# Plant response to intermittent heat stress involves modulation of mRNA translation efficiency

Arnaud Dannfald, Marie-Christine Carpentier, Rémy Merret, Jean-Jacques

Favory, Jean-Marc Deragon

► To cite this version:

Arnaud Dannfald, Marie-Christine Carpentier, Rémy Merret, Jean-Jacques Favory, Jean-Marc Deragon. Plant response to intermittent heat stress involves modulation of mRNA translation efficiency. Plant Physiology, 2024, 197 (2), pp.kiae648. 10.1093/plphys/kiae648. hal-04874246

HAL Id: hal-04874246

https://hal.science/hal-04874246v1

Submitted on 14 Mar 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Plant response to intermittent heat stress involves modulation of mRNA translation efficiency

Arnaud Dannfald,<fnref n="1" />,<fnref n="2" /> ID Marie-Christine Carpentier,<fnref n="1" />,<fnref n="2" /> ID Rémy Merret,<fnref n="1" />,<fnref n="2" /> ID Jean-Jacques Favory,<fnref n="1" />,<fnref n="2" /> ID Jean-Marc Deragon<fnref n="1" />,<fnref n="2" />,* ID

The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (https://academic.oup.com/plphys/pages/General-Instructions) is Jean-Marc Deragon (jean-marc.deragon@univ-perp.fr).

## Abstract

Acquired thermotolerance (also known as priming) is the ability of cells or organisms to survive acute heat stress if preceded by a milder one. In plants, acquired thermotolerance has been studied mainly at the transcriptional level, including recent descriptions of sophisticated regulatory circuits that are essential for this learning capacity. Here, we tested the involvement of polysome-related processes [translation and cotranslational mRNA decay (CTRD)] in Arabidopsis (Arabidopsis thaliana) thermotolerance using two heat stress regimes with and without a priming event. We found that priming is essential to restore the general translational potential of plants shortly after acute heat stress. We observed that mRNAs not involved in heat stress suffered from reduced translation efficiency at high temperatures, whereas heat stress-related mRNAs were translated more efficiently under the same condition. We also showed that the induction of the unfolded protein response (UPR) pathway in acute heat stress is favored by a previous priming event and that, in the absence of priming, ER-translated mRNAs become preferential targets of CTRD. Finally, we present evidence that CTRD can specifically regulate more than a thousand genes during heat stress and should be considered as an independent gene regulatory mechanism.

## Introduction

Global climate change is a reality, day-to-day impacting our capacity to ensure food security worldwide (Duchenne-Moutien and Neetoo 2021). Human activities are directly responsible for warming the world's climate by 1.1 °C above preindustrial levels, and global warming is expected to reach 1.5 °C by the early 2030s (IPCC 2023). A direct consequence of these rises is an increase in the number of days per year with extremely high temperatures, a situation that threatens plant survival. Understanding how plants reprogram gene expression in response to heat is therefore crucial to developing the next generation of heat stress-resistant crops.

The reprogramming of gene expression involves many steps, from transcription and translation to post-translational modifications and degradation of RNA and proteins. To obtain an integrated view of the mechanisms regulating gene expression during heat stress, it is essential to obtain information on all these steps and the way they influence each other. Our current understanding of how plant gene expression is reprogrammed after a single heat stress event mainly concerns the gene transcription step (Kotak et al. 2007; Scharf et al. 2012; Jacob et al. 2017; Kerbler and Wigge 2023). Briefly, upon heat stress, heat shock proteins (HSP)90/70 are redirected to unfolded proteins, allowing heat shock factor (HSF)A1 to enter the nucleus to displace histone variant H2A.Z and stimulate transcription of target genes (in cooperation with other transcription factors such as double-stranded RNA binding 2A (DRB2A) and ABA-responsive element binding factors (ABFs/AREBs). Induced proteins include secondary transcription factors (such as HSFA2 and HSFA3) that positively

feedback on HSF and HSP transcription. An important function of HSP and other chaperone proteins is to restore protein homeostasis by preventing the accumulation of misfolded proteins in the cytosol via the cytosolic protein response (CPR) pathway (Sugio et al. 2009), and in the endoplasmic reticulum (ER), through the Unfolded Protein Response (UPR) pathway (Howell 2021; Yu et al. 2022). The CPR and UPR pathways are also linked to protein degradation, preventing the precipitation of irremediably unfolded proteins (Chen et al. 2022; Krshnan et al. 2022; Löchli et al. 2022).

An important aspect of plant heat stress response is the ability of plants to withstand a severe heat stress if they have previously been exposed to a milder one (Bäurle 2016; Crisp et al. 2016; Shekhawat et al. 2022; Charng et al. 2023). This priming event allows plants to respond to a second acute event with a faster and stronger defense response, i.e. plants can “learn” from the previous event. Plant stress memory (PSM) is defined as the ability of plants to maintain this primed state over time (Charng et al. 2023). The “memory phase” (i.e. the time between the first and second stress) can last from several hours to several days. Our understanding of the mechanisms leading to priming and PSM is mostly limited to the transcriptional and post-translational steps (Shekhawat et al. 2022; Charng et al. 2023). Following priming, HSFA1 can activate the transcription of genes that produce “effectors” (such as HSP101 and HSP21 (Härdahl et al. 1999; Queitsch et al. 2000)) that are responsible for maintaining the primed state in the memory phase and for modifying the outcome of the second acute stress. HSFA1 can also initiate the transcription of genes that produce secondary transcription factors (such as HSFA2

<footnote n="1">¹CNRS LGDP-UMR5096, 66860 Perpignan, France</footnote>

<footnote n="2">²Université de Perpignan Via Domitia, LGDP-UMR5096, 66860 Perpignan, France</footnote>

<footnote>*Author for correspondence: jean-marc.deragon@univ-perp.fr</footnote>
and HSFA3) and "regulators" that can either positively regulate effectors [maintainers, such as heat stress-associated 32-kd protein (HSA32) (Wu et al. 2013)] or negatively [erasers, such as the protease filamentation temperature-sensitive H6 (FtsH6) (Sedaghatmehr et al. 2016)]. Specific chromatin modifications allow the transcriptional re-induction of effector genes at the end of the memory phase (Lamke et al. 2016), while small RNAs are involved in the post-transcriptional regulation of heat-induced mRNAs throughout the heat stress period (Stief et al. 2014; Shekhawat et al. 2022). Therefore, sustained transcriptional activity driven by multiple integrated regulatory circuits and small RNAs is essential for PSM establishment and plant acclimation. Alternative splicing has also been shown to be involved in priming and PSM (Ling et al. 2018). Upon priming, splicing is repressed, leading to the accumulation of stress-responsive transcripts containing introns. Subsequent exposure to heat triggers the correct splicing of these transcripts and the production of the corresponding stress-responsive proteins (Ling et al. 2018, 2021).

Very little is known about the potential contribution of other post-transcriptional regulatory mechanisms (i.e. mRNA decay and translation) to priming and PSM. A recent report using yeast cells showed that both nuclear and cytoplasmic mRNA degradation contribute to gene expression memory (Li et al. 2023), but a similar role for mRNA decay in plants has not yet been explored. However, it has been reported that one of the fastest ways (within minutes) for plants to adapt their genetic program to rapidly fluctuating temperatures is to modulate global mRNA populations by inducing decay processes (Merret et al. 2013; Crisp et al. 2016). We have previously observed that a single brief heat stress can induce the partial decay of nearly 25% of the Arabidopsis transcriptome within a few minutes (Merret et al. 2013). This process, which is critical for plant survival, mainly targets "growth and development" functions and is likely to contribute to the newly established "heat stress" program. Another unexplored possibility is that heat stress simultaneously alters the ability of these destabilized mRNAs to produce corresponding proteins by reducing their translation efficiency. Thus, heat stress could not only reduce the global abundance of specific mRNAs by targeting them for degradation, but also reduce their capacity to produce corresponding proteins by limiting their translation efficiency. In contrast, the translation efficiency of preexisting heat stress-responsive mRNAs could be favored under these conditions.

Recently, it has been shown that polysomes-associated mRNAs can undergo 5'-3' exonucleolytic decay in a process called mRNA cotranslational decay (CTRD) (Pelechano et al. 2015). This process, discovered in yeast (Hu et al. 2009) but conserved in mammals and plants, affects all transcripts (Pelechano et al. 2015; Yu et al. 2016; Carpentier et al. 2020; Guo et al. 2023). It proceeds by decapping polysomal mRNAs, producing a 5'-monophosphate (5'P) end. The exonuclease XRN1/XRN4 then degrades the mRNAs as they are translated, following the last ribosomes. 5'P sequencing (5' P-seq) is an approach that allows the capture and sequencing of mRNA presenting a free 5'-phosphate end and is therefore used to measure CTRD intensity (Carpentier et al. 2021; Zhang and Pelechano 2021). A 3 nucleotide periodicity is observed for 5'P-seq reads (also called degradome reads), reflecting the protection provided by elongating ribosomes. There is also a general accumulation of reads 16-17 nucleotides upstream of stop codons due to translation termination, which is slower than elongation. Because 5'P-seq can reveal ribosome footprints in vivo, it can also be used to assess ribosome dynamics at the initiation, elongation, and termination steps (Nersisyan et al. 2020; Carpentier et al. 2021; Zhang and Pelechano 2021). Although 5'P-seq reads can also

result from other processes, such as miRNA cleavage (German et al. 2008), decapped mRNAs (Nagarajan et al. 2019), mRNAs decay while bound by the exon junction complex (Han et al. 2023) or cleavage by endonucleases (Nagarajan et al. 2023), the three-nucleotide periodicity observed for 5'P-seq reads is a strong indication that CTRD products are dominant in 5'P-seq reads, particularly in a wild-type (i.e. XRN4 functional) background. The discovery of the CTRD process also means that the translation efficiency of a given mRNA is best measured as the ratio of its amount in polysomes divided by the number of molecules actively degraded by CTRD, rather than by its amount in polysomes divided by its total amount (Carpentier et al. 2020). However, it is not yet clear whether CTRDs represent a regulatory mechanism that could regulate translational output independently of the total amount of mRNA in polysomes and whether this process could contribute to priming and PSM.

