Mathieu Blanchette

Lucas Nelson

Master's Research - McGill University

Adam Stecklov

Master's Research - McGill University

César Miguel Valdez Cordova

PhD - McGill University

Google Scholar

Nicole Zhang

PhD - McGill University

Website

Google Scholar

Yijie Zhang

PhD - McGill University

Website

Google Scholar

Publications

Graphylo: A deep learning approach for predicting regulatory DNA and RNA sites from whole-genome multiple alignments

Dongjoon Lim

Changhyun Baek

2024-01-25

iScience (published)

PhyloGFN: Phylogenetic Inference with Generative Flow Networks

Mingyang Zhou

Phylogenetics is a branch of computational biology that studies the evolutionary relationships among biological entities. Its long history a… (see more)nd numerous applications notwithstanding, inference of phylogenetic trees from sequence data remains challenging: the high complexity of tree space poses a significant obstacle for the current combinatorial and probabilistic techniques. In this paper, we adopt the framework of generative flow networks (GFlowNets) to tackle two core problems in phylogenetics: parsimony-based and Bayesian phylogenetic inference. Because GFlowNets are well-suited for sampling complex combinatorial structures, they are a natural choice for exploring and sampling from the multimodal posterior distribution over tree topologies and evolutionary distances. We demonstrate that our amortized posterior sampler, PhyloGFN, produces diverse and high-quality evolutionary hypotheses on real benchmark datasets. PhyloGFN is competitive with prior works in marginal likelihood estimation and achieves a closer fit to the target distribution than state-of-the-art variational inference methods. Our code is available at https://github.com/zmy1116/phylogfn.

2024-01-15

ICLR.cc/2024/Conference (poster)

openreview.net

ARGV: 3D genome structure exploration using augmented reality

Chrisostomos Drogaris

Yanlin Zhang

Eric Zhang

Elena Nazarova

Roman Sarrazin-Gendron

Sélik Wilhelm-Landry

Yan Cyr

Jacek Majewski

Jérôme Waldispühl

Over the past two decades, scientists have increasingly realized the importance of the three-dimensional (3D) genome organization in regulat… (see more)ing cellular activity. Hi-C and related experiments yield 2D contact matrices that can be used to infer 3D models of chromosome structure. Visualizing and analyzing genomes in 3D space remains challenging. Here, we present ARGV, an augmented reality 3D Genome Viewer. ARGV contains more than 350 pre-computed and annotated genome structures inferred from Hi-C and imaging data. It offers interactive and collaborative visualization of genomes in 3D space, using standard mobile phones or tablets. A user study comparing ARGV to existing tools demonstrates its benefits.

2023-12-31

BMC Bioinformatics (published)

Learning the Game: Decoding the Differences between Novice and Expert Players in a Citizen Science Game with Millions of Players.

Eddie Cai

Roman Sarrazin-Gendron

Renata Mutalova

Parham Ghasemloo Gheidari

Alexander Butyaev

Gabriel Richard

Sébastien Caisse

Rob Knight

Attila Szantner

Jérôme Waldispühl

In recent years, video games have surged in popularity, attracting millions of players across platforms. Citizen science games (CSGs) levera… (see more)ge the processing power of gamers to solve computational and scientific problems. Borderlands Science (BLS) is a mini-game within the mass market game Borderlands 3 that turns multiple sequence alignment (MSA) problems into puzzles. Parallel research demonstrated that BLS players outperformed classical approaches solving small sequence alignment tasks. This study aims to analyze the strategical differences in player solutions in BLS as they gain experience. Through the many collected player solutions from players of different experience level, we gained insights into players’ strategies, differences between expert and non-expert players, and how strategies evolve. We developed a Markov chain trained on solutions from players of different experience levels to understand their actions and outcomes. Results indicate that expert players utilize more gaps and achieve more matches, gradually improving and converging toward unique strategies. Our findings reveal distinct and evolving player strategies. For future citizen science projects, it will be important to consider the identification of player strategies and their evolution over time to improve the game design and data processing.

