Significance Plants are continuously exposed to mechanical manipulation by wind, rain, neighboring plants, animals, and human activities. These mechanical stimuli cause short-term molecular changes and long-term developmental effects, affecting flowering time, pathogen defence, and plant architecture. Using water spray to simulate rain, we show that jasmonic acid-signaling factors mediate rapid gene-expression changes. Nearly 300 genes are regulated by MYC2/MYC3/MYC4 transcription factors, particularly affecting the most highly responsive genes. This is controlled by induced binding and activation of water spray-inducible promoters by MYC2. We have identified a core MYC2 “regulon,” including many secondary transcription factors that in turn activate downstream promoters, creating a hierarchical transcriptional network. Finally, we demonstrate that spray-induced jasmonate accumulation is transcriptionally regulated by a MYC2/MYC3/MYC4-controlled positive-feedback loop.

Abstract Mechanical stimuli, such as wind, rain, and touch affect plant development, growth, pest resistance, and ultimately reproductive success. Using water spray to simulate rain, we demonstrate that jasmonic acid (JA) signaling plays a key role in early gene-expression changes, well before it leads to developmental changes in flowering and plant architecture. The JA-activated transcription factors MYC2/MYC3/MYC4 modulate transiently induced expression of 266 genes, most of which peak within 30 min, and control 52% of genes induced >100-fold. Chromatin immunoprecipitation-sequencing analysis indicates that MYC2 dynamically binds >1,300 promoters and trans-activation assays show that MYC2 activates these promoters. By mining our multiomic datasets, we identified a core MYC2/MYC3/MYC4-dependent “regulon” of 82 genes containing many previously unknown MYC2 targets, including transcription factors bHLH19 and ERF109. bHLH19 can in turn directly activate the ORA47 promoter, indicating that MYC2/MYC3/MYC4 initiate a hierarchical network of downstream transcription factors. Finally, we also reveal that rapid water spray-induced accumulation of JA and JA-isoleucine is directly controlled by MYC2/MYC3/MYC4 through a positive amplification loop that regulates JA-biosynthesis genes.

Plants are constantly subjected to a changing environment. As sessile organisms, they have evolved defense mechanisms to cope with abiotic and biotic stresses that can interfere with their development and growth. Stresses, such as salt, wounding, and insect herbivory are known to affect plant growth, development, and flowering time (1⇓⇓–4). These phenotypes are also observed in plants that are repeatedly exposed to mechanical stimulation, including wind, rain, neighboring plants, agricultural equipment, and human touch, colloquially termed “thigomorphogenesis” (5, 6). Such mechanical stimulation without observable damaging of leaves also increases disease resistance against insect and fungal pests (7⇓–9). As flowering time and disease resistance are of significance for global food production, understanding the molecular basis of the touch response may aid in rational design of future crops.

At the core of this response are signaling molecules, such as reactive oxygen species (ROS) and the phytohormones jasmonic acid (JA), abscisic acid (ABA), gibberellic acid (GA), brassinosteroids, auxin, and ethylene (10). Furthermore, a single touch results in fast accumulation of early signaling compounds, like calcium (11, 12), activation of membrane-localized mechanosensitive channels (13, 14), and genome-wide transcriptional changes (15, 16), while repeated touch eventually results in stunted growth and delayed flowering (17).

