(UPDATE Jan. 29 2016: Also see my new post "For #CRISPR HDR, use donor oligos that are complementary to the "gRNA strand". A new paper shows why"- this supports the choice of strand to use, but also impacts the placement of the homology arms.)
For this CRISPR question I am going back to this paper: Yang et al, Optimization of scarless human stem cellgenome editing, Nucleic Acids Research, 2013, 1–13 (from the Church lab). Although this paper had a lot of TALEN data it had comparative data for CRISPR-mediated editing. In this case, a 2-bp mismatch was engineered into the CCR5 locus in human iPS cells.
First of all, from now on I will use the term "ssODN" to refer to single-stranded donor oligonucleotides. (Hooray, more jargon!) In Fig. 3d of Yang et al, they presented a nice series of data in which they varied both the length and the strandedness of the ssODN used for editing in conjunction with a single gRNA, which was held constant of course. The mismatch was within the CRISPR target and was always positioned in the middle of the ssODN. However, ssODN length varied from 50 to 110 nt. (Strangely, the top panel has longer ssODNs also drawn schematically but no data for those was shown). In addition, ssODNs corresponding to either the same strand or the complementary strand to the gRNA were tested.
Now, if you're like me, you might naively assume that the complementary-stranded ssODN would be worse in mediating editing because it might base-pair with the gRNA itself, preventing the gRNA from functioning properly. Sounds reasonable? Turns out, the opposite was true - at least for this individual target. Maximal efficiency of editing was achieved with the complementary ssODN at about 70 nt length, with an absolute efficiency of ~1.5% - not too shabby considering it's iPS cells and without any selection. Interestingly, when non-complementary ssODN (i.e., same strand as the gRNA) were used, the efficiency never reached that efficiency, but it did increase with length up to the maximum tested length (110 nt) where it reached about 0.5%. At this length, it was basically the same whether the complementary or non-complementary ssODN was used.
What should one take from this? Well, the trouble with these sorts of tests is that when you test certain parameters you have to keep the other parameters fixed. In this case the gRNA was kept constant. So the peak in efficiency at 70 nt with the complementary ssODN might be a peculiarity of that particular sequence - perhaps it forms a secondary structure that just happens to inhibit the competing NHEJ pathway, for example?
Also, there is a decent theme forming that for mouse oocyte injections, ssODNs should have homology arms of about 60 nt. This puts the minimum length at 120 nt.
P.S. ...another thought added 12/15/14: Note that for the above observation that max. editing efficiency was achieved with a complementary-strand ssODN of ~70 nt, this means the homology arms were each only ~35 nt long. In fact, a 50 nt ssODN was as efficient as a 90 nt ssODN, meaning ~25 nt homology arms were also workable with a complementary ssODN. But the non-complementary ssODN worked better with longer arms. See Fig. 3 from the Yang paper.
Swiech et al. used AAV vectors to mutate target genes in adult mouse brains. This paper is notable for the careful measurement of on-target mutation efficiencies in vivo, including from single cell nuclei, which strongly indicated that about ~65% of transduced brain cells acquired mutations in both alleles of their initial target gene (Mecp2). Off-target effects were apparently low (0-1.6 % rates of mutation at the "top predicted off-target" for each of 3 Dnmt family genes, measured in GFP+ cells). With their AAV vectors, one vector supplies Cas9 production and the other expresses the guide RNA and also GFP; thus fluorescence indicates transduction. They also introduce an AAV vector that coexpresses up to 3 guide RNAs + GFP for multiplexed targeting.
