Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism

In the paper

“Moreover, alterations in dup15q cortex were of greater magnitude and more homogeneous than those observed in idiopathic ASD cortex (Fig. 3d, Extended Data Fig. 7f, g).”

In the paper

“We confirmed this in our larger cohort and identified 523 genes that differed significantly in expression between the frontal cortex and the temporal cortex in control subjects, but not those with ASD (Fig. 2a); we refer to these genes as the ‘attenuated cortical patterning’ (ACP) set (Extended Data Fig. 6a).”

In the paper

“Although there was no significant DGE in the cerebellum (FDR < 0.05, P distributions in Fig. 1b), similar to observations in a smaller cohort8, there was a replication signal in the cerebellum and overall concordance between ASD-related fold changes in the cortex and cerebellum (Extended Data Fig. 2f–h).”

What the sources say

• Not checked yetcites [8] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source

In the paper

“Analysis of DGE in the cerebellum confirmed a weaker signal than in the cortex and demonstrated that cis changes in dup15q cerebellum (Extended Data Fig. 7h–j) were more concordant with the cortex than trans changes (Extended Data Fig. 7k, l), further supporting the observation that the cortex is selectively vulnerable to transcriptomic alteration in ASD.”

In the paper

“Of the six modules associated with ASD, three were upregulated and three were downregulated, and each showed significant cell-type enrichment (Fig. 4a, b).”

In the paper

“Among the transcription factors identified, SOX5 was of particular interest because of its known role in mammalian corticogenesis23,24, its sole membership in the ACP set, and its correlation with predicted targets in the brains of control subjects, which is lost in ASD (Fig. 2b–d).”

In the paper

“Several other ASD-associated modules showed a weaker common variant signal for ASD, including CTX.M16, which also shows a signal for schizophrenia polygenic risk.”

In the paper

“Significant upregulation in the 15q11.1–13.2 region (cis) was evident in duplication carriers, but not in idiopathic ASD (Fig. 3a).”

In the paper

“Remarkably, CTX.M24 was significantly enriched for lncRNAs, genes expressed highly during fetal cortical development, and genes harbouring protein-disrupting mutations found in ASD, suggesting that lncRNAs will be important targets for investigation in ASD10,25 (FDR < 0.05, Extended Data Fig. 9a, g).”

In the paper

“We also found preservation of most cortex modules in the cerebellum, but with weaker associations to ASD (Extended Data Fig. 10a–h, Supplementary Table 4), consistent with the DGE analysis showing that ASD-related changes are substantially smaller in the cerebellum.”

In the paper

“We highlight two primate-specific lncRNAs, LINC00693 and LINC00689. Both interact with miRNA processing complexes and are typically downregulated during development12, but are upregulated in ASD cortex (Fig. 1c, d, Extended Data Fig. 2n).”

What the sources say

• Not checked yetcites [12] Jaffe, A. E. et al. Developmental regulation of human cortex transcription and its clinical relevance at single base resolution. Nat. Neurosci. 18, 154–161 (2015) source

In the paper

“We confirmed that a significant proportion of ACP genes are regulated by SOX5 by overexpressing it in human neural progenitors. SOX5 induced synaptic genes and repressed cell proliferation (Fig. 2e), and predicted SOX5 targets exhibited net down-regulation, consistent with the repressive function of SOX5 (Fig. 2f, Extended Data Fig. 6l, m).”

In the paper

“revealing strong concordance but a lower average fold change in the cerebellum.”

In the paper

“Compared to this study, samples from ref. 4 were prepared by poly(A) selection RNA-seq, exhibit lower RNA integrity number (RIN, median 4.8 versus 7.3), have lower median sequencing depth (11 million versus 40 million), exhibit greater 5′−3′ bias, and have generally greater variability across all QC metrics.”

What the sources say

• Not checked yetcites [4] Gupta, S. et al. Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism. Nat. Commun. 5, 5748 (2014) source

In the paper

“ESRP2 is expressed but not significantly different between ASD and control cortex.”

In the paper

“PCR validation and sashimi plots for nine splicing events delineated in Extended Data Fig. 4d”

In the paper

“Module plot and GO term enrichment for CTX.M24, which is enriched in ASD-associated rare variants and lncRNAs.”

In the paper

“Example of a strongly conserved lncRNA, which shows robust expression in all three species.”

