Joanna Achinger-Kawecka

Head of 3D Chromatin Organisation Laboratory @SAiGENCI @UniofAdelaide

[Joanna Achinger-Kawecka @aachinger]

NEW preprint led by @ElyssaCampbell4 with @suscla1, where we used MOFA+ to uncover the rapid 3D chromatin and transcription changes triggered by androgens in prostate cancer. (1)

Check it out here: https://t.co/h4bnFjX2KR

[Archit Ghosh, PhD @ArchitGhosh1]

Spatiotemporal lineage tracing reveals the dynamic spatial architecture of tumor growth and metastasis. @NatureGenet https://t.co/bkvmEJIRdc

[Molecular Cell @MolecularCell]

Transposable element splicing reveals a tumor-enriched class of gene-independent transcripts dlvr.​it/TWDCdV

[Jesse Engreitz @jengreitz]

Our latest preprint:

• Improved split-pool Perturb-seq method
• Gene programs in hiPSC-endothelial differentiation
• New role for Hippo pathway in vitro and in vivo
• Strategy for improving differentiation by faking cell density

https://t.co/EHGJRfpCjk

1/

[Siyuan (Steven) Wang @SStevenWang]

Glad to share our latest publication in @naturemethods: Nondisruptive 3D profiling of combinations of epigenetic marks in single cells.

Epigenetic states and 3D chromatin folding are critical regulators of many genomic functions. While these mechanisms are known to be closely interlinked, studying their relationship remains challenging due to technical limitations. Sequencing-based single-cell or spatial histone modification profiling techniques often suffer from low sequencing read count per cell or per spatial spot, limiting gene-locus-specific analyses at the single-cell level. A recent imaging-based method termed epigenomic MERFISH (Cell 2022) enabled single-cell in situ histone modification profiling in a locus-specific manner with high genomic resolution (~2 kb). However, epigenomic MERFISH is limited to profiling only one epigenetic mark at a time, performs poorly when profiling repressive mark, and as we show in this work, disrupts the 3D genome thus prohibiting 3D genome co-profiling.

To address these limitations, we developed Epigenetic Proximity Hybridization Reaction (Epi-PHR), an imaging-based technology that represents the first epigenetic profiling method that:
🧬1) can simultaneously profile more than one histone modification and chromatin associated protein at numerous genomic loci with high genomic resolution,
🧬2) is non-disruptive and retains 3D chromatin architecture, and
🧬3) inherently provides single-cell, single-copy and in situ information.

We first demonstrated Epi-PHR's sensitivity at small genomic targets of 2 kb. We further showcased multiplexed Epi-PHR to profile combinations of epigenetic marks (including both active and repressive marks) at 200 genes in the same single cells in culture and tissue. Finally, we developed allelic Epi-PHR and combined it with fine-scale chromatin tracing to simultaneously profile epigenetic state and chromatin folding at the same genomic target with parent-of-origin specificity, generating the first single-cell phased examination of histone mark deposition and 3D genome architecture at an imprinted locus by any technique.

In the study of the imprinted locus, surprisingly we found among the maternal copies of this locus, the relationship between the histone mark and a chromatin domain boundary is opposite to what one would expect. This insight cannot be derived from existing bulk allele-specific CUT&RUN and Hi-C approaches. Our unexpected finding was uniquely enabled by allelic Epi-PHR combined with chromatin tracing.

We expect Epi-PHR will find broad application in diverse biomedical contexts. This work was co-led by Dr. Yanbo Chen, Dr. Jonathan Radda, and Dr. Myles Alderman III, and was done in collaboration with my @YaleGenetics colleague Professor Andrew Xiao. Thank you all my co-authors for your contributions to this work!

Link to paper: https://t.co/iXoPN8D8lr

[Erman Akkus @Erman_Akkus]

The genomic and epigenomic evolution of colorectal cancer

https://t.co/Anha5vAXJ4

[Cell @CellCellPress]

In the latest issue! Integrative spatial profiling of 3D genome organization and gene expression in tissue dlvr.​it/TW7W4t

[Anna Cuomo @AnnaSECuomo]

Very proud to share the bulk work from my postdoc, now out in @Nature!!
Introducing phase 1 of the TenK10K dataset, with matched WGS and single-cell RNA-seq from almost 2,000 individuals https://t.co/wXzyYgDDcH 🧬🧵👇 (1/n)

[Kazuhiro Maeshima @kazu_maeshima]

Our new paper @CellReports, led by @katsu_s_minami et al.! 🎉🧬🔬
https://t.co/CrVCefnASc
Machine learning-assisted Repli-Histo labeling and single-nucleosome imaging reveal distinct transcription-dependent chromatin constraints across euchromatin and heterochromatin. Congrats!

[Angelika Feldmann @angifeldmann]

Excited to share PostChicago, our lab's new R/Bioconductor package to analyze Capture-(Hi)C data downstream of loop calling. We present two of its applications: Meta-profiling of interactions and detection of crosslinking artefacts. https://t.co/TGfGe5zgWg

[Gene Regulation @generegulation]

Zheng et al, 2026. Transcription factors read a second regulatory code in chromatin. https://t.co/xC0u3By6ie
"TFs interpret two complementary layers of genomic information: the primary DNA sequence and a second code written into the nucleosome architecture"

[Angelika Feldmann @angifeldmann]

We know a bit about how 3D chromatin interactions are formed, but what do we know about how they are disrupted? We asked this question in our latest preprint: https://t.co/PUhpmSiuUF, focusing on the massive loss of promoter interactions during neuronal differentiation.

