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Tetsuya Yamada

@tyamadat.bsky.social

PhD student @UniHeidelberg | Kaessmann lab | UTokyo alumn

11 Posts242 Follower487 Folgt
Mari Sepp@marisepp.bsky.social · 6d ago

Co-option of certain transposable elements as regulatory elements in specific cerebellar cell states, e.g. HERVL in rhombic lip–derived neuroblasts. Led by awesome Tetsuya @tyamadat.bsky.social, together with @ioansarr.bsky.social and @kaessmannlab.bsky.social

Tetsuya Yamada@tyamadat.bsky.social · 7d ago

Our manuscript on the co-option of TEs as cerebellar CREs is now officially published in @natcomms.nature.com! Huge thanks to @kaessmannlab.bsky.social @marisepp.bsky.social, and @ioansarr.bsky.social for the fantastic collaboration throughout this project! www.nature.com/articles/s41...

Tetsuya Yamada@tyamadat.bsky.social · 7d ago

Our manuscript on the co-option of TEs as cerebellar CREs is now officially published in @natcomms.nature.com! Huge thanks to @kaessmannlab.bsky.social @marisepp.bsky.social, and @ioansarr.bsky.social for the fantastic collaboration throughout this project! www.nature.com/articles/s41...

Gene regulatory innovations from transposable elements in primate cerebellum development - Nature Communications

The roles of transposable elements in primate brain development remain underexplored. Here, the authors identify transposable elements with ancestral regulatory potential that have been co-opted as ci...

nature.com

Kaessmann Lab@kaessmannlab.bsky.social · 10mo ago

Did transposable elements shape brain evolution — and if so, which ones, and in which cell states and lineages? Led by @tyamadat.bsky.social, we explored this question in cerebellum development using sequence-based deep learning models! www.biorxiv.org/content/10.1...

Hannah Dickmänken@hannahdckmnkn.bsky.social · 6mo ago

Paper alert! 💻 How many cells do you need to train reliable deep learning models in regulatory genomics? We asked how data quality, sequencing depth, and dataset size affect training of sequence-to-function models from scATAC-seq. Out now www.nature.com/articles/s41... (details below)

Evaluating single-cell ATAC-seq atlasing technologies using sequence-to-function modeling - Nature Communications

Generating high-quality training data for machine learning is costly. Here, authors include sequence-to-function modeling in benchmarking of custom and commercial droplet-based scATAC platforms, and r...

nature.com

Ekin Deniz Aksu@ekindea.bsky.social · 3w ago

I'm excited to share that Corgi is out in @natcomms.nature.com! We refine context-aware sequence-to-function models by using FiLM to condition the model on trans-regulator expression levels. This way Corgi can generalize to unseen cell types. www.nature.com/articles/s41... 🧵Thread 1/n

Context-aware sequence-to-function model of human gene regulation - Nature Communications

This study introduces Corgi and Corgi+ , biology-inspired deep neural network models of regulatory DNA sequences that can generalize to unseen cell types. They accurately impute epigenomic d...

nature.com

Mike Dorrity@mwdorr.bsky.social · 2mo ago

First pre-print from the lab, a collaborative effort led by Jess Bourn @bournsupremacy.bsky.social, a fantastic PhD in my group. We resolve a key problem in development + evolution: how do we quantify heterochrony and link temporal variation to phenotype? www.biorxiv.org/content/10.6...

Quantitative mapping of heterochrony to species-specific phenotypes

The genetic program of animal development is conserved, but its rate of execution varies across species. Heterochrony, shifts in the relative timing of developmental events, generates phenotypic varia...

biorxiv.org

Laurie Belcher@lauriebelch.bsky.social · 2mo ago

The new OrthoFinder paper is out now! In this new work, we introduce major advances in accuracy and scalability, allowing analysis on much larger datasets www.nature.com/articles/s41... github.com/OrthoFinder/...

OrthoFinder: improved phylogenetic orthology inference with enhanced accuracy and scalability - Nature Methods

The updated OrthoFinder v3 software boosts accuracy and scalability in phylogenetic orthology inference with massive and diverse datasets.

nature.com

Joana L. Rocha@joanocha.bsky.social · 2mo ago

We are excited to share our pan-pangenome paper! This is a long time coming work of my postdoc with the incredible @psudmant.bsky.social, and a stellar group of people! I hope you enjoy reading it! And I am excited to talk more more about it this week at #PEQG26!! www.biorxiv.org/content/10.6...

A Pan-pangenome illuminates complex structural variation and selection in humans, chimpanzees, and bonobos

Complete, haplotype-resolved genome assemblies have provided unprecedented insight into the evolution of structurally complex, rapidly evolving regions of human genomes; however, population-scale pang...

biorxiv.org

Martina Capriati@martinacapriati.bsky.social · 3mo ago

Exciting news 📣 The first preprint from @grandlab.bsky.social is out 🧬 How are essential genes controlled? By rapid degradation and recovery of TFs alone or in combination, we show that essential genes rely on a single dominant TF, despite dense co-binding. www.biorxiv.org/content/10.6...

