Abstract
The unfolded protein response (UPR) is activated, when the folding capacity is compromised in the endoplasmic reticulum (ER). To date, most studies focused on the coding genes and microRNAs in UPR. Other non-coding RNAs affected by UPR and their roles in UPR have not been systematically studied. Long noncoding RNAs (lncRNAs) are increasingly recognized as powerful epigenetic regulators. In this study, we transcriptomically profiled the lncRNAs and mRNAs from mouse embryonic fibroblasts under ER stress, and identified many differentially expressed lncRNAs and mRNAs. Genomic location and mRNA-lncRNA co-expression analyses predicted a number of lncRNAs, which potentially regulate the expression of UPR genes. In particular, FR229754, an exonic sense lncRNA, is significantly up-regulated in UPR. FR229754 overlaps with Sel1l, and their expressions correlated with each other. Sel1l is involved in the ER-associated protein degradation. Silencing of FR229754 did not much affect the expression of Sel1l, but markedly reduced the levels of BiP/GRP78/Hspa5, a major ER chaperon up-regulated in UPR. Probing with pathway-specific inhibitors showed that up-regulation of FR229754 and Sel1 depended on the activation of PERK. Together, our study identified a number of candidate lncRNAs and paved the way for future characterization of their functions in UPR.
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Introduction
In eukaryotic cells, the endoplasmic reticulum (ER) is a major organelle that the secretory and membrane proteins enter the secretory pathway to fold, modify and mature. Environmental, physiological and pathophysiological conditions may alter the flux of proteins into the ER and exceed its folding capacity. The resulted accumulation of unfolded proteins activates multiple adaptive cellular processes, which are collectively known as ER stress response and include the unfolded protein response (UPR)1. UPR originally protects the cells to survive the stress insult, and could commit the cells to apoptosis, if the adaptive responses fail to restore the ER proteostasis.
In mammalian cells, UPR encompasses three branches, namely the inositol-requiring protein-1α (IRE1α), activating transcription factor-6α (ATF6α) and protein kinase RNA (PKR)-like ER kinase (PERK)2,3. In the unstressed cells, IRE1α, ATF6α and PERK are bound to BiP/GRP78/Hspa5, a major chaperon in the ER lumen. Upon ER stress, BiP binds to the unfolded proteins accumulated in the ER lumen and dissociates from the three UPR sensors. IRE1α, ATF6α and PERK are then activated by a series of events, including dimerization, phosphorylation, endonuclease splicing, ER-Golgi trafficking and proteolytic processing, and generate three respective downstream transcription factors, namely X-box binding protein 1(XBP1), activating transcription factor 4 (ATF4) and ATF6α. XBP1, ATF4 and ATF6α signal the nucleus to increase the ER chaperon expression to assist protein folding, the phospholipid synthesis to expand the ER, and the ER-associated protein degradation (ERAD) to remove the unfolded proteins through the ubiquitin proteasome system2,3,4.
UPR is regulated by multiple cellular mechanisms including microRNAs. Dozens of microRNAs are differentially expressed after the treatment with ER stress inducers, such as tunicamycin and thapsigargin. Several differentially expressed microRNAs also function as modulators of UPR. For example, miR-30c-2* is up-regulated in UPR by PERK, and in turn attenuates UPR by decreasing XBP15. MiR-211, which is also induced after PERK activation, represses the CHOP transcription by targeting its 5′ untranslated region6. Some microRNAs can affect the expression of UPR-unrelated proteins. For example, miR-708, which is transcribed from an intron of a CHOP-regulated gene, Odz4, controls the expression of rhodopsin in retina and prevents it from entering the ER7.
In the past decade, long noncoding RNAs (lncRNAs) have emerged as another class of non-protein coding RNAs, which play important regulatory roles in multiple cellular processes8. lncRNAs can be classified as intronic, exonic, overlapping and intergenic lncRNAs, based on their locations in regard to the nearest protein-coding genes9. Exonic lncRNAs can be further classified as sense and antisense lncRNAs based on the direction of transcription. The long intergenic noncoding RNAs, also known as lincRNAs, are found to contain introns, exons and polyadenylated tails similarly as the mRNAs, and can be spliced to different transcripts10,11.
