Our long-term research goal is to understand and predict gene regulation based on DNA sequence information and genome-wide experimental data.
Joined December 2018
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The new updates for Charles McAnany’s preprint “Positional Interpretation of Cis-Regulatory Code and Nucleosome Organization with Deep Learning Models” (biorxiv.org/content/10.1101/…) are up!
We introduce PISA, a tool to visualize the cis-regulatory code. See a recap below:
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(9/10) Our BPReveal package provides tools to engineer sequences with desired properties. For example, we designed mutations to alter a nucleosome’s presence in vivo, and our design was corroborated experimentally.
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(10/10) PISA is, at its core, a way to ask how one stretch of DNA affects a biological signal in its surrounding region. If you want to try it out, our complete software suite is available here: github.com/mmtrebuchet/bprev…
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The @ZeitlingerLab is excited to release @Sergiogma91’s preprint “High-resolution binding data of TFIID and cofactors show promoter-specific differences in vivo” (biorxiv.org/content/10.64898…).
TLDR; TFIID behaves differently based on promoter type. More below:
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(6/7) DPR promoters, which contain downstream sequences favorable for TFIID binding, show the highest levels of downstream TBP. Downstream TBP shows the strongest correlation with TAF2, TAF1 and TAF7, consistent with this being the promoter loading state of TFIID.
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(7/7) Our Model: All promoters use TFIID to load TBP, but TATA promoters additionally allow direct TBP binding to the TATA box. Such dual initiation likely enables faster TBP re-loading and larger transcriptional bursts at TATA promoters.
For more details, check out our work!
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19 Nov 2025
The @ZeitlingerLab is pleased to announce @MelanieWeilert’s preprint “Widespread low-affinity motifs enhance chromatin accessibility and regulatory potential in mESCs” (biorxiv.org/content/10.1101/…). Summary below!
(TLDR; low-affinity motifs are common and strong pioneers in vivo!)
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19 Nov 2025
(12) Putting it together, it seems that low-affinity motifs likely evolve easily in enhancers because (1) they arise often, (2) the syntax is flexible, and (3) the effect is relatively large. Due to motif cooperativity, even small changes can affect enhancer function.
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19 Nov 2025
Thanks to our coauthors @kaelanbrennan , @08Kats05, @haining_jiang, and Sabrina Krueger. Thanks again @rmartinezcorral for your mechanistic modeling, we learned so much from you! Finally, thank you to @JuliaZeitlinger for your guidance and inspiration along this journey!
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