Deep mutational scanning reveals pharmacologically relevant insights into TYK2 signaling and disease
- Octant, Inc, United States
- Bristol-Myers Squibb, United States
Figures
Figure 1 with 3 supplements
Effects of >23,000 amino acid variants on TYK2 signaling and protein abundance.
(A) Schematic showing the reporter design for TYK2 deep mutational scanning (DMS) assays on interferon alpha (IFN-α) signaling (left) and protein abundance (right). BC, unique DNA barcode; BFP, blue flourescent protein; GFP, green fluorescent protein; ISRE, interferon-stimulated response element. (B) Heatmaps showing the functional effects of each TYK2 variant, represented as z-scores, for IFN-α signaling (left, 100 U/mL IFN-α condition) and protein abundance (right). Rows and columns of the heatmap correspond to amino acid position and variant identity, respectively. TYK2 protein domains are shown on the far right. GOF, gain-of-function; LOF, loss-of-function; WT, wild-type. (C) Structures of the TYK2 kinase and pseudokinase domains (PDB: 4OLI) with residues colored blue to indicate positions that have at least two significant LOF variants at that position in the IFN-α signaling (left) or protein abundance (right) assay (FDR<0.01). Panel A was created with BioRender.com.
Figure 1—figure supplement 1
Interferon alpha (IFN-α) and abundance deep mutational scanning (DMS) reporters are TYK2-dependent.
(A) IFN-α reporter assay dose-response curves for wild-type (WT) and catalytically inactive (K930E variant) TYK2. RLU, relative luciferase units; WT, wild-type. (B) Flow cytometry data showing that the abundance DMS reporter distinguishes between WT and two strongly destabilizing variants (E154X and K930E). BFP, blue fluorescent protein; GFP, green fluorescent protein.
Figure 1—figure supplement 2
Results of interferon alpha (IFN-α) and abundance deep mutational scanning (DMS) assays.
Heatmap showing results of the IFN-α (1, 10, and 100 U/mL stimulation conditions) and abundance DMS datasets generated in this study. Each cell represents a single variant allele colored by the magnitude of variant effect (Z-statistic). For each heatmap, the x-axis represents amino acid position, and the y-axis represents the induced amino acid change.
Figure 1—figure supplement 3
Deep mutational scanning (DMS) results consistent with other variant effect assessments.
(A) Bar plots quantifying the frequency of loss-of-function (LOF) (blue), neutral (gray), and gain-of-function (GOF) (red) variant effects across the interferon alpha (IFN-α) and abundance DMS datasets. (B) Histograms of stop (red) versus nonstop (gray) variant effects, where greater separation of these two distributions indicates greater dynamic range and power to detect intermediate variant effects. The x-axis represents variant effect measured as Z-statistic of the variant normalized to wild-type (WT) (i.e. WT = 0), and this convention is carried through all subsequent panels. (C) Violin plots of IFN-α (left) and abundance (right) DMS variant effects (Z-statistic, y-axis), grouped and colored by AlphaMissense annotation. The boxplots show the median, the interquartile range (IQR), and 1.5 x IQR whiskers. Brackets indicate pairwise two-sided Kolmogorov–Smirnov tests comparing the Z-statistic distributions between annotation groups (*** p < 0.001, ** p < 0.01, * p < 0.05, ns = not significant). (D) DMS variant effects (log2(fold-change)) for a panel of 32 previously characterized TYK2 variants, grouped by whether they were predicted to be GOF (top), neutral (middle), or LOF (bottom). Points show the log₂ fold change (IFNα conditions) or midpoint shift (Abundance). Error bars span ±2 standard errors (≈95% confidence interval), with errors propagated from the variant and control estimates. Points are colored black where the variant is significant at FDR < 1% (Benjamini–Hochberg) and gray otherwise. (E) Violin plots of IFN-α (left) and abundance (right) DMS variant effects (Z-statistic, x-axis), grouped and colored by ClinVar annotation.
Figure 2 with 1 supplement
Identification of allosteric and other functionally important sites of TYK2.