The aim of this work is to evaluate the importance of translation and CTRD in the regulation of plant gene expression under two heat stress regimes with or without priming. We found that priming preserves the global translational potential of the plant and differentially affects the translational efficiency of stress and nonstress-related genes. We also found that priming is essential for upregulating the UPR pathway and protecting ER-associated mRNA from CTRD. Finally, we provide evidence that CTRD intensity is not simply a consequence of more or less association with polysomes but acts independently during heat stress to regulate the expression of more than a thousand genes.

## Results

### Effect of priming on the global translational potential of plants

Variations in polysome gradient profiles are often used as a proxy to assess the overall translational potential at different developmental stages or environmental conditions (Chassé et al. 2017). In a first attempt to measure the effect of priming on the global translational potential of plants, we used polysome gradient profiles to assess polysome levels at different time points of two heat stress regimes, with and without a priming event (Fig. 1A). The Short-Acquired Thermotolerance (SAT) and Basal Thermotolerance (BT) heat stress regimes have previously been used to study the physiological effects of priming (Yeh et al. 2012). For the SAT regime (Fig. 1A), Arabidopsis plants were grown in vitro for 5 days at 20 °C and collected 5 h after daylight, just before exposure to the 1-hour 37 °C priming event (p1). Plants were also collected after 15 min at 37 °C (p2), after 2 h recovery at 20 °C (p3), after 15 min of the 30 min 44 °C heat stress period (p4), and after 7.5 h recovery at 20 °C (p5). For the BT regime (Fig. 1A), plants were collected before the 30 min 44 °C heat stress period (pA), after 15 min at 44 °C (pB), and after 7.5 h recovery at 20 °C (pC). We chose to examine polysomal processes 15 min post-stress because we estimate that this time point will capture a maximum of the mRNA-related regulatory changes that occurred during the switch from the normal (20 °C) growth and developmental program to the 37 °C and/or 44 °C heat stress response program. We have previously observed that post-transcriptional regulation of mRNAs is important for the rapid reprogramming of gene expression (Merret et al. 2013), and by placing us at the end of the two stress periods (1 h for the 37 °C stress and 30 min for the 44 °C stress), we run the risk of missing most of the very early events

Plants at p5 and pC as well as control plants (i.e. always grown at 20 °C) have the same global phenotype (Fig. 1B and Supplementary Fig. S1A). However, as expected (Yeh et al. 2012),
<figure><img src="image_2.png" /><figcaption>**Figure 1.** A 37 °C priming step positively affects polysome levels at 44 °C and during recovery. **A)** Scheme of SAT (Short-term Acquired Thermotolerance) and BT (Basal Thermotolerance) heat stress regimes (Yeh et al. 2012). Plant samples were collected at different times during SAT (p1 to p5) and BT (pA to pC). **SUB:** ribosome free subunits. **B)** Phenotype of seedlings after SAT or BT treatment at time point p5 and pC, 4 and 8 days after heat stress compared with control (same time points for plants always maintained at 20 °C). **C)** Estimation of the percentage of polysomes at the different time points of SAT and BT compared with the 20 °C situation (arbitrarily fixed at 100%). For each profile shown in (A), the amount of polysomes was normalized to the total amount of ribosomes (i.e. 40S, 60S monosomes and polysomes) and both values were estimated by measuring the corresponding area above the baseline in our sucrose gradient. Error bars represent the standard deviation (SD) of three biological replicates. All variations are significant (t-test *P* < 0.05) except where indicated (ns = not significant).</figcaption></figure>

plants exposed to SAT have better long-term survival than plants exposed to BT (Fig. 1B and Supplementary Fig. S1B). Four days after heat stress, most cotyledons of plants exposed to BT are bleached, while plants exposed to SAT show only reduced growth compared with the control without any bleaching effects (Fig. 1B and Supplementary Fig. S1). Eight days after heat stress, most cotyledons of BT plants are dead, but a substantial proportion of these plants can still recover (Fig. 1B) and produce new leaves after 10 days of recovery (Supplementary Fig. S1A). These results indicate that Arabidopsis (Col0) can survive both heat stress regimes, but in contrasting ways.

Next, we generated polysome profiles using sucrose gradient sedimentation and OD<sub>254nm</sub> measurements for each time point of SAT and BT and measured the proportion of polysomes at each time point compared with the 20 °C condition (Fig. 1, A and C). As expected, heat stress induces a decrease in translational activity by dissociating polysomes from mRNA (Merret et al. 2015). Treatment at 37 °C for 15 min (p2) induces a decrease in polysomes to approximately 25% of the amount present at 20 °C. However, after 2 h at 20 °C (p3), plants are able to recover almost the total amount of polysomes present in the initial 20 °C control condition as previously described (Merret et al. 2017).

Interestingly, when we compared polysomes present in plants exposed to 44 °C for 15 min after priming at 37 °C (Fig. 1C, p4 blue) or without priming (Fig. 1C, pB red), we observed that polysome levels are significantly higher in the primed condition (P-value < 0.05). This suggests that the 37 °C priming step somehow protects the translational potential of the plant by limiting polysome dissociation at 44 °C. However, the most striking effect is observed after 7.5 h of recovery at 20 °C. In the primed condition (p5, blue), polysomes are

back to about 75% of the amount found in the 20 °C control condition. However, this significant recovery is not observed in the nonprimed condition (pC, red), where the polysome levels are still low and identical to the stressed 44 °C condition (compare pB and pC). This result suggests that without priming, plants exposed to 44 °C for 30 min cannot recover their translational potential after 7.5 h at 20 °C and are probably still in a stressed state.

As described previously (Garre et al. 2018), we also used our degradome 5'P-seq data (see Supplementary Table S1) to monitor plant translational potential via SAT and BT (Fig. 2). In the degradome 5'P-seq meta-analysis, an increased amount of protected fragments upstream of the start codon and a decreased amount of the 16–17 nt peak upstream of the stop codons are diagnostic of reduced translational potential (Garre et al. 2018). This is what is observed at 37 °C (p2) with a return to an almost normal situation after 2 h of recovery at 20 °C (p3) (Fig. 2A). At 44 °C, a strong reduction in translation is observed for both situations (p4 and pB), with a slightly stronger effect for pB (Fig. 2B). After 7.5 h at 20 °C without priming, translation is still mainly down (pC), but is functional again at p5, although at a lower level than the initial 20 °C situation (Fig. 2C). These 5'P-seq results are consistent with our polysome profile quantification data, confirming that priming has a strong positive effect on the overall translational potential of plants in response to severe heat stress.

## Genome-wide analyses of the effect of priming on gene regulation: how important are polysome-related processes?

Next, we wanted to evaluate the importance of polysome-related processes (translation and CTRD) in the regulation of gene
<figure><img src="image_3.png" /><figcaption>**Figure 2.** Degradome 5'P-seq meta-analysis confirms the positive impact of priming on general translation levels. Meta-analysis of our degradome 5' P-seq data. An increased amount of protected fragments upstream of the start codon and a decreased amount of the 16-17 nt peak upstream of the stop codons are diagnostic of reduced translation potential (Garre et al. 2018). A) This is what is observed at 37 °C (p2) with a return to a near normal situation after 2 h of recovery at 20 °C (p3). B) At 44 °C a strong reduction of translation is observed for both situations (p4 and pB) with a slightly stronger effect for pB. C) After 7.5 h at 20 °C without priming, translation is still mainly down (pC), but in p5 translation has resumed, although at a lower level than in the initial 20 °C situation. Overall, the 5'P-seq results (A to C) confirm the polysome quantification data (Fig. 1C). RPM, reads per million.</figcaption></figure>

expression at different steps of SAT and BT heat stress. To this end, we performed a multiomics approach using a triple NGS strategy to analyze RNA samples collected at each SAT and BT time point (p1 to p5 and pA to pC) (see Supplementary Figs. S2 and S3 for a description of the experimental design and filtering strategy). We used an mRNA-seq approach to measure steady-state total mRNA levels, a polysomal mRNA-seq strategy to measure the global amount of mRNA associated with polysomes, and a degradome 5'P-seq approach to measure the amount of CTRD products (Fig. 3A, in blue, green, and red, respectively). A Principal Component Analysis (PCA) was used to evaluate the quality of the replicates (Supplementary Fig. S4). The TPM values corresponding to the three replicates of all selected genes in the three databases are available in Supplementary Table S1.

While most studies use polysomal mRNA-seq divided by total mRNA-seq to directly assess translation efficiency (TE), the ratio of polysomal mRNA-seq to degradome 5'P-seq data provides a more realistic assessment of TE (Carpentier et al. 2020). Furthermore, the use of degradome data should allow us to determine whether CTRD represent an independent gene regulatory process or are merely a consequence of association with ribosomes.

To compare variations in the distribution of mRNAs produced by the same set of genes in SAT and BT, we decided to apply a filter to retain only those mRNAs that were present in one or more TPM (mean of replicates) in all conditions (p1 to p5 and pA to pC) (see Supplementary Fig. S3). Of these, 13,123 genes were retained and used for further analysis (representing 50.3% of the total number of Arabidopsis nuclear genes). GO analysis of these 13,123 genes revealed that they are enriched in general functions involved in development and growth (i.e. major GO/Molecular Function terms: catalytic activity 10<sup>E-104</sup>, structural molecule activity 10<sup>E-52</sup>, structural component of ribosomes 10<sup>E-34</sup>; major GO/Biological Process terms: Metabolic process 10<sup>E-112</sup>, Cellular component organization 10<sup>E-88</sup>). This is to be expected in such a meta-analysis, as stress-responsive genes are in minority compared with other nonstress-responsive functions, and some stress-responsive genes will be filtered out of our gene set because they are not present in at least one or more TPM in all conditions.

