Caenorhabditis elegans intestinal development. ELT-2 expression initiates in embryos to promote development and then persists after hatching through the larval and adult stages. Though the sites of ELT-2 binding are characterized and the transcriptional changes that result from ELT-2 depletion are known, an intestine-specific transcriptome profile spanning developmental time has been missing. We generated this dataset by performing Fluorescence Activated Cell Sorting on intestine cells at distinct developmental stages. We analyzed this dataset in conjunction with previously conducted ELT-2 studies to evaluate the role of ELT-2 in directing the intestinal gene regulatory network through development. We found that only 33% of intestine-enriched genes in the embryo were direct targets of ELT-2 but that number increased to 75% by the L3 stage. This suggests additional TFs promote intestinal transcription especially in the embryo. Furthermore, only half of ELT-2's direct target genes were dependent on ELT-2 for their proper expression levels, and an equal proportion of those responded to elt-2 depletion with over-expression as with under-expression. That is, ELT-2 can either activate or repress direct target genes. Additionally, we observed that ELT-2 repressed its own promoter, implicating new models for its autoregulation. Together, our results illustrate that ELT-2 impacts roughly 20–50% of intestine-specific genes, that ELT-2 both positively and negatively controls its direct targets, and that the current model of the intestinal regulatory network is incomplete as the factors responsible for directing the expression of many intestinal genes remain unknown.ELT-2 is the major transcription factor (TF) required for  Caenorhabditis elegans intestine is a model for understanding how GRNs contribute to organogenesis , prompting us to question how the intestinal GRN changes over time (Transcription factors (TFs) work together to form gene regulatory networks (GRNs) that direct the expression of target genes . The Caeogenesis . In embrogenesis . ELT-2 pogenesis . A missiC. elegans intestine is well established. The intestine arises clonally from a single cell, the E cell, and ultimately produces a 20-cell-long tube that extends from the animal's pharynx to its rectum. At the 4-cell stage, specification of the endomesoderm occurs when a non-canonical Wnt-signaling pathway responds to positional cues to alleviate endoderm repression orchestrated by SKN-1   followed by RNA-seq. We then combined that dataset with publically available datasets, including ELT-2 DNA binding maps (ChIP-seq) in the same stages, and transcriptional responses to elt-2 deletion, we set out to evaluate three prevailing questions regarding ELT-2 function: (1) Is ELT-2 binding associated with the expression of all intestine genes?, (2) Does ELT-2 function solely as a transcriptional activator? and (3) Does ELT-2 perform positive autoregulation? Using systems biology approaches, we have characterized the complexity of ELT-2's role in intestinal transcriptional regulation. As more ChIP-seq datasets become available through the modERN Resource (model organism Encyclopedia of Regulatory Networks)  was used as a control. See All worm strains were maintained as described  and cultSome strains were provided by the Caenorhabditis Genetics Center, which is funded by NIH Office of Research Infrastructure Programs (P40 OD010440).C. elegans culture is available on the protocols.io platform: dx.doi.org/10.17504/protocols.io.8epv59zjng1b/v2. In brief, C. elegans were cultured on agar-based NGM plates to reduce any confounding effects that may be introduced by large-scale liquid culture. To produce synchronized cultures sufficient for FACS, two rounds of mixed-stage culture growth were performed followed by two rounds of synchronized growth. C. elegans were fed E. coli strain OP50 and maintained at 20°C. Synchronized worm populations were achieved through hypochlorite treatment.A detailed protocol for https://dx.doi.org/10.17504/protocols.io.dm6gpbw9plzp/v1For embryo stage experiments, ∼100,000 synchronized embryos were seeded onto 20 total 150 mm NGM plates at a density of ∼5,000 embryos per plate. Worms were cultured for 72 hours until gravid and harvested for mixed-stage embryos through hypochlorite treatment. Embryo-stage worms were dissociated through Chitinase and Pronase E treatment and mechanical disruption with a 21-gauge syringe needle. A detailed protocol for embryo dissociation is available on the protocols.io platform: E. coli on peptone-enriched NGM plates for six hours before cell dissociation to reduce any observable starvation-induced responses in the measured transcriptional data. L1 stage worms were dissociated through SDS-DTT and Pronase E treatment and mechanical disruption with a Dounce homogenizer. A detailed protocol for L1 dissociation is available on the protocols.io platform: https://dx.doi.org/10.17504/protocols.io.rm7vzy365lx1/v1For L1 stage experiments, mixed-stage embryos were synchronized to the L1 stage by incubating in M9 overnight rotating in a 20°C incubator for 24 