Brain Wiring and Supragranular-Enriched Genes Linked to Protracted Human Frontal Cortex Development

Hendy, Jasmine P; Takahashi, Emi; Kouwe, André J van der; Charvet, Christine J.

doi:10.1093/cercor/bhaa135

Cited by 12 publications

(18 citation statements)

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“…R. Soc. B 288: 20202987 select lineages [10,15,17,20,21,50]. The sole use of transcription to find corresponding ages may be problematic because of variation in sample quality and genome coverage.…”

Section: Discussionmentioning

confidence: 99%

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Cutting across structural and transcriptomic scales translates time across the lifespan in humans and chimpanzees

Charvet

2021

Proc. R. Soc. B.

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How the unique capacities of human cognition arose in evolution is a question of enduring interest. It is still unclear which developmental programmes are responsible for the emergence of the human brain. The inability to determine corresponding ages between humans and apes has hampered progress in detecting developmental programmes leading to the emergence of the human brain. I harness temporal variation in anatomical, behavioural and transcriptional variation to determine corresponding ages from fetal to postnatal development and ageing, between humans and chimpanzees. This multi-dimensional approach results in 137 corresponding time points across the lifespan, from embryonic day 44 to approximately 55 years of age, in humans and their equivalent ages in chimpanzees. I used these data to test whether developmental programmes, such as the timeline of prefrontal cortex (PFC) maturation, previously claimed to differ between humans and chimpanzees, do so once variation in developmental schedules is controlled for. I compared the maturation of frontal cortex projections from structural magnetic resonance (MR) scans and from temporal variation in the expression of genes used to track long-range projecting neurons (i.e. supragranular-enriched genes) in chimpanzees and humans. Contrary to what has been suggested, the timetable of PFC maturation is not unusually extended in humans. This dataset, which is the largest with which to determine corresponding ages across humans and chimpanzees, provides a rigorous approach to control for variation in developmental schedules and to identify developmental programmes responsible for unique features of the human brain.

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Section: Discussionmentioning

confidence: 99%

“…This is because temporal variation in SE gene expression aligns with the growth of white matter pathways across species [19]. The expression of select SE genes evolved with modifications in tractography from diffusion MR imaging [21,27,28]. Finally, the expression of SE genes covary with functional connectivity across the human brain [29].…”

Section: Introductionmentioning

confidence: 99%

Cutting across structural and transcriptomic scales translates time across the lifespan in humans and chimpanzees

Charvet

2021

Proc. R. Soc. B.

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“…We compared white matter growth to test for variation in the timeline of FC circuits across species. Our definitions of FC and PFC follow those used previously (19,26). Structural MR scans of macaque brains were obtained from the UNC-Wisconsin Rhesus Macaque Neurodevelopment database (n=32; SI Appendix, Table S11).…”

Section: Structural Mr Scans To Test For Variation In Fc White Matter Maturationmentioning

confidence: 99%

“…An ANOVA with age and pathway types as factors showed trends but no signific effect for age (p<0.05) on the pathway types (F=13.16, p<0.01; n=32). Frontal cortex white matter growth in mice ceases before P60 (19); therefore, P60 should represent adult proportions in pathway types.…”

Section: Tractography Quantification and Comparison With Tract-tracersmentioning

confidence: 99%

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Tracing cortical circuits in humans and non-human primates from high resolution connectomic, transcriptomic, and temporal dimensions

Ofori

Baucum

et al. 2021

Preprint

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The neural circuits that support human cognition are a topic of enduring interest. Yet, the lack of tools available to map human brain circuits has precluded our ability to trace the human and non-human primate connectome. We harnessed high-resolution connectomic, anatomic, and transcriptomic data to investigate the evolution and development of frontal cortex circuitry. We applied machine learning to RNA sequencing data to find corresponding ages between humans and macaques and to compare the development of circuits across species. We transcriptionally defined neural circuits by testing for associations between gene expression and white matter maturation. We then considered transcriptional and structural growth to test whether frontal cortex circuit maturation is unusually extended in humans relative to other species. We also considered gene expression and high-resolution diffusion MR tractography of adult brains to test for cross-species variation in frontal cortex circuits. We found that frontal cortex circuitry development is extended in primates, and concomitant with an expansion in cortico-cortical pathways compared with mice in adulthood. Importantly, we found that these parameters varied relatively little across humans and studied primates. These data identify a surprising collection of conserved features in frontal cortex circuits across humans and Old World monkeys. Our work demonstrates that integrating transcriptional and connectomic data across temporal dimensions is a robust approach to trace the evolution of brain connectomics in primates.Significance StatementWe lack appropriate tools to visualize the human brain connectome. We develop new approaches to study connections in the human and non-human primate brains. The integration of transcription with structure offers an unprecedented opportunity to study circuitry evolution. Our integrative approach finds corresponding ages across species and transcriptionally defines neural circuits. We used this information to test for variation in circuit maturation across species and found a surprising constellation of similar features in frontal cortex neural circuits across humans and primates. Integrating across scales of biological organization expands the repertoire of tools available to study connections in primates, which opens new avenues to study connections in health and diseases of the human brain.

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Closing the gap from transcription to the structural connectome enhances the study of connections in the human brain

Charvet

2020

Developmental Dynamics

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The brain is composed of a complex web of networks but we have yet to map the structural connections of the human brain in detail. Diffusion MR imaging is a high‐throughput method that relies on the principle of diffusion to reconstruct tracts (ie, pathways) across the brain. Although diffusion MR tractography is an exciting method to explore the structural connectivity of the brain in development and across species, the tractography has at times led to questionable interpretations. There are at present few if any alternative methods to trace structural pathways in the human brain. Given these limitations and the potential of diffusion MR imaging to map the human connectome, it is imperative that we develop new approaches to validate neuroimaging techniques. I discuss our recent studies integrating neuroimaging with transcriptional and anatomical variation across humans and other species over the course of development and in adulthood. Developing a novel framework to harness the potential of diffusion MR tractography provides new and exciting opportunities to study the evolution of developmental mechanisms generating variation in connections and bridge the gap between model systems to humans.

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Brain Wiring and Supragranular-Enriched Genes Linked to Protracted Human Frontal Cortex Development

Cited by 12 publications

References 58 publications

Cutting across structural and transcriptomic scales translates time across the lifespan in humans and chimpanzees

Cutting across structural and transcriptomic scales translates time across the lifespan in humans and chimpanzees

Tracing cortical circuits in humans and non-human primates from high resolution connectomic, transcriptomic, and temporal dimensions

Closing the gap from transcription to the structural connectome enhances the study of connections in the human brain

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