Using these 13,123 mRNAs, we performed a meta-analysis of their distribution compared with control distributions at 20 °C (Fig. 3A). This allowed us to measure variations in the distribution of total mRNAs, polysome-associated mRNAs and cotranslational
<figure><img src="image_4.png" /><figcaption>**Figure 3.** Variation in the distribution of total mRNAs, polysome-associated mRNAs, cotranslational degradation (CTRD) products and translation efficiency levels at different time points of the short-term acquired thermotolerance (SAT) and Basal Thermotolerance (BT) heat stress regimes. **A)** Distribution [log2 (TPM ratio)] of a set of 13,123 gene products present in at least 1 TPM in all conditions (mean of three replicates) at different SAT and BT time points compared with the p1 situation [log2(TPM ratio) = 0]. The distribution of total mRNAs is shown in blue, polysome-associated mRNAs in brown and CTRD products in red. For p4/pB (44 °C) and p5/pC (20 °C recovery), pale colored boxplots represent unprimed conditions (pB and pC) and dark colored boxplots represent primed conditions (p4 and p5). **B)** Variation in translation efficiency (polysomal mRNAs divided by degradation products) for the set of 13,123 genes used in (A) at different SAT and BT time points compared with the p1 situation. For panels (A) and (B), a Kolmogorov test was used to determine whether the distributions were different from P1 (stars above distributions) and Wilcoxon test was used to compare primed and unprimed distributions (brackets above distribution pair). (\*P < 0.05, \*\*P < 0.01, \*\*\*P < 0.001). For each boxplot, the center line represents the median; the lower and upper limit of the boxes represent, respectively, the first and third quartiles. The whiskers represent 1.5-fold of the interquartile range. Outlier points are not represented.</figcaption></figure>

degradation products, thought to be SAT and BT. To validate that CTRD produces the majority of 5'P-seq reads, we compared the distribution of global 5'P-seq reads with reads found exactly at position 16-17 nt before the stop codon (reads that can only be strictly attributed to CTRD) (Supplementary Fig. S5). To do so we used the translational termination stalling index (TSI) defined as the ratio of the number of 5'P read ends at the ribosome boundary (16 to 17 nt upstream from stop codon) to the mean number of 5'P read ends within the flanking 100 nt (Guo et al. 2023; Carpentier et al. 2024). We show that the distributions generated using the two datasets follow the same trend, confirming that CTRD products are dominant in the global 5'P-seq database in a wild-type (i.e. XRN4 functional) background. The specific effect of priming was also evaluated.

After 15 min exposure at 37 °C (p2), there is a general tendency for a rapid decrease in the steady-state global mRNA levels

compared with the 20 °C condition. As previously reported, this decrease is probably due to a general increase in global mRNA decay during heat stress, mainly targeting general functions involved in development and growth (Merret et al. 2013). We also observed a corresponding reduction in polysome-associated mRNAs and a smaller reduction in CTRD products, resulting in a reduced TE level (Fig. 3B, p1 vs. p2). This result shows that the previously observed decay at 37 °C of a significant proportion of mRNAs (mainly involved in development and growth) is likely to correspond with a global reduction in their translational efficiency. Interestingly, after 2 h of recovery at 20 °C (p3), global and polysome-associated mRNA levels are almost back to their initial levels, while the rate of CTRD remains low. These results challenge the idea that CTRD is a passive mechanism that simply follows the rate of binding to polysomes and support the hypothesis that CTRD is an active/independent regulatory mechanism.
Indeed, under these conditions, keeping the CTRD low while increasing the level of polysome-associated mRNA is a way to increase TE to even higher levels than in the initial 20 °C situation (see p3 in Fig. 3B, compare p1 with p3).

At 44 °C, as at 37 °C, a general reduction is observed for the three distributions in the unprimed (pB, pale colors) and primed (p4, dark colors) conditions (Fig. 3A). At this temperature, the strongest effect of priming is observed for polysome-associated mRNAs, whose level is lower compared with the unprimed condition while the opposite is true for CTRD. Priming therefore acts by lowering the TE of our gene set at 44 °C, a regulation that is less efficient without the priming step (Fig. 3B, compare p1 with p4 and p1 with pB). After 7.5 h of recovery at 20 °C, the effect of priming (p5, dark colors) is very strong (Fig. 3A). In the primed SAT regime, global and polysome-associated mRNA as well as CTRD are increased, resulting in a TE almost back to the initial 20 °C condition (p5 in Fig. 3B). In the unprimed BT regime (pC, pale colors), global and polysome-associated mRNA levels are still down (almost identical to the 44 °C situation), while CTRD increases, leading to a decrease in TE (pC, Fig. 3B). Again, polysomal mRNA levels and CTRD variations are anticorrelated, supporting the hypothesis that both processes could operate independently. We conclude that priming has a significant effect on gene expression, in part by decreasing the TE of our gene set (mainly nonstress-related genes) at 44 °C and increasing it during the recovery period.

## Effect of priming on heat stress-responsive genes

Another way in which priming could affect gene expression is by affecting the global composition of heat-inducible mRNAs that are upregulated at 44 °C. To test this, we first selected from our 13,123 mRNAs in Fig. 3 those that have a higher global steady-state level at 44 °C (compared with the 20 °C control condition) in a primed (N=729) or unprimed (N=197) regime. Surprisingly, a Venn diagram revealed that only 108 of these mRNAs are common to the primed and unprimed conditions (Fig. 4A), demonstrating that the priming step has a very strong influence on the composition of heat-inducible mRNA populations after 15 min exposure to 44 °C. GO analysis of these common mRNAs identified "response to temperature stimulus" (GO: 0009266 P-value 7.28 10<sup>E-38</sup>) and "response to heat" (GO: 0009408, P-value 5.46 10<sup>-37</sup>) as the most statistically supported GO terms. A closer look revealed that mRNAs of genes involved in the CPR, a subcomponent of the general heat stress response (Sugio et al. 2009), were particularly enriched in this group (including HSP101, cytosolic HSP70s, HSP90s, and HSP20s-like; see Supplementary Fig. S6A and Table S2). The CPR is induced by the accumulation of misfolded proteins in the cytosolic compartment and regulates protein folding and degradation, especially after stress.

A similar GO analysis, this time on the 621 genes whose mRNAs specifically accumulate after priming, revealed that "protein folding" (GO:0006457, P-value 8.38 10<sup>-17</sup>) and "response to endoplasmic reticulum stress" (GO:0034976, P-value 9.73 10<sup>-14</sup>) are the most statistically supported GO terms. Major UPR players such as key regulators (Arabidopsis basic leucine zipper 60 (AtbZIP60); ANAC089), key chaperones (binding protein (BIP)1 and 2, CALNEXIN 1 and 2, SHEPERD) and key members of the ER-associated protein degradation (ERAD) system (HMG-CoA reductase degradation protein 1 (HRD1), DERLIN-1, cell division cycle 48 (CDC48) and ubiquitin-specific protease 6 (UBP6)) are found in this group (Supplementary Fig. S6B and Table S2). This result suggests that 15 min of 44 °C stress can induce the general and CPR heat stress response, at least at the

global mRNA level, but that a previous 37 °C priming event is required to additionally induce the UPR response.

GO analysis of the 89 genes whose mRNAs specifically accumulate without priming shows that "response to decreased oxygen levels" (GO:0036294, P-value 2.93 10<sup>-11</sup>) and "response to stress" (GO:006950, P-value 1.14 10<sup>-10</sup>) are among the most supported terms (Supplementary Table S2). Note that only two of these 89 genes can be directly associated with heat stress, suggesting that the 44 °C stress, without priming, increases the range of stress-related genes induced.

We next decided to determine whether or not the observed increase in global mRNA levels at 44 °C in SAT and BT was correlated with a corresponding increase in translational efficiency. For the 621 mRNAs whose accumulation is dependent on a priming event, the increase in steady-state mRNA levels at 44 °C is associated with an increase in polysome-associated mRNAs and degradome fragments (p4, Fig. 4B), leading to a small but significant (P-value < 0.05) global increase in TE compared with the 20 °C situation (Fig. 4C, compare p1 with p4). This is in sharp contrast to the situation of nonstress-related genes, whose steady-state levels and translational efficiency are both downregulated at 44 °C (Fig. 3). We then focused on this subset of mRNAs throughout the SAT (Fig. 4B). Surprisingly, we observed that in contrast to the 44 °C situation (p4), these mRNAs do not show an increase in steady-state mRNA levels at 37 °C (p2). However, they show a strong increase in TE (Fig. 4C, compare p1 with p2), which is mainly due to a strong increase in mRNA-polysome association without a corresponding increase in cotranslational degradation products (p2, Fig. 4B). Therefore, the upregulation of these genes at 37 °C is only due to positive regulation at the translational level, a situation not detectable by simple transcriptomic analysis. This situation also illustrates again that CTRD is not the simple consequence of being associated with polysomes, since in this case the increase in polysomal mRNA does not lead to an increase in CTRD products. In the first recovery period (p3), all three distributions are up with a TE back to the initial 20 °C situation (Fig. 4, B and C). The strong increase in steady-state mRNA levels observed in this first recovery period (p3) is likely due to positive feedback from at least some of the mRNAs that were massively involved in polysomes at 37 °C (P2) (Fig. 4B). In the final recovery period (7.5 h at 20 °C, P5), all three distributions are still up, but TE is back to its initial level (p1), probably as the plants gradually switch from stress to a more balanced genetic program.

In contrast to the 621 mRNAs, the 108 mRNAs that globally accumulate to a higher level at 44 °C in the SAT and BT regime (Fig. 4D, pB/p4) do the same at 37 °C (Fig. 4D, p2). Furthermore, the TE level of these genes is increased at all stages of SAT and BT, with a higher increase in the unprimed (BT) condition compared with the primed (SAT) condition (Fig. 4E). This higher increase in TE in the unprimed condition is mainly due to a lower level of CTRD degradation fragments compared with the primed condition at 44 °C (pB/p4) and during the recovery period (pC/p5) (Fig. 4D).

Finally, looking at the 89 mRNAs whose accumulation only occurs at 44 °C in the BT regime (without priming), we observed an increase in TE (pB in Fig. 4G), mainly due to a strong increase in the association of mRNAs in polysomes combined with the stability of the degradome fragments (pB in Fig. 4F). During the recovery period (pC), the TE of these genes are still increased compared with the initial situation at 20 °C (Fig. 4G).

