1. Evolutionary Biology
  2. Neuroscience

A brain-wide analysis maps structural evolution to distinct anatomical module

  1. Robert A Kozol  Is a corresponding author
  2. Andrew J Conith
  3. Anders Yuiska
  4. Alexia Cree-Newman
  5. Bernadeth Tolentino
  6. Kasey Banesh
  7. Alexandra Paz
  8. Evan Lloyd
  9. Johanna E Kowalko
  10. Alex C Keene
  11. Craig Albertson
  12. Erik R Duboue  Is a corresponding author
  1. Florida Atlantic University, United States
  2. University of Massachusetts Amherst, United States
  3. Texas A&M University, United States
  4. Lehigh University, United States
https://doi.org/10.7554/eLife.80777
Share this article
Cite this article
  1. Robert A Kozol
  2. Andrew J Conith
  3. Anders Yuiska
  4. Alexia Cree-Newman
  5. Bernadeth Tolentino
  6. Kasey Banesh
  7. Alexandra Paz
  8. Evan Lloyd
  9. Johanna E Kowalko
  10. Alex C Keene
  11. Craig Albertson
  12. Erik R Duboue
(2023)
A brain-wide analysis maps structural evolution to distinct anatomical module
eLife 12:e80777.
https://doi.org/10.7554/eLife.80777
  2. Download BibTeX
  3. Download .RIS

Abstract

The vertebrate brain is highly conserved topologically, but less is known about neuroanatomical variation between individual brain regions. Neuroanatomical variation at the regional level is hypothesized to provide functional expansion, building upon ancestral anatomy needed for basic functions. Classically, animal models used to study evolution have lacked tools for detailed anatomical analysis that are widely used in zebrafish and mice, presenting a barrier to studying brain evolution at fine scale. In this study, we sought to investigate the evolution of brain anatomy using a single species of fish consisting of divergent surface and cave morphs, that permits functional genetic testing of regional volume and shape across the entire brain. We generated a high-resolution brain atlas for the blind Mexican cavefish Astyanax mexicanus and coupled the atlas with automated computational tools to directly assess variability in brain region shape and volume across all populations. We measured the volume and shape of every grossly defined neuroanatomical region of the brain and assessed correlations between anatomical regions in surface fish, cavefish, and surface x cave F2 hybrids, whose phenotypes span the range of surface to cave. We find that dorsal regions of the brain are contracted, while ventral regions have expanded, with F2 hybrid data providing support for developmental constraint along the dorsal-ventral axis. Furthermore, these dorsal-ventral relationships in anatomical variation show similar patterns for both volume and shape, suggesting that the anatomical evolution captured by these two parameters, could be driven by similar developmental mechanisms. Together, these data demonstrate that Astyanax mexicanus is a powerful system for functionally determining basic principles of brain evolution and will permit testing how genes influence early patterning events to drive brain-wide anatomical evolution.

Data availability

All raw and analyzed data, custom code and adapted tools have been uploaded into a Dryad repository, doi:10.5061/dryad.w9ghx3frw. Custom code and adaptive tools are also included in the supplemental material.

The following data sets were generated

Article and author information

Author details

  1. Robert A Kozol

    Jupiter Life Science Initiative, Florida Atlantic University, Jupiter, United States
    For correspondence
    rkozol@fau.edu
    Competing interests
    The authors declare that no competing interests exist.

  2. Andrew J Conith

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

  3. Anders Yuiska

    Jupiter Life Science Initiative, Florida Atlantic University, Jupiter, United States
    Competing interests
    The authors declare that no competing interests exist.

  4. Alexia Cree-Newman

    Jupiter Life Science Initiative, Florida Atlantic University, Jupiter, United States
    Competing interests
    The authors declare that no competing interests exist.

  5. Bernadeth Tolentino

    Jupiter Life Science Initiative, Florida Atlantic University, Jupiter, United States
    Competing interests
    The authors declare that no competing interests exist.

  6. Kasey Banesh

    Jupiter Life Science Initiative, Florida Atlantic University, Jupiter, United States
    Competing interests
    The authors declare that no competing interests exist.

  7. Alexandra Paz

    Jupiter Life Science Initiative, Florida Atlantic University, Jupiter, United States
    Competing interests
    The authors declare that no competing interests exist.

  8. Evan Lloyd

    Department of Biology, Texas A&M University, College Station, United States
    Competing interests
    The authors declare that no competing interests exist.

  9. Johanna E Kowalko

    Department of Biological Sciences, Lehigh University, Bethlehem, United States
    Competing interests
    The authors declare that no competing interests exist.

  10. Alex C Keene

    Department of Biology, Texas A&M University, College Station, United States
    Competing interests
    The authors declare that no competing interests exist.