(A) Schematic showing approach to identify key functional sites by pinpointing TYK2 variants that impact interferon alpha (IFN-α) signaling but not protein abundance. LOF, loss-of-function. (B) Scatterplot of individual TYK2 variant effects on IFN-α signaling activity (x-axis) and TYK2 protein abundance (y-axis). Variants highlighted in blue were classified as signaling-only LOF (see Materials and methods for details). GOF, gain-of-function; WT, wild-type. (C) Count of signaling-only LOF variants (horizontal axis) at each residue of TYK2 (vertical axis), shown alongside the functional domains of the protein (left). Regions important for TYK2 function are highlighted in red, including known catalytic, known allosteric, and novel allosteric sites predicted by this analysis. (D) Structure of the TYK2 kinase and pseudokinase domains (PDB: 4OLI) with amino acid positions that have at least two significant signaling-only LOF variants colored blue. Novel allosteric sites predicted by this analysis are labeled with an asterisk (*). (E) Structural model of inactive full-length TYK2 (colored as in D) bound to the intracellular tail of the IFNAR1 receptor (yellow). See Materials and methods for details on how this composite model was constructed. Panel E was created with BioRender.com.
Figure 2—figure supplement 1
Intersecting signaling and abundance deep mutational scanning (DMS) data identifies allosteric and other functionally important sites.
(A) Histogram quantifying the number of amino acid positions that have X signaling-only loss-of-function (LOF) variants (‘count’). (B) TYK2 kinase-pseudokinase structure (PDB: 4OLI) with amino acid positions that have at least one significant signaling-only LOF variant colored blue.
Figure 3 with 1 supplement
Functional characterization of protein-drug interactions.
(A) Conceptual schematic of how inhibitor dose influences variant effect interpretation. (B) Volcano plot of variant effects under very high dose (>IC99) of BMS-986202, with significant drug-resistant variants colored pink (FDR<0.01 used as significance threshold throughout figure). (C) Surface representation of the TYK2 pseudokinase domain (PDB: 6NZP) colored as in (B). (D) Allosteric binding site of the TYK2 pseudokinase domain with inhibitor BMS-986202 bound (dark gray) and positions with significant drug resistance colored pink (as in C) for increasing concentrations of BMS-986202. (E) Scatter plot of variant effects (Z-statistic) in the presence of inhibitor (IC99 concentration), with variants colored by whether they exhibit resistance to BMS-986202 (pink), NDI-034858 (cyan), or both (orange). (F) Heatmap of drug-resistant positions (x-axis) and variants (y-axis) colored as in (E, G). Structure (PDB: 6NZP) of TYK2 pseudokinase domain (colored as in E). (H, I, J) Variants that exhibit drug-potentiation to each inhibitor (at IC75 concentrations) displayed as in (E, F, and G), respectively.
Figure 3—figure supplement 1
Distinct drug-resistance and drug-potentiating profiles of TYK2 allosteric inhibitors.
(A) Chemical structures of BMS-986202 (left) and NDI-034858 (right). (B) Dose-response curves of allosteric inhibitors generated with the interferon alpha (IFN-α) reporter cell line. (C) Structures of bound allosteric inhibitors BMS-986202 (left, PDB: 6NZP) and NDI-034858 (right, PDB: 8S9A) with residues that confer drug resistance colored pink or cyan, respectively. (D) Structures of inhibitors with residues that confer drug potentiation colored as in (C).
Figure 4 with 3 supplements
Human variants that protect against autoimmune disease reduce TYK2 abundance.
(A) Odds ratios from comprehensive phenome-wide association study (PheWAS) for the TYK2 P1104A allele (see Materials and methods), which confirm protective effect on many autoimmune phenotypes (see Supplementary file 2 for list of phenotype abbreviations). (B) Deep mutational scanning (DMS) results for the interferon alpha (IFN-α) (x-axis) and protein abundance (y-axis) assays, as in Figure 2B. Each point represents a unique missense or nonsense variant, and P1104A is highlighted in blue. GOF, gain-of-function; LOF, loss-of-function; WT, wild-type. (C) TYK2 protein abundance measured using western blotting of HEK293T and Kit225 cells harboring the wild-type (WT, gray) and P1104A (blue) alleles of TYK2. Data are shown normalized by the abundance of the WT allele for each cell type. Bars represent means, with error bars reporting standard error, and p-values determined by unpaired t-test. (D) Effect sizes (beta) of association between P1104A allele and abundance of three proteins in human plasma from UK Biobank. Error bars are 95% confidence intervals. (E) Rare variant dose-response curve for TYK2 variants found in the UK Biobank shows that TYK2 protein abundance (x-axis, from DMS assay) predicts the probability of autoimmune disease diagnosis (y-axis). See Materials and methods for details. Gray shading indicates 95% confidence intervals.
Figure 4—figure supplement 1
Common TYK2 variants associated with autoimmune phenotypes reduce TYK2 abundance.
