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Neuronal impact of patient-specific aberrant NRXN1α splicing

Nature Genetics volume 51, pages 1679–1690 (2019)Cite this article

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Abstract

NRXN1 undergoes extensive alternative splicing, and non-recurrent heterozygous deletions in NRXN1 are strongly associated with neuropsychiatric disorders. We establish that human induced pluripotent stem cell (hiPSC)-derived neurons well represent the diversity of NRXN1α alternative splicing observed in the human brain, cataloguing 123 high-confidence in-frame human NRXN1α isoforms. Patient-derived NRXN1+/− hiPSC-neurons show a greater than twofold reduction in half of the wild-type NRXN1α isoforms and express dozens of novel isoforms from the mutant allele. Reduced neuronal activity in patient-derived NRXN1+/− hiPSC-neurons is ameliorated by overexpression of individual control isoforms in a genotype-dependent manner, whereas individual mutant isoforms decrease neuronal activity levels in control hiPSC-neurons. In a genotype-dependent manner, the phenotypic impact of patient-specific NRXN1+/− mutations can occur through a reduction in wild-type NRXN1α isoform levels as well as the presence of mutant NRXN1α isoforms.

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Fig. 1: Cohort description and transcriptomic analysis.
Fig. 2: Conservation of NRXN1α isoforms across mouse PFC, post-mortem PFC and hiPSC-neurons.
Fig. 3: Identification of cell-type-specific NRXN1 isoforms from control isogenic hiPSC-neuronal subtypes.
Fig. 4: Identification of mutant NRXN1α isoforms.
Fig. 5: Single-cell sequencing of hiPSC-neurons.
Fig. 6: Impact of specific NRXN1α isoforms on neuronal activity.

Data availability

To facilitate improved sharing between stem cell laboratories, all hiPSCs have already been deposited at the Rutgers University Cell and DNA Repository (study 160; http://www.nimhstemcells.org/) and all sequencing data have been deposited to GEO (GSE137101, whole short-read RNA-seq and scRNA-seq; and GSE137127, targeted short-read RNA-seq) or SRA (PRJNA563972, Iso-seq).

Code availability

To facilitate improved reproducibility of our data analyses, all code has been deposited at https://github.com/zhushijia/STAR2bSMRT.

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Acknowledgements

K.J.B. is a New York Stem Cell Foundation—Robertson Investigator. This work was partially supported by National Institutes of Health (NIH) grants R01 MH121074 (K.J.B. and G.F.), R01 MH101454 (K.J.B.), R01 MH106056 (K.J.B.), R01 MH107487 (R.M.) and F31 MH112285 (E.F.), a Brain and Behavior Research Foundation Independent Investigator Grant (K.J.B.), a Brain Research Foundation Seed Grant (K.J.B.) and the New York Stem Cell Foundation (K.J.B.). We thank the Neuroscience and Stem Cell cores at Icahn School of Medicine at Mount Sinai. This work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. J. Simon drew the original illustrations used in the schematics shown in Figs. 3a and 6a,d,e. We acknowledge the Mount Sinai Neuropathology Research Core and Brain bank (J. Crary) for providing the human post-mortem brain tissue.

Author information

Author notes

  1. These authors contributed equally: Erin Flaherty, Shijia Zhu.

Authors and Affiliations

  1. Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Erin Flaherty, Michael B. Fernando, Nadejda M. Tsankova & Kristen J. Brennand

  2. Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Erin Flaherty, P. J. Michael Deans, Michael B. Fernando, Nadine Schrode, Megan Fitzgerald, Ian Ladran, Nadejda M. Tsankova & Kristen J. Brennand

  3. Graduate School of Biomedical Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Erin Flaherty, Natalie Barretto, Esther Cheng, Michael B. Fernando & Madeline Halpern

  4. Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Shijia Zhu, P. J. Michael Deans, Nadine Schrode, Nancy Francoeur, Alesia Antoine, Gintaras Deikus, Hardik Shah, Gabriel E. Hoffman, Robert Sebra, Gang Fang & Kristen J. Brennand

  5. Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Shijia Zhu, Nancy Francoeur, Alesia Antoine, Gintaras Deikus, Hardik Shah, Gabriel E. Hoffman, Robert Sebra, Gang Fang & Kristen J. Brennand

  6. Liver Tumor Translational Research Program, Harold C. Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Shijia Zhu

  7. Department of Neurosciences, Institute in the College of Medicine & Life Sciences, The University of Toledo, Toledo, OH, USA

    Khaled Alganem & Robert McCullumsmith

  8. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Megan Fitzgerald, Ian Ladran & Kristen J. Brennand

