Infections by non-segmented negative-strand RNA viruses (NNSV) are widely thought to entail gradient gene expression from the well-established existence of a single promoter at the 3’ end of the viral genome and the assumption of constant transcriptional attenuation between genes. But multiple recent studies show viral mRNA levels in infections by respiratory syncytial virus (RSV), a major human pathogen and member of NNSV, that are inconsistent with a simple gradient. Here we integrate known and newly predicted phenomena into a biophysically reasonable model of NNSV transcription. Our model succeeds in capturing published observations of respiratory syncytial virus and vesicular stomatitis virus (VSV) mRNA levels. We therefore propose a novel understanding of NNSV transcription based on the possibility of ejective polymerase-polymerase collisions and, in the case of RSV, biased polymerase diffusion. Mononegavirales) contain major pathogens such as Ebola, rabies, measles virus, respiratory syncytial virus (RSV), and vesicular stomatitis virus (VSV)—the latter is a highly studied bovine pathogen of the same family, Rhabdoviridae, as rabies virus.Viruses with nonsegmented negative-strand RNA genomes (NNSV)  complex, into the RNA genome.Every NNSV gene contains essential and highly conserved gene start (GS) and less highly conserved gene end (GE) signal sequences flanking the open reading frame (ORF). Transcription is initiated at the GS signal which also serves as a capping signal on the 5’ end of nascent mRNA . The polvia an unknown mechanism between genes (The still widely accepted textbook model of NNSV gene expression predicts a transcription gradient from 1) polymerase entry at the 3’ end of the genome; 2) “obligatorily sequential” start-stop transcription in response to the conserved GS and GE signal sequences; and 3) transcriptional attenuation en genes . Howeveren genes . Regardien genes , the solHere we implement a coarse-grained, mechanistic and stochastic computational model incorporating known and, ultimately, newly proposed features (ejective pol-pol collisions and 5’ biased pol diffusion) of the underlying molecular biophysics to gain a deeper understanding of NNSV transcription and to capture, for the first time, experimentally observed non-gradient RSV and gradient VSV gene expression patterns.https://github.com/BCM-GCID/Publications/tree/main/Rethinking_NNSV_Gene_Expression.Computational models of RSV and VSV transcription were written in the Python programming language using the free and open-source Scientific Python Development Environment (Spyder version 3.3.2). The model code is freely available on GitHub: scan . A random walk is a simple model of diffusion where a simulated pol moves either one genomic chunk 5’ or 3’ along the genome. A parameter Dbias is used as a multiplicative factor (Dscan*Dbias) to 5’ bias (or not) the random walk taken by modeled pols—i.e., Dbias > 1 biases pol movement 5’; Dbias = 1 results in an unbiased random walk. Each genome is divided into chunks of a size thought to reasonably approximate the footprint of a single RSV or VSV pol . Diffusing non-transcribing pols cannot “hop” over other pols and a single genomic chunk can only be occupied by a single pol at any one time.In brief, the models simulate one or more viral RNA-dependent RNA polymerases (pols) entering a linear RSV or VSV genome at the 3’ end and taking a random walk at a rate Dtransc (units = “genomic chunks” per simulated event) translocates onto a GE signal (Gene start (GS) and gene end (GE) signal sequences are modeled as separate genomic chunks positioned along the modeled genomes according to their known positions from sequencing data . TranscrE signal . InitiatThe simulations occur one event at a time  whereby the positions and states (non-transcribing or transcribing) of the one or more modeled pols is stochastically updated according to the rules outlined above before proceeding to the next event. After simulating 10 s of thousands of events, each gene’s mRNA level divided by the total mRNA level is outputted. These data are plotted to visualize a gene expression pattern.We took a heuristic approach to fitting actual observations of RSV and VSV gene expression and started by modeling a single pol taking an unbiased random walk down either genome and stochastically initiating and terminating transcription .In this simple case, the parameters to explore are probabilities of transcription initiation and termination. The termination probabilities can be derived directly from published sequencing data for RSV, as these are simply the complement of the published readthrough rates . For VSVin vitro gene expression patterns  ratios of L and M2 mRNA levels and values of the maximum pol number and ktransc , the average number of pol ejections starts to plateau beyond a max pol # of 10. This again shows that the steady-state number of pols bound to a genome in the model depends on ktransc and that this number is close to 10 at the highest value of ktransc tested (assuming a pol footprint of 28 nt). In addition, curves for the higher values of ktransc start to converge, suggesting that the model is reaching its maximum pol ejection frequency.The average number of pol ejections generally increases with increasing max pol # and increasing ktransc . Howevertransc  . The biaBias, with a value used as a multiplicative factor for 5’ diffusion only  with every 5’ movement while moving only one step (assuming Dscan = 1) with every 3’ movement; the probabilities of moving in either direction remain equal. This change could also be modeled by modifying the probabilities of 5’ vs. 3’ pol translocation and keeping each step size the same.A 5’ pol diffusion bias was modeled by including a new parameter in the model, Dion only . Thus, aBias, and looked for a drop in the predicted value of L:M2 mRNA levels .A 5’ diffusion bias was needed to capture both RSV data sets because of a common dramatic decrease in expression between genes M2 and L. In contrast, a 5’ diffusion bias was not needed to capture the benchmark observations of VSV gene expression used here; however, including one has minimal effect on the model’s output (data not shown). Thus, we simply cannot make a model-supported prediction about whether non-transcribing VSV pols diffuse with a 5’ bias. Continuing with VSV, the high quality fit we report involves a 6-fold range of N-phase  ejective collisions occur between transcribing and non-transcribing NNSV pols; 2) non-transcribing RSV pols (and perhaps VSV pols) undergo 5’ biased diffusion along the viral genome; and 3) an increase in the number of pols bound to and diffusing along an NNSV genome at any one time will lead to more frequent pol-pol collisions and a sharper transcription gradient. Sophisticated single molecule TIRF-based assays are needed to directly test predictions 1-2, while 3 can be tested using established minigenome or recombinant genome assays along with high throughput sequencing.


The precise spatiotemporal gene expression is orchestrated by enhancers that lack general sequence features and thus are difficult to be computationally identified. By nascent RNA sequencing combined with epigenome profiling, we detect active transcription of enhancers from the complex bread wheat genome. We find that genes associated with transcriptional enhancers are expressed at significantly higher levels, and enhancer RNA is more precise and robust in predicting enhancer activity compared to chromatin features. We demonstrate that sub-genome-biased enhancer transcription could drive sub-genome-biased gene expression. This study highlights enhancer transcription as a hallmark in regulating gene expression in wheat.The online version contains supplementary material available at 10.1186/s13059-022-02675-1. Widely cultivated wheat has an extremely large genome, which harbors abundant regulatory elements (REs) in noncoding regions , 2. REs,To answer these questions, we modified two nascent RNA sequencing methods for wheat seedlings: global nuclear run-on sequencing (GRO-seq) and plant native elongating transcript sequencing (pNET-seq) , 24. BotConsistent with previous studies, apparent transcriptional pausing was observed in close proximity to active transcription start sites (TSSs) of annotated genes , 24 Addc. The ovWe next characterized the epigenomic features surrounding intergenic and genic transcribed regions. Overall, both intergenic and genic transcription are strongly associated with open chromatin regions, RNA Pol II engagement and transcriptionally active histone marks including H3K9ac, H3K4me3, H3K36me3, and H3K27ac Fig. e, f. We Drosophila and mammals indicates that highly active enhancers are generally marked by H3K4me3 [Given that intergenic transcribed regions in wheat hold a variety of active regulatory marks, we speculated that a fraction of intergenic TCs represents eRNAs. As indicated in Figure S8a, an intergenic transcribed region displayed high levels of enhancer hallmarks , includi H3K4me3 , 33–36, p < 2.2E−16, Welch’s two-sample t-test) , followed by chromatin accessibility  and active histone modification , which indicated that eRNA is more robust in predicting enhancer activity than canonical chromatin features  gene, which is differentially expressed in various tissues [PR10 from subgenomes A was targeted by a transcribed enhancer and displayed higher expression levels than the other two homoeologs from subgenomes B and D, which were associated with untranscribed enhancers  cultivar “Chinese Spring” was grown under long-day conditions. Leaf tissue of 12-day-old seedlings was collected by flash freezing with liquid nitrogen followed by nuclei isolation.The bread wheat  and cutadapt (version 1.16) programs  to removSequencing reads were cleaned and mapped as described above except the 5′ coordinate of R2 reads with the directionality indicated by R1 reads was considered the position of the engaged polymerase. The pNET-seq signal at each site and the correlations of the 4 biological replicates were calculated as described above. The alignments of 4 biological replicates were combined for subsequent analysis.TSScall  with theWith the aim of accurately achieving the intergenic transcript, we removed the TCs that overlapped with the annotated high confidence and low confidence genes (IWGSC v1.1). To avoid false-positives due to incomplete annotations, we also removed the TCs that overlapped with the upstream and downstream 1 kb of annotated genes. In addition, we applied StringTie  and CPC2https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM2400210 for RNA-seq and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM340901 for GRO-seq). Maize data were downloaded from NCBI (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc= GSM2041246 for RNA-seq and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM1309038 for GRO-seq). Arabidopsis data were download from NCBI (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM2974957 for RNA-seq and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM2974947 for GRO-seq).Human data were downloaded from NCBI . The RNA-seq dataset used to assemble transcripts with coding potential was downloaded from NCBI (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE139019). The sequencing reads were trimmed with Trim Galore (version 0.6.4), and clean reads were mapped to the IWGSC reference sequence (version 1.0) with the HISAT2 program (version 2.1.0) [RNA-seq data used for comparison with nascent RNA-seq data were downloaded from NCBI (n 2.1.0)  was usedn 2.1.0) . The codn 2.1.0) .https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE121903). The reads were cleaned and mapped as described previously [Bisulfite-seq, ChIP-seq, and DNase-seq data of Chinese spring seedling tissue were downloaded from NCBI  or gfp (green fluorescent protein) gene [5 protoplasts using the PEG-mediated transfection method. After 24 h of incubation under dark conditions at room temperature, protoplasts were collected for visualization of fluorescence or luciferase assays. The protoplasts transformed with gfp reporter constructs were observed with a confocal microscope (Nikon C2 plus)  driven by a UBQ10 promoter was used to monitor transfection efficiency in the same vector  of the negative control was 1.6; thus, we set 2.0 as the cutoff of the positive enhancer. The activity for each enhancer candidate is listed in Additional file Sequences of the predicted intergenic enhancers were amplified from Chinese Spring genomic DNA  gene  (Additioin) gene . Brieflyhttps://www.ncbi.nlm.nih.gov/bioproject/PRJNA476679) [Twenty whole genome resequencing data were downloaded from NCBI (A476679) . The reaA476679) . The lowA476679) . Then, SA476679)  with theA476679)  in 500 bAdditional file 1: Figures S1. A diagram of the experimental approach. Figures S2-S4. GRO-seq and pNET-seq data quality. Figures S5-S10. Features of genic and intergenic transcription loci. Figures S11-S13. Characterization of eRNAs. Figures S14-S15. Validation of enhancer activity in wheat protoplasts. Figures S16-S17. eRNA and sub-genome-biased gene expression. Figures S18-S19. Conservation of eRNA regions [Figure S20. Validation of anti-Pol II antibodies. Figure S21. Uncropped images for Figure S20. regions . Figure Additional file 2: Supplementary Table S1. Statistics of nascent RNA sequencing data quality.Additional file 3: Supplementary Table S2. TSS and TC counts identified by TSScall.Additional file 4: Supplementary Table S3. Transcribed enhancer counts linked to homeolog pairs (pNET).Additional file 5: Supplementary Table S4. Transcribed enhancer counts linked to homeolog pairs (GRO).Additional file 6: Supplementary Table S5. Genomic positions and primers used for the reporter assay.Additional file 7: Supplementary Table S6. Location, eRNA level, and enhancer activity of 36 putative enhancers tested in wheat protoplasts.Additional file 8. Review history.