In the paper

“ESRP1 is not expressed in cortex”

In the paper

“Approximately 85% of ASD samples are classified successfully around a false positive rate of 20%.”

What the sources say

• Not checked yetcites [8] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source
• Not checked yetcites [47] Friedman, J., Hastie, T. & Tibshirani, R. Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 33, 1–22 (2010) source

In the paper

“RT–PCR validation of the two lncRNAs shown in Fig. 1c, d; P values computed by two-sided Wilcoxon rank-sum test.”

In the paper

“The first principal component of the cortex differential splicing set is strongly associated with diagnosis, but not other factors.”

In the paper

“These contributions are profoundly heterogeneous but may converge on common pathways that are not yet well understood1–3.”

What the sources say

• Not checked yetcites [1] Gaugler, T. et al. Most genetic risk for autism resides with common variation. Nat. Genet. 46, 881–885 (2014) source
• Not checked yetcites [2] Gratten, J., Visscher, P. M., Mowry, B. J. & Wray, N. R. Interpreting the role of de novo protein-coding mutations in neuropsychiatric disease. Nat. Genet. 45, 234–238 (2013) source
• Not checked yetcites [3] de la Torre-Ubieta, L., Won, H., Stein, J. L. & Geschwind, D. H. Advancing the understanding of autism disease mechanisms through genetics. Nat. Med. 22, 345–361 (2016) source

In the paper

“We confirmed that confounders do not account for the differential splicing signal, reproduced the global differential splicing signal with an alternative pipeline15, and performed technical validation with RT–PCR (Extended Data Figs 4d–g, 5a), confirming the differential splicing analysis.”

What the sources say

• Not checked yetcites [15] Wu, J., Anczuków, O., Krainer, A. R., Zhang, M. Q. & Zhang, C. OLego: fast and sensitive mapping of spliced mRNA-Seq reads using small seeds. Nucleic Acids Res . 41, 5149–5163 (2013) source

In the paper

“Among the transcription factors identified, SOX5 was of particular interest because of its known role in mammalian corticogenesis23,24, its sole membership in the ACP set, and its correlation with predicted targets in the brains of control subjects, which is lost in ASD (Fig. 2b–d).”

What the sources say

• Not checked yetcites [23] Kwan, K. Y. et al. SOX5 postmitotically regulates migration, postmigratory differentiation, and projections of subplate and deep-layer neocortical neurons. Proc. Natl Acad. Sci. USA 105, 16021–16026 (2008) source
• Not checked yetcites [24] Lamb, A. N. et al. Haploinsufficiency of SOX5 at 12p12.1 is associated with developmental delays with prominent language delay, behavior problems, and mild dysmorphic features. Hum. Mutat. 33, 728–740 (2012) source

In the paper

“We demonstrated the robustness of attenuation in cortical patterning in ASD by confirming that the ACP set was not more variable than other genes, that attenuation of cortical patterning was robust to removal of previously analysed samples8, and that the effect could also be observed using a different classification approach (Extended Data Fig. 6b–h).”

What the sources say

• Not checked yetcites [8] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source

In the paper

“This analysis corroborates and extends previous work by identifying sub-modules of those previously identified, thus demonstrating greater biological specificity (Extended Data Figs 8e, 9a).”

In the paper

“Notably, the differential splicing molecular signature is not driven by DGE (Extended Data Fig. 4h), consistent with the observation that splicing alterations are related to common disease risk independently of gene expression changes16.”

What the sources say

• Not checked yetcites [16] Li, Y. I. et al. RNA splicing is a primary link between genetic variation and disease. Science 352, 600–604 (2016) source

In the paper

“This DGE signal was consistent across methods, unrelated to major confounders, and found in more than two-thirds of ASD samples (Extended Data Fig. 1j–m).”

In the paper

“Moreover, 20 of these lncRNAs have been shown to interact with microRNA (miRNA)–protein complexes, and 9 with the fragile X mental retardation protein (FMRP), whose mRNA targets are enriched in ASD risk genes9,10.”

