ReviewGenes2026
Brain Spatial Genomics Atlases.
Review in Genes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent advances in single-cell RNA sequencing (scRNA-seq) have transformed neuroscience research by enabling the identification of genes, cell types, and molecular pathways involved in brain development and function. However, scRNA-seq lacks spatial information regarding the anatomic location of gene expression. Emerging spatial genomics technologies, including MERFISH, CosMx, Stereo-seq, and Visium Spatial Gene Expression overcome this limitation by enabling transcriptomic and epigenomic profiling within intact tissue architecture. Integration of spatial genomics with scRNA-seq has revolutionized genomics and biomedical research by allowing gene expression to be mapped in situ at cellular and even subcellular resolution. These advances have facilitated the construction of brain spatial genomics atlases in several species, including mouse, human, non-human primate, and zebrafish. Spatial genomics technologies are particularly valuable for defining cellular heterogeneity across brain regions and characterizing the spatial organization of neuronal circuits when integrated with single-cell sequencing approaches. These reference atlases provide powerful resources for investigating brain development, function and disease, and for identifying region-specific molecular signatures associated with neurological disorders. Here, we review currently available brain spatial genomics atlases and the spatial genomics technologies used to generate these reference resources.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.