We conclude that the increase in global mRNA levels observed at 44 °C in either SAT or BT is associated with an increase in TE, which is likely to lead to an increase in the production of corresponding heat stress-responsive proteins.
<figure><img src="image_5.png" /><figcaption>**Figure 4.** Effect of a 37 °C priming step on mRNA populations and translation efficiency levels after 15 min of 44 °C exposure. A) Venn diagram showing the number of mRNAs whose steady-state level is increased at 44 °C after priming (p4), without priming (pB) and at the intersection of the two conditions. Only mRNAs with at least 1 TPM in all Short-term Acquired Thermotolerance (SAT) and Basal Thermotolerance (BT) points were considered as starting material (see Supplementary Fig. S3). B) Distribution (log2(TPM ratio)) of a set of 621 mRNAs (only at 44 °C after priming) at different SAT time points compared with the p1 situation (log2(TPM ratio) = 0). C) Boxplots showing the variation in translation efficiency (TE) of the 621 mRNAs during SAT (compared with p1). D) Distribution (log2(TPM ratio)) of a set of 108 mRNAs (up at 44 °C with or without priming) at different SAT (dark colors) or BT (pale colors) time points compared with the p1 situation (log2(TPM ratio) = 0). E) Boxplots showing the variation of TE (compared with p1) of the 108 mRNAs during SAT (dark colors) and BT (pale colors). F) Distribution (log2(TPM ratio)) of a set of 89 mRNAs (only up to 44 °C without priming) at different BT time points compared with the p1 situation (log2(TPM ratio) = 0). G) Boxplots showing the variation in TE (compared with p1) of the 89 mRNAs throughout the BT regime. The distribution of total mRNAs is shown in blue, polysome-associated mRNAs in brown and cotranslational decay (CTRD) products in red. A Kolmogorov test was used to determine whether the distributions were different from p1 (20 °C) (stars above each distribution), and a Wilcoxon test was used to compare primed and unprimed distributions (brackets above distribution pairs). In all cases, p1 was used as the reference, as p1 and pA were compared and found to be equivalent (E). For each boxplot, the center line represents the median; the lower and upper limit of the boxes represent, respectively, the first and third quartiles. The whiskers represent 1.5-fold of the interquartile range. Outlier points are not represented. (\*P < 0.05, \*\*P < 0.01, \*\*\*P < 0.001).</figcaption></figure>

## Cotranslational decay regulates different subsets of transcripts during heat stress and recovery

Since we observed that CTRD does not necessarily correlate with mRNA levels in polysomes (Figs. 3 and 4), we wondered to what extent CTRD could be used as a major mechanism to regulate gene

expression in our two heat stress regimes. To answer this question, we applied a new filter to our initial mRNA set (N = 13,123), retaining only those mRNAs whose steady-state levels do not vary significantly during SAT and BT. This dataset (N = 7,929) was further subdivided into a new dataset, which we named
<figure><img src="image_6.png" /><figcaption>**Figure 5.** Cotranslational decay (CTRD) regulates different subsets of transcripts during heat stress and recovery. A) Heat map of CTRD levels for the main targets of the CTRD pathway (N = 1,126) at different stages of Short-term Acquired Thermotolerance (SAT) and Basal Thermotolerance (BT) stress. Data are normalized to 20 °C; red and yellow correspond to higher and lower CTRD levels, respectively, compared with the 20 °C situation. B) Boxplots showing the distribution of CTRD fragments of mRNAs from cluster 4 (N = 258) at 44 °C in BT (pB) and SAT (p4). C) Boxplots showing the distribution of CTRD fragments of all mRNAs associated with the GO term "endoplasmic reticulum" (N = 944) present in our initial dataset. D) HSP70 binding score of nascent peptides (10 to 80 aa) predicted for cluster 4 mRNAs (violet) and a control dataset consisting of 258 randomly selected mRNAs (green). E) Hydrophobicity scores of nascent peptides (10 to 80 aa) predicted for cluster 4 mRNAs (violet) and a control data set consisting of 258 randomly selected mRNAs (green). F) Western blot detection of XRN4 at 20 °C (p1) and 44 °C in input and polysomes fractions for SAT (p4) and BT (pB). An antibody against RPL13 was used as a loading control G) Boxplot showing the values for the four biological replicates of XRN4 (western blot). For each replicate, an equivalent amount of material was loaded for the input and polysome fractions and the amount of XRN4 was normalized using the RPL13 signal. For (B) and (C), a Kolmogorov test was used to determine whether the distributions were different from p1 (20 °C) (stars above distributions). For (D) and (E), a t-test was used to determine significant variation between the two sets of genes (P-value = 2.64e-24 for (D) and 3.19e-15 for (E)). For (G), a Wilcoxon test was used to assess the significance of the difference between distributions. For (B), (C), and (G), \*P < 0.05, \*\*P < 0.01, \*\*\*P < 0.001, and ns = not significant. For each boxplot, the center line represents the median; the lower and upper limit of the boxes represent, respectively, the first and third quartiles. The whiskers represent 1.5-fold of the interquartile range. Outlier points are not represented.</figcaption></figure>

CTRD-DB. For the CTRD-DB, we removed all transcripts that were differentially regulated in the polysomal mRNA database in at least one time point of SAT and BT (i.e. 3,929 transcripts). From the remaining 4,000 transcripts, we retained only those whose abundance in the degradome database was significantly altered (compared with the 20 °C control) in at least one SAT or BT step (p2 to p5 and/or pB to pC). We considered these selected 1,126 transcripts to be the main targets of the CTRD pathway, as their levels only vary significantly in the degradome database during SAT and BT (see Supplementary Fig. S3).

Using the CTRD-DB, we generated a heat map to visualize how these mRNA clusters and their CTRD levels vary during SAT and BT (Fig. 5A). We found three significant clusters that

were differentially regulated by CTRD. Cluster 1 mRNAs (N = 601) are mainly degraded by CTRD during the 7.5 h recovery period, more so in SAT (p5) compared with BT (pC), while they are mostly preserved from CTRD at 44 °C (pB/p4). GO analysis revealed an enrichment in this cluster for genes whose end products are localized in chloroplasts (GO: 0009507, 8.64 10<sup>E-54</sup>) and involved in small molecule metabolism (GO: 0044281, 4.68 10<sup>E-27</sup>). Cluster 2 mRNAs (N = 222) are preferentially targeted by CTRD at 37 °C but not at 44 °C. GO analysis again revealed an enrichment for genes whose end products are localized in chloroplasts (GO: 0009507, 1.24 10<sup>E-49</sup>) and are involved in the generation of precursor metabolites and energy (GO: 0006091, 5.62 10<sup>E-19</sup>).
Cluster 4 is particularly interesting as it shows a clear difference in CTRD targeting at 44 °C between SAT and BT (Fig. 5A). Indeed, cluster 4 contains 258 transcripts that are actively targeted by CTRD at 44 °C in the BT regime (without priming) but not in the SAT regime (with priming) (compare cluster 4, pB and p4). GO analysis revealed that cluster 4 gene products are mainly localized in the endomembrane system (GO:0012505 endomembrane system, P-value 1.02 10<sup>E-18</sup>) and more specifically in the ER (GO:0005783, P-value 7.93 10<sup>E-16</sup>). A boxplot analysis of these 258 mRNAs confirms that they are degraded much more in BT than in SAT at 44 °C (Fig. 5B).

Previous work in human and mouse cell lines, as well as in Arabidopsis, has established a clear link between severe heat stress and early elongation ribosome pausing (when the nascent peptide emerges from the ribosomal exit tunnel), especially when this peptide is hydrophobic (Liu et al. 2013; Shalgi et al. 2013; Merret et al. 2015). This pause is likely due to the redistribution of HSP70 chaperones away from ribosomes during heat stress, as it can be alleviated by HSP70 overexpression or exacerbated by HSP70 inhibitors (Liu et al. 2013; Shalgi et al. 2013; Merret et al. 2015). Hydrophobic nascent peptides are more dependent on HSP70s for proper folding and are therefore more affected by this pausing step. Since ribosome pausing is associated with the induction of CTRD and cluster 4 mRNAs are major targets of CTRD after severe heat stress in the absence of priming (Fig. 5A), we decided to determine the HSP70 affinity (Fig. 5D) and hydrophobicity scores (Fig. 5E) of cluster 4 N-terminal peptides. We observed that cluster 4 genes encode highly hydrophobic nascent peptides with high HSP70 scores (Fig. 5, D and E). This result suggests that the high hydrophobicity of cluster 4 nascent peptides and their high requirement for HSP70s is probably the reason why they are preferential targets of CTRD at 44 °C in the BT regime. But why does priming prevent this in the SAT regime? We have shown in this study that priming is necessary to induce the UPR response at 44 °C, including the upregulation of ER-specific HSP70s (Bip1 and Bip2) (Fig. 4; Supplementary Fig. S6B and Table S2). This increase in ER-specific HSP70s could limit ribosome pausing, explaining why CTRD is alleviated in the SAT regime for cluster 4 mRNAs. This conclusion is supported by western blot analysis showing that XRN4, the major CTRD enzyme (Merret et al. 2015), localizes more efficiently to polysomes at 44 °C in BT compared with SAT (Fig. 5, F and G), while its mRNA level does not accumulate differently in the three databases at any point of both heat stress regimes (SAT and BT), with a single exception (p5, up in the degradome database, Supplementary Fig. S6C).

Finally, we decided to see if this finding using cluster 4 genes could be generalized to all mRNAs in our initial dataset (N=13,123) that are annotated as being translated in the ER (N=944). We observed that indeed all ER-translated mRNAs are more efficiently targeted by CTRD in BT compared with SAT (Fig. 5C). This suggests that although cluster 4 mRNAs are major targets of CTRD during BT, most mRNAs translated in the ER are likely to be at least partially regulated by CTRD in the same heat stress regime.