AUTS2 gene. Human AUTS2 protein has two major isoforms, full-length (1259 aa) and C-terminal (711 aa), the latter produced from an alternative transcription start site in exon 9. Structurally, AUTS2 contains the putative “AUTS2 domain” (∼200 aa) conserved among AUTS2 and its ohnologs, fibrosin, and fibrosin-like-1. Also, AUTS2 contains extensive low-complexity sequences and intrinsically disordered regions, features typical of RNA-binding proteins. During development, AUTS2 is expressed by specific progenitor cell and neuron types, including pyramidal neurons and Purkinje cells. AUTS2 localizes mainly in cell nuclei, where it regulates transcription and RNA metabolism. Some studies have detected AUTS2 in neurites, where it may regulate cytoskeletal dynamics. Neurodevelopmental functions of AUTS2 have been studied in diverse model systems. In zebrafish, auts2a morphants displayed microcephaly. In mice, excision of different Auts2 exons  caused distinct phenotypes, variously including neonatal breathing abnormalities, cerebellar hypoplasia, dentate gyrus hypoplasia, EEG abnormalities, and behavioral changes. In mouse embryonic stem cells, AUTS2 could promote or delay neuronal differentiation. Cerebral organoids, derived from an AUTS2 syndrome patient containing a pathogenic missense variant in exon 9, exhibited neocortical growth defects. Emerging technologies for analysis of human cerebral organoids will be increasingly useful for understanding mechanisms underlying AUTS2 syndrome. Questions for future research include whether AUTS2 binds RNA directly, how AUTS2 regulates neurogenesis, and how AUTS2 modulates neural circuit formation.AUTS2 syndrome is a genetic disorder that causes intellectual disability, microcephaly, and other phenotypes. Syndrome severity is worse when mutations involve 3’ regions (exons 9-19) of the  AUTS2 gene (autism-susceptibility-gene-2) was first identified in humans by genetic analysis of monozygotic twins with autism and chromosomal translocation t  and microcephaly  . Human A isoform . Sequencocephaly .AUTS2 gene was named for autism susceptibility, many AUTS2 syndrome patients have an outgoing personality in childhood   , NONO syr EP300) , TBR1 syr EP300) , and FBRr EP300) . The simtor TBR1 ; AUTS2 ptor TBR1 ; AUTS2 b300 mRNA ; and FBR300 mRNA , is the 300 mRNA .AUTS2 was first described, its functions could not be predicted on the basis of homology to known proteins. Indeed, only partial sequence homology was found to two genes with unknown functions, designated CG9056 and FLJ11618 (tay), and FLJ11618 as human fibrosin (FBRS). Both genes, it is now known, indeed belong to the same diversified superfamily of genes as AUTS2  gene; also, AUTS2 and FBRSL1 are closer to each other than to FBRS , which regulates neuronal development in the protocerebral bridge and motoneurons . Exons 1–7 are separated by long introns (16–301 kb), while exons 7–19 have shorter introns (∼1–3 kb) (Human ∼1–3 kb) . Full-le∼1–3 kb) . Many va∼1–3 kb) , here de∼1–3 kb) . The AUTSequence analysis has revealed several features of AUTS2 protein that suggest possible functions . Among tSequence analysis also indicates that AUTS2 is likely to be localized in cell nuclei. AUTS2-FL has multiple nuclear localization sequences (NLSs) in the 5′ region, and NucPred indicates 100% likelihood of intranuclear localization. AUTS2-C does not have discrete NLSs, but its overall sequence predicts 70% likelihood of intranuclear localization (NucPred). In addition, AUTS2-FL, but not AUTS2-C, contains a PY motif (PPPY), which may bind WW-domains to interact with other proteins. PY motifs interact with Nedd4 family E3 ubiquitin ligases for proteolysis , and witAUTS2 gene family   . The AUTnd FBRS) . Sequencnd FBRS) . All of nd FBRS) .AUTS2 include two blocs of exons, ExB1 and ExB2 , each connected by splice junctions that encode amino acids across the junctions; as well as several exons that encode non-integer numbers of amino acids   . Moreovear zone) . From E1tterning . AUTS2 ptterning . AUTS2 ptterning . In posttterning   (Another proposed intranuclear function of AUTS2 is to regulate RNA metabolism by associating with RNA-binding protein (RBP) complexes, and possibly with RNA directly. Immunoprecipitation (IP) of AUTS2 from developing mouse cortex followed by mass spectrometry (IP-MS) revealed that AUTS2 interacts with multiple RBPs  DDX5/17   . The hypd below)   . Furtherd below) . More stin vivo.Outside the nucleus, AUTS2-FL was found to interact with guanine nucleotide exchange factors (GEFs) such as P-Rex1 and the Dock1/Elmo2 complex  Hori et. These Gin vivo, since the aforementioned studies were done in cultured HEK cells or mESCs, after overexpression of AUTS2 or proposed interacting molecules.In HEK cells and in mESCs differentiated to radial glia-like neuronal progenitor cells, both AUTS2-FL and AUTS2-C interacted with WDR68 and SKI to form a novel AUTS2-WDR68-SKI (AWS) complex . The AWSauts2a  is similar as in humans, and likewise comprises 19 exons  in the nervous system (Nes-Cre), mutants had normal birth weight but grew more slowly than controls postnatally, and exhibited behavioral abnormalities such as decreased ultrasonic vocalizations (Dynll1) was significantly dysregulated among a panel of 9 candidate Auts2 target genes assayed by RT-PCR. Importantly, excision of exon 7 did not disrupt the exon 9 TSS, and AUTS2-C was presumably still expressed, although this was not tested  throughout the organism died in the neonatal period  or adulthood (CaMKIIa-CreERT2) permitted longer postnatal survival and additional studies  caused cerebellar hypoplasia, with defects of Purkinje cell maturation and synaptogenesis, plus behavioral abnormalities  that reduces both AUTS2-FL and AUTS2-C was also produced  was produced to interfere with expression of both AUTS2-FL and AUTS2-C isoforms (del15/del15Auts2) throughout the CNS (Nes-Cre) died neonatally with severe breathing abnormalities, documented by plethysmography. The erratic breathing implicated abnormal development of brainstem respiratory centers and raised the possibility that AUTS2 might be a vulnerability gene for sudden infant death syndrome. Excision of exon 15 only in the developing cortex (Emx1-Cre) allowed for survival to adulthood, and revealed defects of cortical structure, function, and gene expression (Tshz2) and laminar identity (such as Wnt7b and Pcdh20) were significantly dysregulated, as determined by RNA-seq. Significantly, many RNA transcripts that interacted with AUTS2 in normal neocortex (by RIP-seq) were also dysregulated in del15/del15Auts2 mutant neocortex (by RNA-seq). Indeed, mRNA dysregulation correlated more strongly with binding of the RNA to AUTS2 protein (RIP-seq), than with binding of AUTS2 to cognate genes in chromatin (ChIP-seq). These distinctions support the hypothesis that AUTS2 regulates gene expression mainly by modulating RNA metabolism.Recently, a conditional exon 15 allele  may also be explained, at least in part, by AUTS2 regulation of transcripts Prex1 and Rasgrf2, which were significantly reduced in del15/del15Auts2 neocortex. Both Prex1 and Rasgrf2 encode GEFs that activate Rac1  was recently described (del9/del9Auts2) in the central nervous system (Nes-Cre) was reported to cause early embryonic lethality. Heterozygous exon 9 excision was found to impair neuronal gene expression, as determined by RT-PCR of cultured neocortical cells   treated with ns (MNs) . Interesebrafish ; howeveron types . For coron types , but delon types . WDR68, on types . While din vitro models that can be utilized to investigate the complex and human-specific features of early brain development  . COs, deelopment . As COs AUTS2 variants can start to uncover neurobiological functions that contribute to the clinical heterogeneity observed in AUTS2 syndrome patients  RNA-seq, combined with immunohistochemical, spatial transcriptomics, and chromatin immunoprecipitation techniques can provide important morphological context to reconstruct the organization of disease-related expression patterns . Early rRecent work identified altered morphological and functional properties of apical neural progenitors in AUTS2 deficient COs . FurtherAUTS2 variants in regard to cell-type specific regulatory elements, especially those related to cell cycle control, cell fate inheritance, and timing of neuronal differentiation.Although ChIP-seq is a widely used method to evaluate global active and repressed chromatin states, it is limited by low signal-to-noise ratios and is not compatible with low cellular input–a potentially significant challenge for organoid applications . Howeverin vivo forebrain regulatory programs largely map with those seen in forebrain organoids cultured for over 20 months. Interestingly, during forebrain organoid development, 81% of Simons Foundation Autism Research Initiative (SFARI) genes were found to be expressed  mice (P33–P44) revealed an increased frequency of miniature excitatory postsynaptic currents (mEPSCs) with no change in amplitude, suggesting an increase of functional excitatory synapses  platforms have been extensively utilized to record extracellular field potentials from a diverse and large number of neurons smission .Several studies have investigated electrical properties and neuronal connectivity within CO models . MEAs prAuts2 is dynamically regulated during brain development and is expressed from a gradient in a high rostral to low caudal pattern within the developing neocortex  10.5  10.5  and is axed mice . On thisday 16.5 . Superfiuse line . AlternaLS-mRuby ].Auts2 may disrupt information processing at multiple stages within this structure. In the dentate gyrus, AUTS2 is expressed in two different populations of excitatory projection neurons: granule cells (GCs) and hilar mossy neurons (HMNs). Importantly, forebrain knockout of Auts2 leads to a significant reduction in the number of HMNs , ventrolateral/ventromedial (VL/VM) thalamic nuclei, cerebellum, and hippocampus  and superfamily (such as tay) likewise appear to have overlapping, but diversified functions. Importantly, many AUTS2 functions and interactions with other proteins remain to be confirmed, or have been studied in heterologous cell types (such as HEK cells). Considering these caveats, a paramount future goal will be to better define the functions and binding partners of AUTS2 in neurons from cerebral organoids. With several lines of evidence suggesting that AUTS2 is an RNA-binding protein, this possibility can be investigated using methods such as eCLIP. With the advent of methods to produce human COs and assembloids, future studies can go beyond animal models to evaluate AUTS2 molecular functions, binding partners, and neurodevelopmental roles in developing human neural tissues.As this review has illustrated, multiple functions have been proposed for AUTS2  on the bRH and AB produced figures and supplementary figures. All authors wrote and edited the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The MyoD1 gene plays a key role in regulating the myoblast differentiation process in the early stage of skeletal muscle development. To understand the functional elements of the promoter region and transcriptional regulation of the bovine MyoD1 gene, we cloned eight fragments from the sequence region of the MyoD1 gene promoter and inserted them into eukaryotic expression vectors for cotransfection with the mouse myoblast cell line C2C12 and Madin-Darby bovine kidney (MDBK) line. A variety of transcription factor binding sites in the longest 5′-flanking fragment from Guanling cattle MyoD1-P1 were predicted by using the online software TFSEARCH and ALGGEN PROMO as well as validated by the promoter-binding TF profiling assay II and yeast one-hybrid (Y1H) assay, including MyoD, VDR, MEF1, MEF2, SF1, and Myf6. Myf6 strongly activated the MyoD1 promoter, while MyoD1 was also capable of efficiently activating the expression of its own promoter. The transcription factors MEF2A, SF1, and VDR were further confirmed to be capable of binding to MyoD1 by Y1H system experiments. The effects of the Guanling