Protein C-terminal variations impact proteostasis

Domain: neuroscience
Published: 2026-02-03
Editorial outcome: minor_revision

Abstract
Protein C-termini can vary due to errors or programmed regulation, contributing to proteome diversity, yet their impact on the proteome remains poorly understood. Although aberrant C-termini are often linked to protein degradation, it is unclear if this holds true universally. In this study, we examine how C-terminal variations—arising from disease-associated nonstop mutations, alternative splicing, and translational readthrough—affect protein half-lives. Our findings indicate that, contrary to previous studies, erroneous C-termini can either stabilize or destabilize proteins. We have identified multiple oncoproteins and tumor suppressors whose protein stability is altered by disease-relevant nonstop mutations. Notably, we have found that C-terminal variations commonly influence the stability of canonical proteins, extending beyond their role in protein quality control. Furthermore, we have uncovered C-terminal features that distinguish erroneous from wild-type proteins and reveal that hydrophobic C-termini are targeted by a complex ubiquitin ligase network. Overall, our work broadens the understanding of C-terminal-dependent protein degradation and support that C-terminal variation is a widespread strategy for generating protein forms with distinct half-lives to exert diverse biological functions.

Introduction
Diversity in a given protein’s C-terminal tail is a common feature of proteomes. This diversity can arise from various errors, such as genetic mutations, spontaneous transcriptional or translational mistakes, erroneous splicing, and posttranslational damage. For instance, nonsense and frame-shifting indel (insertion-deletion) mutations produce truncated proteins that terminate with internal peptides or frameshift C-termini, respectively. Nonstop mutations (those occurring within the stop codon of a gene) lead to the expression of full-length proteins displaying C-terminal extensions encoded by the 3’ untranslated region (UTR). Translational misreading, such as ribosomal frameshifting and stop codon readthrough, also generates proteins with abnormal C-termini. It has been estimated that basal stop codon readthrough occurs in mammalian cells at levels ranging from 0.01 to 0.1%, depending on the type of stop codon, and spontaneous frameshift errors can occur at a rate of approximately one in 10^5 codons1,2. These anomalous C-termini were shown to exhibit elevated hydrophobicity, which marks the resulting defective proteins for elimination via Bag6 chaperone-associated E3 ligases—namely RNF126 and RNF1153,4. However, it remains unclear if Bag6-E3 complexes alone are responsible for recognizing the entire spectrum of hydrophobic C-termini in human cells. Moreover, apart from a few documented examples5,6, the effects of disease-associated nonstop C-terminal extensions on the respective mutated proteins remain largely unknown. A recent study systematically investigated the impact of disease-relevant nonstop mutations7. However, that study overlooked the potential influence of canonical C-termini on protein half-life, which may affect the validity of its conclusions.

In addition to unintended errors, programmed regulatory mechanisms such as mRNA alternative splicing and programmed translational recoding events also expand the repertoire of protein C-terminal variants. Alternative splicing occurs in up to 98% of human multi-exon coding genes and often lead to the expression of nearly identical protein isoforms with subtle differences at their C-termini. Programmed stop codon readthrough (context-dependent readthrough) is a well-known form of translational reprogramming, whereby stop codons are interpreted as sense codons that incorporate either a canonical amino acid or a specialized one, such as selenocysteine (Sec) or pyrrolysine (Pyl), resulting in the expression of proteins with extended C-termini8–11. Ribosome profiling and mass spectrometry analyses have revealed that programmed readthrough is much more widespread than previously appreciated12–15. Although the frequency of occasional stop codon readthrough is low, it increases dramatically in programmed readthrough, reaching up to 10-80%, depending on the sequence context of the mRNA and trans factors1,10,16. It has been shown previously that isoform-specific C-termini regulate the stability of SRY, MAX, and SMN2 proteins, with these variations contributing to sex determination, the hypoxia response, and the severity of spinal muscular atrophy, respectively17–19. Our lab has shown that C-terminal extensions in selenoproteins inhibit C-degrons and subsequently prevent selenoprotein degradation20. However, current attention on C-terminal-dependent protein degradation is primarily focused on its role in protein quality control3,21–24. How this pathway influences the canonical proteome and affects diverse biological processes has yet to gain global attention.

In this work, we conduct a comprehensive analysis of the impacts on protein half-life of C-terminal variants resulting from disease-relevant nonstop mutations, alternative mRNA splicing, and programmed translational readthrough. We also investigate how C-terminal amino acid composition and patterns influence protein stability and apply this information to compare canonical and deviant C-termini. Moreover, we perform CRISPR screens to identify additional ubiquitin ligases that target hydrophobic C-termini. Our work not only expands the list of protein species subjected to C-terminal-dependent protein degradation but also indicates that, beyond maintaining proteome fidelity, C-terminal alterations serve as a universal mechanism for modulating the abundance of active proteins to meet various biological needs.

Results
Disease-associated nonstop mutations can either prolong or impair protein half-life
Compared to frameshift and nonsense mutations, nonstop mutations have received less clinical attention because they produce proteins of near-normal length and presumed biological function. Multiple previous reports have suggested that readthrough (RT) C-termini resulting from nonstop mutations and translational readthrough can promote protein degradation5–7,21. For example, Ghosh et al. examined the effects of cancer-associated nonstop mutations by fusing the corresponding RT C-termini to the C-terminus of GFP7. They found that these aberrant C-termini generally reduced GFP expression, and accordingly classified them as being primarily suppressive. However, one limitation of the approach adopted by Ghosh et al. is that it overlooks the potential influence of the wild-type (WT) C-termini on protein half-life. Rather than performing a direct comparison between the effects of RT and WT C-termini on GFP stability, they compared the stability of GFP fused with RT C-termini to GFP alone (Supplementary Fig. 1A, top panel). Here, we found that, similar to RT C-termini, tagging GFP with WT protein C-termini can also lead to GFP degradation (Fig. 1A). However, surprisingly, the degronic potency of the WT C-termini can be either stronger (e.g., MDC, MYH2) or weaker (e.g., TOPORS, PRDM1) than that of their RT counterparts (Fig. 1B). This outcome suggests that nonstop mutations and translational readthroughs may not only be suppressive, but could also be supportive or stimulative, thereby increasing protein abundance.

To test this hypothesis, we performed a GPS (global protein stability)-based peptidomic screen to directly compare the degradation effects of disease-relevant nonstop RT C-termini and their WT counterparts (Fig. 1C and Supplementary Fig. 1A, bottom panel). The GPS approach utilizes a lentiviral-based reporter that co-expresses two fluorescent proteins—GFP fused to the peptide of interest and RFP as an internal control—via an internal ribosome entry site (IRES). Since both the GFP-peptide fusion construct and RFP are translated from the same mRNA, the GFP/RFP ratio represents a measure of the effect of the peptide sequence on GFP stability25. We assessed 2227 nonstop mutations from the pan-cancer NonStopDB dataset6, as well as an additional 799 nonstop mutations and 415 readthrough single-nucleotide polymorphisms (SNPs), some of which are associated with human hereditary diseases5. Specifically, we cloned oligonucleotides encoding the last 58 residues of WT and RT proteins into the GPS reporter, introduced these constructs into HEK293T cells via single-copy viral transduction, and sorted the GPS reporter cells into eight bins based on GFP/RFP ratios, with these latter indicative of the stability of the expressed GFP-peptide fusion construct in each cell. We retrieved oligonucleotides from each bin for sequencing, calculated the Protein Stability Index (PSI) of each peptide, and then determined the difference in PSI between the RT and WT peptides (ΔPSI) (Fig. 1C). A positive ΔPSI value indicates that the nonstop mutation increases the stability of the corresponding protein, and vice versa. We conducted two biological replicates of the screen, which were highly correlated (Fig. 1D).

Consistent with the notion that canonical protein C-termini have evolved to evade C-terminal-mediated degradation26,27, we found that, on average, RT C-termini are more effective at promoting protein degradation than WT C-termini (Fig. 1E). However, each individual nonstop mutation may either enhance (9.51%) or reduce (28.4%) the stability of the corresponding proteins (Fig. 1F, G), using a threshold of |ΔPSI| ≥ 1. Next, we compared our screening results with those of Ghosh et al., who reported that most nonstop mutations reduce protein expression and that the remainder could be considered neutral7. Among the 1908 mutations common to both studies, only 42.89% of those previously annotated as destabilizing actually reduced host protein stability, and in fact, 6.01% were found to increase it. Furthermore, more than 27% of mutations previously considered neutral had measurable effects on protein stability: 16.54% led to stabilization, whereas 11.08% caused degradation (Fig. 1H). The complete dataset is available in Supplementary Data 1.

The length of RT tails resulting from each nonstop mutation varies depending on the location of the downstream stop codon within the 3’ UTR. We examined if changes in protein stability are correlated with RT tail length. Although we did detect a positive correlation, our data also indicate that in many cases even small extensions can significantly influence protein stability (Fig. 2A). To identify short degron motifs, we focused on RT extensions of 20 amino acids or fewer (Fig. 2B). Notably, many of the observed degradation or stabilization events can be attributed to known C-degrons, such as diGlu, diGly and other Gly-based degrons26,28 (Fig. 2C and Supplementary Fig. 1B). Introducing these motifs led to protein destabilization, whereas capping existing C-degrons with RT C-terminal extensions resulted in protein stabilization (Fig. 2D). In addition to known motifs, we identified previously unreported C-terminal sequences that influence protein stability (Fig. 2E and Supplementary Fig. 1C). We validated their effects in full-length proteins using GPS assays (Fig. 2F) and cycloheximide (CHX)-chase experiments with FLAG-tagged constructs (Supplementary Fig. 1D).

Next, we explored the potential pathogenic relevance of protein stability changes caused by nonstop mutations, given that alterations in protein abundance are a key mechanism in cancer and other diseases. Our data revealed a modest bias toward destabilization in tumor suppressor proteins compared to oncoproteins (Fig. 2G). We validated experimentally the nonstop mutation-induced stabilization of several oncoproteins (CCND2, SNCG, FOXA1, HEY1, CPNE9) and the degradation of several tumor suppressor proteins (MAX, PTEN, RAD23B, LIMD1, CTCF, AHNAK, DAB2, RBM4, BCL2L11, DUSP9) by GPS and CHX-chase assays (Fig. 2H, Supplementary Fig. 2A–C). In addition, we confirmed degradation of the proteins MOCS2, NHP2, and FHL1 caused by genetic disease-associated nonstop mutations (Fig. 2I, Supplementary Fig. 2B, C). The differential degradation of wild-type or nonstop mutation-induced readthrough proteins is mainly proteasome-dependent (Supplementary Fig. 2D). Although nonstop mutations account for ~0.2% of all codon-changing mutations, they remain among the least studied due to their presumed mild effects29. Our work provides the most comprehensive functional annotation of disease-relevant nonstop mutations to date, demonstrating that—like nonsense and missense mutations—nonstop mutations may substantially affect cellular processes by altering the abundance of the respective proteins.

Alternative splicing or programmed readthrough diversifies protein C-termini to impact protein stability
In addition to mutations and translational errors, mRNA alternative splicing and programmed translational readthrough contribute to the diversity of the protein C-terminome. Though most studies on C-terminal-mediated degradation have focused on its role in protein quality control, the effects of physiological C-terminal diversification on the proteome remain largely unexplored.

We conducted a sequence analysis of protein isoforms derived from alternative mRNA splicing. Our results reveal that isoforms with distinct C-termini are remarkably widespread. Up to 62.5% of human genes produce isoforms with more than one type of C-terminus, and 22.4% generate isoforms with five or more distinct C-terminal variations (Fig. 3A). Focusing specifically on isoforms that differ only at their C-termini (i.e., with the remainder of the protein sequence being identical), we found that more than 3000 genes encode isoforms with variations of fewer than 20 amino acids, and more than 1000 genes produce isoforms differing by fewer than five residues. Prior research on SMN2 protein has demonstrated that isoform-specific C-terminal variation affects its stability19. To determine if this represents a general phenomenon, we examined 11 additional genes and observed that isoforms of the majority (7 out of 11) exhibited distinct protein half-lives, indicating that C-terminal diversification is a common mechanism for regulating isoform stability (Fig. 3B, C and Supplementary Fig. 3A).

