Life on earth faces constant changes in temperature. Most warm-blooded animals like humans can maintain a fairly stable body temperature, but cold-blooded animals can experience drastic shifts in body temperature.

For example, the body temperature of the worm Caenorhabditis elegans can vary greatly depending on its surroundings. This species has evolved an exquisite set of temperature-sensing machineries that can react even to subtle fluctuations, which enables the worm to adjust its behaviour. However, drastic shifts in temperature can cause significant changes within the organism.

Transient exposure to heat can activate genes that help cells to repair damaged proteins, while cold shock can influence the production of proteins in the cell. Although C. elegans can tolerate short periods of stress, an extended exposure to extreme temperatures can kill the worm. Until now, it was not known how C. elegans responds to cold shock followed by warmer temperatures, also referred to as cold-warming.

To address this question, Jiang et al. created random mutations in C. elegans and isolated the worms that responded to cold-warming differently. The results revealed a molecular pathway that turns on genes in response to cold-warming. Jiang et al. found that two genes and their proteins, ISY-1 and ZIP-10, control which other genes are switched on or off in response to this temperature change.

When the worms were exposed to cold-warming over a long period, the pathway remained active and many of the worms died, in particular older animals. These findings suggest that this genetic program might have evolved to help younger animals survive better when stress conditions are high and food resources limited.

More work is needed to explore this new pathway and its implication in the heat-cold shock mechanisms. The affected genes are often the same across different organisms and can therefore be engineered to benefit research and medical applications in unexpected ways. For example, patients suffering a heart attack or brain injury are exposed to colder temperature to prevent the risk of tissue injuries once the blood flow goes back to normal. Therefore, the findings of this study may help us to understand how human cells respond to and are protected by low temperature.

Temperature shifts pervasively affect numerous biological processes in all organisms. Heat shock stimuli activate expression of many heat-shock inducible genes through the sigma-32 factor and the evolutionarily conserved transcription factor HSF (Heat Shock Factor) in bacteria and eukaryotes, respectively (Gomez-Pastor et al., 2018; Yura et al., 1993). Coordinated expression of heat shock-induced chaperone proteins facilitates cellular proteostasis and adaptation to temperature upshift (Mahat et al., 2016; Solís et al., 2016). In contrast to heat shock response, how organisms respond to cold shock is still largely unknown (Al-Fageeh and Smales, 2006; Choi et al., 2012; Yenari and Han, 2012; Zhu, 2016). Although extensive RNA expression profiling studies have identified many protein-coding genes and non-coding RNAs that are regulated by cold shock via both transcriptional and post-transcriptional mechanisms (Al-Fageeh and Smales, 2006; Giuliodori et al., 2010; Kandror et al., 2004; Zhou et al., 2017), master regulators of cold shock response and cold-regulated genes (counterparts of HSF) have long been elusive and mechanisms of cold shock response in multicellular organisms remain poorly characterized.

At the organismic level, warm-blooded mammals normally keep body temperature at about 37°C and initiate multiple homeostatic mechanisms to maintain body temperature upon exposure to hypothermia (Bautista, 2015; Morrison, 2016; Tansey and Johnson, 2015; Vriens et al., 2014). In humans, therapeutic hypothermia (32–34°C) has been widely used to treat ischemic disorders and proposed to activate multifaceted cellular programs to protect against ischemic damages (Choi et al., 2012; Polderman, 2009; Yenari and Han, 2012). By contrast, cold-blooded animals including most invertebrates experience varying body temperature depending on the environment, but can nonetheless elicit stereotypic behavioral, physiological and transcriptional response to chronic hypothermia or transient cold shock (Al-Fageeh and Smales, 2006; Garrity et al., 2010). Like many other types of stress, prolonged severe hypothermia can lead to the death of organisms, in most cases likely because of failure in adapting to the stress, or alternatively through stress-induced phenoptosis, namely genetically programed organismic death (Longo et al., 2005; Skulachev, 1999; 2002). Although phenoptosis has been phenotypically documented in many cases, its evolutionary significance and genetic mechanisms remain unclear and debated (Longo et al., 2005; Sapolsky, 2004).

We previously discovered a C. elegans genetic pathway that maintains cell membrane fluidity by regulating lipid desaturation in response to moderate hypothermia (10–15°C) (Fan and Evans, 2015; Ma et al., 2015). Expression of the gene fat-7, which encodes a lipid desaturase, is transcriptionally induced by 10–15°C but not by more severe hypothermia (i.e. cold shock at 0–4°C), which impairs C. elegans reproduction and growth, and elicits distinct physiological and behavioral responses (Garrity et al., 2010; Lyons et al., 1975; Ma et al., 2015; Murray et al., 2007). However, as severe hypothermia arrests most of cell biological processes, strong transcriptional responses to cold shock e.g. 0–4°C likely only manifest during the organismic recovery to normal ambient temperature. We thus hypothesize that a genetic pathway differing from that operating under moderate hypothermia exposure controls the transcriptional response to severe hypothermia/cold shock followed by warming in C. elegans.

In this work, we performed transcriptome profiling to first identify genes that are regulated by exposure to cold shock followed by recovery at normal temperature. We then used GFP-based transcriptional reporters in large-scale forward genetic screens to identify a genetic pathway consisting of isy-1 and zip-10, the latter of which responds to cold-warming (CW) and mediates transcriptional responses to CW. Unexpectedly, we found strong zip-10 induction promotes organismal death while deficiency of zip-10 confers resistance to prolonged CW stress, more prominently in adults than young larvae. We propose that CW activates a ZIP-10 dependent genetic program favoring C. elegans phenoptosis and postulate that such programmed organismic death may have evolved to promote wild-population kin selection under thermal stress conditions.

To identify new mechanisms of C. elegans response to severe hypothermia, we performed RNA sequencing (RNA-seq) of wild-type C. elegans populations after 2 hrs exposure to 4°C cold shock followed by recovery at 20°C for 1 hr. We used such CW conditions in an attempt to identify genes that specifically and rapidly respond to CW rather than those that respond to general organismic deterioration after long cold exposure. After differential expression analyses of triplicate samples, we identified 604 genes that are significantly up- or down-regulated by such CW conditions (Figure 1—source data 1, Figure 1A and Figure 1—figure supplement 1A). Gene ontology analysis indicates that the CW-regulated genes are involved in biological processes including lipid metabolisms, autophagy, proteostasis and cell signaling (Figure 1—figure supplement 1B). We generated transgenic C. elegans strains in which GFP is driven by promoters of the top-ranked CW-inducible genes. In this work, we focus on asp-17 as a robust CW-inducible reporter gene owing to its low baseline expression level and high-fold induction by CW, features that permitted facile isolation of full-penetrance mutants after random mutagenesis (see below) with both abnormal asp-17p::GFP expression and altered organismic tolerance to prolonged cold stress.