  9. Childhood Psychiatry Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA

    Peter Gochman & Judith Rapoport

  10. Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Nadejda M. Tsankova

  11. Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Gabriel E. Hoffman & Kristen J. Brennand

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  1. Erin Flaherty
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  2. Shijia Zhu
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Contributions

K.J.B., E.F., S.Z. and G.F. contributed to experimental design. P.G. and J.R. developed the cohort, consented the patients and obtained skin biopsies. K.J.B., E.F., I.L. and M.Fitzgerald generated all hiPSCs and NPCs for cell culture experiments. S.Z. designed and developed the hybrid sequencing-based isoform correction and identification method and completed all targeted sequencing analysis. G.F. and K.J.B. supervised all the computational data analysis. A.A., N.F., G.D. and R.S. completed Iso-seq library preparation and sequencing. N.B. differentiated NGN2 and ASCL1/DLX2 hiPSC-neurons for targeted sequencing. E.C. conducted neuron-tracing experiments. M.P.D. and M.Fernando completed immunostaining and analysis for GABA. M.H. completed western blots. R.M. and K.A. performed kinase assay and analysis. E.F., G.E.H. and N.S. completed whole-transcriptome RNA-seq analysis. H.S. completed variant calling on RNA-seq data. N.T. provided fetal post-mortem tissue. K.J.B., E.F., G.F. and S.Z. wrote the manuscript.

Corresponding authors

Correspondence to Gang Fang or Kristen J. Brennand.

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The authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Validation of deletions in hiPSC cohort and whole transcriptome RNA-seq analysis.

a, Schematic showing the structure of the NRXN1 gene and location of 5’-((blue) and 3’-deletions (red). b,c, Mean and s.e. of Taqman CNV assay confirming 3’-CNV in fibroblasts from one 3’-NRXN1+/- case (b) and 5’-CNV in fibroblasts from both 5’-NRXN1+/- cases (c); two replicates per sample per probe. d, PCR of cDNA across exons encompassed by the 3’-deletion in controls and 3’-NRXN1+/- hiPSC-NPCs, two independent validations. e, Mean and s.e. of the log2FoldChange by qPCR across the novel junction (exon 20-24) created by 3’-deletion across 2 controls and 2 3’-NRXN1+/- hiPSC-NPCs compared using a two-sided t-test. f, Sanger sequencing result from a TOPO cloned NRXN1α isoform from 3’-NRXN1+/- hiPSC-neurons (n = 1) confirming presence of novel exon junction (exon 20-24). g, Confirmation of the sex of each sample. h, PCA plot of combined hiPSC-NPC (19 samples, 8 donors) and hiPSC-neuron (18 samples, 8 donors) RNA-seq dataset showing separation by cell type on PC1. i,j, Volcano plot showing differentially expressed genes within hiPSC-NPCs (i) and hiPSC-neurons (j) individually. k, FPKM of NRXN1 expression across fetal PFC (1), adult dlPFC (3) and control hiPSC-neurons (3). l, Circle plot showing hierarchical clustering of samples by cell type and by donor. m,n Pearson correlation of gene expression within and between donors in hiPSC-NPCs (19 samples, 8 donors) (m) and hiPSC-neurons (18 samples, 8 donors) (n) by one-sided Wilcoxon test. o, Gene set enrichments for genes correlated with NRXN1 spicing in the Common Mind Consortium dlPFC dataset.

Extended Data Fig. 2 Cell type composition.

a, Heatmap showing log2FPKM values of sub-type marker genes in hiPSC-neurons across genotypes. b, Cell type composition scores obtained using Cibersort4 in hiPSC-neurons (9 controls, 4 donors; 9 cases, 4 donors), by diagnosis. c, Images of GABA immunostaining overlaid with MAP2. d, Mean percent of GABA+ cells from control (8 images, 2 coverslips), 5’-NRXN1+/- (8 images, 2 coverslips) and 3’-NRXN1+/- (11 images, 3 coverslips). Error bars are s.e. e, Representative images of SYN1 immunostaining alone and overlaid with MAP2 immunostaining and DAPI. f, Mean intensity of SYN1+ puncta normalized to MAP2 intensity (3 images per coverslip, 8 coverslips per donor, 2 donors per genotype). Error bars are s.e.

Extended Data Fig. 3 Pipeline Schematic and quality control of Iso-seq data.

a, Schematic of the sample preparation for the hybrid sequencing approach. b, Schematic of the computational pipeline developed for the hybrid sequencing approach. c, UCSC genome browser view of whole transcriptome Iso-seq data across the NRXN1 locus from five hiPSC-neuron samples. d,e, Representative bioanalyzer traces from Iso-seq library prep passing QC (d) compared to library prep failed QC (e). f, Targeted short-read sequencing counts per million for 3’-NRXN1+/- specific junction site showing 3’-NRXN1+/- hiPSC-neurons passing QC in green and failing QC in red. g,h, Pearson’s correlation of junction site expression from targeted long read vs. targeted short read data showing one of the samples passing QC (g) and one sample failing QC (h).

