Goffeau, A. et al. Life with 6000 genes. Science 274, 546–567 (1996).
Google Scholar
C. elegans Sequencing Consortium.Genome sequence of the nematode C. elegans: a platform for investigating biology. Science 282, 2012–2018 (1998).
Google Scholar
Initiative, T. A. G. Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature 408, 796–815 (2000).
Google Scholar
Lander, E. S. et al. Initial sequencing and analysis of the human genome. Nature 409, 860–921 (2001).
Google Scholar
Lewin, H. A. et al. Earth BioGenome Project: sequencing life for the future of life. Proc. Natl Acad. Sci. USA 115, 4325–4333 (2018).
Google Scholar
Lewin, H. A. et al. The Earth BioGenome Project 2020: starting the clock. Proc. Natl Acad. Sci. USA 119, e2115635118 (2022).
Google Scholar
Sullivan, P. F. et al. Leveraging base-pair mammalian constraint to understand genetic variation and human disease. Science 380, eabn2937 (2024).
Google Scholar
Kapli, P., Yang, Z. & Telford, M. J. Phylogenetic tree building in the genomic age. Nat. Rev. Genet. 21, 428–444 (2020).
Google Scholar
Smith, S. D., Pennell, M. W., Dunn, C. W. & Edwards, S. V. Phylogenetics is the new genetics (for most of biodiversity). Trends Ecol. Evol. 35, 415–425 (2020).
Google Scholar
Kim, S. & Wysocka, J. Deciphering the multi-scale, quantitative cis-regulatory code. Mol. Cell 83, 373–392 (2023).
Google Scholar
Oliver, S. G. From DNA sequence to biological function. Nature 379, 597–600 (1996).
Google Scholar
Arendt, D. The evolution of cell types in animals: emerging principles from molecular studies. Nat. Rev. Genet. 9, 868–882 (2008).
Google Scholar
Kolodziejczyk, A. A., Kim, J. K., Svensson, V., Marioni, J. C. & Teichmann, S. A. The technology and biology of single-cell RNA sequencing. Mol. Cell 58, 610–620 (2015).
Google Scholar
Rao, A., Barkley, D., França, G. S. & Yanai, I. Exploring tissue architecture using spatial transcriptomics. Nature 596, 211–220 (2021).
Google Scholar
Minnoye, L. et al. Chromatin accessibility profiling methods. Nat. Rev. Meth. Primers 1, 10 (2021).
Google Scholar
Regev, A. et al. The Human Cell Atlas. eLife 6, e27041 (2017).
Google Scholar
Haniffa, M. et al. A roadmap for the Human Developmental Cell Atlas. Nature 597, 196–205 (2021).
Google Scholar
Lee, T. A. et al. A single-nucleus atlas of seed-to-seed development in Arabidopsis. Preprint at bioRxiv https://doi.org/10.1101/2023.03.23.533992 (2023).
Schaum, N. et al. Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. Nature 562, 367–372 (2018).
Google Scholar
Li, H. et al. Fly Cell Atlas: a single-nucleus transcriptomic atlas of the adult fruit fly. Science 375, eabk2432 (2022).
Google Scholar
Zhang, X. et al. A spatially resolved multi-omic single-cell atlas of soybean development. Cell 188, 550–567 (2025).
Google Scholar
Marand, A. P., Chen, Z., Gallavotti, A. & Schmitz, R. J. A cis-regulatory atlas in maize at single-cell resolution. Cell 184, 3041–3055 (2021).
Google Scholar
Cao, J. et al. Comprehensive single-cell transcriptional profiling of a multicellular organism. Science 357, 661–667 (2017). References 18–23 represent comprehensive whole-organism cell atlases for animal and plant model species.
Google Scholar
Toker, I. A. et al. Divergence in neuronal signaling pathways despite conserved neuronal identity among Caenorhabditis species. Curr. Biol. 35, 2927–2945 (2025).
Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).
Google Scholar
Marks, D. S. et al. Protein 3D structure computed from evolutionary sequence variation. PLoS ONE 6, e28766 (2011).
Google Scholar
Mendieta, J. P. et al. Investigating the cis-regulatory basis of C3 and C4 photosynthesis in grasses at single-cell resolution. Proc. Natl Acad. Sci. USA 121, e2402781121 (2024).
Triesch, S. et al. Single-nuclei sequencing of Moricandia arvensis reveals bundle sheath cell function in the photorespiratory shuttle of C3-C4 intermediate Brassicaceae. J. Exp. Bot. https://doi.org/10.1093/jxb/eraf245 (2025).
Li, J. et al. Deep learning of cross-species single-cell landscapes identifies conserved regulatory programs underlying cell types. Nat. Genet. 54, 1711–1720 (2022).
Google Scholar
Agarwal, V. & Shendure, J. Predicting mRNA abundance directly from genomic sequence using deep convolutional neural networks. Cell Rep. 31, 107663 (2020).
Google Scholar
Avsec, Ž. et al. Effective gene expression prediction from sequence by integrating long-range interactions. Nat. Methods 18, 1196–1203 (2021).
Google Scholar
Janssens, J. et al. Decoding gene regulation in the fly brain. Nature 601, 630–636 (2022).
Google Scholar
Pearce, J. D. et al. A cross-species generative cell atlas across 1.5 billion years of evolution: the TranscriptFormer single-cell model. Preprint at bioRxiv https://doi.org/10.1101/2025.04.25.650731 (2025).
Taskiran, I. I. et al. Cell-type-directed design of synthetic enhancers. Nature 626, 212–220 (2024).
Google Scholar
Mich, J. K. et al. Functional enhancer elements drive subclass-selective expression from mouse to primate neocortex. Cell Rep. 34, 108754 (2021).
Google Scholar
Frazer, J. et al. Disease variant prediction with deep generative models of evolutionary data. Nature 599, 91–95 (2021).
Google Scholar
Church, S. H., Mah, J. L. & Dunn, C. W. Integrating phylogenies into single-cell RNA sequencing analysis allows comparisons across species, genes, and cells. PLoS Biol. 22, e3002633 (2024).
Google Scholar
Del Campo, J. et al. The others: our biased perspective of eukaryotic genomes. Trends Ecol. Evol. 29, 252–259 (2014).
Google Scholar
Ku, C. & Sebé-Pedrós, A. Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes. Philos. Trans. R. Soc. B 374, 20190098 (2019).
Google Scholar
Alacid, E. & Richards, T. A. A cell–cell atlas approach for understanding symbiotic interactions between microbes. Curr. Opin. Microbiol. 64, 47–59 (2021).
Google Scholar
Hu, M., Zheng, X., Fan, C.-M. & Zheng, Y. Lineage dynamics of the endosymbiotic cell type in the soft coral Xenia. Nature 582, 534–538 (2020).
Google Scholar
Levy, S. et al. A stony coral cell atlas illuminates the molecular and cellular basis of coral symbiosis, calcification, and immunity. Cell 184, 2973–2987 (2021).
Google Scholar
Serrano, K. et al. Spatial co-transcriptomics reveals discrete stages of the arbuscular mycorrhizal symbiosis. Nat. Plants 10, 673–688 (2024).
Google Scholar
Fromm, A. et al. Single-cell RNA-seq of the rare virosphere reveals the native hosts of giant viruses in the marine environment. Nat. Microbiol. 9, 1619–1629 (2024).
Google Scholar
Ku, C. et al. A single-cell view on alga-virus interactions reveals sequential transcriptional programs and infection states. Sci. Adv. 6, eaba4137 (2020). References 42–45 represent the first examples of using single-cell methods to study symbiotic interactions, simultaneously mapping host and symbiont gene expression programs within the same cells.