hours. L1 worms were then fed OP50 https://dx.doi.org/10.17504/protocols.io.14egn7zwmv5d/v1For L3 stage experiments, synchronized L1 worms were cultured for an additional 48 hours on peptone-enriched NGM plates for 48 hours at 20°C. L3 stage worms were dissociated similarly to L1, where the final centrifugation speed for cell harvest was reduced from 100 rcf to 20 rcf. A detailed protocol for L3 dissociation is available on the protocols.io platform: https://dx.doi.org/10.17504/protocols.io.j8nlkk43dl5r/v1GFP+ intestine cells were isolated from GFP- non-intestine cells by FACS using a BD FACSAria III cell sorter. Additional dyes were used depending on the developmental stage. For embryo stage experiments, viability dye propidium iodide was used to separate live cells (PI-) from dead cells (PI+). For L1 stage experiments, viability dyes were not used because preliminary experiments identified that intestine cells preferentially take up viability dyes confounded sorting (data not shown). For L3 stage experiments, viability dyes are also not used. We observed that L3 stage cell preps have a high degree of debris, so a cell-permeable nucleic acid dye such as DR was used to distinguish cells (DR+) from debris (DR-). FACS plots and post-hoc analysis were performed with FlowJo (v 10) . Cell stApproximately 300,000 GFP+ intestine cells and 1,000,000 GFP- non-intestine cells were collected for RNA isolation for each developmental stage. Three biological replicates for each developmental stage were performed . FACS isTotal RNA extractions were performed with miRNeasy Micro kit (Qiagen 217084). RNA quantity was measured using a Qubit 3.0 fluorometer (Thermo Fisher Q33216) and Qubit High Sensitivity RNA assay kit (Thermo Fisher Q32852). RNA was of a consistently high quality (RIN > 8.0) as determined on an Agilent 2200 TapeStation using high sensitivity RNA reagents (Agilent 5067-5579). Total RNA samples were stored at -80°C until RNA-seq library preparation was performed.https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi? &acc=GSE214581 with Reviewer Token Link: ixuzuasmhlurjit. The gtf alignment files used in this analysis are also deposited there. The raw sequencing files are available at Short Read Archive under Project PRJNA885900.To measure the intestine-specific transcriptome, RNA-seq library preparation was performed with the NEBNext Ultra II RNA Library Prep Kit and sequenced with the Illumina platform (NEB E7770S). Ribosomal RNAs were depleted through the NEBNext Poly(A) mRNA Magnetic Isolation Module (NEB E7490S). All samples were sequenced on the Illumina NovaSeq 6000 instrument except for replicates 1 and 2 for L1 stage samples, which were sequenced on an Illumina HiSeq X-ten instrument. All raw sequencing and processed files are publicly available on NCBI GEO under Accession GSE214581 and accessible at fastp (v 0.20.0)  with hisat2 (v 2.1.0) (featureCounts (v 1.6.4) (Sequencing reads were processed using a custom pipeline on the Rocky Mountain Advanced Computing Consortium Summit Supercomputer . The proDESeq2 package (v 1.28.1) in the R Environment   (deeptools (v 3.5.0) (bamCoverage command using deeptools (v 3.2.0)  . Peaks welt-2 deletion was downloaded from the publication supplemental material (DESeq2 package (v 1.28.1) in the R Environment . . . ComparaTissue-specific genes were generated by downloading gene lists associated with the following anatomy ontology terms from WormBase:WBbt:0005730 WBbt:0005735 (nervous system)WBbt:0005736 (excretory system)WBbt:0005737 (muscular system)WBbt:0005747 (reproductive system)WBbt:0005749 (coelomic system)WBbt:0005772 (intestine)C. elegans TFs was provided in the wTF3.0 TF list . . All scrGO terms for gene sets were evaluated using R package topGO (v 2.44.0) . GO analE. coli feeding strains engineered to produce double-stranded RNA cognate to the elt-2 transcript. RNAi feeding strains were obtained from the Ahringer RNAi feeding library  objective, an Insight SSI 7-Color Solid State Light Engine, and SoftWorx software (Applied Precision) using 1 µm z-stacks. To remove birefringent gut granule autofluorescence, animals were fixed and permeabilized through liquid nitrogen freeze-crack and subsequent washes with methanol, acetone, and PBST. Worms were mounted on microscope slides prepared with 5% agar pads and sealed with Valap.elt-2 promoter experiments, images were collected using a Keyence BZ-X800 fluorescence microscope equipped with a Keyence PLAN APO 40×  objective using 1 µm z-stacks. Worms were paralyzed with 25 mM sodium azide and mounted on microscope slides suspended in M9 and sealed with Valap. Imaging settings were kept constant between RNAi treatments and developmental stages per strain. Multi-panel images were processed and stitched, maximum Z projections were generated, and intestine fluorescence reporter was measured in ImageJ distribution Fiji , with the null hypothesis of a ratio of 1. Confidence intervals are 95% standard error around the ratio of means . Secondary FLAP probes were ordered from Stellaris LGC with dual 5′ and 3′ fluorophore labeling. FLAPY probes were labeled with