Summary: Researchers have shown that genes encode a comprehensive molecular “wiring map” that guides neurons to their correct targets across the entire brain.
Using a new machine learning framework called SPERRFY, scientists demonstrated that overlapping patterns of gene expression act as positional cues for axons, validating and extending the chemoaffinity theory proposed six decades ago. The work shows that the same molecular GPS known to organize simple sensory circuits also helps organize brain-wide connectivity.
Key Facts
- SPERRFY decoding: The team developed SPERRFY (Spatial Positional Encoding for Reconstructing Rules of axonal Fiber connectivitY), which links a map of neural connections with the expression levels of 763 genes across 213 mouse brain regions.
- Predictive power: SPERRFY identified gene expression gradients that reconstructed the brain’s wiring with strong accuracy (prediction score 0.88 on a 0–1 scale), outperforming models that relied only on physical distance (score ~0.70).
- Two-level organization: Broad gene expression patterns set the overall layout between regions, while finer patterns specify individual connections within regions.
- Whole-brain validation: This is the first large-scale computational support for Roger Sperry’s chemoaffinity theory applied at the whole-brain level rather than to localized sensory circuits alone.
Source: Nagoya University
How the brain’s complex circuits are genetically specified is a central question in neuroscience. This study provides strong evidence that genes create a map of molecular identities that axons use to find their targets during development, offering new directions for understanding brain formation and disorders.
Published in Proceedings of the National Academy of Sciences, the research combines connectomic data and spatial gene expression to reveal reproducible wiring rules and candidate genes involved in directing axonal growth.
Mapping connections with integrated data
A team led by researchers at Nagoya University sought to discover the wiring rules that guide axons—neuronal projections that transmit signals—to their correct targets. They combined two complementary datasets: a connectome that maps which brain regions connect to each other, and a spatial gene expression atlas measuring activity of 763 genes in 213 mouse brain areas.
Some genes show high expression in particular regions and low expression elsewhere. These differential expression patterns overlap to create a unique molecular identity for each region. SPERRFY uses machine learning to extract those overlapping gene expression gradients and link them to observed connectivity.
For each connected pair of regions, SPERRFY pairs the gene expression profile of the source region with that of the target region. From many such pairs the algorithm infers latent gradients that effectively tell each region where it sits relative to every other region. Reconstructing connectivity from these gradients produced a high predictive score (0.88), while a distance-only model scored about 0.70.
The analysis revealed a hierarchical organization: broad gradients encode interregional layout and coarse topography, while finer gradients and gene combinations specify precise intraregional connections.
Testing a 60-year-old theory across the whole brain
Roger Sperry’s chemoaffinity theory, proposed in 1963, proposed that chemical concentration gradients provide positional cues that guide axons during development. That idea was well supported in localized sensory systems such as the visual and olfactory pathways, but testing it at the scale of the entire brain was challenging.
Using SPERRFY and modern transcriptomic and connectomic datasets, the researchers were able to operationalize Sperry’s concept at whole-brain scale. Their results indicate that molecular gradients do function as a kind of GPS across the brain, not just in specific sensory circuits.
Future directions and applications
By comparing many genes to the wiring map, SPERRFY identified individual genes whose spatial patterns closely matched the inferred positional gradients, including genes already known to influence axon guidance. Those genes provide promising targets for follow-up experiments aimed at uncovering the molecular mechanisms of wiring.
The method is adaptable: where connectome maps and gene expression data exist, SPERRFY can be applied to other species, including humans, marmosets, and fruit flies. As datasets grow, this approach can test whether similar molecular wiring principles are conserved across species and how they evolved. It may also help clarify how disruptions in wiring contribute to neurodevelopmental disorders.
Key Questions Answered:
A: Each brain region has a distinct molecular identity produced by hundreds of overlapping gene expression patterns. These spatial gradients act like a GPS for growing axons, indicating relative positions and guiding connections.
A: Proposed by Roger Sperry in 1963, the chemoaffinity theory posits that neurons follow chemical gradients to find their synaptic partners. This study provides computational evidence that the same principle helps organize the entire brain’s connectivity.
A: Yes. SPERRFY can be applied wherever matched connectome and spatial gene expression datasets exist, making it applicable to humans and other species to study normal development and disorders of brain wiring.
Editorial Notes:
- This article was edited by a Neuroscience News editor.
- The journal paper was reviewed in full.
- Additional context was provided by editorial staff.
About this brain mapping and genetics research news
Author: Merle Naidoo
Source: Nagoya University
Contact: Merle Naidoo – Nagoya University
Image: Image credited to 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
Understanding how brain-wide neural circuits are genetically wired is a fundamental challenge. While Sperry’s chemoaffinity theory proposes that molecular gradients provide positional cues for axonal projections, its application has largely been limited to localized sensory systems. Here, the authors present SPERRFY, a data-driven framework that implements Sperry’s idea at whole-brain scale by integrating connectomic maps with spatial transcriptomic profiles.
Using canonical correlation analysis to extract dominant gradient pairs that align with observed connectivity, the framework captures both global interregional organization and local intraregional structure. Connectivity reconstructed from these gradients shows strong predictive performance, and permutation-based null models support the biological relevance of the inferred gradients. SPERRFY can also screen candidate genes that contribute to positional wiring information, offering molecular insight into the developmental logic of brain-wide circuitry. These results extend Sperry’s foundational theory beyond sensory domains, providing a unified data-driven framework for genetically encoded connectivity across the entire brain.