  11. Craig Albertson

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

  12. Erik R Duboue

    Jupiter Life Science Initiative, Florida Atlantic University, Jupiter, United States
    For correspondence
    eduboue@fau.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3303-5149

Funding

National Institutes of Health (R15MH118625)

  • Erik R Duboue

National Institutes of Health (R01GM127872)

  • Alex C Keene

National Institutes of Health (R35GM138345)

  • Johanna E Kowalko

National Institutes of Health (R15HD099022)

  • Johanna E Kowalko

National Institutes of Health (R21NS122166)

  • Johanna E Kowalko
  • Alex C Keene

National Science Foundation (1923372)

  • Johanna E Kowalko
  • Alex C Keene
  • Erik R Duboue

National Science Foundation (2202359)

  • Johanna E Kowalko

Human Frontier Science Program (RGP0062)

  • Alex C Keene

National Institutes of Health (DE026446)

  • Craig Albertson

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

Ethics

Animal experimentation: Mexican tetras were cared for in accordance with NIH guidelines and all experiments were approved by the Florida Atlantic University Institutional Care and Use Committee protocol #A1929.

Copyright

© 2023, Kozol 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

  • 1,109
    views
  • 137
    downloads
  • 7
    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. Robert A Kozol
  2. Andrew J Conith
  3. Anders Yuiska
  4. Alexia Cree-Newman
  5. Bernadeth Tolentino
  6. Kasey Banesh
  7. Alexandra Paz
  8. Evan Lloyd
  9. Johanna E Kowalko
  10. Alex C Keene
  11. Craig Albertson
  12. Erik R Duboue
(2023)
A brain-wide analysis maps structural evolution to distinct anatomical module
eLife 12:e80777.
https://doi.org/10.7554/eLife.80777

Share this article

https://doi.org/10.7554/eLife.80777

Categories and tags

Further reading

    1. Chromosomes and Gene Expression
    2. Evolutionary Biology

    The emergence and evolution of gene expression in genome regions replete with regulatory motifs

    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. Evolutionary Biology

    Estimating dispersal rates and locating genetic ancestors with genome-wide genealogies

    Matthew Osmond, Graham Coop
    Research Article Updated

    Spatial patterns in genetic diversity are shaped by individuals dispersing from their parents and larger-scale population movements. It has long been appreciated that these patterns of movement shape the underlying genealogies along the genome leading to geographic patterns of isolation-by-distance in contemporary population genetic data. However, extracting the enormous amount of information contained in genealogies along recombining sequences has, until recently, not been computationally feasible. Here, we capitalize on important recent advances in genome-wide gene-genealogy reconstruction and develop methods to use thousands of trees to estimate per-generation dispersal rates and to locate the genetic ancestors of a sample back through time. We take a likelihood approach in continuous space using a simple approximate model (branching Brownian motion) as our prior distribution of spatial genealogies. After testing our method with simulations we apply it to Arabidopsis thaliana. We estimate a dispersal rate of roughly 60 km2/generation, slightly higher across latitude than across longitude, potentially reflecting a northward post-glacial expansion. Locating ancestors allows us to visualize major geographic movements, alternative geographic histories, and admixture. Our method highlights the huge amount of information about past dispersal events and population movements contained in genome-wide genealogies.

    1. Evolutionary Biology

    Discarded sequencing reads uncover natural variation in pest resistance in Thlaspi arvense

    Dario Galanti, Jun Hee Jung ... Oliver Bossdorf
    Research Article

    Understanding the genomic basis of natural variation in plant pest resistance is an important goal in plant science, but it usually requires large and labor-intensive phenotyping experiments. Here, we explored the possibility that non-target reads from plant DNA sequencing can serve as phenotyping proxies for addressing such questions. We used data from a whole-genome and -epigenome sequencing study of 207 natural lines of field pennycress (Thlaspi arvense) that were grown in a common environment and spontaneously colonized by aphids, mildew, and other microbes. We found that the numbers of non-target reads assigned to the pest species differed between populations, had significant SNP-based heritability, and were associated with climate of origin and baseline glucosinolate contents. Specifically, pennycress lines from cold and thermally fluctuating habitats, presumably less favorable to aphids, showed higher aphid DNA load, i.e., decreased aphid resistance. Genome-wide association analyses identified genetic variants at known defense genes but also novel genomic regions associated with variation in aphid and mildew DNA load. Moreover, we found several differentially methylated regions associated with pathogen loads, in particular differential methylation at transposons and hypomethylation in the promoter of a gene involved in stomatal closure, likely induced by pathogens. Our study provides first insights into the defense mechanisms of Thlaspi arvense, a rising crop and model species, and demonstrates that non-target whole-genome sequencing reads, usually discarded, can be leveraged to estimate intensities of plant biotic interactions. With rapidly increasing numbers of large sequencing datasets worldwide, this approach should have broad application in fundamental and applied research.