Cal Fluor 610 and FLAP X probes were labeled with Quasar 670 . All samples were imaged on a DeltaVision Elite inverted microscope described above. Images were processed in the ImageJ distribution Fiji  and non-intestine cell (GFP-) populations . To deteWe were concerned that the process of cell dissociation itself could introduce transcriptional changes due to cell stress or handling. To evaluate the extent of these changes, we determined the transcriptional differences between whole worms and freshly dissociated but unsorted cells . We founact-5, elt-2, ges-1, ifb-2), germline , neuron , muscle , and hypodermis tissues   . In all n = 848) (n = 644), suggesting that gene expression in the embryonic intestine is distinct from larval expression.To identify intestine-expressed transcripts in each of the embryo, L1, and L3 stages, differential expression analysis was performed . In eachn = 848)  indicatiinnate immune response, peroxisome, membrane raft, carbohydrate binding, and glucuronosyltransferase activity. These categories were consistent with known intestinal biological functions. GO terms associated specifically in embryos included DNA-binding TF activity, indicating transcriptional regulatory roles. GO terms associated with the L1 stage included proton-transporting V-type ATPase complex, and terms associated with the L3 stage included defense response to Gram-negative bacterium, suggesting the importance of larval defense. These findings indicate that some tasks are common across all developmental stages whereas others are unique to a given stage.GO analysis identified categories of genes that were shared in all stages of intestine-enriched genes such as acy-4, bre-2, and C02D5.4 were detected as intestine expressed across all stages in our study but were not annotated as intestine-enriched in WormBase  (P < 0.01 (see Methods). We plotted all three datasets as aligned heatmaps, filtering for all protein-coding genes in the genome. Finally, we used the transcriptional response to elt-2 loss (plotted as fold-change ratio and sorted within categories based on this response) to order genes within each category. Genes dependent on ELT-2 for their expression  are shown in green, and genes that are conversely repressed by ELT-2 (they become over-expressed upon elt-2 depletion) are shown in pink.Previous reports have proposed that ELT-2 participates in the transcription of every gene expressed in differentiating and mature intestines . This asRNA-seq) . We diviRNA-seq) . “ELT-2 elt-2 depletion was collected by COPAS sorting whole L1 worms that had either lost or retained an unstable ELT-2::GFP rescue array , suggesting that ELT-2 occupancy does assist in predicting intestine-enriched expression. In the embryo stage, however, only 31%  of intestine-enriched genes were bound by ELT-2, indicating that ELT-2 occupancy alone is insufficient to predict a gene's intestine-enriched status. This percentage increased in L1  and L3  stages  stages , illustrOur findings illustrate that a subset of ELT-2 binding is associated with intestine-enriched gene expression. For this subset, our next question was whether the degree of ELT-2 occupancy could predict the degree of transcriptional output. A simple mechanistic model would predict that TF binding quantitatively influences transcriptional output such that genes with high ELT-2 occupancy would be highly intestine expressed. In contrast, an alternative model could posit that ELT-2 occupancy is independent from the degree of intestine expression.To distinguish between these scenarios, we first plotted intestine RNA-seq counts (regularized and log-transformed) for ELT-2 bound vs not bound genes . For allR2 values ranged from 0.04 to 0.14, indicating low predictive value and suggesting against a scenario where the degree of ELT-2 occupancy informs gene expression level. Stratifying based on ELT-2 regulatory status  vs wildtype conditions  as were negatively regulated .Previous reports have suggested that ELT-2 functions exclusively as an activator of the intestine GRN . To evalnditions . Of the elt-2 depletion albeit at a lower rate (P < 1E-35). These results suggest that the bulk of direct ELT-2 targets are not dependent on ELT-2 for their transcriptional activity. It is possible that other factors or contexts may be required for ELT-2 transcriptional regulation. Additionally, these results demonstrate that ELT-2 functions not only as an activator but also represses distinct sets of target genes.Genes that were not bound by ELT-2, still respond to wer rate . In all Since ELT-2 is intestine expressed throughout development, we wondered how ELT-2's role as an activator or a repressor of downstream target genes varied over time. We observed 13 ELT-2 repressed genes and 2 ELT-2 activated genes distinct to the embryonic stage . Conversreproductive system, nervous system, muscular system, intestine, and epithelial system, and a separate set of ubiquitously expressed genes  and a set repressed by ELT-2 . elt-2 was detected as an activated target due to the nature of the elt-2 deletion allele used in this study. The number of