Extended Data Fig. 4 Comparison of long and short read data for quantification and threshold testing.

a, Correlation of NRXN1α junction expression from long read and short read sequencing across control (control 1 n = 39, control 2 n = 37) and 3’-NRXN1+/- (3’-NRXN1+/- 1 n = 36, 3’-NRXN1+/- 2 n = 45) hiPSC-neuron samples. Red triangles represent canonical junctions while black represent non-canonical. b, Correlation of NRXN1α isoform expression from long read quantification and short read quantification across control (Control 1 n = 90, Control 2 n = 88) and 3’-NRXN1+/- (3’-NRXN1+/- 1 n = 89, 3’-NRXN1+/- 2 n = 96) hiPSC-neuron samples. Colored triangles represent in-frame isoforms, predicted to be translated (red), untranslated (black) and TOPO cloned (green). c, Correlation of mouse and human NRXN1α isoform expression and corresponding Venn diagrams for the number of isoforms across expression thresholds (≥2 n = 112, ≥3 n = 88, ≥4 n = 75, ≥5 n = 63, ≥6 n = 60, ≥7 n = 57, ≥8 n = 54, ≥9 n = 52, ≥10 n = 50).

Extended Data Fig. 5 Cell type specific NRXN1 expression.

a,b, PCA of isogenic samples differentiated into three hiPSC-neuronal cell types colored by cell type (ASCL1/DLX2 (5), hiPSC-neuron (6), and NGN2 (6) (a) or by NRXN1 genotype (control (8), case (9) from 3 donors each) (b). c, Representative confocal images from 2 independent differentiations of control and NRXN1+/- ASCL1/DLX2-GABAergic hiPSC-neurons. d, Expression of glutamatergic, GABAergic and pan-neuronal marker genes across NRXN1+/- (9) and control (8) NGN2-glutamatergic and ASCL1/DLX2-GABAergic hiPSC-neurons. Boxplot shows median and IQR. e, Sum of all NRXN1 transcripts expressed across control (2 donors), 3’-NRXN1+/- (2 donors) and 5’-NRXN1+/- (2 donors) in NGN2-glutamatergic and ASCL1/DLX2-GABAergic hiPSC-neurons. f,g, NRXN1α (f) and NRXN1β (g) isoform usage expressed across control, 3’-NRXN1+/- and 5’-NRXN1+/- donors in NGN2-glutamatergic and ASCL1/DLX2-GABAergic hiPSC-neurons. Boxplot displays median and range with P < 0.01 indicated by “**” from two way ANOVA with Holm-Sidak’s test.

Extended Data Fig. 6 Examination of NRXN1α canonical splice sites and total NRXN1 isoform expression.

a, Pearson’s correlation of NRXN1α isoform expression across control and 3’-NRXN1+/- hiPSC-neurons (n = 99 isoforms, r computed by t-statistics). b,c, Bar plot of the total read count for each NRXN1α exon along with the fraction that each NRXN1α junction is included in control hiPSC-neurons (b) and 3’-NRXN1+/- hiPSC-neurons. Red circle indicates the novel junction created by the 3’-NRXN1+/- deletion (c). d, Schematic of the experimental design to test activity induced regulation at NRXN1α canonical splice sites. e, Fold change of canonical splice site exclusion in controls (gray) and a 3’-NRXN1+/- hiPSC-neuron (red) plus KCl compared to PBS control (dotted line). f, Bar plot showing fold change of SS4 in KCl treated control and 3’-NRXN1+/- hiPSC-neurons (compared to PBS). g, Schematic of the experimental design to test developmental regulation at NRXN1α canonical splice sites. h, Fold change of canonical splice sites in control hiPSC-neurons at 2-weeks (light gray), 4-weeks (gray) and 6-weeks (dark gray) post-differentiation compared to NPCs (dotted line). i, Specific examination of developmental exclusion of SS4. Error bars are s.e. j-m, Expression of levels of all NRXN1 isoforms (j), NRXN1α (k), NRXN1β (l), NRXN1γ (m) across NRXN1 genotypes (8 control, 3 donors; 5 3’-NRXN1+/-, 2 donors; 5 5’-NRXN1+/-, 2 donors) in hiPSC-neurons. Violin plot displays density and range with P < 0.05 indicated by “*” from Wilcoxon Signed Rank Test. n, Pearson’s correlation of all NRXN1 isoforms (18 samples, 6 donors) with NRXN1α, NRXN1β and NRXN1γ (r values calculated using t-statistics).