cattle MyoD1 gene on the mRNA expression of the MEF2A, SF1, and VDR genes were determined by using a lentivirus-mediated overexpression technique, confirming that overexpression of the MyoD1 gene upregulated the mRNA expression of MEF2A as well as downregulated the expression of SF1 and VDR in the process of muscle myogenesis. Our study revealed the effects of transcription factors including MEF2A, SF1 and VDR on regulatory aspects of MyoD1, providing abundant information for transcriptional regulation of MyoD1 in muscle differentiation. The MyoD1 gene plays a key role in regulating the myoblast differentiation process in the early stage of skeletal muscle development. It consists of skeletal muscle tissue, connective tissue, nerve tissue, and blood or vascular tissue, and plays an important role in anatomical positioning, locomotion, preemption, mastication, and other dynamic events, including body metabolism regulation.2,3 The study of skeletal muscle has centered on efforts to dissect the underlying molecular mechanisms that regulate the initial activation and subsequent modulation of the contractile protein gene set in the muscle development process, leading to understanding the regulation of muscle growth and quality in meat-producing animal species.4–6 Several transcriptional regulatory factors, including myoblast determination protein family members, are believed to act as terminal effectors of signaling cascades and to produce appropriate developmental stage-specific transcripts, regulating the development and growth of skeletal muscle.7Skeletal myogenesis is characterized by a series of discrete developmental events that regulate the establishment of stable stem cell lineages, differentiation into diverse myoblasts, and specialization of the contractile unit to slow-twitch (type I) and fast-twitch (type II).8–11 that belong to a family of muscle-specific basic helix-loop-helix (bHLH) transcription factors: myogenic differentiation (MyoD),12 myogenic factor 5 (Myf5),13 myogenin (MyoG),14 and myogenic regulatory factor 4 .15 Among the MRFs, the determination factor Myf5 is expressed before adoption of the myogenic fate. MyoD, induced by Myf5, regulates the differentiation potential of an activated myoblast by inducing cell cycle arrest, a prerequisite for myogenic initiation, and acts together with MyoG and myocyte enhancer factor 2 (MEF2) to drive differentiation.16 It is also involved in regulating the growth, development, and repair of skeletal muscle at the embryonic stage to maintain the relative stability of the individual skeletal muscle.17,18 MyoG expression happens later and is crucial for terminal differentiation, while Mrf4 promotes both fate determination and differentiation.19,20 MyoD and Myf5 play a leading role in the differentiation of stem cells into myoblasts, coordinating the formation of muscle cells.10 Obviously, these transcription factors do not act alone but exist as part of a complex network of mediators that control every stage of myogenesis.21–24 The expression of MRF genes displays subtle correlativity in myogenesis and is dependent on MyoD, showing synergistic effects among members of the MyoD gene family.21 Skeletal muscle differentiation takes place when MRF genes of the MyoD family are activated in muscle progenitors, and this genetic program is operative in both the trunk and head regions.25 Among the MRF genes, the myogenic differentiation 1 (MyoD1) gene, first cloned in 1987,12 encodes a nuclear protein that belongs to the bHLH family of transcription factors and the myogenic factor subfamily. As a well-known transcription factor involved in controlling myogenic processes, MyoD1 is widely used as a gene model for the regulation of myogenesis. Promoters are important regulatory elements that initiate transcription and regulate the intensity and specificity of transcriptional genes.26,27 Previous studies have revealed that MyoD1 can promote transcriptional activation to regulate the expression of muscle-specific genes, including MyoG, creatine kinase, myosin, and desmin, by binding to their promoter regions.28,29 Despite significant progress in understanding the regulatory mechanisms of MyoD-mediated myogenesis at the transcriptional level in mice, chickens, and pigs,22,23,30 the roles of the core MyoD1 gene promoter-regulatory regions in the regulation of muscle differentiation remain elusive in cattle.31Skeletal myogenesis is regulated by the MyoD protein family, which includes four myogenic regulatory factors (MRFs)32–34 Qiu et al. (2010) have reported the important role of MyoD in bovine muscle development.35 In addition, Zhang et al. (2015) have reported that the Guanling bovine MyoD1 gene promoter region contains binding sites for the transcription factors MyoD, transcription factor IID (TFIID), Pax3, myocyte enhancer factor 1 (MEF1), MEF2, and vitamin D receptor (VDR);36 however, the effects of these transcription factors on the MyoD1 gene promoter are not clear. This experiment was designed to investigate the effects of the core MyoD1 gene promoter-regulatory regions on the regulation of bovine muscle differentiation by binding to transcriptional factors. In the present study, we successfully cloned the core coding region of the Guanling bovine MyoD1 gene promoter and overexpressed it in the mouse myoblast cell line C2C12 and Madin-Darby bovine kidney (MDBK) line to understand the transcriptional regulation mechanisms of the MyoD1 gene promoter-binding transcriptional factors, including myocyte enhancer factor 2A (MEF2A), steroidogenic factor 1 (SF1), and VDR, in skeletal myogenesis. Our study revealed the effects of transcription factors including MEF2A, SF1 and VDR on regulatory of MyoD1, providing abundant information for transcriptional regulation of MyoD1 in muscle differentiation.Skeletal muscle from domestic animals including cattle is a major source of high-quality protein in the human diet. Recent studies have investigated utilization of MyoD in animal breeding for meat improvement.2.2.1.To begin to discover the muscle-specific regulation of MyoD1 gene transcription, we cloned a total of eight fragments of different lengths from a region of the MyoD1 gene promoter and inserted them into the pGL3-basic reporter plasmid. The fragments were as follows: −1897/−680 (MyoD1-P0), −1897/+650 (MyoD1-P1), −976/+650 (MyoD1-P2), +78/+650 (MyoD1-P3), −976/+17 (MyoD1-P4), −420/+17 (MyoD1-P5), −108/+94 (MyoD1-P6), and −40/+17 (MyoD1-P7), relative to the predicted transcription start site at +1 . The con2.2.http://diyhpl.us/∼bryan/irc/protocol-online/protocol-cache/TFSEARCH.html)  (A variety of transcription factor binding sites in the longest 5′-flanking fragment from Guanling cattle MyoD1-P1 were predicted by using the online software TFSEARCH (CH.html)  and ALGGupc.es/) . The Guaupc.es/)  and 2, aTo investigate if these transcription factors were involved in activation of the Guanling cattle MyoD1 promoter, we used the promoter-binding TF profiling assay to detect both direct- and indirect-TF binding sites to the DNA. MyoD1-P4 and MyoD1-P5 with higher luciferase activity were cotransfected with selectively responsive transcription factors into the mouse myoblast cell lines C2C12 and MDBK. The fluorescence activity showed that the MyoD1 and Myf6 genes could significantly increase the activity of the MyoD1 gene in the C2C12 and MDBK cell lines . As show2.3.2.3.1The experimental data were measured by a Multifunctional Microplate Reader  and statistically processed to represent the intensity of luminosity, meaning the amount of washed-off probe in the nuclear extracts after binding of each of the transcription factors to the corresponsive probe, indirectly indicating whether the promoter carries the transcription factor binding sites. As shown in 2.3.2The bait vector pAbAi-MyoD1 was digested with BbsI to produce linearized products that were transformed into Y1H competent cells. The yeast transformants were screened on synthetic dextrose (SD)/-uracil (Ura) plates and further identified using colony polymerase chain reaction (PCR), confirming the successful transformation.36,47 and SF156 in the functional region of the promoter were recovered from the gel and ligated with the pGADT7 vector to construct the prey plasmids pGADT7-SF1, pGADT7-MEF2A, and pGADT7-VDR. PCR confirmed that the fragments of the MEF2A, SF1, and VDR genes were successfully inserted into the pGADT7 vector.The fragments amplified from the MEF2A and VDR that are proved to be involved in myogenic mechanism,The prey plasmids  and the pGADT7 empty vector were transfected into the bait strains. The transfected strains were inoculated on SD/-leucine (Leu)/Aureobasidin A (AbA) plates. As shown in 2.4.The fragment amplified from the coding DNA sequence region of the MyoD1 gene was used to construct the lentiviral overexpression vector pCDH-CMV-MyoD1-EF1-GFP + Puro. As shown in 3.et al. (1995) have reported that the Myf6 promoter is activated directly by other bHLH muscle-specific transcription factors, including MyoD1, but was unable to activate its own promoter in mice.37 In the present study, the Guanling cattle MyoD1 gene was proven to be directly activated by Myf6, and further experiments should be designed to study whether the MyoD1 gene can be indirectly activated by other transcription factors through indirect pathways. The MyoD gene family  has been shown to act as a key regulator that controls the expression of specific proteins in the proliferation and differentiation of muscle cells.8–11,18,27 Among them, MyoD1 plays an important role in muscle growth in the transcriptional regulation of muscle-specific genes,38 while Myf6 (MRF4) primarily functions in a downstream role in myogenesis, including myofiber formation19,39 and the maintenance of the muscle phenotype.39 The Myf6 and MyoD1 promoters are regulated quite differently, leading to opposite roles of MRF4 and MyoD in cell proliferation and myogenic differentiation,40 in which MyoD is a potential negative intercessor of MRF4 in regulating the cell cycle. Thus, while all of the myogenic bHLH factors are able to mediate myogenesis, it is becoming clear that they are regulated by different mechanisms.This study provided evidence for direct activation of the bovine MyoD1 promoter by the muscle-specific transcription factor Myf6. We demonstrated that a small region of the MyoD1 gene surrounding the transcription start site directs muscle-specific expression. Among the 10 transcription factors evaluated in the present study, Myf6 strongly activated the MyoD1 promoter, while MyoD1 also was capable of efficiently activating the expression of its own promoter. Black et al. ,36,41 who have reported a number of transcription factor binding sites, including MyoD, MEF1, MEF2, Myf6 and VDR, in the Guanling bovine MyoD1 gene promoter. Zhou et al. (2016) reported that the action sites of transcription factors MyoD, Myf5 and Myf6 of Guanling cattle are not on core region of with MyoD1 gene promoter. In the present study, the key transcription factor binding sites VDR and MEF2A that are proved to be involved in myogenic mechanism,36,47 and SF1 in the functional region of the promoter have been shown to be capable of binding to the MyoD1 gene promoter by the Y1H assay. The MEF2 family, which is widespread in muscle cells, belongs to the MADS superfamily and includes four structurally similar members, MEF2A, MEF2B, MEF2C, and MEF2D, playing a role in the activation of muscle-specific gene transcription.7,42,43 The MEF2 family acts as a major regulator of myogenic gene expression to activate or enhance gene expression by directly binding to many muscle-specific gene promoters or enhancers. Studies on the MEF2 gene families have mostly concentrated on MEF2A.44–47 The expression of MEF2 factors can be activated by members of the myogenic bHLH family, including MyoD,48 while the MEF2 binding site is required for the expression of several myogenic bHLH factors.49 Chen et al. (2016) revealed the relation of MEF2A to myogenic response by downregulating expression and activity of the uncoupling protein 