(A) Effects (as z-scores) of two common partial loss-of-function missense variants of TYK2 on relatively well-powered autoimmune traits in UK Biobank (UKBB). (**) denotes that the variant is the most likely causal variant for the trait at the 5E-08 threshold, while (*) denotes that the variant is the most likely causal variant for the trait at the 5E-05 significance threshold. PsO, psoriasis; RA, rheumatoid arthritis; HT, hypothyroidism; UC, ulcerative colitis; IBD, inflammatory bowel disease; pooled, autoimmune phenotypes combined; pooled (no IBD), same as pooled but excluding IBD cases. (B) Example flow cytometry data showing variants with intermediate abundance (P1104A, L1014P) relative to wild-type (WT) and an early stop variant (E154X). (C) Sanger sequencing traces confirming P1104A mutation in Kit225 cells. (D) Representative western blot of WT and P1104A TYK2 in HEK293T and Kit225 cells. (E) Effect sizes (beta) of association between TYK2 alleles (P1104A, blue; and I684S, pink) and abundance of 12 proteins in human plasma from UKBB. All 12 proteins show a significant association with P1104A, while only the top 3 show a significant association with I684S. Error bars are 95% confidence intervals. (F) Deep mutational scanning results for the interferon alpha (IFN-α) (x-axis) and protein abundance (y-axis) assays, as in Figure 2B. Each point represents a unique missense or nonsense variant, with P1104A and I684S variants colored blue and pink, respectively.
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Figure 4—figure supplement 1—source data 1
Uncropped, labeled image of western blot for Figure 4—figure supplement 1D.
- https://cdn.elifesciences.org/articles/110149/elife-110149-fig4-figsupp1-data1-v1.zip
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Figure 4—figure supplement 1—source data 2
Uncropped, unlabeled original image of western blot for Figure 4—figure supplement 1D.
- https://cdn.elifesciences.org/articles/110149/elife-110149-fig4-figsupp1-data2-v1.zip
Figure 4—figure supplement 2
Rare variants that reduce TYK2 abundance protect against autoimmune phenotypes.
(A) Cumulative density plots quantifying the frequency of autoimmune disease in patient variants against the respective variant effect on protein abundance (left) or interferon alpha (IFN-α) signaling (right). Variants with very low abundance scores are uniquely associated with no autoimmune disease. (B) Rare variant association test for TYK2 variants found in the UK Biobank, comparing probability of autoimmune disease (y-axis) against variant effects on TYK2 abundance (left, reproduced from main Figure 4E) or IFN-α signaling (right), showing that reduced TYK2 protein abundance (left) is correlated with a reduced probability of autoimmune disease. Effects on IFN-α signaling (right) show no correlation with autoimmune disease. Gray shading indicates 95% confidence intervals.
Figure 4—figure supplement 3
Raw western blots used to validate reduced protein abundance of P1104A.
(A-G) Images of all blots stained for TYK2 (top) and GAPDH loading control (bottom). For each lane, TYK2 band density was normalized to GAPDH band density. Lanes that were excluded are marked with a red X, determined by whether either band was outside of the linear detection range or contained blotting artifacts. Lanes are labeled by allele (wild-type [WT] or P1104A), with the cell background (HEK or Kit225) labeled above the alleles. Protein molecular weights (in kDa) are indicated along the left side of each image. See Materials and methods for more details on how bands were quantified and normalized for analysis.
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Figure 4—figure supplement 3—source data 1
Uncropped, labeled images of western blots for Figure 4—figure supplement 3 (all panels).
- https://cdn.elifesciences.org/articles/110149/elife-110149-fig4-figsupp3-data1-v1.zip
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Figure 4—figure supplement 3—source data 2
Uncropped, unlabeled original images of western blots for Figure 4—figure supplement 3 (all panels).
- https://cdn.elifesciences.org/articles/110149/elife-110149-fig4-figsupp3-data2-v1.zip
Tables
Table 1
Experimental conditions assayed by deep mutational scanning (DMS).
| Reporter | Cytokine stimulation | Inhibitor |
|---|---|---|
| IFN-α | – | – |
| IFN-α | 1 U/mL IFN-α | – |
| IFN-α | 10 U/mL IFN-α | – |
| IFN-α | 100 U/mL IFN-α | – |
| IFN-α | 100 U/mL IFN-α | 20 nM BMS-986202 (IC75) |
| IFN-α | 100 U/mL IFN-α | 1 µM BMS-986202 (IC99) |
| IFN-α | 100 U/mL IFN-α | 10 µM BMS-986202 (>IC99) |
| IFN-α | 100 U/mL IFN-α | 7 nM NDI-034858 (IC75) |
| IFN-α | 100 U/mL IFN-α | 1 µM NDI-034858 (IC99) |
| Abundance | – | – |
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IC: inhibitory concentration.