While a well-calibrated touch response in plants should not automatically result in a wound response, a clear overlap between the wound response and the response to touch is apparent. Repeated wounding of leaves results in increased JA accumulation in Arabidopsis (18, 19) and stunts its growth in a JA-dependent manner (2, 20). Similarly, regular touch increases JA accumulation (7, 21). Some of the JA genes known to be up-regulated by wounding, such as JASMONATE ZIM-DOMAIN (JAZ) 10, 12-OXOPHYTODIENOATE REDUCTASE (OPR) 3, LYPOXYGENASE (LOX), and ALLENE OXIDE CYCLASE (AOC) have been also shown to be touch-inducible (22⇓–24). In Arabidopsis, this effect of touch on gene expression can be alleviated in allene oxide synthase (aos) and opr3 mutants (7). At the same time, some genes are specifically responsive to either wounding or touch and the expression of a significant set of touch genes, including TOUCH (TCH) 2, TCH4, and CALMODULIN-LIKE (CML) 39, is independent of JA (7). Finally, whereas both touch and wounding cause a fast accumulation of calcium (6), the concomitant modulated electric potential in wounded leaves appears not to occur in touched leaves (25), hence further indicative of discriminating signaling cascades between touch and wounding responses.

JA integrates environmental stresses and developmental signals to regulate plant growth and defense (26, 27). A key transcription factor (TF) of the JA-signaling pathway is the basic helix–loop–helix (bHLH) TF MYC2 (28), which is involved in many aspects of plant defense and development (2, 29⇓⇓⇓–33). Importantly, in addition to CORONATINE INSENSITIVE 1 (COI1) (34) and the JAZ repressors (35), MYC2 and its paralogs MYC3 and MYC4 also regulate the JA-dependent delay of flowering time (36) and, whereas untouched myc2 mutants show no flowering phenotype (34), the myc2 myc3 myc4 triple (myc234) mutant flowers early (36). Although many indirect targets of MYC2 have been identified through analyses of myc2 and myc234 mutants (29, 37, 38), few of its direct targets have been identified to date (31, 33, 39⇓–41).

Besides JA, the volatile phytohormone ethylene has been widely linked to touch responses in the past, although it seems that for most touch responses ethylene is not directly involved (10). Both expression of the touch-responsive genes TCH2, TCH3, and TCH4, as well as the developmental changes associated with touch, are not noticeably affected in the ethylene signaling mutants ein2 and etr1 (42). Similarly, touch-induced expression of the JA-biosynthesis gene OPR3 appears independent from ETHYLENE RECEPTOR 1 (ETR1) (43). Nevertheless, some studies have reported ethylene accumulation and expression of the ethylene biosynthesis gene 1-AMINOCYCLOPROPANE-1-CARBOXYLATE SYNTHASE (ACS) is induced after touch (10, 44, 45). Given the cross-talk between ethylene and other hormones like JA in regulation of growth and development (32, 33), a role for ethylene in some aspects of the touch response cannot be excluded (10). To what extent the genome-wide transcriptome is affected after touch in any of the ethylene signaling mutants, or any hormone signaling mutants by extension, has however not yet been investigated.

A single touch can impose fast and wide-spread transcriptional changes (15, 17). Transcriptional, posttranscriptional, and posttranslational mechanisms underlying the touch response have been identified. These include the identification of cis-regulatory regions, the characterization of active mRNA degradation components, and posttranslational modifications that affect touch-induced transcript accumulation levels (46⇓⇓⇓–50). Although transcription factors are central to such transcriptional reprogramming, a regulatory network underlying the touch response remains to be identified.

Using water spray as a trigger (5), we have screened the responsiveness of hallmark mechanical stimulation-responsive genes in selected core signaling mutants to identify major pathways regulating their transcriptional response. To substantiate our findings, we have undertaken in-depth multiomics profiling of the early water spray-induced response in Arabidopsis in the context of JA-signaling components and have discovered a regulatory network governed by MYC2, MYC3, and MYC4.