3 (UCP3) promoter in Guanling bovine.47 In the present study, mRNA expression of the MEF2A gene was upregulated by overexpression of the MyoD1 gene; however, MEF2A was unable to activate the MyoD1 gene promoter directly. It is proposed that MEF2 factors activate the MyoD1 gene promoter through an indirect pathway and that MEF2A and MyoD1 appear to function in a complex network by auto- and cross-activating the expression of themselves as well as each other.We have reported that the Guanling cattle MyoD1 gene promoter contains multiple putative transcription factor binding sites, including MyoD, VDR, MEF1, MEF2, SF1, and Myf6. This finding is partially consistent with the results of Zhang 50 is believed to activate intracellular signaling pathways in skeletal muscle51 and to mediate the nongenomic effects of the steroid hormone 1a,25-dihydroxyvitamin D3  2D3) in chick myoblasts.52 The results of the present study confirmed that VDR is a MyoD1 gene promoter binding transcription factor, but unable to significant increase activation of MyoD1 gene  of the MyoD1 gene surrounding the transcription start site and found novel transcription factor binding sites, including VDR and SF1, in the Guanling cattle MyoD1 gene promoter by the promoter-binding TF profiling assay II. Myf6 strongly activated the MyoD1 promoter, while MyoD1 was also capable of efficiently activating the expression of its own promoter. The transcription factors MEF2A, SF1, and VDR were further confirmed to be capable of binding to MyoD1 by Y1H system experiments. Overexpression of the MyoD1 gene upregulated the expression of MEF2A, while it downregulated the mRNA expression of SF1 and VDR in the process of muscle myogenesis.4.4.1All procedures in the present study were approved by the Experimental Animal Management Committee of the Key Laboratory of Animal Genetics, Breeding, and Reproduction in the Plateau Mountainous Region, Guizhou University, Guiyang, China, and were performed according to the guidelines developed by the China Council of Animal Care.N = 3) were used for venous blood collection, according to the livestock slaughtering industry standards (GB/T 20551-2006) of the Chinese Ministry of Agriculture. Blood samples were first treated with heparin sodium anticoagulation and then stored at −70 °C for genomic DNA extraction using AxyPrepDNA Blood Genomic DNA Miniprep Kit , according to the manufacturer's instructions. The three Guanling cattle were slaughtered following standard commercial procedures to collect the latissimus dorsi muscles. The fresh muscle tissues were placed in liquid nitrogen and stored at −80 °C for total RNA extraction.Three 15 month old Guanling cattle , according to the manufacturer's instructions. For cDNA cloning, the first-strand cDNA was synthesized from 1 μg of total RNA, according to the instructions of the Revert Aid™ First Strand cDNA Synthesis Kit .Genomic DNA was extracted from the latissimus dorsi samples of Guanling cattle by using AxyPrep genomic DNA small kit , according to the manufacturer's instructions. The quality of DNA was estimated by agarose gel electrophoresis.4.3http://www.premierbiosoft.com/primerdesign/index.html) and Oligo 6.0 (http://www.oligo.net/), according to the complete sequences from NCBI (−1), and 8 μL of ddH2O. The reaction conditions were carried out with predenaturation at 94 °C for 2 min; followed by 35 cycles of 94 °C for 30 s, 58–62 °C , the MRF gene family , the MEF2 gene family , the SF1 gene (NM_001081614.1), and the VDR gene (NM_001167932.1) were designed by Primer Premier 5.0  with the nuclear extracts from longissimus dorsi and purified target fragments recovered from PCR. In the screening, briefly, we used the promoter fragments and the fluorescently labelled probes to bind competitively to the protein in the nucleus extracts, and then the complex TF-bound probes were separated by denaturation using a set of procedures including column centrifugation and elution, according to the manufacturer's instructions . After denaturation, the complex compounds were incubated with a hybrid plate for measurement with a Multifunctional Microplate Reader . Androgen receptor (AR) was used as the blank control to normalize the readings that were statistically treated.4.5ABlank, ATreated, and AControl were the averages of the blank, control, and experimental groups, respectively. Whereas AControl was expressed as the readings of the control group minus ABlank, and ATreated was expressed as the readings of the experimental group minus AControl. The judgment value was calculated by AControl/ATreated. The statistically treated data were greater than 50, and the judgment value was greater than 3 in the present study.4.64.6.1The PCR-amplified fragments of the MEF2A, SF1, and VDR were recovered from the gel, and ligated with the pGADT7 vector to construct the prey plasmids pGADT7-SF1, pGADT7-MEF2A, and pGADT7-VDR.−1 ampicillin for overnight inoculation at 37 °C. The individual colonies with a normal morphological size were picked for subculture in 20 mL of LB liquid medium overnight at 37 °C, from which the plasmids were extracted and verified by dual-enzyme digestion.The PCR-amplified fragments of the MyoD1 gens and pAbAi were excised with the restriction enzyme, and then recovered by AxyPrep DNA Gel Recovery Kit , respectively. MyoD1 was ligated to pAbAi-1 to construct the bait vector pAbAi-MyoD1. The bait vector pAbAi-MyoD1 and the prey vector pGADT7-SF1 were transfected into the TOP10 strain and then spread transfected bacteria on lysogeny broth (LB) plates containing 1 mg mL4.6.2600) values were 0.8–1.0, the culture solution was centrifuged at 3000 rpm and 4 °C for 5 min. The sediment was resuspended in 50 mL of ice-cold sterile water, and centrifuged at 3000 rpm and 4 °C for 5 min. The step was repeated two more times. The last sediment was resuspended in 200 μL of ice-cold 1 M sorbitol and divided into two precooled Eppendorf® tubes containing 80 μL per tube. The prepared competent yeast cells were stored at −80 °C.The Y1H monoclone from yeast peptone dextrose adenine (YPDA) plates was inoculated in 15 mL of YPDA liquid medium at 30 °C with shaking at 200 rpm for 24 h, and 100 μL of culture was inoculated in 100 mL of YPDA solution at 30 °C with shaking at 200 rpm for 16–18 h. When the optical density at 600 nm  was picked for culture in 15 mL of YPDA liquid medium at 30 °C with shaking at 200 rpm for 24 h, and 100 μL of culture was inoculated in 100 mL of YPDA solution at 30 °C with shaking at 200 rpm for 12–16 h. When the ODThe pGADT7 empty plasmid and pGADT7 prey plasmids were transfected into Y1H (pAbAi-1) competent cells using an Eppendorf® electroporator with electroporation parameters of 1500 V and 5 min, respectively. A 150 μL sample of the yeast cells was spread on SD/-Leu/AbA plates and incubated at 30 °C for 4–5 days. The bait strains were also spread on SD/-Leu/AbA plates as controls.4.74.7.1E. coli. The plasmid DNA samples were isolated from E. coli cultures, digested with restriction enzymes, and separated by electrophoresis on agarose gels to compare the fragment sizes to the target inserts. The plasmid DNA samples indeed harboring the target inserts were sequenced by Invitrogen to further confirm the identities of the target fragments, which were designated as pGL3-MyoD1 and pcDNA3.1(+) – SF1.The PCR fragments containing the target promoter were sequenced and separated by 1.2% agarose gel electrophoresis, and the bands corresponding to the PCR products were excised from the gel. DNA samples were purified from the gel slices using an AxyPrep DNA Gel Recovery Kit, according to the manufacturer's instructions . The recovered target fragments were ligated to pcDNA3.1(+) and pGL3-basic using T4 DNA ligase overnight at 16 °C and then transformed into 4.7.2http://omegabiotek.com/store/product/plasmid-mini-kit-1-q-spin/), and the concentrations were estimated by a micro-spectrophotometer. Mouse C2C12 cells showing stable growth were inoculated onto 24-well cell culture plates at 1 × 105 cells per well and incubated in an incubator at 37 °C, 5% CO2, and saturated humidity to 80% confluency for transfection with two groups of plasmid DNAs. The testing group consisted of 600 ng of pGL3-MyoD1 + 200 ng of pcDNA3.1(+) – SF1 + 60 ng of pRL-TK plasmid DNAs, while the control group contained 600 ng of pGL3-MyoD1 + 200 ng of pcDNA3.1(+) + 60 ng of pRL-TK plasmid DNAs. Each group was placed in three dual-wells and incubated in an incubator at 37 °C, 5% CO2, and saturated humidity for 24 h. The cell cultures were harvested for lysis with 120 μL of lysis buffer.The endotoxin-free plasmid DNAs were isolated from the plasmids pGL3-MyoD1, pcDNA3.1(+) – SF1, pcDNA3.1(+), and pGL3-basic as well as the internal reference vector pRL-TK by using an Endo-Free Plasmid Mini Kit I (Q-spin)  (4.7.3Cell lysate (20 μL) was placed in a white 96-well microtiter plate to measure the luciferase activity using the Dual-Luciferase® Reporter Assay System , according to the manufacturer's instructions. Briefly, 100 μL of F assay reagent I was predispensed into the bottom of the tube, followed by gently tapping the tube wall for 3–5 times to mix, and put into a Multifunctional Microplate Reader  immediately to measure the luminous value (M1) in firefly luciferase luminous units (RLUs). A total of 100 μL of R assay reagent II was added the bottom of the tube, followed by gently tapping the tube wall for 3–5 times to mix, and put into a multifunctional microplate reader immediately to record the luminous value (M2) in RLUs. The relative luciferase activity, calculated by M1/M2, was presented as the mean ± standard deviation of three replicates.4.84 cells per well and inoculated overnight in 10% fetal bovine serum (FBS) complete medium. Puromycin was prepared as a 1 mg mL−1 stock solution and diluted with FBS complete medium, followed by addition to wells at working concentrations of 0, 0.2, 0.4, 0.8, 1, 1.5, 3, and 10 μg mL−1. The plate was inoculated in an incubator to observe cell growth over 3 days for screening of the lowest concentration that kills all cells. In the present study, 1 μg mL−1 puromycin was used as the screening concentration.The cells in a 10 cm Petri dish were grown to about 80% confluency and digested by 0.25% trypsin for cell counting. Then, the cells were transferred to a 24-well plate at 5 × 105 cells per well and cultured overnight in 10% FBS medium. Meanwhile, the lentivirus solution was removed from −80 °C and thawed in an ice-water bath. Once the virus was fully thawed, the proper amount was transferred to a well of a 24-well plate and diluted with FBS medium to 1 × 107 virus per well to bring up the volume in the wells to 1 mL containing 2 μg mL−1 polybrene. Six hours after viral infection, the medium was removed and replaced with 2 mL of FBS complete medium, and the cells were incubated in an incubator. One well was used as uninfected control cells. At 48 h after infection, the medium was replaced with screening medium containing 1 μg mL−1 puromycin, and the cells were cultured in an incubator and observed daily. The screening medium was replaced daily for 3–5 days when the control cells were completely dead. The infected cells were continuously cultured on maintenance medium containing 0.5 μg mL−1 puromycin to grow to the desired density. Two days later, the infected cells in each well of a 6-well plate were transferred to two wells, and the cells were continuously cultured on maintenance medium for 2–3 days. Then, the cells from one well were examined, and those from another well continued to be cultured. Ten days after antibiotic screening, the cells were collected for detection of the expression of the target genes using Q-PCR SsoFast™ EvaGreen Supermix . Stable cell lines were frozen for future use.The target cells were transferred to a 24-well plate at 5 × 10Houqiang Xu and Wei Chen conceived and designed the experiments; Di Zhou, Tao Yang, Ming Zhang performed the experiments; Di Zhou and Yuanyuan Wang analyzed the data; Di Zhou wrote the paper.The authors declare that no conflicting interests exist.