Key resources table
| Reagent type (species) or resource | Designation | Source or reference | Identifiers | Additional information |
|---|---|---|---|---|
| Gene (Homo sapiens) | TYK2 | UniProt | UniProt:P29597 | |
| Genetic reagent | IFN-α signaling DMS reporter | This study | ISRE-minP-luciferase barcoded reporter with doxycycline-inducible TYK2 | |
| Genetic reagent | Protein abundance (VAMP-seq) DMS reporter | This study | GFP-TYK2-IRES-BFP-T2A-BSR reporter | |
| Genetic reagent (H. sapiens) | TYK2 knockout sgRNAs | Synthego | Gene Knockout Kit v2; sgRNA sequences in Materials and methods | |
| Genetic reagent (H. sapiens) | STAT2 transgene | This study | NCBI:NM_005419.4 | Constitutive expression under EF1A promoter; piggyBac integration |
| Genetic reagent (H. sapiens) | IRF9 transgene | This study | NCBI:NM_006084.5 | Constitutive expression under EF1A promoter; piggyBac integration |
| Genetic reagent | P1104A HDR ssODN donor | IDT | AltR end-modifications; sequence in Materials and methods | |
| Cell line (H. sapiens) | HEK293T | ATCC, this study | H11 landing pad; TYK2 knockout | |
| Cell line (H. sapiens) | Kit225 | JCRB | IL-2-dependent human T-cell line | |
| Recombinant DNA reagent | TYK2 DMS variant libraries | This paper | Barcoded variant libraries for signaling and abundance assays; see Materials and methods | |
| Sequence-based reagent | DNA oligo pools (variant libraries) | Twist Bioscience | ~270 bp oligos encoding all single amino acid substitutions; see Materials and methods | |
| Antibody | Rabbit anti-TYK2 | Abcam | Cat#:ab223733; no RRID registered | (1:500) |
| Antibody | Mouse anti-GAPDH (1A10) | Novus Biologicals | Cat#:NBP1-47339; RRID:AB_3212111 | (1:10,000) |
| Antibody | IRDye 800CW Goat anti-Rabbit IgG | LI-COR | Cat#:926-32211; RRID:AB_621843 | (1:15,000) |
| Antibody | IRDye 800CW Goat anti-Mouse IgG | LI-COR | Cat#:926-32210; RRID:AB_621842 | (1:15,000) |
| Peptide, recombinant protein | Human IFN-alpha 2a | PBL Assay Science | Cat#:11100 | Cytokine |
| Peptide, recombinant protein | Human IL-2 | Thermo Fisher | Cat#:PHC0023 | Cytokine |
| Peptide, recombinant protein | Pyogenes HiFi Cas9 V3 | IDT | CRISPR RNP editing of Kit225 cells | |
| Chemical compound, drug | BMS-986202 | MedChemExpress | Cat#:HY-131968; CAS:1771691-34-9 | TYK2 pseudokinase domain inhibitor |
| Chemical compound, drug | NDI-034858 (TAK-279/Zasocitinib) | MedChemExpress | Cat#:HY-150096; CAS:2272904-53-5 | TYK2 pseudokinase domain inhibitor |
| Chemical compound, drug | Doxycycline hyclate | ApexBio | Cat#:A4052; CAS:24390-14-5 | |
| Chemical compound, drug | Blasticidin S HCl | Gibco | Cat#:A1113903 | |
| Commercial assay or kit | Lipofectamine CRISPRMAX | Invitrogen | Cat#:CMAX00015 | RNP transfection |
| Commercial assay or kit | Quick-DNA Kit | Zymo | Cat#:D3024 | Genomic DNA extraction |
| Commercial assay or kit | ZR-96 PCR Kit | Zymo | Cat#:D4024 | 96-Well genotyping |
| Commercial assay or kit | ClonaCell | STEMCELL Technologies | Cat#:03814 | Isoclonal cell line generation |
| Commercial assay or kit | DNeasy Blood and Tissue Kit | QIAGEN | Cat#:69504 | Genomic DNA extraction |
| Commercial assay or kit | EZ-PCR Mycoplasma Detection Kit | Sartorius | Cat#:20-700-20 | Mycoplasma testing |
| Commercial assay or kit | Rapid Gold BCA Protein Assay Kit | Pierce | Cat#:A53225 | Protein quantification |
| Software, algorithm | Custom R/analysis code | https://github.com/octantbio/bms-dms; Abell et al., 2026 | ||
| Software, algorithm | UCSF ChimeraX | Pettersen et al., 2021 | RRID:SCR_015872 | Molecular visualization |
| Software, algorithm | Fiji/ImageJ | Schindelin et al., 2012 | RRID:SCR_002285 | Densitometry and image analysis |
| Software, algorithm | FlowJo | BD Biosciences | RRID:SCR_008520 | Flow cytometry analysis |
| Software, algorithm | REGENIE | Mbatchou et al., 2021 | Association testing | |
