TranscriptFormer: A generative cell atlas across 1.5 billion years of evolution
Summary
Single-cell transcriptomics is revolutionizing our understanding of cellular diversity, yet comparing transcriptional programs across the tree of life remains challenging. We developed TranscriptFormer, a family of generative foundation models trained on up to 112 million cells spanning 1.53 billion years of evolution across 12 species. We demonstrate state-of-the-art performance on cell type classification, even for species separated over 685 million years of evolution, and zero-shot dise
Content
# TranscriptFormer: A generative cell atlas across 1.5 billion years of evolution
*Published: 2026 May 7*
Single-cell transcriptomics is revolutionizing our understanding of cellular
diversity, yet comparing transcriptional programs across the tree of life
remains challenging. We developed TranscriptFormer, a family of generative
foundation models trained on up to 112 million cells spanning 1.53 billion years
of evolution across 12 species. We demonstrate state-of-the-art performance on
cell type classification, even for species separated over 685 million years of
evolution, and zero-shot disease state identification in human cells.
Developmental trajectories, phylogenetic relationships and cellular hierarchies
emerge naturally in TranscriptFormer's representations without any explicit
training on these annotations. This work establishes a powerful framework for
quantitative single-cell analysis and comparative cellular biology, thus
demonstrating that universal principles of cellular organization can be learned
and predicted across the tree of life.
DOI: 10.1126/science.aec8514