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Figure 1—source data 1

Lists of genes up- and down-regulated by CW with adjusted p<0.05 and log2FoldChange from biological triplicate samples of wild-type C. elegans.

https://doi.org/10.7554/eLife.35037.005

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C. elegans asp-17 encodes an aspartyl-like protease with unknown molecular functions. Like other CW-inducible genes, asp-17 up-regulation is more prominently induced by severe than moderate hypothermia followed by recovery from cold shock (Figure 1B and C). Among the aspartyl-like protease family members, we found that only asp-17 was robustly and specifically induced by CW (Figure 1D). The up-regulation of endogenous asp-17 by CW can be recapitulated by an integrated GFP reporter driven by the endogenous asp-17 promoter, indicating transcriptional regulation of asp-17 by CW (Figure 2—figure supplement 1A). We varied CW treatment conditions and found that the induction of asp-17 strictly required the warming phase after cold shock (Figure 1E). However, heat shock at 32°C did not increase asp-17 expression (Figure 1E), consistent with previous large-scale transcriptome profiling studies in C. elegans (Brunquell et al., 2016). Single-molecule fluorescent in situ hybridization (smFISH) identified the CW-induced asp-17 predominantly in intestinal cells (Figure 1F). Since CW activates numerous other genes in addition to asp-17, we sought to use asp-17p::GFP as a robust readout reporter to identify the upstream genetic pathway and transcriptional regulators that control asp-17 induction by CW.

We performed a forward genetic screen using EMS-induced random mutagenesis of a parental strain carrying a genome-integrated asp-17p::GFP reporter and isolated over 30 mutants with constitutive asp-17p::GFP expression in the absence of CW (Figure 2—figure supplement 1B and C). We molecularly cloned one mutant dma50 that exhibited fully penetrant and constitutively strong expression of asp-17p::GFP (Figure 2A,B and Figure 2—figure supplement 1D–1F). Compared with wild type, dma50 strongly up-regulated asp-17::GFP in the intestine (Figure 2B). By single nucleotide polymorphism (SNP)-based linkage analysis of the intestinal asp-17p::GFP phenotype, we mapped dma50 to a genetic interval on Chromosome V and used whole-genome sequencing to identify candidate causal gene mutations (Figure 2—figure supplement 1D,E). Based on phenocopying by feeding RNAi against the candidate genes and transformation rescue of the asp-17p::GFP phenotype, dma50 defines a previously uncharacterized C. elegans gene isy-1 (Figure 2A–F and Figure 2—figure supplement 1F). isy-1 (Interactor of SYF1 in yeast) encodes a protein with strong sequence similarity to an evolutionarily highly conserved family of RNA-binding proteins in eukaryotes (Figure 2A and Figure 2—figure supplement 2A–C) (Dix et al., 1999; Du et al., 2015).

dma50 caused substitution of a negatively charged glutamate, which is completely conserved in the ISY protein family, to a positively charged lysine in the predicted coiled-coil region of C. elegans ISY-1 (Figure 2A). An isy-1p::isy-1::GFP translational reporter indicated a rather ubiquitous distribution of ISY-1::GFP in many tissues including intestinal nuclei (Figure 2C). The strong intestinal asp-17p::GFP expression caused by dma50 was fully rescued by transgenic expression of wild-type isy-1(+), single-copy integration of a mCherry-tagged isy-1(+) allele, or isy-1(+) expression driven by the intestine-specific ges-1 promoter (Figure 2E and F). In addition, the ges-1-driven transgenic expression of sense plus antisense isy-1 RNAi fully recapitulated the dma50 phenotype (Figure 2D). Endogenous expression of asp-17 was also drastically up-regulated in isy-1 mutants (Figure 2—figure supplement 2D). Thus, these results identify isy-1 as a causal cell-autonomous regulator of asp-17.

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Human ISY1 is critical for certain microRNA processing while yeast ISY1 is a likely component of the spliceosome (Dix et al., 1999; Du et al., 2015; Galej et al., 2016). We found that CW-induced asp-17 up-regulation was further enhanced in isy-1 mutants compared with wild type (Figure 3A), suggesting that ISY-1 normally restricts transcriptional activity of asp-17. To determine the mechanism by which ISY-1 regulates transcription of asp-17, we sought to identify transcription factors (TF) that meet two criteria: a), its mRNA or protein products are altered in isy-1 mutants, and b), it is genetically epistatic to isy-1, that is, its loss-of-function (LOF) can suppress isy-1 LOF (thus also likely required for asp-17 induction by CW). We performed RNA-seq from triplicate samples of wild-type hermaphrodites and isy-1 mutants, from which we analyzed differentially expressed TF-encoding genes in isy-1 mutants and found that a bZIP-type transcription factor-encoding gene zip-10 met both criteria (Figure 3B, Figure 3—source data 1). zip-10 mRNA was drastically up-regulated in isy-1 mutants, whereas levels of closely related bZIP family genes, such as zip-11, were unaffected (Figure 3C). Importantly, genetic deletion of zip-10 completely abrogated the ability of isy-1 RNAi to activate asp-17p::GFP (Figure 3D). These results indicate that ISY-1 regulates asp-17 by controlling the level of zip-10 mRNAs.

