Hypoxia is an environmental risk factor for many disorders throughout life. Perinatal hypoxia contributes to autism spectrum disorder (ASD), while hypoxic conditions in the elderly facilitate memory deficits. However, the effects of hypoxia on adolescence remains elusive. CNTNAP2 is a critical molecule in ASD pathogenesis with undefined mechanisms. We investigate hypoxia’s impact on adolescence and the underlying mechanism related to CNTNAP2.Three-chamber social approach test, Y maze, Morris Water Maze and Open Field Test were applied to evaluate behavioral alterations. Immunoblotting, 5′- RACE and dual-luciferase reporter assay were performed to examine CNTNAP2 protein expression, transcription start site (TSS) of human CNTNAP2 gene and CNTNAP2 promoter activity, respectively.Intermittent hypoxia treatment improved social behaviors and working memory in adolescent mice. CNTNAP2 was increased in the brains of hypoxia-treated mice. The sequencing results identified the TSS at 518 bp upstream of the translation start site ATG. Hypoxia upregulated CNTNAP2 by interacting with functional hypoxia response elements in CNTNAP2 promoter.Intermittent hypoxia enhanced sociability and working memory associated with CNTNAP2 upregulation. Our study provides novel insights into intermittent hypoxia’s impact on development and the interaction between genetic and environmental risk factors in ASD pathogenesis. Oxygen homeostasis is crucial for the survival of organisms, and the brain is especially susceptible to hypoxia due to its vast demand for oxygen . HypoxiaAlthough the exact mechanisms underlying hypoxia’s impact on brain functions remain unclear, transcription factor hypoxia-inducible factor 1 (HIF-1) is the unquestionable regulator of the brain’s response to hypoxia, like elsewhere in the body . HIF-1 iAs an environmental risk factor for neurodevelopmental disease, hypoxia has been intensively studied in prenatal and perinatal stages. Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterizing social communication deficits and repetitive/restrictive behaviors and interests . In clinCNTNAP2 gene locates in chromosome 7, encoding an eponymous protein belonging to the neurexin superfamily. CNTNAP2 protein was initially found as an adhesion molecule connecting neurons and glial cells  cell genomic DNA by PCR and cloned into the pGL3-Basic vector (Promega Cat# E1751). A series of deletion fragments were sub-cloned into the pGL3-Basic vector upstream of the luciferase reporter gene using pCNTNAP2-A as the template and proper restrictive enzymes. The primers with restrictive enzyme sites were synthesized as listed in A 2,868 bp  5′-flanking region of the human Total RNA was extracted from a human fetus brain sample by TRI reagent as instructed by the manufacturer (Sigma). 5′-RACE assay was conducted using the Smarter RACE 5′/3′ kit (Clontech) following the user manual. 1 ug total RNA was used to synthesize the 5′-RACE-Ready first-strand cDNA template. Using this cDNA template, 5′ rapid amplification of cDNA ends (RACE) was performed through PCR reactions with universal forward primer (provided in the kit) and the CNTNAP2-specific reverse primer (5′-GATTACGCCAAGCTT aagaggaaggcagagcgacggggacggt). The 5-RACE product was cloned into the pRACE vector via In-Fusion HD Cloning. The transcription start site (TSS) was mapped by sequencing independent colonies from the cloning.RRID:CVCL_0045) was cultured in Dulbecco’s Modified Eagle Medium (Cytiva Cat# SH30243.01) supplemented with 10% fetal bovine serum (Gibco Cat# 12483020), 100 U/mL Penicillin-Streptomycin (Gibco Cat# 15140122). Rat pheochromocytoma-derived PC12 cell line (RRID:CVCL_F659) was maintained in the same DMEM medium supplemented with 15% fetal bovine serum. Cells were seeded in a 48-well plate at the seeding density of 0.05 × 106/well and maintained in an incubator at 37°C with 5% CO2. Cell transfections were performed with Polyethylenimine. For hypoxia treatment, transfected cells were maintained at 37°C in an incubator with 21% O2 as the control treatment or in an incubator with 2% O2 as the hypoxia treatment for 24 h.Human embryonic kidney 293 (HEK) cell line . Firefly and Renilla luciferase activities were sequentially measured using the Dual-Luciferase Reporter Assay System (Promega Cat# E1980). Relative luciferase units (RLU) were calculated by normalizing Firefly luciferase activities to the corresponding Renilla luciferase activities to reflect the relative promoter activities.To examine the promoter activity for pCNTNAP2 constructs, PC12 cells were co-transfected with 250 ng Firefly luciferase plasmids  and 0.5 ng Renilla luciferase plasmid pCMV-Luc to control for the transfection efficiency. To examine the effects of HIF-1α on RRID:IMSR_JAX:000664) were group-housed with free access to food and water. Mice were randomly assigned to control and hypoxia treatment groups. The hypoxia treatment was performed in a hypoxia chamber  with an 8% O2 supply, 16 h/day for 2 weeks . Mice were euthanized using isoflurane with care to reduce the suffering. Brains were extracted, snap-frozen and kept in – 80°C for the following experiments. The animal experiments were approved by the University of British Columbia Animal Care and Use Committee (ID: A15-0229) and Animal Experimental Ethical Inspection of Laboratory Animal Center, Wenzhou Medical University (ID: xmsq 2021-0003).C57BL/6J mice , β-Actin (8H10D10) . Secondary antibodies: goat anti-mouse IgG , goat anti-rabbit IgG .Brain samples were homogenized and lysed in RIPA lysis buffer supplemented with a protease inhibitor cocktail (Roche from Sigma-Aldrich Cat# 11873580001). Protein concentration was measured by protein assay. The lysates were resolved on 8% Tris-glycine SDS-PAGE and transferred onto nitrocellulose membranes. Membranes were blocked in 5% non-fat milk in PBS for 1 h at room temperature, followed by blotting with primary antibodies overnight (16 h) at 4°C. The following day, membranes were washed with washing buffer Tris-buffered saline with 0.1% Tween-20 (TBST), then blotted with secondary antibodies for 1 h at room temperature. After washing with TBST, images were developed using ECL. Primary antibodies: anti-Caspr2 (D6S10)  filled with opaque water as previously described . The plaOpen filed test was conducted to detect the locomotor activity and anxious behavior change. Mice were put in an open field (50 cm × 50 cm) for 10 min free exploration. The open field is divided into 25 squares of equal area; each 10 cm × 10 cm is a grid. The four squares near the corner are set as corners, the 9 squares in the middle are set as the center area, and the remaining 12 squares are set as the edge area. Any-maze (Stoelting) was used to record the routes, speed, distance, and the time in center zone.n) are shown in the figure legends. GraphPad Prism 8 was used for statistical analyses and quantification graphs. One-way or two-way analyses of variance (ANOVA) were used to analyze multiple comparisons, followed by post-hoc multiple comparisons tests specified in the figure legends. Sidak’s multiple comparisons test was applied for the analyses of three-chamber approach test, Morris Water Maze test and promoter activity. In three-chamber approach test, the treatment and subject are the independent variable; the interaction time is the dependent variable. In Morris Water Maze test, the treatment and time (Day 2–5) are the independent variable; the latency or distance is the dependent variable. In the promoter activity analysis, two independent variables are the treatment and different fragments, while dependent variable is promoter activity. A p-value less than 0.05 was considered statistically significant.All the data are expressed as mean ± standard error of the mean (SEM). Replicate numbers  for 14 days, followed by behavior tests at 6 weeks old. First, three-chamber social approach test was performed to examine sociability and novelty preference. In stage I sociability test, both control and hypoxia-treated mice spent more time interacting with stranger 1 than with the empty cage, indicating normal sociability. Two-week hypoxia treatment did not affect the time spent with empty cage, p = 0.1530 . These results suggest that the 2-week hypoxia treatment increases the sociability in adolescent mice without locomotor activity change and anxious influence.To investigate whether hypoxia affects social behavior and memory in adolescent mice, 1-month wildtype C57BL/6J mice were treated with intermittent hypoxia , p = 0.0153, indicating an elevation in sociability, but not in male , p = 0.2311 , p = 0.3351; female , p = 0.2542 , hepatocyte nuclear factor 1 homeobox A (HNF-1A), forkhead box protein P3 (FOXP3), signal transducer and activator of transcription 4 (STAT4), transcription factor 4 (TCF4), HIF-1α, and specificity protein 1 (SP1)  assay to identify the transcription start site (TSS) of the human  bp band . The seq bp band . Putativine tool  with a d 1 (SP1) .CNTNAP2 gene promoter, we cloned a 2,868 bp 5′-flanking region of the human CNTNAP2 gene from HEK genomic DNA. Deletion