.
I am now looking into adding a gradient of some kind before subsequent sorting, just to clean my sample up a bit. Do you have any suggestions on gradients gentle enough for nuclei? Any protocols you recommend? I’d like to keep it as close as possible to the protocol you have already provided me, with a gradient added in. Thanks!!
Hey @ShanTan - I’m delighted to hear that the protocol is working for you! I spent a lot of time optimizing it, so I’m glad to hear you can just start using it and get the results.
You definitely could use a gradient. Opti-prep is popular. I have used it. It can be effective for cleanup but I always run into clumping issues and I didn’t feel it was worth it. My colleague Lite in Gereau Lab uses Optiprep all the time. You can get some inspiration here: Human and mouse trigeminal ganglia cell atlas implicates multiple cell types in migraine - PubMed
But it sounds like your problem is low number of target nucs, which the gradient won’t help with. Why not just resuspend your nucs in less buffer so they’re denser and you can sort faster? I usually would do like 500 ul.
Why do you need 6K nucs? You might consider plate-based single-nuc if you have rare populations. i do this frequently now.
Lastly, aren’t you a med student now? 
Props to you for still keeping the science going. It only gets harder as you move along the path.
Thanks for this @achamess! Definitely, med school is time-consuming! But research is still a big love of mine, so I’m trying hard to make it work!
Would you mind expanding on the plate-based single-nuc? Yes, I’m working with a rare population of cells and am assuming we won’t get more than 6-10k cells when pooling samples. There is also a ton of debris, but I’ve been trying the gradient and it makes my final cell number even lower (around 3k). So now I’m thinking of sticking to the previous protocol and trying the plate-based single-nuc. We have a 10x Genomics pipeline here at McGill, but not sure it’s going to work with my current setup. We are consistently losing a huge fraction of cells during the spin-down step and are only able to capture and sequence around 500 cells. Looking to try something else if possible that will be more fruitful for us!
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Sure. There are various low-throughput, high-sensitivity methods for sn/scRNA-seq by sorting single cells/nucs into plate wells. There are fewer cores that offer this. You may have some at McGill. Ask around. Otherwise, you’ll need to look outside. Methods include Smart-seq2, Smart-seq3, Cel-seq2. AIBS has done a lot of their brain work single nuc in plates.
https://www.nature.com/articles/nprot.2016.015
This way, you can go after very rare populations because each well is a reaction. So hundreds of nucs would be totally fine.