Multiomics

Multiomics

The rise of systems biology and high-throughput technologies has led to the emergence of so-called “multiomic” approaches, which aim to integrate various layers of molecular information—genomic, transcriptomic, proteomic, epigenomic, and even metabolomic—in order to comprehensively understand complex biological mechanisms. This integration goes beyond the limitations of single-level analyses and allows researchers to explore the dynamic molecular networks that underlie cellular functions, tissue interactions, and developmental trajectories, both normal and pathological.

In this context, several RQR researchers use these tools to investigate early alterations that impact embryonic or neurological development.

Julie Hussin works at the intersection of artificial intelligence (AI), population genetics, and multiomics, with the goal of developing equitable AI tools to better understand reproductive health.

Maritza Jaramillo studies how certain infections may disrupt protein production in placental cells. To better understand these effects, her team uses multiomic tools (RNA-seq, RIBO-seq, proteomics) on human cellular models to identify molecular changes caused by infection.

Serge McGraw uses multiomic approaches to understand how early errors in epigenetic mechanisms can disrupt brain development and lead to neurodevelopmental disorders in children. By studying various cellular and animal models, his team identifies molecular alterations that affect neuron formation, with the goal of developing targeted epigenetic therapies.