Nacho Molina

RNA polymerase II initiation factors show different dynamic behaviour upon induced transcription in live cells Transcription by RNA polymerase II (Pol II) requires the ordered action of general transcription factors (GTFs) forming the pre-initiation complex (PIC). How these events unfold kinetically remains un...

Read our new preprint where we uncover a hierarchy in human PIC assembly and establish a quantitative framework that connects factor exchange kinetics to the regulation of Pol II activity in living human cells. doi: doi.org/10.64898/202...
By A. Oravecz and our collaborators @molinalab.bsky.social

Congratulations, Arnaud!

This is not a HiC map! Ever wondered if multiple enhancers get activated simultaneously? We measured chromatin accessibility on thousands of molecules by nanopore to create genome-wide co-accessibility maps. Proud of @mathias-boulanger.bsky.social @kasitc.bsky.social Biology in the thread👇

Activity of most genes is controlled by multiple enhancers, but is there activation coordinated? We leveraged Nanopore to identify a specific set of elements that are simultaneously accessible on the same DNA molecules and are coordinated in their activation. www.biorxiv.org/content/10.1...

Excited to see this published with additional data following our preprint a while back. Cool combination (in our biased view) of controlled TF expression and machine learning to decode chromatin sensitivity. www.sciencedirect.com/science/arti....

Now available in its final form @narjournal.bsky.social !
doi.org/10.1093/nar/...
Find out how we can reconstruct enhancer activity in vivo in the Drosophila embryo using scRNAseq data and Optimal Transport.

#EMBLsinglemolecule was a blast! Happy to host the birth of single molecule genomics as a field and to think about the future with the microscopy crowd. Thanks to participants and organizers!

Carrying on with Session 4 on #EMBLSingleMolecule Day 3 🤓💪🏼
➡️ 'Decoding Gene Regulation at the Single-Molecule Level through Biophysical Modeling of DNA Footprinting Data'
🎙️ Nacho Molina – Institute of Genetics and Molecular and Cellular Biology
@molinalab.bsky.social @igbmc.bsky.social @embl.org

YouTube video by Nikolai Slavov Quantification of gene expression control in a mammalian tissue at single cell resolution | SCP2025

The talk by @andrewleduc.bsky.social at #SCP2025 is on YouTube:

𝐐𝐮𝐚𝐧𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐠𝐞𝐧𝐞 𝐞𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧 𝐜𝐨𝐧𝐭𝐫𝐨𝐥 𝐢𝐧 𝐚 𝐦𝐚𝐦𝐦𝐚𝐥𝐢𝐚𝐧 𝐭𝐢𝐬𝐬𝐮𝐞 𝐚𝐭 𝐬𝐢𝐧𝐠𝐥𝐞 𝐜𝐞𝐥𝐥 𝐫𝐞𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧

youtu.be/adkY6txDyqs?...

🚨 Only a few more days to REGISTER for the TriRhena Gene Regulation Club in Freiburg.

Whether you are new or an established researcher in the Basel-Freiburg-Strasbourg region, this is your meeting when working in transcription, chromatin & gene regulation!

✍️ www.ie-freiburg.mpg.de/gene-regulat...

🟦 Label-free single-cell proteomics (blue bars).

🟧 Multiplexed single-cell proteomics affords higher throughput (orange bars).

⬛️ Proteome depth & quantitative accuracy are comparable.

We aim to make the 🟧 bars taller.

www.parallelsq.org/psmtags

www.biorxiv.org/content/10.1...

For Spanish speakers, this is a fantastic podcast about science and much more!

No doubt, this is one of the most exciting meetings of the year! And we will present our new method, HiddenFoot 😉: www.biorxiv.org/content/10.1...

‼️Last chance to join us in person for #EMBLSingleMolecule! Attend talks, network, socialise, and experience the atmosphere on the campus 🤩

🎫 Register by 3 Jun 👉🏼 http://s.embl.org/grg25-01-bl

🧬RNA processing
🧬Translation
🧬Transcription & chromatin regulation
🧬Method development
🧬Theory

Very cool, Lars! Congrats!

Clonal tracing with somatic epimutations reveals dynamics of blood ageing - Nature The discovery that DNA methylation of different CpG sites can serve as digital barcodes of clonal identity led to the development of EPI-Clone, an algorithm that enables single-cell lineage tracing th...

Out @nature.com: Clonal tracing with somatic epimutations

🧬 Single cell methylome encodes cell state & clonal identity

🔨 EPI-Clone reads out both (+mutations, +RNA) at scale

🩸 Clonal expansions of HSCs are universal from age 50, not driven by CH mutations

doi.org/10.1038/s415...
🧵

Just in case you missed this and it’s something that might interest you. #SingleMoleculeBiology, #Chromatin, #Transcription, #TF, #Nucleosome, #PolII, #Biophysics, #MachineLearning, #ComputationalBiology 👇

Time for a short thread! We developed HiddenFoot, a biophysics-inspired approach to decode single-molecule footprinting data and infer TF, nucleosome, and RNA Pol II binding profiles on individual DNA molecules. One molecule at a time! www.biorxiv.org/content/10.1...

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Thanks!

Dissecting regulatory syntax in human development with scalable multiomics and deep learning Transcription factors (TFs) establish cell identity during development by binding regulatory DNA in a sequence-specific manner, often promoting local chromatin accessibility, and regulating gene expre...

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 🧬🖥️

Thanks!

I'm neighboring the chromatin biology field at the moment and there is a lot I need to understand. Especially, the specific techniques/methodologies in use to study chromatin, however this one looks 🔥🔥🔥.
Many congratulations 👏🏻 🎉 to all those involved!
Hey #ChromatinSky people where are you at 🤩?

Muchas gracias!!!

Finally, if you've made it this far, you might be interested in testing the code. Feedback is very welcome! github.com/MolinaLab-IG...

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HiddenFoot also works with Fiber-seq data! It reveals chromatin structure and nucleosome occupancy heterogeneity at single-molecule resolution driven by TF binding.

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HiddenFoot resolves Pol II and nucleosome occupancy at the HIV-1 promoter, molecule by molecule. Under transcriptional inhibition (TLD), Pol II footprints vanish, while nucleosome occupancy at the +1 and −1 positions increases.

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HiddenFoot infers pairwise interaction energies from single-molecule data and compares them to simulated equilibrium profiles to distinguish true TF–TF cooperativity from nucleosome-mediated co-binding.

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HiddenFoot is a thermodynamics-based model that integrates known TF PWMs and nucleosome occupancy to efficiently evaluate all possible non-overlapping binding configurations. It fits model parameters using both stochastic gradient descent and MCMC.

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Time for a short thread! We developed HiddenFoot, a biophysics-inspired approach to decode single-molecule footprinting data and infer TF, nucleosome, and RNA Pol II binding profiles on individual DNA molecules. One molecule at a time! www.biorxiv.org/content/10.1...

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