## Changes in CTRD levels at 44 °C between primed and unprimed conditions result in corresponding changes in protein levels during the recovery period

If CTRD can act as an independent gene regulatory mechanism, we should expect that specific mRNA degradation by CTRD should, at

least in some cases, lead to a corresponding decrease in protein accumulation. We selected four genes whose corresponding mRNA is targeted by CTRD at 44 °C in BT but not in SAT (i.e. part of cluster 4 in Fig. 5) and monitored their protein level during the recovery period using western blots (Fig. 6). Although no significant difference in protein level was observed at 44 °C between SAT and BT, a significant reduction was observed in the recovery period of the BT versus SAT regime (Fig. 6). Since the global steady-state and polysomal levels of these mRNAs are unchanged throughout SAT and BT, and the only significant difference is in the degradome 5'P-seq database at 44 °C, the differences in protein accumulation observed in the recovery period are likely due to the variation in CTRD levels between the primed and unprimed conditions.

## Discussion

Thermotolerance (also known as priming) is a well-known phenomenon discovered more than 40 years ago and defined as the ability of a mild heat shock treatment to protect cultured human cells from a more severe one (Gerner and Schneider 1975). Mild heat shock has been shown in several animal cell culture systems to be important for the induction of HSP70 chaperones (Lindquist 1981) and the stimulation of translation under severe heat shock conditions (Lindquist 1980), two important features of thermotolerance. More recently, it has been shown in mouse cells that pretreatment with mild heat stress limits the ribosome pausing effect induced by more severe heat stress (Shalgi et al. 2013). Thermotolerance has also been well studied in plants, particularly the transcriptional regulation of heat shock proteins and their impact on plant survival (Martinez-Medina et al. 2016; Mauch-Mani et al. 2017; Charng et al. 2023). In this work, we used a multiomics approach with a three-pronged NGS strategy to investigate the role of polysome-related processes (translation and cotranslational decay) in the acquisition of plant thermotolerance. First, using polysome gradient quantification and meta-analysis of degradome 5'P-seq data, we show that priming has a small positive effect on global translation in plants at 44 °C, but a much stronger effect in the early recovery period (Figs. 1 and 2). This priming-dependent spectacular rescue of plant translation potential only 7.5 h after severe heat stress was unexpected and is likely to be involved in the better long-term survival of plants exposed to SAT compared with BT. Indeed, the early increase in translation potential (almost to its 20 °C level) is likely to be the key to restoring the growth and development program in SAT plants. This "solution" is not available to BT plants, which at the same time still have a very low translation potential (identical to the 44 °C condition).

To further elucidate the importance of polysome-related processes in the regulation of gene expression, we generated transcriptome (mRNA-seq), translatome (polysome mRNA-seq), and degradome (5'P-seq) databases at all stages of the SAT and BT heat stress regimes. We started with a large dataset of genes that produce mRNAs that are present in at least 1 TPM at all SAT and BT steps (N=13,123). This allowed us to monitor the regulatory behavior of ubiquitously expressed, mainly nonstress-related genes at the 5-day seedling development stage. As expected, we found that the steady-state levels of these mRNAs decrease at 37 °C, reflecting the decay process previously described under these conditions (Merret et al. 2013). Here, we show that this decrease in steady-state mRNA levels is associated with a significant decrease in translational efficiency (Fig. 3). We suggest that down-regulation of these mRNAs at the translational level, rather than simply reducing their levels by decay, is important
<figure><img src="image_7.png" /><figcaption>**Figure 6.** Targeted mRNA degradation by cotranslational decay (CTRD) at 44 °C leads to the production of less protein in the Basal Thermotolerance (BT) recovery period. Western blots were used to assess the relative accumulation of four proteins [SOS1 (AT2G01980), PDAT1 (AT5G13640), PMT5 (AT3G18830), and NCL (AT1G53210)] coded by cluster 4 mRNAs, targeted by CTRD at 44 °C in BT but not in Short-term Acquired Thermotolerance (SAT). Histograms representing the degradome 5'P-seq ratio at 44 °C (pB (BT) and p4 (SAT)) for these mRNAs are presented on the left of each panel (log2 of the ratio compared with 20 °C, values correspond to the mean of three biological replicates and error bars represent the standard deviation of these three biological replicates). For the western blot analyses (1 of 5 to 6 replicates shown), an equivalent amount of total protein was loaded and the amount of protein was normalized to the ACTIN signal for SOS1, PDAT1, and PMT5 and to RPL13 for NCL. Boxplots were used to show variations in protein steady-state level at 44 °C (pB (BT) and p4 (SAT)) and 4 h recovery after SAT (primed) or BT (not-primed) compared with the 20 °C condition. For each boxplot, the center line represents the median; the lower and upper limit of the boxes represent, respectively, the first and third quartiles. The whiskers represent 1.5-fold of the interquartile range. Outlier points are not represented. Wilcoxon tests were used to compare conditions ("P < 0.05, **P < 0.01, ***P < 0.001, ns = not significant).</figcaption></figure>

for switching from the "growth and development" to the "heat stress" program within minutes of exposure to 37 °C. At 44 °C, translation efficiency is again reduced, with a stronger effect for SAT than for BT, but the strongest effect of priming is in the recovery period, where translation efficiency can return almost to its 20 °C level, a situation not observed for BT (Fig. 3). In the SAT regime, the rescue of translation efficiency observed in our mRNA dataset, combined with the strong overall increase in plant translation potential at this stage (Figs. 1 and 2), is likely to be important for restarting the "growth and development" program.

We next used the same strategy, but this time focusing on ubiquitously expressed genes whose steady-state level is significantly increased at 44 °C in the SAT and/or BT. In contrast to the situation described above, these 44 °C heat stress-inducible mRNAs (N = 818) are not degraded at 37 °C and show a clear increase in translation efficiency (and not a decrease as seen for nonstress-related genes). An increase in translation efficiency is also observed at 44 °C, in combination with the observed increase in their global mRNA abundance. These results again point to a significant contribution of translation in positively regulating the onset of the
heat stress response. However, the mechanism by which translation efficiency is increased is not equivalent for mRNAs upregulated at 44 °C only in the SAT regime (N=621) compared with those regulated only by BT (N=89) or by both regimes (N=108) (Fig. 4A). Surprisingly, mRNAs upregulated at 44 °C only in the SAT regime are not upregulated at 37 °C in the mRNA-seq database (Fig. 4B). Nevertheless, the translation efficiency of these mRNAs is strongly enhanced due to their increased presence in the polysome without a corresponding increase in the corresponding degradation fragments (p2 in Fig. 4B). Thus, this population of mRNAs is only upregulated at the translational level after a single 37 °C exposure, a regulation that is not detectable by transcriptomic analysis. This 37 °C translational upregulation is likely to affect subsequent steps, as these mRNAs have increased steady-state levels in the first 20 °C recovery period (p3) and through the SAT. We conclude from these analyses (Figs. 3 and 4) that translation is an important regulatory step that contributes to the establishment of plant thermotolerance.

GO analysis of the 621 mRNAs that require priming for induction at 44 °C revealed that they include a large proportion of genes involved in the UPR pathway (Howell 2021) (Supplementary Table S2). In contrasts, the 108 mRNAs upregulated in both SAT and BT, which consist mainly of general heat stress genes and, more specifically, genes involved in the CPR pathway (Sugio et al. 2009) (Supplementary Table S2). This result suggests that the upregulation of the UPR in acute heat stress is dependent on a previous priming event, which is not the case for CPR. This is an unexpected consequence of priming that has not been previously documented and is likely to contribute to the thermotolerance property of the plant.

In this work, as previously recommended, we used a ratio between the translatome (polysome mRNA-seq) and degradome (5'P-seq) databases to better estimate translation efficiency (Carpentier et al. 2020). In addition, this allowed us to test whether the accumulation of CTRD fragments always correlated with the amount of mRNAs measured in polysomes. In many cases, we observed a clear anticorrelation between the amount of mRNAs detected in polysomes and the accumulation of the corresponding CTRD fragments (the most obvious situations are Fig. 3A, p2, p3, pC; Fig. 4B, p2; Fig. 4D, pB, pC; Fig. 4F, pB, pC). These observations suggest that CTRD is not simply a neutral consequence of the presence of mRNAs in polysomes but could be used as an independent mechanism to regulate gene expression. In support of this proposition, we found that 1,126 transcripts vary only during SAT and/or BT in the degradome (5'P-seq) database (Fig. 5), suggesting that these mRNAs are exclusively regulated by CTRD in our experimental setting. Among these preferential targets of CTRD, we found a group of mRNAs (Fig. 5, cluster 4) that are predominantly translated in the ER. These mRNAs are targeted by CTRD at 44 °C in BT but not in SAT (Fig. 5, A and B). We propose that this difference between SAT and BT results from the inability to induce the UPR pathway in BT and to increase the amount of HSP70s (BIPs) chaperones in the ER (see above). Indeed, cluster 4 mRNAs encode proteins with highly hydrophobic nascent peptides that require HSP70s for folding (Fig. 5, D and E). In SAT, the increased levels of BIPs in the ER due to UPR induction likely help to fold these hydrophobic nascent peptides, preventing ribosome pausing, and the induction of CTRD for these messages (Liu et al. 2013; Shalgi et al. 2013; Merret et al. 2015). This cannot occur in BT because the UPR pathway is not stimulated in this condition, leading to a higher level of CTRD. We also observed that the situation described for cluster 4 mRNAs, which are likely to be regulated only by CTRD in SAT/BT (N=258), can be extended to all

mRNAs translated in the ER (N=944) (Fig. 5C). In support of this model, we observed that XRN4, the major enzyme responsible for CTRD (Merret et al. 2015), is present at higher levels in the BT polysome at 44 °C compared with SAT (Fig. 5, F and G). The mRNAs in clusters 1 to 3 (Fig. 5A) do not share the characteristics found in cluster 4, and the reason why these mRNAs are also preferential targets of CTRD is unknown. One possibility is that tRNA populations, as well as their epitranscriptomic status, vary during SAT and BT and that translation of transcripts with specific codon bias is slowed (and CTRD increased) at some points in these heat stress regimes. Further work is required to test this hypothesis.

To experimentally validate our hypothesis that CTRD can regulate gene expression independently of other mechanisms, we use western blots to show that four cluster 4 mRNAs underacumulate their corresponding protein only during the BT recovery period (Fig. 6). This strong anticorrelation between CTRD intensity and protein production, while the global steady-state and polysomal levels of these mRNAs are unchanged throughout SAT and BT, makes it likely that CTRD is at the origin of this effect.