The complement system is one of the first defense lines protecting from invading pathogens. However, it may turn offensive to the body’s own cells and tissues when deregulated by the presence of rare genetic variants that impair physiological regulation and/or provoke abnormal activity of key enzymatic components. Factor B and complement C2 are examples of paralogs engaged in the alternative and classical/lectin complement pathway, respectively. Pathogenic mutations in the von Willebrand factor A domain (vWA) of FB have been known for years. Despite substantial homology between two proteins and the demonstration that certain substitutions in FB translated to C2 result in analogous phenotype, there was a limited number of reports on pathogenic C2 variants in patients. Recently, we studied a cohort of patients suffering from rare kidney diseases and confirmed the existence of two gain-of-function and three loss-of-function mutations within the C2 gene sequences coding for the vWA domain (amino acids 254-452) or nearly located unstructured region (243-253) of C2 protein. Herein, we report the functional consequences of amino acid substitution of glutamine at position 263. The p.Q263G variant resulted in the gain-of-function phenotype, similarly to a homologous mutation p.D279G in FB. Conversely, the p.Q263P variant found in a patient with C3 glomerulopathy resulted in the loss of C2 function. Our results confirm that the N-terminal part of the vWA domain is a hot spot crucial for the complement C2 function. The complement system is formed by serum proteins organized into a chain of proteolytic and conformational changes that eventually lead to the osmotic lysis of target cell . C2 protPatient data are retrieved from the Spanish aHUS/C3G Registry. The previous collection was described in , and theThe human lymphoma cell lines Raji and Ramos  were cultured in RPMI 1640 medium with L-glutamine (ATCC) supplemented with 10% FBS (ATCC) at 37°C in humidified 5% CO2 atmosphere. Ramos cells with CD55 or CD46 knockout were produced by CRISPR/Cas9 technology as described in ref . Obtainend, 4th and 7th day post-transfection and stored at -80°C. Crude medium was loaded onto HisTrap FF affinity column  and eluted with linear gradient of 0-0.7 M imidazole using an Äkta Start System. The purified proteins were analyzed with SDS-PAGE electrophoresis and Western blot, as described in (The wild-type C2 cDNA sequence (based on accession number NM_000063.5) was codon-optimized for expression in eukaryotic system, and six histidine codons were added at 3` terminus. The construct was synthesized and cloned into the pCEP4 vector in the framework of GeneArt Gene Synthesis service by Thermo Fisher. The Q263P and Q263G mutations were introduced using QuikChange XL Site-Directed Mutagenesis Kit (Agilent) into codon-optimized sequence of wild-type C2 cDNA. Proteins were expressed in HEK293 Freestyle cells (Thermo Fisher) transfected with the respective plasmids using Freestyle Max reagent (Thermo Fisher). Conditioned FreeStyle 293 expression medium (Thermo Fisher) was collected on the 2CDC assay was performed on Raji and Ramos cell lines sensitized with rituximab (50 μg/ml) and treated with normal human serum (NHS) or C2-depleted supplemented  supplemented with physiological concentration (25 µg/ml) of C2 variants. The assay is described in detail in .2+ and Mg2+ (DGVB++), incubated 30 min at 37°C with shaking (300 rpm). Then erythrocytes were washed and plated on a V-shaped plate. Cells were overlaid with C2 variants  diluted in physiological concentration (25 µg/ml) in NHS or ΔC2 serum. Cells were pelleted and hemoglobin released to the supernatant was measured at 405 nm in a Synergy H1 microplate reader (Biotek). Cell lysis was calculated as a percentage of full lysis obtained for the supernatant of erythrocytes treated with distilled water.The hemolytic assay was performed on human erythrocytes sensitized with anti-human red blood cells antibodies  diluted 1:50 in dextrose gelatin-veronal buffer supplemented with 1mM CaCP convertase assay was performed on human erythrocytes as for the hemolytic assay. Then cells were overlaid with the mixture of C2-depleted serum mixed with C2 variants  at physiological concentration (25 µg/ml) and compstatin (30 mM) or eculizumab (70 nM). After indicated time period, the reaction was stopped with 40 mM EDTA-GVB buffer. Cells were washed, pelleted, and overlaid with EDTA-GVB buffer containing 1:20 dilution of guinea pig serum (Harlan Laboratories). The readout of hemoglobin release was performed as described above.2+ and Mg2+. The cleavage into C2a and C2b was analyzed by Western blot and SDS-PAGE, as described in (Purified C2 variants were incubated for 0 and 120 minutes with 4 nM C1s enzyme (Complement Technology) diluted in 5 mM veronal buffer supplemented with 1mM Caribed in .For assessing amino frequency occurrence in position in MIDAS region, we used the same methods and sequences data set as it is described in reference . The thrPerformance of cytotoxic assays in C2-depleted serum supplemented with recombinant C2 variants aimed to dissect a phenotype of mutation whereas addition of C2 proteins to NHS that contains wild-type C2, aimed to reveal dominant or recessive character of mutation. Reconstitution of C2-depleted serum with recombinant Q263G variant significantly increases the CDC beyond the level attainable for reconstitution with wild-type C2, whereas the addition of Q263P variant resulted in cell lysis comparable to the readout of C2-depleted serum  are involved in metal ion binding : D260, S262, S264, T337, D376. In all analyzed C2 and factor B sequences, the mentioned residues are universally conserved, which shows the importance of the MIDAS motif for C2 or factor B biological activity. On the other hand, position 263  is occupied by glutamine residue or aspartic acid for C2 and factor B sequences respectively. Analysis of known protein complexes formed by C2/factor B proteins shows, that the side chain of residue 263 is not involved in any protein-protein interaction and is exposed to solvent . Importade novo convertase formation and serve as source of terminal complement components that form membrane attack complexes on the platform of convertases formed in the previous step of the assay.Compared to its alternative pathway paralog, factor B, complement C2 has a much lower physiological concentration, which makes it a bottleneck of the classical complement pathway , 22. TheTo our best knowledge, the mutation p.Q263G in C2 was not identified in patients yet. However, the pathogenic character of the corresponding mutation in factor B, p. D279G, was revealed by Roumenina et al., who identified it in an aHUS patient. The fact, that LoF mutation p.Q263P is present in a patient with C3G, a disease characterized by excessive complement activation in the fluid phase, should be considered an accidental finding not related to the pathomechanism of the disease. Partial deficiencies of C2, which would be equivalent to heterozygous non-functional C2 variants like Q263P, are common in normal populations. In this particular patient, the relevant genetic finding is the CFH A110S variant that determines a partial FH deficiency, which confers a predisposition to C3G . Nonethe2+ ion.As revealed in other studies , 27 and We present the growing evidence that the von Willebrand factor type A domain and unstructured region at its N terminus contain numerous sites crucial for the enzymatic activity of classical convertase. The corresponding gene fragment is therefore a hot spot that can accumulate mutations resulting in either LoF or GoF phenotypes. Our results speak for the necessity of identification and characterization of C2 mutations found in patients, as they potentially contribute to pathogenic conditions characterized by both diminished and excessive complement activation. We also provided an example that substitutions like the one at position 263, which triggers neither substantial structural change nor affects residues engaged in protein-protein interactions, may lead to unobvious phenotypic effects.The original contributions presented in the study are included in the article/Conceptualization of the study: MO, SRdC, AU. Experimental work: AK, MT, DK, AF-M, PS, SO, IJ, AU. Bioinformatics and database search: EA, SRdC. Writing of the manuscript: AK, SRdC, SO, AU, MO. All authors contributed to the article and approved the submitted version.