Extended Data Fig. 7 Single cell expression of synaptic genes.

a, Violin plot displaying density of the expression of NRXN and multiple synaptic marker genes in single cells across control (2 donors) and NRXN1+/- (3 donors) hiPSC-neurons. b, Violin plot displaying density and range of the expression of multiple synaptic genes identified as marker genes in immature neuronal clusters from scRNA-seq data across control (2 donors) and NRXN1+/- (3 donors) hiPSC-neurons.

Extended Data Fig. 8 Investigation of hiPSC-neuron morphology, cellular signaling, and NRXN1 overexpression.

a, Strategy to label individual hiPSC-neurons. b-g, Mean neurite number across genotypes (control 71 neurons, 2 donors; 3’-NRXN1+/-- 72 neurons, 2 donors; 5’-NRXN1+/- 50 neurons 2 donors) “****” indicates P < 0.00001 and “***”indicates P < 0.0001 by one-way ANOVA with Holm-Sidak’s test; (b) or by coverslip (2 donors, 12 coverslips, 3 regions each) (c,d) mean neurite length across genotypes (control 71 neurons, 2 donors; 3’-NRXN1+/- 72 neurons, 2 donors; 5’-NRXN1+/- 50 neurons, 2 donors); (e) or by coverslip (2 donors, 12 coverslips, 3 regions each) (f,g). Two donors per genotype indicated by different shading within each plot. h, Differentially active kinases (3’- NRXN1+/- hiPSC-neurons: 6 samples, 2 donors; controls: 5 samples, 2 donors). i, Volcano plot of –log10(P-value) and log2(FoldChange) from linear model of RNA-seq (3’-NRXN1+/- hiPSC-neurons: 5 samples, 2 donors; controls 6 samples, 2 donors); DE kinase associated genes labeled. j, Violin plot of median and quartiles of RPKM for kinase hits with largest fold-change in RNA-seq (3’-NRXN1+/- hiPSC-neurons: 5 samples, 2 donors; controls: 6 samples, 2 donors). k, Differentially active kinases in (5’- NRXN1+/- hiPSC-neurons: 3 samples, 1 donors; controls 5 samples, 2 donors). l, Volcano plot of –log10(P-value) and log2(FoldChange) from linear model of RNA-seq (5’-NRXN1+/- hiPSC-neurons: 3 samples, 1 donors; controls 6 samples, 2 donors); DE kinase associated genes labeled. m, Violin plot of median and quartiles of RPKM for kinase hits with largest fold change values in RNA-seq (5’-NRXN1+/- hiPSC-neurons: 3 samples, 1 donors; controls 6 samples, 2 donors). n, Isoform constructs for overexpression with log2(FoldChange) from hybrid sequencing dataset. o, Mean fold-change from qPCR of NRXN1 expression (3 replicates per condition. p, Representative western blot (2 replicates) for anti-FLAG (48hr expression of control-enriched NRXN1α-FLAG). q, Representative western blot (2 replicates) for anti-FLAG (48hr expression of 3’-NRXN1+/- specific NRXN1α-FLAG). All error bars are s.e.

Extended Data Fig. 9 Predicted protein models for wild-type and mutant NRXN1α isoforms.

a, Superimposed image of the top ten most abundant wildtype NRXN1α isoforms in hiPSC-neurons. b, Superimposed predicted protein model of the top ten most abundant mutant isoforms. c, Superimposed predicted protein model of the top ten most abundant mutant isoforms compared to the most abundant wildtype isoform (grey). d, Individual predicted protein models of the top ten most abundant wild type isoforms. e, Individual predicted protein models of the top ten most abundant mutant isoforms. Insets in each panel highlight C-terminal region of NRXN1α isoforms where 3’-NRXN1+/- deletion is located.

Extended Data Fig. 10 Investigation of NRXN1α isoform changes across development.

a,b, Bar plot of the total read count for each NRXN1α exon along with the fraction that each NRXN1α junction is included in adult dlPFC samples (a) and fetal PFC samples (b); pink boxes represent potential developmentally regulated exons. c, Schematic of NRXN1α isoform structure, with each row representing a unique NRXN1α isoform and each column representing a NRXN1 exon. Colored exons (blue, fetal PFC specific; green, adult dlPFC specific; orange, shared) are spliced into the transcript while blank exons are spliced out. Abundance of each NRXN1α isoform across fetal PFC and adult dlPFC samples.

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Flaherty, E., Zhu, S., Barretto, N. et al. Neuronal impact of patient-specific aberrant NRXN1α splicing. Nat Genet 51, 1679–1690 (2019). https://doi.org/10.1038/s41588-019-0539-z

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