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Stein Aerts @steinaerts.bsky.social · 18d

We have two open positions for a ML and a LLM engineer to launch a machine learning expertise unit in our center @vibai.bsky.social, see vib.ai/en/opportuni...

vib.ai

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Alexandra P @alexanrna.bsky.social · Sep 10

1/ First preprint from @jdemeul.bsky.social lab 🥳! We present our new multi-modal single-cell long-read method SPLONGGET (Single-cell Profiling of LONG-read Genome, Epigenome, and Transcriptome)! www.biorxiv.org/content/10.1...

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scverse @scverse.bsky.social · Sep 10

We will have our next community meeting on Tuesday, 2025-09-16 at 18:00 CEST! Niklas Kempynck will be presenting on CREsted, a package for training enhancer models on scATAC-seq data.
(Zoom registration link and more information in thread!)
🧵

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Alexandra P @alexanrna.bsky.social · Sep 10

12/ Additionally thanks to: @vschpc.bsky.social , @fwovlaanderen.bsky.social , @vib-ccb.bsky.social , @singlecellcore.bsky.social , Genomics Core Leuven, and KU Leuven.

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Alexandra P @alexanrna.bsky.social · Sep 10

11/ This was a huge collaborative effort, so shoutout to Ruben, Marios, Luuk, Joris in the lab, and our collaborators @jancools.bsky.social , Margo Aertgeerts, Heidi Segers.

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Alexandra P @alexanrna.bsky.social · Sep 10

10/ We anticipate SPLONGGET to work on any standard 10X Multiome-compatible sample.
If you want to learn more, read the full pre-print here: www.biorxiv.org/content/10.1....

Long-read single-cell genome, transcriptome and open chromatin profiling links genotype to phenotypes.

Current single-cell multiomics methods typically provide limited genomic information, constraining genotype-phenotype studies. To address this gap, we developed SPLONGGET (Single-cell Profiling of LON...

www.biorxiv.org

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Alexandra P @alexanrna.bsky.social · Sep 10

9/ Taken together, SPLONGGET keeps the quality and ease of use of 10X Multiome and additionally unlocks the whole-genome and full-length transcriptome, allowing us to study the genotype-to-phenotype effects of somatic variation.

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Alexandra P @alexanrna.bsky.social · Sep 10

8/ With SPLONGGET we were able to figure out the exact molecular mechanisms underpinning CAR T-cell therapy resistance. At relapse, we identify an ~8 MB deletion encompassing CD19 as well as 4 unique SNVs in conserved splice site motives that lead to intron retention and non-functional transcripts.

IGV screenshot of cDNA reads at CD19 region with multiple SNVs in brackets.

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Alexandra P @alexanrna.bsky.social · Sep 10

7/ We further explore the effect of CNAs on gene expression and chromatin accessibility. For example, we can observe changes between D0 and Q1, when isochromosome 7 is formed (p-arm lost and q-arm gained).

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Alexandra P @alexanrna.bsky.social · Sep 10

6/ SPLONGGET also allowed us to comprehensively detect different types of variation including SNP and SVs across time points. Importantly, we identify various CNVs from this data, including the ones which are only present at later time points. We can also look at CN profiles of individual cells.

Copy number profiles for individual cells and circors plot with different variants inlcuding SNP and SVs

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Alexandra P @alexanrna.bsky.social · Sep 10

5/ With the SPLONGGET transcriptome and accessibility data we identified different tumour subclones and immune populations. To gain more insight into gene regulatory changes over time, we ran SCENIC+ from our collaborators at @steinaerts.bsky.social lab and identified key regulators, including ERG.

UMAP projection of ATAC and RNA data including time point and cell type annotations

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Alexandra P @alexanrna.bsky.social · Sep 10

4/ With our collaborators, @jancools.bsky.social, Margo Aertgeerts, and Heidi Segers we applied SPLONGGET to longitudinal samples from a case of B-ALL to follow its evolution from diagnosis through therapy and ultimately resistance to anti-CD19 CAR T-cell therapy.

fishtail plot showing different sampled timepoints and different cloned detected.

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Alexandra P @alexanrna.bsky.social · Sep 10

3/ Libraries can also be used for target enrichment and are backwards compatible with short reads.

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Alexandra P @alexanrna.bsky.social · Sep 10

2/ We adapted @10xgenomics.bsky.social Multiome to retain all tagmentation fragments (not just short ATAC ones) and intact cDNA. Sequencing these libraries on @nanoporetech.com simultaneous full-length transcriptome, open chromatin and whole-genome data from 1000’s of cells.

the data generation protocol visualisation

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Alexandra P @alexanrna.bsky.social · Sep 10

1/ First preprint from @jdemeul.bsky.social lab 🥳! We present our new multi-modal single-cell long-read method SPLONGGET (Single-cell Profiling of LONG-read Genome, Epigenome, and Transcriptome)! www.biorxiv.org/content/10.1...

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FlyBase @flybase.bsky.social · Aug 15

FlyBase needs your help! We ask that European labs continue to contribute to Cambridge, UK FlyBase, whereas US and other non-European labs can contribute to US FlyBase. For more information and how to donate: wiki.flybase.org/wiki/FlyBase...