In both Drosophila and mammals, the achaete-scute (ASC/ASCL) proneural bHLH transcription factors are expressed in the developing central and peripheral nervous systems, where they function during specification and maintenance of the neural stem cells in opposition to Notch signaling. In addition to their role in nervous system development, ASC transcription factors are oncogenic and exhibit chromatin reprogramming activity; however, the impact of ASC on chromatin dynamics during neural stem cell generation remains elusive. Here, we investigate the chromatin changes accompanying neural commitment using an integrative genetics and genomics methodology.We found that ASC factors bind equally strongly to two distinct classes of cis-regulatory elements: open regions remodeled earlier during maternal to zygotic transition by Zelda and less accessible, Zelda-independent regions. Both classes of cis-elements exhibit enhanced chromatin accessibility during neural specification and correlate with transcriptional regulation of genes involved in a variety of biological processes necessary for neuroblast function/homeostasis. We identified an ASC-Notch regulated TF network that includes likely prime regulators of neuroblast function. Using a cohort of ASC target genes, we report that ASC null neuroblasts are defectively specified, remaining initially stalled, unable to divide, and lacking expression of many proneural targets. When mutant neuroblasts eventually start proliferating, they produce compromised progeny. Reporter lines driven by proneural-bound enhancers display ASC dependency, suggesting that the partial neuroblast identity seen in the absence of ASC genes is likely driven by other, proneural-independent, cis-elements. Neuroblast impairment and the late differentiation defects of ASC mutants are corrected by ectodermal induction of individual ASC genes but not by individual members of the TF network downstream of ASC. However, in wild-type embryos, the induction of individual members of this network induces CNS hyperplasia, suggesting that they synergize with the activating function of ASC to consolidate the chromatin dynamics that promote neural specification.We demonstrate that ASC proneural transcription factors are indispensable for the timely initiation of the neural stem cell program at the chromatin level by regulating a large number of enhancers in the vicinity of neural genes. This early chromatin remodeling is crucial for both neuroblast homeostasis as well as future progeny fidelity.The online version contains supplementary material available at 10.1186/s12915-022-01300-8. The Drosophila genome exhibits complex and dynamic developmental chromatin and transcriptional patterns –6. Due tASCLs in both sequence and proneural function , and Asense (Ase), which regulate central (CNS) and peripheral (PNS) nervous system development , 15. Thefunction –21. Althfunction , 23. In function . Examplefunction , prostatfunction , medullafunction , gastroefunction , gliomasfunction –33. Alsofunction  attest tASH genes have duplicated, whereas ase has remained as single-copy. Drosophilids’ three ASH genes, ac, sc, and l(1)sc, exhibit a considerable degree of functional redundancy [ASH genes leads to embryonic lethality, a deletion of ase is viable and fertile, suggesting that its NB expression is dispensable [Within the insects, two ancestral ASC-like proneural factors have been characterized, ASH (Achaete and Scute homolog) and Asense (Ase) , 39. In dundancy , 41. In dundancy , 43. Witdundancy , 45. Thidundancy , 46. Newdundancy , in ASC-dundancy . These Apensable , 49.Here, we have followed up on early seminal genetic work and addressed this biological process from a genomics point of view and present novel insights regarding the chromatin changes that accompany CNS neural stem cell birth in terms of global proneural binding, active histone mark deposition, and transcriptional profiles. Combining these datasets revealed a putative TF-network of proneural target genes, which are likely to comprise the forefront arsenal ensuring neuroblast functionality. Notably, ASC mutant neuroblasts undergo NE to NB transition poorly, remaining in a ‘stalled state’ characterized by a lack of timely expression of many proneural targets and, importantly, without dividing. Eventually, they overcome this arrest but cannot sufficiently sustain stem cell competence, evident by the depleted glia and neuronal population resulting in a highly hypoplastic nerve cord. Therefore, ASH proneurals appear to be largely dispensable for the NB delamination process, but are required for timely initiation of the neural stem cell program.To address the role of the ASH proneural factors, we screened a number of Gal4 lines for embryonic neuroectodermal expression and selected bib-Gal4 to express myc-tagged variants of Sc and L1)sc for genome-wide binding and transcriptome studies. bib-Gal4 is active in the procephalic and ventral neuroectoderm from stage 8 onwards and by stage 16 GFP is detected in the ventral nerve cord (VNC) and the mature epidermis sc Fig. , resultiNext, we evaluated the genomic distribution of the proneural binding consensus events and found high enrichments in 5kb upstream of the TSS regions, and in 5′UTRs  , 11 we iNext, we used the 1983 potential proneural regulated target genes in the Flymine tool  for downwor, dpn, scrt, klu, the temporal genes hb, Kr, nub, and grh [zip, sqh, Rok, and Rho1 [cycE, E2F1, and stg; and members of apico-basal polarity organizing Par complex (baz), Pins complex , the Centrosome organizing center , and the basal compartment  [Next, we extracted from Flybase  genes as and grh ; genes eand Rho1 ; the celt, pros) . Thus, pIn addition, we investigated the expression patterns of the proneural-targeted genes using the BDGP in situ RNA database integrated in the Flymine tool Fig. E. Thus, nvy and wor, two bona fide neuroblast markers [Next, we asked whether proneural activity affects chromatin organization in terms of enhancer remodeling and transcriptional output. For this reason, we generated replicated RNA-seq experiments and H3K27Ac ChIP-seq datasets from staged embryos    between the U-scAPAA and U-NΔE embryos  Fig. F. In add05) Fig. G, as wel05) Fig. H. We fouASC null (Df(1)scB57 or Df(1)260.1) embryos are known to display a drastic reduction of mature neurons, whereas at earlier times they only show a mild reduction in delaminated neuroblasts [roblasts . HoweverA first striking observation was that during the early stages of neurogenesis (embryo stages 8-10 or NB delamination waves S1-3) mutant NBs are stalled. We found that Dpn Fig. A, Wor AC, Scrt E, NerfinASC- NBs, however, accumulated both these markers demonstrating a G2/M arrest, suggesting that after delamination they retained the NE-expressed FUCCI signal since they had not divided yet . In other words, the ASC- GMC profile also seems impaired.Despite this early developmental arrest, starting at late stage 10/early 11, we observed a gradual rebound in NB marker expression, accompanied by the initiation of NB mitoses. By late stage 11, ASC mutant NBs had started expressing Dpn Fig. B, Scrt F, Oli AD. In parASC mutant, although the complement of NB-specific markers is disturbed.Even though ASC mutant NBs displayed a pronounced delay in the onset of their developmental program and GMC generation, their delamination from the ectoderm did not appear to be greatly affected  are stalled in Dpn expression , all above progeny comes from precursors specified at the early S1–S2 waves of neurogenesis. We wondered whether ASC mutants also exhibit defects in neurons/glia born from later NB waves during late st10-11, a time when mutant NB activity has rebounded. eagle-lacZ is a marker of four late NBs and their progeny,  . At stagASC deficiency, if transgenically provided using the neuroectodermal driver bib-Gal4 sc19 ASC deficiency, which deletes ac, sc, and l(1)sc, but spares ase. In this background, NB stalling was still evident during stage 9 scB57. The late CNS hypoplasia was also improved in Df(1)sc19. The population of glia was richer sc scB57 embryos, summarized in Fig. To investigate the transcriptional activity of the proneural bound elements we generated 10 transgenic division , and onel target . Most ofnvy enhancers, exhibited different patterns, nvy-KV14 had CNS and PNS expression sc-B57 mutant, KV23 was never activated scB57 mutant in the ASC-independent sensory organs [atonal and amos, proneural factors exclusive to PNS primordia [Thus, with the sole exception of the y organs , most lirimordia , 93.By mapping ASH binding events during neural stem cell specification, we found a high co-occurrence with accessible regions pre-modeled during MZT, a time when Zelda is crucial for establishing chromatin organization for subsequent tissue-specific transcription , 94. SinASC mutants are mis-specified and cannot overcome functionally the initial stalling. Interestingly, murine Ascl1 depleted neural precursors also exhibit a similar delay [Our work indicates that during NE to NB specification spanning stages 8-11, proneural-mediated chromatin reorganization and transcription is essential for the proper later unfolding of the entire NB lineage. For the first time, we demonstrate that proneurals establish NB homeostasis of all 5 delamination waves, based on our genomic data Fig. B, the phar delay .ASC- background . It is known that the transition from neuroectoderm to NB involves a mutually antagonistic interplay between the proneurals and Notch; however it remains unclear to date if the effect of Notch on the proneural targets is indirect, via Notch repressing ASC proneural expression, or direct on their individual enhancers, which are activated by ASC proneurals. The dominant effect of Notch activation even upon overexpression of a proneural factor [Integration of the proneural binding events with the RNA-seq and H3K27Ac changes during Notch-mediated lateral inhibition revealed a downstream TF network, likely to consolidate the neural cell fate. Some of these had been earlier described as potential proneural target genes, like dpn , scrt [1pn [scrt , ase [48crt [ase , and ner[nerfin1 , 104. Onl target  despite et [scrt , sna, dpl factor  argues iASC deletion  of longitudinal glia (defective GP lineage) and the dMP2/vMP2 segment-spanning interneurons (defective MP2 lineage) could be the underlying cause for the lack of longitudinal tracts that eventually may lead to nerve cord fragmentation.The mature VNC pattern is the outcome of a complex crosstalk of glia and neuron interactions occurring in the CNS, midline  and PNS ASC gene expression has been extinguished. For at least one of these genes, tap, we showed that its protein expression is greatly compromised in ASC mutant GMCs scB7/FM7,KrGal4,UAS-GFP(I); bib-Gal4(III) females were used for the UAS rescue experiments and for the UAS-FUCCI experiment.UAS-CD8-GFP (II); bib-Gal4 (III) homozygous females were crossed to homozygous UAS-6xmyc-scAPAA, UAS-6xmyc-l(1)sc or UAS-NΔecd males for the embryo collections used in ChIP-seq and RNA-seq experiments. The Df(1)sc-B57 and Df(1)scFor the generation of UAS-l(1)sc N-terminally 6xmyc-tagged flies, the l(1)sc coding region was amplified using primers with EcoR1 XhoI restriction sites overhangs  from yw cDNA , using KAPA High Fidelity Polymerase  and subsequently inserted in the entry pENTR™3C vector . We used pTMW (Drosophila Genomics Resource Center #1107) as the destination vector and the Gateway® LR Clonase® II kit  to generate the final l(1)sc-pTMW vector. Subsequently the l(1)sc-pTMW construct was inserted into yw flies via P-element transformation. For the generation of enhancer-lacZ reporter flies we used the pBlueRabbit lacZ vector, which contains an hsp70 minimal promoter upstream of a lacZ reporter gene . Putative proneural bound regions were amplified with the corresponding primers with overhangs for EagI (forward primers) and XbaI (reverse primers)  and fixed for 20 min with vigorous agitation. Embryos were devitellinized by vigorous shaking in methanol for 30–40 s. After 3 quick methanol rinses, samples were stored in methanol at -20 °C. On the day of immunostaining, embryos were rehydrated in PT . Blocking was then conducted for at least 2 h with PBT (PT+ 0.5% BSA). Primary antibodies were diluted in PBT and incubated overnight at 4 °C. The next day, samples were washed extensively in PT. Embryos were incubated with