In conclusion, we show here that polysome-related processes (translation and CTRD) are important to regulate gene expression after heat stress with or without a priming event. We observed that induction of the UPR in acute heat stress requires a previous priming event at a milder temperature and that in the absence of priming, ER-translated mRNAs become preferential targets of CTRD. Finally, we present evidence that CTRD should be considered as a gene regulatory mechanism that does not necessarily correlate with mRNA polysome association.

# Materials and methods

## Plant material, growth conditions, and heat stress

In all experiments, the wild-type Columbia ecotype was used. Plants were grown in vitro for 5 days on synthetic Murashige and Skoog (MS) medium (MS0213, Duchefa) containing 1% sucrose and 0.8% plant agar at 20 °C under a 16 h light (120 µmol.m⁻².s⁻¹)/ 8 h dark cycle. Heat stress was applied in darkness by immersing the plates in a water bath. For SAT, plates were transferred from the in vitro chamber to the water bath for 1 h at 37 °C, then transferred back to the chamber for 2 h before returning to the water bath for 30 min at 44 °C. Plates were then returned to the chamber for recovery. For BT, plants were transferred directly from the chamber to the water bath for 30 min at 44 °C and then returned to the chamber for recovery. The different heat stresses were carried out in the dark and recovery was carried out under the same conditions as initial growth.

## Polysome gradients

Polysome profiling was performed as described previously (Merret et al. 2013). For polysome quantification, 100 mg ground powder (5-day-old seedlings) was incubated for 10 min on ice with 3 volumes of lysis buffer (200 mM Tris-HCl, pH: 9, 200 mM KCl, 25 mM EGTA, 35 mM MgCl2, 1% (v/v) detergent mixture [1% (v/v) Tween 20, 1% (v/v) Triton, 1% (w/v) Brij 35% and 1% (v/v) Igepal], 1% (w/v) sodium deoxycholate, 0.5% (w/v) polyoxyethylene tridecyl ether, 5 mM dithiothreitol, 50 µg mL⁻¹ cycloheximide, 50 µg mL⁻¹ chloramphenicol, and 1% (v/v) protease inhibitor cocktail (Sigma-Aldrich). The extract was centrifuged at 16,000 × g for 10 min, and 300 µL of the supernatant was loaded onto 9 mL 15–60% sucrose gradients. Ultracentrifugation was performed at 38,000 rpm (180,000 × g) for 3 h using an SW41 rotor (Beckman Coulter). Polysome profiles were recorded using an ISCO absorbance detector at 254 nm and
sucrose gradients were collected in 12 fractions of 650 µL each: fractions 1–4 containing free mRNPs, fractions 5–8 containing ribosomal subunits and monosomes and fractions 9–12 containing polysomes. Absorbance at 254 nm was recorded using PeakTrack software and polysome profiles were plotted using Excel. The total amount of ribosomes was evaluated by measuring the area between the 40S, 60S, monosomes and polysomes profile and the basal lines, while the number of polysomes was evaluated by measuring the area on the polysome portion of the profile only. The ratio of polysomes to total ribosomes at 20 °C was arbitrarily set to 100%. Values represent the mean of three biological replicates.

For polysome RNA extraction, 400 mg of ground powder (5-day seedlings) was used, following the same procedure as described above for purification of polysome fractions. The polysome fractions were pooled and SDS and EDTA were added to a final concentration of 0.1% and 4 mM, respectively. One volume of phenol/chloroform/isoamyl alcohol (25:24:1) was then added, the solution vortexed for 1 min and centrifuged at 16,000 × g for 15 min. The aqueous phase was retained and one volume of chloroform/isoamyl alcohol (25:1) was added, the solution was vortexed for 1 min and centrifuged at 16,000 × g for 15 min. The aqueous phase was retained, and 2 volumes of 100% ethanol were added, followed by centrifugation at 16,000 × g for 15 min. All centrifugations were performed at room temperature to avoid sucrose precipitation. The pellets were washed twice with 70% ethanol and resuspended in 30 µL of cold RNAse-free water.

## Total RNA extraction and NGS libraries

For total RNA extraction, 50 mg of ground powder (5 day seedlings) was used. One volume of 8 M guanidine hydrochloride solution buffered at pH 8.5 and one volume of phenol/chloroform/isoamyl alcohol (25:24:1) was added, the solution was vortexed for 1 min and centrifuged at 16,000 × g for 15 min. The aqueous phase was retained and one volume of chloroform/isoamyl alcohol (25:1) was added, the solution was vortexed for 1 min and centrifuged at 16,000 × g for 15 min. The aqueous phase was retained and 2 volumes of 100% ethanol were added followed by centrifugation at 16,000 × g for 15 min. The pellets were washed twice with 70% ethanol and resuspended in 50 µL of cold RNAse-free water.

All NGS experiments were performed in biological triplicates (i.e. different batches of seedlings collected and stressed at 1-week intervals), either on total RNA fractions or on polysomal RNA fractions (see above). All purified RNA extracts were DNAse treated using the Ambion Turbo DNAse Kit (Life Technology). Quantity and quality of RNA were assessed using the Qubit Agilent 2100 Bioanalyzer and Plant RNA Nano Chip, respectively.

For RNA-Seq (total and polysomal), 1 µg of RNA was used for RNA library preparation using either total or polysomal RNA. Libraries were prepared using a NEBNext Poly(A) mRNA Magnetic Isolation Module and a NEBNext Ultra II Directional RNA Library Prep Kit for Illumina (New England Biolabs, #E7760S/L).

Degradome (5'P-seq) libraries were prepared as previously described (Carpentier et al. 2021). Briefly, 50 µg of total RNA was subjected to two rounds of poly(A+) purification. After ligation of 5' adaptors, excess adaptors were removed by a new round of poly (A+) purification. Reverse transcription was performed using the SuperScript IV system according to the manufacturer's instructions. cDNAs were amplified by 11 cycles of PCR. Libraries were purified using SPRIselect beads prior to quality control and normalization. Library quality was checked using an Agilent High Sensitivity DNA Kit (Agilent). Libraries were normalized, multiplexed, and sequenced on NextSeq 550 (Illumina) in 75 pb single reads.

## Statistical analyses

All data presented were tested for normality using the Shapiro test. Depending on the result, a parametric or nonparametric test was used to compare significance between conditions. For quantification of polysome profiles (Fig. 1C), t-tests were performed to test for significant differences between conditions. For Figs. 3 and 4, two-sample Kolmogorov-Smirnov tests were used to determine whether distributions differed from p1 (20 °C), and Wilcoxon tests were used to compare distributions between primed and unprimed conditions (pB vs. p4 and pC vs. p5). For Fig. 5, B and C, two-sample Kolmogorov-Smirnov tests were used to compare distributions against p1 (20 °C). For Fig. 5, D and E, hydrophobicity and HSC/HSP70 scores were compared using a t-test. For Figs. 5G and 6, relative protein enrichments of western blots were compared using a Wilcoxon test. In Supplementary Fig. S1B, the comparison of the resistance index between control, primed and unprimed conditions was performed using a Wilcoxon test. All tests were performed using RStudio software.

## Bioinformatic analysis

Raw reads were trimmed using Trimmomatic v0.39 (Bolger et al. 2014). For RNA-Seq data, adapters and low-quality reads were removed. For 5'P-seq data, reads were trimmed to 50 nt. Trimmed reads were filtered from reads corresponding to chloroplast, mitochondrial, ribosomal, and small RNA sequences using bowtie2 v2.4.4 (Langmead and Salzberg 2012) in "sensitive-local" mode. The remaining reads were mapped to the TAIR10 genome and corresponding gtf file annotations (Araport11) using Hisat2 v2.2.1 (Kim et al. 2019) with default parameters. Only unique mapped reads were retained using samtools v1.13 with the "-q 10" option (Li et al. 2009). Read counts were performed using htseq-count v1.99.2 in "union" mode (Anders et al. 2015). Transcripts per million (TPM) values for each gene were calculated using the following methods: First, the read counts are divided by the length of each gene in kilobases (rpk), second, all rpk values in a sample are summed and divided by 1,000,000 ("per million" scaling factor), and third, the rpk values are divided by the scaling factor per million (TPM). For 5'P-seq data, unique alignment bam files are analyzed using the FivePSeq software (Nersisyan et al. 2020). Five TAIR10 chromosomes and Araport11 gtf are used as reference files.

A first filter was applied to the original dataset of 37,390 genes: only transcripts containing ≥1 TPM in all studied conditions (p1 to p5 and pA to pC) were retained, resulting in the dataset of 13,123 genes used in Figs. 2 to 4. The quality of replicates was determined by a PCA analysis. Differential gene expression (DEG) analysis was performed on this dataset using DESeq2 (BiocManager) for statistical analysis (P-value < 0.05). Only DEG genes with TPM fold-change (FC) values >2 at 44 °C (compared with 20 °C reference) were declared as significantly upregulated and used in Fig. 4.

To generate the CTRD-specific database of Fig. 5, DEGs (up or down) in the RNASeqTotal database (5,194 genes) or the RNA SeqPolysomal database (3,929 genes) were filtered out, resulting in a new dataset of 4,000 genes. A further DEG analysis was then performed on these 4,000 genes using the 5'P-seq database and 1,126 genes were found to be differentially regulated, retained and considered to be major targets of CTRD. All GO analyses were performed using the Gprofiler website (Raudvere et al. 2019).

## Heat map, hydrophobicity, and HSP70 scoring

Hydrophobicity and HSC/HSP70 scoring were performed as described previously (Shalgi et al. 2013). Protein sequences encoded
by cluster 4 (which are targets of CTRD at the pB step of BT) and a random population (of equal size; n = 258) were downloaded from TAIR10 and scores were calculated. Briefly, Kyte-Doolittle hydrophobicity scores and HSC/HSP70 binding scores were each calculated on 13 amino acid long windows shifted by one amino acid from the N-terminus to the C-terminus of the first 80 amino acids of each protein encoded by the two datasets examined (cluster 4 and random dataset). Mean values were calculated in each class from the values obtained for each gene, and the curves were fitted with the cubic spline interpolation mathematical function. A t-test was performed between each pair of populations.