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Figure 3—source data 1

Lists of genes up- and down-regulated by the isy-1(dma50) mutation with adjusted p<0.05 and log2FoldChange from biological triplicate samples of wild-type and isy-1(dma50) mutant C. elegans.

https://doi.org/10.7554/eLife.35037.012

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Next, we examined how the ISY-1/ZIP-10/ASP-17 pathway is regulated by CW. CW did not apparently alter levels of endogenous isy-1 mRNAs or mCherry-tagged ISY-1 proteins under the endogenous isy-1 promoter (Figure 2—figure supplement 2D and E). By contrast, we found that CW induced drastic up-regulation of ZIP-10 proteins from a tagged zip-10p::zip-10::EGFP::FLAG allele in an integrated transgenic strain (Figure 3E). Although EGFP fluorescence was invisible in animals carrying such transgenes (likely because it is sandwiched by zip-10 and FLAG), the striking induction of ZIP-10::EGFP::FLAG was completely blocked by RNAi against zip-10 or GFP, confirming the transgene specificity (Figure 3F). The baseline level of ZIP-10::EGFP::FLAG was close to the detection limit of western blot under normal conditions, but nonetheless is strongly up-regulated upon RNAi against isy-1 (Figure 3F). Similar to that of asp-17, the induction of zip-10p::zip-10::EGFP::FLAG strictly required the warming phase of CW and occurred rapidly but transiently after warming during CW (Figure 3G). CW strongly up-regulated asp-17 expression in both wild type and isy-1 mutants, which exhibited abnormally high zip-10 mRNA levels (Figure 3H). Furthermore, zip-10 deletion completely abrogated the up-regulation of asp-17 levels by CW (Figure 3I). We also examined the ZIP-10 dependency of other CW-inducible genes identified by RNA-seq and found that at least cpr-3 also required ZIP-10, but other CW-inducible genes including srr-6 and F53A9.1, did not (Figure 3I). These results demonstrate that ISY-1 suppresses asp-17 by decreasing zip-10 levels whereas CW up-regulates ZIP-10 protein abundance to promote asp-17 expression.

How is zip-10 regulated by ISY-1 and CW? Loss of ISY-1 function affected neither general intron splicing, based on an intronic GFP reporter assay, nor specific splicing of zip-10, although both CW and isy-1 mutations strongly up-regulated zip-10 mRNA levels (Figure 3—figure supplement 1A–1E). We constructed a GFP transcriptional reporter driven by the endogenous zip-10 promoter and found it was markedly up-regulated by isy-1 RNAi (Figure 3—figure supplement 2A). While non-thermal stresses such as hypoxia and starvation did not increase ZIP-10 levels, CW drastically increased abundance of ZIP-10 in both cytosol and nucleus without affecting abundance of other house-keeping proteins, including HSP90, tubulin and histone H3 (Figure 3—figure supplement 2B and C). CW up-regulation of ZIP-10 required warming and was enhanced by more prolonged cold shock (Figure 3—figure supplement 2D). Since CW can markedly increase zip-10 mRNA levels but to a lesser extent than the isy-1 mutation (Figure 3—figure supplement 1D and E), we tested whether ZIP-10 proteins might be regulated by CW through translational control and mRNA stability. RNAi against genes encoding eIF5 and a component of the Ccr4-Not complex did not apparently alter ZIP-10 levels (Figure 3—figure supplement 2E). Together, these results indicate that CW and ISY-1 regulate zip-10 primarily at the transcriptional level.

Human ISY1 facilitates the processing of primary transcripts encoding certain families of microRNAs (Du et al., 2015). Both zip-10 and asp-17 are up-regulated in a mutant C. elegans strain deficient in the microRNA mir-60 (Kato et al., 2016). We thus tested whether mir-60 mediates the regulation of zip-10 by ISY-1. Immunoprecipitation of mCherry-tagged ISY-1 followed by quantitative PCR (QPCR) revealed specific binding of primary transcripts encoding mir-60 as well as a protein-coding gene cebp-1 (Figure 4A–4C). Although neither isy-1 nor mir-60 levels were affected by CW, we found CW slightly increased mir-60 binding to ISY-1, perhaps as a feedback mechanism to limit over-activation of zip-10-dependent genes after CW treatment (Figure 4B). Importantly, mature mir-60 levels were drastically decreased in isy-1 mutants while loss of mir-60 led to up-regulation of zip-10 and zip-10-dependent subset of CW-inducible genes, including asp-17 and cpr-3, but not many other CW-inducible genes (Figure 4D and E and Supplementary file 1). The 3’ untranslated region (Utr) of zip-10 appeared not to be regulated by CW or isy-1 RNAi (Figure 4F). However, isy-1 RNAi caused an abnormally high baseline level of ZIP-10 in the absence of CW and enabled further heightened ZIP-10 up-regulation in response to CW, followed by its down-regulation over an extended period of warming (Figure 4G). These results indicate that CW regulates transcription of zip-10 (and thereby that of asp-17), while ISY-1 controls expression of zip-10 via mir-60, likely through microRNA processing and regulation of additional upstream transcriptional zip-10 regulators that respond to CW.

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We compared the genes differentially regulated by CW and those by isy-1(dma50) mutants and found 246 genes, including the two ZIP-10-dependent targets asp-17 and cpr-3, that are commonly regulated by both conditions (Figure 5A, Figure 5—source data 1). Global transcriptome changes between these two conditions are also significantly correlated (Figure 5B) (correlation coefficient R as 0.54, significance P value as 0). We used the bioinformatics tool MEME (Bailey et al., 2009) to identify motifs present in the promoters (~600 bp upstream of transcription start sites) of the commonly regulated gene subset and identified a single enriched motif characterized by AT-rich sequences (Figure 5C). The gene most enriched with this motif is asp-17, the promoter of which contains 16 such motifs (Figure 5C). ZIP-10 is a bZIP-type transcription factor predicted to contain N-terminal low sequence-complexity domains and a C-terminal DNA-binding and glutamine-rich transactivation domain (Figure 3—figure supplement 2F–H). To test whether the asp-17 promoter with the identified AT-rich motifs can be bound directly by ZIP-10, we performed chromatin immunoprecipitation (ChIP) experiments and detected asp-17 promoter sequences in the FLAG-tagged ZIP-10 chromatin complex only under CW conditions (Figure 5D). These results indicate that ZIP-10 directly binds to and activates the asp-17 promoter in the genetic program regulated by ISY-1 and CW.