Discussion Water Spray Invokes Major Dynamic Transcriptome and Proteome Changes through a Regulatory Network of Transcription Factors. Mechanical stimulation triggers a wide-spread transcriptional response. Our RNA-seq datasets were consistent with 2 published transcriptomic datasets (15, 16), with 230 genes in all 4 and 1,671 genes in 2 of 4 datasets differentially expressed. The increased time resolution of our dataset allowed for a more dynamic dissection. Over 700 genes respond to the water spray treatment within 10 min. Most of these genes continue to increase in expression, peaking at 25 min, returning to near unsprayed levels within 1 h, including bHLH19, ERF109, and TCH2/4. Only very few of the DEGs peak at 10 min with a clear overrepresentation of TFs such as MYC2 and ORA47, suggesting a transcriptional network is being initiated rapidly. Nearly half of the DEGs are differentially expressed at a single time point, illustrating the transient nature of this regulatory network and its implication for the transcriptional response. Accordingly, proteomic analysis revealed that the abundance of over 300 proteins was altered in at least 1 time point after water spray. Several kinases/phosphatases were identified, confirming the importance of phosphorylation cascades in mechanical stimulation signaling (50). In addition, redox status seems to play an important role with many peroxidases, thioredoxins, and glutaredoxins being altered in abundance after water spray. This is in line with previous reports of touch-induced ROS bursts (12). As a central JA-response regulator, a critical role for MYC2 in insect- and wound-response is well documented (63). Importantly, MYC2 and its paralogs MYC3 and MYC4 are also reported to be involved in the regulation of flowering time (17, 36), a hallmark feature of the touch response. However, their involvement in mechanical stimulation-induced gene expression had not been investigated to date. Here, we have assessed the genome-wide action of MYC2 in response to water spray through RNA-seq on myc234, MYC2-tagged ChIP-seq, and promoter trans-activation assays. The RNA-seq and ChIP-seq data combined showed that MYC2 (in addition to MYC3/4) (in)directly controls the majority of the most water spray-responsive genes. MYC2/MYC3/MYC4 regulate in particular early-response genes, while MYC2 gene expression itself peaks 10 min after water spray. This further supports the concept that MYC2 activation is 1 of the first transcriptional events following touch. Generally, our analyses support a preference for MYC2 to directly regulate other TFs, which is largely in agreement with a recent study in tomato (64), and consequently positions MYC2 highly in the hierarchical regulatory network. Indeed, 20 TF genes were found to be directly targeted and regulated by MYC2 after water spray, including bHLH19 and ERF109. ERF109 functions in ROS-related stress response, insect-resistance, and auxin/JA-related lateral root formation (38, 58, 65), among others. Very recently, involvement of ERF109 in JA-dependent wound regeneration was shown (66). bHLH19 has recently been implicated in JA-dependent Fe-metabolism (67). Our results add an additional role in the mechanical stimulation response for these TFs. Given the overlap between the mechanical stimulation response and other (a)biotic stresses, such as wounding, salt, and insect attack, and the prominent role of MYC2 in stress response and development, our MYC2-target gene list could be useful to assess a role for these TFs in other signaling cascades, as well. MYC2 Regulates JA Biosynthesis and Hormone Levels. Previous reports have shown the importance of JA and the JA-signaling components JAR1, COI1, OPR3, and AOS in thigmomorphogenis (7, 26, 34, 35). However, it was unknown to what extent JA affects the transcriptional responses to mechanical stimulation. Our results show that ∼30% of the water spray-induced genes are JA-responsive, whereas a clear non-JA–dependent circuit exists, exemplified by JA- and COI1-independence of the TCH genes (5, 57). Accordingly, at the protein level the JA-biosynthesis enzymes OPCL1 and AOC2 were found to be differentially abundant in response to water spray, underlining the importance of JA. Some of the most striking effects of MYC2/MYC3/MYC4 were observed by hormone profiling. Although JA levels have previously been shown to be induced by touch and wounding in different species (7, 18, 19, 68, 69), the direct role of MYC2 on hormonal levels had not been described before. Our hormone analysis shows that the water spray-induced accumulation of JA and JA-Ile are largely dependent on MYC2/MYC3/MYC4. Whereas an initial increase in JA and JA-Ile levels is observed in both Col-0 and myc234, the large boost in JA and JA-Ile accumulation in Col-0 is completely absent in myc234. This correlates with the widespread MYC2/MYC3/MYC4-dependent up-regulation of JA biosynthesis genes after water spray and is further supported by direct binding of no less than half of the JA-metabolism gene promoters (13 of 26) by MYC2. JA and JA-Ile levels peak at 25 min and drop strongly by 40 to 60 min, which could be the result of enzymatic deactivation of the active hormone, and thus attenuation of the JA signal. This is supported by earlier peak expression for JA-biosynthesis genes like, for example, LOX3/4 and OPCL1, compared to JA-catabolism genes, such as JASMONIC ACID OXIDASE 2 (JAO2) and JAO4 (70). Interestingly, JAO2 and JAO4 are also directly bound by MYC2 in our ChIP-seq analysis, indicating that in addition to JA biosynthesis, JA turnover appears transcriptionally regulated by MYC2 as well. In conclusion, this study provides a high-resolution landscape of the transcriptional, hormonal, and proteomic effects of water spray in Arabidopsis. It clearly shows the direct role of JA and the MYC2/MYC3/MYC4 TFs in the regulation of a large proportion of the transcriptome changes, both by directly setting a secondary network of TFs in motion and directly controlling JA metabolism. Notably, however, this JA- and MYC2/MYC3/MYC4-dependent TF network does not seem to modulate other classic touch marker genes, such as TCH3 and TCH4, meaning that additional touch-induced signaling pathways await discovery.