| Software, algorithm | GCTA-COJO | Yang et al., 2011 | Conditional analysis | |
| Software, algorithm | SuSIE | Wang et al., 2020 | Fine-mapping | |
| Software, algorithm | Ensembl VEP | McLaren et al., 2016 | RRID:SCR_007931 | Variant annotation |
| Software, algorithm | CRISPR-DAV | Wang et al., 2020 | CRISPR NGS data analysis | |
| Software, algorithm | R SKAT-O | Lee et al., 2012 | Variance component test | |
| Software, algorithm | R AllelicSeries | McCaw et al., 2023 | Allelic series association test | |
| Software, algorithm | Synthego ICE Analysis | Synthego | CRISPR editing efficiency | |
| Software, algorithm | BioRender | BioRender.com | Figure generation | |
| Software, algorithm | AlphaMissense | Cheng et al., 2023 | ||
| Software, algorithm | ClinVar | Landrum et al., 2025 | RRID:SCR_006169 | |
| Software, algorithm | bcl2Fastq | Illumina | ||
| Other | TYK2 DMS raw FASTQ files | This study | NCBI BioProject: PRJNA1291213 | SRA |
| Other | TYK2 DMS barcode maps and read counts | This study | Zenodo: 15347448 | |
| Other | TYK2 IFN-α signaling DMS scores | This study | MaveDB: urn:mavedb:00001270a | |
| Other | TYK2 abundance DMS scores | This study | MaveDB: urn:mavedb:00001271a | |
| Other | UK Biobank | Sun et al., 2023; Bycroft et al., 2018 | Genetic and proteomic data | |
| Other | FinnGen | Kurki et al., 2023 | PheWAS; GWAS summary statistics |
Additional files
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Supplementary file 1
Variants that impact interferon alpha (IFN-α) signaling but not TYK2 protein abundance.
- https://cdn.elifesciences.org/articles/110149/elife-110149-supp1-v1.xlsx
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Supplementary file 2
Phenome-wide association study (PheWAS) data sources and disease codes.
OR, odds ratio; FG, FinnGen; UKBB, UK Biobank; PMID, PubMed Identifier. p-value of phenotype association with P1104A allele (see Materials and methods). PMID for FinnGen: 36653562; PMID for UKBB: 30305743.
- https://cdn.elifesciences.org/articles/110149/elife-110149-supp2-v1.xlsx
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Supplementary file 3
Deep mutational scanning (DMS) protein abundance score model fitting and model selection.
PC, principal component.
- https://cdn.elifesciences.org/articles/110149/elife-110149-supp3-v1.xlsx
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Supplementary file 4
Oligo sequences used in this study.
- https://cdn.elifesciences.org/articles/110149/elife-110149-supp4-v1.xlsx
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Supplementary file 5
UK Biobank autoimmune disease diagnosis codes.
- https://cdn.elifesciences.org/articles/110149/elife-110149-supp5-v1.xlsx
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Supplementary file 6
Deep mutational scanning (DMS) protein abundance score best fit model coefficients.
PC, principal component.
- https://cdn.elifesciences.org/articles/110149/elife-110149-supp6-v1.xlsx
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Supplementary file 7
Deep mutational scanning (DMS) interferon alpha (IFN-α) score model fitting and model selection.
PC, principal component.
- https://cdn.elifesciences.org/articles/110149/elife-110149-supp7-v1.xlsx
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Supplementary file 8
Deep mutational scanning (DMS) interferon alpha (IFN-α) score best fit model coefficients.
PC, principal component.
- https://cdn.elifesciences.org/articles/110149/elife-110149-supp8-v1.xlsx
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MDAR checklist
- https://cdn.elifesciences.org/articles/110149/elife-110149-mdarchecklist1-v1.pdf
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Deep mutational scanning reveals pharmacologically relevant insights into TYK2 signaling and disease
eLife 15:RP110149.
https://doi.org/10.7554/eLife.110149.2