Programmed translational readthrough has been identified in more than 100 human genes through techniques such as ribosome profiling, mass spectrometry, and reporter assays (Supplementary Fig. 3B and Supplementary Data 2). There is already evidence that the extended C-termini generated by programmed readthrough can influence protein stability. For instance, our previous study uncovered that recoding the UGA codon into Sec increases selenoprotein stability20. We have also verified that the double-readthrough form of MTCH2 (MTCH2xx) is less stable than its shorter variants (MTCH2, MTCH2x) 30 (Fig. 3D). To further assess the impact of programmed readthrough, we examined ten selected genes and found that readthrough events affected protein stability in six of them, including CGGBP1, BTG1, TIMP1, SQSTM1, PRDX4, and VDR (Fig. 3E and Supplementary Fig. 3C). In these cases, the readthrough isoforms were either more or less stable than their canonical forms. Together, these findings underscore the universal and functional significance of protein C-terminal diversification—both canonical and aberrant—in regulating protein half-lives across the proteome.

Amino acid composition and arrangement in protein C-termini influence protein half-lives
Given the widespread influence of protein C-termini on protein stability, we investigated the specific features of the C-terminus that affect protein half-lives. Previous studies, including our own, have defined several C-degron motifs that promote protein degradation26,28. However, our research has indicated that most C-terminal sequences influencing stability do not adhere to well-defined consensus motifs. This sequence degeneracy likely accounts for the broad impact of C-termini on the proteome. Supporting this idea, we observed that attaching commonly used epitope tags to protein C-termini also alters their half-lives (Fig. 4A). Traditionally, the identification of functional motifs relies on multiple sequence alignment to detect conserved residues, followed by site-directed mutagenesis for validation. However, this method has limitations; principally, in that it struggles to detect ambiguous, complex, or dropout features. Furthermore, conclusions drawn from mutagenesis are often template- and amino acid-specific, and extending such analyses across multiple sequences or residues is labor-intensive. To address these challenges, we employed a context-independent add-in approach. To do so, specific amino acid features were introduced into randomized peptide sequences, enabling assessment in a pooled manner of their effects across diverse sequence contexts. Previously, we applied this random peptide platform effectively to study how sequences surrounding known C-degrons influenced degradation efficiency27.

To systematically explore the influence of amino acid identity, position, and arrangement on protein stability, we designed five peptide templates that varied either in terms of their terminal residue or overall composition (Fig. 4B). The results revealed several key trends. The presence of small terminal amino acids (Gly, Ala), or increased overall frequencies of Arg, Cys, or hydrophobic residues (Val, Ile, Leu, Met, Phe, Tyr, Trp), tended to promote degradation. In contrast, enrichment of acidic residues (Asp, Glu) was associated with increased stability (Fig. 4C). The positional context of these residues proved critical. For instance, although hydrophobic residue enrichment generally promoted degradation, their presence at the terminal position did not elicit the same effect. Similarly, Gly triggered degradation only when positioned at the extreme C-terminus. Most notably, the arrangement of amino acids also played a crucial role in determining protein half-life. Even when the total number of specific residues was held constant, clustering (rather than dispersing) them prompted a pronounced effect. In particular, consecutive Cys residues exerted the strongest synergistic degradative impact (Fig. 4D). These findings highlight that not only the identity of C-terminal residues, but also their positioning and arrangement, are key determinants of protein stability.

Enrichment of Cys and Trp, along with depletion of Asp and Glu, drives protein degradation arising from readthrough and frameshift events
Next, we compared the C-termini of canonical and aberrant proteins using insights from our random peptide assay as reference points (Figs. 5, 6). We focused our analysis on canonical cytosolic proteins, as proteins localized to different compartments or organelles are likely subject to distinct evolutionary pressures23,27. For example, secreted proteins may not encounter cytosol-localized E3 ligases. Specifically, we examined the C-termini of human cytosolic proteins using principal component analysis (PCA) of the final 150 amino acid residues. We detected clear signals of selective pressure on protein stability, evident in both amino acid composition and terminal residue usage. Specifically, we observed a gradual decrease in hydrophobic amino acids toward the C-terminus (PC1), along with a marked depletion of Gly and Ala at the extreme C-terminus (PC2) (Fig. 5A, B and Supplementary Fig. 4A, B). The percentages next to PC1 and PC2 represent the proportion of total variance in the dataset explained by each principal component. In addition to amino acid composition, amino acid arrangement also appears to be under evolutionary constraints. The frequency of consecutive hydrophobic or acidic residues at the C-termini of human cytosolic proteins deviates significantly from random expectations, being lower for hydrophobic clusters and higher for acidic clusters (Fig. 5C). We extended this analysis to canonical cytosolic proteins across multiple species, recognizing that global amino acid usage differs substantially among the kingdoms of life. Interestingly, although C-terminal compositional biases were evident across species, they were always relative to the overall proteomic amino acid usage of each species (Fig. 5D, E). Notably, these trends are not uniformly conserved. For example, a reduction in hydrophobic amino acids was observed in mouse, nematode, yeast, and bacterial proteomes, but it was either absent or less pronounced in those of flies (Fig. 5F, left panel). Moreover, unlike cytosolic proteins in human, mouse, nematode and yeast, the terminal residues of cytosolic proteins in fly, plant, and bacterial proteomes do not appear to deviate from the remainder of the C-terminal region along PC2 (Fig. 5E). These differences may reflect species-specific biology, such as the high prevalence of stop codon readthroughs in flies and plants12,15, or the absence of E3 ligases targeting Gly/Ala C-degrons in bacteria.

Our PCA revealed distinct compositional differences between canonical and aberrant C-termini arising from readthrough and frameshift events (Fig. 6A and Supplementary Fig. 4C, D). Contrary to previous reports that have suggested a general increase in hydrophobicity in aberrant proteins, our analysis showed that only Cys, Trp, Arg, and Pro are consistently enriched in all types of erroneous C-termini. Among these residues, Cys and Trp—two of the rarest amino acids—exhibited the most significant increases (Fig. 6B). In parallel, we observed a consistent depletion of the acidic, stabilizing residues Asp and Glu in aberrant C-termini. This opposing trend, i.e., enrichment of Cys and Trp, yet depletion of Asp and Glu, was conserved across species (Fig. 6C). To assess the functional impact of Cys and Trp enrichment, we compiled a list of proteins displaying readthrough extensions that were enriched for these residues and compared their stability to their canonical counterparts. We found that these readthrough variants were consistently less stable (Fig. 6D), and this destabilization was largely attributable to Cys and Trp, as substituting them with Ala significantly improved protein stability (Fig. 6E). Further evidencing the roles of Cys, Trp, Asp, and Glu in determining protein stability, we introduced Ala substitutions into the readthrough extensions of the disease-associated nonstop mutation genes presented in Fig. 1. This set of experiments confirmed that Cys and Trp contribute to degradation, whereas Asp and Glu confer stability (Fig. 6F).

Thus, our findings indicate that canonical C-termini have evolved under selective pressure to minimize degradation, whereas aberrant proteins resulting from frameshift or stop codon readthrough can be recognized by the atypical amino acid composition of their C-terminal tails. This compositional signal provides a broad, sequence-independent cue for identifying deviant proteins. In addition to the increased hydrophobicity observed for some readthrough products (see below), enrichment for Cys and Trp, coupled with depletion of Asp and Glu, have emerged from our data as key determinants driving the selective clearance of abnormal proteins, thereby preserving proteome integrity.

Multiple ubiquitin ligases collaborate to target erroneous proteins with hydrophobic C-termini for degradation
Previous studies have suggested that elevated C-terminal hydrophobicity is a hallmark of erroneous proteins, with such hydrophobic tails being recognized by the Bag6 chaperone-RNF126 ubiquitin ligase complex to trigger proteasome-mediated degradation3,4. However, it remains unclear if the Bag6-RNF126 complex alone is sufficient to recognize the full spectrum of hydrophobic C-termini in human cells. In addition, the influence of hydrophobic residue arrangement and surrounding sequence context on this degradation mechanism remains enigmatic.

To address these questions, we examined the degradation pathways of seven readthrough proteins with hydrophobic extensions, identified from the disease-associated nonstop mutation screen described above (Figs. 1, 7A). As indicated by their negative ΔPSI values, all seven hydrophobic C-termini promoted degradation of their respective host proteins. Surprisingly, only one of these—TMEM70-RT—proved to be a target of the Bag6-RNF126 complex (Fig. 7B), challenging the notion that this pathway is solely responsible for recognizing hydrophobic C-termini. To explore alternative degradative mechanisms, we performed CRISPR/Cas9 screens for three hydrophobic variants (RGS18-RT, UBA5-RT, RAB18-RT), and identified MARCH6 and RNF139 as additional E3 ligases involved in recognizing hydrophobic C-termini (Fig. 7C). Notably, knockout of Bag6/RNF126, RNF139, or MARCH6 failed to prevent degradation of all hydrophobic variants, such as LAMTOR5-RT and ARHGEF35-RT, implying either the involvement of yet unidentified E3 ligases or functional redundancy among known ones (Fig. 7D).

Since multiple E3 ligases target hydrophobic C-termini, we adopted RGS18-RT as a model to dissect how the arrangement of hydrophobic residues and local sequence context influence degradation. RGS18-RT harbors two hydrophobic segments, H1 (LILLIFM) and H2 (LYICF), separated by the two residues TN. We generated a series of RGS18-RT mutants, i.e., constructs retaining only one hydrophobic segment (with or without TN), scrambled variants, and constructs with altered TN positioning (Fig. 7E). Although all of the resulting variants promoted degradation when fused to the C-terminus of GFP, the extent of degradation varied widely, even with minor sequence alterations (Fig. 7F). For example, the H1-TN variant (LRKLILLIFMTN) promoted stronger degradation than TN-H1 (LRKTNLILLIFMTN), despite both having the same amino acid compositions. Similarly, TN-H2 (LRKTNLYICF) was more destabilizing than its scrambled counterpart, TN-S2 (LRKTNFCIYL). Crucially, these subtle sequence differences not only modulated degradation levels but also dictated which E3 ligase mediated recognition (Fig. 7G). For instance, the H2 variant was specifically targeted by MARCH6, whereas inclusion of the TN motif upstream (TN-H2) shifted recognition to RNF139. Neither ligase recognized the scrambled version of the TN-H2 variant, i.e., TN-S2, highlighting the sequence specificity of substrate recognition. Similar context-dependent shifts in ligase specificity were also observed among H1-based constructs (Fig. 7G).

Together, these findings uncover the unexpected complexity in the ubiquitin ligase network targeting the hydrophobic C-termini arising from diverse erroneous events. They also demonstrate that degradation is not dictated solely by the presence of hydrophobic residues, but also their precise arrangement and the surrounding sequence context, representing factors that determine both degradation efficiency and the identity of the responsible degradation machinery.

Methods
Cell culture, lentivirus production, and gene knockout
HEK293T cells (ATCC® CRL-3216) were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 10% fetal bovine serum (Hyclone), 100 μg/ml streptomycin, and 100 μ/ml penicillin (Gibco). Cells were maintained at 37 °C in a humidified incubator with 6% CO₂. To block proteasome dependent protein degradation, cells were treated with 1 nM bortezomib (BioVision) for 6 hr.

For lentivirus production, HEK293T cells were co-transfected with packaging plasmids pRev, pTat, pHIV gag/pol, pVSVG, and the lentiviral construct of interest using the TransIT-293 transfection reagent (Mirus Bio). Viral supernatants were harvested 48 hours post-transfection. For transduction, cells were incubated with viral supernatants in the presence of 8 μg/mL polybrene (Sigma-Aldrich) for 24 h.

To achieve gene knockout, stable Cas9-expressing HEK293T cells were transduced with lentiviruses encoding gene-specific sgRNAs. Cells were analyzed five days post-infection. Target sequences and catalog information are listed in Supplementary Table 1.

GPS assay and random peptide platform
To generate GPS reporter constructs, peptides or genes of interest were cloned into pLenti-GPS RFP-IRES-GFP or BFP-IRES-GFP vectors using Gibson assembly (New England Biolabs) or Gateway recombination (Invitrogen). HEK293T cells were transduced with lentiviruses expressing reporter constructs at low multiplicity of infection (MOI ~ 0.1) and selected with 1 μg/ml puromycin (Clontech) for 7 days to establish stable GPS reporter lines.

GFP/RFP or GFP/BFP fluorescence ratios were quantified by flow cytometry using a BD LSR Fortessa system (BD Biosciences) with lasers at 561 nm, 488 nm, and 405 nm for RFP, GFP, and BFP excitation, respectively. For standard GPS assays, a minimum of 10,000 cells was analyzed using FlowJo software. We analyzed the results by first gating single cells based on FSC and SSC signals, and then selecting RFP-positive cells (Supplementary Fig. 5). All GPS analysis were done in biological triplicate.

