@twangmdphd.bsky.social
Resident physician at Stanford Pathology | Greenleaf Lab | Penn MSTP | Interested in chemical biology, epigenetics, and clinically useful tests.
Sensitive, direct detection of non-coding off-target base editor unwinding and editing in primary cells
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Sensitive, direct detection of non-coding off-target base editor unwinding and editing in primary cells [new]
Direct seq. quantifies off-target base editor & DNA unwinding.
Sensitive, direct detection of non-coding off-target base editor unwinding and editing in primary cells https://www.biorxiv.org/content/10.1101/2025.09.25.678665v1
26.09.2025 04:33 — 👍 0 🔁 1 💬 0 📌 08/ This was a group effort drawing expertise from different parts of the Greenleaf Lab and the larger Stanford Genetics community. A big thank you to @selinjessa.bsky.social, Georgi, Sandy, and @anshulkundaje.bsky.social I am especially grateful to Will for encouraging me to take on this project.
29.09.2025 18:28 — 👍 2 🔁 0 💬 0 📌 07/ There’s much more in the preprint (deep learning of novel T-cell non-coding off-targets, SpRY editors, and comparisons to other methods to name a few), but I won’t give it all away here. Base editors hold immense promise, and we hope our insights help to improve them.
29.09.2025 18:28 — 👍 1 🔁 0 💬 1 📌 0
6/ We also show how deep learning can predict the effects of non-coding edits. Here, an erythroid but not T-cell model predicts loss of DNA accessibility upon editing. The model learns the GATA motif driving this prediction. This site is of course the intended target of Casgevy.
29.09.2025 18:28 — 👍 1 🔁 0 💬 1 📌 0
5/ We extensively optimized beCasKAS to be compatible with primary human T cells and 5moU mRNA delivery. Transient mRNA delivery limits off-target formation, which can be further mitigated by carefully selecting mRNA dose.
29.09.2025 18:28 — 👍 0 🔁 0 💬 1 📌 0
4/ We are able to see the known strand-specific editing patterns of two contrasting editors: eBE (using hAPOBEC3A) and ABE8e. Using plasmid delivery in HEK293Ts, we find these two editors have surprisingly similar absolute editing frequencies.
29.09.2025 18:28 — 👍 0 🔁 0 💬 1 📌 0
3/ beCasKAS makes two measurements at each off-target site. The unwound R-loop appears as a peak, and individual edits appear as mismatched nucleotides.
29.09.2025 18:28 — 👍 0 🔁 0 💬 1 📌 0
2/ We use an N3-kethoxal pulldown probe because it has the same selectivity for ssDNA as the deaminases used in base editing. The cell permeable kethoxal allows us to enrich for unwound Cas9 R-loops that must occur before DNA editing. This selectivity underlies our sensitivity.
29.09.2025 18:28 — 👍 0 🔁 0 💬 1 📌 0
1/ Happy to share our preprint from the Greenleaf Lab: beCasKAS, our method to directly detect CRISPR base editor off-targets in primary cells. We additionally show how non-coding edits can be triaged for epigenetic dysregulation using deep learning.
www.biorxiv.org/content/10.1...
Delighted to share our latest work deciphering the landscape of chromatin accessibility and modeling the DNA sequence syntax rules underlying gene regulation during human fetal development! www.biorxiv.org/content/10.1... Read on for more: 🧵 1/16 #GeneReg 🧬🖥️
03.05.2025 18:27 — 👍 127 🔁 59 💬 2 📌 3
www.biorxiv.org/content/10.1...
Our study published today on #bioRxiv describe the identification of a deaminase that converts 5mC to T, enabling direct sequencing of the human methylome and genome. This achievement was made possible through a collaborative effort across all departments at #NEB.
(1st post @BlueSky) Preprint alert🚨a long thread. Cautions in the use of @nanopore sequencing to map DNA modifications: officially reported “accuracy” ≠ reliable mapping in real applications. We performed a critical assessment of nanopore sequencing (across different versions of models) for the 1/n
20.11.2024 11:41 — 👍 115 🔁 44 💬 6 📌 10who knew it would be easier to get everyone to switch social media platforms than getting them to use hg38
14.11.2024 18:45 — 👍 254 🔁 62 💬 15 📌 13