ELT-2 regulated target TFs increased over developmental time. ELT-2 regulation of these TFs may explain the observed ELT-2 transcriptional dependence for genes without evidence of ELT-2 promoter binding , ets-4 (ETS class TF) and pqm-1 (ParaQuat Methylviologen responsive)   . We asse1.2E-18) .P = 3.3E-6) (P = 1.3E-8) (P = 1.4E-8)  . We obse 3.3E-6) . Upon EL 1.3E-8) . In cont 1.4E-8) .pqm-1 transcript abundance increases upon ELT-2 depletion  allele previously used to perform transcriptomics was a complete coding sequence deletion. The use of this allele obscured any transcriptional response of elt-2 to either elt-2 or elt-7 mutations. To determine if elt-2 is also an “elt-7 over-compensated” gene, we measured elt-2 promoter activity in an elt-7 genetic deletion background. We observed that the elt-2 promoter is no longer over-expressed when both ELT-2 and ELT-7 are depleted  mutants with or without elt-7 (elt-2 promoter in elt-2 (-) mutants compared to wildtype ; elt-7 (-) double mutants. These results serve to support the biological significance of our findings in a reporter construct context.We were interested to determine if our results demonstrating ELT-2 negative autoregulation were specific to the reporter construct or if these phenomena could be observed using a complementary method. To do this, we re-analyzed our RNA-seq data and visualized the ut elt-7 . We measwildtype . Additioelt-2 promoter when relieved of ELT-2 repression. Previous transcriptomics work has shown that elt-7 is not over-expressed upon loss of elt-2 at the mRNA level  participate(s) in the intestinal GRN.Together, these results suggest that ELT-2 protein negatively regulates its own promoter in an ELT-7 dependent manner. We suggest that ELT-7 is responsible for over-activating the cription . These fC. elegans larval and adult-stage intestines perform digestion and metabolism characteristic of most animal intestines. However, they also perform additional functions that in other animals are overseen by separate organs such as yolk production, insulin signaling, regulation of developmental aging, immune response, stress response, and detoxification  ELT-2 binding is associated with the expression of all intestine genes, (2) ELT-2 functions solely as a transcriptional activator, and (3) ELT-2 performs positive autoregulation.elt-2 (-) (RNA-seq), and our newly generated intestine transcriptome data to evaluate this hypothesis. We identified that 31% of embryo stage intestine-enriched genes had observable ELT-2 binding in their promoters and that the percent of intestine-enriched genes bound by ELT-2 increased over developmental time to 75% in the L3 stage. This suggests that not all intestine-enriched genes are regulated by ELT-2 but that the intestinal transcriptome becomes more reliant on ELT-2 in later developmental stages. Therefore, our revised model imagines a network of embryonic TFs, including ELT-2, that shape the embryonic intestinal transcriptome but then become reduced at larval stages allowing ELT-2 to play a larger role in those stages.Previous work suggested that ELT-2 is predominantly responsible for intestine gene activation due to a high prevalence of TGATAA sequences in intestine gene promoters and based on the assumption that ELT-2 behaves as an activator  was occurring elsewhere in the worm as a downstream, indirect response. By placing their over-expression phenotypes squarely within the intestinal cells where ELT-2 is present, this result adds greater support to the idea that ELT-2 is intimately associated at a mechanistic level with their repression. cebp-1 and ets-4 are TFs that function in pathogen response with additional roles in neuronal axon regeneration  are all identical, interpreting those experiments will be challenging. A dissection of the ELT-2 protein itself may be fruitful to determine whether it contains separate domains to recruit activating or repressing machinery. However, no such domains are predicted from the sequence. What will be necessary is an investigation into the inter-reliance between ELT-2, ELT-7, and PQM-1—all TFs that bind identical sequences. And it is clear from our work that there are missing components of the intestinal GRN, particularly in the embryo. Overall, how tissue specific GRNs change dynamically over developmental time is poorly understood in any system. But, due to its past foundational work and overall tractability, the iyad088_Supplementary_DataClick here for additional data file.


