Can anyone give me clear-cut instructions on how I can design a homology arm for HDR after using Crispr-Cas9 to delete my target gene. How could i introduce the silent mutations in my arms, the flank sequences, everything. Should I clone my HDR template in a plasmid or not and how to do that?
Hi hiname,
For a precise CRISPR-Cas9-mediated gene deletion via HDR, your donor template should consist of two homology arms (typically 500–800 bp each) flanking the desired deletion junction, with any intended knock-in sequence (if applicable) in between. To design them, use tools like Benchling or SnapGene: input your target genomic sequence, select gRNA sites at the deletion boundaries, and generate arms from ~500 bp upstream and downstream of each cut site.
To introduce silent mutations, focus on the PAM (NGG) and seed sequence (first 12 nt of spacer) of your gRNA in the downstream arm—alter synonymous codons (e.g., via wobble positions) to disrupt re-cutting without changing the protein. Aim for 3–5 mismatches total; verify with codon tables or software to ensure no amino acid change.
Flank sequences are simply the homology arms themselves, chosen for high GC content (40–60%) and minimal repeats to boost efficiency. Order as dsDNA oligo or synthesise as ssODN for short templates (<200 bp total); for longer ones (>1 kb), clone into a plasmid backbone like pUC19 using Gibson assembly or restriction ligation—linearise the vector, insert your annealed arms + junction via T4 ligase, transform into competent E. coli, and purify via miniprep.
Transfect the plasmid (1–2 µg) alongside Cas9/gRNA into cells 24 h post-seeding for optimal HDR. Test knock-outs via PCR/Sanger across the junction.
Kevin
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You are asking for quite a lot of help here, and you haven't demonstrated any prior research. Whilst on SO, they do have a post describing how to ask a good question.
I would also say that this question is best for your PI, a postdoc, or a PhD student versed in CRISPR. Short of that, there are many resources from places like snapgene or benchling that show up with a simple google and would be a good starting point.