For the random peptide assay, oligonucleotides encoding 12- or 15-residue random peptides were synthesized (Life Technologies) and amplified by polymerase chain reaction (PCR) using 5’ and 3’ linker sequences. Random residues were encoded using NNK degenerate codons (N=A/T/G/C; K=G/T). PCR products were cloned into the pDONR223 vector via Gibson assembly and transferred into the pLenti-GPS reporter vector using Gateway LR recombination. To reduce synthesis bias, three independent libraries were constructed for each design using separately synthesized oligonucleotides. Each library had an estimated complexity of ~10^10 unique variants. Due to the large complexity of random peptide libraries (~10^10), 100,000 cells per library were analyzed in triplicate. The percentage of cells with reduced GFP/RFP ratios (termed “% degradation”) was used as an index of peptide-mediated degradation27.

GPS-peptidomic screen for disease-associated nonstop mutations
Disease-associated nonstop mutations were collected in September 2021 from TCGA (https://portal.gdc.cancer.gov/) and the NonStopDB database (http://NonStopDB.dkfz.de). Readthrough-associated SNPs were retrieved from dbSNP (https://www.ncbi.nlm.nih.gov/snp/). All coding and 3’ UTR sequences were verified using Ensembl and NCBI databases. DNA sequences encoding the final 58 amino acids of canonical and mutated proteins were synthesized (Twist Biosciences), PCR-amplified using a KAPA HiFi HotStart kit (Roche), and cloned into the GPS vector via Gateway recombination. A library complexity of >10^3-fold was maintained throughout cloning.

The GPS-peptidomic reporter cell library was generated by lentiviral transfection at an MOI of ~0.05 to minimize double-integration events. The library was generated at ~1000-fold representation and sorted into eight bins based on GFP/RFP ratios using a BD FACSAria II SORP sorter (BD Biosciences). Genomic DNA from each bin was extracted and used for PCR amplification of integrated oligos using TaKaRa Ex Taq® DNA Polymerase Hot-Start Version (Takara Bio) with the following primers:
• Forward primer (5’-GAGCTGAAGGGCATCGACTTCAAGG-3’)
• Reverse primer (5’-GCGTCAGATGTGTATAAGAGACAG-3’)

PCR conditions: 21 cycles of 98 °C for 10 s, 60 °C for 30 s, 72 °C for 30 s, with a final extension at 72 °C for 5 min. Products were purified using a MinElute PCR purification kit (QIAGEN) and quantified using Qubit™ fluorometric quantification (Thermo). A second PCR (8 cycles, same conditions) was performed to add Illumina indices using the primers listed in Supplementary Table 2. Indexed products were purified with AMPure XP beads (Beckman Colter) and quantified via a Bioanalyzer 2100 system (Agilent). Sequencing was performed using the MiSeq Reagent Kit v3 (Illumina) with the primer 5’-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG-3’. Only reads that perfectly matched the designed sequences were retained. Peptides with ≥60 reads in both replicates were included in downstream analysis. PSI values were calculated to evaluate degradation-promoting activity.

Cycloheximide-chase assay
Genes of interest were cloned into a Lenti-based vector via Gateway recombination to generate FLAG-tagged reporter constructs. Stable cell lines were established by lentiviral infection as described above. Cells were treated with 100 µg/mL cycloheximide (Calbiochem), and samples were collected at multiple time points. Protein abundance was analyzed by immunoblotting using primary antibodies against the Flag-tag (Sigma-Aldrich, M2 at 1:1000) and GAPDH (GeneTex, 100118 at 1:1000).

CRISPR/Cas9 screen
Stable Cas9-expressing GPS reporter cells were transduced with lentiviruses from the Proteostasis sublibrary of the Human CRISPR Deletion Library (a gift from Michael Bassik, Addgene #101930)51 at an MOI of 1. After 10 days, mCherry+ cells with the top 5% highest GFP/BFP ratios were sorted, while the total population was used as a control. Genomic DNA was extracted, and sgRNA sequences were PCR-amplified as described previously52. Sequencing was performed using a MiSeq Reagent Kit V3 (Illumina), and sgRNA enrichment was analyzed using the casTLE algorithm53. According to the analysis pipeline, casTLE applies an Empirical Bayesian framework to estimate the functional impact of gene knockouts in CRISPR-Cas9 pooled screens. It accounts for variability in guide RNA (gRNA) efficacy and potential off-target effects by modeling the observed data across multiple gRNAs per gene. The analysis begins by mapping each gRNA to the corresponding target gene and extracting read counts from both treatment and control conditions. These counts are then normalized using median-based scaling, and log2 fold-changes are computed relative to the reference samples to quantify the effect of each gRNA. casTLE then integrates the fold-change distributions across all gRNAs to infer a gene-level effect size, confidence score, and false discovery rate (FDR). The final output is a ranked list of genes, enabling identification of biologically meaningful hits.

Bioinformatics of canonical and aberrant protein C-termini
To examine human protein isoforms, sequences were downloaded from the Ensembl database (Homo_sapiens.GRCh38.pep.all.fa, December 2022). C-terminal variants were defined as the last 20 amino acids differing among isoforms from the same gene. Isoforms differing only at the C-terminus were identified by clustering those with identical N-terminal sequences, yet varied within the final 20 residues. Cross-species canonical protein sequences were obtained from NCBI for:
• Human (Homo sapiens; GCF_000001405.39_GRCh38.p13)
• Mouse (Mus musculus; GCF_000001635.27_GRCm39)
• Fly (Drosophila melanogaster; GCF_000001215.4_Release_6_plus_ISO1_MT)
• Plant (Arabidopsis thaliana; GCF_000001735.4_TAIR10.1)
• Nematode (Caenorhabditis elegans; GCF_000002985.6_WBcel)
• Yeast (Saccharomyces cerevisiae; GCF_000146045.2_R64)
• Bacteria (Escherichia coli; GCF_000005845.2_ASM584v2)

To analyze the C-termini of canonical cytosolic proteins, we annotated protein subcellular localizations using the PANTHER Knowledgebase (http://www.pantherdb.org/). Only proteins annotated as cytosolic were included in the analysis.

Aberrant readthrough C-termini were simulated by in-frame translation of the 3’ UTR (excluding yeast and bacteria due to an absence of available data). Frameshifts arise when the reading frame shifts by +1 or –1 nucleotide, resulting in entirely altered downstream amino acid sequences. To model these events and generate frameshifted C-terminal sequences in silico, we removed the first nucleotide (for +1 frameshift) or the first two nucleotides (for –1 frameshift) from all protein-coding genes. These modified sequences were then translated to produce all possible +1 and –1 frameshift peptides. Peptides shorter than 20 residues were discarded, and redundant sequences were removed prior to amino acid composition analysis.

Principal Component Analysis and amino acid enrichment analysis
To investigate positional amino acid preferences within the terminal 150 residues of proteins, we developed a normalization method for amino acid and position that helps to account for variations in amino acid frequencies and sequence lengths. We calculated the normalized ratio (r_ij) of each of the 20 standard amino acids at every position within the last 150 residues and then divided the frequency across all positions in the protein sequences:

r_ij = (c_ij / t_j) / (C_i / T)

The numerator represents the observed frequency of the i-th amino acid (c_ij) at the j-th position, normalized by the total number of amino acids (t_j) at that same position (j-th). The denominator represents the expected frequency of the i-th amino acid (C_i) across all sequences, normalized by the total number of all amino acids (T). After dividing the observed frequency by the expected frequency, the equation yields a normalized value that indicates whether a particular amino acid is more or less likely to appear at a specific position than would be expected by chance. This approach resulted in a 20×150 matrix representing the normalized relative amino acid frequencies at each position. This matrix of ratios was then utilized to perform Principal Component Analysis (PCA) for each position using the prcomp function in R. In the PCA, the percentages shown next to each principal component indicate the proportion of total variance in the dataset explained by that component. The first principal component (PC1) captures the largest possible variance, whereas the second principal component (PC2) captures the second-largest variance, subject to being orthogonal to PC1.

To assess the continuity of hydrophobic and acidic amino acids in the C-termini of human proteins, we analyzed the last 50 residues of each canonical human protein. For each peptide, we identified and counted the consecutive stretches of hydrophobic (I, L, V, M, Y, F, W) and acidic (D, E) residues of length 2, 3, and ≥4, respectively. The total number of each stretch type was then summed across the whole peptide set to obtain the observed frequencies. To establish baseline frequencies of the stretches that are amino-acid-composition-dependent, we randomized the amino acid order within each peptide—preserving the original composition—and repeated the same stretch-counting procedure. This process was performed 10,000 times to produce distributions of baseline frequencies for each stretch type, minimizing bias from individual randomizations. Observed frequencies were then normalized against the baseline frequencies to calculate observed-to-expected ratios. Statistical significance of enrichment or depletion for each stretch type was assessed by testing whether these ratios deviated significantly from 1 using a two-sided permutation test with 100,000 permutations.

Statistical analyses
To justify the statistical significance for the PSI threshold (|ΔPSI| ≥ 1) used in our GPS screen of disease-associated nonstop mutations, we generated a background distribution of ΔPSI values by calculating PSI differences between two biological replicates. We then assessed the significance of the ±1 thresholds by evaluating the right and left tail probabilities of this distribution. The corresponding probabilities are 1.45×10–4 and 1.4×10–4, respectively.

