Small RNA Biology in Early Embryos
Every human embryo carries a complex molecular programme encoded not just in its DNA, but in thousands of tiny RNA molecules. These small non-coding RNAs — including microRNAs, piRNAs, and others — act as switches and silencers, determining which genes are active at each stage of development.
Our lab investigates how this RNA landscape changes across the first five days of embryo life, and what happens when it goes wrong. By combining single-cell sequencing with advanced bioinformatics, we are building the first comprehensive atlas of small non-coding RNAs in human preimplantation development.
e.g. fluorescence confocal of embryo
The Digital Embryo
What if we could simulate human embryo development on a computer? The Digital Embryo initiative aims to construct predictive computational models by integrating multi-omic datasets — transcriptomics, epigenomics, chromatin accessibility — into a unified framework.
By unifying publicly available single-cell data with novel clinical samples from our lab, this initiative seeks to build the first comprehensive in silico model of human preimplantation development — one that can predict which embryos will thrive and which will not.
e.g. UMAP or computational figure
Endometrial Receptivity & Implantation
For a pregnancy to occur, the embryo and uterus must engage in a precise molecular conversation. When this dialogue fails, recurrent implantation failure (RIF) results — one of the most frustrating diagnoses in reproductive medicine, affecting couples who produce healthy embryos but cannot sustain a pregnancy.
We use transcriptomic and multi-omic approaches to decode the endometrial environment, identify biomarkers of receptivity failure, and test therapeutic interventions — including platelet-rich plasma and organoid models — to improve outcomes for RIF patients.
e.g. endometrial histology or organoid