Publications

We're at the start of our collaborative research endeavour but can build on a strong track record of complementary expertise. Explore some of our work relevant to EPIC below. Click on the headers to discover a selection of our publications

New publications stemming from our ERC Synergy-funded research will be listed as the project progresses.

Selected publications

Intron location and sequence modulate gene expression in Yarrowia lipolytica

Qi Qi, Pedro Tomaz da Silva, Vasileios Vangalis , Seppe Dockx, Jan Steensels, Karin Voordeckers, Julien Gagneur, Kevin J. Verstrepen

Nucleic Acids Research, 2026

Nucleotide dependency analysis of genomic language models detects functional elements

Pedro Tomaz da Silva, Alexander Karollus, Johannes Hingerl, Gihanna Sta. Teresa Galindez, Nils Wagner, Xavier Hernandez-Alias, Danny Incarnato & Julien Gagneur

Nature Genetics, 2025

scooby: modeling multimodal genomic profiles from DNA sequence at single-cell resolution

Johannes C. Hingerl, Laura D. Martens, Alexander Karollus, Trevor Manz, Jason D. Buenrostro, Fabian J. Theis & Julien Gagneur

Nature Methods, 2025

Flashzoi: an enhanced Borzoi for accelerated genomic analysis

Johannes C Hingerl , Alexander Karollus , Julien Gagneur

Bioinformatics, 2025

Ribosomes modulate transcriptome abundance via generalized frameshift and out-of-frame mRNA decay

Yujie Zhang, Lilit Nersisyan, Eliska Fürst, Ioannis Alexopoulos, Carlos Santolaria, Susanne Huch, Claudio Bassot, Elena Garre, Per Sunnerhagen, Ilaria Piazza, Vicent Pelechano

Molecular Cell, 2025

We did foundational work on regulatory network evolution

Voordeckers, K., Pougach, K. & Verstrepen, K. J. How do regulatory networks evolve and expand throughout evolution? Curr. Opin. Biotechnol. 34, 180–188 (2015).
Pougach, K., Voet, A., Kondrashov, F. A., Voordeckers, K., Christiaens, J. F., Baying, B., Benes, V., Sakai, R., Aerts, J., Zhu, B., Van Dijck, P. & Verstrepen, K. J. Duplication of a promiscuous transcription factor drives the emergence of a new regulatory network. Nat. Commun. 5, 4868 (2014).
Voordeckers, K., Brown, C. A., Vanneste, K., van der Zande, E., Voet, A., Maere, S. & Verstrepen, K. J. Reconstruction of ancestral metabolic enzymes reveals molecular mechanisms underlying evolutionary innovation through gene duplication. PLoS Biol. 10, e1001446 (2012).
Snoek, T., Picca Nicolino, M., Van den Bremt, S., Mertens, S., Saels, V., Verplaetse, A., Steensels, J. & Verstrepen, K. J. Large-scale robot-assisted genome shuffling yields industrial Saccharomyces cerevisiae yeasts with increased ethanol tolerance. Biotechnol. Biofuels 8, 32 (2015).
Gemayel, R., Yang, Y., Dzialo, M. C., Kominek, J., Vowinckel, J., Saels, V., Van Huffel, L., van der Zande, E., Ralser, M., Steensels, J., Voordeckers, K. & Verstrepen, K. J. Variable repeats in the eukaryotic polyubiquitin gene ubi4 modulate proteostasis and stress survival. Nat. Commun. 8, 397 (2017).