All experiments using the random peptide library were performed as three independent biological replicates. The statistical significance of the GPS screening results and random peptide assays were determined by an unpaired two-tailed Students’ t test. Enrichment for hydrophobic and acidic stretches was evaluated using a two-sided permutation test based on deviations from the expected observed-to-expected ratio of 1. Statistical significance was defined as a P-value less than 0.05.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript „Protein C-Terminal Variations Broadly Impact Proteostasis” by Ching-Yu Chu et al investigates the question, how often aberrant C-termini are linked to protein degradation and in which proteins mechanisms like disease-associated nonstop mutations, alternative splicing, translational readthrough lead to protein stabilization. Oncoproteins and tumor suppressor proteins have been identified in which disease-relevant nonstop mutations lead to changes in protein stability. Like in other publications, the authors found that hydrophobic C-termini are targeted for degradation and the authors have identified further E3s that are involved in this process. The manuscript uncovers some interesting connections between variations in C-terminal composition of proteins and their stability. Thus, the manuscript is interesting enough to be published, yet several points have to be addressed before publication.\nMajor points:\n1. Page 3, line 13: I did not read anything about believes in the cited literature, I assume the authors wanted to write “were shown to” or something like that.\n2. Page 3 line 13-17: The sentence However, whether Bag6-RNF126… is somehow misleading, as in the literature citation “Mechanisms of readthrough mitigation reveal principles of GCN1-mediated translational quality control” by Müller et al another complex (Bag6-RNF115) was shown to be involved in degradation of a protein with a hydrophobic C-terminus. Furthermore, it was shown in budding yeast that the degradation of C-degrons with hydrophobic amino acids depends on Doa10 (MARCH6 in humans) or other E3 (e.g. Orphan quality control by an SCF ubiquitin ligase directed to pervasive C-degrons by Kong et al; Conserved degronome features governing quality control associated proteolysis by Mashahreh et al; Degradation Signals for Ubiquitin-Proteasome Dependent Cytosolic Protein Quality Control (CytoQC) in Yeast by Maurer et al), so it is not surprising that several E3s are involved in targeting degrons with hydrophobic amino acids in the C-terminus. Also, it has been shown by Hasenjäger et al (C-terminal sequence stability profiling in Saccharomyces cerevisiae reveals protective protein quality control pathways) that C-terminal extension of proteins by translational stop codon read through can generate stabilized or destabilized proteins, but that destabilization occurs more frequently.\n3. Page 3 line 17-18: The literature that was cited here for this sentence contains more than just a few examples.\n4. Results section: the results presented in the manuscript rely on protein abundance measurements that are translated in protein stability. However, this might not be true for all examples, translational effects could also take place. It would be good to show for at least important examples that protein abundance changes are caused by protein stability changes, e.g. by performing a translation shut-off experiment.\n5. Page 6 line 11-14: the experiments do not support a view that expression was enhanced, simply the protein abundance was increased. The actual mechanism by which the higher abundance was achieved was not addressed.\n6. Page 11 line 10-14: It might be difficult to delineate specific C-degron sequences from the mix of all sequences targeted by several E3s that recognize different motifs. However, focusing on the peptides that are recognized by a specific E3 might be informative and revealing specific sequences that are targeted by an E3. Thus, this approach should be followed as well by the authors.\n7. End of page 13, first paragraph of page 14: The whole analysis of the C-terminal ends is not very convincing. Without using compartment specific data sets for destabilizing amino acids and mapped on the proteome of the compartment/organelle the results are meaningless. The C-termini of proteins contain targeting signals (e.g. peroxixomal targeting by KDEL) and the C-termini of e.g. secreted proteins might not be under the same evolutionary pressure than the rest of the proteome, because they do not meet the E3s that exert the evolutionary pressure. Comparison of the proteome-wide data across different species does not reveal much. Hasenjäger et al (C-terminal sequence stability profiling in Saccharomyces cerevisiae reveals protective protein quality control pathways) showed differences in C-terminal amino acid composition of yeast proteins depending on protein localization. It is not clear how relevant the analysis in the present manuscript is for the cytosolic quality control machinery if all the proteins from other compartments are taken into consideration as well.\n8. Part “Multiple Ubiquitin Ligases Collaborate to Target Erroneous Proteins with Hydrophobic C-Termini for Degradation” page 15-18: Only 7 peptides were investigated. My guess is that with an increased number of peptides a higher complexity would be uncovered.\n9. Page 18 line 12-13: I never read about a concept like “non-canonical C-termini universally lead to degradation”. See also the comment on the Hasenjäger et al publication at the end of point 2.\n10. Figure 4 C: not all stability changes mentioned in the text (arginine, cysteine) were backed up by a statistical test.\nMinor points:\n1. Please check the spelling, in the abstract I spotted liked instead of linked.\n2. The description how Frameshift C-termini were generated (page 28 line 8-10) is not very clear. Frameshifts do not occur only at the start codon, but for the analysis only those were taken into consideration?\n3. Figure 6: the width of the columns in B or C changes, is there any meaning behind?", "reviewer_2": "In this manuscript, Chu et al. expand our understanding on how C-terminal deviations impact protein stability. Using Global Protein Stability (GPS) assay, the authors monitor protein half-lives by comparing the stability of GFP fused wild-type C-termini to aberrant readthrough variants. This approach allows them to assess the physiologically relevant effect of readthroughs on protein stability and, by extension, cellular abundance. While it was known that erroneous C-termini can destabilize proteins, this study reveals that some disease associated nonstop mutations are more stable than their wild-type counterparts. Beyond nonstop mutations, the authors also investigate the effects of alternative splicing, programed stop codon readthrough, and commonly used C-terminal tags on protein stability. Although it remains unclear how many erroneous C-termini containing proteins are recognized by the cell as abnormal and degraded, the authors successfully identify two E3 ubiquitin ligases, RNF139 and MARCH6, that selectively recognize certain hydrophobic C-termini and promote their degradation. Overall speaking, this reviewer finds the manuscript compelling, significant to the field and related fields, and believes it is suitable for publication in Nature Communications once the Major and Minor points are addressed.\nMajor point:\nThis reviewer notes a discrepancy in the length of the analyzed regions described in Figure 6 A, specifically, the use of the last 50 residues for canonical proteins, the last 30 residues for RT proteins, and the last 20 residues for frameshift proteins. As information clarifying the rationale regarding this analysis is missing in the materials and methods section, this reviewer strongly encourages the authors to clarify and rectify this inconsistency.\nMinor points:\n1. Page 6 lines 11-14. Based on the data presented in the manuscript, this reviewer is convinced that some nonstop mutations and translational readthroughs may enhance protein abundance due to a decrease in their degradation. However, that would not be equivalent to “enhancing protein expression”.\n2. Page 7 lines 7-8. This reviewer would like the authors to clarify, in either the main text or in the materials and methods section, how they determined that the viral transduction was single-copy.\n3. Page 9 lines 11-14. While there are many implications to the findings reported, this reviewer is not convinced that the data presented in the manuscript is sufficient to directly support the claim that “nonstop mutations can substantially affect cellular protein function”.\n4. Figure 3 B and C. This reviewer would find it easier to follow the figure if the panels in B were in the same order as the sequences in C or vice versa.\n5. Figure 3 B. This reviewer had a difficult time distinguishing between the pink trace and the red trace (which is under the blue trace) in AP1S2 panel.\n6. Figure 5. It is not clear to this reviewer what the percentages next to PC1 and PC2 represent.\n7. Figure S3 C legend. Typo “… in Figure 3C.” should be corrected to “… in Figure 3 D and E.”\n8. The RT sequences and the CDS sequences are misaligned in multiple figures.\n9. As the identity of the amino acid that replaces the stop codon is not important to the half-lives of the proteins, this reviewer suggests the authors to simplify their figures. For example, in Figure 2 D “ZNF438 *>L” could just contain “ZNF438”.", "reviewer_3": "Summary:\nThis manuscript, \"Protein C-Terminal Variations Broadly Impact Proteostasis,\" examines how changes in protein C-termini —arising from nonstop mutations, alternative splicing, and translational readthrough—affect protein stability. The authors use GPS-based screening, in combination with CRISPR knockouts and bioinformatic analyses, to explore how these C-terminal extensions influence protein degradation. They report that while many extensions have little effect, some can lead to stabilization or destabilization, and they identify sequence features—such as hydrophobicity and the presence of proline or cysteine—associated with these outcomes. The study also attempts to link these effects to specific ubiquitin ligases.\nOverall assessment:\nThis is a good study, based primarily on an established screening platform. However, many of the key observations—such as the destabilizing role of hydrophobic residues, the involvement of CRL-type ubiquitin ligases, and the broader principle that C-terminal sequences can encode degrons—have been reported previously. The inclusion of isoforms generated by splicing and translational readthrough and the random peptide screen add some breadth, but the conceptual insights are modest and largely descriptive.\nThe GPS assay is inherently limited by its artificial nature: it relies on overexpression and fusion to a stabilizing protein, and does not account for endogenous factors such as localization, complex formation, folding, or post-translational modifications. Moreover, the study lacks biochemical validation or independent experimental confirmation. As a result, the conclusions remain correlative and do not reach the level of mechanistic or physiological insight expected for publication in Nature Communications. The manuscript may be more appropriate for a specialized journal.\nMajor Comments:\n1. Limited conceptual novelty: Many central findings—such as the destabilizing role of hydrophobic residues at C-termini, the function of E3 ubiquitin ligases, and the idea that C-terminal extensions can encode degrons—have been described in previous literature. The current study largely confirms and modestly extends these observations, without revealing new and solid mechanistic principles.\n2. Use of a single screening approach and lack of validation: The conclusions are derived almost entirely from the GPS screen, which involves artificial overexpression and fusion to a stabilizing protein. This setup does not reflect physiological conditions. No orthogonal validation (e.g., pulse-chase assays, degradation rescue, or western blotting) is presented. Thus, the results remain observational and descriptive.\n3. Internal inconsistencies and unaddressed contradictions: The authors highlight hydrophobicity and the presence of tryptophan or cysteine as correlates of protein stability. However, when attempting to verify these associations using the authors' own data (as presented in Supplementary Table 1), clear inconsistencies emerge. For example, in cases where the aberrant isoform contains more hydrophobic residues than the WT, the expected destabilization is observed (mean ΔPSI = –1.84). In contrast, when hydrophobicity is higher in the WT and reduced in the aberrant isoform, the stabilization effect is minor (mean ΔPSI ≈ 0.41)—well below the authors' own threshold for biological relevance (|ΔPSI| ≥ 1). Similar inconsistencies are noted regarding the presence of cysteine and tryptophan, which are suggested to correlate with stability but do not consistently show expected effects. These asymmetries are neither acknowledged nor discussed in the manuscript and may suggest that other, more complex features of aberrant extensions influence stability beyond the highlighted amino acid content.\n4. Overlooking a key (negative) finding: One of the most striking observations is that the majority of C-terminal extensions do not significantly affect protein stability. This negative result is not discussed. Additionally, while the authors distinguish between isoforms derived from different mechanisms (readthrough, splicing, nonstop mutations)—a potentially novel classification—this distinction is treated descriptively. The manuscript does not explore whether these mechanisms differ in their degron content, ligase dependencies, or stability profiles.\n5. Insufficient methodological detail and lack of validation in CRISPR screens: While the manuscript is relatively easy to read, it lacks sufficient technical detail: definitions of degron features, hydrophobicity scoring, and amino acid enrichment metrics are vague; PSI thresholds are used without statistical justification; bioinformatic identification of E3 ligases is underexplained; figure legends lack clarity; and no validation is provided for the CRISPR knockouts.