In vivo interrogation of gene function in the mammalian brain using CRISPR-Cas9
Nature Biotechnology. 19 October 2014
Thank you to my colleague Max for pointing this out to me. If you are doing CRISPR on mice, fish or whatever creatures you are working one, and you are direct-Sanger-sequencing PCR products from #CRISPR animals, you know that animals with more than one type of allele will generate confusing, overlapping sequence traces usual extending past the CRISPR cut site. This is because CRISPR (or TALENS and ZFNs for that matter) usually generates indel mutations. Although the sanger data is fine to confirm something got altered by CRISPR, the overlapping peaks make it hard to identify exactly what the indel is. Poly Peak Parser is an easy to use web interface for pulling the alternate allele (e.g. the newly generated indel) out of an .abi or .scf file that has double peaks due to indel heterozygosity. It is designed to be used on PCR Sanger data from F1 heterozygote animals.
Poly peak parser: Method and software for identification of unknown indels using sanger sequencing of polymerase chain reaction products.Hill JT, Demarest BL, Bisgrove BW, Su YC, Smith M, Yost HJ.Dev Dyn. 2014 Aug 27. doi: 10.1002/dvdy.24183. [Epub ahead of print]
Web tool:
http://spark.rstudio.com/yostlab/PolyPeakParser/
The catch is that you have to supply the reference allele sequence (such as wild type), and it really only works well if there are 2 and only 2 alleles embedded in the sanger data, one of which is the reference sequence. Then it will extract the alternate allele from the double peak data. I tried it out using sanger data from a mouse that was confirmed to be a heterozygote for wild type allele + a new, short deletion; Poly Peak Parser quickly returned the alternate allele confirming the 1 bp deletion.
In practice, however, founder animals from CRISPR injections are usually not simply heterozygous for wild type and a new indel allele. They usually have at least two mutated alleles and sometimes more, if they are mosaic. As the authors of this tool state in their paper, Poly Peak Parser is really designed for analyzing F1 animals. So here is a suggested workflow:
1. If you have sanger files from PCRs of founder animals and they clearly have double peaks, try inputting the .scf along with a wild type reference sequence into Poly Peak Parser and see if it returns an alternate allele that looks like it mostly has unambiguous base calls.
2. If the "alternate allele" has lots of ambiguous bases, the animal may be mosaic, or simply has two new but distinct mutations.
Either way, breed founder animals to wild type to get F1s and the data will be much more clear.
Harms et al have created this detailed set of protocols for conducting CRISPR/Cas9 mutagenesis and editing in mouse embryos. Included are more guidelines and instructions for choosing targets, then on to ligation protocols for cloning protospacers in sgRNA expression vectors, in vitro RNA synthesis, pronuclear injection, and follow-up screening/genotyping of founder animals, as well as HDR donor design and considerations. Also a timeline schematic.
Mouse Genome Editing Using the CRISPR/Cas System.Harms DW, Quadros RM, Seruggia D, Ohtsuka M, Takahashi G, Montoliu L, Gurumurthy CB.Curr Protoc Hum Genet. 2014 Oct 1;83:15.7.1-15.7.27. doi: 10.1002/0471142905.hg1507s83.
Far above Cayuga's waters - my alma mater! - there are some excellent scientists using CRISPR to engineer mutations in mice. This paper is from John Schimenti's lab at Cornell and I believe it contains the most thorough review of mouse CRISPR engineering to date.
A Mouse Geneticist's Practical Guide to CRISPR Applications. Singh P, Schimenti JC, Bolcun-Filas E. Genetics. 2014 Sep 29. pii: genetics.114.169771. [Epub ahead of print]
More than merely a review article, it has some additional new data from this group. They tested whether inhibition of the NHEJ pathway could enhance efficiency of CRISPR-mediated homology-directed repair, since these pathways compete following CRISPR cleavage; this was based on similar experiments done in Drosophila using ZFNs to do HDR. The answer seems to be yes, it helps in mouse embryos as well. The compound they used was SCR7, an inhibitor of ligase IV (a key player in NHEJ). Crucially, it seems that SCR7 can be applied directly to mouse embryo culture media with minimal toxicity. Go to Table 2 for the result suggesting a shift in balance from predominantly NHEJ alleles toward more HDR alleles.
