Tempo and mode of gene expression evolution in the brain across primates
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Evaluation Summary:
This paper represents a significant contribution to the study of gene expression and brain evolution in primates, which will be of interest to the evolutionary biology, anthropology, and comparative neuroscience communities. By performing RNA-seq on 18 taxa across the breadth of the extant primate phylogeny, the authors can examine how gene expression levels have changed over the past 70 million years of evolution and attempt to infer genes that contribute to the large amount of variation in brain size across primates. While the data set itself is valuable and exciting, methodological detail is lacking and several opportunities to leverage phylogenetically informed methods to study gene expression and brain size evolution are missed.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)
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Abstract
Primate evolution has led to a remarkable diversity of behavioral specializations and pronounced brain size variation among species (Barton, 2012; DeCasien and Higham, 2019; Powell et al., 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 represent 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 the study of genetic regulation of brain evolution.
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Evaluation Summary:
This paper represents a significant contribution to the study of gene expression and brain evolution in primates, which will be of interest to the evolutionary biology, anthropology, and comparative neuroscience communities. By performing RNA-seq on 18 taxa across the breadth of the extant primate phylogeny, the authors can examine how gene expression levels have changed over the past 70 million years of evolution and attempt to infer genes that contribute to the large amount of variation in brain size across primates. While the data set itself is valuable and exciting, methodological detail is lacking and several opportunities to leverage phylogenetically informed methods to study gene expression and brain size evolution are missed.
(This preprint has been reviewed by eLife. We include the public reviews from the …
Evaluation Summary:
This paper represents a significant contribution to the study of gene expression and brain evolution in primates, which will be of interest to the evolutionary biology, anthropology, and comparative neuroscience communities. By performing RNA-seq on 18 taxa across the breadth of the extant primate phylogeny, the authors can examine how gene expression levels have changed over the past 70 million years of evolution and attempt to infer genes that contribute to the large amount of variation in brain size across primates. While the data set itself is valuable and exciting, methodological detail is lacking and several opportunities to leverage phylogenetically informed methods to study gene expression and brain size evolution are missed.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)
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Reviewer #1 (Public Review):
I find the dataset and the questions driving this manuscript very compelling, and the analyses currently presented a very promising start, but I think the manuscript falls short of fulfilling its potential. My chief concern is the sparse amount of detail in both the methods (especially the wrangling of the de novo transcriptomes and all the downstream consequences of choices made then) and results that makes it hard to evaluate what are fundamentally some very tricky analyses. In turn, this undersells the value of this very rich and unique dataset, which again, I commend the authors for collecting.
As might be expected given the singularity of humans' cognitive abilities, much of the paper focuses on comparing gene expression in the human brain relative to other primates, to a degree that sometimes strikes …
Reviewer #1 (Public Review):
I find the dataset and the questions driving this manuscript very compelling, and the analyses currently presented a very promising start, but I think the manuscript falls short of fulfilling its potential. My chief concern is the sparse amount of detail in both the methods (especially the wrangling of the de novo transcriptomes and all the downstream consequences of choices made then) and results that makes it hard to evaluate what are fundamentally some very tricky analyses. In turn, this undersells the value of this very rich and unique dataset, which again, I commend the authors for collecting.
As might be expected given the singularity of humans' cognitive abilities, much of the paper focuses on comparing gene expression in the human brain relative to other primates, to a degree that sometimes strikes me as somewhat self-limiting. For example, the analyses of evolutionary rate seem to me to only scratch the surface of the sort of questions this dataset makes addressable for the first time and I would have dearly enjoyed seeing explored in more depth. As such, my main concern is not so much with any perceived critical flaws in the analyses presented, but with what has now come almost within reach but hasn't been addressed in this manuscript.
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Reviewer #2 (Public Review):
Bauernfeind et al. have created a remarkable transcriptome dataset of unprecedented content, comprising 18 primate species and four brain regions. They analyse the dataset to address questions on divergence in brain gene expression, as well as human-specific expression patterns.
The authors report that both humans and chimpanzees (hominoids) show unexpectedly high levels of brain gene expression divergence relative to the 16 other primates studied, including other great apes. Most previous work in the field had concentrated on human-specific brain expression changes, relative to chimpanzees and macaques, and this result is highly interesting in that it suggests that many unique features of the human brain, reflected in gene expression, are actually shared with chimpanzees. In fact, this may not be so …
Reviewer #2 (Public Review):
Bauernfeind et al. have created a remarkable transcriptome dataset of unprecedented content, comprising 18 primate species and four brain regions. They analyse the dataset to address questions on divergence in brain gene expression, as well as human-specific expression patterns.
The authors report that both humans and chimpanzees (hominoids) show unexpectedly high levels of brain gene expression divergence relative to the 16 other primates studied, including other great apes. Most previous work in the field had concentrated on human-specific brain expression changes, relative to chimpanzees and macaques, and this result is highly interesting in that it suggests that many unique features of the human brain, reflected in gene expression, are actually shared with chimpanzees. In fact, this may not be so surprising in the light of our growing understanding of chimpanzee cognitive skills.
It is also notable that Bauernfeind et al. find little to no saturation in expression divergence with time among primates in the brain (using human as reference), in contrast to saturation reported at longer evolutionary scale. This suggests a reevaluation of models of drift and selection on brain gene expression.
Meanwhile, the data may deserve deeper analysis both with respect to overall expression divergence across primates and human-specific expression divergence, and also in the context of the correlation between gene expression and brain size, a major question studied by the authors. These could be preferentially performed within explicit phylogenetic frameworks that include positive selection, which could help distinguish drift from adaptive changes.
Without such explicit analysis, what the authors report in the current manuscript's abstract about genes with expression levels correlated with brain size could be simply reflecting phylogenetic divergence. Also, the conclusion that these genes show positive selection signatures in their regulatory regions may not be supported by the data, as multiple testing correction seems to be lacking for the analysis applied here.
Nevertheless, the authors should be commended for compiling this dataset, which holds the potential for significantly furthering our understanding into expression divergence. The dataset could be used effectively to test the roles of cell type composition changes vs. cell type-specific (or cell-autonomous) changes across the identified expression divergence patterns, or to study the relative roles of trans- vs. cis-driven divergence.
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