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Human UPF3A and UPF3B enable fault‐tolerant activation of nonsense‐mediated mRNA decay

2022; Springer Nature; Volume: 41; Issue: 10 Linguagem: Inglês

10.15252/embj.2021109191

1460-2075

Damaris Wallmeroth, Jan‐Wilm Lackmann, Sabrina Kueckelmann, Janine Altmüller, Christoph Dieterich, Volker Boehm, Niels H. Gehring,

Viral Infectious Diseases and Gene Expression in Insects

Article22 April 2022Open Access Source DataTransparent process Human UPF3A and UPF3B enable fault-tolerant activation of nonsense-mediated mRNA decay Damaris Wallmeroth Damaris Wallmeroth orcid.org/0000-0003-3437-4070 Institute for Genetics, University of Cologne, Cologne, Germany Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany Contribution: Conceptualization, ​Investigation, Visualization, Methodology, Writing - original draft, Writing - review & editing Search for more papers by this author Jan-Wilm Lackmann Jan-Wilm Lackmann orcid.org/0000-0001-8182-8034 CECAD Research Center, University of Cologne, Cologne, Germany Contribution: Resources, Data curation, ​Investigation Search for more papers by this author Sabrina Kueckelmann Sabrina Kueckelmann orcid.org/0000-0001-8070-8823 Institute for Genetics, University of Cologne, Cologne, Germany Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany Contribution: ​Investigation Search for more papers by this author Janine Altmüller Janine Altmüller Cologne Center for Genomics (CCG), University of Cologne, Cologne, Germany Contribution: Resources, Data curation Search for more papers by this author Christoph Dieterich Christoph Dieterich orcid.org/0000-0001-9468-6311 Section of Bioinformatics and Systems Cardiology, Department of Internal Medicine III and Klaus Tschira Institute for Integrative Computational Cardiology, Heidelberg University Hospital, Heidelberg, Germany DZHK (German Centre for Cardiovascular Research), Partner site Heidelberg/Mannheim, Heidelberg, Germany Contribution: Funding acquisition Search for more papers by this author Volker Boehm Corresponding Author Volker Boehm [email protected] orcid.org/0000-0001-7588-9842 Institute for Genetics, University of Cologne, Cologne, Germany Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany Search for more papers by this author Niels H Gehring Corresponding Author Niels H Gehring [email protected] orcid.org/0000-0001-7792-1164 Institute for Genetics, University of Cologne, Cologne, Germany Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany Contribution: Conceptualization, Supervision, Funding acquisition, Methodology, Writing - original draft, Writing - review & editing Search for more papers by this author Damaris Wallmeroth Damaris Wallmeroth orcid.org/0000-0003-3437-4070 Institute for Genetics, University of Cologne, Cologne, Germany Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany Contribution: Conceptualization, ​Investigation, Visualization, Methodology, Writing - original draft, Writing - review & editing Search for more papers by this author Jan-Wilm Lackmann Jan-Wilm Lackmann orcid.org/0000-0001-8182-8034 CECAD Research Center, University of Cologne, Cologne, Germany Contribution: Resources, Data curation, ​Investigation Search for more papers by this author Sabrina Kueckelmann Sabrina Kueckelmann orcid.org/0000-0001-8070-8823 Institute for Genetics, University of Cologne, Cologne, Germany Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany Contribution: ​Investigation Search for more papers by this author Janine Altmüller Janine Altmüller Cologne Center for Genomics (CCG), University of Cologne, Cologne, Germany Contribution: Resources, Data curation Search for more papers by this author Christoph Dieterich Christoph Dieterich orcid.org/0000-0001-9468-6311 Section of Bioinformatics and Systems Cardiology, Department of Internal Medicine III and Klaus Tschira Institute for Integrative Computational Cardiology, Heidelberg University Hospital, Heidelberg, Germany DZHK (German Centre for Cardiovascular Research), Partner site Heidelberg/Mannheim, Heidelberg, Germany Contribution: Funding acquisition Search for more papers by this author Volker Boehm Corresponding Author Volker Boehm [email protected] orcid.org/0000-0001-7588-9842 Institute for Genetics, University of Cologne, Cologne, Germany Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany Search for more papers by this author Niels H Gehring Corresponding Author Niels H Gehring [email protected] orcid.org/0000-0001-7792-1164 Institute for Genetics, University of Cologne, Cologne, Germany Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany Contribution: Conceptualization, Supervision, Funding acquisition, Methodology, Writing - original draft, Writing - review & editing Search for more papers by this author Author Information Damaris Wallmeroth1,2, Jan-Wilm Lackmann3, Sabrina Kueckelmann1,2, Janine Altmüller4,7,8, Christoph Dieterich5,6, Volker Boehm *,1,2 and Niels H Gehring *,1,2 1Institute for Genetics, University of Cologne, Cologne, Germany 2Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany 3CECAD Research Center, University of Cologne, Cologne, Germany 4Cologne Center for Genomics (CCG), University of Cologne, Cologne, Germany 5Section of Bioinformatics and Systems Cardiology, Department of Internal Medicine III and Klaus Tschira Institute for Integrative Computational Cardiology, Heidelberg University Hospital, Heidelberg, Germany 6DZHK (German Centre for Cardiovascular Research), Partner site Heidelberg/Mannheim, Heidelberg, Germany 7Present address: Core Facility Genomics, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany 8Present address: Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany *Corresponding author. Tel: +49 221 470 5260; E-mail: [email protected] *Corresponding author. Tel: +49 221 470 3873; E-mail: [email protected] The EMBO Journal (2022)41:e109191https://doi.org/10.15252/embj.2021109191 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract The paralogous human proteins UPF3A and UPF3B are involved in recognizing mRNAs targeted by nonsense-mediated mRNA decay (NMD). UPF3B has been demonstrated to support NMD, presumably by bridging an exon junction complex (EJC) to the NMD factor UPF2. The role of UPF3A has been described either as a weak NMD activator or an NMD inhibitor. Here, we present a comprehensive functional analysis of UPF3A and UPF3B in human cells using combinatory experimental approaches. Overexpression or knockout of UPF3A as well as knockout of UPF3B did not substantially change global NMD activity. In contrast, the co-depletion of UPF3A and UPF3B resulted in a marked NMD inhibition and a transcriptome-wide upregulation of NMD substrates, demonstrating a functional redundancy between both NMD factors. In rescue experiments, UPF2 or EJC binding-deficient UPF3B largely retained NMD activity. However, combinations of different mutants, including deletion of the middle domain, showed additive or synergistic effects and therefore failed to maintain NMD. Collectively, UPF3A and UPF3B emerge as fault-tolerant, functionally redundant NMD activators in human cells. Synopsis Human cells express two paralogs of the UPF3 gene, UPF3A and UPF3B, whose function in nonsense-mediated mRNA decay (NMD) is still a matter of debate. Here, both UPF3 paralogs are characterized as redundant NMD activators in human cells. Human UPF3A and UPF3B are fault-tolerant activators of the NMD pathway The co-depletion of both UPF3 paralogs results in strong NMD inhibition Bridge formation between the exon junction complex and the NMD machinery is not required NMD tolerates the inactivation of single UPF3B functional domains Introduction Precisely regulated expression of correct gene products is indispensable for eukaryotic life. This is underlined by the existence of several quality control mechanisms for gene expression, one of which is the nonsense-mediated mRNA decay (NMD). NMD is primarily known for its ability to eliminate mature mRNAs that contain a premature termination codon (PTC). Thereby, NMD prevents the synthesis and accumulation of C-terminally truncated proteins, which may possess undesirable and potentially disease-causing properties (Frischmeyer & Dietz, 1999). Although the removal of PTC-containing mRNAs was initially considered the most important function of NMD, later studies showed that NMD plays an important role in