## Western blot analyses

For polysomal-XRN4 western blots, proteins were extracted from sucrose fractions (1 to 12) after sucrose gradient sedimentation (see above) using 2 volumes of absolute ethanol. After 6 h of incubation at 4 °C and centrifugation, protein pellets were washed and resuspended in Laemmli 4x buffer [0.25 M Tris-HCl pH 6.8, 8% SDS (v/v), 40% glycerol (v/v) and 0.002% bromophenol blue (w/v), 5% beta-mercaptoethanol (v/v)]. For SOS1, PDAT1, NCL, and PMT5 western blots, proteins were extracted from 25 mg of powder by added 100 µL of Laemmli 4x buffer (0.25 M Tris-HCl pH 6.8, 8% SDS (v/v), 40% glycerol (v/v) and 0.002% bromophenol blue (w/v), 5% beta-mercaptoethanol (v/v)). After an incubation at 95 °C for 5 min, proteins were separated on SDS-PAGE gels and electrotransferred to polyvinylidene fluoride membranes. Immunoblotting was performed in Tris-buffered saline (TBS), 5% skimmed milk (w/v), 1% Tween (v/v). XRN4 primary antibody was diluted 1/5,000 (Merret et al. 2013) and incubated overnight at 4 °C with agitation. RPL13 primary antibody (Agrisera: AS13 2650) was diluted 1/2,500 and incubated overnight at 4 °C with agitation. ACTIN (Agrisera: AS21 4615), SOS1 (PhytoAB: PHY3582A), PDAT1 (PhytoAB: PHYY1871A), PMT5 (PhytoAB: P0854A), and NCL (PhytoAB: PHY2585S) primary antibodies were diluted 1/1,000 and incubated overnight at 4 °C with agitation. After incubation, the membranes were washed six times in TBS, 1% Tween (v/v). Secondary antibody (rabbit, except for ACTIN: mouse) was incubated in TBS, 5% skim milk (w/v), 1% (Tween) (v/v) for 1 h at room temperature with agitation. The membranes were washed six times with TBS, 1% Tween (v/v). Development was performed using the Millipore Immobilon-P kit. Images were captured using the Fusion FX imaging system (Vilber). All blots were prepared and immunoblotted in parallel and simultaneously exposed for chemiluminescence quantification using the Vilber quantification module. For each of the four replicates of polysomal-XRN4 blots, equivalent amounts of polysomal proteins were loaded across both input and polysome fractions. RPL13 was used as a loading control, and the XRN4 levels were normalized against the RPL13 signal. For the SOS1, PDAT1, PMT5, and NCL western blots, equivalent amounts of total protein were loaded. ACTIN was employed as the loading control for SOS1, PDAT1, and PMT5, while RPL13 served as the control for NCL.

## Accession numbers

Sequence data from this article can be found in the GenBank/EMBL data libraries under accession numbers PRJNA1044736 (mRNA-seq), PRJNA1044743 (Polysome mRNA-seq), and PRJNA1044724 (Degradome (5'P-seq)).

## Acknowledgments

We thank Marie Morlans for technical help.

## Author contributions

A.D., R.M., J.J.F., and J.M.D. designed the research. A.D., R.M., and J.J.F. performed the experiments. A.D., M.C.C., R.M., J.J.F., and J.M.D. analyzed the data. A.D., R.M., J.J.F., and J.M.D. wrote the article.

## Supplementary data

The following materials are available in the online version of this article.

**Supplementary Figure S1.** Effect of priming on Arabidopsis seedling phenotypes.

**Supplementary Figure S2.** Visual summary of the experimental procedure.

**Supplementary Figure S3.** Experimental design and filtering strategy used to generate Figs. 2 to 5.

**Supplementary Figure S4.** Library quality control.

**Supplementary Figure S5.** Comparison of the distribution of the ratio at different short acquired thermotolerance (SAT) and basal thermotolerance (BT) time points (compared to the p1 situation) of total degradome reads (shown in light and dark red boxplots) to the ratio of reads found exactly at position 16–17nt before the stop codon (as measured by the translational termination stalling index (TSI), shown in light and dark green boxplots) for the genes of Fig. 3.

**Supplementary Figure S6.** Priming is required to induce key members of the Unfolded Protein Response (UPR) pathway, while both basal thermotolerance (BT) and short acquired thermotolerance (SAT) induce the cytosolic protein response (CPR) pathway.

**Supplementary Table S1.** 5'P-seq; polysome-seq; mRNA-seq.

**Supplementary Table S2.** Heat-stress and CPR genes up regulated at 44°C (primed and unprimed). UPR genes up-regulated at 44°C only if preceded by a 37°C priming step. Stress-responsive genes up-regulated at 44°C only in the absence of priming.

## Funding

This work was supported by a grant from the Agence National de la Recherche (ANR-22-CE20-0023-01), by a "New Frontier" grant from the Laboratoires d'Excellences (LABEX) "TULIP" (ANR-10-LABX-41), by the CNRS and Université de Perpignan via Domitia. A.D. Salary was financed by the Occitanie Region. This study is set within the framework of the École Universitaire de Recherche TULIP-GS (ANR-18-EURE-0019).

*Conflict of interest statement.* None declared.

## References

Anders S, Pyl PT, Huber W. HTSeq-a python framework to work with high-throughput sequencing data. *Bioinformatics*. 2015;31(2): 166–169. https://doi.org/10.1093/bioinformatics/btu638

Bäurle I. Plant heat adaptation: priming in response to heat stress. *F1000Res*. 2016:5:F1000 Faculty Rev-694. https://doi.org/10.12688/f1000research.7526.1

Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for illumina sequence data. *Bioinformatics*. 2014;30(15):2114–2120. https://doi.org/10.1093/bioinformatics/btu170

Carpentier MC, Bousquet-Antonelli C, Merret R. Fast and efficient 5'p degradome library preparation for analysis of co-translational decay in Arabidopsis. *Plants (Basel)*. 2021;10(3):466. https://doi.org/10.3390/plants10030466
Carpentier MC, Deragon JM, Jean V, Be SHV, Bousquet-Antonelli C, Merret R. Monitoring of XRN4 targets reveals the importance of co-translational decay during Arabidopsis development. *Plant Physiol.* 2020;184(3):1251-1262. https://doi.org/10.1104/pp.20.00942

Carpentier MC, Receveur AE, Boubegtitene A, Cadoudal A, Bousquet-Antonelli C, Merret R. Genome-wide analysis of mRNA decay in Arabidopsis shoot and root reveals the importance of co-translational mRNA decay in the general mRNA turnover. *Nucleic Acids Res.* 2024;52(13):7910-7924. https://doi.org/10.1093/nar/gkae363

Charng YY, Mitra S, Yu SJ. Maintenance of abiotic stress memory in plants: lessons learned from heat acclimation. *Plant Cell.* 2023;35(1):187-200. https://doi.org/10.1093/plcell/koac313

Chassé H, Boulben S, Costache V, Cormier P, Morales J. Analysis of translation using polysome profiling. *Nucleic Acids Res.* 2017; 45(3):e15. https://doi.org/10.1093/nar/gkw907

Chen Q, Wu Y, Yu F, Xie Q. Coordinative regulation of ERAD and selective autophagy in plants. *Essays Biochem.* 2022;66(2):179-188. https://doi.org/10.1042/EBC20210099

Crisp PA, Ganguly D, Eichten SR, Borevitz JO, Fogson BJ. Reconsidering plant memory: intersections between stress recovery, RNA turnover, and epigenetics. *Sci Adv.* 2016;2(2):e1501340. https://doi.org/10.1126/sciadv.1501340

Duchenne-Moutien RA, Neetoo H. Climate change and emerging food safety issues: a review. *J Food Prot.* 2021;84(11):1884-1897. https://doi.org/10.4315/JFP-21-141

Garre E, Pelechano V, Sanchez Del Pino M, Alepuz P, Sunnerhagen P. The Lsm1-7/Pat1 complex binds to stress-activated mRNAs and modulates the response to hyperosmotic shock. *PLoS Genet.* 2018;14(7):e1007563. https://doi.org/10.1371/journal.pgen.1007563

German MA, Pillay M, Jeong DH, Hetawal A, Luo S, Janardhanan P, Kannan V, Rymarquis LA, Nobuta K, German R, et al. Global identification of microRNA-target RNA pairs by parallel analysis of RNA ends. *Nat Biotechnol.* 2008;26(8):941-946. https://doi.org/10.1038/nbt1417

Gerner EW, Schneider MJ. Induced thermal resistance in HeLa cells. *Nature.* 1975;256(5517):500-502. https://doi.org/10.1038/256500a0

Guo R, Yu X, Gregory BD. The identification of conserved sequence features of co-translationally decayed mRNAs and upstream open reading frames in angiosperm transcriptomes. *Plant Direct.* 2023;7(1):e479. https://doi.org/10.1002/pld3.479

Han WY, Hou BH, Lee WC, Chan TC, Lin TH, Chen HM. Arabidopsis mRNA decay landscape shaped by XRN 5'-3' exoribonucleases. *Plant J.* 2023;114(4):895-913. https://doi.org/10.1111/tpj.16181

Härdahl U, Hall RB, Ostyyoung KW, Vierling E, Bornman JF, Sundby C. The chloroplast small heat shock protein undergoes oxidation-dependent conformational changes and may protect plants from oxidative stress. *Cell Stress Chaperones.* 1999;4(2):129-138. https://doi.org/10.1379/1466-1268(1999)004<0129:tcshsp>2.3.co;2

Howell SH. Evolution of the unfolded protein response in plants. *Plant Cell Environ.* 2021;44(8):2625-2635. https://doi.org/10.1111/pce.14063

Hu W, Sweet TJ, Chamnongpol S, Baker KE, Coller J. Co-translational mRNA decay in Saccharomyces cerevisiae. *Nature.* 2009;461(7261): 225-229. https://doi.org/10.1038/nature08265

