New tool revolutionizes lineage tracing
A publication about the computational tool Gene Expression Memory-based Lineage Inference (GEMLI) has recently been published in Nature Communications. It was developed by SciLifeLab researchers Marcel Tarbier and Vicent Pelechano in collaboration with Almut Eisele and David Suter from EPFL (École Polytechnique Fédérale de Lausanne) in Switzerland. GEMLI will enhance lineage tracing studies significantly, offering a valuable resource for researchers worldwide.
Traditionally, lineage tracing has been a difficult process, often limited in resolution and scope. Moreover, most scRNA-seq datasets lack the lineage information crucial for understanding cellular dynamics.
Peering into the cellular past
GEMLI tackles these challenges head-on. By analyzing heritable gene expression patterns, it identifies small to medium-sized cell lineages with precision. This innovative approach enables the study of important cell fate decisions and even the reconstruction of complex structures.
“Lineage information is extremely valuable when characterizing development or complex diseases such as cancer, but it’s hard to obtain and in some settings – such as human tissues – even impossible. GEMLI revolutionizes lineage studies by inferring accurate lineage information purely from gene expression – allowing the study of lineages in any setting and even adding information to legacy datasets,” says Karolinska Institutet and SciLifeLab researcher Marcel Tarbier.
Applications in cancer research
GEMLI’s impact extends to cancer research, where it has unveiled previously unknown gene expression changes at the onset of breast cancer invasiveness. This newfound understanding promises new avenues for diagnosis and treatment.
One of GEMLI’s greatest strengths is its flexibility. Whether in understanding development, disease, or regeneration, GEMLI offers insights into the role of small cell lineages across diverse contexts. Moreover, its functionality extends beyond the lab, making it a powerful tool for everyday applications.
Accessible to all researchers
Above all, GEMLI is not just a theoretical concept, it’s a practical tool available for researchers worldwide. Accessible as an R package on GitHub, GEMLI empowers scientists to explore cellular lineage dynamics.
All in all. This tool represents a significant leap forward in our understanding of cellular biology. With its ability to decipher lineage information from scRNA-seq data, GEMLI holds the promise of transformative discoveries that could reshape our approach to medicine and beyond.
