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Gene family evolution underlies cell-type diversification in the hypothalamus of teleosts

Nature Ecology & Evolution volume 6, pages 63–76 (2022)Cite this article

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Abstract

Hundreds of cell types form the vertebrate brain but it is largely unknown how similar cellular repertoires are between or within species or how cell-type diversity evolves. To examine cell-type diversity across and within species, we performed single-cell RNA sequencing of ~130,000 hypothalamic cells from zebrafish (Danio rerio) and surface and cave morphs of Mexican tetra (Astyanax mexicanus). We found that over 75% of cell types were shared between zebrafish and Mexican tetra, which diverged from a common ancestor over 150 million years ago. Shared cell types displayed shifts in paralogue expression that were generated by subfunctionalization after genome duplication. Expression of terminal effector genes, such as neuropeptides, was more conserved than the expression of their associated transcriptional regulators. Species-specific cell types were enriched for the expression of species-specific genes and characterized by the neofunctionalization of expression patterns of members of recently expanded or contracted gene families. Comparisons between surface and cave morphs revealed differences in immune repertoires and transcriptional changes in neuropeptidergic cell types associated with genomic differences. The single-cell atlases presented here are a powerful resource to explore hypothalamic cell types and reveal how gene family evolution and shifts in paralogue expression contribute to cellular diversity.

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Fig. 1: Integration of zebrafish and Mexican tetra single-cell data reveals extensive conservation of cell types.
Fig. 2: Shared subclusters are highly similar between species and express paralogous genes.
Fig. 3: Paralogue shifts are due to differential divergence after duplication between species.
Fig. 4: Divergence of GRNs underlying neuronal genes.
Fig. 5: Species-specific subclusters are associated with species-specific genes.
Fig. 6: Divergence in subcluster repertoires and transcriptomes across Pachon, Tinaja and Molino cave morphs.

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Data availability

Processed scRNA-seq counts and metadata, marker gene lists, trinarized gene lists, SI results, SCENIC results, results from genetic analysis and GO lists are available as Supplementary Data. Raw sequencing results are available at the Sequence Read Archive (SRA) under BioProject ID PRJNA754013.

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Acknowledgements

We thank C. J. Tabin for providing A. mexicanus samples and advice on experimental design. We thank members of the Schier laboratory for discussion and advice, including B. Raj, J. Liu, P. Abitua and A. Nichols and the Harvard zebrafish and cavefish facilities staff, including B. Martineau, for technical support. We thank G. Camp, W. Salzburger and N. Jurisch-Yaksi for helpful comments on the manuscript. This work was supported by a postdoctoral fellowship from the Canadian Institutes of Health Research to M.E.R.S., a grant from the Swiss National Science Foundation (SNSF) to M.E.R.S. (SPARK 196313), grants from SNSF (SPARK 195955) and the University of Basel to A.N.S. and a National Institutes of Health grant (DP1HD094764), an ERC Advanced grant (834788), an Allen Discovery Center grant and a McKnight Foundation Technological Innovations in Neuroscience Award to A.F.S.

Author information

Authors and Affiliations

  1. Biozentrum, University of Basel, Basel, Switzerland

    Maxwell E. R. Shafer, Ahilya N. Sawh & Alexander F. Schier

  2. Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA

    Maxwell E. R. Shafer, Ahilya N. Sawh & Alexander F. Schier

  3. Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA

    Alexander F. Schier

  4. Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Alexander F. Schier

  5. Harvard Stem Cell Institute, Harvard University, Cambridge, MA, USA

    Alexander F. Schier

  6. Center for Brain Science, Harvard University, Cambridge, MA, USA

    Alexander F. Schier

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Contributions

M.E.R.S. and A.F.S. conceived and designed the study. A.N.S. and M.E.R.S. conceived and performed SI analysis. M.E.R.S. performed all other experiments and analysis, including scRNA-seq experiments and all bioinformatic analysis. M.E.R.S., A.N.S. and A.F.S. wrote the manuscript. All authors read and approved of the manuscript.

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Correspondence to Maxwell E. R. Shafer or Alexander F. Schier.

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Extended data

Extended Data Fig. 1 Hypothalamic and POA cell types in zebrafish and Mexican tetra.

(a) UMAP of zebrafish cells coloured and labelled by annotated cell type. (b) UMAP of Mexican tetra surface- and cave-morphs coloured and labelled by annotated cell type. (c) DotPlot of the top 2 maker genes for each zebrafish cluster from (a). (d) DotPlot of the top 2 marker genes for each Mexican tetra cluster from (b). Examples of potentially homologous cell types and their top marker genes share a colour (blue, green, red) in (c) and (d). (e) UMAP of merged but not batch-corrected zebrafish and Mexican tetra single-cell datasets.

Extended Data Fig. 2 Marker genes for cell types shared between zebrafish and Mexican tetra.