[Anders Sejr Hansen @Anders_S_Hansen]

Really enjoyed reading this excellent and thought-provoking new review on long-range enhancer-mediated gene regulation:
https://t.co/kDE2gebxea

[Kazuhiro Maeshima @kazu_maeshima]

Is euchromatin really “open”? 🧬 Using super-resolution imaging🔬 our new study @NatureGenet reveals: Euchromatin forms condensed domains in live cells. Cohesin constrains them and prevents domain mixing for proper transcriptional insulation🚧 🔗https://t.co/HjjYOjycld (1/2)

[Archit Ghosh, PhD @ArchitGhosh1]

Mechanisms and functional implications of long-range enhancer-dependent gene regulation. @NatureGenet https://t.co/7vA7zGdVMb

[Feng Yue @yuefeng_1]

Excited to share Spatial-ATAC-Hi-C @naturemethods, spatial profiling of 3D genome organization + chromatin accessibility in tissue. Excitingly, it detects CNVs and SVs in tumors and reveals spatial heterogeneity.

Great collaboration with @RongFan8.

https://t.co/XO0FhoZepO

[Waggoner Lab @LabWaggoner]

Mapping enhancer–gene regulatory interactions from single-cell data @NatureGenet @robin_andersson @broadinstitute @novonordiskfond @jengreitz
https://t.co/3BBuoaHS3W

[Siyuan (Steven) Wang @SStevenWang]

Glad to share our latest publication in Science! This work reports:
🧬 the first single-cell 3D genome atlas of human tonsil and B cell immunity,
🧬 the first image-based 3D genomics dataset of any human tissue,
🧬 a new function for cohesin loop extrusion, and
🧬 a novel chromatin "curl" structure.

Antibody-mediated immunity relies on the generation of point mutations in rearranged immunoglobulin (Ig) loci of activated germinal center (GC) B cells. This process - called somatic hypermutation (SHM) - allows for antibody affinity maturation but also acts at certain non-Ig sites in the genome, thereby contributing to mutations and chromosomal translocations that drive B cell oncogenesis. My collaborator Prof. David Schatz's previous work indicates that SHM susceptibility is controlled by the cooperative action of cis-acting SHM target elements and the architectural properties of topologically associating domains (TADs), but how the genome is spatially organized across multiple length scales as GC B cells develop and activate SHM and how 3D genome architecture influences the targeting of SHM remains unknown.

To test the functional requirement of 3D genome organization for SHM, in this work we developed a 3D genome and spatial transcriptome toolbox optimized for clinical tonsil tissue, and used it to define single cell 3D genome architectures and nuclear organization in GC B cells undergoing SHM in normal human tonsil samples and in malignant GC-derived human B cell lymphoma cell cultures. Our new work generated the following key insights:

🧬 At the large scale, the nuclear positioning of TADs is linked to SHM susceptibility, with the nuclear periphery being more permissive to SHM and the nuclear interior being more protected from SHM.

🧬 At the fine scale, increased intra-TAD looping contacts in gene regions are associated with SHM susceptibility.

🧬 Most importantly, through rapid, targeted degradation of cohesin component RAD21, our new results provide the first direct evidence that the cohesin mediated loop extrusion is essential for SHM. We further showed that the effects of loop extrusion on SHM cannot be solely attributed to transcription activity changes. This represents a brand new function of the famous loop extrusion process.

🧬 In addition, we serendipitously discovered a novel chromatin “curl” structure – a chromatin loop with two long (~25 kb) stem regions aligned in parallel with each other (distinct from e.g., CTCF anchored chromatin loops where two stems are aligned in an anti-parallel fashion). To our best knowledge, this is the first report of such a structure outside of the contexts of DNA recombination/transposition.

I'd like to thank all my co-authors, especially co-corresponding author legendary immunobiologist Prof. David Schatz, and co-first authors Yubao, Jianshu, and Yuan. It has truly been a wonderful experience working with you.

Link to paper:
https://t.co/rmKT7KE9bA

[Jian Ma @jmuiuc]

Very excited to share our @ScienceMagazine paper on single-cell #3D #genome reorganization in #Alzheimer's disease.
We jointly measured gene expression and 3D genome architecture in individual human brain cells using #GAGEseq, then integrated these data w/ chromatin accessibility and spatial transcriptomics. We uncovered increased #compartment #mingling and distance-dependent rewiring of gene regulatory contacts in AD.
We also developed #Hicformer, a transformer-based model that integrates DNA sequence with 3D genome features to predict cell type-specific gene expression and prioritize candidate regulatory elements.
Huge kudos to co-first authors @zocean636 and @xinyuelu1999; and many thanks to Zhijun Duan @UW, Hansruedi Mathys @PittTweet, & David Bennett @rushalzheimers for the wonderful collaboration, as well as to all our co-authors. @CarnegieMellon @SCSatCMU @CMUCompBio #AlzheimersDisease #3DGenome #SingleCell #AI

https://t.co/G3yPdRMeym

[UCSF Neurosurgery @NeurosurgUCSF]

Out today in @Nature: Daniel Lim, MD, PhD (@danlimlab) and colleagues @UCSF have discovered that genes are controlled not only by DNA sequence and chemical epigenetic marks, but also by where they are located inside the nucleus. 🔗https://t.co/TWEzFAQ9SB
https://t.co/qA6KhH90Fv

[Mark Dawson @MAF_Dawson]

A labour of love!! Incredibly proud of Brian, @BalicJesse and so many in @TheDawsonLab who did a mountain of work. Grateful to all our collaborators. Thanks also to @maxvcg for a lovely N&V.

https://t.co/ZLVPIC2mjr