Using a comprehensive atlas and predictive models to reveal the complexity and evolution of brain-active regulatory elements-Reference-Cited by-同舟云学术

Using a comprehensive atlas and predictive models to reveal the complexity and evolution of brain-active regulatory elements

Published:2024-05-24 Issue:21 Volume:10 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Pratt Henry E.¹^ORCID,Andrews Gregory¹^ORCID,Shedd Nicole¹^ORCID,Phalke Nishigandha¹^ORCID,Li Tongxin¹²^ORCID,Pampari Anusri³,Jensen Matthew⁴^ORCID,Wen Cindy⁵⁶⁷^ORCID,Consortium PsychENCODE,Gandal Michael J.⁵⁶⁷⁸⁹^ORCID,Geschwind Daniel H.⁷¹⁰¹¹^ORCID,Gerstein Mark⁴¹²¹³¹⁴^ORCID,Moore Jill¹^ORCID,Kundaje Anshul³¹⁵^ORCID,Colubri Andrés¹^ORCID,Weng Zhiping¹^ORCID

Affiliation:

1. Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA.

2. Khoury College of Computer Science, Northeastern University, Boston, MA 02115, USA.

3. Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.

4. Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA.

5. Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA.

6. Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.

7. Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.

8. Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.

9. Lifespan Brain Institute, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA.

10. Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.

11. Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA 90095, USA.

12. Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.

13. Department of Computer Science, Yale University, New Haven, CT 06520, USA.

14. Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA.

15. Department of Computer Science, Stanford University, Stanford, CA 94305, USA.

Abstract

Most genetic variants associated with psychiatric disorders are located in noncoding regions of the genome. To investigate their functional implications, we integrate epigenetic data from the PsychENCODE Consortium and other published sources to construct a comprehensive atlas of candidate brain cis-regulatory elements. Using deep learning, we model these elements’ sequence syntax and predict how binding sites for lineage-specific transcription factors contribute to cell type–specific gene regulation in various types of glia and neurons. The elements’ evolutionary history suggests that new regulatory information in the brain emerges primarily via smaller sequence mutations within conserved mammalian elements rather than entirely new human- or primate-specific sequences. However, primate-specific candidate elements, particularly those active during fetal brain development and in excitatory neurons and astrocytes, are implicated in the heritability of brain-related human traits. Additionally, we introduce PsychSCREEN, a web-based platform offering interactive visualization of PsychENCODE-generated genetic and epigenetic data from diverse brain cell types in individuals with psychiatric disorders and healthy controls.

Publisher

American Association for the Advancement of Science (AAAS)

Link

https://www.science.org/doi/pdf/10.1126/sciadv.adj4452

Reference118 articles.

1. Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain

2. The remarkable, yet not extraordinary, human brain as a scaled-up primate brain and its associated cost

3. Comprehensive functional genomic resource and integrative model for the human brain

4. Integrative functional genomic analysis of human brain development and neuropsychiatric risks

5. Temporal dynamics and genetic control of transcription in the human prefrontal cortex

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Leveraging a large language model to predict protein phase transition: A physical, multiscale, and interpretable approach;Proceedings of the National Academy of Sciences;2024-08-07