0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessSignificance The cerebral cortex of the human brain is a highly complex, heterogeneous tissue that contains many cell types that are exquisitely regulated at the level of gene expression by noncoding regulatory elements, presumably in a cell-type–dependent manner. However, assessing the regulatory elements in individual cell types is technically challenging, and therefore most of the previous studies on gene regulation were performed with bulk brain tissue. Here we analyze two major types of neurons isolated from the cerebral cortex of humans, chimpanzees, and rhesus macaques, and report complex patterns of cell-type–specific evolution of the regulatory elements in numerous genes. Many genes with evolving regulation are implicated in language abilities as well as psychiatric disorders.
Alexey Kozlenkov, Marit W. Vermunt, Pasha Apontes, Junhao Li, Ke Hao, Chet C. Sherwood, Patrick R. Hof, John J. Ely, Michael Wegner, Eran A. Mukamel, Menno P. Creyghton, Eugene V Koonin, Stella Dracheva (2020). Evolution of regulatory signatures in primate cortical neurons at cell-type resolution. , 117(45), DOI: https://doi.org/10.1073/pnas.2011884117.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2020
Authors
13
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1073/pnas.2011884117
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access