Congenital heart defects (CHD) are the most common congenital abnormality, with an overall global birth prevalence of 9.41 per 1000 live births. The etiology of CHDs is complex and still poorly understood. Environmental factors account for about 10% of all cases, while the rest are likely explained by a genetic component that is still under intense research. Transcription factors and signaling molecules are promising candidates for studies regarding the genetic burden of CHDs. The present narrative review provides an overview of the current knowledge regarding some of the genetic mechanisms involved in the embryological development of the cardiovascular system. In addition, we reviewed the association between the genetic variation in transcription factors and signaling molecules involved in heart development, including TBX5, GATA4, NKX2-5 and CRELD1, and congenital heart defects, providing insight into the complex pathogenesis of this heterogeneous group of diseases. Further research is needed in order to uncover their downstream targets and the complex network of interactions with non-genetic risk factors for a better molecular–phenotype correlation. Congenital heart defects (CHD) can be defined as structural abnormalities of the heart and/or the great vessels present at birth and are caused by alterations in the normal embryological development of the cardiovascular system. They are a heterogeneous group of diseases. Botto et al. proposed a classification for etiologic studies based on anatomical, clinical and embryological similarity . They diCHDs are the most common congenital abnormality, followed by limb anomalies, congenital anomalies of the kidney and urinary tract and nervous system anomalies . The oveThe etiology of CHDs is complex and still poorly understood. Clearly identified environmental factors (non-genetic risk factors) account for about 10% of CHDs . The mosThe aim of this narrative review is to provide an overview of the current knowledge regarding some of the genetic mechanisms involved in the embryological development of the cardiovascular system. We briefly summarized the embryologic stages of heart development and overviewed the role played by some transcription factors and signaling molecules in this process. We also reviewed their association with congenital heart defects, providing insight into the complex pathogenesis of this heterogeneous group of diseases.Wnt growth factors and enter an environment that promotes cardiomyocyte differentiation, via active Wnt inhibition; the expression of bone morphogenetic protein (BMP) growth factors; and other cardiac-specific transcription factors, such as Nkx2.5 and Islet1 [The heart is one of the first organs to develop in the human embryo. It originates mostly from the mesoderm, with the contribution of ectodermal-derived cells  . The head Islet1 ,14,15,16The closure of the neural tube and the development of the nervous system determines the cranio-caudal and anterior folding of the embryo, which places the heart-forming region in its final position . This prTBX) transcription factor family [The cellular ultrastructure of cardiomyocytes makes all of them capable of contraction (via sarcomeres), spontaneous depolarization and the conduction of the electrical impulses generated (via ion pumps or channels and gap junctions) ,12. Cardr family . The fatr family .Anf/Nppa) and Connexin 40 (Cx40/Gja5), a gap-junction protein [The looping of the heart tube represents a scaffold for the future four-chambered heart. During this process, the cardiac jelly between the endocardium and the myocardium disappears at the outer curvatures so the cardiomyocytes in these regions resume proliferation, along with differentiation, forming the primordia for the future ventricles at the arterial pole and the atrial appendices at the venous pole. This is referred to as the ballooning model . The pro protein ,21. The  protein ,20. The  protein .The secondary myocardium gives rise only to the trabeculated portion of the mature atria. The rest of the atrial myocardium forms via the incorporation of the venous system . The sysThe septation of the heart is a complex process that leads to the development of its closed double circulation characteristic. The process starts with the formation of extracellular matrix cushions in the atrioventricular canal and the outflow tract, which are further populated by endocardium-derived mesenchymal cells .Atrial septation begins with the primary septum, a crescent-shaped structure formed by the proliferation of atrial cells, growing towards the atrioventricular canal and closing the primary atrial foramen (ostium primum) by fusing with the major atrioventricular cushions ,12. To eThe septation of the ventricles starts during the ballooning process with the formation of the muscular septum, by apposition, adding cells at its base from the adjacent growing left ventricular free wall . With thThe outflow tract connects the ventricles to the aortic sac, which in turn is connected to the third, fourth and fifth pairs of pharyngeal arch arteries . The sepTBX5 is a transcription factor from the T-box family with a highly conserved expression pattern in the heart, forelimb and retina in different vertebrate species [ species .TBX5 demonstrates an expression gradient from the venous pole of the heart (the region of the developing atria) to the right ventricle and the outflow tract, where it is absent [TBX5 expression, which include upregulating sarcomere structure genes and genes involved in cellular calcium handling [The T-box transcription factor family plays an important role in regulating the cardiomyocyte identity in the developing heart . TBX5 des absent ,26. Recehandling .TBX5/TBX20 interaction, while