View in EDS HTML Full Text PDF Full Text

The evolution of gene regulation in mammalian cerebellum development.

Saved in:
Bibliographic Details
Title: The evolution of gene regulation in mammalian cerebellum development.
Authors: Sarropoulos, Ioannis (AUTHOR), Sepp, Mari (AUTHOR), Yamada, Tetsuya (AUTHOR), Schäfer, Philipp S. L. (AUTHOR), Trost, Nils (AUTHOR), Schmidt, Julia (AUTHOR), Schneider, Céline (AUTHOR), Drummer, Charis (AUTHOR), Mißbach, Sophie (AUTHOR), Taskiran, Ibrahim I. (AUTHOR), Hecker, Nikolai (AUTHOR), Bravo González-Blas, Carmen (AUTHOR), Frömel, Robert (AUTHOR), Joshi, Piyush (AUTHOR), Leushkin, Evgeny (AUTHOR), Arnskötter, Frederik (AUTHOR), Leiss, Kevin (AUTHOR), Okonechnikov, Konstantin (AUTHOR), Lisgo, Steven (AUTHOR), Palkovits, Miklós (AUTHOR)
Source: Science. 1/29/2026, Vol. 391 Issue 6784, p1-26. 26p.
Subjects: Cerebellum, Human evolution, Genetic regulation, Mammals, Deep learning, Cis-regulatory elements (Genetics), Chromatin, Transcription factors
Abstract: Gene regulatory changes are considered major drivers of evolutionary innovations, including the cerebellum's expansion during human evolution, yet they remain largely unexplored. In this study, we combined single-nucleus measurements of gene expression and chromatin accessibility from six mammals (human, bonobo, macaque, marmoset, mouse, and opossum) to uncover conserved and diverged regulatory networks in cerebellum development. We identified core regulators of cell identity and developed sequence-based models that revealed conserved regulatory codes. By predicting chromatin accessibility across 240 mammalian species, we reconstructed the evolutionary histories of human cis-regulatory elements, identifying sets associated with positive selection and gene expression changes, including the recent gain of THRB expression in cerebellar progenitor cells. Collectively, our work reveals the shared and mammalian lineage-specific regulatory programs governing cerebellum development. Editor's summary: The mechanisms underlying brain development during evolution remain to be fully elucidated. Sarropulos et al. focused on the cerebellum and used previous single-nucleus multiome (RNA expression and DNA accessibility) and newly generated datasets across six mammalian species (human, bonobo, macaque, marmoset, mouse, and opossum) to develop a deep-learning model able to predict gene regulatory networks and cis-regulatory elements conserved or diverged during evolution for cerebellum development. By combining the cross-species multiomic resource with state-of-the-art machine learning and deep learning modeling of gene regulatory networks and enhancer grammar, this work provides valuable insights into brain development and evolution. —Mattia Maroso INTRODUCTION: The mammalian cerebellum has experienced many evolutionary innovations, but their molecular basis remains elusive. Most phenotypic changes are thought to be driven by mutations in cis-regulatory elements (CREs) such as enhancers and promoters, which control gene expression in a cell type–specific manner. However, the fast CRE evolution and our limited understanding of how DNA sequences encode regulatory activity have hindered our ability to study regulatory innovations. RATIONALE: Single-cell multiomics enable the mapping of CRE cell type specificity, whereas recent advances in machine learning facilitate predicting CRE accessibility from DNA sequence. We reasoned that if CRE sequence codes of cerebellar cell types are conserved across mammals, then we could use sequence-based deep learning models to reconstruct CRE evolutionary histories from genomic sequences and identify sequence changes underlying gene regulatory innovation. RESULTS: We built comprehensive single-cell gene expression and chromatin accessibility atlases of cerebellum development across six mammalian species, human, bonobo, macaque, marmoset, mouse, and opossum, spanning 780,000 single-cell profiles. We aligned developmental timelines between species, found common cell types, and dated our previously reported expansion of fetal Purkinje cells in the human lineage within the past 40 million years, highlighting a recent evolutionary innovation in the cerebellum. By inferring gene regulatory networks, we identified major transcription factor regulators of cerebellar cell identities and showed that their activity is largely conserved across species. Grouping CREs on the basis of their spatiotemporal accessibility revealed shared transcription factor motif signatures between human and mouse CREs, suggesting that their regulatory codes, i.e., motif combinations, are conserved despite extensive turnover of individual CREs. Next, we developed deep learning models that successfully predicted cerebellar cell type–specific CRE accessibilities from DNA sequence