1. Chromosomes and Gene Expression
  2. Evolutionary Biology

Tempo and mode of gene expression evolution in the brain across primates

  1. Katherine Rickelton  Is a corresponding author
  2. Trisha M Zintel
  3. Jason Pizzollo
  4. Emily Miller
  5. John J Ely
  6. Mary Ann Raghanti
  7. William D Hopkins
  8. Patrick R Hof
  9. Chet C Sherwood
  10. Amy L Bauernfeind
  11. Courtney C Babbitt  Is a corresponding author
  1. University of Massachusetts Amherst, United States
  2. MAEBIOS, United States
  3. Kent State University, United States
  4. The University of Texas MD Anderson Cancer Center, United States
  5. Icahn School of Medicine at Mount Sinai, United States
  6. George Washington University, United States
  7. Washington University in St. Louis, United States
https://doi.org/10.7554/eLife.70276
Share this article
Cite this article
  1. Katherine Rickelton
  2. Trisha M Zintel
  3. Jason Pizzollo
  4. Emily Miller
  5. John J Ely
  6. Mary Ann Raghanti
  7. William D Hopkins
  8. Patrick R Hof
  9. Chet C Sherwood
  10. Amy L Bauernfeind
  11. Courtney C Babbitt
(2024)
Tempo and mode of gene expression evolution in the brain across primates
eLife 13:e70276.
https://doi.org/10.7554/eLife.70276
  2. Download BibTeX
  3. Download .RIS

Abstract

Primate evolution has led to a remarkable diversity of behavioral specializations and pronounced brain size variation among species (Barton, 2012; DeCasien & Higham, 2019; Powell, Isler, & Barton, 2017). Gene expression provides a promising opportunity for studying the molecular basis of brain evolution, but it has been explored in very few primate species to date (e.g. Khaitovich et al., 2005; Khrameeva et al., 2020; Ma et al., 2022; Somel et al., 2009). To understand the landscape of gene expression evolution across the primate lineage, we generated and analyzed RNA-Seq data from four brain regions in an unprecedented eighteen species. Here we show a remarkable level of variation in gene expression among hominid species, including humans and chimpanzees, despite their relatively recent divergence time from other primates. We found that individual genes display a wide range of expression dynamics across evolutionary time reflective of the diverse selection pressures acting on genes within primate brain tissue. Using our samples that represents a 190-fold difference in primate brain size, we identified genes with variation in expression most correlated with brain size. Our study extensively broadens the phylogenetic context of what is known about the molecular evolution of the brain across primates and identifies novel candidate genes for study of genetic regulation of brain evolution.

Data availability

Sequencing data have been deposited in the Short Read Archive: BioProject PRJNA639850

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Katherine Rickelton

    Department of Biology, University of Massachusetts Amherst, Amherst, United States
    For correspondence
    krickelton@umass.edu
    Competing interests
    The authors declare that no competing interests exist.

  2. Trisha M Zintel

    Department of Biology, University of Massachusetts Amherst, Amherst, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. Jason Pizzollo

    Department of Biology, University of Massachusetts Amherst, Amherst, United States
    Competing interests
    The authors declare that no competing interests exist.

  4. Emily Miller

    Department of Biology, University of Massachusetts Amherst, Amherst, United States
    Competing interests
    The authors declare that no competing interests exist.

  5. John J Ely

    Epidemiology Unit, MAEBIOS, Alamogordo, United States
    Competing interests
    The authors declare that no competing interests exist.

  6. Mary Ann Raghanti

    Department of Anthropology, Kent State University, Kent, United States
    Competing interests
    The authors declare that no competing interests exist.

  7. William D Hopkins

    Department of Comparative Medicine, The University of Texas MD Anderson Cancer Center, Bastrop, United States
    Competing interests
    The authors declare that no competing interests exist.

  8. Patrick R Hof

    Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, United States
    Competing interests
    The authors declare that no competing interests exist.

  9. Chet C Sherwood

    Department of Anthropology, George Washington University, Washington DC, United States
    Competing interests
    The authors declare that no competing interests exist.