the post-transcriptional regulation of a substantial part of the transcriptome (Lelivelt & Culbertson, 1999; He et al, 2003; Mendell et al, 2004; Rehwinkel et al, 2005). The importance of the factors involved in NMD is underscored by the severe impact that mutations in components of this machinery have on development in metazoans, up to causing embryonic lethality in mammals (Medghalchi et al, 2001; Metzstein & Krasnow, 2006; Weischenfeldt et al, 2008; Wittkopp et al, 2009; McIlwain et al, 2010; Hwang & Maquat, 2011; Li et al, 2015). The final step of gene expression is the cytoplasmic translation of the mRNA by ribosomes. Previous studies suggested that prolonged ribosome stalling at a termination codon indicates improper translation termination and thereby triggers NMD (Amrani et al, 2004; Peixeiro et al, 2012). This could be caused by a long 3' untranslated region (UTR) that increases the distance between the stalled ribosome and the poly(A)-binding protein (PABPC1), which normally promotes proper translation termination (Amrani et al, 2004). Alternatively, NMD can also be activated by any PTC located more than 50–55 nt upstream of the 3'-most exon–exon junction. Transcripts with such a PTC may be transcribed from mutant genes with nonsense mutations but could also be generated by defective or alternative splicing (Kervestin & Jacobson, 2012). The aforementioned 50–55 nt boundary between NMD-activating and NMD-resistant PTCs is determined by the RNA-binding exon junction complex (EJC), which is deposited by the spliceosome 20–24 nt upstream of every spliced exon–exon junction (Le Hir et al, 2000). The EJCs remain attached on the mature mRNA during export into the cytoplasm, where they are removed by translating ribosomes or the disassembly factor PYM1 (Le Hir et al, 2000; Dostie & Dreyfuss, 2002). If translation terminates prematurely due to the presence of a PTC, EJCs bound downstream of the PTC serve as a marker for the NMD machinery and the initial activation of NMD (Kim et al, 2001; Le Hir et al, 2001). Extensive research over many decades has resulted in a model for EJC-dependent NMD. According to this model, the central factor UPF1 is bound non-specifically to all mRNAs in the cell and is removed from the coding sequence by translating ribosomes (Hogg & Goff, 2010; Hurt et al, 2013; Kurosaki & Maquat, 2013; Zund et al, 2013). If translation terminates prematurely, UPF1 interacts with the stalled ribosome and serves as the anchoring point for the other NMD factors. According to the literature, the presence of a downstream EJC is detected by a bridge to UPF1, which is established via one of the EJC-binding UPF3 proteins (UPF3A or UPF3B, see below) and the UPF1- as well as UPF3-binding protein UPF2 (Weng et al, 1996; Kim et al, 2001; Le Hir et al, 2001; Chamieh et al, 2008). This series of interactions marks the termination codon as premature and stimulates the phosphorylation of N- and C-terminal SQ motif-containing regions of UPF1 by the kinase SMG1 (Yamashita et al, 2001). In its phosphorylated state UPF1 recruits the heterodimer SMG5-SMG7 and/or SMG6, which are responsible for both exoribonucleolytic and endoribonucleolytic degradation of the mRNA, respectively (Chen & Shyu, 2003; Lejeune et al, 2003; Boehm et al, 2021). The endonuclease SMG6 cleaves the mRNA in close proximity to the PTC, resulting in two mRNA fragments (Eberle et al, 2009) of which the 3' fragment is degraded by the 5'-to-3' exoribonuclease XRN1 (Huntzinger et al, 2008; Eberle et al, 2009). In vertebrates, two independent genes referred to as UPF3A and UPF3B encode UPF3 paralogs. Both of them express two major isoforms by alternative splicing, resulting in at least four different UPF3 isoforms (Lykke-Andersen et al, 2000; Serin et al, 2001). These four human UPF3 proteins show a similar architecture and contain the same domains—with the notable exception of the UPF3A isoform lacking exon 4—but differ in details regarding their interactions to NMD-relevant proteins. As described above, the main function of UPF3A and UPF3B is believed to physically bridge the NMD protein UPF2 to the EJC (Lykke-Andersen et al, 2000; Serin et al, 2001; Kashima et al, 2006; Chamieh et al, 