\n6. PCA results potentially biased by unequal sequence lengths: In Figure 6A, the PCA is based on sequences of differing lengths (50 residues for WT, 30 for readthrough, and 20 for frameshifted isoforms). This difference could dominate the observed clustering. Moreover, the PCA analysis is visually presented but not quantitatively supported. Figure S4 is inconsistent with Figure 6 regarding the included sequences.\n7. Unclear analyses in Figure 7: Panels 7C and 7E–F are not adequately described in the text or methods section. Figure 7C lacks any actual information regarding what is the presented data or how the analysis was done. Panels 7E–F appear to contradict earlier interpretations and reinforce the descriptive—and sometimes inconclusive—nature of the findings. The rationale for these analyses is not clearly articulated.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Response to Referee 1\nReviewer #1 (Remarks to the Author):\nThe manuscript „Protein C-Terminal Varia@ons Broadly Impact Proteostasis” by Ching-Yu Chu\net al inves@gates the ques@on, how oKen aberrant C-termini are linked to protein degrada@on\nand in which proteins mechanisms like disease-associated nonstop muta@ons, alterna@ve\nsplicing, transla@onal readthrough lead to protein stabiliza@on. Oncoproteins and tumor\nsuppressor proteins have been iden@fied in which disease-relevant nonstop muta@ons lead\nto changes in protein stability. Like in other publica@ons, the authors found that hydrophobic\nC-termini are targeted for degrada@on and the authors have iden@fied further E3s that are\ninvolved in this process. The manuscript uncovers some interes@ng connec@ons between\nvaria@ons in C-terminal composi@on of proteins and their stability. Thus, the manuscript is\ninteres@ng enough to be published, yet several points have to be addressed before publica@on.\nMajor points:\n1. Page 3, line 13: I did not read anything about believes in the cited literature, I assume the\nauthors wanted to write “were shown to” or something like that.\nAcknowledged. We have corrected “are typically believed to” to “were shown to” (p. 3, ln. 13).\n2. Page 3 line 13-17: The sentence However, whether Bag6-RNF126… is somehow misleading,\nas in the literature cita@on “Mechanisms of readthrough mi@ga@on reveal principles of GCN1-\nmediated transla@onal quality control” by Müller et al another complex (Bag6-RNF115) was\nshown to be involved in degrada@on of a protein with a hydrophobic C-terminus.\nWe thank the reviewer for raising this important point. In response, we have revised the\nstatement as follows: “These anomalous C-termini were shown to exhibit elevated\nhydrophobicity, which marks the resul=ng defec=ve proteins for elimina=on via Bag6\nchaperone-associated E3 ligases—namely RNF126 and RNF1153, 4.” (p. 3, ln. 13-15).\nFurthermore, it was shown in budding yeast that the degrada@on of C-degrons with\nhydrophobic amino acids depends on Doa10 (MARCH6 in humans) or other E3 (e.g. Orphan\nquality control by an SCF ubiqui@n ligase directed to pervasive C-degrons by Kong et al;\nConserved degronome features governing quality control associated proteolysis by\nMashahreh et al; Degrada@on Signals for Ubiqui@n-Proteasome Dependent Cytosolic Protein\nQuality Control (CytoQC) in Yeast by Maurer et al), so it is not surprising that several E3s are\ninvolved in targe@ng degrons with hydrophobic amino acids in the C-terminus.\nWe have carefully reviewed the papers specified by the reviewer to assess if their findings\nfrom yeast could be appropriately incorporated into our Introduc@on. Indeed, mul@ple E3\nligases—Doa10, Ltn1, SCFDas1 and San1—have been implicated in targe@ng C-degrons in\nbudding yeast. However, whether these E3 ligases specifically recognize “hydrophobic” C-\ntermini is not fully addressed in these studies. The studies by Maurer et al. and Mashahreh et\nal. do not dissect the specific features of C-degrons recognized by Doa10, Ltn1 and San1 (PMID:\n27172186, 36481666). Instead of targe@ng hydrophobic sequences, the study by Kong et al.\nsuggests that SCFDas1 recognizes ΦN C-degrons, which exhibit ‘lower’ overall hydrophobicity\ncompared to typical yeast C-degrons (PMID: 38102142). The study by Hasenjäger et al. reports\nthat isoleucine, valine/threonine, and lysine are frequently found at the –1, –2, and –4\n1\nposi@ons, respec@vely, in SCFDas1-dependent C-degrons (PMID: 37595870), indica@ng a more\ndefined sequence mo@f rather than general hydrophobicity as the key recogni@on\ndeterminants.\nGiven the uncertainty regarding the role of hydrophobicity in C-degron recogni@on by these\nyeast E3 ligases—along with documented differences between yeast and human systems,\nsuch as the absence of RNF126, RNF115, and CRL2/CRL4 family E3 ligases in yeast, and the\nlack of San1 and Das1 homologs in mammals—we believe that including yeast-specific\nfindings may introduce some confusion in our report. Consequently, in response to the\nreviewer’s comment, we have instead clarified the scope of our study by explicitly sta@ng “in\nhuman cells” in the relevant sentence (p. 3, ln. 17).\nAlso, it has been shown by Hasenjäger et al (C-terminal sequence stability profiling in\nSaccharomyces cerevisiae reveals protec@ve protein quality control pathways) that C-terminal\nextension of proteins by transla@onal stop codon read through can generate stabilized or\ndestabilized proteins, but that destabiliza@on occurs more frequently.\nAcknowledged. In response, we have removed the statement: “if a typical C-termini always\ntriggers protein degrada=on remains unclear.” (p. 3, ln. 17-19).\n3. Page 3 line 17-18: The literature that was cited here for this sentence contains more than\njust a few examples.\nIn response to the reviewer’s comment, we have removed original cita@on #7 (p. 3, ln. 17). As\nnoted, this cita@on refers to a global study, but as discussed in our Results sec@on (p. 6, ln. 4-\n14), the construct used in that study has certain limita@ons, which may affect the validity of\ntheir findings.\n4. Results sec@on: the results presented in the manuscript rely on protein abundance\nmeasurements that are translated in protein stability. However, this might not be true for all\nexamples, transla@onal effects could also take place. It would be good to show for at least\nimportant examples that protein abundance changes are caused by protein stability changes,\ne.g. by performing a transla@on shut-off experiment.\nWe appreciate the reviewer’s sugges@on and have included a new transla@on shut-off\n(cycloheximide-chase) experiment to verify that the observed changes in protein abundance\nare indeed caused by altered protein stability (new Fig. S2B).\n5. Page 6 line 11-14: the experiments do not support a view that expression was enhanced,\nsimply the protein abundance was increased. The actual mechanism by which the higher\nabundance was achieved was not addressed.\nAcknowledged. We have corrected “enhancing protein expression” to “increasing protein\nabundance” (p. 6, ln. 13-14).\n6. Page 11 line 10-14: It might be difficult to delineate specific C-degron sequences from the\nmix of all sequences targeted by several E3s that recognize different mo@fs. However, focusing\non the pep@des that are recognized by a specific E3 might be informa@ve and revealing\n2\nspecific sequences that are targeted by an E3. Thus, this approach should be followed as well\nby the authors.\nWe were surprised to find that a high propor@on of both aberrant and canonical C-terminal\nvariants affect protein stability. While mapping the complete C-terminal mo@f–E3 ligase\nnetwork is a major challenge, there is livle jus@fica@on for priori@zing any single E3 among\nthe ~600 present in the human proteome. Given that hydrophobic C-termini cons@tute the\nmajority of degrada@on-inducing signals, we focused on iden@fying their specific E3 ligases.\nOur findings reveal that mul@ple E3s—Bag6–RNF126, RNF139, and MARCH6—coopera@vely\nrecognize and target hydrophobic C-termini (Fig. 7). We will con@nue to explore addi@onal C-\nterminal mo@f–E3 interac@ons in future studies.\n7. End of page 13, first paragraph of page 14: The whole analysis of the C-terminal ends is not\nvery convincing. Without using compartment specific data sets for destabilizing amino acids\nand mapped on the proteome of the compartment/organelle the results are meaningless. The\nC-termini of proteins contain targe@ng signals (e.g. peroxixomal targe@ng by KDEL) and the C-\ntermini of e.g. secreted proteins might not be under the same evolu@onary pressure than the\nrest of the proteome, because they do not meet the E3s that exert the evolu@onary pressure.\nComparison of the proteome-wide data across different species does not reveal much.\nHasenjäger et al (C-terminal sequence stability profiling in Saccharomyces cerevisiae reveals\nprotec@ve protein quality control pathways) showed differences in C-terminal amino acid\ncomposi@on of yeast proteins depending on protein localiza@on. It is not clear how relevant\nthe analysis in the present manuscript is for the cytosolic quality control machinery if all the\nproteins from other compartments are taken into considera@on as well.\nWe thank the reviewer for raising this important point. In response, we have re-performed\nthe analysis solely using the “cytosolic protein” dataset and revised the text accordingly\n(revised Fig. 5A-5F, p. 14, ln. 10-13; p. 29, ln. 7-9). The results obtained using the cytosolic\nprotein dataset are consistent with those from the total canonical protein dataset.\nAddi@onally, we have added a new statement to clarify the underlying ra@onale: “We focused\nour analysis on canonical cytosolic proteins, as proteins localized to different compartments\nor organelles are likely subject to dis=nct evolu=onary pressures (PMID: 33469951, 37595870).\nFor example, secreted proteins may not encounter cytosol-localized E3 ligases.” (p. 13, ln. 9-\n14).\nIn line with the reviewer’s comment, our previous work demonstrated that deple@on of the\nextreme C-terminal glycine (Gly⁻¹) is influenced by protein localiza@on in humans (see Fig. 4A\nin EMBO J. e105846). Specifically, Gly⁻¹ is rare among cytosolic and nuclear proteins, as well\nas for membrane proteins with C-termini facing the cytosol (inward), but not among secreted\nproteins or membrane proteins whose C-termini face the extracellular space or ER lumen\n(outward). These findings support that proteins localized to different cellular compartments\nor organelles are subject to dis@nct evolu@onary pressures.\n8. Part “Mul@ple Ubiqui@n Ligases Collaborate to Target Erroneous Proteins with Hydrophobic\nC-Termini for Degrada@on” page 15-18: Only 7 pep@des were inves@gated. My guess is that\nwith an increased number of pep@des a higher complexity would be uncovered.\nWe agree with the reviewer’s comment that analyzing a greater number of pep@des would\nlikely reveal increased complexity. Although our study examined only seven pep@des, we\n3\nobserved that the stability of two pep@des was unaffected by individual knockdown of any of\nthe three E3 ligases we tested. This outcome indicates that addi@onal E3 ubiqui@n ligases\nremain to be iden@fied. As noted in the manuscript: “Notably, knockout of Bag6/RNF126,\nRNF139, or MARCH6 failed to prevent degrada=on of all hydrophobic variants, such as\nLAMTOR5-RT and ARHGEF35-RT, implying either the involvement of yet uniden=fied ubiqui=n\nligases or func=onal redundancy among known ones (Fig. 7D).” (p. 17, ln. 3-6)\n9. Page 18 line 12-13: I never read about a concept like “non-canonical C-termini universally\nlead to degrada@on”. See also the comment on the Hasenjäger et al publica@on at the end of\npoint 2.\nAcknowledged. We have removed the statement: “non-canonical C-termini universally lead to\ndegrada=on”. The revised next now reads: “Contrary to a previous study (PMID: 39448564),\nour findings demonstrate that disease-associated nonstop muta=ons can either enhance or\nreduce protein stability.” (p. 18, ln. 16-17)\n10. Figure 4 C: not all stability changes men@oned in the text (arginine, cysteine) were backed\nup by a sta@s@cal test.\nAcknowledged. Sta@s@cal analyses for all amino acids men@oned in our text have now been\nincluded (revised Fig. 4C).\nMinor points:\n1. Please check the spelling, in the abstract I spoved liked instead of linked.\nAcknowledged. We have corrected “liked” to “linked” (p. 2, ln. 4).\n2. The descrip@on how FrameshiK C-termini were generated (page 28 line 8-10) is not very\nclear. FrameshiKs do not occur only at the start codon, but for the analysis only those were\ntaken into considera@on?\nRather than limi@ng our analysis to frameshiKs occurring at the start codon, we have\nconsidered frameshiK events at all possible posi@ons within the coding region. In response to\nthe reviewer’s comment, we have revised the descrip@on of our method to improve clarity\nfor readers (p.29, ln. 11-18).\nFrameshiKs arise when the reading frame shiKs by +1 or –1 nucleo@de, resul@ng in en@rely\naltered downstream amino acid sequences. To model these events and generate frameshiKed\nC-terminal sequences in silico, we removed the first nucleo@de (for +1 frameshiK) or the first\ntwo nucleo@des (for –1 frameshiK) from all protein-coding genes. These modified sequences\nwere then translated to produce “all possible” +1 and –1 frameshiK pep@des. Pep@des shorter\nthan 20 residues were discarded, and redundant sequences were removed prior to the amino\nacid composi@on analysis shown in Fig. 6A–6C.\n3. Figure 6: the width of the columns in B or C changes, is there any meaning behind?\nApologies for this oversight. The varia@on in column widths in Figures 6B and 6C was due to\nforma}ng errors during the conversion from PowerPoint to PDF. We have reprocessed the\nfigures to ensure consistent column widths (revised Figs. 6B and 6C).