Most genetic or mechanistic studies of Autism Spectrum Disorders (ASDs) still focus predominantly on protein- coding genes. The genomic landscape has, however, expanded greatly in recent years, with the identification of new transcript classes such as conserved long noncoding RNAs (lncRNAs) in humans and other eukaryotes that cover a significant fraction of the genome but so far remain largely uncharacterized. Though the functions of the vast majority of lncRNAs are unclear, they have been implicated in numerous gene transcription processes, as indicators of transcription factor activity, decoys that titrate away RNA binding proteins, functional guides for ribonucleoprotein complexes, and scaffolds for the assembly of functionally related proteins like transcriptional regulators. RNA coimmunoprecipitation experiments have also indicated that many are associated with chromatin-modifying complexes. As such, these transcripts are now believed to be a key component of gene regulatory networks. Crucially, there is emerging evidence that lncRNAs play a role in neurodevelopmental disorders, including ASDs, though systematic studies assessing their degree of involvement are still scarce. Comprehensive profiling of lncRNAs has remained challenging because they are typically expressed at much lower levels compared to messenger RNAs (mRNAs). We therefore intend to leverage newly developed hybrid short- and long-read sequencing and RNA capture technologies to deeply profile the lncRNA transcriptome in post-mortem brain samples of 40 ASD cases and 40 controls. Our efforts will be focused on two brain regions that have previously been implicated in ASD, the prefrontal cortex and the cerebellum. By deep short-read sequencing of samples enriched for lncRNAs using a specific set of capture probes we designed, we will identify lncRNAs that are dysregulated in ASD cases. The short-read data will further be combined with long-read sequencing data for a subset of samples generated on the PacBio RS platform to reconstruct full-length lncRNA transcript isoforms, which will provide a complete map of brain-expressed lncRNA genes and the diversity of transcripts they generate, in unprecedented detail. Finally, we will integrate our non-coding expression data with existing mRNA-Seq data generated for the same samples to construct coding/non-coding co-expression networks that can identify key driver lncRNAs whose dysregulation may contribute to ASD. Together these results will not only improve our understanding of the mechanisms underlying ASD pathogenesis, potentially providing new targets for prevention, earlier diagnostics and improved therapeutics, but also provide a more robust framework for future noncoding RNA studies in any disease context.

Public Health Relevance

Autism spectrum disorders (ASDs) affect 1% of the general population and impose a major burden on families and society. Despite recent advances that have pointed to involvement of biological pathways such as synaptic function and chromatin remodelers, causal genes and risk variants still remain to be identified for most ASD cases. We anticipate that a significant proportion of these variants reside outside protein-coding genes, which we plan to assess by profiling non-coding RNA expression, taking advantage of recent improvements in sequencing technology, along with newly developed algorithms and experimental approaches.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21MH105881-02
Application #
8968868
Study Section
Genetics of Health and Disease Study Section (GHD)
Program Officer
Senthil, Geetha
Project Start
2014-12-01
Project End
2017-11-30
Budget Start
2015-12-01
Budget End
2017-11-30
Support Year
2
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Icahn School of Medicine at Mount Sinai
Department
Psychiatry
Type
Schools of Medicine
DUNS #
078861598
City
New York
State
NY
Country
United States
Zip Code
10029
Toker, Lilah; Mancarci, Burak Ogan; Tripathy, Shreejoy et al. (2018) Transcriptomic Evidence for Alterations in Astrocytes and Parvalbumin Interneurons in Subjects With Bipolar Disorder and Schizophrenia. Biol Psychiatry 84:787-796
Wang, Daifeng; Liu, Shuang; Warrell, Jonathan et al. (2018) Comprehensive functional genomic resource and integrative model for the human brain. Science 362:
Li, Mingfeng; Santpere, Gabriel; Imamura Kawasawa, Yuka et al. (2018) Integrative functional genomic analysis of human brain development and neuropsychiatric risks. Science 362:
Bryois, Julien; Garrett, Melanie E; Song, Lingyun et al. (2018) Evaluation of chromatin accessibility in prefrontal cortex of individuals with schizophrenia. Nat Commun 9:3121
Gusev, Alexander; Mancuso, Nicholas; Won, Hyejung et al. (2018) Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights. Nat Genet 50:538-548
An, Joon-Yong; Lin, Kevin; Zhu, Lingxue et al. (2018) Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder. Science 362:
Gandal, Michael J; Zhang, Pan; Hadjimichael, Evi et al. (2018) Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder. Science 362:
Girdhar, Kiran; Hoffman, Gabriel E; Jiang, Yan et al. (2018) Cell-specific histone modification maps in the human frontal lobe link schizophrenia risk to the neuronal epigenome. Nat Neurosci 21:1126-1136
Kozlenkov, Alexey; Li, Junhao; Apontes, Pasha et al. (2018) A unique role for DNA (hydroxy)methylation in epigenetic regulation of human inhibitory neurons. Sci Adv 4:eaau6190
Doostparast Torshizi, Abolfazl; Duan, Jubao; Wang, Kai (2018) Transcriptional network analysis on brains reveals a potential regulatory role of PPP1R3F in autism spectrum disorders. BMC Res Notes 11:489

Showing the most recent 10 out of 20 publications