Mechanistically, lncRNAs regulate gene transcription either in cis or in trans. For example, Xist, which is transcribed from one X chromosome, activities the X chromosome silencing12,13,14. HOTAIR, which is transcribed from the HOXC cluster, interacts with the Polycomb repressive complex 2 to represses the transcription of the HOXD cluster in trans15,16. Some lncRNAs post-transcriptionally regulate genes expression by affecting the pre-mRNA splicing and mRNA translation. MALAT1, a nuclear lncRNA widely associated with cancer metastasis, affects the phosphorylation of serine/arginine-containing splicing factors17. lncRNAs can also function as competing endogenous RNAs (ceRNAs) to interact with microRNAs and antagonize the microRNA-mediated regulation. For example, HULC, a lncRNA highly up-regulated in liver cancers, can act as a ceRNA to sponge miR-372, and reduce the transcriptional repression of miR-372 targets genes18.
In addition to the microRNAs affected by or modulating UPR, several lncRNAs have also been linked with UPR19. The expression of calreticulin, an ER chaperone involved in glycoprotein folding, is regulated by miR-455 and ncRNA-RB1, a lncRNA that shares a bidirectional promoter with the RB1 gene. Silencing of ncRNA-RB1 reduced calreticulin levels20. Malat1 was reported to be up-regulated about two fold in UPR, and the up-regulation depended on PERK activation21. A megacluster of microRNAs and their host long non-coding RNA transcript (lnc-MGC) are increased in the glomeruli of mouse models of diabetic nephropathy22. Lnc-MGC appears to be regulated by CHOP, a transcription factor downstream of PERK. Lnc-MGC plays a role in glomerular extracellular matrix formation and hypertrophy in diabetic mice, possibly through interaction with the cluster microRNAs. Hypoxia significantly increased the expression of HypERlnc, a lncRNA in pericytes and perivascular mural cells23. HypERlnc has been suggested to regulate both the viability and permeability of pericytes and endothelial cells and UPR activation, which is believed to contribute to the development of many cardiopulmonary diseases.
To date, the global expression profile of lncRNAs under ER stress has not been reported. In this study, we used a comprehensive mRNA/lncRNA microarray to examine the transcriptome of MEFs under ER stress, and identified a large number of differentially expressed lncRNAs and mRNAs. We then performed genomic location and mRNA-lncRNA co-expression analyses to identify several candidate lncRNAs, which potentially regulate the expression of UPR genes. In particular, we carried out characterization of the functional involvement and expression of FR229754, an up-regulated lncRNA, in UPR.
Results
Time course of UPR activation in MEFs
Before performing microarray analysis, we first determined the time course of the UPR activation in MEFs. The MEFs were treated with 5 μg/ml tunicamycin, 200 nM thapsigargin or vehicle control for up to 24 h, and the cells were harvested at 0, 4, 8, 12, 16, 24 h, respectively. Real-time PCR experiments showed that the expression of BiP, IRE1α, PERK, ATF6α, Chop and ATF4, another transcription factor downstream of PERK, steadily increased over 24 h (Fig. 1a). The expression of IRE1β and ATF6β, the isoforms of IRE1α and ATF6α that are not activated in UPR, remained largely unchanged (Supplementary Fig. 1). Analysis of Xbp-1 splicing showed that Xbp-1 became fully spliced, which indicated the activation of the IRE1α branch, as early as 4 h (Fig. 1b). These results together demonstrated that the transcriptional up-regulation of many UPR target genes increased over 24 h in MEFs, and the three branches were likely activated in different chronological orders, a finding consistent with several previous reports24,25,26. Because prolonged UPR activation is known to trigger apoptosis, we also examined the cleavage of poly (ADP-ribose) polymerase (PARP) in MEFs treated with tunicamycin and thapsigargin. Much lower or undetectable PARP cleavage was seen in the MEFs treated with tunicamycin or thapsigargin for 4 to 16 h, but the cleavage was significantly increased in the MEFs with UPR induced for 24 h, indicating that apoptosis was minimal at 16 h under these conditions (Fig. 1c). Therefore we chose 16 h as an arbitrary time point to analyze the expression profile of mRNAs and lncRNAs from the tunicamycin-treated MEFs.