fragments of the 2,868 bp 5′-flanking region were cloned into the pGL3-Basic vector  and pGL3-Promoter (P) were transfected simultaneously as negative and positive controls.To analyze the function of the human c vector . The pGLigestion . To examp = 0.0025). The longest construct 2,868 bp pCNTNAP2-A  also showed significant luciferase activity  slightly elevated the promoter activity . A further deletion from −2046 bp to −1460 bp (pCNTNAP2-C) showed little effect on promoter activity . Deletions from both ends to generate pCNTNAP2-D (−868to +47 bp) gave rise to the highest promoter activity of 43.25 ± 3.65 RLU (p < 0.001), supporting that the TSS is located within the +47 bp 3′ boundary. To narrow the region that contains essential transcription machinery, three pairs of 5′ deletions with + 47 bp and + 437 bp 3′ ends were generated. pCNTNAP2-E (−298 to +437 bp), pCNTNAP2-G (−198 to + 437 bp), and pCNTNAP2-I (−6 to +437 bp) with +437 bp 3′ end showed dwindling but significant promoter activities , indicating that the essential transcription machinery is within the −6 bp 5′ boundary. While pCNTNAP2-F (−298 to +47 bp) displayed decent promoter activity , further deletions at the 5′ end to pCNTNAP2-H (−198 to +47 bp) substantially diminished promoter activity to 4.54 ± 0.28 RLU (p = 0.8494), indicating some essential elements between −298 and −198 bp.Compared with the empty vector pGL3-Basic (1 RLU), pGL3-Promoter showed robust promoter activity of 14.3 ± 1.49 RLU CGTG hypoxia-responsive elements (HRE) in the human promoter : HRE1  containing HRE1-5, pCNTNAP2-G (−198 to +437 bp) containing HRE4-5, and pCNTNAP2-I (−6 to +437 bp) with no HREs were transfected into HEK cells and treated with hypoxia condition (2% O2) for 24 h (p < 0.001), and 2.98 ± 0.40 (p = 0.0023) folds, respectively, while the activity of pCNTNAP2-I without HREs was not affected . Similarly, co-transfected HIF-1α elevated the activities of pCNTNAP2-A  and pCNTNAP2-G  but not pCNTNAP2-I  and 2.23 ± 0.63 folds (p = 0.0051) respectively. In contrast, activities of HRE1 , HRE2 , and HRE5  were not affected, suggesting that HRE3  and HRE4  in the human CNTNAP2 promoter are functional  . NotablyHowever, the effect of hypoxia treatment can be influenced by many variable factors, such as the oxygen level, the frequency and length of treatment, and the age when receiving treatment. In our study, social behaviors and short-term memory (working memory) was significantly enhanced, while long-term memory  was not affected. The intermittent hypoxia treatment in our study may have mixed effects on different phases of memory consolidation. As reported by The sex difference was noticed in our experiment . Both maCntnap2 knockout mice and rats consistently display characteristic ASD phenotypes   and HRE4  are functional HREs responsive to hypoxia treatment  , Transcr (FOXP2) , and Sto (FOXP2) . Notably (FOXP2) , supportreatment . This coreatment . Our finThe regulation of CNTNAP2 by hypoxia implicates some roles or consequences of CNTNAP2 in response to the oxygen homeostasis disturbance. Since the brain is especially susceptible to hypoxia , and CNTThe regulation relationship will provide novel clues toward understanding the interaction between genetic and environmental factors in ASD pathogenesis. Future studies can further investigate the transcriptional regulation network under hypoxia, particularly the regulatory relationships with target genes involved in pathogenic conditions.CNTNAP2 gene expression at the protein level. We identified the TSS and analyzed the transcriptional activation of the human CNTNAP2 gene promoter. Hypoxia upregulates CNTNAP2 expression via two functional HREs in the CNTNAP2 promoter. These results will provide novel insights into the impacts of hypoxia exposure on adolescent development and the potential interaction between CNTNAP2 and hypoxia in ASD pathogenesis.In conclusion, our results showed for the first time that intermittent hypoxia treatment at the adolescent stage enhances social behaviors and reference working memory. Our study also reveals that hypoxia upregulates human The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The animal study was reviewed and approved by University of British Columbia and Wenzhou Medical University.WS conceived and designed the experiments. QZ, LX, YB, and PC performed the experiments. QZ, LX, FC, MX, YW, and WS analyzed and contributed reagents, materials, analytical tools. QZ, LX, YW, and WS wrote the manuscript. All authors reviewed the manuscript.


Circular RNAs (circRNAs) also play crucial roles in ubiquitous life processes. Whether circRNAs are required for m6A regulation in renal cell carcinoma (RCC) remains unclear. Meta‐analysis and bioinformatics identified that IGF2BP3 was upregulated in RCC and indicated a worse prognosis. IGF2BP3 significantly promoted RCC progression in vitro and in vivo. Mechanistically, circRARS bound to KH1–KH2 domains of IGF2BP3 to enhance m6A modification recognition. A 12‐nt sequence (GUCUUCCAGCAA) was proven to be the IGF2BP3‐binding site of circRARS. Additionally, CAPN15, CD44, HMGA2, TNRC6A and ZMIZ2 were screened to be the target genes regulated by the IGF2BP3/circRARS complex in an m6A‐dependent manner. Stabiliser proteins, including HuR, Matrin3 and pAbPC1, were recruited by circRARS, thereby increasing the mRNA stability of the forementioned five target genes. Consequently, the IGF2BP3/circRARS complex facilitated the lipid accumulation of RCC cells and promoted sunitinib resistance via target genes. circRARS synergised with IGF2BP3 to facilitate m6A recognition, thereby promoting RCC progression. Thus, IGF2BP3 could be a potential biomarker for RCC diagnosis and prognosis and a therapeutic target.As the most prominent RNA modification, N6‐methyladenosine  to increase the m Whether there were other molecules involved in the regulation of m6A recognition of IGF2BP3 still needs to be explored.N6‐methyladenosine (mCircular RNAs (circRNAs) are class of closed loop transcripts formed by precursor mRNAs.circRNAs interact with proteins via specific binding sites or tertiary structures.6A proteins and regulate their function directly. For example, circSTAG1 can bind to an m6A eraser, ALKBH5, and inhibit its nuclear translocation, thereby upregulating the m6A of FAAH mRNA.6A sites in bladder cancer.6A recognition of IGF2BP3 in RCC as well?Accumulating evidence shows that circRNAs could bind to m6A modification recognition. A 12‐nt sequence (GUCUUCCAGCAA) was shown to be the IGF2BP3‐binding site of circRARS. And IGF2BP3/circRARS mediated the mRNA stability of CAPN15, CD44, HMGA2, TNRC6A and ZMIZ2 via an m6A‐dependent manner. Our results clarified the oncogenic function of IGF2BP3/circRARS complex in RCC progression and suggested a novel therapeutic target for RCC patients.In this study, we validated the potential of IGF2BP3 as a biomarker for RCC diagnosis and prognosis through large‐scale meta‐analysis and bioinformatics. The mechanical excavation revealed that hsa_circ_0001550 (circRARS), a circRNA derived from exon2‐4 of arginyl‐tRNA synthetase 1 (RARS1), bound to KH1–KH2 domains of IGF2BP3 to enhance m22.1Q‐test and Higgins I2 metrics. The cutoff value of obvious heterogeneity was set as I2 > 50%.Articles about IGF2BP3 and RCC prognosis published before November 2020 were searched in database including PubMed, Web of Science, Embase and Cochrane Library. We used the following search strategy to filter studies on IGF2BP3 expression and RCC prognosis: (‘IGF2BP3’ or ‘insulin‐like growth factor 2 mRNA‐binding protein 3’ or ‘IMP3’), together with (‘outcome’ or ‘prognos*’ or ‘surviv*’) and . Content filtering, data extraction and quality evaluation were performed independently by two authors (Y.L. and K.L.). Seven studies were finally included in this meta‐analysis Table .11, 32.2Fifty pairs of RCC specimens and para‐cancer renal tissues from surgical resection were obtained from the authors’ institute. All the samples were frozen in −80°C immediately after surgery removal. Pathological diagnosis was confirmed. Informed consents were obtained from all patients preoperatively. This study was approved by the Ethic Committee of Human Research of HUST.2.32.Human RCC cell lines  and immortalised renal tubular epithelial cell HK‐2 were obtained from the American Type Culture Collection in the USA and cultured in Dulbecco's Modified Eagle's Medium high‐glucose  supplemented with 10% foetal bovine serum  and 1% streptomycin–penicillin (Google Biotechnology) at 37°C with 5% CO2.4The sequences of siRNA are listed in Table 2.5The sequences of sgRNA of IGF2BP3 are listed in Table 2.6Cell counting kit 8  was applied to examine cell proliferation ability and sensitivity to sunitinib as previously described.2.7Cell cycle analysis of RCC cells was performed using a FACS scan flow cytometer after incubation with reagents from a PI/RNase Staining Kit (Beyotime). Data were analysed using ModFit LT 2.0.2.8RCC cells fixed with 4% formalin were washed with phosphate‐buffered saline (PBS), and were stained with oil red for 30 min at room