(a) DotPlot of the top 5 marker genes for each integrated cluster. (b) Proportion of cells from each cluster by species or species-morph (height of each bar along the x-axis). Width of each bar along the y-axis indicates the proportion of that cluster in the integrated data. Red outlines indicate the Mexican tetra-specific Ciliated cluster, and the integrated Immune clusters which are over-represented in the Mexican tetra dataset. (c) Density plot of the number of subclusters versus the fraction of each subcluster that is either from the zebrafish or Mexican tetra dataset. Subclusters with the majority of cells from the zebrafish dataset are shown in purple, and those with the majority of cells from the Mexican tetra dataset in yellow.

Extended Data Fig. 3 Shared subclusters are highly similar due to paralogous gene expression.

(a) Gene orthology confidence from Ensembl for all marker genes, or those marker genes which were paralogs of a marker gene in the other species. (b) Gene order score from Ensembl for all marker genes, or those marker genes which were paralogs of a marker gene in the other species. (c) The percentage of conserved, species-specific, and species-specific paralogous subcluster marker genes corrected by SCORPiOS synteny-correction. (d) The percentage of morph-specific marker genes for each subcluster which were paralogs of either the conserved or opposite species-specific marker gene for surface- and cave-morphs of Mexican tetra. (e) The odds ratio for the enrichment of paralogs in the species-specific genes for each subcluster for zebrafish and Mexican tetra. (f) The row-scaled ΔSI for all subclusters between zebrafish and Mexican tetra. Yellow indicates the highest ΔSI value between Mexican tetra and zebrafish subclusters. For all boxplots, box bounds represent the first and third quartiles and whiskers 1.5 times the interquartile range, thicker line represents the median.

Extended Data Fig. 4 Paralog shifts are associated with loss of ancestral gene expression patterns.

(a-b) Empirical cumulative distribution function (ECDF) for expression divergence (dT) for paralogous gene pairs. (c-d) ECDF of the number of cell types that have overlapping expression patterns within ancestral cell types for paralogous genes pairs (redundancy score, orange highlight in b). (e-f) ECDF of the number of non-ancestral cell types expressing each individual paralogous gene. Results for c-e are grouped by the age of the duplication inferred from the last common ancestor (LCA) which had both genes - from the oldest (Opisthokonta, yellow), to the most recent common ancestor (Otophysi, red), and to those gene duplicates which are only found in either D. rerio or Astyanax mexicanus (dark red). Results from b, d, and f are filtered and grouped by the originating whole genome duplication event (WGD), either vertebrate (2 R) or teleost (3 R).

Extended Data Fig. 5 Gene regulatory networks identified by GENIE3/SCENIC.

(a) Comparison of the random forest weights for orthologous transcription factors in the zebrafish (y-axis) and Mexican tetra (x-axis) data for example terminal effector genes. Colours indicate whether those transcription factors are in the top 2% of transcription factors for each gene in either zebrafish (blue) and Mexican tetra (red), both (yellow), or none (black).

Extended Data Fig. 6 Species-specific subcluster identities are not dependent on species-specific genes.

(a) tSNEs of cells from clusters containing a species-specific neuronal subcluster coloured by the original subcluster identity. (b) tSNEs of cells from clusters containing a species-specific neuronal subcluster coloured by subcluster identity derived from subclustering without species-specific genes. (c) Sankey diagrams illustrating the relationship between original subcluster identities and identities from subclustering without species-specific genes. Box heights and line widths are proportional to the number of cells in each subcluster and connection, respectively. Shaded connections represent cells from species-specific subclusters.

Extended Data Fig. 7 Comparison of subcluster identities between independent and integrated analysis.

(a) Sankey diagram of Mexican tetra surface-morph-specific subclusters and their relationship to integrated subclusters, and zebrafish subclusters. Box heights and line widths are proportional to the number of cells in each subcluster and connection, respectively. (d) Sankey diagram of Mexican tetra cave-morph-specific subclusters and their relationship to integrated subclusters, and zebrafish subclusters. Box heights and line widths are proportional to the number of cells in each subcluster and connection, respectively. (c) Sankey diagram of the Zebrafish species-specific subclusters (middle) and their relationship to subclusters independently identified in the zebrafish (right) or Mexican tetra datasets (left). Box heights and line widths are proportional to the number of cells in each subcluster and connection, respectively. (d) Sankey diagram of the subclusters shared by, (“Shared (147)”) or specific to, surface- and/or cave-morphs (“Cave-specific” or “Surface-specific”). The middle column depicts whether each subcluster is found in all cave-morph samples (“All Caves”), different combinations of multiple caves, or only in the datasets from specific cave-lineages (“Pachon” or “Molino”). Box heights and line widths are proportional to the number of cells in each subcluster and connection, respectively.

Extended Data Fig. 8 Comparison of neuropeptides and gene regulatory networks between surface- and cave-morphs.