Essential genes are dominantly activated by single transcription factors

Cell viability depends on the precise expression of essential genes, which are controlled by CpG-island (CGI) promoters densely bound by transcription factors (TFs). This has led to the prevailing model that TFs cooperate to ensure ubiquitous expression. Here, using rapid and reversible single and combinatorial degradation in murine stem cells, we systematically dissect the regulatory interactions between five key TFs. We uncover an unexpectedly specific architecture in which regulatory dominance, rather than cooperation, is the prevailing mode, where individual TFs autonomously drive chromatin opening and gene activation at largely distinct promoters. Cooperative regulation occurs at a minority of sites with antagonistic or synergistic outcomes modulated by the interplay between nucleosome positioning and TF sensitivity to chromatin. This logic is recapitulated at synthetic sequences and reflected in human genetic variation. These findings reveal that single TFs dominantly activate distinct sets of CGI-linked genes, including essential genes, across development, homeostasis, and disease. ### Competing Interest Statement The authors have declared no competing interest. DFG, GR 6341/2-1, 556634773

biorxiv.org

Huisheng (Julie) Zhu@huishengzhu.bsky.social · 4mo ago

Why do schizophrenia GWAS signals look so flat across the genome? In our recent preprint, we explored why psychiatric disorders — and, more broadly, brain-related traits involving the central nervous system — appear to have unusual genetic architectures. 🧵1/n

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Prajna Hebbar@prajnahebbar.bsky.social · 4mo ago

We built the first complete genome for the common marmoset, fully resolving regions that were previously missing: centromeres, acrocentric short arms, and more. A new reference genome for anyone working with marmosets. This was an awesome collaborative effort & I’m grateful to all my co-authors! 🧬

bioRxiv Genomics@biorxiv-genomic.bsky.social · 4mo ago

A Complete Genome for the Common Marmoset https://www.biorxiv.org/content/10.64898/2026.03.25.713844v1

Li Zhao@lizhao.bsky.social · 4mo ago

We wrote a review on using machine learning to study evolutionary genetics and molecular evolution in Trends in Genetics. It is open access—please take a look if you are interested in this topic www.sciencedirect.com/science/arti... @cp-trendsgenetics.bsky.social

Machine learning for evolutionary genetics and molecular evolution

Over the past decade, the rapid expansion of large-scale data and advances in computational power have allowed machine learning (ML), especially deep …

sciencedirect.com

Sambina Islam Aninta@sambean12.bsky.social · 5mo ago

MPRAs are the gold-standard tool for measuring how DNA sequences drive gene expression and prioritizing variant effects. In this preprint we asked: does it matter WHERE you place a variant in an MPRA? Spoiler: yes, and it might lead you to miss disease-causing variants. 1/6 doi.org/10.64898/202...

Position-dependent variant effects reveal importance of context in genomic regulation

Gene expression is governed by the DNA sequence, which is read out through complex interactions between transcription factors (TFs), co-activators, and chromatin. Massively Parallel Reporter Assays (MPRAs) provide a high-throughput framework for functionally characterizing how regulatory DNA sequences impact the expression of a model gene. MPRAs have also proven to be useful for measuring the effects of genetic variation, where each allele is typically tested in the center of ~200 bp of genomic context cloned into the MPRA, but the impact of variant position and local context remains largely unexplored. In this study, we systematically investigate how shifting the position of a variant within an MPRA probe influences its regulatory activity using models that predict expression in MPRAs from DNA sequence. We find that while the direction of variant effects is usually preserved across positions, the magnitude of expression changes can vary substantially depending on where the variant is placed within the construct. This positional bias appears to be largely explained by the strong position-dependent activity of TFs whose binding the variants perturb. In a subset of cases, interactions consistent with cooperativity between TFs also contribute to position-specific effects. ~1% of variants appear to disrupt RNA polymerase III (Pol III) promoters within Alu elements, resulting in position-specificity because both A and B boxes are required for function and exclusion of either motif due to window shifts disrupts the variants' effects. However, we saw little evidence to support the hypothesis that the positional dependence of variant effects resulted from the redundancy of motifs. Overall, our study demonstrates the complexity of cis-regulatory grammar and how it can confound the interpretation of regulatory variants. ### Competing Interest Statement R.T. has filed intellectual property related to MPRA and MPRA models. The other authors declare no competing interests.

biorxiv.org

Dario Tommasini@dariotommasini.bsky.social · 5mo ago

Inhibitory neurons are among the most transcriptomically diverse class of neurons in the CNS, with some brain regions having 60+ distinct cell types. Do humans share the same repertoire as rodents? Birds? Fish? 1/13

James Briscoe@jamesbriscoe.bsky.social · 5mo ago

New Perspective form Rory Maizels & me: "Gene regulatory networks: from correlative models to causal explanations" Gene regulatory networks are supposed to give us mechanistic explanations of development, so why are we drowning in 'hairballs' of statistical correlations? rdcu.be/e7zx7

Gene regulatory networks: from correlative models to causal explanations

Nature Reviews Genetics - In this Perspective, Maizels and Briscoe discuss the limitations of current models of gene regulatory networks and outline solutions to harness data abundance without...

rdcu.be