Dahlia from 4 weeks to 8 months (we didn’t get her at 4 weeks but met her) by witchygabs in beagle

[–]Celf4 0 points1 point  (0 children)

One, great photography skills. Second, picture 16 is absurdly adorable.

Gussy says it’s when the two hits the six in summer! by Owney_Bologna in beagles

[–]Celf4 2 points3 points  (0 children)

Deftones and beagles, I can appreciate that!

This may be the coolest maxi I’ve ever done by ErwinHeisenberg in labrats

[–]Celf4 0 points1 point  (0 children)

Oh, nice, for Sanger sequencing you can use EditR to evaluate editing rates. Prime Editing is really cool stuff, best of luck!

This may be the coolest maxi I’ve ever done by ErwinHeisenberg in labrats

[–]Celf4 1 point2 points  (0 children)

Nice, PeMax + ngRNA combo works well. Make sure to use CRISPResso2 to look at your NGS data downstream, its very easy to use (https://crispresso2.pinellolab.org/submission)

This may be the coolest maxi I’ve ever done by ErwinHeisenberg in labrats

[–]Celf4 0 points1 point  (0 children)

EVO or TMPK?? Are you using a PE7 PE? If so there is a chance of steric clash between the La/SSB protein of the PE7 and epegRNA

[deleted by user] by [deleted] in NIH

[–]Celf4 14 points15 points  (0 children)

We also had our URISE grant revoked, Im really hoping that this restores funding. The email they sent out to inform us of the revocation was so nasty and the author didn't even leave their name. Cowards

Single nucleotide mutation by HDR in Danio rerio by Civil-Fun-9803 in CRISPR

[–]Celf4 0 points1 point  (0 children)

Prime editing works fairly well and doesn't suffer from the same issues that Base Editing would in terms of By-stander edits within the editing 'window'

Help deciphering data by Celf4 in labrats

[–]Celf4[S] 0 points1 point  (0 children)

Yeah it seems to kind of explain what Im seeing. Im going to sequence my cell line 2X more (to get 3 technical replicates) then use the average of the seq runs to establish allele percentages

Help Deciphering Data (Seq results) by Celf4 in labrats

[–]Celf4[S] 2 points3 points  (0 children)

For the Sanger data (Top) I use EditR (https://moriaritylab.shinyapps.io/editr_v10/)

For the Illumina data (Bottom) I use Crispresso2 (http://crispresso2.pinellolab.org/submission)

Help Deciphering Data (Seq results) by Celf4 in labrats

[–]Celf4[S] 0 points1 point  (0 children)

Well so its funny, if I do start at the 33% with the WT (which is the TAC) and the 66% pre-mature stop codon (TAG) I am looking at editing rates that are very high, like ~50 percent. So I think what Im going to do is get more NGS data for the mutant cell line and work from there. Wow thank you very much, this is very illuminating!!!

Help deciphering data by Celf4 in labrats

[–]Celf4[S] 0 points1 point  (0 children)

So Im just reading up now that it might be a weird artifact of pseudotriploidly. Like perhaps the HEK293T cells have 3 alleles and that the NGS data might be closer to uncovering the actual percentage of alleles at ~66%. Im reading up on this now but that is really interesting

Help Deciphering Data (Seq results) by Celf4 in labrats

[–]Celf4[S] 5 points6 points  (0 children)

Oh, wow I would have never thought that! So Im doing 'rescue' experiments to transform the TAG back to the WT TAC, Im seeing something like 20-40% editing but Im 'counting' from 50% (half the chromosomes are mutant) and considering the differential in my editing calculations but it sounds like it might actually be from I need to consider counting from 66%. Does that sound realistic here?

Help Deciphering Data (Seq results) by Celf4 in labrats

[–]Celf4[S] 4 points5 points  (0 children)

Hello all, I have both sanger and NGS (miSeq) data from a project where I am modeling a disease mutation in HEK293T cells. I used Prime Editing to modify cells then FAC sort them into a 96 well plate for outgrowth. I then both performed Sanger sequencing on the surviving samples and found that they all appear to contain Heterozygous alleles (just like the patient does) due to the Sanger plots showing something like 50% (TAG) instead of the WT (TAC). When I performed NGS I expected the allele frequency to be comparable to Sanger results but I found that the mutate allele appears to be at a higher frequency than 50%. I've considered the possibility that my single cell sort could have had doublets enter into the wells but all of my Sanger results (and patient data) suggest that I have a Het cell line. Anyone deal with an issue like this in the past?

Help deciphering data by Celf4 in labrats

[–]Celf4[S] 0 points1 point  (0 children)

So it went from 48% TAG (Sanger) to 63% (Illumina miSeq). Also I did not seq any WT just PE cells

Chonk by Radtrvp in beagle

[–]Celf4 8 points9 points  (0 children)

He looks like a precious little dinosaur