Microarray analysis of lncRNA and mRNA profiles in MEFs
Our microarray contains 51,302 probes, which were 60-nucleotide long and designed to hybridize with the entire mouse transcriptome of 24,239 mRNAs and 35,757 lncRNAs. The mouse lncRNAs were pooled from the several lncRNA databases: Ensembl, RefSeq, Ultra-conserved region encoding LncRNA (UCR), lncRNAdb, ncRNA and NONCODE. In our study, the expression of 881, 69 and 13 lncRNAs, and 976, 129 and 32 mRNAs was found to change over 2, 5 and 10 fold in the tunicamycin-treated MEFs, respectively (Fig. 2a). The mRNAs and lncRNAs changed over 5 fold are shown in heatmaps (Fig. 2b,c). Chop, Herpud1 (homocysteine inducible er protein with ubiquitin like domain 1), Ero1lb (endoplasmic reticulum oxidoreductase 1β), BiP and Hrd1/Snyn1 (HMG-CoA reductase degradation 1/synoviolin 1) were among the most strongly up-regulated genes (DEGs) (Fig. 2b). 15 and 54 lncRNAs increased or decreased over 5 fold, respectively, and they were further categorized into 13 intergenic, 18 intronic, 32 exonic sense, 2 exonic antisense and 4 overlapping lncRNAs.
The top 500 differentially expressed lncRNAs are predicted to be involved in several molecular functions, namely protein binding, ion binding and catalytic activity, and participate in a host of biological processes: metabolism, localization biosynthesis and transport (Fig. 2d,e). We then used real-time PCR to validate the expression of six randomly selected lncRNAs (n278914, n290844, FR223708, n416682, FR346657 and FR091011) and mRNAs (Calnexin, Calreticulin, Krt20, Has2, Hrd1 and Edem), which were differentially expressed after UPR activation as identified by the microarray study. Comparable trend of change was seen by both techniques from the RNAs prepared from three independently cultured MEFs (Fig. 3a). Furthermore, we examined the time course of FR346657, FR091011, Hrd1 and Edem expression in MEFs treated with 5 μg/ml tunicamycin for up to 24 h (Fig. 3b). Most of their expression reached planteu at 8 h, and subsequently decreased or maintained throughout 24 h.
Genomic locations of the differentially expressed lncRNAs in UPR
We next analyzed the chromosomal distribution of the lncRNAs differentially expressed greater than twofold after UPR activation, and found that these transcripts scattered widely on all chromosomes (Supplementary Fig. 2). Several recent studies have suggested that the expression patterns of many lncRNAs strongly correlate with their neighboring/overlapping coding genes8. We therefore examined the presence of any coding genes neighboring or overlapping with the most differentially expressed lncRNAs identified in the microarray study. We found that, among the lncRNAs differentially expressed over 5 fold, 22 lncRNAs neighbor or overlap with 22 coding genes, whose expressions also significantly changed in UPR (Table 1). These 22 lncRNAs include one lincRNA (n290468), nine intronic lncRNAs (FR322715, FR342061, FR315668, FR197614, FR351780, FR333518, FR378244, FR201427 and FR262136), nine exonic sense lncRNAs (FR223709, FR167504, n285450, n281650, FR229754, FR086606, FR095406, FR378356 and FR366793), one exonic antisense lncRNA (FR159674) and two overlapping lncRNAs (n295470 and n266048). The expressions of most lncRNAs in this group changed in the same direction as their nearest genes, with comparable fold.
