Anamaria Elek
@aelek.bsky.social
190 followers 400 following 15 posts
Postdoc @ Kaessmann and Sasse labs @zmbh.uni-heidelberg.de Previously PhD @ Sebé-Perdós lab @crg.eu Interested in regulatory genomics, evolution, machine learning, and especially the combination of all of the above. https://anamaria.elek.hr/
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aelek.bsky.social
BCA is a project to look out for — charting the diversity of cell type transcriptomes across the tree of life. Not only will it empower evolutionary studies, but also drive advances in biotechnology, biomedicine, and ecology. Kudos to the relentless, meticulous, and persistent team doing this work!
arnausebe.bsky.social
Happy to share the Biodiversity Cell Atlas white paper, out today in @nature.com. We look at the possibilities, challenges, and potential impacts of molecularly mapping cells across the tree of life.
www.nature.com/articles/s41...
Reposted by Anamaria Elek
tahneema.bsky.social
🚀 Check out our new review article “From Tiny Exons to Big Insights: The Expanding Field of #Microexons” now out in Annual Review of Genomics and Human Genetics!

doi.org/10.1146/annu...

Special thanks to @mirimiam.bsky.social, @crg.eu and @upf.edu!
aelek.bsky.social
A shout-out to people who made this possible: first and foremost @martaig.bsky.social and @arnausebe.bsky.social, but also @zolotarg.bsky.social @xgrau.bsky.social as well as all the ASP lab members, and of course @lukasmahieu.bsky.social @steinaerts.bsky.social and all the members of LCB in Leuven
aelek.bsky.social
We anticipate that applying the same approaches to other species of cnidarians and early-branching animals will enable comparative cell type analyses that will reconstruct evolutionary relationships of the major animal cell types and regulatory processes by which they first evolved.
aelek.bsky.social
To wrap up, here we pave the way for moving beyond conventional transcriptome-based cell type characterization in non-model species, by analyzing regulatory traits that define cell type identities in Nematostella, such as CREs sequence motif composition, active TFs, and GRN architecture.
aelek.bsky.social
We therefore show that effector gene usage groups functionally similar cell types, but regulatory features also reflect their ontogenetic relationships. E.g. GATA/Islet neurons show regulatory seq. similarities with
EMS and pharyngeal derivatives, and Pou4/FoxL2 neurons with ectodermal derivatives.
Cell type relationships based on regulatory sequence similarity
aelek.bsky.social
Finally, we explored cell type clustering using different features. We highlight transcriptionally similar retractor muscles, which share many access. genes, but have distinct sets of CREs bound by distinct TFs, and each clusters with the derivatives of their precursors (ecto. for TR and EMS for MR)
aelek.bsky.social
With invaluable help of @lukasmahieu.bsky.social and @steinaerts.bsky.social lab we trained deep learning sequence models to prioritize motifs predictive of cell type specific accessibility, and to uncover mostly flexible motif syntax in Nematostella, in line with billboard-like model of TF binding.
Motifs identified with deep learning in CREs of different cell types.
aelek.bsky.social
With that in hand, we characterized each cell type by usage of TF motifs, and then linked active TFs to their target genes in cell type specific gene regulatory networks (GRNs). We showcase cnidocyte GRN as an example and highlight important TFs with central roles in the network (FoxL2, Pou4, Sox2).
Cnidocyte gene regulatory characterization.
aelek.bsky.social
The link between ATAC and RNA - from gene regulatory perspective - are TF binding motifs, which are not known for most Nematostella TFs. We devised a correlation-based approach to assign one motif to each TF, selected as best correlated among all motifs inferred by sequence similarity and orthology.
Correlation-based motif assignment approach.
aelek.bsky.social
We used the atlas to characterize and quantify candidate CREs, including cell type-specific enhancers, cell type-specific promoters (SP), constitutive promoters (CP) and a smaller number of candidate alternative promoters (AP). We validated muscle and neuron AP of Gabra2 using transgenic reporters.
Alternative promoter of Gabra2 in neurons and muscle.
aelek.bsky.social
To start, @martaig.bsky.social produced the first scATAC atlas for a non-model species, profiling 60k cells from adult and gastrula Nematostella vectensis - see it annotated in the app: sebelab.crg.eu/nematostella-cis-regulatory-atlas/ and the genome browser: sebelab.crg.eu/nematostella-cis-reg-jb2
scATAC atlas of Nematostella vectensis.
aelek.bsky.social
In this project we wanted to extend cell type characterization in early-branching animals from transcriptome-based (scRNA) to regulatory-based definition, by experimentally profiling chromatin accessibility (scATAC) and computationally inferring TF binding to cis-regulatory elements (CREs).
aelek.bsky.social
