Gatt, C. | bioRxiv Science

bioRxiv2025

Deep exploration of transcriptomic cellular identities over evolutionary time

Whole-organism cell atlases have painted the cellular landscapes of individual species; however, comparing cells across the tree of life remains challenging. Most cross-species analyses are restricted to orthologous genes, while the complexity of atlas data constitutes an access barrier for many researchers. We developed a computational strategy to accelerate the exploration of cellular identities at scale. We integrated 30 atlases detailing the expression of 861,013 genes by 2,645,508 animal and plant cells and trained a universal model of cellular transcriptomes to track cell type diversification over evolutionary times. Transfer learning achieved cell type annotation of a de novo atlas of the insect Cryptocercus punctulatus within minutes. We devised a generative artificial intelligence approach to construct virtual cell atlases from genome sequences and used it to synthesise an atlas of the Tasmanian tiger, extinct since 1936. We then reduced the footprint of extant atlases by 100 times while retaining crucial information and developed interfaces to answer dozens of query types within seconds, boosting atlas exploration by [~]50,000 times.

evolutionary biology↗

bioRxiv2024

Integration of hyperspectral imaging and transcriptomics from individual cells with HyperSeq

Microscopy and omics are complementary approaches to probe the molecular state of cells in health and disease, combining granularity with scalability. While important advances have been achieved over the last decade in each area, integrating both imaging- and sequencing-based assays on the same cell has proven challenging. In this study, a new approach called HyperSeq that combines hyperspectral autofluorescence imaging with transcriptomics on the same cell is demonstrated. HyperSeq was applied to Michigan Cancer Foundation 7 (MCF-7) breast cancer cells and identified a subpopulation of cells exhibiting bright autofluorescence rings at the plasma membrane in optical channel 13 ({lambda}ex = 431 nm,{lambda} em = 594 nm). Correlating the presence of a ring with the gene expression in the same cell indicated that ringed cells are more likely to express hallmark genes of apoptosis and less likely to express genes associated with ATP production. Further, correlation of cell morphology with gene expression suggested that multiple members of the spliceosome were downregulated in larger MCF-7 cells. Multiple genes were evenly expressed across cell sizes but also exhibited higher usage of specific exons in larger or smaller cells. Finally, correlation between gene expression and fluorescence within the spectral range of Nicotinamide adenine dinucleotide hydrogen (NADH) provided insight into the metabolic states of MCF-7 cells. These observations provided a link between the cells optical spectrum and its internal molecular state, demonstrating the utility of HyperSeq to study cell biology at single cell resolution by integrating spectral, morphological and transcriptomic analyses into a single, streamlined workflow.

bioinformatics↗