across species. Using a model trained on human and mouse data, DeepCeREvo (deep learning of cerebellar regulatory evolution), we demonstrated that the logic linking DNA sequence to CRE function, the regulatory grammar, of cerebellar cell types remained markedly stable over 160 million years of mammalian evolution. Building on this, we expanded our predictions to 240 mammalian genomes and reconstructed the evolutionary histories of human CREs. We identified clade-specific CREs that, after their emergence, were preserved, and detected signs of positive selection in human-specific elements, suggesting potential links to evolutionary innovations. We validated these predictions using nonhuman primate datasets not included in model training and enhancer reporter assays. Finally, we linked primate-specific CREs to genes with expression gains in the same cell type in the primate lineage. Notably, we traced an expression gain of THRB in human early progenitor cells to single-nucleotide substitutions that potentially created a new CRE ~3 kilobases upstream of the transcription start site ~25 to 40 million years ago. CONCLUSION: Our study provides a comprehensive framework for understanding gene regulatory evolution by combining comparative single-cell genomics with machine learning approaches. We demonstrate that despite rapid turnover of individual regulatory elements, conserved regulatory grammar governs cell type–specific gene expression in cerebellum development across mammals. By linking specific sequence changes to expression evolution, we identified regulatory innovations that likely contributed to human cerebellar evolution. This approach is broadly applicable to understanding regulatory evolution across tissues and species. Single-cell multiomics analysis of cerebellar regulatory evolution across mammals.: Single-cell multiomics atlases delineate gene regulation of cerebellar cell types across species (left). Sequence-based deep learning models revealed that the regulatory grammar, the sequence logic underlying CRE accessibility, of cerebellar cell types has been conserved over 160 million years of mammalian evolution, enabling inference of evolutionary histories of human CREs using orthologous regions across 240 mammals (top right). Recent innovations in human CREs are linked to changes in gene expression between species (bottom right). [ABSTRACT FROM AUTHOR]
Copyright of Science is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: pbh
DbLabel: Psychology and Behavioral Sciences Collection
An: 191204548
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: The evolution of gene regulation in mammalian cerebellum development.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Sarropoulos%2C+Ioannis%22">Sarropoulos, Ioannis</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sepp%2C+Mari%22">Sepp, Mari</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yamada%2C+Tetsuya%22">Yamada, Tetsuya</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schäfer%2C+Philipp+S%2E+L%2E%22">Schäfer, Philipp S. L.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Trost%2C+Nils%22">Trost, Nils</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schmidt%2C+Julia%22">Schmidt, Julia</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schneider%2C+Céline%22">Schneider, Céline</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Drummer%2C+Charis%22">Drummer, Charis</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mißbach%2C+Sophie%22">Mißbach, Sophie</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Taskiran%2C+Ibrahim+I%2E%22">Taskiran, Ibrahim I.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hecker%2C+Nikolai%22">Hecker, Nikolai</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bravo+González-Blas%2C+Carmen%22">Bravo González-Blas, Carmen</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Frömel%2C+Robert%22">Frömel, Robert</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Joshi%2C+Piyush%22">Joshi, Piyush</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Leushkin%2C+Evgeny%22">Leushkin, Evgeny</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Arnskötter%2C+Frederik%22">Arnskötter, Frederik</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Leiss%2C+Kevin%22">Leiss, Kevin</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Okonechnikov%2C+Konstantin%22">Okonechnikov, Konstantin</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lisgo%2C+Steven%22">Lisgo, Steven</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Palkovits%2C+Miklós%22">Palkovits, Miklós</searchLink> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Science%22">Science</searchLink>. 1/29/2026, Vol. 391 Issue 6784, p1-26. 