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Lists of genes commonly regulated by CW and the isy-1(dma50) mutation with adjusted p<0.05 and log2FoldChange from biological triplicate samples of wild-type and isy-1(dma50) mutant C. elegans.

https://doi.org/10.7554/eLife.35037.017

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The striking regulation of zip-10 and asp-17 by CW and ISY-1 prompted us to examine the organismic phenotype of various mutants upon prolonged CW stress. A majority of wild-type C. elegans adults died upon prolonged CW stress (e.g. 2–4°C for over 24 hrs) (Ohta et al., 2014). We found that asp-17 or zip-10 loss-of-function mutants exhibited markedly higher survival rates than wild type under the same prolonged CW stress condition (Figure 5E). Consistent with a role of wild-type zip-10 in promoting organismic death, inducible zip-10 over-expression by mild transient heat shock, mediated by the hsp-16 promoter, promoted animal death even in the absence of CW (Figure 5F). By contrast, other ectopically induced zip genes including zip-11 and zip-2 did not affect animal death, while a mutation specifically disrupting the glutamine-rich transactivation domain of ZIP-10 abolished the death-promoting effect (Figure 5F and Figure 3—figure supplement 2H). Although zip-10 is genetically epistatic to isy-1 in the regulation of asp-17, we found that isy-1 mutants are also markedly resistant to prolonged cold stress. This paradox was resolved after we observed that many downstream target genes of the stress-coping transcription factors HIF-1, HSF-1 and DAF-16 are up-regulated in isy-1 mutants, and LOF of at least daf-16 could partly suppress cold tolerance by isy-1 RNAi (Figure 5G and H). Since ISY-1 regulates zip-10 via mir-60 (Figure 4) supporting a role of ISY-1 in specific microRNA processing (Du et al., 2015), we performed small RNA library sequencing of wild type animals and isy-1 mutants and identified specific members of microRNAs that were differentially regulated, including mir-60 and additional microRNAs predicted to target stress-coping TFs (Figure 5—figure supplement 1A–F). Thus, isy-1 mutants likely exhibit pleiotropic phenotypes caused by abnormal activation of multiple TFs in addition to ZIP-10. In contrast to ZIP-10 dependent genes (asp-17 and cpr-3), the HIF-1/HSF-1/DAF-16 target genes were not apparently induced by CW (Figure 1—source data 1). Furthermore, unlike HSF-1 or DAF-16 that are induced by other types of stress stimuli, ZIP-10 is more strongly induced by CW in adults than in larvae (Figure 5—figure supplement 2C), suggesting phenoptosis-promoting effects of zip-10 more specifically for adults. Indeed, the phenotypic difference in cold tolerance between wild type animals and zip-10 mutants manifested more prominently in developmentally more mature-stage and older animals (Figure 5—figure supplement 2D). These results indicate that CW specifically activates a ZIP-10-driven and developmental stage-modulated transcriptional genetic program to promote the organismic death, or phenoptosis, of C. elegans (Figure 5I).

From a genetic screen for C. elegans mutants with altered transcriptional response to CW, we identified isy-1 and subsequently discovered the CW and ISY-1-regulated transcription factor ZIP-10 as a key mediator of the transcriptional response to CW. A thermal stress-responding TF might be expected to promote adaptation of animals towards the stressor, causing its LOF mutants to be sensitive to the stress. Unexpectedly, we found zip-10 mutants are markedly resistant to prolonged cold stress. However, unlike other stress-responding TFs that activate genes largely beneficial for physiological homeostasis and thus animal health under stress conditions (Baird et al., 2014; Dempersmier et al., 2015; Hwang and Lee, 2011; Kandror et al., 2004; Kumsta et al., 2017; Landis and Murphy, 2010), identified transcriptional targets of ZIP-10 include at least two Cathepsin-type proteases, CPR-3 and ASP-17 (Figure 4E). In contrast to aspartyl-type proteases which are largely unknown in cellular functions, caspase-type proteases are well-known apoptotic cell death executioners while CPR-4, a Cathepsin CPR-3 paralogue, has been shown to inhibit cell deaths in C. elegans (Metzstein et al., 1998; Peng et al., 2017; Peter, 2011). Ectopic expression of zip-10 and its targets promotes organismic deaths, in contrast to the effect of zip-10 or asp-17 deficiency on cold tolerance (Figure 5E and F). As duration of cold shock affects levels of ZIP-10 and transient CW does not trigger phenoptosis, the pro-death role of the zip-10 genetic program likely depends on multiple factors, including the duration and severity of cold exposure. Notably, apoptotic cell death-promoting effects have also been described for specific members of mammalian bZIP TFs (Chüeh et al., 2017; Hartman et al., 2004; Ritchie et al., 2009). The specific and robust induction of ZIP-10 by CW, the opposing cold-tolerance phenotypes caused by zip-10 loss-of-function and gain-of-function genetic manipulations, as well as the pro-death roles of ZIP-10 targets support the notion that the zip-10 pathway is activated by severe CW to promote phenoptosis.

How do ISY-1 and CW regulate the zip-10 pathway? We found that the zip-10 promoter activity responds to the loss of ISY-1, which normally maintains mir-60 levels and thereby regulates zip-10 transcription likely through the processing of small RNAs. Severe cold stress also leads to accumulation of another class of small RNA risiRNA, which is important for maintaining rRNA homeostasis (Zhou et al., 2017). Whether ISY-1 might also affect risiRNA processing remains to be characterized. Constitutive up-regulation of ZIP-10 targets in isy-1 mutants and the lack of evidence for regulation of ISY-1 by CW supports ISY-1 as a gate-keeper for the ZIP-10-driven transcriptional response to CW (Figure 5I). Regulation of zip-10 is primarily transcriptional based on evidence we present in this study; further studies are required to discern to what extent mir-60 might directly act at the zip-10 locus or more indirectly impact the transcription of zip-10, e.g. by post-transcriptionally inhibiting translation of a transcriptional activator. Up-regulation of the activity of the zip-10 promoter by CW indicates that additional cold-responding sensors and effectors upstream of ZIP-10 remain to be identified, by signaling mechanisms perhaps similar to the well-characterized cold-responding pathways found in other organisms (Dempersmier et al., 2015; Kandror et al., 2004; Zhu, 2016). Precisely how zip-10 is regulated by CW in coordination with ISY-1 to promote C. elegans death under prolonged CW stress awaits further investigation.

The roles of ZIP-10 and a dedicated genetic program in promoting organismic death are surprising but would make sense in light of the evolutionary kin selection theory. Kin selection refers to the evolutionary process promoting the reproductive success of an organism's kin despite a cost to the organism's own reproduction (Hamilton, 1963; Smith, 1964). Dedicated genetic programs may have evolved to promote kin selection at the population level. Although the concept and potential mechanisms of programed organismic death, or phenoptosis, are debated, examples of kin selection and stress-induced organismic deterioration have been widely documented in many organisms (Longo et al., 2005; Sapolsky, 2004; Skulachev, 1999; 2002).

