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. 2021 Jul;78(14):5605-5630.
doi: 10.1007/s00018-021-03865-z. Epub 2021 Jun 8.

Splicing and editing of ionotropic glutamate receptors: a comprehensive analysis based on human RNA-Seq data

Robin Herbrechter  1 , Nadine Hube  1 , Raoul Buchholz  1 , Andreas Reiner  2
Affiliations

Splicing and editing of ionotropic glutamate receptors: a comprehensive analysis based on human RNA-Seq data

Robin Herbrechter et al. Cell Mol Life Sci. 2021 Jul.

Abstract

Ionotropic glutamate receptors (iGluRs) play key roles for signaling in the central nervous system. Alternative splicing and RNA editing are well-known mechanisms to increase iGluR diversity and to provide context-dependent regulation. Earlier work on isoform identification has focused on the analysis of cloned transcripts, mostly from rodents. We here set out to obtain a systematic overview of iGluR splicing and editing in human brain based on RNA-Seq data. Using data from two large-scale transcriptome studies, we established a workflow for the de novo identification and quantification of alternative splice and editing events. We detected all canonical iGluR splice junctions, assessed the abundance of alternative events described in the literature, and identified new splice events in AMPA, kainate, delta, and NMDA receptor subunits. Notable events include an abundant transcript encoding the GluA4 amino-terminal domain, GluA4-ATD, a novel C-terminal GluD1 (delta receptor 1) isoform, GluD1-b, and potentially new GluK4 and GluN2C isoforms. C-terminal GluN1 splicing may be controlled by inclusion of a cassette exon, which shows preference for one of the two acceptor sites in the last exon. Moreover, we identified alternative untranslated regions (UTRs) and species-specific differences in splicing. In contrast, editing in exonic iGluR regions appears to be mostly limited to ten previously described sites, two of which result in silent amino acid changes. Coupling of proximal editing/editing and editing/splice events occurs to variable degree. Overall, this analysis provides the first inventory of alternative splicing and editing in human brain iGluRs and provides the impetus for further transcriptome-based and functional investigations.

Keywords: C-to-U editing; Next-generation sequencing (NGS); Nonsense-mediated decay (NMD); Primate-specific; Single-nucleotide polymorphism (SNP); Splicing error.

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Conflict of interest statement

The authors declare that they have no conflicts of interest.

Figures

Fig. 1
Fig. 1
RNA-Seq data analysis and abundance of human iGluR transcripts. A Alignment of individual cDNA reads to a reference genome provides direct information on splice junctions and single-nucleotide mismatches. B Single-nucleotide coverage of the canonical iGluR exons over all 35 analyzed datasets (Table S1–3). Short bars indicate the coverage of individual exons; red and blue bars indicate 5′- and 3′-exons, respectively. Longer bars show the corresponding mean
Fig. 2
Fig. 2
Analysis of canonical, known, and newly identified iGluR splice junctions. A All 259 known canonical junctions were identified. Normalization to the mean junction abundance of the respective subunit shows that canonical junctions belonging to a gene occur with rather similar abundance (see also Fig. S7A). B Most known alternative splice junctions from previously annotated transcripts were identified (93/120), but only 46 were classified as relevant based on our abundance criteria (blue). Normalization was performed with respect to the corresponding canonical junctions, see Methods. C Another 772 junctions were newly identified using a de novo identification approach, but based on their relative abundances, only 19 were classified as relevant (blue). D The relevant alternative junctions correspond to different events and iGluRs: C, alternative combination of canonical donor and acceptor sites; D, alternative donor site; A, alternative acceptor site; DA, alternative acceptor and donor sites. For splice site analysis see Fig. S6
Fig. 3
Fig. 3
De novo identified GluD1-b splicing isoform. A Our analysis revealed the existence of splice junctions, which indicate the incorporation of a 91 nt alternative exon (ae) between canonical exons 15 and 16. The coverage track shows a clearly defined exon (stop codons indicated by asterisks). B 5′- and 3′-junction abundance relative to the canonical junction (median indicated as bars; number of datasets with sufficient coverage given in parenthesis). C Incorporation of the alternative exon results in a hitherto undescribed isoform, GluD1-b, (896 aa), which contains an alternative C-terminus. D RT-PCR detection in human brain RNA. Exon-specific primers (F1/R1) show the amount of transcripts with (376 bp) and without (285 bp) alternative exon. Primers F2/R1 confirm the identity of the alternative exon, which was further confirmed by sequencing. Bands are absent in negative controls without reverse transcriptase (-RT). E Relative amounts of alternative F1/R1 RT-PCR product in RNAs from different human tissues. For further information, see Fig. S18
Fig. 4
Fig. 4
Alternative splicing in the C-terminal region of GluN1. A We detected all four C-terminal isoforms, which originate from incorporation of an alternative exon (ae) and the presence of two different acceptor sites in exon 19 [124]. B A comparison of splicing in different datasets (n = 33) shows a positive correlation between incorporation of the alternative exon (A+) and usage of the alternative acceptor site (B+). For other species, see Fig. S19. C A correlation analysis indicates that the absence or presence of the alternative exon (A−/A+) predicts the choice of the acceptor site (B−/B+; left), but not vice versa (right). D Resulting probability diagram for splicing to the alternative acceptor site
Fig. 5
Fig. 5
RNA editing in iGluRs and correlation with splicing. A Detection of single-nucleotide mismatches that report on potential A-to-I or C-to-U editing events (for details see Methods and Fig. S24). B Abundance of the ten most frequent events in different datasets (mean indicated by bars; (n) number of shown datasets (≥ 40 reads); see also Fig. S26). C Co-editing of sites within single-read distance. The circle sizes represent the read numbers obtained with editing-specific queries (see Table S8). Statistical testing shows independence for GluA2 Q607R/Q608Q editing, but interdependence for GluK2 Y571C/I567V and Q621R/G615G editing. D Relation between RNA editing and adjacent splice site usage. Statistical testing was performed with Pearson’s chi-squared test of independence (***p ≤ 0.0005; (n) number of total reads)
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