2023-12-31

FDG (published)

H3K27me3 spreading organizes canonical PRC1 chromatin architecture to
regulate developmental programs

Brian Krug

Bo Hu

Haifen Chen

Adam Ptack

Xiao Chen

Kristjan H. Gretarsson

Shriya Deshmukh

Nisha Kabir

Augusto Faria Andrade

Elias Jabbour

Ashot S. Harutyunyan

John J. Y. Lee

Maud Hulswit

Damien Faury

Caterina Russo

Xinjing Xu

Michael J. Johnston

Audrey Baguette

Nathan A. Dahl

Alexander G. Weil … (see 12 more)

Benjamin Ellezam

Rola Dali

Khadija Wilson

Benjamin A. Garcia

Rajesh Kumar Soni

Marco Gallo

Michael D. Taylor

Claudia L. Kleinman

Jacek Majewski

Nada Jabado

Chao Lu

Polycomb Repressive Complex 2 (PRC2)-mediated histone H3K27 tri-methylation (H3K27me3) recruits canonical PRC1 (cPRC1) to maintain heterochr… (see more)omatin. In early development, polycomb-regulated genes are connected through long-range 3D interactions which resolve upon differentiation. Here, we report that polycomb looping is controlled by H3K27me3 spreading and regulates target gene silencing and cell fate specification. Using glioma-derived H3 Lys-27-Met (H3K27M) mutations as tools to restrict H3K27me3 deposition, we show that H3K27me3 confinement concentrates the chromatin pool of cPRC1, resulting in heightened 3D interactions mirroring chromatin architecture of pluripotency, and stringent gene repression that maintains cells in progenitor states to facilitate tumor development. Conversely, H3K27me3 spread in pluripotent stem cells, following neural differentiation or loss of the H3K36 methyltransferase NSD1, dilutes cPRC1 concentration and dissolves polycomb loops. These results identify the regulatory principles and disease implications of polycomb looping and nominate histone modification-guided distribution of reader complexes as an important mechanism for nuclear compartment organization. The confinement of H3K27me3 at PRC2 nucleation sites without its spreading correlates with increased 3D chromatin interactions. The H3K27M oncohistone concentrates canonical PRC1 that anchors chromatin loop interactions in gliomas, silencing developmental programs. Stem and progenitor cells require factors promoting H3K27me3 confinement, including H3K36me2, to maintain cPRC1 loop architecture. The cPRC1-H3K27me3 interaction is a targetable driver of aberrant self-renewal in tumor cells.

2023-11-27

bioRxiv (preprint)

Player-Guided AI outperforms standard AI in Sequence Alignment Puzzles.

Renata Mutalova

Roman Sarrazin-Gendron

Parham Ghasemloo Gheidari

Eddie Cai

Gabriel Richard

Sébastien Caisse

Rob Knight

Attila Szantner

Jérôme Waldispühl

Although Artificial Intelligence (AI) has gained widespread popularity across different fields, it is essential to recognize that AI systems… (see more), while impressive, do not consistently exhibit robust generalization, particularly for difficult problems such as the Multiple Sequence Alignment (MSA). In this study, we focus on bridging this performance gap by integrating human solutions into AI training. To illustrate these principles, we leverage data from Borderlands Science, a popular citizen science game in which small instances of the MSA problem are represented as puzzles. Our goal is to leverage the collective intelligence of human players to enhance the capabilities of AI agents. To achieve this, we have developed a Player-guided AI system that enables the AI model to learn from both standard training processes and the solutions provided by players. Our findings demonstrate that incorporating human-annotated information into the AI model improves its performance on puzzle tasks. Furthermore, the Player-guided AI model shows a decrease in noise compared to a pure AI model. This advancement allows for leveraging the model to align new sequences with improved accuracy and effectiveness. Moreover, this research brings attention to the potential of integrating AI and human expertise to address other challenges where the performance of AI models may be unsatisfactory.

2023-11-04

International Conference on Climate Informatics (published)

Reference panel-guided super-resolution inference of Hi-C data

Yanlin Zhang

Abstract Motivation Accurately assessing contacts between DNA fragments inside the nucleus with Hi-C experiment is crucial for understanding… (see more) the role of 3D genome organization in gene regulation. This challenging task is due in part to the high sequencing depth of Hi-C libraries required to support high-resolution analyses. Most existing Hi-C data are collected with limited sequencing coverage, leading to poor chromatin interaction frequency estimation. Current computational approaches to enhance Hi-C signals focus on the analysis of individual Hi-C datasets of interest, without taking advantage of the facts that (i) several hundred Hi-C contact maps are publicly available and (ii) the vast majority of local spatial organizations are conserved across multiple cell types. Results Here, we present RefHiC-SR, an attention-based deep learning framework that uses a reference panel of Hi-C datasets to facilitate the enhancement of Hi-C data resolution of a given study sample. We compare RefHiC-SR against tools that do not use reference samples and find that RefHiC-SR outperforms other programs across different cell types, and sequencing depths. It also enables high-accuracy mapping of structures such as loops and topologically associating domains. Availability and implementation https://github.com/BlanchetteLab/RefHiC.