Laboratory conditions for hermaphroditic C. elegans clearly no longer exert selection pressure for genetic programs underlying phenoptosis or kin selection. However, our mathematic modeling of an exemplar situation of population growth for wild-type and zip-10 deficient animals under food-limiting and CW stress conditions supports the phenoptosis or kin selection hypothesis for the zip-10 pathway (Figure 5—figure supplement 2A and B). Experimentally, we found that both the CW-induced zip-10 expression and the death-promoting effect of ZIP-10 occurred more prominently in older adults than in larvae (Figure 5—figure supplement 2C and D). Extending from the kin selection theory, we postulate that the evolutionary advantage of programmed organismic death might manifest in the wild, where resources for growth and reproduction are limited and environments can change drastically. As such, the selective death of adult animals would benefit young and reproductively more privileged populations to facilitate the spreading of genes by young populations under resource-limiting and high-stress conditions. Our work provides an unprecedented example of stress-induced phenoptosis in C. elegans and identify a specific transcription factor in a genetic program that likely evolved to promote kin selection during animal evolution. These findings therefore bear broad implications for understanding thermal stress response, programmed organismic death (phenoptosis) and evolutionary biology.

1. 1. Wei J
   2. Yuehua W
   3. Yong L
   4. Arthur O
   5. Bingying W
   6. Xuebing W
   7. Shuo L
   8. Yongjun D
   9. Dengke KM

   (2018) CW RNA seq

   Publicly available at NCBI BioProject (Accession no. PRJNA430003).

   https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA430003
2. 1. Wei J
   2. Yuehua W
   3. Yong L
   4. Arthur O
   5. Bingying W
   6. Xuebing W
   7. Shuo L
   8. Yongjun D
   9. Dengke KM

   (2018) Small RNA seq in isy-1 mutants

   Publicly available at NCBI BioProject (Accession no. PRJNA430140).

   https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA430140

1. 1. Al-Fageeh MB
   2. Smales CM

   (2006) Control and regulation of the cellular responses to cold shock: the responses in yeast and mammalian systems

   Biochemical Journal 397:247–259.

   https://doi.org/10.1042/BJ20060166

   • PubMed
   • Google Scholar
2. 1. Bailey TL
   2. Boden M
   3. Buske FA
   4. Frith M
   5. Grant CE
   6. Clementi L
   7. Ren J
   8. Li WW
   9. Noble WS

   (2009) MEME SUITE: tools for motif discovery and searching

   Nucleic Acids Research 37:W202–W208.

   https://doi.org/10.1093/nar/gkp335

   • PubMed
   • Google Scholar
3. 1. Baird NA
   2. Douglas PM
   3. Simic MS
   4. Grant AR
   5. Moresco JJ
   6. Wolff SC
   7. Yates JR
   8. Manning G
   9. Dillin A

   (2014) HSF-1-mediated cytoskeletal integrity determines thermotolerance and life span

   Science 346:360–363.

   https://doi.org/10.1126/science.1253168

   • PubMed
   • Google Scholar
4. 1. Bautista DM

   (2015) Spicy science: David Julius and the discovery of temperature-sensitive TRP channels

   Temperature 2:135–141.

   https://doi.org/10.1080/23328940.2015.1047077

   • Google Scholar
5. 1. Bindea G
   2. Mlecnik B
   3. Hackl H
   4. Charoentong P
   5. Tosolini M
   6. Kirilovsky A
   7. Fridman WH
   8. Pagès F
   9. Trajanoski Z
   10. Galon J

   (2009) ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks

   Bioinformatics 25:1091–1093.

   https://doi.org/10.1093/bioinformatics/btp101

   • PubMed
   • Google Scholar
6. 1. Brenner S

   (1974)

   The genetics of Caenorhabditis elegans

   Genetics 77:71–94.

   • PubMed
   • Google Scholar
7. 1. Brunquell J
   2. Morris S
   3. Lu Y
   4. Cheng F
   5. Westerheide SD

   (2016) The genome-wide role of HSF-1 in the regulation of gene expression in Caenorhabditis elegans

   BMC Genomics 17:559.

   https://doi.org/10.1186/s12864-016-2837-5

   • PubMed
   • Google Scholar
8. 1. Choi HA
   2. Badjatia N
   3. Mayer SA

   (2012) Hypothermia for acute brain injury--mechanisms and practical aspects

   Nature Reviews Neurology 8:214–222.

   https://doi.org/10.1038/nrneurol.2012.21

   • PubMed
   • Google Scholar
9. 1. Chüeh AC
   2. Tse JWT
   3. Dickinson M
   4. Ioannidis P
   5. Jenkins L
   6. Togel L
   7. Tan B
   8. Luk I
   9. Davalos-Salas M
   10. Nightingale R
   11. Thompson MR
   12. Williams BRG
   13. Lessene G
   14. Lee EF
   15. Fairlie WD
   16. Dhillon AS
   17. Mariadason JM

   (2017) ATF3 repression of BC_L-X_Ldetermines apoptotic sensitivity to HDAC inhibitors across tumor types

   Clinical Cancer Research 23:5573–5584.

   https://doi.org/10.1158/1078-0432.CCR-17-0466

   • PubMed
   • Google Scholar
10. 1. Davis MW
    2. Hammarlund M
    3. Harrach T
    4. Hullett P
    5. Olsen S
    6. Jorgensen EM

    (2005) Rapid single nucleotide polymorphism mapping in C. elegans

    BMC Genomics 6:118.

    https://doi.org/10.1186/1471-2164-6-118

    • PubMed
    • Google Scholar
11. 1. Dempersmier J
    2. Sambeat A
    3. Gulyaeva O
    4. Paul SM
    5. Hudak CS
    6. Raposo HF
    7. Kwan HY
    8. Kang C
    9. Wong RH
    10. Sul HS

    (2015) Cold-inducible Zfp516 activates UCP1 transcription to promote browning of white fat and development of brown fat

    Molecular Cell 57:235–246.