Google Scholar
Burki, F., Sandin, M. M. & Jamy, M. Diversity and ecology of protists revealed by metabarcoding. Curr. Biol. 31, 1267–1280 (2021).
Google Scholar
Delmont, T. O. et al. Functional repertoire convergence of distantly related eukaryotic plankton lineages abundant in the sunlit ocean. Cell Genom. 2, 100123 (2022).
Google Scholar
Cordier, T., Lanzén, A., Apothéloz-Perret-Gentil, L., Stoeck, T. & Pawlowski, J. Embracing environmental genomics and machine learning for routine biomonitoring. Trends Microbiol. 27, 387–397 (2019).
Google Scholar
Marchetti, A. et al. Comparative metatranscriptomics identifies molecular bases for the physiological responses of phytoplankton to varying iron availability. Proc. Natl Acad. Sci. USA 109, E317–E325 (2012).
Google Scholar
Brunet, T. & King, N. The origin of animal multicellularity and cell differentiation. Dev. Cell 43, 124–140 (2017).
Google Scholar
Sebé-Pedrós, A., Degnan, B. M. & Ruiz-Trillo, I. The origin of Metazoa: a unicellular perspective. Nat. Rev. Genet. 18, 498–512 (2017).
Google Scholar
Arendt, D. et al. The origin and evolution of cell types. Nat. Rev. Genet. 17, 744–757 (2016). Establishes a foundational conceptual framework for the study of cell type evolution and outlines key open questions and future research directions in the field.
Google Scholar
Archibald, J. M., Simpson, A. G. B. & Slamovits, C. H. Handbook of the Protists (Springer, 2017).
Fritz-Laylin, L. K. et al. The genome of Naegleria gruberi illuminates early eukaryotic versatility. Cell 140, 631–642 (2010).
Google Scholar
Brunet, T. et al. Light-regulated collective contractility in a multicellular choanoflagellate. Science 366, 326–334 (2019).
Google Scholar
Brunet, T. et al. A flagellate-to-amoeboid switch in the closest living relatives of animals. eLife 10, 61037 (2021).
Google Scholar
Dayel, M. J. et al. Cell differentiation and morphogenesis in the colony-forming choanoflagellate Salpingoeca rosetta. Dev. Biol. 357, 73–82 (2011).
Google Scholar
Phillips, M. A. et al. Malaria. Nat. Rev. Dis. Primers 3, 17050 (2017).
Google Scholar
Häckel, E. Monograph of Monera. J. Cell Sci. s2-9, 327–341 (1869).
Google Scholar
Saville-Kent, W. A Manual of the Infusoria: Including a Description of All Known Flagellate, Ciliate, and Tentaculiferous Protozoa, British and Foreign, and an Account of the Organization and the Affinities of the Sponges Vol. 1 (D. Bogue, 1880).
Ramón y Cajal, S. Histologie Du Système Nerveux de l’homme & Des Vertébrés: Cervelet, Cerveau Moyen, Rétine, Couche Optique, Corps Strié, Écorce Cérébrale Générale & Régionale, Grand Sympathique Vol. 2 (A. Maloine, 1911).
Ramón y Cajal, S. Estructura de los centros nerviosos de las Aves. Revista Trimestral de Histología Normal y Patológica 1, 1–10 (1888).
Virchow, R. Cellular Pathology as Based Upon Physiological and Pathological Histology (John Churchill, 1860).
Hyman, L. H. The Invertebrates: Protozoa through Ctenophora (McGraw-Hill, 1940).
Willmer, E. N. Cytology and Evolution (Academic, 1970).
Vergara, H. M. et al. Whole-body integration of gene expression and single-cell morphology. Cell 184, 4819–4837 (2021).
Google Scholar
Steinmetz, P. R. H. et al. Independent evolution of striated muscles in cnidarians and bilaterians. Nature 487, 231–234 (2012).