Notably, the nearest gene to an exonic sense lncRNA, FR229754, is Sel1l, which encodes the mammalian homologue of yeast Hrd3p. Sel1l, which encodes the mammalian homologue of yeast Hrd3p. Hrd3p is a binding partner of Hrd1p, an E3 ubiquitin ligase essential in the ERAD and highly up-regulated in UPR (Fig. 2b). SEL1L knockout cells are defective in the degradation of misfolded ER luminal proteins27. The expressions of FR229754 and Sel1l were up-regulated over 8 and 11 fold in UPR, respectively, as shown by the microarray analysis. The rest lncRNA-neighbouring/overlapping genes include Adam12, Pls3, Cacna1c, Pde8b, Errfi1, Dlc1, Cxadr, Krt20, Sh3kbp1, Mical2, Prss16, Has2, Grb14, Kif26b, Slc7a11, Nudt6, Igfbp5 and Mylk, respectively, which encode proteins involved in a wide spectrum of cellular functions from cytoskeleton organization, ion transport, glucose metabolism to extracellular matrix formation. For example, Adam12, which encodes a disintegrin and metalloprotease involved in cell adhesion and extracellular matrix formation, overlaps with a lincRNA, n290468. Hyaluronan synthase 2 (Has2) is involved in hyaluronan synthesis and extracellular matrix formation, and is next to an exonic sense lncRNA, FR086606. Real-time PCR and immunoblotting analysis confirmed the transcriptional up-regulation of FR229754 and Sel1l and down-regulation of n290468 and Adam12 in three independent sets of tunicamycin-treated MEFs (Fig. 4a), their trend of change over the course of UPR for up to 24 h (Fig. 4b), and the up-and down-regulation of Sel1l and Adam12 at protein level (Supplementary Fig. 3).
lncRNA functions predicted by lncRNA-mRNA co-expression analyses
We next identified the mRNAs that were expressed in a fashion statistically correlated with the above-identified lncRNAs, using lncRNA-mRNA co-expression analysis. The identified mRNAs might be expressed under the same promoter, i.e. in the comparable trend as the lncRNA, or represent the possible targets that were regulated by the lncRNA. FR229754 and n290468, which overlaps with Sel1l and Adam12, respectively, were co-expressed with a large number of UPR genes, in addition to genes and from other cellular pathways, e.g. extracellular matrix (ECM), PI3 kinase (PI3K)-Akt, MAP kinase (MAPK) and glucose metabolism (Fig. 5a,b). FR229754 correlated with the expression of many UPR genes, including several ER chaperones and ERAD components, e.g. Sel1l, BiP, Edem, Ero1, DnaJ and Derl3 (Fig. 5a). n290468 was also co-expressed with many UPR genes and several ECM genes including Adam12 (Fig. 5b).
The functional impact and expression of FR229754
Because the expression of FR229754 correlated with Sel1l and many UPR genes, and it was strongly up-regulated in UPR, we next examined the impact of FR229754 silencing on the expression of Sel1l and BiP. Two small interfering RNAs designed against FR229754 reduced the expression of FR229754 in the unstressed and tunicamycin-treated MEFs, with si-2 being more potent (Fig. 6a). Interestingly, the level of Sel1l was not much affected by FR229754 in the MEFs transfected with si-2, while the level of BiP was greatly reduced and especially in the tunicamycin-treated MEFs transfected with si-2, suggesting that the level of FR229754 affects the up-regulation of BiP in UPR (Fig. 6b,c).
We further analyzed which UPR branch was more intimately involved in the expression of FR229754 and Sel1l. In order to assess the contribution of each UPR branch (Ire1α, Perk and Atf6) to lncRNA expression, we used the specific inhibitors targeting Ire1α, Perk and Atf6α, respectively. 4μ8C, GSK2606414 and Ceapin-A7, inhibit the XBP1 splicing, PERK phosphorylation and the ER-Golgi trafficking of ATF6, respectively28,29,30. Several studies have suggested that the transcriptional regulation of UPR target genes relies on the activation of individual UPR branch, i.e. Ire1α-, Perk- and Atf6α-dependent26,31,32, although overlap in some target genes has also been reported25. Real-time PCR analysis (Supplementary Fig. 4) confirmed that treatment with 4μ8C, GSK2606414 and Ceapin-A7 induced similar changes to many UPR gene [including ER chaperones (BIP), PERK downstream effector (Chop, ATF4) and ERAD effector (EDEM and p58)] expression, in a comparable fashion as the IRE1α-, PERK- and ATF6α-deficient MEFs25. In our experiment, incubation with GSK2606414, not 4μ8C and Ceapin-A7, largely reversed the increase of FR229754 and Sel1l induced by tunicamycin treatment, suggesting that the activation of Perk branch, not Ire1α and Atf6α, mediates the transcriptional up-regulation of FR229754 and Sel1l (Fig. 7a,b).
