Summary: Researchers have provided the first large-scale demonstration that genes encode a comprehensive molecular “wiring map” that guides neurons to their appropriate targets across the entire brain.
Using a new machine learning framework named SPERRFY, the team showed that overlapping patterns of gene activity predict long-range neural connections. Their results validate and extend Roger Sperry’s chemoaffinity theory from simple sensory circuits to whole-brain organization, suggesting a shared molecular GPS underlies complex brain wiring.
Key Facts
- SPERRFY Decoding: The authors developed SPERRFY, an analysis pipeline that links a map of brain connections with spatial expression levels for 763 genes measured across 213 mouse brain regions.
- Predictive Power: By extracting overlapping gene expression gradients, the method reconstructed connectivity with a high prediction score of 0.88 (on a 0–1 scale), outperforming models that used only anatomical distance (score ~0.70).
- Two-Level Organization: Broad gene expression gradients establish overarching regional organization, while finer, local gradients refine specific axonal targeting within those regions.
- Whole-Brain Validation: This study provides computational, brain-wide support for Sperry’s chemoaffinity idea, showing that molecular gradients can account for connectivity beyond previously studied sensory systems.
Source: Nagoya University
How the brain’s complex circuits are genetically specified is a central question in neuroscience. This study shows that a combination of spatial gene expression patterns encodes positional information that guides axons to their proper targets, effectively producing a molecular map of neural wiring.
Published in Proceedings of the National Academy of Sciences, the findings were derived from machine learning analyses of mouse connectomic and transcriptomic data, and they open new possibilities for investigating brain development and disease.
Mapping connections between brain regions with data
The research, led by teams at Nagoya University, set out to uncover the organizing rules that guide axons during development. Axons are the elongated projections from neurons that establish the long-range links forming neural circuits.
SPERRFY integrates two complementary datasets: a connectome that documents which brain regions are connected, and spatial gene expression profiles showing activity levels for hundreds of genes across 213 brain regions in mice. Differences in gene activity create distinct spatial patterns—gradients—that together give each area a characteristic molecular identity.
Naoki Honda, senior author and professor at Nagoya University’s Graduate School of Medicine, explains that when hundreds of these patterns overlap, they form unique positional signatures for each region. SPERRFY was designed to uncover those signatures and determine how they relate to wiring.
For every connected region pair, SPERRFY matches the gene activity profile of the source region with that of the target region. From these paired profiles the method infers latent gene expression gradients that serve as positional coordinates across the brain. These inferred gradients reconstruct the connectome with high accuracy: a prediction-performance score of 0.88, compared with roughly 0.70 when only physical distance between regions is considered.
The analysis also revealed hierarchical structure: large-scale gradients account for interregional organization, while additional, finer gradients govern the specific routing of axons within regions. This two-tiered arrangement helps explain how broad regional relationships and precise local targeting are both encoded by gene expression.
Testing a 60-year-old theory at whole-brain scale
Roger Sperry’s chemoaffinity theory, formulated in 1963, proposed that chemical gradients provide positional cues that guide axons to their targets. Historically, evidence for chemoaffinity came mainly from relatively simple sensory systems such as vision and olfaction.
Because whole-brain connectivity is vastly more complex, testing Sperry’s idea at that scale required computational methods capable of integrating large connectomic and transcriptomic datasets. By operationalizing the theory in a data-driven framework, SPERRFY supplies the first comprehensive computational validation that chemoaffinity-like molecular gradients can explain connectivity across the entire brain.
Jigen Koike, first author, notes that the approach bridges a longstanding conceptual idea with modern data resources and machine learning, extending a foundational developmental principle to much broader brain organization.
Future directions
Beyond reconstructing connectivity, SPERRFY can screen for candidate genes whose spatial patterns closely match inferred positional gradients. Some of the genes identified are already implicated in axon guidance, which supports the biological relevance of the inferred gradients and offers concrete targets for follow-up experimental studies.
The method is adaptable to any species with mapped neural circuits and spatial gene expression data, including humans, marmosets, and fruit flies. As comparative datasets grow, SPERRFY could help determine whether similar molecular wiring principles are conserved across species and how they have evolved. It may also provide a framework for investigating how altered gene expression disrupts wiring in neurodevelopmental disorders.
Key Questions Answered:
A: Each brain region carries a distinct molecular identity made up of hundreds of overlapping gene expression patterns. These spatial gradients act like a GPS, providing positional information that guides growing axons to their proper targets.
A: Proposed by Roger Sperry in 1963, the chemoaffinity theory posits that gradients of molecular cues provide spatial instructions for axonal targeting. This study shows that the same principle can be applied to organize connectivity across the whole brain, not just in simple sensory circuits.
A: Yes. SPERRFY can be applied to any species with available connectomic and spatial transcriptomic maps, including humans. Applied to human data, the approach could help clarify how atypical wiring patterns arise in developmental disorders.
Editorial Notes:
- This article was edited by a Neuroscience News editor.
- Journal paper reviewed in full.
- Additional context added by staff.
About this brain mapping and genetics research news
Author: Merle Naidoo
Source: Nagoya University
Contact: Merle Naidoo – Nagoya University
Image: Image credit: Neuroscience News
Original Research: Open access. “A data-driven framework linking the connectome to spatial gene expression gradients inspired by chemoaffinity theory” by Jigen Koike, Ken Nakae, Riichiro Hira, Yuichiro Yada, and Naoki Honda. PNAS
DOI: 10.1073/pnas.2516572123
Abstract
A data-driven framework linking the connectome to spatial gene expression gradients inspired by chemoaffinity theory
A fundamental challenge in neuroscience is to understand how genetic programs specify brain-wide neural circuits. Sperry’s chemoaffinity theory proposed that spatially varying molecular cues provide positional information for axonal projections, but evidence for this principle has been mostly limited to localized sensory systems.
Here, the authors introduce SPERRFY (Spatial Positional Encoding for Reconstructing Rules of axonal Fiber connectivitY), a data-driven framework that implements Sperry’s idea at whole-brain scale. By integrating connectomic maps with spatial transcriptomic profiles from the mouse brain atlas, SPERRFY infers latent positional gradients that underlie axonal wiring.
Using canonical correlation analysis, the method extracts top gradient pairs that align with observed connectivity, capturing both global interregional organization and finer intraregional structure. Connectivity reconstructed from these gradients yields strong predictive performance, and permutation-based controls support the biological significance of the inferred structures.
SPERRFY also enables screening for candidate genes that may encode positional information, offering molecular leads to probe the developmental logic of brain wiring. These results extend Sperry’s foundational theory beyond sensory circuits and provide a unified, data-driven framework for understanding genetically encoded connectivity across the brain.