temperature. The excess oil red was removed with PBS before observation. A triglyceride assay kit (Jiancheng) was used to assess the triglyceride level of RCC cells as previously described.2.9Total RNA of RCC tissues and cells were isolated with Ultrapure RNA Kit (CWBIO) and reverse‐transcribed using a Superscript II reverse transcription kit (Vazyme). After that, SYBR‐Green reagent (Vazyme) was applied for quantitative reverse transcription polymerase chain reaction . Primers were purchased from TSINGKE (TSINGKE) as Table 2.10Nuclear and cytoplasmic RNA of RCC cells was isolated with a PARIS Kit (Invitrogen). GAPDH was employed as a cytoplasmic control, while U6 served as a nuclear control.2.11Cy3‐labelled circRARS probe was purchased from Sangon  and analysed by qRT‐PCR. U6 was used for normalisation.2.13Biotin‐labelled circRARS probe was purchased from Sangon  was added into supernatants and upside down at 4°C overnight. Meanwhile, antibody against IgG  was used as negative control. Then protein A/G magnetic beads (MCE) were added into supernatants and upside down at 4°C for 2 h. The immune‐complexes were separated using SDS‐PAGE.RCC cells were lysed in IP lysis buffer (Beyotime) containing protease inhibitor (Takara). Following centrifugation at 12 000× 2.168 RCC cells were cross‐linked with ultraviolet light (250 J/cm2) for 10 min in PBS and collected by scraping. The RNA‐binding protein immunoprecipitation (RIP) kit (Millipore) was utilised. Cross‐linked cells were lysed and antibodies against IGF2BP3, m6A or IgG were pre‐incubated with magnetic beads for 30 min. Then, magnetic beads and cell lysis were incubated together at 4°C overnight. RNA‐Seq or qRT‐PCR were performed for co‐precipitated RNAs detection . Illumina HiSeq X Ten platform was used to prepare library and to do the transcriptome sequencing. The sequencing and analysis were carried out by SeqHealth Technology Co., Ltd. The cutoff value was |fold change| > 2 and 2.186 ACHN cells was injected into left renal capsule (n = 5 mice/group). Then, we sutured the wound layer by layer. Tumour size was measured 4 weeks later with in‐Vivo FX PRO small animal imaging system (BRUKER). After that, we executed the mice and collected tumours for immunohistochemistry (IHC) assays and Western blotting. For metastasis model construction, 1 × 106 ACHN cells were injected into tail‐vein of each mouse (n = 5 mice/group). Ten weeks later, we executed the mice and collected lungs and livers for hematoxylin and eosin (H&E) staining.The Animal Ethics Committee of HUST proved all in vivo experiments in this study. ACHN cells stably transfected with IGF2BP3 vector or si‐circRARS were used for injection. Four‐week‐old male BALB/c nude mice were purchased from HFK Biotechnology. For orthotopic renal tumour injection assays, mice were anesthetised. Left kidney was exposed from the left subcostal side. A total of 1 × 102.19https://xenabrowser.net/heatmap/, KIRC dataset), GEO database  and Oncomine database . The interaction between IGF2BP3 with circRARS was predicted by catRAPID  with the sequence of IGF2BP3 protein and circRARS nucleotide. Target genes related signalling pathways were analysed using the gene set enrichment analysis . Based on p‐value (<.05) and False Discovery Rate , we identified gene sets which were associated with target genes in TCGA‐KIRC dataset. Differentially expression genes were analysed with R ‘limma’ (version 3.42.2) package. Gene ontology analysis and plotting were performed using R ‘clusterProfiler’ (version 3.14.3) package. Potential m6A‐modified regions of target genes were predicted based on the IGF2BP3‐targeted RIP‐sequencing (RIP‐Seq) datasets and METTL3‐knockdown m6A‐targeted RIP‐Seq datasets  on IGV software.The expression of genes including IGF2BP3, CAPN15, CD44 and other related genes, as well as clinical data were downloaded from The Cancer Genome Atlas database  curve, etc., were utilised in this study as indicated. All data are shown as mean ± standard error of the mean (S.E.M.). Analyses were performed by GraphPad Prism 7.0 and SPSS 22.0. p < .05 was considered to be statistically significant .Student's 2.21The datasets supporting the conclusions of this manuscript are included within the manuscript and supporting information. Other data and materials about this study could be requested from the corresponding author.33.1We conducted meta‐analyses including seven studies and confirmed that IGF2BP3 was a risk factor for prognosis of RCC patients Figure . Next, wTo further explore the biological properties of IGF2BP3 in RCC progression, we designed a CRISPR‐sgRNA or a plasmid vehicle to specifically regulate IGF2BP3 expression in RCC cell lines Figure . CCK8 anIn vivo, stable knockdown of IGF2BP3 attenuated renal orthotopic xenograft growth of RCC Figures  and S3G.3.26A modification in RCC cell lines, as ‘GGAC’ motifs were mostly enriched in RIP samples, which is consistent with previous study  is a circRNA formed by reverse splicing of exons 2−4 of the RARS1 gene Figure . It coulThe epithelial–mesenchymal transition (EMT) is an essential pathway in many malignancies. We determined the EMT levels under different expressions of IGF2BP3 and circRARS. We found that IGF2BP3 and circRARS synergistically promote the EMT progress of RCC cells Figure .6A modification sites. And circRARS could bind to IGF2BP3, forming a complex to synergise the oncogenic properties in RCC cells.In conclusion, we validated the potential of IGF2BP3 to bind m3.3To explore the specific binding sites of IGF2BP3 and circRARS, catRAPID tools were applied to predict the probability and position of the interaction Figure . Next, f3.4To distinguish the downstream targets of IGF2BP3/circRARS complex, RNA‐Seq of circRARS knockdown RCC cells was performed Figure . Several3.56A‐dependent manner. In this study, we utilised IGF2BP3‐targeted RIP‐Seq datasets and METTL3‐knockdown m6A‐targeted RIP‐Seq datasets on IGV software to identify potential m6A modification sites on the forementioned five genes.6A modification site on each of the mRNA of CAPN15, CD44, HMGA2, TNRC6A and ZMIZ2 , promoting tumour progression.6A‐related proteins and influenced m6A modification as well. MiR‐33a, lncRNA GAS5 and circNDUFB2 were proved to regulate the expression of METTL3, ALKBH5 and IGF2BPs.6A sequences to regulate m6A modifications.6A modification sites.6A binding, we filtered multiple IGF2BP3‐binding circRNAs via RIP‐Seq. RNA pull‐down assays confirmed that circRARS bound to IGF2BP3 to form a complex. Thus, we hypothesised that circRARS regulated IGF2BP3 to recognise m6A sites. We then figured several downstream genes via RNA‐Seq of circRARS knockdown. In particular, the mRNA stabilities of CAPN15, CD44, HMGA2, TNRC6A and ZMIZ2 were regulated by IGF2BP3/circRARS complex via m6A‐dependent manners. However, the specific mechanisms in circRARS selective regulation required further explorations.Non‐coding RNAs included miRNAs, lncRNAs and circRNAs. Notably, due to their stability, non‐coding RNAs were likely to act as biomarkers for diagnosis and prognosis for cancer.6A reader protein, IGF2BPs mainly bound to m6A modification sites by their KH3–KH4 domains. And the KH1–KH2 domains acted as an accessory in the binding process. In this study, we confirmed that circRARS was mainly bound to KH1–KH2 domains of IGF2BP3 and presumed that circRARS could facilitate IGF2BP3 recognition of m6A sites. After combination with m6A modification sites, IGF2BP3 could recruit stabilisers including HuR, Matrin3 and pAbPC1, and formed a ‘safe house’ for mRNAs. HuR/IGF2BP3 interacted to form the P bodies and stabilised mRNA.As an mAs previously mentioned, we found that the expression of CAPN15, CD44, HMGA2, TNRC6A and ZMIZ2 were regulated by IGF2BP3/circRARS complex. The canonical downstream targets of IGF2BP3 included Myc, CD44, HMGA2, etc. It has been reported that IGF2BP3 could bind to the CRD sequence of Myc.6A‐related proteins and non‐coding RNAs are regarded as potential diagnostic and prognostic ‘sentinels’ for cancers and therapeutic targets.6A‐dependent manner. Targeting IGF2BP3/circRARS complex might provide us new strategies and directions for RCC patients management.Currently, mYuenan Liu, Kailei Chen and Yi Shou performed most of the experiments and wrote this manuscript and contributed equally to this work. Qingyang Zhang contributed extraordinary in the revision process and language polishing. Sen Li, Jun Wang and Ziwei Huang finished some of animal experiments and analysed the data. Jiaju Xu and Mingfeng Li conducted some of cell experiments and analysed the data. Di Liu and Huageng Liang collected RCC tissues and accomplished bioinformatic analysis. Hongmei Yang and Xiaoping Zhang designed the whole project and supervised all experiments. All authors revised and approved the manuscript.The authors declare they have no conflicts of interest.This study was approved by the Ethic Committee of Human Research of HUST and the Animal Ethics Committee of HUST.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.Supporting InformationClick here for additional data file.