What the sources say

• Not checked yetcites [9] Iossifov, I. et al. The contribution of de novo coding mutations to autism spectrum disorder. Nature 515, 216–221 (2014) source
• Not checked yetcites [10] Parikshak, N. N. et al. Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism. Cell 155, 1008–1021 (2013) source

In the paper

“This overlap supports a model of ASD pathophysiology based on changes in the balance of excitation and inhibition and in neuronal activity22 and suggests that alterations in transcript structure are likely to be an important component.”

What the sources say

• Not checked yetcites [22] Mullins, C., Fishell, G. & Tsien, R. W. Unifying views of autism spectrum disorders: a consideration of autoregulatory feedback loops. Neuron 89, 1131–1156 (2016) source

In the paper

“Remarkably, CTX.M24 was significantly enriched for lncRNAs, genes expressed highly during fetal cortical development, and genes harbouring protein-disrupting mutations found in ASD, suggesting that lncRNAs will be important targets for investigation in ASD10,25 (FDR < 0.05, Extended Data Fig. 9a, g).”

What the sources say

• Not checked yetcites [10] Parikshak, N. N. et al. Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism. Cell 155, 1008–1021 (2013) source
• Not checked yetcites [25] Willsey, A. J. et al. Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism. Cell 155, 997–1007 (2013) source

In the paper

“Together, the DGE and differential splicing analyses in dup15q provide further biological validation of the ASD transcriptomic signature and demonstrate that a genetically defined form of ASD exhibits similar changes to idiopathic ASD.”

In the paper

“Notably, we used a modified version of WGCNA that involves bootstrapping the underlying dataset 100 times and constructing 100 networks. The consensus of these networks (median edge strength across all bootstrapped networks) was then used as the final network39, ensuring that a subset of samples does not drive the network structure.”

What the sources say

• Not checked yetcites [39] Langfelder, P. & Horvath, S. Eigengene networks for studying the relationships between co-expression modules. BMC Syst. Biol. 1, 54 (2007) source

In the paper

“The sample dissections, RNA extractions, and RNA sequencing experiments were randomized (Supplementary Information).”

In the paper

“In this regard, it is notable that the observed transcriptome changes are consistent with an ongoing process that is triggered largely by genetic and prenatal factors3,9,10,23, but that evolves during the first decade of brain development.”

What the sources say

• Not checked yetcites [3] de la Torre-Ubieta, L., Won, H., Stein, J. L. & Geschwind, D. H. Advancing the understanding of autism disease mechanisms through genetics. Nat. Med. 22, 345–361 (2016) source
• Not checked yetcites [9] Iossifov, I. et al. The contribution of de novo coding mutations to autism spectrum disorder. Nature 515, 216–221 (2014) source
• Not checked yetcites [10] Parikshak, N. N. et al. Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism. Cell 155, 1008–1021 (2013) source
• Not checked yetcites [23] Kwan, K. Y. et al. SOX5 postmitotically regulates migration, postmigratory differentiation, and projections of subplate and deep-layer neocortical neurons. Proc. Natl Acad. Sci. USA 105, 16021–16026 (2008) source

In the paper

“Similar to d except for the differential alternative splicing analysis.”

In the paper

“the known positive correlation between SRRM4 and RBFOX1 and anticorrelation between PTBP1 and SRRM4 (refs 14,19)”

What the sources say

• Not checked yetcites [14] Irimia, M. et al. A highly conserved program of neuronal microexons is misregulated in autistic brains. Cell 159, 1511–1523 (2014) source
• Not checked yetcites [19] Raj, B. et al. A global regulatory mechanism for activating an exon network required for neurogenesis. Mol. Cell 56, 90–103 (2014) source

In the paper

“However, the correlation between the number of detected events in genes and gene length is minimal (R2 = 0.004), and the correlation is even smaller for events at P < 0.01 (R2 = 0.00012) demonstrating that longer genes are not more likely to contain differential splicing events.”

In the paper

“The investigators were blinded to diagnosis until the analysis but unblinded during the analysis.”

In the paper

“Co-expression of lncRNAs with genes harbouring ASD-associated protein coding mutations suggests that these noncoding RNAs are involved in similar biological functions and are potential candidate ASD risk loci.”

In the paper

“Notably, this sample size is underpowered to evaluate significant changes in many genes or splicing events; however, the goal was to validate the accuracy of our data and analyses across genes, so we show the correlation of fold changes between ASD and control across genes or events.”

In the paper

“No statistical methods were used to predetermine sample size.”