  10. Amy L Bauernfeind

    Department of Neuroscience, Washington University in St. Louis, St Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8518-3819

  11. Courtney C Babbitt

    Department of Biology, University of Massachusetts Amherst, Amherst, United States
    For correspondence
    cbabbitt@bio.umass.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8793-4364

Funding

National Science Foundation (BCS-1750377)

  • Courtney C Babbitt

National Institutes of Health (T32 GM135096)

  • Katherine Rickelton

James S. McDonnell Foundation (220020293)

  • Chet C Sherwood

National Institutes of Health (NS-092988)

  • Chet C Sherwood

National Science Foundation (SMA-1542848)

  • Chet C Sherwood

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2024, Rickelton et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,922
    views
  • 295
    downloads
  • 2
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Katherine Rickelton
  2. Trisha M Zintel
  3. Jason Pizzollo
  4. Emily Miller
  5. John J Ely
  6. Mary Ann Raghanti
  7. William D Hopkins
  8. Patrick R Hof
  9. Chet C Sherwood
  10. Amy L Bauernfeind
  11. Courtney C Babbitt
(2024)
Tempo and mode of gene expression evolution in the brain across primates
eLife 13:e70276.
https://doi.org/10.7554/eLife.70276

Share this article

https://doi.org/10.7554/eLife.70276

Categories and tags

Research organism

Further reading

    1. Chromosomes and Gene Expression

    Sir2 and Fun30 regulate ribosomal DNA replication timing via MCM helicase positioning and nucleosome occupancy

    Carmina Lichauco, Eric J Foss ... Antonio Bedalov
    Research Article

    The association between late replication timing and low transcription rates in eukaryotic heterochromatin is well known, yet the specific mechanisms underlying this link remain uncertain. In Saccharomyces cerevisiae, the histone deacetylase Sir2 is required for both transcriptional silencing and late replication at the repetitive ribosomal DNA (rDNA) arrays. We have previously reported that in the absence of SIR2, a de-repressed RNA PolII repositions MCM replicative helicases from their loading site at the ribosomal origin, where they abut well-positioned, high-occupancy nucleosomes, to an adjacent region with lower nucleosome occupancy. By developing a method that can distinguish activation of closely spaced MCM complexes, here we show that the displaced MCMs at rDNA origins have increased firing propensity compared to the nondisplaced MCMs. Furthermore, we found that both activation of the repositioned MCMs and low occupancy of the adjacent nucleosomes critically depend on the chromatin remodeling activity of FUN30. Our study elucidates the mechanism by which Sir2 delays replication timing, and it demonstrates, for the first time, that activation of a specific replication origin in vivo relies on the nucleosome context shaped by a single chromatin remodeler.

    1. Chromosomes and Gene Expression

    Cryogenic Electron Microscopy: MagIC beads for scarce macromolecules

    Carlos Moreno-Yruela, Beat Fierz
    Insight

    Specialized magnetic beads that bind target proteins to a cryogenic electron microscopy grid make it possible to study the structure of protein complexes from dilute samples.

    1. Chromosomes and Gene Expression
    2. Structural Biology and Molecular Biophysics

    Surprising features of nuclear receptor interaction networks revealed by live-cell single-molecule imaging

    Liza Dahal, Thomas GW Graham ... Xavier Darzacq
    Research Article

    Type II nuclear receptors (T2NRs) require heterodimerization with a common partner, the retinoid X receptor (RXR), to bind cognate DNA recognition sites in chromatin. Based on previous biochemical and overexpression studies, binding of T2NRs to chromatin is proposed to be regulated by competition for a limiting pool of the core RXR subunit. However, this mechanism has not yet been tested for endogenous proteins in live cells. Using single-molecule tracking (SMT) and proximity-assisted photoactivation (PAPA), we monitored interactions between endogenously tagged RXR and retinoic acid receptor (RAR) in live cells. Unexpectedly, we find that higher expression of RAR, but not RXR, increases heterodimerization and chromatin binding in U2OS cells. This surprising finding indicates the limiting factor is not RXR but likely its cadre of obligate dimer binding partners. SMT and PAPA thus provide a direct way to probe which components are functionally limiting within a complex TF interaction network providing new insights into mechanisms of gene regulation in vivo with implications for drug development targeting nuclear receptors.