Discussion
In this study, we examined the transcriptomic profiles of lncRNAs and mRNAs of MEFs treated with ER stress-inducing compound. Our data of the mRNA profiles in MEFs treated with tunicamycin are consistent with previous profiling studies in MEFs and other tissues33,34,35,36,37. Interestingly, we found that genes from pathways seemingly unrelated to the ER were also significantly altered after UPR activation. These include genes responsible for cell adhesion and extracellular matrix remodeling, e.g. Adam12, Has2 and collagen isoforms (CO1A1, CO1A2 and CO6A1). Similar findings were reported by a proteomics study36. Our lncRNA-mRNA co-expression analysis also showed that FR229754 and n290468 were co-expressed with genes from other cellular pathways such as ECM, PI3K-Akt, MAPK and glucose metabolism. These results strongly suggest that the activation of UPR induces the adaptive changes in multiple cellular processes, in addition to the canonical ER proteostasis-regulating pathway. How the canonical and noncanonical pathways coordinate in the activation and maintenance of UPR awaits future characterization. Some lncRNAs identified in this study may link these pathways together.
We used two approaches to probe the potential functions of the differentially expressed lncRNAs in UPR. First, by identifying the genomic location of the most differentially expressed lncRNAs, we predicted that the genes, which neighbor or overlap with the differentially expressed lncRNAs, may be their cis targets. On the other hand, we used the lncRNA-mRNA network to identify the mRNAs, whose expressions correlated with two differentially expressed lncRNAs, FR229754 and n290468. The identification of Sel1l and Adam12 as their co-expressing mRNAs corroborated our genomic location approach. A host of lncRNAs are known to regulate the expressions of their target genes at epigenetic (as recruiters, tethers and scaffolds) and transcriptional (as decoys, coregulators, and RNA polymerase II inhibitors) levels8. Future studies are required to characterize how the lncRNAs identified by these two approaches mechanistically affect the expression of their potential target genes, including UPR-related and unrelated genes.
One interesting lncRNA candidate identified from this study is FR229754, which overlaps with Sel1l in terms of genomic sequence and correlated with Sel1l and other UPR genes such as BiP at expression level. Studies in yeast and higher organisms have identified three different pathways for the degradation of ERAD substrates, depending on the location of the misfolded domains, namely ERAD-L, ERAD-M and ERAD-C (with misfolding in the ER lumen, inside the ER membrane and on the cytosolic side of a transmembrane protein, respectively)38. The ERAD-L pathway is further categorized into the ERAD-Ls (for degradation of soluble luminal proteins) and ERAD-Lm (degradation of transmembrane proteins) pathways39. In yeast and higher organisms, Hrd1p is shown to is shown to recognize and degrade ERAD-L and ERAD-M substrates, whereas the other evolutionarily conserved ER ubiquitin ligase Doa10/TEB4 mediates ERAD-C substrate degradation38,39,40,41,42.
Mammalian and chicken Sel1l have been shown as an essential component required for the degradation of ERAD-Ls, but not ERAD-Lm substrates27,39,40,41. Sel1l knockout mice suffer embryonic lethality43. Silencing of FR229754 greatly reduced the level of BiP, indicating that FR229754 level affects the chaperone adaptive response in UPR. We further used specific inhibitors and demonstrated that the transcriptional up-regulation of FR229754 and Sel1l is dependent on the activation of Perk branch. Because the inhibitors used to block the three UPR pathways likely have off-target effects, future studies using the MEFs isolated from IRE1α-, PERK- and ATF6α-deficient mice would be required to validate and compare with the findings of our study. In summary, our study identified a large number of differentially expressed lncRNAs after the UPR activation. The lncRNAs and the possible mRNA targets predicted by the bioinformatic analysis in this study lay a foundation for future functional characterization of non-coding RNAs in UPR.
Methods
Animals
Pathogen-free male and female C57BL/6 J mice were purchased from Vital River Laboratory Animal Technology Co. Ltd. (Beijing, China). 10-week-old mice were mated in a temperature-controlled room with a 12-h light/dark cycle. Pregnancy was assessed by visual inspection of a distended abdomen. The animal protocol followed the “Principles of laboratory animal care” (NIH publication No. 86-23), and was approved by the Ethics Committee of Peking Union Medical College.