Transcription Factor A Mitochondrial (TFAM) was first purified 35 years ago as an activator of mitochondrial transcription. Because of its critical contributions to mitochondrial DNA transcription and replication, this protein was viewed as a master regulator of mitochondrial biogenesis. However, now it is clear that TFAM’s cellular role is more nuanced than previously thought. In this review, we attempted to compile and assess various, at times contradictory, lines of evidence supporting this protein’s diverse roles. It is carried out in the belief that the resolution of the existing contradictions is a prerequisite for further advancements in the field.Transcription Factor A Mitochondrial (TFAM), through its contributions to mtDNA maintenance and expression, is essential for cellular bioenergetics and, therefore, for the very survival of cells. Thirty-five years of research on TFAM structure and function generated a considerable body of experimental evidence, some of which remains to be fully reconciled. Recent advancements allowed an unprecedented glimpse into the structure of TFAM complexed with promoter DNA and TFAM within the open promoter complexes. These novel insights, however, raise new questions about the function of this remarkable protein. In our review, we compile the available literature on TFAM structure and function and provide some critical analysis of the available data. Life, as we know it, has numerous manifestations, but no uniformly accepted definition. However, living systems must sustain and reproduce themselves. These processes are dependent on chemical energy, which living systems absorb from the environment, typically in the form of nutrients, and energy capture, most often in the form of ATP, which is casually referred to as the “universal energy currency” of life . Therefo2. These reducing equivalents are then “burnt” by the respiratory chain; the released energy is stored in the form of an electrochemical gradient across the mitochondrial inner membrane and captured in the high-energy bonds of ATP 42], the In vivo  experiments are the gold standard in biological research. Yet, these experiments are time-, labor-, and resource-expensive and are, therefore, inherently low-throughput. In addition, these experiments are not as tractable as those in vitro or in situ (in cultured cells). For example, mice with Ckmm promoter-driven TFAM KO specific to the heart and skeletal muscle survived for 2–4 weeks in , for 12 Inactivation of the genes that play key roles in mtDNA transcription and replication, such as TFAM, is embryonically lethal. This necessitates conducting animal studies using tissue-specific KOs. This mode of experimentation has two important limitations: First, each organ is composed of parenchymal cells that perform tissue-specific functions  and stromal (supporting) cells . Inactivation of the gene of interest in the parenchymal cells using tissue-specific-promoter-driven expression of a recombinase typically does not result in this gene’s inactivation in stromal cells. Yet, most biochemical assays are performed in whole-organ lysates composed of the contents of both parenchymal and stromal cells. Depending on the tissue, the parenchymal/stromal cell ratio can vary. For example, in the heart, cardiac myocytes constitute 25% by number and 75% by volume ,145. ThiIn situ systems are intermediate between in vitro and in vivo systems in terms of throughput, tractability, cost, and limitations. Recently, a GeneSwap approach that enables in situ reverse genetic analysis of proteins involved in mtDNA replication and transcription has been reported . This meIn general, the future progress of TFAM research strongly depends on improvement of the existing experimental approaches and the development of new ones.In total, 181 variants in the TFAM gene are listed in the UniProt database, of which 4 are predicted to result in premature termination of the polypeptide chain. However, only two pathogenic TFAM variants have been described in human patients. A c.533C > T (p.Pro178Leu) mutation was reported in a consanguineous kindred of Colombian–Basque descent. Two siblings presented with severe intrauterine growth restriction, elevated transaminases, conjugated hyperbilirubinemia, and hypoglycemia. Both patients died of progressive liver failure in early infancy . TFAM prAnother study described three affected individuals from a consanguineous family affected by variable seizures and intellectual disability, which segregated with c.694C > T, p.Arg232Cys mutation in TFAM . AdditioGiven the critical role played by TFAM in cellular physiology through its contributions to mtDNA maintenance and expression, it is somewhat surprising that only a few pathogenic mutations have been described in this protein. However, this observation is in good agreement with a recent study that examined the functionality of oTFAMs in human cells and identified 730 substitutions conditionally permissive for mtDNA replication .What are TFAM’s contributions to mitochondrial transcription beyond the LSP and HSP1? Current models of mitochondrial transcription limit their scope to these two promoters.What are the structures of mitochondrial transcription complexes in situ? In vitro studies have suggested that POLRMT and TFB2M and/or partial DNA melting can reverse the orientation of TFAM binding at HSP1. Could other proteins further modify the structure of transcription complexes in situ ?How should the TFAM residues that make DNA contact be defined, and what are the identities of those residues? The evidence from TFAM:LSP crystals suggests that some residues  may either intercalate into DNA  or make What are the determinants of TFAM sequence-specific DNA binding?If sequence-specific TFAM binding upstream of the mitochondrial promoter is an initiating event in the assembly of the transcription complexes, how does the orientation of TFAM binding upstream of the HSP1 promoter invert upon the transition to open complex? Is TFAM dissociation from DNA involved in the process?To what extent does the statement that “TFAM ‘coats’ mtDNA” reflect the actual situation in situ?What are the mechanistic basis and biological significance of observed uneven TFAM distribution between nucleoids within the same cell?What is the mechanism of the resistance of free (not DNA-bound) TFAM to degradation by proteases in POLRMT KO cells ?What mechanisms govern mtDNA persistence and transcription in tissues of tissue-specific TFAM KO animals?Thirty-five years of TFAM research has dramatically improved our understanding of this protein’s structure and function. However, much remains to be learned. Resolving outstanding questions would facilitate progress in the field. Some of these questions are:We believe that further progress will be driven, in large part, by the development of new experimental approaches and the improvement of existing ones.


The indole-3-pyruvic acid (IPA) pathway is the main auxin biosynthesis pathway in the plant kingdom. Local control of auxin biosynthesis through this pathway regulates plant growth and development and the responses to biotic and abiotic stresses. During the past decades, genetic, physiological, biochemical, and molecular studies have greatly advanced our understanding of tryptophan-dependent auxin biosynthesis. The IPA pathway includes two steps: Trp is converted to IPA by TRYPTOPHAN AMINOTRANSFERASE OF ARABIDOPSIS/TRYPTOPHAN AMINOTRANSFERASE RELATED PROTEINs (TAA1/TARs), and then IPA is converted to IAA by the flavin monooxygenases (YUCCAs). The IPA pathway is regulated at multiple levels, including transcriptional and post-transcriptional regulation, protein modification, and feedback regulation, resulting in changes in gene transcription, enzyme activity and protein localization. Ongoing research indicates that tissue-specific DNA methylation and miRNA-directed regulation of transcription factors may also play key roles in the precise regulation of IPA-dependent auxin biosynthesis in plants. This review will mainly summarize the regulatory mechanisms of the IPA pathway and address the many unresolved questions regarding this auxin biosynthesis pathway in plants. Auxin plays a vital role in regulating plant growth, development, and response to environmental stress ,2,3,4. MIn plants, IAA is mainly synthesized through two pathways, the Trp-dependent and Trp-independent pathways . The TrpAtTAA1 exhibited no altered phenotypes, indicating that TAA1 encodes a key but not rate-limited enzyme ..YUC geneGenetic disruption of the IPA pathway, and the resulting dysregulation of IAA levels, leads to plant developmental defects under both normal and stress environments . To mainDue to the important role of IAA in plant growth and development, genes involved in IAA biosynthesis, metabolism, transport and signaling are often subject to tight genetic regulation. Auxin biosynthetic genes either show redundancy or their single mutants result in lethality or sterility, such that classical genetic approaches may not be able to comprehensively screen for key auxin-related genes. The use of small chemical inhibitors can complement classical genetics. These small molecules often competitively occupy the ligand binding pocket of the target enzymes and can be applied in discreet doses to give a wide range of effects ,28,29. TThe compound L-kynurenine (Kyn) was found in a screen for ethylene (ET) signaling inhibitors. Exogenous application of Kyn results in root elongation that is insensitive to ET. Subsequent studies have shown that TAA1/TAR1 catalyzes the conversion of Kyn to kynurenic acid (KYNA), and that this metabolite has no inhibitory effect on root growth. Computational Docking and Molecular Modeling results further suggested that Kyn acts as a competitive inhibitor of Trp in TAA1/TAR proteins, thereby reducing conversion of IPA and decreasing the levels of free IAA . SeveralA second class of IPA pathway inhibitors target the YUC proteins. Yucasin, or 5-(4-chlorophenyl)-4H-1,2,4-triazole-3-thiol, was identified from a screen for compounds