2008). Both, UPF3A and UPF3B interact via their conserved RNA recognition motif (RRM) in the N terminus with the C-terminal MIF4G (middle portion of EIF4G) domain of UPF2 (Kadlec et al, 2004). In cells in which both paralogs are expressed, UPF3A and UPF3B compete for their binding partner UPF2 due to their identical mode of binding (Chan et al, 2009). Since UPF3A molecules that are not complexed with UFP2 are inherently unstable, high UPF3B levels impede the binding of UPF3A to UPF2 and result in a decrease of UPF3A levels. To emphasize the extent of this steady-state UPF3 protein imbalance, a recent study using HEK293 cells estimated that although UPF3B mRNA is only 3-fold higher expressed than UPF3A, UPF3B protein levels are 100-fold higher than UPF3A (Cho et al, 2022). Conversely, when UPF3B levels are low, a larger proportion of UPF3A molecules can bind to UPF2, thereby stabilizing UPF3A. Hence, UPF3A levels are regulated by both, its paralog UPF3B, and its binding partner UPF2 (Chan et al, 2009). UPF3B interacts via a C-terminal sequence referred to as EJC binding motif (EBM) with a contiguous surface formed by the EJC core components EIF4A3, MAGOH and RBM8A (Gehring et al, 2003; Buchwald et al, 2010). UPF3A also contains an EBM and could therefore in principle interact with the EJC. However, its EBM sequence binds weaker to the EJC than that of UPF3B (Kunz et al, 2006). In addition, UPF3A is expressed considerably less due to the above-described competition with UPF3B. This suggests that under normal conditions, UPF3B represents the main EJC-interacting UPF3 paralog in the cell. Recently, UPF3B, but not UPF3A, was reported to interact with the eukaryotic release factor 3a (eRF3a, official symbol: GSPT1) via the so far uncharacterized middle domain (amino acids (aa) 147–256) (Neu-Yilik et al, 2017). Due to this interaction and binding of the terminating ribosome, it can delay translation termination, which is known to define aberrant termination events and trigger NMD (Amrani et al, 2004; Peixeiro et al, 2012; Neu-Yilik et al, 2017). Based on the reasons stated above, UPF3B is considered to be the major NMD-acting UPF3 paralog in mammalian cells. Over the last 10 years, several studies have investigated the impact of reduced UPF3B expression on NMD activity with different technologies in different human or murine cell types. Using reporter systems (e.g., PTC-containing β-globin) in human HeLa or HEK293 cells, stabilizing effects could be observed upon UPF3B knockdown, although mostly with mild effects (Metze et al, 2013; Baird et al, 2018). Contrary to other core NMD factors, UPF3B was only ranked at position 470 in a recent NMD-targeted siRNA screen (Baird et al, 2018) and not found in the top 24 hits of a CRISPR-based forward genetic screen for NMD pathway defects (Alexandrov et al, 2017), suggesting that reduced UPF3B expression does not severely impair NMD activity. Analyses of RNA-seq, microarray, and qPCR experiments from several patient-derived lymphoblastoid cell lines showed significant upregulation of hundreds of genes, however with limiting overlap between patients (Domingo et al, 2020) or with previously identified NMD targets (Nguyen et al, 2012). Similar technologies identified varying numbers of UPF3B-dependent NMD targets in several studies using different mouse knockout or antisense oligonucleotide (ASO)-mediated knockdown tissues/cell lines (Jolly et al, 2013; Huang et al, 2018a, 2018b; Tan et al, 2020). The consensus from these studies is that UPF3B is not required for all NMD events and may rather act on a subset of targets. This phenomenon is described in the concept of "branched NMD", which postulates that distinct branches of NMD are dependent on different NMD factors (reviewed in Yi et al, 2021). However, there is an alternative explanation why depletion of UPF3B may only lead to seemingly modest effects on NMD activity. As mentioned above, the paralog UPF3A becomes more abundant when UPF3B protein levels are reduced and thus accumulating UPF3A could functionally replace UPF3B. Some early studies showed that indeed UPF3A and UPF3B both trigger degradation of a reporter construct when tethered downstream of a termination