bioRxiv Science⌕ Search

bioRxiv · 10.64898/2025.12.11.693619

Orthogonal Modes of Gene Expression Evolution Shape Human Neocortical Development and Disease Vulnerability

Abstract

The neocortex is responsible for higher-order cognitive abilities such as language, abstract reasoning, and executive function--capacities that are particularly advanced in humans. To elucidate the molecular foundations of neocortical evolution in the human lineage, it is essential to examine how conserved gene repertoires have undergone expression changes relative to other mammals. The expression changes in conserved genes are widely regarded as key drivers of the phenotypic evolution of human-specific traits. In this study, we performed a comprehensive comparative single-cell transcriptomic analysis of fetal neocortical development across four mammalian species: human, macaque, mouse, and ferret. To validate human-specific expression changes, we further analyzed brain organoids derived from both human and chimpanzee stem cells. Genes exhibiting human-specific expression shifts were systematically classified along three orthogonal dimensions: overall expression level (Human Level Distinctive; HLD), temporal expression trend (Human Trend Distinctive; HTD), and differentiation lineage specificity (Human Differentiation trajectory Distinctive; HDD). HLD genes were frequently enriched for long introns and located near Human Accelerated Regions (HARs), and showed pronounced upregulation in humans. These genes were strongly associated with neurodevelopmental disorders such as autism spectrum disorder and developmental delay, as well as with megalencephaly and glioblastoma. HTD genes, in contrast, exhibited a unique pattern in humans, peaking early in development and subsequently declining--opposite to the steadily increasing trends observed in other species. These genes were significantly enriched for oxidative phosphorylation and ribosomal functions, pointing to a temporally restricted elevation in biosynthetic activity in early human corticogenesis. HDD genes displayed a marked shift in lineage-specific expression: cilia-related genes that are typically expressed in apical progenitors in non-human species were instead highly expressed in outer radial glia (oRGs) in humans. This spatial reorganization of ciliary gene activity suggests an oRG-specific adaptation in signaling architecture. Together, these results highlight the diversity of regulatory changes that have shaped human cortical development. Distinct classes of gene expression evolution--mediated in part by HARs--appear to have contributed not only to the expansion and increased complexity of the human neocortex, but also to its heightened vulnerability to neurodevelopmental and oncogenic pathologies. The identified human distinctive genes will be the target of future experimental verification to elucidate the precise molecular mechanisms regulating human-specific aspects of cortical development.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sheu, X. D., Yamauchi, Y. Y., Suzuki, I. K.. 2025-12-12. Orthogonal Modes of Gene Expression Evolution Shape Human Neocortical Development and Disease Vulnerability. https://doi.org/10.64898/2025.12.11.693619

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Targeted finetuning enables co-folding models to learn ligand-induced protein conformational states

Advances in protein structure prediction have enabled all-atom protein-ligand co-folding models that predict bound conformations directly from sequence and small-molecule structure. However, these models often fail to generalize to novel binding sites or alternative protein conformational states, limiting their utility for chemical biology and drug discovery. Here we show this limitation reflects training data bias rather than architectural constraints and can be overcome through targeted finetuning. Using ten previously unseen X-ray structures of Werner (WRN) helicase from a drug discovery program, we finetune Boltz-1 to learn both an allosteric binding site and a large conformational change locking the enzyme in an inactive state, while preserving accuracy on the ATP-bound state. The finetuned model generalizes to different chemical series and transfers the conformational logic across RecQ-family helicases in a binding-site sequence-dependent manner. This approach provides a blueprint for adapting foundation models as new structural and mechanistic data emerge, enabling co-folding networks to capture ligand-induced conformational switches and binding poses absent from their training data but central to biological regulation and therapeutic intervention.

bioinformatics↗

Benchmarking single-cell foundation models for aging biology

Single cell foundation models (scFMs) provide representations of cellular states, but their utility across biological questions in aging research remains unclear. We established a benchmark of cellular representations for aging research, evaluating ten general-purpose scFMs, three aging-specific models and conventional methods across five biological questions using more than 2.5 million single cell transcriptomes. Using frozen pretrained representations, Geneformer performed best among scFMs for chronological age prediction and age pseudotime concordance, although 2,000 highly variable genes achieved higher mean performance. Several scFMs captured positive molecular age shifts across three disease contexts, consistent with reported aging-associated changes. SCimilarity performed well for rare cellular state identification across out-of-distribution datasets, exceeding aging specific models and conventional baselines. At the gene level, scGPT showed the highest recovery of reference TF target interactions, including aging-related regulatory hubs. Overall, scFMs supported diverse aging analyses, but performance depended on the biological question, highlighting their utility for rare cellular state identification and regulatory analysis.

bioinformatics↗

CryoMV: Structure-Prior-Guided Modeling and Real-Particle Validation of Continuous Conformational Transitions in Cryo-EM

Continuous protein conformations are essential for understanding fundamental biological processes and supporting drug discovery. Although cryo-EM can resolve individual states at high resolution, recovering continuous heterogeneity from 2D particle images remains challenging. High noise, motion blur, and limited structural priors make it difficult to accurately generate and validate high-resolution continuous conformations using raw particle data. Here, we introduce cryoMV, a framework that integrates structure-prior-guided modeling with real-particle validation for continuous conformational transitions. CryoMV uses reference density maps to establish structural anchors and motion priors, models candidate transition paths between selected conformations, and transfers the learned representation to raw 2D cryo-EM particle images. Each candidate conformation is subsequently evaluated using the estimated particle poses and contrast transfer functions. Supported conformations are reconstructed through raw particle back-projection and assessed using canonical half-maps and Fourier shell correlation. On EMPIAR-10516 and EMPIAR-10345, cryoMV achieves excellent performance in terms of robustness, verifiability, and reconstruction resolution. By incorporating structure-prior modeling and evidence from the raw particles, cryoMV offers an explicit mechanism for assessing whether generated conformations are supported by experimental data and provides a practical approach to reducing model-induced artifacts in continuous cryo-EM heterogeneity analysis.

bioinformatics↗