IPCC. Climate change 2023: synthesis report. contribution of working groups I, II and III to the sixth assessment report of the intergovernmental panel on climate change. In: Core Writing Team, Lee H, Romero J, editors. Geneva, Switzerland: IPCC, 2023. p. 35-115. https://doi.org/110.59327/IPCC/AR6-9789291691647

Jacob P, Hirt H, Bendahmane A. The heat-shock protein/chaperone network and multiple stress resistance. *Plant Biotechnol J.* 2017;15(4):405-414. https://doi.org/10.1111/pbi.12659

Kerbler SM, Wigge PA. Temperature sensing in plants. *Annu Rev Plant Biol.* 2023;74(1):341-366. https://doi.org/10.1146/annurev-arplant-102820-102235

Kim D, Paggi JM, Park C, Bennett C, Salzberg SL. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. *Nat Biotechnol.* 2019;37(8):907-915. https://doi.org/10.1038/s41587-019-0201-4

Kotak S, Larkindale J, Lee U, von Koskull-Doring P, Vierling E, Scharf KD. Complexity of the heat stress response in plants. *Curr Opin Plant Biol.* 2007;10(3):310-316. https://doi.org/10.1016/j.pbi.2007.04.011

Krshnan L, van de Weijer ML, Carvalho P. Endoplasmic reticulum-associated protein degradation. *Cold Spring Harb Perspect Biol.* 2022;14(12):a041247. https://doi.org/10.1101/cshperspect.a041247

Lamke J, Brzezinka K, Altmann S, Baurle I. A hit-and-run heat shock factor governs sustained histone methylation and transcriptional stress memory. *EMBO J.* 2016;35(2):162-175. https://doi.org/10.1525/embj.201592593

Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. *Nat Methods.* 2012;9(4):357-359. https://doi.org/10.1038/nmeth.1923

Li B, Zeis P, Zhang Y, Alekseenko A, Furst E, Sanchez YP, Lin G, Tekkedil MM, Piazza I, Steinmetz LM, et al. Differential regulation of mRNA stability modulates transcriptional memory and facilitates environmental adaptation. *Nat Commun.* 2023;14(1):910. https://doi.org/10.1038/s41467-023-36586-x

Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R; 1000 Genome Project Data Processing Subgroup. The sequence alignment/map format and SAMtools. *Bioinformatics.* 2009;25(16):2078-2079. https://doi.org/10.1093/bioinformatics/btp352

Lindquist S. Varying patterns of protein synthesis in Drosophila during heat shock: implications for regulation. *Dev Biol.* 1980;77(2):463-479. https://doi.org/10.1016/0012-1606(80)90488-1

Lindquist S. Regulation of protein synthesis during heat shock. *Nature.* 1981;293(5830):311-314. https://doi.org/10.1038/293311a0

Ling Y, Mahfouz MM, Zhou S. Pre-mRNA alternative splicing as a modulator for heat stress response in plants. *Trends Plant Sci.* 2021;26(11):1153-1170. https://doi.org/10.1016/j.tplants.2021.07.008

Ling Y, Serrano N, Gao G, Atia M, Mokhtar M, Woo YH, Bazin J, Veluchamy A, Benhamed M, Crespi M, et al. Thermopriming triggers splicing memory in Arabidopsis. *J Exp Bot.* 2018;69(10):2659-2675. https://doi.org/10.1093/jxb/ery062

Liu B, Han Y, Qian SB. Cotranslational response to proteotoxic stress by elongation pausing of ribosomes. *Mol Cell.* 2013;49(3):453-463. https://doi.org/10.1016/j.molcel.2012.12.001

Löchli K, Torbica E, Haile-Weldeslasie M, Baku D, Aziz A, Bublak D, Fragkostefanakis S. Crosstalk between endoplasmic reticulum and cytosolic unfolded protein response in tomato. *Cell Stress Chaperones.* 2022;28(5):511-528. https://doi.org/10.1007/s12192-022-01316-7

Martinez-Medina A, Flors V, Heil M, Mauch-Mani B, Pieterse CMJ, Pozo MJ, Ton J, van Dam NM, Conrath U. Recognizing plant defense priming. *Trends Plant Sci.* 2016;21(10):818-822. https://doi.org/10.1016/j.tplants.2016.07.009

Mauch-Mani B, Baccelli I, Luna E, Flors V. Defense priming: an adaptive part of induced resistance. *Annu Rev Plant Biol.* 2017;68(1):485-512. https://doi.org/10.1146/annurev-arplant-042916-041132

Merret R, Carpentier MC, Favory JJ, Picart C, Descombin J, Bousquet-Antonelli C, Tillard P, Lejay L, Deragon JM, Charng YY. Heat shock protein HSP101 affects the release of ribosomal protein mRNAs for recovery after heat shock. *Plant Physiol.* 2017;174(2):1216-1225. https://doi.org/10.1104/pp.17.00269
Merret R, Descombin J, Juan YT, Favory JJ, Carpentier MC, Chaparro C, Charng YY, Deragon JM, Bousquet-Antonelli C. XRN4 and LARP1 are required for a heat-triggered mRNA decay pathway involved in plant acclimation and survival during thermal stress. *Cell Rep.* 2013;5(5):1279-1293. https://doi.org/10.1016/j.celrep.2013.11.019

Merret R, Nagarajan VK, Carpentier MC, Park S, Favory JJ, Descombin J, Picart C, Charng YY, Green PJ, Deragon JM, et al. Heat-induced ribosome pausing triggers mRNA co-translational decay in Arabidopsis thaliana. *Nucleic Acids Res.* 2015;43(8):4121-4132. https://doi.org/10.1093/nar/gkv234

Nagarajan VK, Kukulich PM, von Hagel B, Green PJ. RNA degradomes reveal substrates and importance for dark and nitrogen stress responses of Arabidopsis XRN4. *Nucleic Acids Res.* 2019;47(17):9216-9230. https://doi.org/10.1093/nar/gkz712

Nagarajan VK, Stuart CJ, DiBattista AT, Accerbi M, Caplan JL, Green PJ. RNA degradome analysis reveals DNE1 endoribonuclease is required for the turnover of diverse mRNA substrates in Arabidopsis. *Plant Cell.* 2023;35(6):1936-1955. https://doi.org/10.1093/plcell/koad085

Nersisyan L, Ropat M, Pelechano V. Improved computational analysis of ribosome dynamics from 5'P degradome data using fiveپ街seq. NAR *Genom Bioinform.* 2020;2(4):lqaa099. https://doi.org/10.1093/nargab/lqaa099

Pelechano V, Wei W, Steinmetz LM. Widespread co-translational RNA decay reveals ribosome dynamics. *Cell*. 2015;161(6):1400-1412. https://doi.org/10.1016/j.cell.2015.05.008

Queitsch C, Hong SW, Vierling E, Lindquist S. Heat shock protein 101 plays a crucial role in thermotolerance in Arabidopsis. *Plant Cell*. 2000;12(4):479-492. https://doi.org/10.1105/tpc.12.4.479

Raudvere U, Kolberg L, Kuzmin I, Arak T, Adler P, Peterson H, Vilo J. G: Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update). *Nucleic Acids Res.* 2019;47(W1):W191-W198. https://doi.org/10.1093/nar/gkz369

Scharf KD, Berberich T, Ebersberger I, Nover L. The plant heat stress transcription factor (Hsf) family: structure, function and evolution. *Biochim Biophys Acta*. 2012;1819(2):104-119. https://doi.org/10.1016/j.bbagrm.2011.10.002

Sedaghatmehr M, Mueller-Roeber B, Balazadeh S. The plastid metalloprotease FtsH6 and small heat shock protein HSP21 jointly regulate thermomemory in Arabidopsis. *Nat Commun.* 2016;7(1):12439. https://doi.org/10.1038/ncomms12439

Shalgi R, Hurt JA, Krykbaeva I, Taipale M, Lindquist S, Burge CB. Widespread regulation of translation by elongation pausing in heat shock. *Mol Cell.* 2013;49(3):439-452. https://doi.org/10.1016/j.molcel.2012.11.028

Shekhawat K, Almeida-Trapp M, Garcia-Ramirez GX, Hirt H. Beat the heat: plant- and microbe-mediated strategies for crop thermotolerance. *Trends Plant Sci.* 2022;27(8):802-813. https://doi.org/10.1016/j.tplants.2022.02.008

Stief A, Brzezinka K, Lamke J, Baurle I. Epigenetic responses to heat stress at different time scales and the involvement of small RNAs. *Plant Signal Behav.* 2014;9(10):e970430. https://doi.org/10.4161/15592316.2014.970430

Sugio A, Dreos R, Aparicio F, Maule AJ. The cytosolic protein response as a subcomponent of the wider heat shock response in Arabidopsis. *Plant Cell.* 2009;21(2):642-654. https://doi.org/10.1105/tpc.108.062596

Wu TY, Juan YT, Hsu YH, Wu SH, Liao HT, Fung RW, Charng YY. Interplay between heat shock proteins HSP101 and HSA32 prolongs heat acclimation memory posttranscriptionally in Arabidopsis. *Plant Physiol.* 2013;161(4):2075-2084. https://doi.org/10.1104/pp.112.212589

Yeh CH, Kaplinsky NJ, Hu C, Charng YY. Some like it hot, some like it warm: phenotyping to explore thermotolerance diversity. *Plant Sci.* 2012;195:10-23. https://doi.org/10.1016/j.plantsci.2012.06.004

Yu CY, Cho Y, Sharma O, Kanehara K. What's unique? The unfolded protein response in plants. *J Exp Bot.* 2022;73(5):1268-1276. https://doi.org/10.1093/jxb/erab513

Yu X, Willmann MR, Anderson SJ, Gregory BD. Genome-wide mapping of uncapped and cleaved transcripts reveals a role for the nuclear mRNA cap-binding complex in cotranslational RNA decay in Arabidopsis. *Plant Cell.* 2016;28(10):2385-2397. https://doi.org/10.1105/tpc.16.00456

Zhang Y, Pelechano V. High-throughput 5'P sequencing enables the study of degradation-associated ribosome stalls. *Cell Rep Methods.* 2021;1(1):100001. https://doi.org/10.1016/j.crmeth.2021.100001