I am very happy to have posted my first bioRxiv preprint. A long time in the making - and still adding a few final touches to it - but we're excited to finally have it out there in the wild:
www.biorxiv.org/content/10.1...
Read below for a few highlights...
Decoding cnidarian cell type gene regulation
Animal cell types are defined by differential access to genomic information, a process orchestrated by the combinatorial activity of transcription factors that bind to cis -regulatory elements (CREs) to control gene expression. However, the regulatory logic and specific gene networks that define cell identities remain poorly resolved across the animal tree of life. As early-branching metazoans, cnidarians can offer insights into the early evolution of cell type-specific genome regulation. Here, we profiled chromatin accessibility in 60,000 cells from whole adults and gastrula-stage embryos of the sea anemone Nematostella vectensis. We identified 112,728 CREs and quantified their activity across cell types, revealing pervasive combinatorial enhancer usage and distinct promoter architectures. To decode the underlying regulatory grammar, we trained sequence-based models predicting CRE accessibility and used these models to infer ontogenetic relationships among cell types. By integrating sequence motifs, transcription factor expression, and CRE accessibility, we systematically reconstructed the gene regulatory networks that define cnidarian cell types. Our results reveal the regulatory complexity underlying cell differentiation in a morphologically simple animal and highlight conserved principles in animal gene regulation. This work provides a foundation for comparative regulatory genomics to understand the evolutionary emergence of animal cell type diversity. ### Competing Interest Statement The authors have declared no competing interest. European Research Council, https://ror.org/0472cxd90, ERC-StG 851647 Ministerio de Ciencia e Innovación, https://ror.org/05r0vyz12, PID2021-124757NB-I00, FPI Severo Ochoa PhD fellowship European Union, https://ror.org/019w4f821, Marie Skłodowska-Curie INTREPiD co-fund agreement 75442, Marie Skłodowska-Curie grant agreement 101031767
www.biorxiv.org
aelek.bsky.social
Fixed! Thanks for pointing it out
aelek.bsky.social
Enhorabuena to my first PhD sibling 🥰
arnausebe.bsky.social
In keeping with tradition - here Cris receiving the lab porró from @aelek.bsky.social and celebrating in style. Congratulations Cris!
Reposted by Anamaria Elek
juruehle.bsky.social
🧬🔍How can enhancers achieve tissue-specific activity?
We use MPRAs of synthetic enhancers to derive interpretable rules on TFBS arrangement 🚦 and discover that negative synergies drive specificity in hematopoiesis 🩸. Shoutout to @Robert Frömel & @larsplus.bsky.social for leading this work 🦹🦸.
larsplus.bsky.social
Out in Cell @cp-cell.bsky.social: Design principles of cell-state-specific enhancers in hematopoiesis
🧬🩸 screen of fully synthetic enhancers in blood progenitors
🤖 AI that creates new cell state specific enhancers
🔍 negative synergies between TFs lead to specificity!
www.cell.com/cell/fulltex...
🧵
Design principles of cell-state-specific enhancers in hematopoiesis
Screen of minimalistic enhancers in blood progenitor cells demonstrates widespread dual activator-repressor function of transcription factors (TFs) and enables the model-guided design of cell-state-sp...
www.cell.com
Reposted by Anamaria Elek
larsplus.bsky.social
Out in Cell @cp-cell.bsky.social: Design principles of cell-state-specific enhancers in hematopoiesis
🧬🩸 screen of fully synthetic enhancers in blood progenitors
🤖 AI that creates new cell state specific enhancers
🔍 negative synergies between TFs lead to specificity!
www.cell.com/cell/fulltex...
🧵
Design principles of cell-state-specific enhancers in hematopoiesis
Screen of minimalistic enhancers in blood progenitor cells demonstrates widespread dual activator-repressor function of transcription factors (TFs) and enables the model-guided design of cell-state-sp...
www.cell.com
Reposted by Anamaria Elek
niklaskemp.bsky.social
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...
Reposted by Anamaria Elek
mirimiam.bsky.social
"The main fates after gene duplication are gene loss, redundancy, subfunctionalization and neofunctionalization".

In our new review, @fedemantica.bsky.social and I argue we are missing the most prevalent one: specialization. And the same applies to alternative splicing! 1/7

tinyurl.com/45k7kbmp
Reposted by Anamaria Elek
xgrau.bsky.social
New preprint from the @arnausebe.bsky.social lab! 💐

Here @crisnava.bsky.social, @seanamontgomery.bsky.social & collaborators develop a novel ChIPseq protocol, and demonstrate its huge potential to study the evolution of chromatin function and regulation across the eukaryotic tree of life.
Figure 1 from the paper, with two panels. Panel a shows a schematic cladogram of the eukaryotic tree of life with an adjacent table showing the presence/absence of various histone post-translational modifications in various lineages. Panel b is a summary of the multiplexing strategy for ChIP-seq experiments developed in the paper.