\nReviewer #2 (Remarks to the Author)\nIn this manuscript, Chu et al. expand our understanding on how C-terminal devia@ons impact\nprotein stability. Using Global Protein Stability (GPS) assay, the authors monitor protein half-\nlives by comparing the stability of GFP fused wild-type C-termini to aberrant readthrough\nvariants. This approach allows them to assess the physiologically relevant effect of\nreadthroughs on protein stability and, by extension, cellular abundance. While it was known\nthat erroneous C-termini can destabilize proteins, this study reveals that some disease\nassociated nonstop muta@ons are more stable than their wild-type counterparts. Beyond\nnonstop muta@ons, the authors also inves@gate the effects of alterna@ve splicing, programed\nstop codon readthrough, and commonly used C-terminal tags on protein stability. Although it\nremains unclear how many erroneous C-termini containing proteins are recognized by the cell\nas abnormal and degraded, the authors successfully iden@fy two E3 ubiqui@n ligases, RNF139\nand MARCH6, that selec@vely recognize certain hydrophobic C-termini and promote their\ndegrada@on. Overall speaking, this reviewer finds the manuscript compelling, significant to\nthe field and related fields, and believes it is suitable for publica@on in Nature\nCommunica@ons once the Major and Minor points are addressed.\nMajor point:\nThis reviewer notes a discrepancy in the length of the analyzed regions described in Figure 6\nA, specifically, the use of the last 50 residues for canonical proteins, the last 30 residues for RT\nproteins, and the last 20 residues for frameshiK proteins. As informa@on clarifying the\nra@onale regarding this analysis is missing in the materials and methods sec@on, this reviewer\nstrongly encourages the authors to clarify and rec@fy this inconsistency.\nWe appreciate the reviewer’s though~ul comment. In response, we have re-analyzed all\ndatasets using the final 20 residues to ensure consistency across comparisons (revised Fig. 6A).\nIn our ini@al analysis, we focused on the last 50 residues of canonical proteins, as this more\naccurately captures trends in amino acid composi@on near canonical C-termini. However,\nmost frameshiK and readthrough pep@des are rela@vely short due to the proximity of\ndownstream stop codons. Applying a uniform 50-residue threshold across all datasets would\nhave retained only 16.3%, 12.5%, and 8.05% of readthrough, frameshiK +1, and frameshiK –\noriginally applied the different minimum length thresholds for each dataset.\nMinor points:\n1. Page 6 lines 11-14. Based on the data presented in the manuscript, this reviewer is\nconvinced that some nonstop muta@ons and transla@onal readthroughs may enhance protein\nabundance due to a decrease in their degrada@on. However, that would not be equivalent to\n“enhancing protein expression”.\nAcknowledged. We have corrected “enhancing protein expression” to “increasing protein\nabundance” (p. 6, ln. 13-14).\n5\n2. Page 7 lines 7-8. This reviewer would like the authors to clarify, in either the main text or in\nthe materials and methods sec@on, how they determined that the viral transduc@on was\nsingle-copy.\nAcknowledged. We have added a detailed explana@on to clarify how single-copy viral\ntransduc@on was achieved in the revised Materials and Methods sec@on (p. 25, ln. 17-18).\nTo ensure that each cell was infected by only one viral par@cle, we performed len@viral\ntransduc@on at a low mul@plicity of infec@on (MOI) of 0.05, corresponding to a cell-to-virus\nra@o of approximately 200:1. Based on the Poisson distribu@on, this se}ng results in 99.98%\nof infected cells carrying a single viral integrant. Following transduc@on, we applied puromycin\nselec@on to eliminate uninfected cells prior to FACS analysis.\n3. Page 9 lines 11-14. While there are many implica@ons to the findings reported, this reviewer\nis not convinced that the data presented in the manuscript is sufficient to directly support the\nclaim that “nonstop muta@ons can substan@ally affect cellular protein func@on”.\nAcknowledged. We have revised the statement from “nonstop muta=ons can substan=ally\naffect cellular protein func=on” to “nonstop muta=ons may substan=ally affect cellular\nprocesses by altering the abundance of the respec=ve proteins.” (p. 9, ln. 13-14).\n4. Figure 3 B and C. This reviewer would find it easier to follow the figure if the panels in B\nwere in the same order as the sequences in C or vice versa.\nWe thank the reviewer for carefully examining our figures. We have now aligned the panel\norder in Fig. 3B with the sequence order in Fig. 3C for consistency (revised Figs. 3B and 3C).\n5. Figure 3 B. This reviewer had a difficult @me dis@nguishing between the pink trace and the\nred trace (which is under the blue trace) in AP1S2 panel.\nAcknowledged. To improve visibility, we have changed the color of the stability histogram for\nisoform 5 of AS1S2 from pink to orange (revised AS1S2 panel of Fig. 3B).\n6. Figure 5. It is not clear to this reviewer what the percentages next to PC1 and PC2 represent.\nTo improve clarity for readers, we have now included an explana@on of the percentages next\nto PC1 and PC2 in the revised Results and Materials and Methods sec@ons (p. 13, ln. 17-19; p.\n30, ln. 17-18; p. 31, ln. 1-3).\nIn the principal component analysis (PCA), the percentages shown next to each principal\ncomponent (e.g., PC1 and PC2) indicate the propor@on of total variance in the dataset\nexplained by that component. The first principal component (PC1) captures the largest\npossible variance, whereas the second principal component (PC2) captures the second-largest\nvariance, subject to being orthogonal to PC1.\n7. Figure S3 C legend. Typo “… in Figure 3C.” should be corrected to “… in Figure 3 D and E.”\nWe thank the reviewer for carefully examining our figures. We have now corrected “3C” to\n“3D and 3E” (p. 47, ln. 8).\n8. The RT sequences and the CDS sequences are misaligned in mul@ple figures.\ncontaining CDS sequences and now corrected any misalignments (Figs. 2C, 2E, 3C, 6D, S2C,\nS3C).\n9. As the iden@ty of the amino acid that replaces the stop codon is not important to the half-\nlives of the proteins, this reviewer suggests the authors to simplify their figures. For example,\nin Figure 2 D “ZNF438 *>L” could just contain “ZNF438”.\nFor short readthroughs, i.e., where the downstream stop codon within the 3ʹUTR is located\nclose to the nonstop muta@on, we are uncertain if the iden@ty of the amino acid replacing the\noriginal stop codon affects protein half-life. Therefore, we believe that labeling the muta@on\ntype is a more appropriate approach and consequently respec~ully request to retain our\nnota@on.\nResponse to Referee 3\nReviewer #3 (Remarks to the Author):\nSummary:\nThis manuscript, \"Protein C-Terminal Varia@ons Broadly Impact Proteostasis,\" examines how\nchanges in protein C-termini—arising from nonstop muta@ons, alterna@ve splicing, and\ntransla@onal readthrough—affect protein stability. The authors use GPS-based screening, in\ncombina@on with CRISPR knockouts and bioinforma@c analyses, to explore how these C-\nterminal extensions influence protein degrada@on. They report that while many extensions\nhave livle effect, some can lead to stabiliza@on or destabiliza@on, and they iden@fy sequence\nfeatures—such as hydrophobicity and the presence of proline or cysteine—associated with\nthese outcomes. The study also avempts to link these effects to specific ubiqui@n ligases.\nOverall assessment:\nThis is a good study, based primarily on an established screening pla~orm. However, many of\nthe key observa@ons—such as the destabilizing role of hydrophobic residues, the involvement\nof CRL-type ubiqui@n ligases, and the broader principle that C-terminal sequences can encode\ndegrons—have been reported previously. The inclusion of isoforms generated by splicing and\ntransla@onal readthrough and the random pep@de screen add some breadth, but the\nconceptual insights are modest and largely descrip@ve.\nThe GPS assay is inherently limited by its ar@ficial nature: it relies on overexpression and fusion\nto a stabilizing protein, and does not account for endogenous factors such as localiza@on,\ncomplex forma@on, folding, or post-transla@onal modifica@ons. Moreover, the study lacks\nbiochemical valida@on or independent experimental confirma@on. As a result, the conclusions\nremain correla@ve and do not reach the level of mechanis@c or physiological insight expected\nfor publica@on in Nature Communica@ons. The manuscript may be more appropriate for a\nspecialized journal.\nMajor Comments:\n1. Limited conceptual novelty: Many central findings—such as the destabilizing role of\nhydrophobic residues at C-termini, the func@on of E3 ubiqui@n ligases, and the idea that C-\n7\nterminal extensions can encode degrons—have been described in previous literature. The\ncurrent study largely confirms and modestly extends these observa@ons, without revealing\nnew and solid mechanis@c principles.\nWe respec~ully disagree with the reviewer’s assessment that our study lacks conceptual\nnovelty. Our work provides several significant and original contribu@ons, as outlined below:\n1. We present the first systema@c analysis of over 3,000 disease-associated nonstop\nmuta@ons to evaluate their impact on protein stability. Prior to our study, only a few\nindividual cases had been reported (PMID: 32719554, 26442586), all showing protein\ndestabiliza@on. Although a related study by Ghosh et al. (PMID: 39448564) inves@gated\nsimilar ques@ons, their conclusions are likely affected by key limita@ons in experimental\ndesign, which we discuss in detail in our manuscript (p. 6, ln. 1-14).\n2. Challenging the widely held view that nonstop muta@ons predominantly lead to protein\ndegrada@on, our findings demonstrate that such muta@ons can also stabilize proteins. We\nhave experimentally confirmed stabiliza@on of several oncoproteins (FOXA1, CCND2, SNCG,\nHEY1, CPNE9) and degrada@on of numerous tumor suppressors (MAX, PAD23B, LIMD1,\nCTCF, AHNAK, DAB2, RBM4, BCL2L11, DUSP9). In addi@on, we have validated the\ndegrada@on of NHP2, MOCS2, and FHL1 resul@ng from gene@c disease-associated nonstop\nmuta@ons. These findings are enMrely novel.\n3. We have performed the first comprehensive assessment of how natural C-terminal\nvaria@on—arising from alterna@ve splicing and programmed readthrough—affects protein\nhalf-life. Our findings reveal that up to 60% of tested C-terminal variants significantly alter\nprotein stability, revealing that C-degron pathways func@on more broadly than previously\nrecognized. This aspect of C-terminal regula@on has been largely underexplored in prior\nwork.\n4. We extend current understanding by showing that it is not only amino acid enrichment,\nbut also amino acid spa@al arrangement, that influences protein stability. Specifically,\ncon@nuous stretches of par@cular residues exert a stronger effect than the same residues\ndispersed throughout the sequence.\n5. Contrary to prior models proposing a general increase in hydrophobicity as the main driver\nof aberrant protein degrada@on, our findings show that enrichment for cysteine and\ntryptophan—and deple=on of aspartate and glutamate—are more cri@cal determinants in\npromo@ng selec@ve clearance of abnormal proteins. This provides a more mechanis@c and\nnuanced framework for understanding how proteome integrity is maintained.\n6. We have iden@fied a set of E3 ligases—including Bag6-RNF126, MARCH6, and RNF139—\nthat cooperate in targe@ng proteins with hydrophobic C-termini in human cells. Notably,\nwe show that degrada@on is not solely dictated by hydrophobicity, but that it also depends\non the specific sequence context and residue arrangement. These parameters influence\nboth degrada@on efficiency and selec@on of the responsible E3 ligase. This outcome\nrepresents a novel and mechanis@c advance in our understanding of hydrophobic C-degron\nrecogni@on.\n2. Use of a single screening approach and lack of valida@on: The conclusions are derived\nalmost en@rely from the GPS screen, which involves ar@ficial overexpression and fusion to a\nstabilizing protein. This setup does not reflect physiological condi@ons. No orthogonal\n8\nvalida@on (e.g., pulse-chase assays, degrada@on rescue, or western blo}ng) is presented.\nThus, the results remain observa@onal and descrip@ve.\nAcknowledged. We have included a new transla@on shut-off (cycloheximide-chase)\nexperiment to verify that the observed changes in protein abundance in the GPS assays are\nindeed caused by altered protein stability (new Fig. S2B).\n3. Internal inconsistencies and unaddressed contradic@ons: The authors highlight\nhydrophobicity and the presence of tryptophan or cysteine as correlates of protein stability.\nHowever, when avemp@ng to verify these associa@ons using the authors' own data (as\npresented in Supplementary Table 1), clear inconsistencies emerge. For example, in cases\nwhere the aberrant isoform contains more hydrophobic residues than the WT, the expected\ndestabiliza@on is observed (mean ΔPSI = –1.84). In contrast, when hydrophobicity is higher in\nthe WT and reduced in the aberrant isoform, the stabiliza@on effect is minor (mean ΔPSI ≈\n0.41)—well below the authors' own threshold for biological relevance (|ΔPSI| ≥ 1). Similar\ninconsistencies are noted regarding the presence of cysteine and tryptophan, which are\nsuggested to correlate with stability but do not consistently show expected effects. These\nasymmetries are neither acknowledged nor discussed in the manuscript and may suggest that\nother, more complex features of aberrant extensions influence stability beyond the\nhighlighted amino acid content.\nIndeed, beyond hydrophobicity and the presence of tryptophan or cysteine, more complex\nfeatures at the protein C-terminus influence stability. As demonstrated by our random\npeptide assays (Fig. 4C), additional factors—such as the presence of small terminal amino\nacids (e.g., glycine, alanine) or an increased frequency of arginine residues—also promote\ndegradation. In contrast, enrichment of acidic residues (aspartic acid, glutamic acid)\ncontributes to stabilization. To validate the role of cysteine and tryptophan in promoting\ndegradation, we have conducted an independent mutagenesis experiment substituting these\nresidues with alanine, which confirmed their functional contributions (Fig. 6F).\nThe spatial arrangement of amino acids also plays a critical role. Even when the total number\nof specific residues remains the same, clustering these residues enhances their synergistic\neffect on degradation/stabilization (Fig. 4D). Furthermore, sequences with identical amino\nacid compositions can exhibit markedly different degradation efficiencies depending on\nresidue order and local sequence context. For example, TN-H2 (LRKTNLYICF) was more\ndestabilizing than its scrambled counterpart TN-S2 (LRKTNFCIYL), despite having the same\namino acid content (Fig. 7F).