26p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Cerebellum%22">Cerebellum</searchLink><br /><searchLink fieldCode="DE" term="%22Human+evolution%22">Human evolution</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+regulation%22">Genetic regulation</searchLink><br /><searchLink fieldCode="DE" term="%22Mammals%22">Mammals</searchLink><br /><searchLink fieldCode="DE" term="%22Deep+learning%22">Deep learning</searchLink><br /><searchLink fieldCode="DE" term="%22Cis-regulatory+elements+%28Genetics%29%22">Cis-regulatory elements (Genetics)</searchLink><br /><searchLink fieldCode="DE" term="%22Chromatin%22">Chromatin</searchLink><br /><searchLink fieldCode="DE" term="%22Transcription+factors%22">Transcription factors</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Gene regulatory changes are considered major drivers of evolutionary innovations, including the cerebellum's expansion during human evolution, yet they remain largely unexplored. In this study, we combined single-nucleus measurements of gene expression and chromatin accessibility from six mammals (human, bonobo, macaque, marmoset, mouse, and opossum) to uncover conserved and diverged regulatory networks in cerebellum development. We identified core regulators of cell identity and developed sequence-based models that revealed conserved regulatory codes. By predicting chromatin accessibility across 240 mammalian species, we reconstructed the evolutionary histories of human cis-regulatory elements, identifying sets associated with positive selection and gene expression changes, including the recent gain of THRB expression in cerebellar progenitor cells. Collectively, our work reveals the shared and mammalian lineage-specific regulatory programs governing cerebellum development. Editor's summary: The mechanisms underlying brain development during evolution remain to be fully elucidated. Sarropulos et al. focused on the cerebellum and used previous single-nucleus multiome (RNA expression and DNA accessibility) and newly generated datasets across six mammalian species (human, bonobo, macaque, marmoset, mouse, and opossum) to develop a deep-learning model able to predict gene regulatory networks and cis-regulatory elements conserved or diverged during evolution for cerebellum development. By combining the cross-species multiomic resource with state-of-the-art machine learning and deep learning modeling of gene regulatory networks and enhancer grammar, this work provides valuable insights into brain development and evolution. —Mattia Maroso INTRODUCTION: The mammalian cerebellum has experienced many evolutionary innovations, but their molecular basis remains elusive. Most phenotypic changes are thought to be driven by mutations in cis-regulatory elements (CREs) such as enhancers and promoters, which control gene expression in a cell type–specific manner. However, the fast CRE evolution and our limited understanding of how DNA sequences encode regulatory activity have hindered our ability to study regulatory innovations. RATIONALE: Single-cell multiomics enable the mapping of CRE cell type specificity, whereas recent advances in machine learning facilitate predicting CRE accessibility from DNA sequence. We reasoned that if CRE sequence codes of cerebellar cell types are conserved across mammals, then we could use sequence-based deep learning models to reconstruct CRE evolutionary histories from genomic sequences and identify sequence changes underlying gene regulatory innovation. RESULTS: We built comprehensive single-cell gene expression and chromatin accessibility atlases of cerebellum development across six mammalian species, human, bonobo, macaque, marmoset, mouse, and opossum, spanning 780,000 single-cell profiles. We aligned developmental timelines between species, found common cell types, and dated our previously reported expansion of fetal Purkinje cells in the human lineage within the past 40 million years, highlighting a recent evolutionary innovation in the cerebellum. By inferring gene regulatory networks, we identified major transcription factor regulators of cerebellar cell identities and showed that their activity is largely conserved across species. Grouping CREs on the basis of their spatiotemporal accessibility revealed shared transcription factor motif signatures between human and mouse CREs, suggesting that their regulatory codes, i.e., motif combinations, are conserved despite extensive turnover of individual CREs. Next, we developed deep learning models that successfully predicted cerebellar cell type–specific CRE accessibilities from DNA sequence across species. Using a model trained on human and mouse data, DeepCeREvo (deep learning of cerebellar regulatory evolution), we demonstrated that the logic linking DNA sequence to CRE function, the regulatory grammar, of cerebellar cell types remained markedly stable over 160 million years of mammalian evolution. Building on this, we