FlyBase:Contribute to FlyBase - FlyBase Wiki

wiki.flybase.org

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Dr. Lucky Tran @luckytran.com · Aug 24

"This could be the difference whether your child gets cancer. Are you willing for them to die because the therapy for them is delayed?"

Powerful video with voices from top US scientists on the very real and devastating impacts of the funding cuts.

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FlyBase @flybase.bsky.social · Jun 3

We currently have a call for support that has gone out to European labs, to support FlyBase-UK. We are asking our colleagues from labs in the US and other countries to wait for a similar call to them that will go out in the near future, to support the US sites. We thank you for your patience.

Mark A. Hanson @hansonmark.bsky.social · Jun 3

URGENT: FlyBase has lost practically all its funding overnight; even user fees are tied up in denied grant funding. 🤬🤯

Any lab using @flybase.bsky.social please donate using the link in post below.

This incredible community, on whose backs our #Drosophila labs depend, can't be left out to dry.

Marc Dionne @marcsdionne.bsky.social · Jun 3

My lab studies bacterial infections. We spend a lot of time looking at (or for) species-specific genetic and genomic databases for hosts and microbes. FlyBase is the best of all—there is literally no comparison. Its existence is under threat. Please donate.
www.philanthropy.cam.ac.uk/give-to-camb...

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VIB-KU Leuven Center for Brain & Disease Research @cbdresearch.bsky.social · May 27

🤸‍♂️ We once again teamed up with TAJO vzw — an organization combatting early school leaving, and allowing youth from vulnerable home situations to enter society autonomously and prepared — to inspire young people to get interested in neuroscience!

Find out more 👉 cbd.sites.vib.be/en/news#/new...

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Oxford Nanopore @nanoporetech.com · May 22

Our spotlight winner, Ruben Cools, presented his full talk exploring how they are bridging genotype and phenotype through long Oxford Nanopore read, single-molecule multiomics. #NanoporeConf

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VIB.AI @vibai.bsky.social · May 6

VIB.AI's International PhD call is now open!
https://tinyurl.com/53nc9vnd

If you're interested in applying AI to biology, take a look at the PhD projects across our labs.

🗓️ Deadline: June 22nd

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Hannah Dickmänken @hannahdckmnkn.bsky.social · Apr 4

Our new preprint is out! We optimized our open-source platform, HyDrop (v2), for scATAC sequencing and generated new atlases for the mouse cortex and Drosophila embryo with 607k cells. Now, we can train sequence-to-function models on data generated with HyDrop v2!
www.biorxiv.org/content/10.1...

Data collected with the new sequencing platform HyDrop v2 is shown. First, a schematic overview of the bead batches of the microfluidic beads is followed by a tSNE and a barplot showing the costs in comparison to 10x Genomics.
Then, a track of mouse data (cortex) is shown together with nucleotide contribution scores in the FIRE enhancer in microglia. Here, the HyDrop and 10x based models show the same contributions.
On the right, the Drosophila embryo collection is explained; in the paper HyDrop v2 and 10x data are compared to sciATAC data. Then, a nucleotide contribution score is also shown, whereas HyDrop v2 and 10x models show the same contribution, just as in mouse.

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Niklas Kempynck @niklaskemp.bsky.social · Apr 3

We released our preprint on the CREsted package. CREsted allows for complete modeling of cell type-specific enhancer codes from scATAC-seq data. We demonstrate CREsted’s robust functionality in various species and tissues, and in vivo validate our findings: www.biorxiv.org/content/10.1...

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Seppe De Winter @seppedewinter.bsky.social · Feb 28

We wrote a review article on modelling and design of transcriptional enhancers using sequence-to-function models.

From conventional machine learning methods to CNNs and using models as oracles/generative AI for synthetic enhancer design!

@natrevbioeng.bsky.social

www.nature.com/articles/s44...

Modelling and design of transcriptional enhancers - Nature Reviews Bioengineering

Enhancers are genomic elements critical for regulating gene expression. In this Review, the authors discuss how sequence-to-function models can be used to unravel the rules underlying enhancer activit...

www.nature.com

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Niklas Kempynck @niklaskemp.bsky.social · Feb 14

Just very happy to have our paper out today! A big thanks to all our co-authors, and to Nikolai and @steinaerts.bsky.social for the teamwork over the past years. If you are interested in using our models for cross-species enhancer studies, check out crested.readthedocs.io/en/stable/mo... 🙂

VIB.AI @vibai.bsky.social · Feb 14

In a new study, Nikolai Hecker, Niklas Kempynck et al. in the team of @steinaerts.bsky.social explore 300 million years of brain evolution through the lens of enhancer codes.
www.science.org/doi/10.1126/...

Enhancer-driven cell type comparison reveals similarities between the mammalian and bird pallium

Combinations of transcription factors govern the identity of cell types, which is reflected by genomic enhancer codes. We used deep learning to characterize these enhancer codes and devised three metr...

www.science.org

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