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

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

  • 1,868
    views
  • 292
    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

Further reading

    1. Chromosomes and Gene Expression
    2. Evolutionary Biology
    Timothy Fuqua, Yiqiao Sun, Andreas Wagner
    Research Article

    Gene regulation is essential for life and controlled by regulatory DNA. Mutations can modify the activity of regulatory DNA, and also create new regulatory DNA, a process called regulatory emergence. Non-regulatory and regulatory DNA contain motifs to which transcription factors may bind. In prokaryotes, gene expression requires a stretch of DNA called a promoter, which contains two motifs called –10 and –35 boxes. However, these motifs may occur in both promoters and non-promoter DNA in multiple copies. They have been implicated in some studies to improve promoter activity, and in others to repress it. Here, we ask whether the presence of such motifs in different genetic sequences influences promoter evolution and emergence. To understand whether and how promoter motifs influence promoter emergence and evolution, we start from 50 ‘promoter islands’, DNA sequences enriched with –10 and –35 boxes. We mutagenize these starting ‘parent’ sequences, and measure gene expression driven by 240,000 of the resulting mutants. We find that the probability that mutations create an active promoter varies more than 200-fold, and is not correlated with the number of promoter motifs. For parent sequences without promoter activity, mutations created over 1500 new –10 and –35 boxes at unique positions in the library, but only ~0.3% of these resulted in de-novo promoter activity. Only ~13% of all –10 and –35 boxes contribute to de-novo promoter activity. For parent sequences with promoter activity, mutations created new –10 and –35 boxes in 11 specific positions that partially overlap with preexisting ones to modulate expression. We also find that –10 and –35 boxes do not repress promoter activity. Overall, our work demonstrates how promoter motifs influence promoter emergence and evolution. It has implications for predicting and understanding regulatory evolution, de novo genes, and phenotypic evolution.

    1. Chromosomes and Gene Expression
    2. Developmental Biology
    Valentin Babosha, Natalia Klimenko ... Oksana Maksimenko
    Research Article

    The male-specific lethal complex (MSL), which consists of five proteins and two non-coding roX RNAs, is involved in the transcriptional enhancement of X-linked genes to compensate for the sex chromosome monosomy in Drosophila XY males compared with XX females. The MSL1 and MSL2 proteins form the heterotetrameric core of the MSL complex and are critical for the specific recruitment of the complex to the high-affinity ‘entry’ sites (HAS) on the X chromosome. In this study, we demonstrated that the N-terminal region of MSL1 is critical for stability and functions of MSL1. Amino acid deletions and substitutions in the N-terminal region of MSL1 strongly affect both the interaction with roX2 RNA and the MSL complex binding to HAS on the X chromosome. In particular, substitution of the conserved N-terminal amino-acids 3–7 in MSL1 (MSL1GS) affects male viability similar to the inactivation of genes encoding roX RNAs. In addition, MSL1GS binds to promoters such as MSL1WT but does not co-bind with MSL2 and MSL3 to X chromosomal HAS. However, overexpression of MSL2 partially restores the dosage compensation. Thus, the interaction of MSL1 with roX RNA is critical for the efficient assembly of the MSL complex on HAS of the male X chromosome.