secondary antibodies for 3 h at room temperature. After extensive PT washes, 80 μl n-propyl gallate-glycerol mountant was added to each sample and incubated overnight at 4 °C. Embryos were then mounted and imaged in TCS SP8 confocal microscope system (Leica). Image analysis was performed with the Leica LAS X software. Antibodies used are listed in Additional file We developed a low-input Drosophila embryo ChIP-seq protocol based on . BrieflyEmbryos were collected at 0–2hs and then transferred to mature at 29 °C for 3 h (3-5hs collections). All embryo collections were performed during the same time window, from morning to mid-afternoon, to minimize clock-mediated changes in gene expression, after a 30-min pre-clearing. Embryos were directly transferred in 50 μl TRIzol-containing tubes and stored at − 80. On the day of RNA extraction, embryos were defrosted and homogenized using 1.5 ml manual pestle. For each replicate, 5 independent daily collections were pooled after homogenization and RNA was isolated with phenol/chloroform without columns. RNA-seq libraries construction was performed with the Ion Total RNA-seq Kit v2 (Thermo Fisher), using Poly(A) RNA selection with Dynabeads mRNA DIRECT Micro Kit Ambion (Life Technologies) according to manufacturers’ protocols. Libraries were sequenced on Ion Proton™ System (ThermoFisher) with PI CHIP v3, utilizing for template the Ion PI Hi-Q OT2 200 kit (# A26434) and the Ion PI Hi-Q Sequencing 200 kit .https://www.R-project.org/), Pavis (https://manticore.niehs.nih.gov/pavis2/ Flybase R6.01 assembly) [https://www.flymine.org v51) [https://gbiomed.kuleuven.be [http://flybase.org/cgi-bin/cvreport.pl?cvterm=FBbt:00001369&childdepth=2, FBbt:00001369 (Fly Anatomy) “VNC neuroblast” genes used to generate Fig. https://insitu.fruitfly.org downloads/insitu_annot.csv.gz was used to run the GSEA presented in Fig. Fastq files were transferred from Ion Proton and Illumina Basespace to IMBB servers for storage and analysis. Mapping was performed to dm6 . Software and Algorithms used in this study: SAMtools , MACS2 (ssembly) , Flymineorg v51) , i-cis Teuven.be , UCSC geeuven.be  , (samtools view -q 30). Bedgraphs were generated using bedtools genomecov and uploaded to the UCSC genome browser. Prior to peak calling, we excluded reads from the bam files mapped on repetitive regions. We also excluded reads that fell in our custom “black list regions” (available upon request). Peak calling was performed using macs2 over input (-p 0.05) and peak overlaps were generated with bedtools (intersect -wa), excluding Chromosomes U and Uextra. This resulted in 4129 common peaks between the two biological replicates. In order to derive a more confident proneural consensus, we used the second scAPAA, rep which was stronger, and imposing an FC>2 filter, based on the enrichment score from the macs2 output file of the 2nd rep. This resulted in 2,984 confident proneural consensus peaks, commonly called in both replicates  from two studies , 59 and https://genome.ucsc.edu/index.html and regulation/track:BDTNP DNase Accs/table:S5-14 Regions (bdtnpDnaseAccS5-14) and then used UCSC/LiftOver to convert to dm6. ChIP-seq data for Ac (ENCFF073ETO), Da (ENCFF718YZD), E(spl)m8 (ENCFF074INK) were downloaded from https://epic.gs.washington.edu/modERN/.For the DHS st5-st14 dataset , we downWe downloaded and mapped to dm6 parameters from the following Illumina sequencing datasets: SRR1779551 (Zelda) and its input SRR1779552. NC14 histone marks SRR1505729 H3K27me3), SRR1505714 (H3K27Ac), SRR1505718 (H3K4me1), and SRR1505740 (input). SRR388356 (PolII) and SRR388382 (input). To correct for the difference in fragment size between Ion Torrent and Illumina (75bp) sequencing we processed the IonTorrent datasets as follows: fastq reads were filtered and trimmed using cutadapt -m100 -l100 prior to Hisat2 mapping . We indexed all bam files and used deepTools bamCompare, computeMatrix, plotProfile for Fig. K27me3, SFor the boxplots in Fig. We generated the RPKM count matrix with multiBigwigSummary on the total of 16,512 st. 9 DHS sites  with thehttps://www.gsea-msigdb.org/gsea/index.jsp) was performed using the ranked gene lists from the edgeR output files against the BDGP in situ database terms and genes assigned to proneural peaks or affected DHS sites.Mapping was performed using Hisat2 . Counts were generated from bam files with HTSeq-count (-i gene_id). Differential Expression Analysis was performed with edgeR using batch correction and likelihood ratio tests (glmFit/glmLRT method), since replicates were performed in different time points resulting in large dispersions within groups. Tests were performed on 7862 genes after keeping genes with cpm>3 in at least 3 samples. edgeR output of the U-scAPAA vs. U-NΔE analysis is provided in Additional file Additional file 1: Fig. S1. Embryonic phenotypes of bib-Gal4 driven expression of U-scAPAA and U-NΔE and genomic analyses of proneural binding consensus. Fig. S2. Proneural regulated chromatin effects correlate with transcriptional output. Fig. S3. ASC mutant neuroblasts are initially arrested at G2/M. Fig. S4. GMC expression of proneural targets is impaired in ASC mutants. Fig. S5. A study of several neuroblast markers reveals the presence of delaminated ASC mutant NBs. Fig. S6. Depletion of glia and neuronal populations in ASC mutants result in severe axonal defects. Fig. S7. Asense provides partial neuroblast functionality and CNS development in the absence of ac, sc and l(1)sc. Fig. S8. Neuroectodermal induction of proneural targets enhances neurogenesis at the expense of epidermal fate.Additional file 2: Table S1. Proneural consensus binding sites genomic coordinates and gene annotation. Table S2. Motif analysis and genomic distribution of the Class I and Class II Proneural binding events. Table S3. Flymine Analysis of Proneural Target Genes. Table S4. Differential acetylation analysis of H3K27Ac ChIP-seq signal on stage 9 DHS regions. Table S5. Analysis from U-scAPAA versus U-NΔE embryo RNA-seq profiling. Table S6. Genomic landscape of selected proneural TF targets. Table S7. Genomic characteristics of peaks cloned in lacZ reporter flies.Additional file 3: Supplemental Methods. Fly strains, primers, antibodies, ChIP-seq protocol for low Drosophila embryo number, Ion Torrent Sequencing and Illumina sequencing.


During fasting, hepatocytes produce glucose in response to hormonal signals. Glucagon and glucocorticoids are principal fasting hormones that cooperate in regulating glucose production via gluconeogenesis. However, how these hormone signals are integrated and interpreted to a biological output is unknown. Here, we use genome-wide profiling of gene expression, enhancer dynamics and transcription factor (TF) binding in primary mouse hepatocytes to uncover the mode of cooperation between glucagon and glucocorticoids. We found that compared to a single treatment with each hormone, a dual treatment directs hepatocytes to a pro-gluconeogenic gene program by synergistically inducing gluconeogenic genes. The cooperative mechanism driving synergistic gene expression is based on ‘assisted loading’ whereby a glucagon-activated TF  leads to enhancer activation which facilitates binding of the glucocorticoid receptor (GR) upon glucocorticoid stimulation. Glucagon does not only activate single enhancers but also activates enhancer clusters, thereby assisting the loading of GR also across enhancer units within the cluster. In summary, we show that cells integrate extracellular signals by an enhancer-specific mechanism: one hormone-activated TF activates enhancers, thereby assisting the loading of a TF stimulated by a second hormone, leading to synergistic gene induction and a tailored transcriptional response to fasting.  During fasting, significant hormonal and metabolic changes occur to ensure sufficient energy supply to cells. Insulin levels decrease while glucagon and glucocorticoids levels increase . LipolysGluconeogenesis is potently stimulated by the two fasting hormones glucagon and glucocorticoids. The effects of these hormones on hepatocytes are widespread and are in part mediated via transcriptional regulation . GlucagoWhile other TFs were shown to play a role in regulating gluconeogenic gene expression ,23, CREBEarly studies have shown that co-infusion of glucagon and glucocorticoids leads to above-additive glucose production ,25, suggAs detailed above, the cooperation between glucagon and glucocorticoids is well known. However, there are many open questions which we set out to answer in this study: What is the genome-wide transcriptional effect of glucagon and glucocorticoids on hepatocytes? Do the two hormones cooperate to regulate only a handful of genes or is it a cooperation module broadly affecting the transcriptional response to fasting? Is the crosstalk between the two hormones only cooperative or also antagonistic? What are the determinants of CREB-GR cooperation in terms of enhancer environment, enhancer selectivity, motif strength and TF binding?Glucagon 100 nM , corticosterone 1 μM .Primary hepatocytes were isolated from male, 8–10 weeks-old mice (strain C57BL/6JOlaHsd)Isolation and plating of primary mouse hepatocytes (PMH) was performed as detailed in our published protocol with no modifications . Three hRpl13). The primers indicated ‘nascent’ were designed to amplify nascent transcripts (i.e. the amplified region span exon-intron junctions) as a proxy for transcription and in order to avoid confounding post-transcriptional events. The sequences of primers used in this study are:Total RNA was isolated from primary mouse hepatocytes using NucleoSpin kit (Macherey-Nagel cat# 740955.25) according to the manufacturer's protocol. For qPCR, 1 μg of total RNA was reverse transcribed to generate cDNA (Quantabio cat# 76047–074). qPCR was performed using a C1000 Touch thermal cycler CFX96 instrument (Bio-Rad) using SYBR Green (Quantabio cat# 101414–276). Gene values were normalized with a house keeping gene  - Fwd: AGGATCGGGGTACCAGTTCA, Rev: ATGTGCCGTATATCAGGCGGFh1 (nascent) – Fwd: AGGTGTCGAACTCTACACGGA, Rev: GCTGGTCAGAGTTTGTTTGCTTTFosl2 (nascent) – Fwd: CGTCGAATCCGGAGGGAGA, Rev: GCATAATGTCGACCCATGTCCGpcpd1 (nascent) – Fwd: CCAGCGCTTCTTCCACTCTC, Rev: GACCCACCTTTGACAAGTCCTPpp1r3g (nascent) – Fwd: GGATGCACTTCGCTCGATTG, Rev: ATAGCTTTGATCCACCCCGCMt1 (nascent) – Fwd: CTGCTCCACCGGTAAGACTC, Rev: CAAGCCTCTACAACTCGGGGNr3c1 – Fwd: CTCCCCCTGGTAGAGACGAA, Rev: TTGACTGTAGCTCCACCCCTCreb1 – Fwd: TGTAGTTTGACGCGGTGTGT, Rev: TCCACTCTGCTGGTTGTCTGPMH were treated with hormone combinations for 1 h. Then, cells were cross-linked with 1% formaldehyde  for 10 min at room temperature and quenched with 0.125M glycine. Crosslinked samples were washed in phosphate buffered saline (PBS), resuspended in ChIP lysis buffer  and sonicated  to release 100–1000 bp fragments. Samples were diluted 1:5 with ChIP dilution buffer . Antibodies (4 μl per 2 mL sample) against H3K27ac , or GR  were conjugated to magnetic beads  for 2 h at 4°C. Chromatin was immunoprecipitated with antibody-bead conjugates for 16 h at 4°C. Immunocomplexes were washed sequentially with the following buffers: low-salt buffer , high salt buffer , low salt buffer and TE buffer . Chromatin was de-proteinized with proteinase K  for 2 h at 55°C and de-crosslinked for 12 h at 65°C. DNA was subsequently phenol-chloroform purified and ethanol precipitated.The sequences of primers used in ChIP-PCR are:Unassisted site – Fwd: TCACCCTGTGCCAGGACCAA, Rev: TGGGGAAGGGTGAGCAAGCTAssisted site 1 – Fwd: ATTGCCTGCTGGCGACTAAA, Rev: GGATCCAAGTCCAAGGCACAAssisted site 2 – Fwd: GTGCCGACAAACCTCTACTTG, Rev: AAGAGTGCTACCTGTGACGACFor quality control of RNA yield and library synthesis products, the RNA ScreenTape and D1000 ScreenTape kits (both from Agilent Technologies), Qubit RNA HS Assay kit, and Qubit DNA HS Assay kit (both from Invitrogen) were used for each specific step. mRNA libraries were prepared from 1 μg RNA using the KAPA Stranded mRNA-Seq Kit, with mRNA Capture Beads . ChIP DNA libraries were prepared using the KAPA HyperPrep Kit . The multiplex sample pool (1.6 pM including PhiX 1%) was loaded on NextSeq 500/550 High Output v2 kit (75 cycles) cartridge, and loaded onto the NextSeq 500 System , with 75 cycles and single-read sequencing conditions.To separate nuclear and cytoplasmic fractions, we followed the REAP protocol  with modProtein samples were loaded on 12% polyacrylamide SDS gels. Proteins were transferred  