Methods Plant Material and Treatment. The myc2 myc3 myc4 (myc234) and coi1-16 mutant lines have been described previously (30, 71) and were a kind gift from Roberto Solano, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain. etr1-1 was kindly donated by Kirk Overmyer, University of Helsinki, Helsinki, Finland, and the msl mutants were kindly provided by Elizabeth Haswell, Washington University in St. Louis, St. Louis, MO. The mutant line erf109 (SALK_150614) originates from the Nottingham Arabidopsis Stock Centre and the myc2 MYC2::MYC2-FLAG line was described previously (72). Arabidopsis seeds were dry-sterilized overnight in commercial bleach (1:8 dilution in water) containing 3% HCl. Seeds were placed on 0.5× Murashige and Skoog media (including vitamins), 0.5% 2-ethanesulfonic acid, pH 5.8, 0.7% phytoagar plates, and stratified for 2 to 3 d at 4 °C, after which the plates were transferred to standard growth conditions (21 °C, 16-h/8-h light/dark regime) for 10 to 14 d. For transcript and metabolite analyses, seedlings were stimulated by spraying downward onto the plate from around 15-cm distance 5 to 10 times (depending on the size of the plate) with milliQ water using a spraying bottle (Black&Gold, 500-mL multipurpose sprayer, cat. no. CLEA0055), except where specified. An example treatment is shown in Movie S1. The average droplet size of the spray is 211 ± 12 µm, as determined by immersion sampling in silicon oil and measurement under a microscope. The water volume of 1 spray is around 625 μL, and we sprayed with enough force to allow the droplets to travel upward against gravity around 52 cm (implying an initial speed of about >3 m/s ignoring air friction). Excess water was then drained off and plates were closed for the indicated time before sampling. Approximately 5 to 10 whole seedlings were sampled for each biological repeat, and the plants were quickly dried with tissue paper before snap-freezing in liquid nitrogen. In case of touching without spraying, seedlings were touched with a blunt forceps for ∼10 s (SI Appendix, Fig. S1) or using a gentle paint brush (Langnickel Snowhite 4, L4530) (Fig. 2B and Movie S2). For phenotype analysis (SI Appendix, Fig. S2 D and E), seeds were sown in soil, stratified for 2 d at 4 °C, and grown in standard growth conditions (21 °C; 16-h/8-h light/dark regime). From 14 d after transfer to the growth room onward until bolting, leaves were touched 10 times twice per day with blunt tweezers. Construct Design. All constructs were made using Gateway technology (Invitrogen). Promoter regions of ORA47, ERF13, ERF105, MYB77, ZAT10, ERF5, ERF104, ERF109, ERF13, and bHLH19 were isolated using primer P53-72 (Dataset S14) and BP recombined into pDONR221 (Invitrogen). The coding sequences of ERF109 and bHLH19 were isolated using primers P49/50 and P51/52, respectively (Dataset S14) and cloned into pDONR221 (Invitrogen). The entry plasmids were sequence-verified and subsequently LR recombined into pGWL7 for the promoters and p2GW7 for the coding sequences. Cloning of MYC2 and MYC2D105N was described previously (41). Creation of the MYC2::MYC2-FLAG line has been described previously (72). Expression Analysis. Total RNA extraction was isolated using the Spectrum Plant Total RNA Kit (Sigma-Aldrich) and 1 μg was used for cDNA synthesis using iScript (Bio-Rad). qPCR was performed with primers P1-P46 (Dataset S14). For normalization housekeeping genes POLYUBIQUITIN 10 (UBQ10; At4g05320) and UBIQUITIN-CONJUGATING ENZYME 21 (UBC21; At5g25760) were used. Promoter Trans-Activation Assays in Tobacco Protoplasts. Transient promoter trans-activation assays in tobacco protoplasts were performed as described previously (73). ChIP-seq. Approximately 100 mg of myc2 MYC2:MYC2-FLAG or Col-0 seeds per plate were grown for 2 wk on Murashige and Skoog media in square Petri dishes. Samples were spray-treated with