Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. SynGO: An Evidence-Based, Expert-Curated Knowledge Base for the Synapse

SynGO: An Evidence-Based, Expert-Curated Knowledge Base for the Synapse

Thumbnail Image
Download
Name

nihms-1048803.pdf

Description
Accepted version
Size

1.68 MB

Format

Unknown

Checksum (MD5)

0a280c2527d7b2cd9b606d9fe9b82e4d

sword-2020-07-20T15:51:36.original.xml (130 B)
Original SWORD entry document
Author(s)
Feng, Guoping
Date Issued
2019
Journal
Neuron
Publisher
Elsevier BV
Version
Author's final manuscript
Abstract
© 2019 Elsevier Inc. Synapses are fundamental information-processing units of the brain, and synaptic dysregulation is central to many brain disorders (“synaptopathies”). However, systematic annotation of synaptic genes and ontology of synaptic processes are currently lacking. We established SynGO, an interactive knowledge base that accumulates available research about synapse biology using Gene Ontology (GO) annotations to novel ontology terms: 87 synaptic locations and 179 synaptic processes. SynGO annotations are exclusively based on published, expert-curated evidence. Using 2,922 annotations for 1,112 genes, we show that synaptic genes are exceptionally well conserved and less tolerant to mutations than other genes. Many SynGO terms are significantly overrepresented among gene variations associated with intelligence, educational attainment, ADHD, autism, and bipolar disorder and among de novo variants associated with neurodevelopmental disorders, including schizophrenia. SynGO is a public, universal reference for synapse research and an online analysis platform for interpretation of large-scale -omics data (https://syngoportal.org and http://geneontology.org). The SynGO consortium presents a framework to annotate synaptic protein locations and functions and annotations for 1,112 synaptic genes based on published experimental evidence. SynGO reports exceptional features and disease associations for synaptic genes and provides an online data analysis platform.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
http://creativecommons.org/licenses/by-nc-nd/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/134814.2
DOI of Published Version
https://doi.org/10.1016/J.NEURON.2019.05.002
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.