the boundary between the TBX5 positive/TBX20 negative cardiomyocytes (specific to the left ventricle) and the TBX5 negative/TBX20 positive myocardium (specific to the right ventricle) appears to indicate the position of the interventricular septum [TBX5 in the second heart field and is regulated by interactions with Sonic Hedgehog (SHH) signaling, with the SHH ligand secreted from the pulmonary endoderm [The transcription factor is involved in the septation of the heart, for both the atria and the ventricles. The location of the ventricular septum depends on the r septum ,29. In aendoderm ,31.TBX5 appears to play a central role in the development of the ventricular conduction system via the specification and regulation of gene expression. It activates the expression pattern for the fast-conducting phenotype characteristic for the ventricular conduction system cells by driving the gene regulatory network, composed of genes such as CX40, SCN5A, RYR2, KCNK3 or KCNJ2, and coding for Na+, K+ and Ca++ channels, both in the developing and the adult heart [TBX5 missense mutation  in relation to early onset atrial fibrillation. The mice showed variable RR intervals and a susceptibility to atrial fibrillation, similarly to patients with the similar mutation. The cardiomyocytes demonstrated decreased systolic and diastolic intracellular calcium concentrations, thus affecting action potentials, probably due to changes in the regulatory element activity and transcriptional regulation (epigenetic changes) induced by the TBX5 mutation, confirming the central role played by the transcription factor in the development of the conduction system [lt heart ,32,33. Vn system .TBX5 signaling. In an experimental model performed on mice, they showed that increasing the maternal leucine levels will increase embryonic lysine-leucylation, thus modifying the lysine residues in TBX5 and inhibiting its transcriptional activity [Zhang et al. demonstrated that increased maternal leucine levels in the first trimester of pregnancy increase the risk for congenital heart defects in the offspring due to the inhibition of activity . This unTBX5 haploinsufficiency has been shown to be the cause of Holt–Oram syndrome (HOS), an autosomal dominant disorder affecting cardiac and upper limb development, with a high penetrance and variable expression [TBX5 mutations are nonsense or frameshift mutations, which result in the introduction of premature stop codons, obtaining a truncated protein with impaired function. Al-Qattan et al. reviewed the genotype–phenotype correlation in typical HOS patients resulting from missense mutations of TBX5, concluding that most of the mutations were found in the DNA-binding domain of the gene, thus affecting the interaction with other transcription factors regulating the embryological development of the heart and limbs (such as GATA4 or NKX2-5) and causing loss of function [pression ,37,38. Tpression . The majfunction .TBX5 gene in relation to heart disease, in addition to the known features of typical HOS, underlining the complex molecular regulation of the developing heart and uncovering new roles for this transcription factor during the embryological period. TBX5 and their phenotype.Recent reports have shown a heterogeneous pattern of genetic variants of the GATA4 is a transcription factor from the GATA family characterized by a highly conserved two zinc fingers domain that binds to the specific DNA sequence 5′-(A/T)GATA(A/G)-3′ in the promoters of target genes [et genes .MYL3) or troponin C (TNNC1) and I (TNNI3), but also genes for Na+/Ca2+-exchanger (SLC8A3), acetylcholine receptor-M2 (CHRM2), cardiac-restricted ankyrine repeat protein (CARP), carnitine palmitoyltransferase-1b (CPT1B), and other transcription factors, such as NKX2-5, which have been shown to be regulated by GATA4 [GATA transcription factors (GATA4/5/6) exhibit redundant functions and interact with each other to ensure the specification of cardiac cells and subsequent heart development [Many cardiac-specific genes possess GATA elements in their regulatory regions, including not only structural sarcomere genes, such as myosin light chain-3  in the endocardial cushions and the growth and remodeling of the atrioventricular cushions, playing an important role in valve development [GATA4 interacts with different cofactors in order to promote cell-type-specific gene expression programs [GATA4 and RERE (arginine-glutamic acid dipeptide repeats gene), a cardiac-expressed nuclear receptor co-regulator, in the development of the membranous portion of the ventricular septum, via their effects on EMT and mesenchymal cell proliferation [GATA4 and FOG2/ZFPM2 gene mutations have shown a disturbance in the normal interaction between the two transcription factors, leading to similar phenotypes , suggesting that the gene pair has an important role in the development of the outflow tract [GATA4 is involved in the localization of the atrioventricular canal by activating enhancers that lead to H3K27 acetylation, thus activating atrioventricular canal-specific gene loci. This is in contrast to its role in the