bioRxivEvolutionary BiologyPreprint
Evolutionary Origins of Molecular Programs Underlying Brain Circuitry
Z HuangiD, Shenglong Li, Zhenkun ZhuangiD, Duoyuan CheniD, Xiao DuiD, Qun LiuiD, Cirong LiuiD, Shaojie MaiD, Yidi SuniD, Hongli DuiD, Shiping LiuiD, Guangyi FaniD, Longqi LiuiD, Shijie HaoiD
Abstract
The vertebrate pallium harbors independently evolved structures that, nevertheless, support strikingly similar sensory and cognitive circuit architectures. The mechanisms and evolutionary timing driving the emergence of these parallel pallial circuits remain unelucidated. Here, we integrated spatial transcriptomic and single-nucleus RNA-seq datasets from eight representative vertebrate species spanning approximately 500 million years of evolution to reconstruct the evolutionary assembly of the primary sensory-allocortical (Pr-Al) molecular axis, a conserved cortical hierarchical axis defined in our prior work. We uncovered that Pr- and Al-like neuronal identities are deeply conserved across sarcopterygians, encompassing all tetrapods and lobe-finned fishes. Intriguingly, this ancestral neuronal homology is uncoupled from spatially partitioned patterning: only tetrapods further compartmentalized these Pr- and Al- neurons into distinct pallium regions. Functional enrichment of Pr- and Al- gene programs uncovered a conserved tetrapod genetic core suite including MAPK signaling and axon guidance pathways. This core toolkit underwent sequential functional refinement from amphibians through mammals. Notably, mammals and birds convergently evolved association-cortical molecular profiles enriched for synaptic regulatory genes to support advanced cognitive functions. Collectively, this work delineates a stepwise vertebrate pallium evolutionary paradigm that explains how conserved molecular modules shape spatially organized brain circuitry across deep evolutionary time.
- organism: mouse
- organism: human
- organism: zebrafish
- assay: spatial transcriptomics
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: clustering
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
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