    https://doi.org/10.1016/j.molcel.2014.12.005

    • PubMed
    • Google Scholar
12. 1. Dix I
    2. Russell C
    3. Yehuda SB
    4. Kupiec M
    5. Beggs JD

    (1999) The identification and characterization of a novel splicing protein, Isy1p, of Saccharomyces cerevisiae

    RNA 5:360–368.

    https://doi.org/10.1017/S1355838299981396

    • PubMed
    • Google Scholar
13. 1. Du P
    2. Wang L
    3. Sliz P
    4. Gregory RI

    (2015) A Biogenesis Step Upstream of Microprocessor Controls miR-17∼92 Expression

    Cell 162:885–899.

    https://doi.org/10.1016/j.cell.2015.07.008

    • PubMed
    • Google Scholar
14. 1. Fan W
    2. Evans RM

    (2015) Turning up the heat on membrane fluidity

    Cell 161:962–963.

    https://doi.org/10.1016/j.cell.2015.04.046

    • PubMed
    • Google Scholar
15. 1. Friedländer MR
    2. Mackowiak SD
    3. Li N
    4. Chen W
    5. Rajewsky N

    (2012) miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades

    Nucleic Acids Research 40:37–52.

    https://doi.org/10.1093/nar/gkr688

    • PubMed
    • Google Scholar
16. 1. Frøkjaer-Jensen C
    2. Davis MW
    3. Hopkins CE
    4. Newman BJ
    5. Thummel JM
    6. Olesen SP
    7. Grunnet M
    8. Jorgensen EM

    (2008) Single-copy insertion of transgenes in Caenorhabditis elegans

    Nature Genetics 40:1375–1383.

    https://doi.org/10.1038/ng.248

    • PubMed
    • Google Scholar
17. 1. Galej WP
    2. Wilkinson ME
    3. Fica SM
    4. Oubridge C
    5. Newman AJ
    6. Nagai K

    (2016) Cryo-EM structure of the spliceosome immediately after branching

    Nature 537:197–201.

    https://doi.org/10.1038/nature19316

    • PubMed
    • Google Scholar
18. 1. Garrity PA
    2. Goodman MB
    3. Samuel AD
    4. Sengupta P

    (2010) Running hot and cold: behavioral strategies, neural circuits, and the molecular machinery for thermotaxis in C. elegans and Drosophila

    Genes & Development 24:2365–2382.

    https://doi.org/10.1101/gad.1953710

    • PubMed
    • Google Scholar
19. 1. Giuliodori AM
    2. Di Pietro F
    3. Marzi S
    4. Masquida B
    5. Wagner R
    6. Romby P
    7. Gualerzi CO
    8. Pon CL

    (2010) The cspA mRNA is a thermosensor that modulates translation of the cold-shock protein CspA

    Molecular Cell 37:21–33.

    https://doi.org/10.1016/j.molcel.2009.11.033

    • PubMed
    • Google Scholar
20. 1. Gomez-Pastor R
    2. Burchfiel ET
    3. Thiele DJ

    (2018) Regulation of heat shock transcription factors and their roles in physiology and disease

    Nature Reviews Molecular Cell Biology 19:4–19.

    https://doi.org/10.1038/nrm.2017.73

    • PubMed
    • Google Scholar
21. 1. Hamilton WD

    (1963) The Evolution of Altruistic Behavior

    The American Naturalist 97:354–356.

    https://doi.org/10.1086/497114

    • Google Scholar
22. 1. Hartman MG
    2. Lu D
    3. Kim ML
    4. Kociba GJ
    5. Shukri T
    6. Buteau J
    7. Wang X
    8. Frankel WL
    9. Guttridge D
    10. Prentki M
    11. Grey ST
    12. Ron D
    13. Hai T

    (2004) Role for activating transcription factor 3 in stress-induced beta-cell apoptosis

    Molecular and Cellular Biology 24:5721–5732.

    https://doi.org/10.1128/MCB.24.13.5721-5732.2004

    • PubMed
    • Google Scholar
23. 1. Hwang AB
    2. Lee SJ

    (2011) Regulation of life span by mitochondrial respiration: the HIF-1 and ROS connection

    Aging 3:304–310.

    https://doi.org/10.18632/aging.100292

    • PubMed
    • Google Scholar
24. 1. Jan CH
    2. Friedman RC
    3. Ruby JG
    4. Bartel DP

    (2011) Formation, regulation and evolution of Caenorhabditis elegans 3'UTRs

    Nature 469:97–101.

    https://doi.org/10.1038/nature09616

    • PubMed
    • Google Scholar
25. 1. Ji N
    2. Oudenaarden A

    (2005)

    WormBook

    Single molecule fluorescent in situ hybridization (smFISH) of C. elegans worms and embryos, WormBook.

    • Google Scholar
26. 1. John B
    2. Enright AJ
    3. Aravin A
    4. Tuschl T
    5. Sander C
    6. Marks DS

    (2004) Human MicroRNA targets

    PLoS Biology 2:e363.

    https://doi.org/10.1371/journal.pbio.0020363

    • PubMed
    • Google Scholar
27. 1. Kamath RS
    2. Ahringer J

    (2003) Genome-wide RNAi screening in Caenorhabditis elegans

    Methods 30:313–321.

    https://doi.org/10.1016/S1046-2023(03)00050-1

    • PubMed
    • Google Scholar
28. 1. Kandror O
    2. Bretschneider N
    3. Kreydin E
    4. Cavalieri D
    5. Goldberg AL

    (2004) Yeast adapt to near-freezing temperatures by STRE/Msn2,4-dependent induction of trehalose synthesis and certain molecular chaperones

    Molecular Cell 13:771–781.

    https://doi.org/10.1016/S1097-2765(04)00148-0

    • PubMed
    • Google Scholar
29. 1. Kato M
    2. Kashem MA
    3. Cheng C

    (2016) An intestinal microRNA modulates the homeostatic adaptation to chronic oxidative stress inC. elegans

    Aging 8:1979–2005.

    https://doi.org/10.18632/aging.101029

    • PubMed
    • Google Scholar
30. 1. Kershner AM
    2. Kimble J

    (2010) Genome-wide analysis of mRNA targets for Caenorhabditis elegans FBF, a conserved stem cell regulator

    PNAS 107:3936–3941.