distilled water. At the selected time points, the seedlings were quickly plucked from the plates, with representative seedlings immediately snap-frozen in liquid nitrogen for subsequent transcript and protein analysis. The remaining 5 to 10 g of seedlings was quickly submerged in nylon stockings in 1% formaldehyde (Sigma-Aldrich cat no. F8775) in 10 mM Hepes-NaOH pH 7.4, and vacuum-infiltrated for 10 min. The vacuum was then released and reapplied for 10 min. Next, formaldehyde was replaced with 200 mM glycine and again vacuum-infiltrated for 10 min. Finally, the samples were washed with distilled water, removed from the stockings, and snap-frozen. ChIP-seq experiments were performed as previously described (74), with minor modifications. Approximately 500 mg of 2-wk-old myc2 MYC2:MYC2-FLAG and Col-0 seedling tissue was used. Experiments were conducted with antibodies against FLAG (F1804, Millipore Sigma). As a negative control, mouse IgG (015-000-003, Jackson ImmunoResearch) was used. Anti-FLAG antibody and IgG were coupled to 50-µL Protein G Dynabeads (10004D, Thermo Fisher Scientific) 6 h and subsequently incubated overnight with equal amounts of sonicated chromatin. After overnight incubation, beads were washed twice with high salt buffer (50 mM Tris⋅HCl pH 7.4, 150 mM NaCl, 2 mM EDTA, 0.5% Triton X-100), low salt (50 mM Tris⋅HCl pH 7.4, 500 mM NaCl, 2 mM EDTA, 0.5% Triton X-100), and wash buffer (50 mM Tris⋅HCl pH 7.4, 50 mM NaCl, 2 mM EDTA). After elution, samples were decross-linked and digested with proteinase K digestion before the DNA was precipitated. ChIP-seq libraries were generated following the manufacturer’s instructions (Illumina) and sequenced on the Illumina HiSeq 2500 Sequencing system. Sequencing reads were aligned to the TAIR10 genome assembly using Bowtie2 (75). Overrepresented peaks were called using SICER (76) (P < 0.01). RNA-seq Analysis. Total RNA was extracted from snap-frozen tissues using the Sigma Spectrum Plant RNA kit, and genomic DNA was removed using Ambion DNA-free kit. Libraries for RNA-seq analysis were prepared from 500 ng DNase-treated total RNA using the Illumina Ribo-zero Plant kit (RS-122-2401), following standard procedures, as described previously (77). The number of replicates for the myc234 time-course experiment were n = 3, except for myc234 25 min (n = 4). For the MYC2-FLAG time course n = 4. Libraries were clustered on an Illumina cBot using Truseq SR Cluster Kit v3 cBOT HS (GD-401-3001). Sequencing was then performed on an Illumina HiSeq 1500 using SBS kit v3 for 50 to 61 cycles (FC-401-3002). Reads were aligned to TAIR10 with STAR (78), and 24 to 39 million (myc234 time course) or 13 to 23 million (MYC2-FLAG time course) uniquely aligned reads were obtained for each sample. Aligned reads were assigned to genes with featureCounts (79). DEGs were called with DEseq2 with no independent filtering (80). Transcripts were considered to be significantly differentially expressed between genotypes when P adj < 0.05 (after multiple testing correction) and fold-change > 2×. Hormone Quantification. Samples (n = 5) were extracted, purified, and analyzed according to method described previously (81). Briefly, ∼20 mg of frozen material per sample was homogenized and extracted in 1 mL of ice-cold 50% aqueous acetonitrile (vol/vol) with the mixture of 13C- or deuterium-labeled internal standards using a bead mill (27 Hz, 10 min, 4 °C; MixerMill, Retsch) and sonicator (3 min, 4 °C; Ultrasonic bath P 310 H, Elma) After centrifugation (14,000 rpm, 15 min, 4 °C), the supernatant was purified as following. A solid-phase extraction column Oasis HLB (30 mg 1 cc; Waters) was conditioned with 1 mL of 100% methanol and 1 mL of deionized water (Milli-Q, Merck Millipore). After the conditioning steps, each sample was loaded on an SPE column and flow-through fraction was collected together with the elution