codon (Lykke-Andersen et al, 2000; Gehring et al, 2003). The efficiency of UPF3A to elicit NMD was weaker in comparison to UPF3B, which was attributed to a weaker interaction with the EJC (Kunz et al, 2006). Notably, two patient-derived lymphoblastoid cell lines with different loss-of-function UPF3B mutations showed differentially increased UPF3A expression, which was inversely correlated with the severity of the patients' phenotype (Nguyen et al, 2012). This potential functional redundancy might explain why loss of UPF3B is—in contrast to other core NMD factors (mentioned above)—not embryonically lethal in humans and mice. In addition, a number of NMD substrates were only stabilized after a combined knockdown of UPF3A and UPF3B, but not after individual knockdowns (Chan et al, 2009). Taken together, these observations would suggest that, at least with respect to their NMD activity, UPF3A and UPF3B serve a similar, perhaps even redundant, function. On the other hand, it was recently reported that loss/downregulation of UPF3A in different murine cell lines/types or HeLa cells results in increased transcript destabilization, and UFP3A overexpression leads to NMD inhibition (Shum et al, 2016). These results would rather indicate opposing functions of the two UPF3 paralogs with UPF3A being either inactive as an NMD factor or an antagonist of UPF3B and acting as an NMD inhibitor. These different observations could also be interpreted as evolutionary "subfunctionalization" of UPF3A, acting as an NMD inhibitor on some transcripts and as an NMD activator on others (Jones & Wilkinson, 2017). In this study, we elucidate the functions and molecularly dissect the UPF3 paralogs UPF3A and UPF3B in the NMD pathway using different UPF3A and UPF3B overexpression and knockout (KO) HEK293 cell lines. We found that neither overexpression nor genomic KO of UPF3A resulted in substantial changes of NMD activity. In UPF3B KO cells, UPF3A protein levels were upregulated, but NMD activity was maintained at almost normal level. In contrast, the co-depletion of both UPF3 paralogs resulted in a marked NMD inhibition and a global upregulation of PTC-containing transcripts. Moreover, rescue experiments revealed that UPF3A and UPF3B proteins have additional functions besides bridging the EJC and the NMD machinery. Taken together, our data support a model of human NMD, in which UPF3A and UPF3B can replace each other and therefore perform redundant functions. Results UPF3A overexpression or knockout does not affect NMD efficiency Prior work using different mammalian models and various experimental approaches reached different conclusions regarding as to whether UPF3A is an NMD activator or repressor (Fig 1A). Therefore, we set out to re-examine the role of UPF3A in human cells by specifically manipulating its expression levels. Compared to UPF3B, UPF3A is barely present in commonly cultured human cells under regular conditions, because it is destabilized when not bound to the interaction partner UPF2, resulting in a rapid turnover of "free" UPF3A (Chan et al, 2009). We hypothesized that increasing the abundance of UPF3A should lead to the stabilization of NMD targets if UPF3A is an NMD inhibitor. To test this hypothesis, we generated Flp-In T-REx 293 (HEK293) and Flp-In T-REx HeLa (HeLa) cells inducibly overexpressing FLAG-tagged wildtype UPF3A to high protein levels (Fig 1B). Quantification of the FLAG-UPF3A protein levels via Western blot and whole proteome mass spectrometry analysis showed an average increase of 123- and 80-fold, respectively, compared to endogenous UPF3A, which was nearly undetectable in wildtype (WT) conditions (Fig EV1A and B). Western blot analyses also revealed that FLAG-UPF3A was approximately 5-fold higher expressed than endogenous UPF3B (Fig EV1A). We conclude that the obtained FLAG-UPF3A expression levels should be sufficient to observe a potential NMD-inhibitory effect. Global analysis of the transcriptome using RNA-seq (Fig EV1C and Datasets EV1–EV3) revealed, except for UPF3A itself, barely any significant differential gene expression (DGE), differential transcript usage (DTU) or alternative splicing (AS) events upon UPF3A overexpression compared