Cell culture and chemicals
Mouse embryonic fibroblasts (MEFs) were isolated from pregnant mice at E13.5 and cultured in DMEM containing 10% fetal bovine serum as previously described44. Tunicamycin, thapsigargin, 4μ8C and GSK2606414 were purchased from Calbiochem. Ceapin-A7 was a generous gift from Drs. Ciara Gallagher and Peter Walter (University of California San Francisco). All other chemicals were purchased from Sigma-Aldrich, unless stated otherwise. To induce ER stress, MEFs were treated with 5 μg/ml tunicamycin (Tm) for up to 24 hours. To inactivate each UPR branch (Ire1α, Perk and Atf6α), the MEF cells were treated with 10 μM 4μ8C, 10 μM GSK2606414 and 10 μM Ceapin-A7.
RNA extraction and reverse transcription-polymerase chain reaction
Total RNAs were extracted from cells using Trizol (Invitrogen, USA), following the manufacturer’s instruction. The concentration and purity of the RNA samples were determined using a NanoDrop 2000C (Thermo Scientific, USA). 1.5 μg of RNA was reverse transcribed to cDNA using oligo(dT) and random primers with the TransScript First-Strand cDNA Synthesis SuperMix kit (TransGen Biotech, Beijing). The Xbp1 splicing was detected by standard reverse transcription-polymerase chain reaction using 2 × Taq PCR StarMix (GenStar, Beijing). The specific primers for murine Xbp1 and Glyceraldehyde-3-phosphate dehydrogenase (Gapdh) are as follows: Xbp1: Forward, GAACCAGGAGTTAAGAACACG; Reverse, AGGCAACAGTGTCAGAGTCC; Gapdh: Forward, GGCCTCCAAGGAGTAAGA; Reverse, GTGCAGCGAACTTTATTGA.
Microarray analysis
The OE Mouse lncRNA Microarray V2.0 (OEBiotech, Shanghai) was used for the global profiling of mouse lncRNAs and protein-coding transcripts. Total RNAs were quantified and the RNA integrity was assessed using Agilent Bioanalyzer 2100 (Agilent Technologies, USA). The labeling, microarray hybridization and wash were performed by the microarray facility at OEBiotech, Shanghai. Briefly, cDNAs were transcribed from total RNAs, synthesized to cRNAs and labeled with cyanine-3-CTP. The labeled cRNAs were then hybridized onto the microarray. After wash, the fluorescent signals were scanned using the Agilent Scanner G2505C (Agilent Technologies, USA).
Feature Extraction software V10.7.1.1 (Agilent Technologies, USA) was used to analyze the array images to obtain the raw data, which was further analyzed by Genespring software (Agilent Technologies, USA). The differentially expressed protein-coding genes and lncRNAs were identified, and fold change as well as P value from the statistics t-test were calculated. We set a limit for the up- or down-regulated lncRNAs as fold change ≥ 2.0 and P value ≤ 0.05.