\nTogether, these findings underscore that multiple C-terminal features act in combination to\ninfluence protein half-life. Therefore, it is not appropriate to correlate ΔPSI values with any\nsingle attribute—such as hydrophobicity, or the presence of cysteine or tryptophan—\nwithout considering the broader sequence context.\nWe respectfully disagree with the reviewer’s assertion that this complexity was neither\nacknowledged nor discussed in the manuscript. As detailed in the text:\n• p. 12, ln. 12-15: “The presence of small terminal amino acids (Gly, Ala), or increased\noverall frequencies of Arg, Cys, or hydrophobic residues (Val, Ile, Leu, Met, Phe, Tyr, Trp),\ntended to promote degradation. In contrast, enrichment of acidic residues (Asp, Glu) was\nassociated with increased stability (Fig. 4C).”\n9\n• p. 12, ln. 18-19; p. 13, ln. 1-2: “Most notably, the arrangement of amino acids also played\na crucial role in determining protein half-life. Even when the total number of specific\nresidues was held constant, clustering (rather than dispersing) them prompted a\npronounced effect.”\n• p. 18, ln. 6-10: “… degradation is not dictated solely by the presence of hydrophobic\nresidues, but also their precise arrangement and the surrounding sequence context,\nrepresenting factors that determine both degradation efficiency and the identity of the\nresponsible degradation machinery.”\n• P. 21 ln. 8-11: “We demonstrate that permuting hydrophobic residues or shuffling\nadjacent hydrophilic residues not only alters the degree of degradation but also shifts E3\nligase specificity. This outcome indicates that recognition of hydrophobic protein regions\nis more selective and dependent on sequence context than previously appreciated.”\nThese sections collectively acknowledge and address the multifactorial nature of C-terminal\ndegradation signals.\n4. Overlooking a key (nega@ve) finding: One of the most striking observa@ons is that the\nmajority of C-terminal extensions do not significantly affect protein stability. This nega@ve\nresult is not discussed. Addi@onally, while the authors dis@nguish between isoforms derived\nfrom different mechanisms (readthrough, splicing, nonstop muta@ons)—a poten@ally novel\nclassifica@on—this dis@nc@on is treated descrip@vely. The manuscript does not explore\nwhether these mechanisms differ in their degron content, ligase dependencies, or stability\nprofiles.\nContrary to the reviewer’s comment, one of the most striking findings of our study is that the\nmajority of C-terminal extensions do, in fact, affect protein stability. Accordingly, we focused\nour analysis on these posi@ve results.\nWe were surprised to discover that a substan@al propor@on of both aberrant and canonical C-\nterminal variants influence protein stability—par@cularly given that only a few specific\nexamples had previously been reported. Prior to our work, changes in protein stability induced\nby disease-associated nonstop muta@ons had been documented in only a limited number of\ncases (PMID: 32719554, 26442586), all of which resulted in protein destabiliza@on. Moreover,\nexis@ng research on C-terminal-dependent protein degrada@on has primarily focused on its\nrole in protein quality control. To date, only three genes—SRY, MAX, and SMN2—have been\nshown to produce protein isoforms via alterna@ve splicing that differ in stability due to C-\nterminal varia@on (PMID: 33004521, 33636164, 20194437).\nOur findings challenge this limited view, demonstra@ng that such effects are far more common\nthan generally accepted. Specifically, we found that up to 40% of more than 3,000 disease-\nrelevant nonstop muta@ons significantly affect protein half-life, either by stabilizing or\ndestabilizing the protein (Fig. 1G). To our knowledge, ours is the first study to report that\nnonstop muta@ons can lead to protein stabiliza@on.\nFurthermore, we provide the first systema@c inves@ga@on of the impact of canonical C-\nterminal varia@on—arising from alterna@ve splicing and programmed readthrough—on\nprotein stability. We found that up to 60% of the examined C-terminal variants significantly\nalter protein half-life (Fig. 3), underscoring a broader regulatory role of protein C-termini in\ndetermining the stability of canonical proteins.\nincomplete. The field con@nues to pursue gene@c and biochemical screens, as well as\nfunc@onal assays, to address these knowledge gaps. As such, it is not yet possible to reliably\ndescribe or predict differences in degron content, E3 ligase dependency, or stability profiles\namong C-terminal variants resul@ng from readthrough, splicing, or nonstop muta@ons. We\nare commived to addressing these ques@ons in future studies.\n5. Insufficient methodological detail and lack of validation in CRISPR screens: While the\nmanuscript is rela@vely easy to read, it lacks sufficient technical detail: defini@ons of degron\nfeatures, hydrophobicity scoring, and amino acid enrichment metrics are vague; PSI\nthresholds are used without sta@s@cal jus@fica@on; bioinforma@c iden@fica@on of E3 ligases\nis underexplained; figure legends lack clarity; and no valida@on is provided for the CRISPR\nknockouts.\nValida@on of the CRISPR screens was already presented in Fig. 7D of the submived manuscript.\nSpecifically, we used two different sgRNAs to knockout each E3 ligase to confirm that RGS18-\nRT is targeted by MARCH6, and that UBA5-RT and RAB18-RT are recognized by RNF139.\nIn response to the reviewer’s comment, we have added methodological details on the amino\nacid enrichment matrix and CRISPR screens in the revised Materials and Methods sec@on (p.\n27, ln. 8; p. 28, ln. 1-10). Furthermore, we have included a new sta@s@cal jus@fica@on for the\nPSI threshold (|ΔPSI| ≥ 1) in the Materials and Methods sec@on (p. 31, ln. 18-19; p. 32, ln. 1-\n3).\nWe are unclear as to what the reviewer means by \"defini@ons of degron features” and\n“hydrophobicity scoring\". We must clarify that hydrophobicity scoring was not employed in\nthe current study. As already noted in the submived manuscript (p. 12, ln. 13), we define\nhydrophobic residues as Val, Ile, Leu, Met, Phe, Tyr, and Trp. Based on our random pep@de\nassays, we observed that the presence of small terminal amino acids (glycine, alanine),\nas well as increased frequencies of arginine, cysteine, or hydrophobic residues (valine, isoleucine,\nleucine, methionine, phenylalanine, tyrosine, tryptophan), generally promoted degrada@on.\nIn contrast, enrichment of acidic residues (aspar@c acid, glutamic acid) was associated with\nincreased stability (Fig. 4C).\n6. PCA results poten@ally biased by unequal sequence lengths: In Figure 6A, the PCA is based\non sequences of differing lengths (50 residues for WT, 30 for readthrough, and 20 for\nframeshiKed isoforms). This difference could dominate the observed clustering. Moreover,\nthe PCA analysis is visually presented but not quan@ta@vely supported. Figure S4 is\ninconsistent with Figure 6 regarding the included sequences.\nWe appreciate the reviewer’s though~ul comment. In response, we have re-analyzed all\ndatasets using the final 20 residues to ensure consistency across comparisons (revised Fig. 6A\nand S4D [original S4C]). In addi@on, we have added loading plots for the PCA analysis shown\nin Fig. 6A to quan@ta@vely illustrate the contribu@on of each of the 20 amino acids to the\nprincipal components (new Fig. S4C).\nIn our ini@al analysis, we focused on the last 50 residues of canonical proteins, as this more\naccurately reflects amino acid composi@on paverns near canonical C-termini. However,\nmost frameshiK and readthrough pep@des are rela@vely short, due to the proximity of\ndownstream stop codons. Applying the same 50-residue threshold across all datasets would\nhave resulted\n11\nin only 16.3%, 12.5%, and 8.05% of readthrough, frameshiK +1, and frameshiK –1 C-terminal\nsequences being retained, respec@vely. To ensure adequate representa@on, we had therefore\noriginally applied different minimum length thresholds across datasets.\n7. Unclear analyses in Figure 7: Panels 7C and 7E–F are not adequately described in the text\nor methods sec@on. Figure 7C lacks any actual informa@on regarding what is the presented\ndata or how the analysis was done. Panels 7E–F appear to contradict earlier interpreta@ons\nand reinforce the descrip@ve—and some@mes inconclusive—nature of the findings. The\nra@onale for these analyses is not clearly ar@culated.\nFig. 7C: We have added methodological details regarding the CRISPR screen and casTLE\nanalysis to the revised figure legend (p. 45, ln. 12-15) and the Materials and Methods sec@on\n(p. 27, ln. 8; p. 28, ln. 1-10). To calculate the casTLE score—which quan@fies both the\nconfidence and effect size of each gene iden@fied in the screen—we followed the protocol\ndescribed by Morgens et al. (PMID: 37000620).\nFig. 7E-F: We have revised our statement to clarify the ra@onale for the analysis: “Since\nmul=ple E3 ligases target hydrophobic C-termini, we adopted RGS18-RT as a model to dissect\nhow the arrangement of hydrophobic residues and local sequence context influence\ndegrada=on.” (p. 17, ln. 7-9).\nWe respec~ully disagree with the reviewer’s assessment that the results in panels 7E–F\ncontradict our earlier interpreta@on. Our findings demonstrate that mul@ple C-terminal\nfeatures act in combina@on to influence protein half-life. For further clarifica@on, please refer\nto our detailed response to this reviewer’s comment #3.\nResponse to Referee 4\nReviewer #4 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This\nis part of the Nature Communica@ons ini=a=ve to facilitate training in peer review and to\nprovide appropriate recogni=on for Early Career Researchers who co-review manuscripts.\nReply: Thank you for your contribu@ons.\n12"}, {"round": 2, "reviewer_comments": {"reviewer_1": "Most of my concerns have been addressed satisfactorily. However, two points remain that should be addressed prior to publication:\n1. Original comment: 3. Page 3 line 17-18: The literature that was cited here for this sentence contains more than just a few examples.\nReply: In response to the reviewer’s comment, we have removed original citation #7 (p. 3, ln. 17). As noted, this citation refers to a global study, but as discussed in our Results section (p. 6, ln. 4-14), the construct used in that study has certain limitations, which may affect the validity of their findings.\nMy remaining concern: Removing literature citations that are not fitting to the authors narrative is somehow dubious. The published literature should be added to introduction, limitations within the cited literature could be addressed in the introduction as well.\n2. Original comment: 4. Results section: the results presented in the manuscript rely on protein abundance measurements that are translated in protein stability. However, this might not be true for all examples, translational effects could also take place. It would be good to show for at least important examples that protein abundance changes are caused by protein stability changes, e.g. by performing a translation shut-off experiment.\nReply: We appreciate the reviewer’s suggestion and have included a new translation shut-off (cycloheximide-chase) experiment to verify that the observed changes in protein abundance are indeed caused by altered protein stability (new Fig. S2B).\nMy remaining concern: Following sentence is used to refer to the new data (Fig S2B): In addition to known motifs, we discovered novel C-terminal sequences that influence protein stability and validated their effects using GPS assays and cycloheximide-chase experiments in the context of the respective native protein backbones (Figs. 2E, 2F, S1C, S2B).\nWhat does a native protein backbone actually mean if a GFP-tagged variant has been used? Either the protein is in native state (untagged) or modified (e.g. tagged with GFP). The concept of a native protein backbone modified with GFP is unknown to me.", "reviewer_2": "The authors have addressed all the concerns raised by this reviewer. This revised manuscript is ready for publication.", "reviewer_3": "I appreciate the authors’ detailed responses to my comments and the additional data provided. However, after carefully evaluating the revised manuscript and rebuttal, I must emphasize that my original concerns remain largely unresolved.\nConceptual novelty: The central claims—that nonstop mutations can stabilize or destabilize proteins and that residue clustering or enrichment patterns contribute to these effects—remain incremental extensions of prior work. As noted in my initial review, the destabilizing role of hydrophobic residues, the involvement of CRL-type ligases, and the existence of C-terminal degrons have all been well documented. The new analyses (e.g., cysteine/tryptophan enrichment, residue clustering) add breadth but not fundamentally new mechanistic concepts.\nAssay limitations: The GPS system is still the backbone of the study. While the authors added cycloheximide-chase assays and selected full-length constructs, the overwhelming majority of data remain based on GFP–peptide fusions in HEK293T cells. These artificial assays cannot fully capture endogenous factors such as folding, localization, and complex formation, and therefore the conclusions remain correlative.\nMechanistic depth: Despite the authors explanations attempts in the rebuttable, in my view the manuscript still does not convincingly resolve the inconsistencies in its own dataset, where proposed rules (hydrophobicity, Cys/Trp enrichment) are not consistently predictive. While the authors acknowledge complexity, but the result is still primarily descriptive.\nNeutral majority: Despite the authors’ response, it remains clear that a large proportion of extensions have no significant effect. This important negative result is not sufficiently discussed, and the emphasis continues to be on a minority of destabilizing or stabilizing cases, potentially overstating generality.\nComparison to prior work: In contrast, Ghosh et al. (Nat. Commun. 2024) validated nonstop mutations in endogenous models (e.g., CRISPR-edited PTEN), provided mechanistic links to proteasomal degradation, and explored evolutionary constraints on C-terminal amino acid usage. That study established mechanistic insight, whereas the present manuscript remains largely a descriptive catalog of correlations.