affecting IAA contents in the coleoptile tip . YucasinEpigenetic modifications, including DNA methylation and histone modification in nucleosomes, are critical layers of transcriptional regulation, directing mRNA synthesis and determining gene expression or silencing . SeveralYUC2 promoter in a temperature-dependent way, which then blocks the binding of the transcription factor NUCLEAR FACTOR-YA2 (NF-YA2) to the YUC2 promoter ..YUC2 by YUC2/8 via ABI4, thereby inhibiting primary root elongation. Mechanical wounding can upregulate ERF115, thereby promoting the transcription of YUC3/5/7/8/9 and promoting post-injury root regeneration. ATH2 inhibits the transcription of YUC2 to alter root gravitropism. AGL21 positively regulates YUC5/8/TAR3, and this TF is induced by a variety of hormones including IAA/ABA/JA and a variety of stresses, including salt and drought stress and sulfate (-S) and nitrogen deficiency (-N)   87]. In. InYUC2/YUC2, which in turn decreases auxin content and leaf size ..TAA1 in YUC4 and activates their transcription, promotes somatic embryogenesis . In. InYUC4  species .YUC4 results in the presence of two YUC4 isoforms, both of which have enzymatic activities in Arabidopsis. Of these splicing variants, YUCCA4.1 is present in all tissues and distributed throughout the cytoplasm, whereas YUCCA4.2 is present only in flowers and is localized to the cytoplasmic side of the endoplasmic reticulum membrane, which may confer properties related to subcellular compartmentation of IAA biosynthesis [TAR2, YUC2 and YUC4; however, how alternative splicing influences the expression of these genes needs further investigation.Post-transcriptional regulation of genes can affect the splicing, processing, storage and stability of mRNA, which in turn affects mRNA translation efficiency or the final product, such as creating truncated proteins . Alternaynthesis . There iynthesis ,100. In Another form of RNA processing is polyadenylation, and its distribution in the 5′-untranslated region (UTR) and 3′-UTR is responsible for the stability of mature transcripts and influences their export to the cytoplasm, their subcellular localization, and recognition by the translational machinery ,101. A pckrc3-1, that was prematurely terminated due to a G to A transition at position 731 of the auxiliary subunit (Naa25) of the Arabidopsis N-TERMINAL ACETYLTRANSFERASE NatB [Post-translational modifications, such as phosphorylation, acetylation, ubiquitination and glycosylation, can affect protein localization, stability, activity and interactions with other proteins, adding additional complexity and greater flexibility to regulation of metabolic functions . HoweverASE NatB . CKRC3 iASE NatB .With the development of proteomics, many more types of protein modifications are being identified and studied. Many phosphorylation, acetylation and glycosylation modification sites have been identified on TAA1/TAR and YUC proteins. Whether these modifications are involved in the regulation of IPA-dependent IAA biosynthesis and how they are altered with plant development and stress deserve further investigation ,106.TAR2, YUC1, YUC2, YUC4, and YUC6 in Arabidopsis seedlings, while use of the auxin biosynthetic inhibitor Kyn upregulated the transcription of these genes , which uses methionine as an amino donor and IPA as an amino acceptor to produce L-Trp and 2-oxo-4-methylthiobutyric acid. IPA can also be glucosylated into IPA-Glc by UGT76F1  109,110110.Auxin is an essential hormone that governs plant development and responses to bio- or abiotic stress ,111. Studrm1drm2cmt3 triple mutant, which has low levels of DNA methylation, YUC2 and TAA1 were specifically induced in the leaves, but almost none was detected in the roots [Tissue-specific DNA methylation may regulate local IAA biosynthesis. Local auxin biosynthesis plays a critical role in the formation of the auxin gradient, which functions in regulating plant development and stress response . Multiplhe roots , implyinYUC gene expression in specific tissues, leading to spatiotemporal auxin signaling [Silencing of transcription factors by miRNA may also influence local auxin biosynthesis. As short, single-stranded nucleic acids, miRNA directly cleave target genes and repress the expression, which provides an additional layer of regulation to gene expression . Publishignaling ,97,114. Many studies have shown that auxins play a key regulatory role in enhancing plant stress resistance and improving crop yields ,116,117.


Drosophila embryos. These factors are sequentially and transiently recruited to discrete clusters during activation of non-histone genes. Zelda and the acetyltransferase dCBP nucleate dBrd4 clusters, which then trigger pre-transcriptional clustering of RNAPII. Subsequent transcriptional elongation disperses clusters of dBrd4 and RNAPII. Our results suggest that activation of transcription by eukaryotic TFs involves a succession of distinct biomolecular condensates that culminates in a self-limiting burst of transcription.Binding of transcription factors (TFs) promotes the subsequent recruitment of coactivators and preinitiation complexes to initiate eukaryotic transcription, but this time course is usually not visualized. It is commonly assumed that recruited factors eventually co-reside in a higher-order structure, allowing distantly bound TFs to activate transcription at core promoters. We use live imaging of endogenously tagged proteins, including the pioneer TF Zelda, the coactivator dBrd4, and RNA polymerase II (RNAPII), to define a cascade of events upstream of transcriptional initiation in early  Eukaryotic transcription involves the formation of subnuclear hubs that enrich transcriptional machinery. Here the authors show that the hubs undergo stepwise modifications to fuel a burst of transcription rather than having a stable composition. In particular, transcription factors (TFs) recruit nucleosome remodelers, histone modifiers, and Mediator to promote the formation of PIC. How these numerous upstream inputs are integrated to give the extraordinary specificity and intricacy of transcriptional regulation remains incompletely understood. A common view suggested by biochemical studies is that these factors are progressively assembled into a single final complex through cooperative interactions. However, other sophisticated processes initiating DNA replication and promoting splicing of mRNAs are governed by a series of distinct and ephemeral complexes in which each complex promotes the next in energy-driven steps3. Here, we are interested in the possibility that initiation of transcription similarly involves directional transformations of intermediate complexes that would provide additional opportunity for specificity and regulation.In eukaryotes, the recruitment of RNA polymerase II (RNAPII) to transcription start sites on DNA depends on the assembly of the preinitiation complex (PIC) and is regulated by hundreds of trans-acting factors4. These clusters are thought to function as “transcriptional hubs” by locally enriching transcriptional machinery and enhancing their binding to target DNA sites. Transcriptional hubs are a type of membraneless compartment, whose formation typically involves the multivalent interaction between intrinsically disordered regions (IDRs)5. Accordingly, IDRs are commonly found in the activation domains of TFs as well as the C-terminal domain (CTD) of Rpb1 in RNAPII6. Similar to the idea that a single final complex is assembled on the DNA to initiate transcription, it has been proposed that the heterotypic interactions between IDRs can give rise to a compartment that simultaneously enriches TFs, coactivators, Mediator, and RNAPII at promoters7. Nonetheless, how transcriptional hubs are regulated and whether they undergo compositional changes are still unclear.Visualizing the composition of transcriptional machinery over time might detect intermediate complexes that integrate the multitude of regulatory inputs of transcriptional control. In recent years, advances in confocal and super-resolution imaging led to the discovery that a wide variety of transcriptional regulators are recruited to form clusters at active genes8. The Drosophila embryo provides a powerful context to study the timing of events upstream of transcriptional initiation. The early wave of transcription in Drosophila embryos is coupled to the rapid nuclear division cycles such that a few hundred genes initiate a burst of transcription about 3 min after each mitosis11. The synchrony of early nuclear cycles and real-time localization of tagged proteins allow one to track activation events prior to the onset of transcription, and tools to knockdown function are available to assess the contribution of events to gene activation. In a recent study, live imaging of endogenously tagged RNAPII revealed the abrupt appearance of RNAPII clusters 2–3 min after mitosis12. Brief metabolic labelling revealed foci of nascent transcripts throughout the nuclei in fixed embryos—these foci broadly colocalized with RNAPII clusters, indicating that early-forming RNAPII clusters mark sites of active transcription. Importantly, as nascent transcript levels increased, RNAPII clusters declined and eventually dispersed. These observations are consistent with numerous observations15 and support a model in which a large excess of RNAPII is recruited prior to initiation, which is then inefficiently converted to elongating RNAPII. What produces this pre-transcriptional RNAPII clustering and how it is coordinated with a burst of transcription are not yet fully understood. Here, we follow events during the ~2.5 min between mitotic exit and the formation of RNAPII clusters and the fate of these clusters as transcription ensues at about 3 min after mitosis.Studying the dynamics of transcriptional hubs in living cells is complicated by the discontinuous and stochastic nature of eukaryotic transcription, a phenomenon also known as bursting18. Maternally supplied Zld binds to thousands of enhancers and promoters, and its binding sites exhibit increased