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Human–chimpanzee fused cells reveal cis-regulatory divergence underlying skeletal evolution

A Publisher Correction to this article was published on 24 March 2021

This article has been updated

Abstract

Gene regulatory divergence is thought to play a central role in determining human-specific traits. However, our ability to link divergent regulation to divergent phenotypes is limited. Here, we utilized human–chimpanzee hybrid induced pluripotent stem cells to study gene expression separating these species. The tetraploid hybrid cells allowed us to separate cis- from trans-regulatory effects, and to control for nongenetic confounding factors. We differentiated these cells into cranial neural crest cells, the primary cell type giving rise to the face. We discovered evidence of lineage-specific selection on the hedgehog signaling pathway, including a human-specific sixfold down-regulation of EVC2 (LIMBIN), a key hedgehog gene. Inducing a similar down-regulation of EVC2 substantially reduced hedgehog signaling output. Mice and humans lacking functional EVC2 show striking phenotypic parallels to human–chimpanzee craniofacial differences, suggesting that the regulatory divergence of hedgehog signaling may have contributed to the unique craniofacial morphology of humans.

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Fig. 1: Human–chimpanzee hybrid cells capture interspecific cis-expression changes.
Fig. 2: More divergent expression is more tightly associated with divergent traits.
Fig. 3: EVC2 down-regulation is likely to have reduced Hh signaling output in humans.
Fig. 4: EVC2 down-regulation in humans is likely to have reduced Hh signaling output.
Fig. 5: Phenotypes driven by EVC2 KO are observed between humans and chimpanzees.
Fig. 6: Phenotypes driven by reduced levels of functional EVC2 are observed between humans and chimpanzees.

Data availability

Data were deposited in GEO under accession numbers GSE144825 and GSE146481. Source data are provided with this paper.

Code availability

Code used in this study is available at https://github.com/TheFraserLab/ASEr, https://github.com/TheFraserLab/Agoglia_HumanChimpanzee2020 and https://github.com/TheFraserLab/Hornet/tree/master.

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Acknowledgements

We thank S. Bar, L. Carmel and members of the Fraser, Petrov and Pritchard laboratories for critical comments, and the Gilad laboratory (Chicago University) and the You laboratory (University of Pennsylvania) for sharing data and cells. D.G. was funded by the Human Frontier, Rothschild and Zuckerman fellowships. H.B.F. is supported by National Institutes of Health (NIH) grant no. 2R01GM097171-05A1. The cells used in this study were derived from the iPSCs generated by Gallego Romero et al.86, whose study was supported by the NIH, Office of Research Infrastructure Programs/OD (grant no. P51OD011132).

Author information

Authors and Affiliations

Authors

Contributions

D.G. and H.B.F. designed experiments and analyses and wrote the manuscript with input from all authors. D.G. conducted the analyses. R.M.A. designed the ASE pipeline and generated RNA-seq data. M.K. designed and performed the EVC2 and Hedgehog signaling experiments and was supervised by R.R. W.G. designed and performed the reporter assay experiments and was supervised by N.A. D.S. generated the hybrid cells. V.K.B. and S.N. differentiated the cells and were supervised by J.W. Coral Chen, A.C. and Chider Chen contributed human and chimpanzee DPSCs. D.A.P. cosupervised D.G. H.Z. and Y.M. generated the mouse KO. H.B.F. devised the original idea and supervised the project.

Corresponding authors

Correspondence to David Gokhman or Hunter B. Fraser.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Genetics thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Identifying human-chimpanzee expression changes using hybrid cells.

a, Immunostaining for CNCC markers NR2F1 and PAX3 was performed to confirm CNCC differentiation. b, Expression levels of positive and negative markers in the parental and hybrid CNCCs. c, Heatmap and dendrogram of total gene expression across iPSC and CNCC samples. d,e, Fold-change per gene for hybrid iPSCs and hybrid CNCCs when aligned to the human (GRCh38) vs chimpanzee (panTro5) genomes. Grey points are genes where the absolute difference in log2(fold-change) when aligned to the human vs. chimpanzee genome is greater than 1 (that is, genes with potential alignment bias that were excluded from the analysis). Genes with no observable alignment bias are marked with blue (significant ASE: q-value < 0.05) or yellow (non-significant ASE). f, Venn diagram of genes with significant human-chimpanzee expression changes in parental and hybrid samples. g. Parental vs hybrid iPSC expression changes. See Fig. 1d legend.

Extended Data Fig. 2 Differentially expressed genes are associated with divergent chromatin and phenotypes.

a, Overlap of ASE genes in CNCCs with loci showing divergent regulatory marks. Each of the datasets was examined twice: (1) against Ch > Hu genes (red), and (2) against Hu > Ch genes (blue). In 14 out of 16 datasets, expression differences reflect regulatory differences, that is, Hu > Ch regulatory marks show more overlap with Hu > Ch genes than with Ch > Hu genes, and vice versa. P-value shows one-tailed paired t-test for overall overlap (see Methods). Asterisks mark significant randomization test overlap (FDR < 0.05). See Supplementary Table 8. b, Mean fraction of divergent phenotypes for groups of genes with increasingly higher fold-change thresholds. c, Violin plots showing phenotype assignment accuracy in groups of genes with increasingly more divergent differential expression in parental cells. Randomization test P-values are shown for overall accuracy compared to random (PAUC), and accuracy increase compared to random (Pslope), as shown in d. See Fig. 2c legend. d, Randomization output for the phenotype assignment pipeline. Genes associated with each phenotype were randomly assigned a direction of expression change, while keeping their absolute fold-change. Randomization test P-values are shown for overall accuracy compared to random (PAUC), and accuracy increase compared to random (Pslope). e, Phenotype assignment accuracy before and after applying unidirectionality filtering, for ASE and parental differential expression with cis-contribution ≥ 90%. See Fig. 2d legend. In the unidirectionality filter, only phenotypes where all genes point in the same phenotypic direction (that is, complete agreement) are analyzed48.