chamber myocardium, where it determines deacetylation and gene repression [GATA4 haploinsufficiency determined an impaired migration of Hedgehog-responsive progenitor cells from the second heart field in the outflow tract, causing CHDs [GATA4, in association with NKX2-5, promotes the maturation of differentiated cardiomyocytes after the migration [elopment . Furtherprograms . For exaferation . Functioow tract ,60. In apression ,62. In aing CHDs . Furtherigration .GATA4 is upregulated by mechanical and neurohumoral stimuli, such as increased hemodynamic load, direct wall stretching, angiotensin II, and endothelin-1, thus activating hypertrophy-associated gene promoters [The transcription factor plays an important role in the adult heart as well by promoting the compensatory mechanisms determined by different types of acquired cardiovascular diseases, such as hypertrophy and angiogenesis. romoters ,65.GATA4 mutations are associated with congenital heart defects. Many NKX2-5 is part of the NK-2 homeodomain-containing family, which is related to the Drosophila tinman protein  and highly conserved in many different species, from flies to zebrafish and humans [The transcription factor d humans ,75,76,77d humans ,75.NKX2-5 is expressed in the mesodermal cells of the first heart field, as well as the second heart field and the endoderm underlying it, indicating a central role in the transcriptional regulation of the developing heart due to its expression in progenitor cells [NKX2-5 is essential for heart development, with a heart phenotype similar to that of NKX2-5 knock-out mice in the mesodermal deletion group, while the endodermal expression has very little influence on the normal development of the heart [During the embryologic period, or cells ,76. TissNKX2-5 expression is essential for the maintenance of the ventricular identity of cells during cardiomyocyte differentiation and acts in a dose-dependent manner in preserving the chamber-specific molecular features during atrial and ventricular formation [NKX2-5 plays a specific role in the development of the outflow tract and the right ventricle [NKX2-5 in the outflow tract wall, thus promoting the progressive maturation of the differentiated cardiomyocytes at this level [George et al. revealed that ormation . In addientricle ,77. Immuis level .NKX2-5 appears to be involved in the development of the conduction system by influencing the number of specific myocytes in a dose-dependent manner, with little effect on the transcriptional regulation of gap junction proteins [SCN5A, CACNA1C and KCNH2, thus linking the gene with conduction disturbances [NKX2-5 is required for maintaining the physiological function of the sinoatrial node, with sinus node dysfunction as a result of the downregulation of the transcription factor, although it is not essential for the morphological development of the structure [proteins . Moreoveurbances . Li et atructure .NKX2-5 and MEF2C for ventricular chamber formation by influencing ventricular cardiomyocyte specification [NKX2-5 is regulated by BMP signaling via SMAD4, which controls not only the expression but also the nuclear localization of the transcription factor [Various transcription factors and other regulatory elements interact with one another in order to mediate the normal development of the heart. For example, Vincentz et al. identified a direct interaction between fication . Cardiomn factor .NKX2-5 via its interactions with IGFBP5 [NKX2-5 and CHD [Environmental factors can determine a CHD, but, for the majority of them, the exact molecular mechanism is not yet fully understood. Lai et al. proposed a mechanism for the association between hyperhomocysteinemia and the development of heart malformations by the downregulation of h IGFBP5 . Further and CHD .NKX2-5 is one of the most studied genes in relation to heart disease. It appears to be a hypermutable locus, with an estimation that from 2 to 4% of all CHDs can be explained by mutations in the transcription factor, with the majority of them involving the outflow tract and the septal region [l region ,86. TablCRELD1) gene encodes for a protein that acts as a cell adhesion and signaling molecule, is highly conserved between species, ranging from C. elegans to Homo sapiens, and is expressed both during embryogenesis and adult life in a number of different tissues, but mainly the developing heart, limb buds, branchial arches and brain [The Cysteine-Rich with EGF-Like Domains 1 , in both isolated and syndromic patients, with an additional risk in Down syndrome patients, possibly due to the particular genetic background of trisomy 21 [CRELD1 mutations described so far.isomy 21 ,99. It wisomy 21 . Table 6VEGF) family is essential for angiogenesis, and the pathway involving these signaling molecules is also a key regulator of heart morphogenesis [VEGFA plays an important role in the early stages of heart development, influencing the formation of the heart tube, and its overexpression can lead to impaired heart tube elongation and looping [VEGFA may lead to atrioventricular septal defects and dysplastic atrioventricular valves [VEGFA, such as c.