We have expertise in genome assembly, strain engineering and synthetic biology

Gallone, B., Steensels, J., Mertens, S., Dzialo, M. C., Gordon, J. L., Wauters, R., Theßeling, F. A., Bellinazzo, F., Saels, V., Herrera-Malaver, B., Prahl, T., White, C., Hutzler, M., Meußdoerffer, F., Malcorps, P., Souffriau, B., Daenen, L., Baele, G., Maere, S. & Verstrepen, K. J. Interspecific hybridization facilitates niche adaptation in beer yeast. Nat. Ecol. Evol. 3, 1562–1575 (2019).
Gallone, B., Steensels, J., Prahl, T., Soriaga, L., Saels, V., Herrera-Malaver, B., Merlevede, A., Roncoroni, M., Voordeckers, K., Miraglia, L., Teiling, C., Steffy, B., Taylor, M., Schwartz, A., Richardson, T., White, C., Baele, G., Maere, S. & Verstrepen, K. J. Domestication and Divergence of Saccharomyces cerevisiae Beer Yeasts. Cell 166, 1397-1410.e16 (2016).
Cautereels, C., Smets, J., Bircham, P., De Ruysscher, D., Zimmermann, A., De Rijk, P., Steensels, J., Gorkovskiy, A., Masschelein, J. & Verstrepen, K. J. Combinatorial optimization of gene expression through recombinase-mediated promoter and terminator shuffling in yeast Nature Communications 15, 1112 (2024).
Zimmermann, A., Prieto-Vivas, J.E., Cautereels, C., Gorkovskiy, A., Steensels, J., Van de Peer, Y. & Verstrepen, K. J. A Cas3-base editing tool for targetable in vivo mutagenesis. Nat Commun 14, 3389 (2023).

We pioneered methods to investigate post-transcriptional regulation

Pelechano, V., Wei, W. & Steinmetz, L. M. Extensive transcriptional heterogeneity revealed by isoform profiling. Nature 497, 127–131 (2013).
Zhang, Y. & Pelechano, V. High-throughput 5’P sequencing enables the study of degradationassociated ribosome stalls. Cell Rep. Methods 1, 100001 (2021).
Wilkening, S., Pelechano, V., Järvelin, A. I., Tekkedil, M. M., Anders, S., Benes, V. & Steinmetz, L. M. An efficient method for genome-wide polyadenylation site mapping and RNA quantification. Nucleic Acids Res. 41, e65 (2013).
Wang, J., Li, B., Marques, S., Steinmetz, L. M., Wei, W. & Pelechano, V. TIF-Seq2 disentangles overlapping isoforms in complex human transcriptomes. Nucleic Acids Res. 48, e104 (2020).

We were among the first to reveal extensive transcript isoform variability

Gupta, I., Clauder-Münster, S., Klaus, B., Järvelin, A. I., Aiyar, R. S., Benes, V., Wilkening, S., Huber, W., Pelechano, V. & Steinmetz, L. M. Alternative polyadenylation diversifies post-transcriptional regulation by selective RNA-protein interactions. Mol. Syst. Biol. 10, 719 (2014).
Pelechano, V., Wei, W. & Steinmetz, L. M. Extensive transcriptional heterogeneity revealed by isoform profiling. Nature 497, 127–131 (2013).

We discovered and modeled sequence determinants of post-transcriptional steps in various species

Eser, P., Wachutka, L., Maier, K. C., Demel, C., Boroni, M., Iyer, S., Cramer, P. & Gagneur, J. Determinants of RNA metabolism in the Schizosaccharomyces pombe genome. Mol. Syst. Biol. 12, 857 (2016).
Schwalb, B., Michel, M., Zacher, B., Frühauf, K., Demel, C., Tresch, A., Gagneur, J. & Cramer, P. TTseq maps the human transient transcriptome. Science 352, 1225–1228 (2016).
Cheng, J., Maier, K. C., Avsec, Ž., Rus, P. & Gagneur, J. Cis-regulatory elements explain most of the mRNA stability variation across genes in yeast. RNA N. Y. N 23, 1648–1659 (2017).
Wachutka, L., Caizzi, L., Gagneur, J. & Cramer, P. Global donor and acceptor splicing site kinetics in human cells. eLife 8, e45056 (2019).

We developed innovative deep learning models for regulatory genomics

Avsec, Ž., Barekatain, M., Cheng, J. & Gagneur, J. Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks. Bioinforma. Oxf. Engl. 34, 1261–1269 (2018).
Karollus, A., Avsec, Ž. & Gagneur, J. Predicting mean ribosome load for 5’UTR of any length using deep learning. PLOS Comput. Biol. 17, e1008982 (2021).
Karollus, A., Hingerl, J., Gankin, D., Grosshauser, M., Klemon, K. & Gagneur, J. Species-aware DNA language models capture regulatory elements and their evolution. Genome Biol 25, 83 (2024).
Tomaz da Silva, P., Zhang, Y., Theodorakis, E., Martens, L.D., Yépez, V.A., Pelechano, V. & Gagneur, J. Cellular energy regulates mRNA degradation in a codon-specific manner. Mol Syst Biol. May;20(5):506-520. (2024)