\nIn summary, while the study is carefully executed and provides a valuable dataset, the rebuttal does not fully address the issues of novelty, reliance mostly on artificial assays, and limited mechanistic depth. I therefore maintain my original concerns.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Response to Referee 1\nReviewer #1 (Remarks to the Author):\nMost of my concerns have been addressed sa=sfactorily. However, two points remain that\nshould be addressed prior to publica=on:\nReply: We thank the reviewer for their careful review and valuable sugges=ons. The paper has\nbeen revised accordingly.\n1. Original comment: 3. Page 3 line 17-18: The literature that was cited here for this sentence\ncontains more than just a few examples.\nReply: In response to the reviewer’s comment, we have removed original cita=on #7 (p. 3, ln.\n17). As noted, this cita=on refers to a global study but, as discussed in our Results sec=on (p.\n6, ln. 4-14), the construct used in that study has certain limita=ons, which may affect the\nvalidity of their findings.\nMy remaining concern: Removing literature cita=ons that are not fiTng to the authors\nnarra=ve is somehow dubious. The published literature should be added to introduc=on,\nlimita=ons within the cited literature could be addressed in the introduc=on as well.\nReply: In response to the reviewer’s comment, we now cite the relevant literature in the\nrevised Introduc=on. Specifically, we have added the following sentence: “A recent study\nsystema/cally inves/gated the impact of disease-relevant nonstop muta/ons7. However, that\nstudy overlooked the poten/al influence of canonical C-termini on protein half-life, which may\naffect the validity of the authors’ conclusions.” (p.4, ln.1-4).\n2. Original comment: 4. Results sec=on: the results presented in the manuscript rely on\nprotein abundance measurements that are translated in protein stability. However, this might\nnot be true for all examples, transla=onal effects could also take place. It would be good to\nshow for at least important examples that protein abundance changes are caused by protein\nstability changes, e.g. by performing a transla=on shut-off experiment.\nReply: We appreciate the reviewer’s sugges=on and have included a new transla=on shut-off\n(cycloheximide-chase) experiment to verify that the observed changes in protein abundance\nare indeed caused by altered protein stability (new Fig. S2B).\nMy remaining concern: Following sentence is used to refer to the new data (Fig S2B): In\naddi=on to known mo=fs, we discovered novel C-terminal sequences that influence protein\nstability and validated their effects using GPS assays and cycloheximide-chase experiments in\nthe context of the respec=ve na=ve protein backbones (Figs. 2E, 2F, S1C, S2B).\nWhat does a na=ve protein backbone actually mean if a GFP-tagged variant has been used?\nEither the protein is in na=ve state (untagged) or modified (e.g. tagged with GFP). The concept\nof a na=ve protein backbone modified with GFP is unknown to me.\nReply: We appreciate the reviewer’s insigh_ul comment. The transla=on shut-off\n(cycloheximide-chase) experiment shown in original Fig. S2B was conducted using GFP-tagged\nfull-length proteins.\nabundance are due to altera=ons in protein stability, we decided to perform a more thorough\nvalida=on by using a smaller epitope tag (instead of the GFP tag) and examining addi=onal\nnonstop muta=ons. Consequently, we conducted new cycloheximide-chase experiments for\nseven nonstop muta=ons (we previously only analyzed two), u=lizing FLAG-tagged full-length\nwild-type and readthrough proteins. The original data has been replaced with these new\nresults, which are now presented in revised Fig. S1D (instead of Fig. S2B, as the new loca=on\nis more appropriate) and Fig. S2C. We have also clearly stated in the text that FLAG-tagged\nfull-length proteins were used in these cycloheximide-chase experiments (p.9, ln.13-14).\nResponse to Referee 2\nReviewer #2 (Remarks to the Author):\nThe authors have addressed all the concerns raised by this reviewer. This revised manuscript\nis ready for publica=on.\nReply: We thank the reviewer for their careful review and valuable sugges=ons.\nResponse to Referee 3\nReviewer #3 (Remarks to the Author)：\nI appreciate the authors’ detailed responses to my comments and the addi=onal data\nprovided. However, acer carefully evalua=ng the revised manuscript and rebu`al, I must\nemphasize that my original concerns remain largely unresolved.\nConceptual novelty: The central claims—that nonstop muta=ons can stabilize or destabilize\nproteins and that residue clustering or enrichment pa`erns contribute to these effects—\nremain incremental extensions of prior work. As noted in my ini=al review, the destabilizing\nrole of hydrophobic residues, the involvement of CRL-type ligases, and the existence of C-\nterminal degrons have all been well documented. The new analyses (e.g., cysteine/tryptophan\nenrichment, residue clustering) add breadth but not fundamentally new mechanis=c concepts.\nReply: We strongly disagree with the reviewer’s assessment that our study lacks conceptual\nnovelty. Our work provides the first-ever examples demonstra=ng that nonstop muta=ons can\n“stabilize” proteins. Importantly, contrary to the reviewer’s sugges=on that CRL-type ligases\nare involved, none of the three E3 ligases that recognize hydrophobic C-termini—two of which\nwe iden=fy here for the first =me (RNF139 and MARCH6), along with one previously known\n(RNF126)—belong to the CRL-type ligase family. This underscores a previously unrecognized\nmechanism.\nBeyond the enrichment for cysteine/tryptophan and residue clustering contribu=ng to protein\nstability, as noted by the reviewer, our study offers mul=ple novel conceptual insights,\nsummarized as follows. Notably, points #4 and #5 introduce new mechanis=c paradigms:\n1. First-ever global analysis of nonstop muta=ons: We provide the first comprehensive\nevalua=on of over 3,000 disease-associated nonstop muta=ons, systema=cally uncovering\ntheir diverse effects on protein stability.\n2\n2. Nonstop muta=ons can stabilize proteins: For the first =me, we demonstrate that nonstop\nmuta=ons can stabilize proteins, in contrast to all previously characterized nonstop\nmuta=ons, which promote protein degrada=on.\n3. Systema=c assessment of naturally occurring C-terminal varia=ons: We deliver the first in-\ndepth inves=ga=on of how natural C-terminal diversity, driven by alterna=ve splicing and\nprogramed readthrough, cri=cally modulates protein half-life.\n4. Sequence context, not just hydrophobicity, governs degrada=on: We establish that\ndegrada=on is determined not solely by overall C-terminal hydrophobicity but by the\nprecise arrangement of hydrophobic residues and their surrounding sequence context,\nwhich together dictate both the iden=ty of the responsible E3 ligase and the extent of\ndegrada=on.\n5. Discovery of novel E3 ligases targe=ng hydrophobic C-termini: We iden=fy two previously\nunrecognized E3 ligases—MARCH6 and RNF139—that act alongside Bag6-RNF126 to\nselec=vely target proteins bearing hydrophobic C-termini in human cells, thereby unveiling\na new mechanis=c layer of complexity in C-terminal-dependent protein degrada=on.\nAssay limita=ons: The GPS system is s=ll the backbone of the study. While the authors added\ncycloheximide-chase assays and selected full-length constructs, the overwhelming majority of\ndata remain based on GFP–pep=de fusions in HEK293T cells. These ar=ficial assays cannot\nfully capture endogenous factors such as folding, localiza=on, and complex forma=on, and\ntherefore the conclusions remain correla=ve.\nReply: To rule out any poten=al impact of the GFP tag on protein stability, we conducted\naddi=onal cycloheximide-chase experiments using “FLAG-tagged” full-length proteins, which\nare now presented in new Figs. S1D and S2C.\nWe strongly disagree with the reviewer’s asser=on that the GPS system cannot adequately\ncapture endogenous factors, thereby rendering our conclusions correla=ve. This claim\ncontradicts extensive experimental and published evidence, both from our own work and\nthe broader field. The GPS system we developed (Science 322: 918–923; Science 322: 923–\n929) has become a cornerstone technology in protein degrada=on research, already having\nmore than 578 cita=ons, and it is widely recognized as a rigorous, high-throughput, and\nphysiological relevant pla_orm for quan=fying cellular protein stability.\nAs demonstrated by numerous references, the GPS assay and its deriva=ves have directly\nenabled landmark discoveries across diverse biological contexts (Cell 173: 1622-1635.e14;\nMol Cell 70: 488-501.e5; Science 365: eaaw4912; Nat Commun 13: 7588; Mol Cell 83: 3377-\n3392.e6; Mol Cell 83: 1921-1935.e7; Science 381: eadh5021; Nat Commun 14: 8363; Mol\nCell 83: 57-73.e9; Proc Natl Acad Sci USA 120: e2308870120; Nat Commun 14: 2474; J Cell\nBiol 223: e202311035; EMBO J 43: 2862-2877; Nat Commun 15: 3558; Nat Commun 15: 4703;\nNature 628: 878-886; Mol Cell 85: 829-842.e6; Nat Commun 16: 1511; Nature 534: 719-23;\nMol Cell 63: 1055-65; Mol Cell 73: 377-389.e11; Cell 186: 3227-3244.e20; Nature 617: 395-\n402; Nat Commun 15: 1541; among many others). Due to its superior reproducibility,\nprecision, and scalability, the GPS system has effec=vely supplanted tradi=onal methods such\nas cycloheximide or pulse-chase assays as the preferred technique for protein stability\nmeasurements.\nindependent laboratories, we find the reviewer’s concern regarding it to be unfounded and\nunsupported, and he/she appears to have completely overlooked substan=al experimental\nevidence to the contrary.\nMechanis=c depth: Despite the authors explana=ons a`empts in the rebu`able, in my view\nthe manuscript s=ll does not convincingly resolve the inconsistencies in its own dataset, where\nproposed rules (hydrophobicity, Cys/Trp enrichment) are not consistently predic=ve. While\nthe authors acknowledge complexity, but the result is s=ll primarily descrip=ve.\nReply: We strongly disagree with the reviewer’s assessment that our study is descrip=ve and\nlacks mechanis=c depth. Contrary to this comment, we have iden=fied two previously\nunrecognized E3 ligases—MARCH6 and RNF139—that work together with the Bag6–RNF126\ncomplex to target proteins with hydrophobic C-termini for degrada=on. Importantly, we\ndemonstrate that degrada=on is not driven solely by hydrophobicity, as previously assumed,\nbut it is also cri=cally influenced by the specific sequence context and spa=al arrangement of\nresidues. These factors determine both the efficiency of degrada=on and the selec=on of the\nresponsible E3 ligase. Collec=vely, our findings represent a substan=al mechanis=c advance,\nsignificantly enhancing our understanding of how hydrophobic C-termini are recognized and\ndegraded.\nAddi=onally, we strongly disagree with the reviewer’s assessment of inconsistency in our\ndataset. As we men=oned in our previous rebu`al, mul=ple C-terminal features work together\nto influence protein half-life. Beyond hydrophobicity and the presence of tryptophan or\ncysteine, small terminal residues and an increased frequency of arginine residues also\npromote degrada=on, while the enrichment of acidic residues contributes to stabiliza=on.\nThus, the reviewer’s a`empt to evaluate dataset consistency by predic=ng protein stability\nbased on a single or limited set of a`ributes—without considering the combinatorial effects\nof mul=ple C-terminal determinants—could never accurately reflect the underlying biology or\ncomplexity revealed by our data.\nNeutral majority: Despite the authors’ response, it remains clear that a large propor=on of\nextensions have no significant effect. This important nega=ve result is not sufficiently\ndiscussed, and the emphasis con=nues to be on a minority of destabilizing or stabilizing cases,\npoten=ally oversta=ng generality.\nReply: We strongly disagree with the reviewer’s viewpoint that 38% (28.4% showing\ndegrada=on and 9.51% showing stabiliza=on; Fig. 1G), 64% (7 out of 11), and 60% (6 out of\n10) of protein stability–influencing C-terminal varia=ons arising from nonstop muta=ons,\nalterna=ve mRNA splicing, and programmed readthrough, respec=vely, cons=tute a ‘minority’.\nSuch propor=ons represent substan=al and biologically meaningful frac=ons of our dataset\nand, therefore, cannot reasonably be regarded as excep=onal cases.\nFurthermore, we find it en=rely expected—and not surprising—that some extensions show\nno apparent effect on protein stability. This is because mul=ple complex C-terminal features,\nwith opposing (“posi=ve” or “nega=ve”) effects, act combinatorially to influence protein half-\nlife, as clearly illustrated in our figures (Figs. 4C, 4D) and text (p.13, ln. 17-19; p.14, ln.1-9). In\nresponse to the reviewer’s comment, we have now added a statement in the revised\nDiscussion to clarify this concept (p.22, ln. 16-19).\nmuta=ons in endogenous models (e.g., CRISPR-edited PTEN), provided mechanis=c links to\nproteasomal degrada=on, and explored evolu=onary constraints on C-terminal amino acid\nusage. That study established mechanis=c insight, whereas the present manuscript remains\nlargely a descrip=ve catalog of correla=ons.\nReply: Again, we cannot comprehend the reviewer’s assessment that our study lacks\nmechanis=c insight. In fact, rather than merely demonstra=ng that degrada=on is\n‘proteasome-dependent’, we have further elucidated the underlying recogni=on mechanism\n(i.e., iden=fica=on by E3 ubiqui=n ligases) responsible for proteasomal degrada=on—a key\naspect not addressed in the prior work cited by this reviewer. Specifically, we have discovered\ntwo previously unrecognized E3 ligases—MARCH6 and RNF139—that act in concert with the\nBag6–RNF126 complex to target proteins with hydrophobic C-termini.\nTo address the reviewer’s comment, we have now added new data demonstrating that the\ndifferential degradation of wild-type or nonstop mutation-induced readthrough LAMTOR5,\nRBBP4, MAX, CCND4 and SNCG proteins is proteasome-dependent (Fig. S2D; p.10, ln. 5-7).\nResponse to Referee 4\nReviewer #4 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This\nis part of the Nature Communica=ons ini=a=ve to facilitate training in peer review and to\nprovide appropriate recogni=on for Early Career Researchers who co-review manuscripts.\nReply: Thank you for your contribu=ons.\n5"}]

Decision letter