Google Scholar
Ogino, K., Tsuneki, K. & Furuya, H. Distinction of cell types in Dicyema japonicum (phylum Dicyemida) by expression patterns of 16 genes. J. Parasitol. 97, 596–601 (2011).
Google Scholar
Novershtern, N. et al. Densely interconnected transcriptional circuits control cell states in human hematopoiesis. Cell 144, 296–309 (2011).
Google Scholar
Minnoye, L. et al. Cross-species analysis of enhancer logic using deep learning. Genome Res. 30, 1815–1834 (2020).
Google Scholar
Alié, A. et al. The ancestral gene repertoire of animal stem cells. Proc. Natl Acad. Sci. USA 112, E7093–E7100 (2015).
Google Scholar
Cherbas, L. et al. The transcriptional diversity of 25 Drosophila cell lines. Genome Res. 21, 301–314 (2011).
Google Scholar
Tanay, A. & Sebé-Pedrós, A. Evolutionary cell type mapping with single-cell genomics. Trends Genet. 37, 919–932 (2021).
Google Scholar
Musser, J. M. et al. Profiling cellular diversity in sponges informs animal cell type and nervous system evolution. Science 374, 717–723 (2021).
Google Scholar
Sebé-Pedrós, A. et al. Cnidarian cell type diversity and regulation revealed by whole-organism single-cell RNA-seq. Cell 173, 1520–1534 (2018).
Google Scholar
Sebé-Pedrós, A. et al. Early metazoan cell type diversity and the evolution of multicellular gene regulation. Nat. Ecol. Evol. 2, 1176–1188 (2018).
Google Scholar
Najle, S. R. et al. Stepwise emergence of the neuronal gene expression program in early animal evolution. Cell 186, 4676–4693 (2023).
Google Scholar
Plass, M. et al. Cell type atlas and lineage tree of a whole complex animal by single-cell transcriptomics. Science 1723, eaaq1723 (2018).
Google Scholar
Fincher, C. T., Wurtzel, O., de Hoog, T., Kravarik, K. M. & Reddien, P. W. Cell type transcriptome atlas for the planarian Schmidtea mediterranea. Science 360, eaaq1736 (2018). References 75, 76, 78 and 79 represent the first whole-adult cell atlases for non-model animal species.
Google Scholar
Robertson, H. E. et al. Single cell atlas of Xenoturbella bocki highlights limited cell-type complexity. Nat. Commun. 15, 2469 (2024).
Google Scholar
Álvarez-Campos, P. et al. Annelid adult cell type diversity and their pluripotent cellular origins. Nat. Commun. 15, 3194 (2024).
Ghaddar, A. et al. Whole-body gene expression atlas of an adult metazoan. Sci. Adv. 9, 358 (2023).
Google Scholar
Dogga, S. K. et al. A single cell atlas of sexual development in Plasmodium falciparum. Science 384, eadj4088 (2024). Exemplifies the power of single-cell analysis to molecularly characterize cell states across the life cycle of unicellular eukaryotes.
Google Scholar
Wang, S. Y. et al. Role of epigenetics in unicellular to multicellular transition in Dictyostelium. Genome Biol. 22, 134 (2021).
Google Scholar
Howick, V. M. et al. The Malaria Cell Atlas: single parasite transcriptomes across the complete Plasmodium life cycle. Science 365, eaaw2619 (2019).
Google Scholar
Wang, L. et al. The maturation and aging trajectory of Marchantia polymorpha at single-cell resolution. Dev. Cell 58, 1429–1444 (2023).
Google Scholar
Tanay, A. & Regev, A. Scaling single-cell genomics from phenomenology to mechanism. Nature 541, 331–338 (2017).
Google Scholar
Domcke, S. & Shendure, J. A reference cell tree will serve science better than a reference cell atlas. Cell 186, 1103–1114 (2023).
Google Scholar
Shafer, M. E. R. Cross-species analysis of single-cell transcriptomic data. Front. Cell Dev. Biol. 7, 175 (2019).