Extended Data Fig. 3 EVC2 down-regulation in humans.

a, The down:up ratio of Hh signaling genes across increasingly more stringent FDR and fold-change thresholds. b, Differential expression along all of the exons of EVC2 in a CNCC hybrid (Hy1_30_rep1), showing that the majority of reads come from the chimpanzee alleles. Introns are not shown to scale. c, Violin plots of EVC2 expression across iPSC and CNCC non-hybrid samples from various sources, showing consistent EVC2 down-regulation in humans compared to chimpanzees. Diamonds show mean expression levels. DESeq2 FDR-adjusted P-values are presented for cell type. The observation that the human-chimpanzee ratios are similar to the ones observed within the hybrid cells suggests that the majority of differential expression is driven by cis changes. d, EVC2 expression across nine additional tissues for which both human and chimpanzee data are available56, showing that EVC2 down-regulation is not restricted to iPSCs and CNCCs. Dashed line shows mean expression. One-sided t-test P-values are shown. e, Gorilla vs human EVC2 expression. One-sided t-test P-values are shown. f, Western blot of EVC2 protein levels in human and chimpanzee DPSCs. The samples derive from the same experiment and blots were processed in parallel. For gel source data, see Source Data.

Source data

Extended Data Fig. 4 Differentially regulated regions in EVC2.

ATAC-seq read pileup along EVC2 and for the three loci showing species-biased peaks within EVC2. Arrows mark peaks. b,c, NR2F1 and TFAP2A ChIP-seq read pileup for loci <10 kb away from the ATAC-seq peaks. d, MUSCLE103 sequence alignment of rhesus, gorilla, chimp and human sequences. Regions with a high proportion of mismatches are colored in red. e, Reporter assay comparing relative firefly/Renilla luciferase activity for chimpanzee and human EVC2 sequences following transient transfection in human DPSCs. Empty vector (pGL4.11b) was used as negative control. Box plots show mean (center), 2nd and 3rd quartiles (box boundaries), and minima and maxima (whiskers). One-tailed t-test P-values in two independent experiments of quadruplet measurements (n = 8) are shown.

Extended Data Fig. 5 Reduced levels of EVC2 result in reduced Hedgehog signaling output and affect craniofacial phenotypes.

a, Western blot of Gli1 protein levels (a measure of Hh signaling output induced by Shh) at different Evc2 and Hh signaling input levels. EvcC2 was introduced at various levels into Evc2/ mouse NIH/3T3 fibroblasts through retroviral infection. Cells with higher levels of Evc2 show higher Hh signaling output. p38 served as positive control. Pearson’s R and P-value are shown for 40 nM SHH. The samples derive from the same experiment and blots were processed in parallel. For gel source data, see Source Data. b, Micro-CT radiographic images of the palate bone, enamel (extra bright) and roots of the first mandibular molar in Evc2 control and Evc2 KO mice at P28. c, Diagram of the mandible indicating the landmarks for the parameters measured. d, Mean skull and mandible measurements from Evc2 control and Evc2 KO mice at P28. (n = 5 for each group, FDR-adjusted two-tailed t-test P-values are shown). Whiskers show one standard deviation in each direction. Landmarks used are shown in the titles.

Source data

Extended Data Fig. 6 No aneuploidies observed in CNCC hybrid samples.

Figure shows ASE (top), sliding window ASE median over 20 genes (middle), and Wilcoxon rank sum test P-values for each sliding window against the entire genome (bottom). Dashed line shows mean for ASE and sliding window ASE, and shows Bonferroni P-value cutoff for the Wilcoxon rank sum test. An example of data is presented for autosomal chromosomes 1 and 20, and for chromosome X from the CNCC Hy1_30_rep1 sample. No significant deviations were detected in any of the CNCC hybrid samples. See Agoglia et al. for iPSC aneuploidy analyses12.

Extended Data Fig. 7 No chromosomal duplications or losses observed in the CNCC hybrid samples.

Density plots of percentage of human-aligned reads per gene per chromosome for each of the CNCC hybrid samples. Vertical dashed lines show mean per sample.

Supplementary information

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Supplementary Methods, Tables 24 and 25, and Figures

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Source Data Fig. 4

Unprocessed western blots.

Source Data Extended Data Fig. 3

Unprocessed western blots.

Source Data Extended Data Fig. 5

Unprocessed western blots.

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Gokhman, D., Agoglia, R.M., Kinnebrew, M. et al. Human–chimpanzee fused cells reveal cis-regulatory divergence underlying skeletal evolution. Nat Genet 53, 467–476 (2021). https://doi.org/10.1038/s41588-021-00804-3

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