(1/8) Excited to share our latest preprint introducing ACCESS-ATAC, a high-resolution approach to measure chromatin accessibility and transcription factor binding:

(8/8) Plus we’re not the only ones who have realized the power of Ddd enzymes in chromatin analysis: check out the work from @brian_b_liau and colleagues combining DddA and CRISPR to dissect how sequence impacts chromatin state:

(7/8) In sum, ACCESS-ATAC improves the resolution of ATAC-seq and opens up a new ability to analyze single-allele TF co-occupancy. Want to try it? Reach out-- we have built flexible experimental and computational workflows and would be happy to share reagents and expertise!.

(6/8) Through OccuPIE, we find that a large fraction of TFs show periodicity in their preference to co-occupy adjacent motifs. This periodicity approximates the turn of the DNA helix. This fascinating finding unlocks a key pattern that underlies genomic TF binding site selection.

(5/8) The coolest feature of ACCESS-ATAC is the qualitatively new ability to analyze allelic TF occupancy and co-occupancy. We use a customized computational pipeline, OccuPIE, to generate a first-in-class allelic binding atlas of TFs across the genome.

(4/8) ACCESS-ATAC significantly improves TF binding site prediction, and in single-cell ACCESS-ATAC experiments, we resolve TF binding profiles at equal sensitivity to ATAC-seq with 2-3x fewer cells.

(3/8) ACCESS-ATAC is simple to employ—we add a motif-agnostic Ddd enzyme (DddSs) to the standard Tn5 (ATAC) treatment of bulk or single-cell nuclei and use nextgen sequencing to read out chromatin accessibility. It adds no additional cost or effort to the conventional workflow.

(2/8) Led by @TiannnYuu, @ZhijianLi3, and Ellie Gibbs in a joint effort with the @lucapinello lab, we harness the genome editing abilities of double-stranded DNA cytosine deaminase (Ddd) enzymes to overcome the resolution limitations of ATAC-seq.

RT @Fusion_Conf: ‼️⚠️Registration Deadline TODAY!⚠️‼️ .Register now for the 'From Genetic Discoveries to Gene Function in Human Diseases'….

We are very happy to see that our manuscript, 'Joint Genotypic and Phenotypic Outcome Modeling Improves Base Editing Variant Effect Quantification,' is now published in @NatureGenet . Congratulations @JayoungR.

RT @JayoungR: Excited to share our work introducing BEAN🫘, a pipeline that greatly improves the power of CRISPR base editing screens🚀!. BEA….

RT @lucapinello: Absolutely thrilled to share this incredible work led by @JayoungR ! A huge shoutout to the collaborative efforts with @Sh….

RT @ccassa: I’m excited to share REGatta, a project by @James_D_Fife from @CassaLabBWH which uses biobank data to estimate the clinical ris….

A huge thank you to everyone that contributed to this project since we started it way back in pre-COVID times! @miahamilton5 @minja_bio @ccassa @akinci_ersin @Glettre @3xon5kip and all the members of @sherwoodlab Check out our full manuscript at 16/16.

We are excited to apply our pipeline to get to the bottom of the genetics of lipids and cardiovascular disease risk, unraveling new cellular mechanisms beyond LDL uptake and pinpointing genetic variant effects using more precise CRISPR tools. 15/16.

Altogether, we show that combining CRISPR screening with biobank genome analysis can vastly expand our understanding of the genetics of LDL levels, defining a new cholesterol-altering pathway and flagging new therapeutic candidates. And this is just the beginning. 14/16.

When we silenced OTX2 in mice, they showed a ~40% drop in LDL, on par with the change seen upon suppression of PCSK9, the target of FDA-approved cholesterol-lowering drugs. We found that OTX2 deficiency makes cells act as if constantly starved, so they gobble up more LDL. 13/16

What about genes that lower LDL levels when suppressed? Did our pipeline identify new therapeutic candidates to reduce heart disease risk? We zeroed in on one such candidate, OTX2. People with variants in this gene have substantially lower LDL levels. 12/16.