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Divergent connectomic organization delineates genetic evolutionary traits in the human brain

Bueichekú E, Gonzalez-de-Echavarri JM, Ortiz-Teran L, Montal V, d'Oleire Uquillas F, De Marcos L, Orwig W, Kim CM, Ortiz-Teran E, Basaia S, Diez I, Sepulcre J

Abstracto

The relationship between human brain connectomics and genetic evolutionary traits remains elusive due to the inherent challenges in combining complex associations within cerebral tissue. In this study, insights are provided about the relationship between connectomics, gene expression and divergent evolutionary pathways from non-human primates to humans. Using in vivo human brain resting-state data, we detected two co-existing idiosyncratic functional systems: the segregation network, in charge of module specialization, and the integration network, responsible for information flow. Their topology was approximated to whole-brain genetic expression (Allen Human Brain Atlas) and the co-localization patterns yielded that neuron communication functionalities-linked to Neuron Projection-were overrepresented cell traits. Homologue-orthologue comparisons using dN/dS-ratios bridged the gap between neurogenetic outcomes and biological data, summarizing the known evolutionary divergent pathways within the Homo Sapiens lineage. Evidence suggests that a crosstalk between functional specialization and information flow reflects putative biological qualities of brain architecture, such as neurite cellular functions like axonal or dendrite processes, hypothesized to have been selectively conserved in the species through positive selection. These findings expand our understanding of human brain function and unveil aspects of our cognitive trajectory in relation to our simian ancestors previously left unexplored.

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Reference

Bueichekú E, Gonzalez-de-Echavarri JM, Ortiz-Teran L, Montal V, d'Oleire Uquillas F, De Marcos L, Orwig W, Kim CM, Ortiz-Teran E, Basaia S, Diez I, Sepulcre J. Divergent connectomic organization delineates genetic evolutionary traits in the human brain. Sci Rep. 2021 Oct 4;11(1):19692. doi: 10.1038/s41598-021-99082-6. PMID: 34608211; PMCID: PMC8490416.