    https://doi.org/10.1073/pnas.1000495107

    • PubMed
    • Google Scholar
31. 1. Kim D
    2. Langmead B
    3. Salzberg SL

    (2015) HISAT: a fast spliced aligner with low memory requirements

    Nature Methods 12:357–360.

    https://doi.org/10.1038/nmeth.3317

    • PubMed
    • Google Scholar
32. 1. Krüger J
    2. Rehmsmeier M

    (2006) RNAhybrid: microRNA target prediction easy, fast and flexible

    Nucleic Acids Research 34:W451–W454.

    https://doi.org/10.1093/nar/gkl243

    • PubMed
    • Google Scholar
33. 1. Kumsta C
    2. Chang JT
    3. Schmalz J
    4. Hansen M

    (2017) Hormetic heat stress and HSF-1 induce autophagy to improve survival and proteostasis in C. elegans

    Nature Communications 8:14337.

    https://doi.org/10.1038/ncomms14337

    • PubMed
    • Google Scholar
34. 1. Landis JN
    2. Murphy CT

    (2010) Integration of diverse inputs in the regulation of Caenorhabditis elegans DAF-16/FOXO

    Developmental dynamics : an official publication of the American Association of Anatomists 239:1405–1412.

    https://doi.org/10.1002/dvdy.22244

    • PubMed
    • Google Scholar
35. 1. Langmead B
    2. Salzberg SL

    (2012) Fast gapped-read alignment with Bowtie 2

    Nature Methods 9:357–359.

    https://doi.org/10.1038/nmeth.1923

    • PubMed
    • Google Scholar
36. 1. Liao Y
    2. Smyth GK
    3. Shi W

    (2014) featureCounts: an efficient general purpose program for assigning sequence reads to genomic features

    Bioinformatics 30:923–930.

    https://doi.org/10.1093/bioinformatics/btt656

    • PubMed
    • Google Scholar
37. 1. Longo VD
    2. Mitteldorf J
    3. Skulachev VP

    (2005) Programmed and altruistic ageing

    Nature Reviews Genetics 6:866–872.

    https://doi.org/10.1038/nrg1706

    • PubMed
    • Google Scholar
38. 1. Love MI
    2. Huber W
    3. Anders S

    (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

    Genome Biology 15:550.

    https://doi.org/10.1186/s13059-014-0550-8

    • PubMed
    • Google Scholar
39. 1. Lyons JM
    2. Keith AD
    3. Thomason IJ

    (1975)

    Temperature-induced phase transitions in nematode lipids and their influence on respiration

    Journal of Nematology 7:98–104.

    • PubMed
    • Google Scholar
40. 1. Ma DK
    2. Vozdek R
    3. Bhatla N
    4. Horvitz HR

    (2012) CYSL-1 interacts with the O2-sensing hydroxylase EGL-9 to promote H2S-modulated hypoxia-induced behavioral plasticity in C. elegans

    Neuron 73:925–940.

    https://doi.org/10.1016/j.neuron.2011.12.037

    • PubMed
    • Google Scholar
41. 1. Ma DK
    2. Li Z
    3. Lu AY
    4. Sun F
    5. Chen S
    6. Rothe M
    7. Menzel R
    8. Sun F
    9. Horvitz HR

    (2015) Acyl-CoA Dehydrogenase Drives Heat Adaptation by Sequestering Fatty Acids

    Cell 161:1152–1163.

    https://doi.org/10.1016/j.cell.2015.04.026

    • PubMed
    • Google Scholar
42. 1. Maere S
    2. Heymans K
    3. Kuiper M

    (2005) BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks

    Bioinformatics 21:3448–3449.

    https://doi.org/10.1093/bioinformatics/bti551

    • PubMed
    • Google Scholar
43. 1. Mahat DB
    2. Salamanca HH
    3. Duarte FM
    4. Danko CG
    5. Lis JT

    (2016) Mammalian Heat Shock Response and Mechanisms Underlying Its Genome-wide Transcriptional Regulation

    Molecular Cell 62:63–78.

    https://doi.org/10.1016/j.molcel.2016.02.025

    • PubMed
    • Google Scholar
44. 1. Mello CC
    2. Kramer JM
    3. Stinchcomb D
    4. Ambros V

    (1991)

    Efficient gene transfer in C.elegans: extrachromosomal maintenance and integration of transforming sequences

    The EMBO Journal 10:3959–3970.

    • PubMed
    • Google Scholar
45. 1. Metzstein MM
    2. Stanfield GM
    3. Horvitz HR

    (1998) Genetics of programmed cell death in C. elegans: past, present and future

    Trends in Genetics 14:410–416.

    https://doi.org/10.1016/S0168-9525(98)01573-X

    • PubMed
    • Google Scholar
46. 1. Morrison SF

    (2016) Central control of body temperature

    F1000Research 5:880.

    https://doi.org/10.12688/f1000research.7958.1

    • PubMed
    • Google Scholar
47. 1. Murray P
    2. Hayward SA
    3. Govan GG
    4. Gracey AY
    5. Cossins AR

    (2007) An explicit test of the phospholipid saturation hypothesis of acquired cold tolerance in Caenorhabditis elegans

    PNAS 104:5489–5494.

    https://doi.org/10.1073/pnas.0609590104

    • PubMed
    • Google Scholar
48. 1. Ohta A
    2. Ujisawa T
    3. Sonoda S
    4. Kuhara A

    (2014) Light and pheromone-sensing neurons regulates cold habituation through insulin signalling in Caenorhabditis elegans

    Nature Communications 5:ncomms5412.

    https://doi.org/10.1038/ncomms5412

    • PubMed
    • Google Scholar
49. 1. Peng Y
    2. Zhang M
    3. Zheng L
    4. Liang Q
    5. Li H
    6. Chen JT
    7. Guo H
    8. Yoshina S
    9. Chen YZ
    10. Zhao X
    11. Wu X
    12. Liu B
    13. Mitani S
    14. Yu JS
    15. Xue D

    (2017) Cysteine protease cathepsin B mediates radiation-induced bystander effects

    Nature 547:458–462.

    https://doi.org/10.1038/nature23284

    • PubMed
    • Google Scholar
50. 1. Peter ME

    (2011) Programmed cell death: Apoptosis meets necrosis

    Nature 471:310–312.

    https://doi.org/10.1038/471310a

    • PubMed
    • Google Scholar
51. 1. Polderman KH

    (2009) Mechanisms of action, physiological effects, and complications of hypothermia

    Critical Care Medicine 37:S186–S202.

    https://doi.org/10.1097/CCM.0b013e3181aa5241

    • PubMed
    • Google Scholar
52. 1. Ritchie A
    2. Gutierrez O
    3. Fernandez-Luna JL

    (2009) PAR bZIP-bik is a novel transcriptional pathway that mediates oxidative stress-induced apoptosis in fibroblasts

    Cell Death & Differentiation 16:838–846.

    https://doi.org/10.1038/cdd.2009.13

    • PubMed
    • Google Scholar
53. Book

    1. Sapolsky RM

    (2004)

    Why Zebras Don’t Get Ulcers (3rd Edn)

    New York: Holt Paperbacks.

