Serohijos Lab:
Evolutionary Systems & Biophysical Genomics
We study how evolutionary dynamics shape organismal, genomic, and phenotypic diversity by linking molecular changes to population-level processes. Using a combination of experimental and computational approaches, we investigate the forces driving evolution across scales—from individual mutations to complex traits and microbial community interactions.
What we do
Evolutionary Systems Genomics
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Complex phenotypes of eukaryotes
We are developing a new approach called protein-interaction quantitative trait loci (piQTL) mapping to uncover how genetic differences influence the complex traits of living organisms. While traditional methods focus on gene expression or protein abundance, our method goes a step further by examining how proteins physically interact inside cells—a key factor in determining how cells function and respond to their environment. Using a powerful yeast model system, CRISPR, and protein-fragment complementation via DHFR PCA, we aim to identify the genetic changes that alter protein interaction networks, which in turn drive traits like drug response or stress tolerance. Representative papers: "Genetic landscape of an in vivo protein interactome " by Besse et al. Nature Genetics 2026 (in press), Biorxiv "Protein-protein interaction is a major source of epistasis in genetic interaction networks" by Castellanos-Girouard et al. Nature Communications 2025. |
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Computational Biology and Biophysics
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Multi-scale cell models
We are developing computational tools and models to better predict how genetic mutations affect our cells, health, and risk for disease. Every person carries millions of genomic DNA differences, and some of these change the proteins our cells use to function. These mutations can lead to diseases like cancer, heart disease, or diabetes, but existing prediction tools only look at proteins in isolation. Our approach is different: we will take into account how proteins interact with each other, their 3D structures, and how these interactions change under different conditions—like stress or drug exposure. By combining large-scale biological data and artificial intelligence, these tools aims to give a more accurate view of how specific mutations impact organismal and phenotypic diversity. Representative papers: "Genetic landscape of an in vivo protein interactome " by Besse et al. Nature Genetics 2026 (in press), Biorxiv "Protein-protein interaction is a major source of epistasis in genetic interaction networks" by Castellanos-Girouard et al. Nature Communications 2025. |
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Microbial ecology and evolution
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Microbes are the most abundant and diverse form of life on Earth, playing essential roles in everything from maintaining our health to cleaning up pollution and producing medicines. In nature, they live in complex communities made up of many species that interact, compete, and evolve together. Even within a single microbial species, there can be thousands of genetically distinct clones coexisting. For example, a human gut contains over a trillion bacteria spanning hundreds of species and millions of unique variants. Understanding how these microbial communities change over time and respond to their environment is a major scientific challenge. Our research takes an interdisciplinary approach—combining genetics, evolutionary biology, and immunology—to uncover the rules that govern these dynamic and invisible ecosystems.
Representative papers: "Quantifying the intra- and inter-species community interactions in microbiomes by dynamic covariance mapping", by Gencel et al. Nature Communications 2025. "Doblin: Inferring dominant clonal lineages from DNA barcoding time-series" by Gencel et al. Bioinformatics 2025 "Chromosomal barcoding of E. coli populations reveals lineage diversity dynamics at high resolution" by Jasinska et al. Nature Ecology & Evolution 2020 |
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Latest News
- May 15, 2026: Our work on yeast piQTL is accepted in Nature Genetics. Congratulations Tatsuya and Savandara, and everyone involved!
- May 13, 2026: Two preprints on the biophysics of PPI networks is now in BioRxiv. More details on the publications page.
- May 13, 2026: Jacob received a fellowship from CIHR. Congratulations!
- April 20, 2026: We welcome our international interns for the summer, Augustin (Université Paris-Saclay) and Matteo (University of Trieste)!
- April 15, 2026: We renewed our Discovery grant! Thanks NSERC!
- February 5, 2026: Xavier's paper on epistasis and PPI networks is now out in Nature Communications. Congratulations!
- October 5, 2025: Doblin is now out in Bioinformatics. Congratulations to Melis and David!
- July 9, 2025: Melis's paper on intra- and inter-species dynamics in gut microbiome is now out in Nature Communications. This is a collaborative work with Cang Hui (Stellenbosch University, South Africa), Alfredo Menendez (Université de Sherbrooke), Dana Philpott (University of Toronto), and Shimon Berhstein (Ben Gurion University).
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Département de biochimie Faculté de Médecine |