Google Scholar
Yan, H. et al. Evolution of plant cell-type-specific cis-regulatory elements. Preprint at bioRxiv https://doi.org/10.1101/2024.01.08.574753 (2024).
Hecker, N. et al. Enhancer-driven cell type comparison reveals similarities between the mammalian and bird pallium. Science 387, eadp3957 (2025). One of the first examples of cross-species cell type comparisons based on regulatory sequence information rather than gene expression data.
Bakken, T. E. et al. Comparative cellular analysis of motor cortex in human, marmoset and mouse. Nature 598, 111–119 (2021).
Google Scholar
Song, Y., Miao, Z., Brazma, A. & Papatheodorou, I. Benchmarking strategies for cross-species integration of single-cell RNA sequencing data. Nat. Commun. 14, 6495 (2023).
Google Scholar
Tarashansky, A. J. et al. Mapping single-cell atlases throughout Metazoa unravels cell type evolution. eLife 10, e66747 (2021).
Google Scholar
Mah, J. L. & Dunn, C. W. Cell type evolution reconstruction across species through cell phylogenies of single-cell RNA sequencing data. Nat. Ecol. Evol. 8, 325–338 (2024). Lays out important considerations for cell type phylogenetic reconstruction and evolutionary models.
Google Scholar
Burkhardt, P. & Jékely, G. Evolution of synapses and neurotransmitter systems: the divide-and-conquer model for early neural cell-type evolution. Curr. Opin. Neurobiol. 71, 127–138 (2021).
Google Scholar
Arendt, D., Bertucci, P. Y., Achim, K. & Musser, J. M. Evolution of neuronal types and families. Curr. Opin. Neurobiol. 56, 144–152 (2019).
Google Scholar
Wagner, G. P. The developmental genetics of homology. Nat. Rev. Genet. 8, 473–479 (2007).
Google Scholar
Pacureanu, A., Silva, J. C. da, Yang, Y., Bohic, S. & Cloetens, P. Nanoscale three-dimensional imaging of biological tissue with X-ray holographic tomography. In Proc. SPIE Vol. 10711 Biomedical Imaging and Sensing Conf. (eds Yatagai, T. et al.) 107112B (SPIE, 2018).
Zinchenko, V., Hugger, J., Uhlmann, V., Arendt, D. & Kreshuk, A. MorphoFeatures for unsupervised exploration of cell types, tissues, and organs in volume electron microscopy. eLife 12, e80918 (2023).
Google Scholar
Di Tommaso, P. et al. Nextflow enables reproducible computational workflows. Nat. Biotechnol. 35, 316–319 (2017).
Google Scholar
Denisenko, E. et al. Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows. Genome Biol. 21, 130 (2020).
Google Scholar
Scully, T. & Klein, A. A mannitol-based buffer improves single-cell RNA sequencing of high-salt marine cells. Preprint at bioRxiv https://doi.org/10.1101/2023.04.26.538465 (2023).
Chari, T. et al. Whole-animal multiplexed single-cell RNA-seq reveals transcriptional shifts across Clytia medusa cell types. Sci. Adv. 7, eabh1683 (2021).
Google Scholar
Alles, J. et al. Cell fixation and preservation for droplet-based single-cell transcriptomics. BMC Biol. 15, 44 (2017).
Google Scholar
García-Castro, H. et al. ACME dissociation: a versatile cell fixation-dissociation method for single-cell transcriptomics. Genome Biol. 22, 89 (2021).
Google Scholar
Rosenberg, A. B. et al. Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding. Science 360, 176–182 (2018).
Google Scholar
Bageritz, J. et al. Glyoxal as an alternative fixative for single-cell RNA sequencing. G3 13, jkad160 (2023).
Google Scholar
Jiménez-Gracia, L. et al. FixNCut: single-cell genomics through reversible tissue fixation and dissociation. Genome Biol. 25, 81 (2024).