    • Google Scholar
54. 1. Schmieder R
    2. Edwards R

    (2011) Quality control and preprocessing of metagenomic datasets

    Bioinformatics 27:863–864.

    https://doi.org/10.1093/bioinformatics/btr026

    • PubMed
    • Google Scholar
55. 1. Skulachev VP

    (1999)

    Phenoptosis: programmed death of an organism

    Biochemistry. Biokhimiia 64:1418–1426.

    • PubMed
    • Google Scholar
56. 1. Skulachev VP

    (2002) Programmed death phenomena: from organelle to organism

    Annals of the New York Academy of Sciences 959:214–237.

    https://doi.org/10.1111/j.1749-6632.2002.tb02095.x

    • PubMed
    • Google Scholar
57. 1. Smith JM

    (1964) Group selection and kin selection

    Nature 201:1145–1147.

    https://doi.org/10.1038/2011145a0

    • Google Scholar
58. 1. Solís EJ
    2. Pandey JP
    3. Zheng X
    4. Jin DX
    5. Gupta PB
    6. Airoldi EM
    7. Pincus D
    8. Denic V

    (2016) Defining the essential function of yeast Hsf1 reveals a compact transcriptional program for maintaining eukaryotic proteostasis

    Molecular Cell 63:60–71.

    https://doi.org/10.1016/j.molcel.2016.05.014

    • PubMed
    • Google Scholar
59. 1. Tansey EA
    2. Johnson CD

    (2015) Recent advances in thermoregulation

    Advances in Physiology Education 39:139–148.

    https://doi.org/10.1152/advan.00126.2014

    • PubMed
    • Google Scholar
60. 1. Thorvaldsdóttir H
    2. Robinson JT
    3. Mesirov JP

    (2013) Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration

    Briefings in Bioinformatics 14:178–192.

    https://doi.org/10.1093/bib/bbs017

    • PubMed
    • Google Scholar
61. 1. Vriens J
    2. Nilius B
    3. Voets T

    (2014) Peripheral thermosensation in mammals

    Nature Reviews Neuroscience 15:573–589.

    https://doi.org/10.1038/nrn3784

    • PubMed
    • Google Scholar
62. 1. Yenari MA
    2. Han HS

    (2012) Neuroprotective mechanisms of hypothermia in brain ischaemia

    Nature Reviews Neuroscience 13:267–278.

    https://doi.org/10.1038/nrn3174

    • PubMed
    • Google Scholar
63. 1. Yura T
    2. Nagai H
    3. Mori H

    (1993) Regulation of the heat-shock response in bacteria

    Annual Review of Microbiology 47:321–350.

    https://doi.org/10.1146/annurev.mi.47.100193.001541

    • PubMed
    • Google Scholar
64. 1. Zhou X
    2. Feng X
    3. Mao H
    4. Li M
    5. Xu F
    6. Hu K
    7. Guang S

    (2017) RdRP-synthesized antisense ribosomal siRNAs silence pre-rRNA via the nuclear RNAi pathway

    Nature Structural & Molecular Biology 24:258–269.

    https://doi.org/10.1038/nsmb.3376

    • PubMed
    • Google Scholar
65. 1. Zhu JK

    (2016) Abiotic stress signaling and responses in plants

    Cell 167:313–324.

    https://doi.org/10.1016/j.cell.2016.08.029

    • PubMed
    • Google Scholar

Author details

1. Wei Jiang

   1. Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
   2. Key Laboratory of Metabolism and Molecular Medicine, The Ministry of Education, Fudan University, Shanghai, China
   3. Department of Biochemistry and Molecular Biology, Shanghai Medical College, Fudan University, Shanghai, China
   4. Department of Physiology, University of California, San Francisco, San Francisco, United States

   Contribution

   Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing

   Contributed equally with

   Yuehua Wei and Yong Long

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-7615-0900

2. Yuehua Wei

   1. Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
   2. Department of Physiology, University of California, San Francisco, San Francisco, United States

   Contribution

   Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft

   Contributed equally with

   Wei Jiang and Yong Long

   Competing interests

   No competing interests declared

3. Yong Long

   1. Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
   2. Department of Physiology, University of California, San Francisco, San Francisco, United States
   3. State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China

   Contribution

   Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft

   Contributed equally with

   Wei Jiang and Yuehua Wei

   Competing interests

   No competing interests declared

4. Arthur Owen

   Department of Molecular Cell Biology, University of California, Berkeley, Berkeley, United States

   Contribution

   Investigation, Methodology, Writing—review and editing

   Competing interests

   No competing interests declared

5. Bingying Wang

   1. Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
   2. Department of Physiology, University of California, San Francisco, San Francisco, United States

   Contribution

   Resources, Investigation, Methodology

   Competing interests

   No competing interests declared

6. Xuebing Wu

   Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, United States

   Contribution

   Data curation, Formal analysis, Investigation, Visualization

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-0369-5269

7. Shuo Luo

   Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, United States

   Contribution

   Investigation, Methodology

   Competing interests

   No competing interests declared

8. Yongjun Dang

   1. Key Laboratory of Metabolism and Molecular Medicine, The Ministry of Education, Fudan University, Shanghai, China
   2. Department of Biochemistry and Molecular Biology, Shanghai Medical College, Fudan University, Shanghai, China

   Contribution

   Resources, Methodology

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-7237-1132

9. Dengke K Ma

   1. Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
   2. Department of Physiology, University of California, San Francisco, San Francisco, United States

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing—original draft, Project administration, Writing—review and editing

   For correspondence

   Dengke.Ma@ucsf.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5619-7485

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