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Transcriptomic Perspectives on Neocortical Structure, Development, Evolution, and Disease
Abstract
The cerebral cortex is the source of our most complex cognitive capabilities and a vulnerable target of many neurological and neuropsychiatric disorders. Transcriptomics offers a new approach to understanding the cortex at the level of its underlying genetic code, and rapid technological advances have propelled this field to the high-throughput study of the complete set of transcribed genes at increasingly fine resolution to the level of individual cells. These tools have revealed features of the genetic architecture of adult cortical areas, layers, and cell types, as well as spatiotemporal patterning during development. This has allowed a fresh look at comparative anatomy as well, illustrating surprisingly large differences between mammals while at the same time revealing conservation of some features from avians to mammals. Finally, transcriptomics is fueling progress in understanding the causes of neurodevelopmental diseases such as autism, linking genetic association studies to specific molecular pathways and affected brain regions.
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“It allows gene expression patterns to be mapped onto histologically defined regions, thereby linking molecular signatures to specific pathological features such as amyloid plaques and tau tangles114,121,166,167.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [167]
In the citing paper
“Spatial transcriptomics further enhances transcriptomic profiling by preserving the spatial context of gene expression.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [167]
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“Moreover, combining single-cell or spatial transcriptomics with imaging modalities such as fluorescence in situ hybridization (FISH) or immunohistochemistry enhances validation within native tissue contexts114,167.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [167]
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Metadata
- Authors
- Lein, E. S., Belgard, T. G., Hawrylycz, M., & Molnár, Z.
- Affiliations
- Allen Institute for Brain Science (US)
- Verge Genomics (United States) (US)
- University of Oxford (GB)
- Venue
- Annual Review of Neuroscience
- Publisher
- Annual Reviews
- Published
- 2017-07-25
- Volume
- 40
- Issue
- 1
- Pages
- 629-652
- ISSN
- 0147-006X (ISSN-L)
- 1545-4126
- OpenAlex
- W2619100129
- Cited by
- 92
- References
- 125
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 8 · 2023: 12 · 2022: 10 · 2021: 8 · 2020: 14 · 2019: 8 · 2018: 21 · 2017: 6
- FWCI
- 1.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annual Review of Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Medical Research Council (MR/N026039/1, MC_PC_15102)
- Biotechnology and Biological Sciences Research Council (BB/I021833/1, BB/F003285/1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Keywords
- cerebral cortex, neocortex, cortical development, cortical evolution, cortical cell types, cortical layers, single-cell transcriptomics, comparative neuroanatomy, neurodevelopmental disorders, autism spectrum disorder, genetic association studies, molecular pathways
- MeSH terms
- Autism Spectrum Disorder, Animals, Cerebral Cortex, Biological Evolution, Humans, Species Specificity, Genetic Association Studies, Transcriptome
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