expanded our predictions to 240 mammalian genomes and reconstructed the evolutionary histories of human CREs. We identified clade-specific CREs that, after their emergence, were preserved, and detected signs of positive selection in human-specific elements, suggesting potential links to evolutionary innovations. We validated these predictions using nonhuman primate datasets not included in model training and enhancer reporter assays. Finally, we linked primate-specific CREs to genes with expression gains in the same cell type in the primate lineage. Notably, we traced an expression gain of THRB in human early progenitor cells to single-nucleotide substitutions that potentially created a new CRE ~3 kilobases upstream of the transcription start site ~25 to 40 million years ago. CONCLUSION: Our study provides a comprehensive framework for understanding gene regulatory evolution by combining comparative single-cell genomics with machine learning approaches. We demonstrate that despite rapid turnover of individual regulatory elements, conserved regulatory grammar governs cell type–specific gene expression in cerebellum development across mammals. By linking specific sequence changes to expression evolution, we identified regulatory innovations that likely contributed to human cerebellar evolution. This approach is broadly applicable to understanding regulatory evolution across tissues and species. Single-cell multiomics analysis of cerebellar regulatory evolution across mammals.: Single-cell multiomics atlases delineate gene regulation of cerebellar cell types across species (left). Sequence-based deep learning models revealed that the regulatory grammar, the sequence logic underlying CRE accessibility, of cerebellar cell types has been conserved over 160 million years of mammalian evolution, enabling inference of evolutionary histories of human CREs using orthologous regions across 240 mammals (top right). Recent innovations in human CREs are linked to changes in gene expression between species (bottom right). [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Science is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=191204548
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1126/science.adw9154
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 26
        StartPage: 1
    Subjects:
      – SubjectFull: Cerebellum
        Type: general
      – SubjectFull: Human evolution
        Type: general
      – SubjectFull: Genetic regulation
        Type: general
      – SubjectFull: Mammals
        Type: general
      – SubjectFull: Deep learning
        Type: general
      – SubjectFull: Cis-regulatory elements (Genetics)
        Type: general
      – SubjectFull: Chromatin
        Type: general
      – SubjectFull: Transcription factors
        Type: general
    Titles:
      – TitleFull: The evolution of gene regulation in mammalian cerebellum development.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Sarropoulos, Ioannis
      – PersonEntity:
          Name:
            NameFull: Sepp, Mari
      – PersonEntity:
          Name:
            NameFull: Yamada, Tetsuya
      – PersonEntity:
          Name:
            NameFull: Schäfer, Philipp S. L.
      – PersonEntity:
          Name:
            NameFull: Trost, Nils
      – PersonEntity:
          Name:
            NameFull: Schmidt, Julia
      – PersonEntity:
          Name:
            NameFull: Schneider, Céline
      – PersonEntity:
          Name:
            NameFull: Drummer, Charis
      – PersonEntity:
          Name:
            NameFull: Mißbach, Sophie
      – PersonEntity:
          Name:
            NameFull: Taskiran, Ibrahim I.
      – PersonEntity:
          Name:
            NameFull: Hecker, Nikolai
      – PersonEntity:
          Name:
            NameFull: Bravo González-Blas, Carmen
      – PersonEntity:
          Name:
            NameFull: Frömel, Robert
      – PersonEntity:
          Name:
            NameFull: Joshi, Piyush
      – PersonEntity:
          Name:
            NameFull: Leushkin, Evgeny
      – PersonEntity:
          Name:
            NameFull: Arnskötter, Frederik
      – PersonEntity:
          Name:
            NameFull: Leiss, Kevin
      – PersonEntity:
          Name:
            NameFull: Okonechnikov, Konstantin
      – PersonEntity:
          Name:
            NameFull: Lisgo, Steven
      – PersonEntity:
          Name:
            NameFull: Palkovits, Miklós
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 29
              M: 01
              Text: 1/29/2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 00368075
          Numbering:
            – Type: volume
              Value: 391
            – Type: issue
              Value: 6784
          Titles:
            – TitleFull: Science
              Type: main
ResultId 1