to control conditions (Fig 1C and D, for total numbers see Appendix Fig S1A and B). Using these RNA-seq data, we analyzed NMD targets that were previously described to be upregulated in UPF3A overexpressing HeLa cells (Shum et al, 2016). The DGE analysis of eight selected targets and visualization of the read coverage of the NMD substrate SMG5 showed neither in HEK293 nor in HeLa cells substantial up- or downregulation when UPF3A was overexpressed (Figs 1E and EV1D). Contrary to the hypothesis that overexpressed UPF3A acts as an NMD inhibitor, quantification of differential transcript usage via IsoformSwitchAnalyzeR (Vitting-Seerup & Sandelin, 2019) could not detect an accumulation of PTC-containing transcripts (Fig EV1E). Collectively, these analyses indicated that UPF3A overexpression in HEK293 or HeLa cells does not negatively affect NMD in particular. Figure 1. UPF3A overexpression does not affect NMD Schematic representation of the bridge between UPF1 and the EJC during NMD. Binding of UPF3A instead of the stronger bound UPF3B is discussed to either activate or repress NMD. Western blot analyses after induced expression of FLAG-tagged UPF3A in WT HEK293 and HeLa cells (n = 1). Tubulin serves as control. The asterisk indicates unspecific bands. Fraction of expressed genes (genes with non-zero counts in DESeq2) were calculated which exhibit individual or combinations of differential gene expression (DGE), differential transcript usage (DTU), and/or alternative splicing (AS) events in HEK293 and HeLa WT cells overexpressing UPF3A using the respective computational analysis (cutoffs are indicated). AS and DTU events were collapsed on the gene level. For DGE, P-values were calculated by DESeq2 using a two-sided Wald test and corrected for multiple testing using the Benjamini–Hochberg method. For DTU, P-values were calculated by IsoformSwitchAnalyzeR (ISAR) using a DEXSeq-based test and corrected for multiple testing using the Benjamini–Hochberg method. For AS, P-values were calculated by LeafCutter using an asymptotic chi-squared distribution and corrected for multiple testing using the Benjamini–Hochberg method. Volcano plot showing the differential gene expression analyses from the RNA-Seq dataset of HEK293 and HeLa WT cells overexpressing UPF3A. The log2 fold change is plotted against the -log10 adjusted P-value (Padj). P-values were calculated by DESeq2 using a two-sided Wald test and corrected for multiple testing using the Benjamini–Hochberg method. OE = overexpression. Read coverage of SMG5 from WT HEK293 and HeLa RNA-seq data with or without induced UPF3A overexpression shown as Integrative Genomics Viewer (IGV) snapshot. Differential gene expression (from DESeq2) is indicated as log2 fold change (log2FC) on the right. Schematic representation of the protein coding transcript below. Source data are available online for this figure. Source Data for Figure 1 [embj2021109191-sup-0010-SDataFig1.zip] Download figure Download PowerPoint Click here to expand this figure. Figure EV1. UPF3A overexpression does not cause upregulation of NMD-targets Western blot analysis of unaltered HEK293 WT cells or with induced FLAG-UPF3A or FLAG-UPF3B expression. UPF3A, UPF3B, and FLAG levels were detected. Tubulin serves as control. Protein levels were quantified, normalized to tubulin expression, and shown as datapoints and mean (n = 4). Fold-changes of relevant conditions are shown. Skyline analysis of WT and UPF3A-overexpressing cells after whole proteome mass spec analysis. Quantifier intensities of UPF3A (left) and UPF3B (right) were normalized to actin (top) and tubulin (bottom) which were used as "loading controls". Results are shown as datapoints and mean (n = 4). The means were used to calculate the respective fold-changes. Schematic overview of the analysis pipeline. Heatmap of mean log2 fold changes (log2FC) of previously reported UPF3A-responsive NMD targets (Fig 3C of Shum et al, 2016) as determined by DESeq2 using the indicated RNA-Seq data. The data from SMG7 KO with SMG6 KD (Data ref: Boehm et al, 2021) serve as positive control for NMD inhibition. Volcano plot showing the differential transcript usage (via IsoformSwitchAnalyzeR) in RNA-Seq