to a nitrocellulose membrane , blocked for 1 hour with 5% low-fat milk, and incubated for 16 h with primary antibody  diluted 1:1000 in solution . Membranes were incubated with secondary peroxidase AffiniPure goat anti-rabbit immunoglobulin G  or anti-mouse  for 1 h, followed by washes and a 1-minute incubation with western blotting detection reagent . Imaging and quantification were done with ChemiDoc (Bio-Rad).6 PFU/mL). After 24 h, hormones were added for downstream experiments. Ad-DN-CREB was kindly provided by Charles Vinson .Three hours after plating, PMH were infected with adenovirus  was used to cluster genes (k = 5).All genes induced in at least one treatment  were included in the analysis. The normalized tag counts of each gene were used for the analysis. Morpheus  was measured in all conditions as compared to the non-treated control. De novo motif enrichment analysis was performed using the findMotifsGenome option in HOMER (parameter -size given). The entire enhancer landscape  was used as background to account for possible sequence bias. When the analysis was repeated with automatically-generated background (which matches GC content) the rank of GRE and CRE did not change. All motifs with p value ≤ 1–10 are shown.Peak-calling was performed by MACS2, sites from both replicates were merged and ENCODE blacklisted sites were omitted. Differential binding was determined by DEseq2 via the HOMER package . Assisted and unassisted definitions - assisted sites were defined as GR binding sites (GRBS) showing an increase  in dual-treated cells compared to corticosterone-treated cells. Unassisted sites were defined as corticosterone-increased GRBS that are not further increased in the dual treatment. De novo motif enrichment analysis was performed using the findMotifsGenome option in HOMER (parameter -size given). All motifs with p value ≤ 1Tag distribution around peak center or transcription start site (aggregate plots) were analyzed using the annotatePeaks option in HOMER (parameters: -size 8000 -hist 10). Tag density (box plots) was analyzed using the annotatePeaks option in HOMER. In GR ChIP and Dnase-seq, tag density of +/- 200 bp around the center was analyzed (parameter: -size 400 -noann). In H3K27ac ChIP, tag density of +/- 500 bp around the center was analyzed to account for the spread signal of H3K27ac (parameter: -size 1000 -noann). In all cases the plotted data is an average of all replicates.Enhancer clusters were analyzed in the vicinity of 91 assisted sites and 91 randomly-selected unassisted sites. Dnase hypersensitive sites that are found in fasted mice ,19 and ahttps://doi.org/10.1101/2021.04.10.438998).The occurrence of GREs and CREs was found using the annottatePeaks option in HOMER (parameter: -size given). HOMER motifs used: cre.motif, gre.motif. Log odds ratio was reduced by 3 to allow near-consensus motif detection . One asterisk denotes statistical significance of p value ≤ 0.05. Two asterisks denote statistical significance of p value ≤ 0.01. Three asterisks denote statistical significance of p value ≤ 0.001. Four asterisks denote statistical significance of p value ≤ 0.001. ‘ns’ denotes statistical significance of p value ≥ 0.05.We aimed to find what is the nature and extent of glucagon and glucocorticoids crosstalk in regulating hepatic gene expression. We treated primary mouse hepatocytes (PMH) with glucagon and corticosterone (the major glucocorticoid found in mice), either alone or in a dual treatment for 3 h and analyzed their transcriptome using RNA-seq Figure . The 3 hk-means clustering on all genes induced in at least one treatment  non-treated control, (b) the glucagon single treatment and (c) the corticosterone single treatment. (d) In addition, for a gene to be defined as synergistic, its increase in expression in the dual treatment must be higher than the sum of increases in the two single treatments combined. Thus, only genes that pass three pairwise comparisons  and show a fold change in the dual treatment that is higher than the sum of the two single treatments were defined as synergistic. Strikingly, even under these strict criteria, 165 genes were found to be synergistically induced by glucagon and corticosterone, showing that synergy is a central crosstalk mode for these two hormones  bound by CREB. The most enriched motif within corticosterone-activated enhancers was the glucocorticoid response element (GRE) bound by GR. The two most highly enriched motifs in dual-activated enhancers were the GRE and CRE . This isDue to the prevalence of both TF motifs within hormone-activated enhancer regions, we hypothesized that the synergy between glucagon and corticosterone is mediated by a synergistic cooperation between CREB and GR within enhancers. We postulated that this cooperation is brought about via assisted loading within enhancers (see Introduction) as this cooperative model was previously shown to promote synergistic gene expression ,32. In aTo examine a possible promoting effect of glucagon on GR binding, we evaluated dynamic GR binding by determining differential binding following hormone treatment using fold change and p value cutoffs as compared to the non-treated control. There were no sites showing increased GR binding following glucagon treatment. This suggests that, as expected (and as shown further below), glucagon does not directly stimulate GR binding. In contrast, 1,035 sites showed increased GR binding following corticosterone treatment, aligning well with known GR biology and with the potent effect corticosterone had on gene expression in PMH Figure . The marThe observation that 636 GRBS are found only in the dual treatment suggests that GR binding is substantially increased in the presence of glucagon, presumably due to assisted loading. To show this effect from a different angle and to substantiate it statistically, we performed a differential GR binding comparison directly between the corticosterone and the dual treatments. We found 91 GRBS in which GR binding was significantly increased in the dual treatment compared to corticosterone alone Figure . TherefoInterestingly, assisted sites do not reach GR binding intensities that are higher than unassisted sites. Rather, only in the presence of glucagon do assisted sites reach comparable levels of unassisted sited Figure . Thus, iFh1) while it did not affect the corticosterone-dependent induction of a known GR target gene (Mt1). In contrast, we found that DN-CREB abolished synergistic gene induction altogether . Nonetheless, to exclude a global effect of glucagon signaling on GR activity, we examined GR mRNA and protein levels as well as GR nuclear localization. We found that the mRNA or protein levels of GR (or CREB) where not increased in the dual treatment compared to single treatments . Also, gTo find the percentage of GRBSs that harbor GRE or CRE motifs, we searched for motif occurrence in assisted vs. unassisted sites. Indeed, the occurrence of the CRE more than tripled in assisted sited compared to unassisted sites. Remarkably, the occurrence of the GRE was reduced in assisted sites Figure . We hypoThe assisted loading model assumes one TF (in this case CREB) facilitates the binding of another TF (in this case GR) by enhancer activation and irrespective of direct TF-TF interaction. According to this assumption and in contrast to TF-TF heterodimerization, the motifs for both TFs could be placed tens or even hundreds of nucleotides apart. To explore this, we isolated assisted sited where both a GRE and a CRE were found and binned them by the distance between the two motifs. We found no preference to a fixed number of nucleotides spacing the two motifs [as is the case in heterodimerization ]. Rathercluster activation. By proxy, assisted loading can occur within an enhancer cluster whereby one TF binds one enhancer unit within the cluster, leading to activation of the enhancer cluster at large. Then, the other TF more easily binds a second enhancer unit within the same cluster. This hypothesis might reconcile an unexpected observation – only 32% of assisted sites harbored both a CRE and a GRE.Various studies in recent years have shown that enhancers often appear in clusters whereby several enhancers (which we term in the rest of the text ‘enhancer units’) flank each other and are concordant in histone modification and chromatin accessibility patterns . EnhanceTo examine this hypothesis, we scanned assisted sites for nearby enhancers, using chromatin accessibility data as an acceptable marker for enhancers . Based oCells are routinely exposed to a myriad of extracellular signals and are constantly responding to them, thereby adapting to a changing environment and maintaining homeostasis. The manner by which extracellular signals are integrated and translated in cells to produce a coherent response is poorly understood. Here, we investigated the hepatic fasting response which is heavily reliant on transcriptional regulation ,23,58. Ta) We observe no glucagon-dependent GR gene induction, increase in GR protein levels or increase in GR nuclear localization. b) The effect of glucagon on GR was highly enhancer-specific. Most GRBS were unaffected by glucagon altogether. This shows that the augmenting effect of glucagon is brought about only at particular enhancers and an effect of glucagon on overall GR activity as previously described could not explain this observation. c) Inhibiting CREB does not affect GR target genes but do abolish synergistic gene induction. d) CREB inhibition does not affect GR binding at unassisted sites but does impair it at assisted sites. e) We observed both a synergistic and an antagonistic crosstalk between glucagon and corticosterone simultaneously. This bifurcated response could not be explained by an overall effect of glucagon on GR. f) We did not find a fixed motif distance between CREs and GREs, making the physical interaction scenario between GR and CREB less likely in our case.Synergy between GR and the cAMP-PKA pathway in regulating gene expression was shown ,60,61. HWe found that the glucagon-CREB axis leads to enhancer activation that assists GR binding near synergistically-induced genes. We have previously shown the reciprocal phenomenon whereby GR assists the loading of CREB in a different set of enhancers . Thus, tThe assisted loading mode of cooperation between TFs is particularly fitted for tailoring a transcriptional response to two or more signals because it is gene-specific and enhancer-specific. Thus, while other modes of cooperation affect all genes regulated by a certain TF, assisted loading leads to synergistic gene induction only on a subset of genes. It appears that GR serve as an extreme example for assisted loading-type of crosstalk with other TFs. GR binding to the genome was shown to be altered by several TFs under different conditions. GR occupancy is increased by C/EBPβ , STAT5 , E47 7171, AP-1 different TF activated by a different hormone. Thus, two different hormonal signals are integrated by two different TFs via assisted loading: glucagon activates CREB and increases enhancer activity of the cluster at large, thereby assisting binding of GR stimulated by corticosterone. Based on these results, it is plausible that glucagon, via CREB, generates an environment conducive to GR binding by increased enhancer cluster acetylation. Cluster-wide histone acetylation was shown to positively affect gene induction via several possible mechanisms  and together regulate gene expression. Enhancer units within the cluster are in close proximity in three-dimensional space and thus constitute a regulatory apparatus promoting transcription. Recent observations suggest that TF binding is controlled by activation of enhancer clusters rather than single enhancers . Moreovechanisms . Our resIn summary, in this study we provide evidence that by employing assisted loading, two signals are integrated to boost a biological response by coordinating enhancer activation, TF binding and synergistic gene expression. This phenomenon is bi-lateral and is dictated by motif strength, serving to optimize gene regulation by enhancers. This integration of signals expands beyond single enhancers and is also at play in enhancer clusters.https://www.ncbi.nlm.nih.gov/geo/) under accession number GSE189271.All RNA-seq and ChIP-seq data have been deposited in the Gene Expression Omnibus (GEO; gkac358_Supplemental_FilesClick here for additional data file.