chromatin accessibility and histone acetylation24. Depletion of maternally expressed Zld curtails early zygotic transcription, and the embryos become highly defective at the mid-blastula transition (MBT)16. The transactivation domain of Zld has been mapped to an intrinsically disordered region25. Moreover, fluorescently tagged Zld forms highly dynamic clusters in the nucleus27, and previous studies suggest that Zld clusters increase the local concentration of other TFs and facilitate their binding to target DNA29. Knockdown of Zld reduces RNAPII “speckles” in fixed embryos30. While these previous studies support a model in which Zld promotes the recruitment of additional components to form transcriptional hubs and facilitates the onset of zygotic transcription, the exact mechanism has not been determined.Zelda (Zld) is a pioneer TF that widely promotes the early wave of zygotic gene expressionDrosophila embryos. We show that Zld acts through transcription coactivators, including the lysine acetyltransferase dCBP and the BET protein dBrd4, to initiate RNAPII clustering at non-histone genes. Importantly, real-time imaging reveals only limited colocalization of these factors at transcriptional hubs, suggesting dynamic and directional changes in the composition such that upstream activators do not stably persist in the hubs with downstream effectors and RNAPII. We propose a model in which Zld forms numerous largely unstable clusters, some of which trigger a dCBP-dependent step to build more stable dBrd4 clusters; a subset of these dBrd4 clusters then promotes RNAPII clustering near active promoters, and this pool of RNAPII fuels a burst of transcription. Inhibition of transcriptional elongation stabilizes some Zld and dBrd4 clusters, indicating that transcription directly or indirectly promotes their dispersal. Finally, while early inhibition of transcription inhibits RNAPII clustering, abrupt inhibition of transcript elongation after hub formation stabilizes RNAPII clusters. These findings indicate that transcription destabilizes hubs, a feedback that could lead to cycles of RNAPII accumulation and depletion, thereby contributing to the busting feature of transcription. We suggest that the onset of transcription, like the onset of replication, involves upstream events that directionally modify the machinery to precisely control the process.In this study, we combine genetic perturbation and real-time imaging to delineate a pathway that nucleates and serially transforms transcriptional hubs to trigger initiation of transcription in early Drosophila embryos12. As a previous study showed that the depletion of Zld reduced RNAPII speckles in immunostaining30, we wanted to further characterize this process using real-time approaches. To block the actions of Zld in the nucleus, we sequestered endogenously GFP-tagged Zld in the cytoplasm by the JabbaTrap, which is an anti-GFP nanobody fused with the lipid-droplet protein Jabba, and then recorded RNAPII dynamics using mCherry-tagged Rpb132. During a normal cell cycle in control embryos, RNAPII abruptly formed two classes of clusters about 2–3 min after mitosis, including the large clusters at the two histone locus bodies (HLBs) and more numerous small clusters  is known to be deposited by the lysine acetyltransferase CBP/p300 and is a major determinant of enhancer activity33. Upon testing candidates, we found that the Drosophila homolog of CBP, encoded by Nejire (Nej), is necessary for RNAPII clustering. Because dCBP/Nej is required for the production of eggs35, we used RNAi to deplete maternal dCBP in early embryos by expressing shRNA targeting dCBP only from the late stages of oogenesis  in cycle 12 was blocked by the knockdown of dCBP, phenocopying the knockdown of Zld  homeotic, encoding 2 isoforms of a BET homolog, dBdr4 herein. Like its mammalian orthologs, dBrd4 functions in transcriptional regulation, as shown in cell lines and gastrulating embryos45. However, the role of maternally supplied dBrd4 in the minor wave of zygotic transcription in early embryos has not been examined, partly due to the female sterility of genetic mutants46.We hypothesized that acetylation marks deposited by dCBP subsequently initiate RNAPII clustering via recruitment of chromatin readers, such as those recognizing acetylated lysine residues. In line with this hypothesis, the mammalian bromodomain and extraterminal (BET) protein Brd4 binds acetylated histones and is critical for the formation of transcriptional condensates at super-enhancers49. In addition to the general chromatin interaction with mitotic chromosomes, we observed discrete clusters of dBrd4 during most of the cell cycle except a short period at the beginning of interphase , we observed a moderate positive correlation between dBrd4 and RNAPII intensity Fig. , consistOnce the co-clusters formed and matured, the subsequent behaviors varied but all culminated in the loss or separation of dBrd4 from the RNAPII clusters. In the example in Fig. The separation of dBrd4 from matured RNAPII clusters could be in part due to movement during imaging of the two channels (less than 1 s). To avoid mobility, we injected 2% formaldehyde into embryos at about 3 min post mitosis and incubated them for another 8 min. The injection of formaldehyde rapidly arrested the progression of nuclear division cycles, while the sfGFP-dBrd4 and mCherry-Rpb1 clusters were immobilized and retained their fluorescence  also involves histone acetylation and subsequent recruitment of Brd463. Notably, elegant work has shown that dozens of factors are recruited to the ERα target promoter in a cyclical and sequential fashion64. We envision that many of these factors are dynamically recruited to the hubs, and that the enzymatic reactions they carry out contribute to the speed and irreversibility of the transformation of transcriptional hubs. Lastly, we suggest that the formation of transcriptional hubs in early embryos ensures the rapid initiation of a transcriptional burst within a short interphase window; in other biological contexts, the hubs might serve additional functions such as bridging enhancers and promoters or coordinating expression of multiple loci67. The Drosophila embryos will provide a powerful system to dissect the relationship between transcriptional hubs, chromatin interactions, and transcription dynamics.Regardless of the molecular details, we expect that similar regulatory principles are employed by evolutionarily diverse transcription factors to mediate transcriptional activation. For example, in the zebrafish embryo, the pioneer factors Nanog, Pou5f3, and Sox19b similarly recruit CBP/p300 and Brd4 to establish transcriptional competence during early zygotic gene expressionDrosophila melanogaster were maintained on standard cornmeal-yeast medium at 25 °C. Flies were transferred to egg-laying cages 2–3 days before experiments, and embryos were collected on grape juice agar plates with yeast paste. Fly lines used in this study are listed in Supplementary Table Embryos were collected in egg-laying cages, dechorionated with 40% bleach, washed three times with water, and then transferred onto grape juice agar plates. Embryos were aligned and transferred to coverslips with glue derived from double-sided tape using heptane. The embryos were then covered with halocarbon oil  for microscopy. The preparation of embryos and microscopy were performed at room temperature ( ~ 22 °C).31 and injected at 750 ng/μl. α-amanitin  was dissolved in water and injected at 0.5–1 mg/ml. JQ1  supplied as 10 mM solution in DMSO was diluted fresh with water to 0.1 mM before injection. Formaldehyde from a 16% stock solution  was diluted fresh with water to 2% before injection.Once aligned and glued to a coverslip, embryos were slightly dehydrated in a desiccation chamber for 7–9 min before being covered in halocarbon oil and subjected to microinjection. JabbaTrap mRNA was synthesized as described in ref. For visualizing EGFP-Rpb3 following knockdown of a gene targeted by a specific shRNA:EGFP-Rpb3; UASp-shRNA  x EGFP-Rpb3, Mat-tub-Gal4; Mat-tub-Gal4 For visualizing mNeonGreen-Zld following knockdown of a gene by a specific shRNA:UASp-shRNA  x mNeonGreen-Zld; Mat-tub-Gal4 For visualizing sfGFP-dBrd4 following knockdown of a gene targeted by a specific shRNA:sfGFP-dBrd4;; UASp-shRNA  x sfGFP-dBrd4;; Mat-tub-Gal4 Since it is the maternal genotype that governs the development of syncytial embryos, we describe the crosses producing the parents of the experimental embryos. The following P0 crosses were set up to generate females for embryo collection in germline RNAi experiments.Mat-tub-Gal4. The progeny were crossed with their siblings and transferred to egg-laying cages for collection of the experimentally imaged embryos  or heterozygous 2) for the tagged locus to be imaged and expressed the shRNA of interest in the female germline under the influence of  for the Fs(1)h locus (5’-CGGTGGCTCACTGGACGACA-3’) were ordered from Integrated DNA Technologies (IA), annealed and cloned into the expression vector pU6-BbsI-chiRNA using standard protocols68. To make donor plasmids, about 1 kb of homology arms upstream and downstream of the start codon were amplified from the genomic DNA of the nos-Cas9 (III) flies. HaloTag and sfGFP DNA fragments with 5x Gly-Gly-Ser linker were amplified from plasmids previously made in the lab by PCR. Vector backbone was amplified from pDsRed-attP with the 3xP3-DsRed cassette removed. All DNA fragments were then gel-purified and assembled by Gibson assembly. The sgRNA-expressing and donor plasmids were sent to Rainbow Transgenic Flies for microinjection. After injection, surviving adults were crossed to yw, N/FM7c balancer flies and screened by PCR for successful knock-in. Transformants were backcrossed with wild type (Canton S: w1118) at least three times before performing experiments.DNA oligos for sequences of sgRNA targeting the 5’ end of the dBrd4-encoding dBrd4 allele. We thus used embryos from the HaloTag-dBrd4/+ females for experiments. HaloTag TMR ligand was dissolved in