(a) DotPlot showing expression of galn in the cells from the galn+ cluster (Neuronal_07), and expression of oxt, avp, and ENSAMXG00000021172 in the Neuronal_19 cluster. Cells are grouped by species-morph and cave-lineage. (b) Similarity Index between the transcription factor sets for surface- and cave-morphs of Mexican tetra for neuropeptides, neurotransmitters, synaptic genes, and ion channels. (c-f) Random forest weights for orthologous transcription factors in the Mexican tetra surface-morph (y-axis) and Mexican tetra cave-morph (x-axis) data for the neuropeptides galn, hcrt, oxt, and avp. Colours indicate whether those transcription factors are in the top 2% of transcription factors for each gene in either surface-morphs (green) and cave-morphs (yellow), both (purple), or none (black). For all boxplots, box bounds represent the first and third quartiles and whiskers 1.5 times the interquartile range, thicker line represents the median.

Extended Data Fig. 9 Transcriptional signatures of neuro-inflammation resistance in cave-morphs.

(a) tSNE reduction of immune clusters (Tcells, Bcells, Microglia, Macrophages, Mast cells, Thrombocytes, Neutrophils, and Erythorcytes) from surface- and cave-morph Mexican tetra coloured and labelled by species-morph. (b) tSNE reduction of immune cell types from surface- and cave-morph Mexican tetra coloured by cluster. (c) Marker genes for surface- and cave-morph versions of each immune cell type. Red outlines indicate differential expression of neuro-inflammation associated genes in cave-morph immune cells. Gene expression is quantified by both the percentage of cells which express each gene (dot size) and the average expression in those cells (colour scale). (d) tSNE reduction showing expression of ccr9a in Mexican tetra immune cells. (e) Proportion of cells within each immune subcluster which come from Choy surface-morphs, or Molino, Tinaja, or Pachon cave-morphs.

Extended Data Fig. 10 A permanent stress response in a cave-morph-specific neuronal subcluster.

(a) tSNE reduction of Neuronal_03 cluster from Mexican tetra coloured and labelled by subcluster. (b) tSNE reduction of Neuronal_03 cluster from Mexican tetra coloured by species-morph. (c) DotPlot of the top 5 marker genes for each subcluster of the Neuronal_03 cell type (x-axis), and their expression across all subclusters (y-axis). Gene expression is quantified by both the percentage of cells which express each gene (dot size) and the average expression in those cells (colour scale). (d) Dendrogram of the Neuronal_03 subclusters based on the Variable Features of the Neuronal_03 cluster, and the proportion barplot of cells from each species-morph per subcluster. (e) GO analysis of genes differentially expressed between Neuronal_03_1 and Neuronal_03_4. (f) tSNE reduction of Neuronal_03 cluster from Mexican tetra coloured by hspb1 expression. Neuronal_03_4 subcluster is highlighted by a dotted line. (g) Sankey diagram of the relationships between the Mexican tetra subclusters (left-hand side), integrated subclusters (middle), and zebrafish subclusters (right-hand side). Box heights and line widths are proportional to the number of cells in each subcluster and connection, respectively.

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Supplementary Methods/Results, Refs 1–17 and Figs. 1–9.

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Supplementary Data

Supplementary data for Cavefish single-cell sequencing publication. This archive contains the supplementary data for the paper “Gene family evolution underlies cell type diversification in the hypothalamus of teleosts”, which includes all of the raw and partially processed data produced by the analyses presented. The archive contains: (1) The raw count data for both the zebrafish (D. rerio) and Mexican tetra (A. mexicanus) single-cell experiments, as compressed.csv files. (2) The Seurat object metadata for the zebrafish (D. rerio), Mexican tetra (A. mexicanus) and integrated Seurat objects, containing sample, species and cell-type cluster labels for each cell. (3) CSVs for all marker gene lists used in the publication. (4) CSVs for all pseudobulk expression data for all cell type labels. (5) The raw data used for calculating the SI for each cluster and subcluster identity in the integrated data. (6) Results from SCENIC/GENIE3 analysis, including the Linklists and tfModules outputs from SCENIC. (7) Results of the weir fst analysis between cave and surface populations, for both INDELs and SNPs. (8) Ensembl biomart export files for determining paralogy relationships between genes within and across species. (9) Results of trinarization of gene expression across all identities and the uniquely expressed genes per identity. These are provided as R object files (.rds). Supplemental_data/3-marker_gene_lists. This folder contains marker gene lists for clusters and subclusters (“.sub”), for the zebrafish (“Drerio”), Mexican tetra (“Amexicanus”) or integrated (“Integrated”) datasets. Supplemental_data/4-pseudobulk_expression. This folder contains psuedobulk expression profiles for clusters (“Clusters”) and subclusters (“Subclusters”), for the zebrafish (“Drerio”), combined Mexican tetra and the surface- and cave-morphs of Mexican tetra, and integrated datasets.

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Shafer, M.E.R., Sawh, A.N. & Schier, A.F. Gene family evolution underlies cell-type diversification in the hypothalamus of teleosts. Nat Ecol Evol 6, 63–76 (2022). https://doi.org/10.1038/s41559-021-01580-3

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