data of HEK293 and HeLa WT cells overexpressing UPF3A. Isoforms containing GENCODE (release 33) annotated PTC (red, TRUE), regular stop codons (blue, FALSE) or having no annotated open reading frame (gray, NA) are indicated. The change in isoform fraction (dIF) is plotted against the -log10 adjusted P-value (Padj). Density plots show the distribution of filtered isoforms in respect to the dIF, cutoffs were |dIF| > 0.1 and Padj < 0.05. P-values were calculated by IsoformSwitchAnalyzeR using a DEXSeq-based test and corrected for multiple testing using the Benjamini–Hochberg method. OE = overexpression. Source data are available online for this figure. Download figure Download PowerPoint Next, we approached the question of UPF3A function in the opposite way by generating UPF3A knockout (KO) HEK293 cell lines. Using CRISPR-Cas9 genome editing, we isolated three clones that lacked the UPF3A-specific band on the Western blot even after downregulation of UPF3B (Fig 2A). Two clones (14 and 20) were characterized in detail. Figure 2. UPF3A KOs show light NMD-independent transcriptome alterations A. Western blot analysis of WT and UPF3A KO cells (clones 4, 14, and 20) with the indicated siRNA treatments (n = 1). UPF3A and UPF3B protein levels were detected, Tubulin serves as control. The asterisk indicates unspecific bands. B. Quantitative RT–PCR of the indicated cell lines treated with the indicated siRNAs for 2 or 6 days. For RSRC2 and SRSF2 the ratio of NMD isoform to canonical isoform was calculated. ZFAS1 expression was normalized to C1orf43 reference. Data points and means are plotted as log2 fold change (log2FC) (n = 3 for RSRC2 and SRSF2, n = 4 for ZFAS1). C. Fraction of expressed genes (genes with non-zero counts in DESeq2) were calculated which exhibit individual or combinations of differential gene expression (DGE), differential transcript usage (DTU) and/or alternative splicing (AS) events in the indicated conditions using the respective computational analysis (cutoffs are indicated). AS and DTU events were collapsed on the gene level. For DGE, P-values were calculated by DESeq2 using a two-sided Wald test and corrected for multiple testing using the Benjamini–Hochberg method. For DTU, P-values were calculated by IsoformSwitchAnalyzeR using a DEXSeq-based test and corrected for multiple testing using the Benjamini–Hochberg method. For AS, P-values were calculated by LeafCutter using an asymptotic chi-squared distribution and corrected for multiple testing using the Benjamini–Hochberg method. D, E. Volcano plots showing the differential gene expression analyses from the indicated RNA-Seq datasets (D UPF3A KO clone 14, E UPF3A KO clone 20). The log2 fold change is plotted against the −log10 adjusted P-value (Padj). P-values were calculated by DESeq2 using a two-sided Wald test and corrected for multiple testing using the Benjamini–Hochberg method. F. nVenn Diagram showing the overlap of up- or downregulated genes in the UPF3A KO cell lines 14 and 20. Log2 fold change < 1 (downregulated) or > 1 (upregulated) and adjusted P-value (Padj) < 0.05. DGE = Differential Gene Expression. Source data are available online for this figure. Source Data for Figure 2 [embj2021109191-sup-0011-SDataFig2.zip] Download figure Download PowerPoint In both cell lines, the UPF3A genomic locus contained insertions and/or deletions causing frame-shifts and eventually PTCs (Figs EV2A–C). To gain a first impression of the NMD activity in the UPF3A KO cells, the transcript levels of three known exemplary endogenous NMD targets, RSRC2, SRSF2, and ZFAS1 were determined by qPCR (Sureau et al, 2001; Lykke-Andersen et al, 2014; Boehm et al, 2021). These targets represent three different classes of NMD substrates: RSRC2 mRNAs can acquire a PTC by alternative splicing, SRSF2 mRNAs can be spliced in the 3' UTR, and ZFAS1 is a non-coding snoRNA host gene containing only a short open reading frame. WT HEK293 cells treated with SMG6 and SMG7 siRNAs were used as a positive control for severe NMD inhibition (Fig 2B) (Boehm et al, 2021). While the absence of UPF3A did not result in strong abundance changes of the NMD-sensitive isoforms of SRSF2 and RSRC2 (mean log2 fold change between −0.