Google Scholar
Fortmann, S. D. et al. Fixation before dissociation using a deep eutectic solvent preserves in vivo states and phospho-signaling in single-cell sequencing. Preprint at bioRxiv https://doi.org/10.1101/2023.02.13.528370 (2023).
Martin, B. K. et al. Optimized single-nucleus transcriptional profiling by combinatorial indexing. Nat. Protoc. 18, 188–207 (2023).
Google Scholar
Habib, N. et al. Massively parallel single-nucleus RNA-seq with DroNc-seq. Nat. Methods 14, 955–958 (2017).
Google Scholar
Petrany, M. J. et al. Single-nucleus RNA-seq identifies transcriptional heterogeneity in multinucleated skeletal myofibers. Nat. Commun. 11, 6374 (2020).
Google Scholar
Guillotin, B. et al. A pan-grass transcriptome reveals patterns of cellular divergence in crops. Nature 617, 785–791 (2023).
Google Scholar
Jariani, A. et al. A new protocol for single-cell RNA-seq reveals stochastic gene expression during lag phase in budding yeast. eLife 9, e55320 (2020).
Google Scholar
Grones, C. et al. Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics. Plant Cell 36, 812–828 (2024).
Heaton, H. et al. Souporcell: robust clustering of single-cell RNA-seq data by genotype without reference genotypes. Nat. Methods 17, 615–620 (2020).
Guigó, R. Genome annotation: from human genetics to biodiversity genomics. Cell Genom. 3, 100375 (2023).
Google Scholar
Weisman, C. M., Murray, A. W. & Eddy, S. R. Mixing genome annotation methods in a comparative analysis inflates the apparent number of lineage-specific genes. Curr. Biol. 32, 2632–2639 (2022).
Google Scholar
Altenhoff, A. M. et al. Standardized benchmarking in the quest for orthologs. Nat. Methods 13, 425–430 (2016).
Google Scholar
Glover, N. et al. Advances and applications in the quest for orthologs. Mol. Biol. Evol. 36, 2157–2164 (2019).
Google Scholar
Rosen, Y. et al. Toward universal cell embeddings: integrating single-cell RNA-seq datasets across species with SATURN. Nat. Methods 21, 1492–1500 (2024).
Google Scholar
Rosen, Y. et al. Universal cell embeddings: a foundation model for cell biology. Preprint at bioRxiv https://doi.org/10.1101/2023.11.28.568918 (2023).
Price, P. D. et al. Detecting signatures of selection on gene expression. Nat. Ecol. Evol. 6, 1035–1045 (2022).
Google Scholar
Bertram, J. et al. CAGEE: computational analysis of gene expression evolution. Mol. Biol. Evol. 40, msad106 (2023).
Google Scholar
Rohlfs, R. V., Harrigan, P. & Nielsen, R. Modeling gene expression evolution with an extended Ornstein–Uhlenbeck process accounting for within-species variation. Mol. Biol. Evol. 31, 201–211 (2014).
Rohlfs, R. V. & Nielsen, R. Phylogenetic ANOVA: the expression variance and evolution model for quantitative trait evolution. Syst. Biol. 64, 695–708 (2015).
Google Scholar
Challis, R., Kumar, S., Sotero-Caio, C., Brown, M. & Blaxter, M. Genomes on a Tree (GoaT): a versatile, scalable search engine for genomic and sequencing project metadata across the eukaryotic tree of life. Wellcome Open Res. 8, 24 (2023).
Google Scholar
Zeng, H. What is a cell type and how to define it? Cell 185, 2739–2755 (2022).
Google Scholar
Osumi-Sutherland, D. et al. Cell type ontologies of the Human Cell Atlas. Nat. Cell Biol. 23, 1129–1135 (2021).
Google Scholar
Morris, S. A. The evolving concept of cell identity in the single cell era. Development 146, dev169748 (2019).
Google Scholar