Real-time quantitative PCR (Real-time PCR)
Primers for mRNA or lncRNA used in real-time PCR were designed using Primer 6 software (PREMIER Biosoft, USA), and then verified using the Basic Local Alignment Search Tool (BLAST) from National Centre for Biotechnology Information. Sequence information is as follows: Ire1α: Forward, 5′-TTCTGAGGTTCTTAGCCA-3′; Reverse, 5′-CATGCATTCACAAACATGA-3′; Atf4: Forward, 5′-CCTGATAGAAGAGGTCCG-3′; Reverse, 5′-GGTACTTTCACTACAAAATAAT-3′; Perk: Forward, 5′-ATTTATGTCGGTAGTGTCA-3′; Reverse, 5′-CTTGAAAGAAGTCATAATAGTT-3′; BiP: Forward, 5′-CAGAGTGGAGTTGAAAAT-3′; Reverse, 5′-AAAATTAGACCAGTGTAAA-3′; Chop: Forward, 5′-CCTGCCTTTCACCTTGGA-3′; Reverse, 5′-GCTTTGGGATGTGCGTGT-3′; Atf6α: Forward, 5′-TGAGCAGCTGAAGAAGGAGA-3′; Reverse, 5′-TTCTCTGACACCACCTCGTC-3′; Sel1l: Forward, 5′-TTCGTCTGGCTGCTTGGT-3′; Reverse, 5′-TGCGTATCTTCTTGCGTGTT-3′; Adam12: Forward, 5′-TGGGACCAGAGAGGAGCTTAC-3′; Reverse, 5′-GTTGCACAGTCAGCACGTCT-3′; Has2: Forward, 5′-GAGCACCAAGGTTCTGCTTC-3′; Reverse, 5′-CTCTCCATACGGCGAGAGTC-3′; Krt20: Forward, 5′-GTGGCTCGCTGTATAGGAAGG-3′; Reverse, 5′-CAGGTCCGATCCGTTGGAG-3′; Hrd1: Forward, 5′-AGCTACTTCAGTGAACCCCACT-3′; Reverse, 5′-CTCCTCTACAATGCCCACTGAC-3′; Edem: Forward, 5′-TCTACATGCGCCAGATCGAC-3′; Reverse, 5′-TCGACAGCATCACAGATGGG-3′; Ire1β: Forward, 5′- TGAGGAACAAGAAGCACCACT-3′; Reverse, 5′- AGAGCTGGTGGGTAGTAGGG-3′; Atf6β: Forward, 5′- GAGGAGCAGGCACAGTTGTT-3′; Reverse, 5′- AAGATGGGTAGAGGGTCCCA-3′; p58ipk: Forward, 5′-GCTGAACTCCGTTCTGTCCA-3′; Reverse, 5′-TCGACAGCATCACAGATGGG-3′; Calnexin: Forward, 5′-GCTAGGGAGAATGAATTGCCG-3′; Reverse, 5′- TTGGGCTTCCATCCAATCGC-3′; Calreticulin: Forward, 5′-TACAAGGGCGAGTGGAAACC-3′; Reverse, 5′-GCATCGGGGGAGTATTCAGG-3′; Gapdh: Forward, 5′-CCCAACACTGAGCATCTCC-3′; Reverse, 5′-GGGTGCAGCGAACTTTATT-3′; FR223708: Forward, 5′-ATTAAAGCAGTTACACCCAGCA-3′; Reverse, 5′-ACCCAACGCTACCATCCAC-3′; FR229754: Forward, 5′-GGTCGCCCTGCCCACA-3′; Reverse, 5′-AAACCCCAGCGTGTCCC-3′; FR091011: Forward, 5′-AGGACTAGAGTAAGCAGGAGA-3′; Reverse, 5′-TTCACGGCTGTGGGTTGA-3′; FR346657: Forward, 5′-GTGCGGTGGTTACAGAAG-3′; Reverse, 5′-CAGTCCCAGGTGGCATCC-3′; n290468: Forward, 5′-AGCCAAACACTCAACTGGAC-3′; Reverse, 5′-GGCCTCCTTTCCAACATGCTT-3′; n416682: Forward, 5′-AAGGCAAACCAAACAGAC-3′; Reverse, 5′-TACAGCACGGATGAAGAG-3′; n290844: Forward, 5′-GCGTAGAGGGCAGGTATTGT-3′; Reverse, 5′- CAGGAATCAGACCCACGGAA-3′; n278914: Forward, 5′-GTGGCCCAGATCTTTCCATCT-3′; Reverse, 5′-AAGGCCAGACTGGGGAGAAG-3′. The real-time PCR reactions were performed in 96-well optical plates using StepOnePlusTM Real-time PCR system (Applied Biosystems) with SYBR Green PCR Master Mix (TransGen Biotech, Beijing). All experiments were performed in triplicate, and all samples were normalized to the expression of Gapdh.
Genomic sequence analysis
The genomic sequence of murine lncRNAs and mRNAs were obtained using the UCSC genome browser (http://genome.ucsc.edu/) and the following databases: Ensembl, RefSeq, Ultra-conserved region encoding LncRNA (UCR), lncRNAdb, ncRNA and NONCODE. The chromosome locations of lncRNAs were annotated by the version of Dec. 2011 (GRCm38/mm10).