fraction 1 mL 30% aqueous acetonitrile (vol/vol). Samples were evaporated to dryness using speed vac (SpeedVac SPD111V, Thermo Scientific). Prior to LC-MS analysis, samples were dissolved in 40 µL of 30% acetonitrile (vol/vol) and transferred to insert-equipped vials. MS analysis of targeted compounds was performed by an UHPLC-electrospray ionization-MS/MS system comprising of a 1290 Infinity Binary LC System coupled to a 6490 Triple Quad LC-MS System with Jet Stream and Dual Ion Funnel technologies (Agilent Technologies). A list of internal standards used in this study is provided in Dataset S15. The quantification was carried out in Agilent MassHunter Workstation Software Quantitative (Agilent Technologies). Mass Spectrometry. For protein extraction, 200 mg of ground seedlings (4 biological replicates per sample group) were resuspended in 400 μL of 125 m mM Tris⋅HCl pH 7.0, 7% SDS, 0.5% PVP-40, 25 mM DTT, 1 mM complete protease inhibitor mixture (Roche) and vortexed repeatedly over the course of 5 min. Debris were pelleted by centrifugation and 250 μL of supernatant transferred to fresh tubes. Chloroform:methanol extraction was performed as previously described (82) and the protein layer washed twice in methanol. The pellet was then treated with −20 °C 90% acetone for 2 h with the acetone being changed after 1 h. Pellets were resuspended in 1% SDS, 50 mM ammonium bicarbonate, 10 mM DTT, and treated with 25 mM iodoacetic acid for 30 min in the dark before digestion with trypsin (Life Sciences) 1:20. Samples were cleaned up by combined J4-SDS2 (Nest group) and C18 (Waters) HPLC columns before drying down in a vacuum centrifuge. Peptide samples were analyzed on a ThermoFisher Orbitrap Fusion over the course of 240 min using a 75-μm × 20-mm trap column (ThermoFisher) and a 75-μm × 500-mm analytical column (ThermoFisher). Data files were converted to *.mzML (Msconvert 3.0.9992) before spectral matching through CometMS (2017.01 rev. 4) with reversed decoy database (TAIR10). Peptide scores were cut off at a false-discovery rate of 2% and rescored through PeptideProphet (TPP v5.0.0 Typhoon) and protein lists assembled with ProteinProphet (TPP v5.0.0 Typhoon). Relative abundance measurements were assembled with Abacus (83) and statistical analysis conducted through the DESeq2 packages (80) in the R statistical computing environment (3.5.1). Proteins with at least an average of 5 spectral counts per replicate in at least 1 time point, and a median of the average spectral counts per time point higher than 3 were deemed as reliably quantified and retained for statistical analysis (4,243 proteins) (Dataset S16). Proteins with a fold-change >1.5× and P adj < 0.05 (DESeq2) were retained as significantly differential. Additional MS1 data were extracted for a subset of proteins through the MS1 filtering workflow in Skyline (4.1.0.11796). Cluster Analyses and Venn Diagrams. Average linkage hierarchical clustering with Pearson correlation and k-means clustering were performed using the multiple experiment viewer (MeV) software. Venn diagrams were made using a web application (http://bioinformatics.psb.ugent.be/webtools/Venn/). Statistical Information. Information on statistical processing for the large datasets (RNA-seq, ChIP-seq, and proteomics) are specified in the respective Methods sections. Complete lists of P values are available in SI Appendix. For additional experiments, 2-tailed Student’s t tests were used, with number of replicates and error bars as indicated in the figure legends. Data Availability. RNA-seq data have been deposited in the ArrayExpress database under accession nos. E-MTAB-8019 and E-MTAB-8021. The ChIP-seq data have been deposited at Gene Expression Omnibus under accesion no. GSE132316. The MS proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE (84) partner repository with the dataset identifier PXD014008.