DMSO at 5 mM as stock solution and diluted fresh to 10–15 μM with water for microinjection. Injected embryos were incubated for at least 10 min at room temperature before imaging.We noticed that the labeling of HaloTag-dBrd4 by fluorophore-conjugated ligand frequently caused mitotic defects, which could be alleviated in embryos from females heterozygous with untagged UASp-JabbaTrap-bcd3’UTR, 834 bp of bicoid 3’UTR was amplified from the genomic DNA of wild-type flies and inserted into pUASp-attB-JabbaTrap plasmid backbone by Gibson assembly. The plasmid was then injected into attP112 (III) lines for phiC31-mediated integration by BestGene.To construct the donor plasmid for The following P0 cross was set up to obtain progeny used for the JabbaTrap dBrd4 cage.sfGFP-dBrd4, mCherry-Rpb1;; UASp-JabbaTrap-bcd-3’UTR  xsfGFP-dBrd4, mCherry-Rpb1; Mat-tub-Gal4 The following P0 cross was set up to obtain progeny used for the JabbaTrap control cage.mCherry-Rpb1;; UASp-JabbaTrap-bcd-3’UTR  xmCherry-Rpb1;; Mat-tub-Gal4 The resulting F1 progeny were grown and kept at 25 °C for experiments, as growing at 27 °C still led to complete female sterility in JabbaTrap dBrd4 embryos. F1 progeny were allowed to mate with their siblings and transferred to egg-laying cages for experiments  for 5 min at room temperature four times. Embryos were blocked in PBST with 3% donkey serum (Sigma-Aldrich) for 30 min. 1:500 rabbit α-H3K27ac  was then added and incubated at 4 °C overnight. Next, embryos were washed with PBST for 15 min three times, incubated with 1:500 anti-rabbit Alexa Fluor 488  at room temperature for 1 h, washed with PBST for 15 min three times, and mounted on a glass slide in Fluoromount . Hoechst 33258  was added at 1:2000 during the second wash after secondary antibody incubation.RpL32 was used as a reference gene, and dCBP level was quantified by the ΔΔCt method.For each biological replicate, about 100 dechorionated embryos were homogenized by a plastic pestle in TRI Reagent , and the total RNA was extracted using Direct-zol RNA microprep kit . cDNA was synthesized using Promega GoScript Oligo(dT) (#A2790) following manufacturer’s protocol. qPCR mixture was prepared using Bio-Rad SsoAdvanced Universal SYBR Green Supermix (#172-5270) and analyzed on Bio-Rad CFX Connect system. sfGFP-dBrd4 embryos between 0.5 and 1.5 h old were transferred to 50 μl of RIPA buffer supplemented with protease inhibitors . Embryos were homogenized on ice by a plastic pestle, and then 50 ul of 2X SDS-PAGE sample buffer was added. After boiling for 5 min, 10 ul samples were separated on 7.5% SDS-PAGE at room temperature and then transferred to PVDF membrane in a cold room. The membrane was blocked with TBST (0.1% tween 20) and 5% milk, blotted with 1:5000 rabbit anti-GFP  in a cold room overnight, followed by 1:20000 anti-rabbit HRP  at room temperature for 1 h. The membrane was incubated with SuperSignal West Pico PLUS Chemiluminescent Substrate  and exposed to film .About 100 dechorionated Imaging was performed on an Olympus IX70 microscope equipped with PerkinElmer Ultraview Vox confocal system. Movies following the mid-blastula transition in nc14 were acquired with a 60x/1.40 oil objective; all other movies were acquired using a 100x/1.40 oil objective. With the 100x objective, a field of 67 × 67 µm was recorded, which contains about 20–30 nuclei in cycle 12 embryos and about 40–60 nuclei in cycle 13 embryos. Data were acquired using Volocity 6 software (Quorum Technologies). Pixel binning was set to 2 × 2 for imaging of live embryos and 1 × 1 for fixed samples. Focal planes with a 0.5–0.75 μm z-step were recorded at each timepoint. In dual-color imaging, sequential acquisition was performed through channels first then z-planes. Fluorophores were excited with 488 and 561 nm laser lines. Appropriate emission filters were used in most cases. When imaging sfGFP-dBrd4 and mCherry-Rpb1 at higher frame rate (10 s), the “fast sequential” mode without applying emission filters was used, and care was taken to make sure that there was negligible bleed through under the acquisition setting. Images in the same set of experiments were acquired using the same configuration, and laser power was calibrated using a laser power meter (Thorlabs) before each imaging session.69.Data obtained in Volocity were exported as image stacks and background-subtracted with a rolling-ball radius between 50 and 75 pixels in FIJI/ImageJ. All image processing, segmentation, and quantification were performed in FIJI/ImageJ (v2.9.0) and Python 3, using standard and open-sourced libraries such as NumPy and scikit-imageWe used the variance of fluorescent intensities in the nucleus to estimate the degree of clustering. Binary masks corresponding to nuclei were generated by Otsu’s thresholding after Gaussian blurring. When comparing the same embryo over time . The resulting objects were further filtered manually by Rpb1 intensity to remove noise and the large HLB clusters. Object labels were exported from TrackMate as TIFF and used for quantification of fluorescent intensity in Python. For each identified object, the integrated intensities for mCherry-Rpb1 and sfGFP-dBrd4 were calculated after subtracting a nucleoplasmic background, which is determined as the median of nuclear intensity. Pearson’s correlation between the integrated intensities of Rpb1 and dBrd4 was performed in R.mCherry-Rpb1 clusters were detected using the LoG (Laplacian of Gaussian) detector in the TrackMate tool in FIJI71 and then filtered by a minimal size of 2 pixels. Co-clusters were identified by the spatial overlap of at least 1 pixel. The distance between centroids of co-clusters was then measured.For each pair of dual-color imaging (dBrd4-Rpb1 and Rpb3-Rpb1), a total of 6 single-z-plane images from 3 fixed embryos were used for analysis. Segmentation of clusters was performed using the Trainable Weka Segmentation tool in FIJI70. The LoG detector and an object diameter of 8 pixels (1 μm) were used. Data for each track were individually normalized to the initial intensity in the first frame. MCP foci that emerged after the first frame were excluded from analysis.MCP foci were detected, tracked, and quantified by TrackMateP < 0.05 was considered statistically significant. Additional details can be found in the corresponding figure legends.All experiments were repeated at least three times with similar outcomes, and representative images are shown in the figures. Two-tailed Mann-Whitney U tests were performed in R (v.3.2.1). A value of Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Movie 1Reporting SummarySource Data


Drosophila, the depletion of PARP1 or PARG proteins causes a developmental arrest before pupation, resulting in individuals unable to complete their development. This phenotype highlights the critical involvement of poly(ADP-ribosyl)ating enzymes in regulating the metamorphic process. In this study, we provide compelling evidence that these enzymes intricately coordinate transcriptional changes in both developmental and metabolic pathways during metamorphosis. Specifically, they promote the expression of genes crucial for pupation, while simultaneously negatively regulating the expression of metabolic genes before the transition to the pupal stage. Additionally, these enzymes suppress the expression of genes that are no longer required during this transformative period. Our findings shed light on the intricate interplay between poly(ADP-ribosyl)ating enzymes, developmental processes, and metabolic regulation before metamorphosis and highlight a new role of poly(ADP-ribosyl)ating enzymes in the global regulation of transcription.Metabolism, known to be temporally regulated to meet evolving energy demands, plays a crucial role in shaping developmental pace. Recent studies have demonstrated that two key proteins PARP1 and PARG play a regulatory role in the transcription of both morphogenic and metabolic genes. Intriguingly, in  Previous studies have demonstrated that metabolism is not a constant process throughout an organism's life but rather exhibits temporal regulation to match the dynamic energy demands4. Additionally, it has been observed that metabolism influences the pace of development5, further emphasizing the need for coordinated regulation between developmental progression and metabolic activities.The orchestration of multicellular organism development relies on the sequential progression of proliferation and differentiation, each phase being accompanied by the activation of specific gene expression programs and diverse energy requirements7. PARP1 synthesizes poly(ADP-ribose) chains that modify chromatin proteins, resulting in their dissociation from DNA and subsequent chromatin opening10. Conversely, poly(ADP-ribose) glycohydrolase (PARG) reverses PARP1 activity by removing poly(ADP-ribose) moieties from acceptor proteins13. Recent studies have revealed a complementary, rather than antagonistic, relationship between PARG and PARP116. Upon activation, PARP1 undergoes automodification and dissociates from chromatin, leading to its inactivation18. In contrast, by removing poly(ADP-ribose) moieties from PARP1, PARG allows for its re-association with chromatin.Poly(ADP-ribose) polymerase 1 (PARP1), a chromatin-associated protein, has emerged as a critical player in developmentparp1C03256 hypomorph and parg27.1 null mutant animals suffer developmental arrest just prior to pupation stage, while their embryonic and larval development is temporally comparable to wildtype animals18. Consequently, the animals are viable but remain third instar larvae, unable to complete their development7. Previous findings suggest that both PARG and PARP1 regulate the transcription of developmental genes during the larva-to-pupa transition14. However, PARG lacks a DNA-binding domain (DBD) and seems to interact with chromatin only to a limited extent19, the specific interaction between PARG and chromatin in the context of the protein’s recruitment remains to be elucidated. We hypothesized that PARG is recruited to regulate transcription