2023-06-29

Bioinformatics (published)

Playing the System: Can Puzzle Players Teach us How to Solve Hard Problems?

Renata Mutalova

Roman Sarrazin-Gendron

Eddie Cai

Gabriel Richard

Parham Ghasemloo Gheidari

Sébastien Caisse

Rob Knight

Attila Szantner

Jérôme Waldispühl

With nearly three billion players, video games are more popular than ever. Casual puzzle games are among the most played categories. These g… (see more)ames capitalize on the players’ analytical and problem-solving skills. Can we leverage these abilities to teach ourselves how to solve complex combinatorial problems? In this study, we harness the collective wisdom of millions of players to tackle the classical NP-hard problem of multiple sequence alignment, relevant to many areas of biology and medicine. We show that Borderlands Science players propose solutions to multiple sequence alignment tasks that perform as well or better than standard approaches, while exploring a much larger area of the Pareto-optimal solution space. We also show the strategies of the players, although highly heterogeneous, follow a collective logic that can be mimicked with Behavioral Cloning with minimal performance loss, allowing the players’ collective wisdom to be leveraged for alignment of any sequences.

2023-04-18

International Conference on Human Factors in Computing Systems (published)

Detection and genomic analysis of BRAF fusions in Juvenile Pilocytic Astrocytoma through the combination and integration of multi-omic data

Melissa Zwaig

Audrey Baguette

Bo Hu

Michael Johnston

Hussein Lakkis

Emily M. Nakada

Damien Faury

Nikoleta Juretic

Benjamin Ellezam

Alexandre G. Weil

Jason Karamchandani

Jacek Majewski

Michael D. Taylor

Marco Gallo

Claudia L. Kleinman

Nada Jabado

Jiannis Ragoussis

Juvenile Pilocytic Astrocytomas (JPAs) are one of the most common pediatric brain tumors, and they are driven by aberrant activation of the … (see more)mitogen-activated protein kinase (MAPK) signaling pathway. RAF-fusions are the most common genetic alterations identified in JPAs, with the prototypical KIAA1549-BRAF fusion leading to loss of BRAF’s auto-inhibitory domain and subsequent constitutive kinase activation. JPAs are highly vascular and show pervasive immune infiltration, which can lead to low tumor cell purity in clinical samples. This can result in gene fusions that are difficult to detect with conventional omics approaches including RNA-Seq. To this effect, we applied RNA-Seq as well as linked-read whole-genome sequencing and in situ Hi-C as new approaches to detect and characterize low-frequency gene fusions at the genomic, transcriptomic and spatial level. Integration of these datasets allowed the identification and detailed characterization of two novel BRAF fusion partners, PTPRZ1 and TOP2B, in addition to the canonical fusion with partner KIAA1549. Additionally, our Hi-C datasets enabled investigations of 3D genome architecture in JPAs which showed a high level of correlation in 3D compartment annotations between JPAs compared to other pediatric tumors, and high similarity to normal adult astrocytes. We detected interactions between BRAF and its fusion partners exclusively in tumor samples containing BRAF fusions. We demonstrate the power of integrating multi-omic datasets to identify low frequency fusions and characterize the JPA genome at high resolution. We suggest that linked-reads and Hi-C could be used in clinic for the detection and characterization of JPAs.

2022-12-11

BMC Cancer (published)

Reference panel guided topological structure annotation of Hi-C data

Yanlin Zhang

2022-11-30

Nature Communications (published)

Leishmania parasites exchange drug-resistance genes through extracellular vesicles

Noélie Douanne

George Dong

Atia Amin

Lorena Bernardo

David Langlais

Martin Olivier

Christopher Fernandez-Prada

2022-06-30

Cell Reports (published)

Reconstruction of full-length LINE-1 progenitors from ancestral genomes

Laura F Campitelli

Isaac Yellan

Mihai Albu

Marjan Barazandeh

Zain M Patel

Timothy R Hughes

2022-05-11

Genetics (published)