Construction of the lncRNA-mRNA co-expression network
The lncRNA-mRNA co-expression network was constructed using the normalized signal intensity of each differentially expressed lncRNA identified from the microarray study against the normalized signal intensity of every mRNA. The Pearson correlation was calculated for each lncRNA-mRNA pair, and then the pairs with correlation coefficient > 0.99 and P-value < 0.05 were deemed significant.
Gene ontological analysis
Gene ontology (GO) (http://www.geneontology.org) was used to assign the co-expressed mRNAs to GO terms and thereby predict the potential molecular functions and biological processes that one lncRNA may be involved. Briefly, we annotated the GO terms of the co-expressed mRNAs for each lncRNA, and then conducted a functional enrichment for the co-expressed mRNAs by summating the GO terms. The enriched functional terms were used to access the involvement of one given lncRNA in biological processes, cellular components and molecular functions. KEGG pathway analyses were performed to predict the biological pathways (http://www.genome.ad.jp/kegg/).
Immunoblotting
Total cellular proteins were prepared using a lysis buffer [20 mM HEPES pH7.5, 150 mM NaCl, 1% Triton-X100, 10% glycerol, 1 mM EDTA 10 mM tetrasodium pyrophosphate, 100 mM NaF, 17.5 mM β-glycerophosphate, 1 mM phenylmethysulfonyl fluoride and protease inhibitor cocktail (Roche)]. The protein lysates were analyzed by SDS-polyacrylamide gel electrophoresis (SDS-PAGE), electrotransferred to polyvinylidene difluoride (PVDF) membranes, and then subjected to immunoblotting using a standard protocol. The primary antibodies used in this study include: PARP (Cell Signaling Technology, 9542), Adam12 (Proteintech, 14139-1-AP), Sel-1l (Santa Cruz, sc-377350), β-actin (Molecular Biological Laboratories, PM053), GAPDH (Proteintech, 60004-1-Ig). After incubation with peroxidase-conjugated secondary antibody (anti-Rabbit IgG, 074-1506, KPL; anti-Mouse IgG, 330, Molecular Biological Laboratories), the proteins of interest were visualized with Clarify Western ECL Substrate (Bio-Rad).
RNA interference
RNA interference was performed using RNAiMAX (Invitrogen). Briefly, MEFs were seeded in 6-well plates and cultured overnight, and transfected with siRNA oligonucleotides (50 nmol per well) with RNAiMAX according to the manufacturer’s instruction. 48 h after transfection, cells were harvested for further analysis. The siRNA oligonucleotides were designed using an on-site algorithms and synthesized by GenePhama (Shanghai, China) as follows: FR229754: siRNA-1: 5′-GCAGCAAACUUUAGGUGAC-3′; siRNA-2: 5′-UCGACUAGCUGACUUACAU-3′. Non-targeting (NT) siRNA: 5′-UUCUCCGAACGUGUCACGU-3′ was also purchased from GenePhama (Shanghai, China).
Statistical analysis
Expression ratios were subjected to a log2 transformation to produce fold-change data. Differential expression levels of lncRNAs and mRNAs were compared, using an independent sample t-test between two groups. P < 0.05 was considered significant.
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Acknowledgements
We thank the members of the laboratory of L.W. for helpful discussions. This work was supported by grants from the National Natural Science Foundation of China (81372201), Ministry of Science and Technology of the People’s Republic of China (2016YFC1302203 and 2012CB517504) to L.W.
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L.W., H.Q. and C.L. conceived and designed the experiments; H.Q., Q.F. and C.L. performed the experiments; H.Q. and Y.Y.W. performed the bioinformatic analysis; H.Q., Q.F. and L.W. analyzed data; L.W. wrote the manuscript.
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Quan, H., Fan, Q., Li, C. et al. The transcriptional profiles and functional implications of long non-coding RNAs in the unfolded protein response. Sci Rep 8, 4981 (2018). https://doi.org/10.1038/s41598-018-23289-3
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DOI: https://doi.org/10.1038/s41598-018-23289-3
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