Acknowledgments This research was supported by Australian Research Council DP160103573 (to O.V.A., A.H.M., and K.B.S.); and the Salk Pioneer Postdoctoral Endowment Fund, Deutsche Forschungsgemeinschaft research Fellowship Za-730/1-1, and National Science Foundation MCB-1024999 (to M.Z.). J.R.E. is an Investigator of the Howard Hughes Medical Institute. K.L. and J.Š. acknowledge the Knut and Alice Wallenberg Foundation, the Swedish Governmental Agency for Innovation Systems, and the Swedish Research Council, and the Swedish Metabolomics Centre (https://www.swedishmetabolomicscentre.se/) for access to instrumentation. O.V.A. was supported by the Swedish Research Council (Vetenskapsrådet 2017-03854), Crafoord Foundation (20170862), Carl Trygger Foundation (CTS 17: 487), Carl Tesdorpf Stiftelse, and NovoNordiskFonden (NNF18OC0034822). A.V.M. was supported by a postdoctoral fellowship by the Sven and Lily Lawski Foundation. M.G.L. was supported by a European Union Marie Curie FP7 International Outgoing Fellowship (252475).

Footnotes Author contributions: A.V.M., K.B.S., J.R.E., A.G., A.H.M., and O.V.A. designed research; A.V.M., O.D., M.Z., J.Š., M.B., R.V.B., M.G.L., S.L., and O.V.A. performed research; A.V.M., O.D., M.Z., J.Š., K.L., A.G., and O.V.A. analyzed data; and A.V.M., A.H.M., and O.V.A. wrote the paper.

The authors declare no competing interest.

This article is a PNAS Direct Submission.

Data deposition: The data reported in this paper have been deposited in the ArrayExpress database, https://www.ebi.ac.uk/arrayexpress/ (accession nos. E-MTAB-8019 [ArrayExpress RNA-seq set 1], E-MTAB-8021 [ArrayExpress RNA-seq set 2]), the Gene Expression Omnibus (GEO) database, https://www.ncbi.nlm.nih.gov/geo (accession no. GSE132316 [ChIP-seq data]), and the ProteomeXchange Consortium PRIDE repository, https://www.ebi.ac.uk/pride/archive/ (accession no. PXD014008).

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