through its interaction with PARP1. To investigate this possibility, we conducted chromatin immunoprecipitation (ChIP) of PARG and PARP1 during the late third instar larval stage. Our results demonstrate that both PARP1 and PARG directly control global changes in the transcriptional profile that occurs prior to metamorphosis for both metabolic and developmental processes but through distinct mechanisms. Firstly, together with PARP1, PARG binds to the promoter region of genes crucial for pupation, promoting their expression. Secondly, in the absence of PARP1, PARG binds to the gene body of metabolic genes, repressing their expression, and binds to genes that are no longer required at the end of larval stages, repressing their expression as well. Together, these results suggest that PARP1 and PARG coordinate the regulation of metabolism and developmental genes during developmental progression.In fruit flies, both parg mutant background, which was compared to a yellow white control line lacking GFP expression. We specifically chose this stage of wandering third instar larvae because it is the final stage before parg and parp1 mutants experience developmental arrest. Furthermore, the timing of this developmental stage is sharp, limiting potential developmental disparities between animals20. We have previously shown that PARG-YFP effectively rescues the developmental arrest observed in parg27.1 null mutants13 and exhibits, on average, a 60% higher expression level compared to endogenous Parg  assays using wandering third instar larvae (puffstage 7–9), expressing PARG-YFP in an endogenous kek1 locus, one of the top peaks  that plays a critical role during metamorphosis25. Collectively, our findings underscore the collaborative role of PARG and PARP1 in promoting the expression of critical developmental genes that play a pivotal role in metamorphosis.Next, we analyzed the time course expression of PARG/PARP1 common target genes in wild-type animalsage Fig. A with arage Fig. B. In conage Fig. C. Gene oage Fig. . A speciage Fig. . These g23. Overall, PARG-alone targets are genes silenced during late third instar larvae and start their expression again during late pupa . Strikingly, these genes exhibit a reduction in expression prior to the transition to pupa, while their expression is substantially upregulated in parg mutant, has we previously reported14. Simultaneously, our investigation unveiled PARG's independent binding to the loci of metabolic genes governing fatty acid biosynthesis, glycogen metabolism, and amino acid metabolism  enzymes directly orchestrate transcriptional changes that start before metamorphosis by promoting the expression of genes required for pupation while in parallel regulating negatively the expression of metabolic genes before the transition to pupal stage.parg27.1/parg27.1; pP{w1, UAST::PARG-EYFP}, 69B-GAL4/TM2, as described in19. The parg27.1 mutant was described in11, P{w1, UAST::PARG-EYFP} was described in43, and 69B-GAL4 driver was described in7. The expression of PARG-EYFP rescues the lethality of parg mutant. The PARP1-YFP line used in ChIP-seq was P{w1, UAST::PARP1-EYFP}, P{GAL4}Mz1087.hx ; parp1C03256/parp1C03256. UAST-PARP1-EYFP was described in32 and Mz1087.hx GAL4 driver was described in44. The expression of PARP1-EYFP rescues the lethality of parp1 mutant. A yellow white strain carrying the mutations y1, w1118 was used as a YFP-negative control line.Flies were raised at 20 °C. The PARG-YFP line used in ChIP-seq corresponds to yellow white and PARG-YFP flies. Total RNA was extracted from cells using the QIAshredder column and RNeasy kit (Qiagen). Contaminating genomic DNA was removed by the g-column provided in the kit. cDNA was obtained by reverse transcription using M-NLV reverse transcriptase (Invitrogen). Real-time PCR assays were run using SYBR Green master mix (Bio-Rad) and an Applied Biosystems StepOnePlusTM instrument. The amount of DNA was normalized using the difference in threshold cycle (CT) values (ΔCT) between rpL32 and parg genes.This assay was performed in triplicate. Twelve wandering third instar larvae were collected for control rpL32) were 5′-GCTAAGCTGTCGCAACAAAT-3′ (forward) and 5′-GAACTTCTTGAATCCGGTGGG-3′ (reverse).The quantitative real-time PCR (qPCR) primer sequences for Drosophila melanogaster ribosomal protein L32 gene (parg were 5′-AGAAACACCCTCAAGAGGAAG-3′ (forward) and 5′-CGCTCTGTGGGACACAC-3′ (reverse).Sequences for Drosophila PARG. This experiment was performed in duplicates for PARG-YFP  and in triplicates for PARP1-YFP. 75 wandering third instar larvae (L3 puff stage 7-9) were collected in a 2 ml DNA LoBind Eppendorf tube and washed twice with 1 ml 1× PBS. The larvae were homogenized in ice-cold lysis buffer  using a pellet pestle. The homogenized lysate was crosslinked using 244.5 µl of 11% formaldehyde to a final concentration of 1.8% for 15 min at room temperature on a rotator. 500 mM Glycine was added to quench the fixative on ice for 5 min. The larval debris was pelleted at 1,000 g for 3 min, and the supernatant was removed. The pellet was resuspended in 1 ml sonication buffer , and chromatin was fragmented to 300–500 bp by Bioruptor sonicator (UCD-200) for 20 cycles  in a cold room. The sonicated material was pelleted at 10,000 g for 10 min at 4 °C, supernatant was collected, and then fragment size was checked prior to immunoprecipitation. The sonicated chromatin was pre-cleared and incubated with an anti-GFP polyclonal antibody  at 4 °C overnight. TP401 recognizes YFP as well. The immunoprecipitated chromatin was then collected with prewashed Protein A agarose beads for 2 h. The beads were sequentially washed with the following buffers: 1 low-salt buffer wash , 3 high-salt buffer washes , 1 LiCL wash , and 2 TE buffer washes before elution. Bound chromatin on beads was eluted twice at room temperature using 250 µl of freshly prepared ChIP elution buffer (1% SDS and 100 mM NaHCO3) for 15 min and reverse-crosslinked overnight at 65 °C. The eluates were then treated with RNase A and proteinase K prior to DNA extraction via phenol–chloroform extraction and ethanol precipitation. The library was prepared using NEBnext multiplex oligos for Illumina kit (Index primer set 4), according to the manufacturer’s protocol. Paired-end sequencing was performed by Novogene Corporation, Sacramento CA. Raw data are available here: (GSE228898).ChIP was performed with PARG-YFP and PARP1-YFP lines and with a yellow white line (control line) that does not express YFP as a negative control line. We performed ChIPseq experiment on YFP-tagged PARG due to the unavailability of antibodies capable of effectively binding to kek1 locus, we performed another set of ChIP assay on PARG-YFP and a yellow white line. This experiment was performed in triplicates. We designed two sets of primers  and one set to amplify the beginning of kek1 gene body where PARG is not detected (negative region).ChIP-qPCR assay was repeated with three biological replicates per condition for ChIP-qPCR confirmation. To confirm that PARG binds to the promoter region of kek1 positive region: 5′-GTTGCGTCGTTCCCGCTGTAGC-3′ (forward) and 5′-CGGTGTGTCCTGGCTAGCGGTAC-3′ (reverse).Primers used for kek1 negative region: 5′-GGATCTGCATGTGGATGAGTTTGCC-3’ (forward) and 5′-GCTCGACATGTAATCGAGGCATTCTC-3′ (reverse).Primers used for Real-time PCR assays were run using SYBR Green master mix (Bio-Rad) volume and an Applied Biosystems StepOnePlus™ instrument. The amount of DNA in the immunoprecipitated fraction (IP) was compared to the Input fraction for both PARG-YFP and yellow white control lines.Drosophila third instar larvae and included PARG-YFP ChIP-seq (this study), (GSE228898). parg mutant RNA-seq from our previous study14, GSE200499. PARP1-YFP ChIP-seq, (GSE217729). parp1 mutant microarray from our previous study45, ATAC-seq22, GSE96922. Pol II ChIP-seq46 (GSE15292). H3K4me3 ChIP-seq46, GSE49491. H3K27Ac ChIP-seq 46, GSE49488. H3K27me3 ChIP-seq46, GSE49490. H3K9me2 ChIP-seq46, GSE47260. H3K9me3 ChIP-seq46, and GSE47258. All these datasets were analyzed from raw data. In addition, we used the Developmental time-course RNA-seq dataset23, SRP001065.In this study, we compared different publicly available ChIP-seq and ATAC-seq datasets. All were performed on whole 47. The quality of raw reads was checked using FastQC (version. 0.11.9), and adapters were removed with fastp48. Trimmed raw reads were aligned to the Drosophila genome (dm6) using Bowtie249. Unmapped and low-quality reads were discarded  using BamTools50. Duplicate reads were identified and removed from mapped reads using Picard MarkDuplicates (http://broadinstitute.github.io/picard). MACS251 was used to call peaks against control  using default settings. Peaks were annotated to genomic features with ChIPseeker 52. Pairwise correlation of peaks was determined using Intervene53. MACS2 bedGraph pileups were used to generate normalized coverage of ChIP-seq signals using Deeptools bigWigCompare by computing the ratio of the signals (IP vs. Control/Input) using a 50 bp bin size. Deeptools multiBigwigSummary and plotCorrelation54 were used to determine genome-wide signal correlation using a 10 kb bin size. Deeptools computematrix Deeptools plotHeatmap54 was used with a 50 bp bin size to create enrichment profiles around peak centers (± 1 kb) in reference mode, or in a 2 kb scale region mode from transcription start site (TSS) to transcription end site (TES) to create enrichment profiles along the genes. Scale region mode also included the 1 kb flanking regions before TSS and after TES.ChIP-seq data were analyzed with Galaxy55. The list of Drosophila transcription factors was obtained from Flybase56 (Gene Ontology “DNA-binding transcription factor activity”). Time-course heatmap was generated with heamap2 after computing z-scores and performing an Euclidian clustering. Gene set of a specific GO-term were retrieved from AmiGO database58.Gene ontology (GO) terms were determined using g:profilerSupplementary Information 1.Supplementary Table S1.Supplementary Table S2.Supplementary Table S3.