-2578C>A, c.+963C>T, c.-634C>G, c.-1154G>A and c.-460T>C, were associated with an increased risk of developing CHDs, especially for tetralogy of Fallot and ventricular septal defects [VEGF signaling pathway, due to haploinsufficiency of VEGF receptors, also contribute to the pathogenesis of tetralogy of Fallot [The vascular endothelial growth factor  signaling pathway is involved in the differentiation of the cardiac mesoderm as it regulates the expression of NKX2-5 transcription factor [BMP4 in the remodeling and expansion of the endocardial cushions; it is required for the normal septation of the outflow tract and the development of the semilunar valves [BMP4 and TBX1 and by VEGFA [BMP4 and CHDs in human populations is still being researched. The association between the single nucleotide polymorphism rs762642 and both atrial and ventricular septal defects was demonstrated in a Chinese population [The bone morphogenetic protein  were associated with the development of tetralogy of Fallot by causing functional changes that alter the transcriptional activity of the promoter, downregulating the transcription factor and its downstream effectors [TBX20, another transcription factor involved in heart development [or cells . The genffectors . Additioffectors . Furtherelopment .As previously stated, CHDs are a heterogeneous group of disorders with complex underlying pathologic mechanisms. In one study, it was estimated that over 400 genes are likely to be involved in their etiology . In addiUnderstanding new concepts regarding heart development has led to a paradigm shift in the pathogenesis of CHDs, from the multifactorial inheritance hypothesis to the “one heart disease—several mechanisms—several genes” hypothesis. It states that having a heart disease may be caused by errors in several embryological mechanisms in a developmental sequence, each of which are orchestrated by a specific set of genes, similarly to the “off targets” model from cancer research ,120. ThiTranscription factors and signaling molecules are promising candidates for studies regarding the genetic burden of CHD. Although many of the pathogenetic mechanisms surrounding heart development have been described, further research is needed in order to uncover their downstream targets and the complex network of interactions with non-genetic risk factors for a better molecular–phenotype correlation.


Escherichiacoli can lead to context-dependent effects due todifferent affinities in the formation of CRISPRa and CRISPRi complexes,resulting in loss of predictable behavior. We show that this effectcan be avoided by using the same scaffold guide RNA structure forboth complexes.Gene expression control based on clustered regularlyinterspacedshort palindromic repeats (CRISPR) has emerged as a powerful approachfor constructing synthetic gene circuits. While the use of CRISPRinterference (CRISPRi) is already well-established in prokaryoticcircuits, CRISPR activation (CRISPRa) is less mature, and a combinationof the two in the same circuits is only just emerging. Here, we reportthat combining CRISPRi with SoxS-based CRISPRa in  While most synthetic circuits builtso far have made use of protein transcription factors to regulategene expression, clustered regularly interspaced short palindromicrepeats (CRISPR)-based genetic regulation has the potential to addressmany of the current limitations.12 Theadvantages of CRISPR-based gene regulation tools compared to circuitsbased on protein transcription factors include decreased cross-talkbetween parts due to highly specific RNA–DNA interactions,reduced metabolic burden coming from protein production, and straightforwarddesign of a virtually unlimited number of orthogonal versions.12Synthetic biologists are building syntheticgene regulatory networks(GRNs) to decipher nature’s design principles13 and CRISPR activation (CRISPRa).15 In bacteria,the repression system uses a single guide RNA (sgRNA), which is composedof a target-specific sequence and a sequence that recruits a catalyticallyinactive version of Cas9 (dCas9). The complex is targeted to a promoteror a coding sequence to inhibit transcription. In contrast, for CRISPRa,dCas9 is targeted upstream of the promoter, and it requires, in addition,an activator protein to recruit the RNA polymerase.15 In prokaryotes, the activator protein can be directly fused to dCas9,21 or alternatively, the sgRNA can be extended with a protein-recruitingRNA scaffold that recruits the transcriptional activator.26 Probably the best characterized bacterial CRISPRa system is basedon a so-called scaffold RNA (scRNA), where the sgRNA is modified toinclude a 3′ MS2 hairpin. This hairpin recruits the MS2 coatprotein (MCP) that is fused to the transcriptional activator SoxS.25The strategies for transcriptional regulationbased on CRISPR areknown as CRISPR interference (CRISPRi)27 Extendingsuch circuits with CRISPRa has the potential to further increase thecomplexity of synthetic gene regulation programs. Here, we show thata combination of CRISPRi with CRISPRa based on scRNA and SoxS canlead to strong context-dependent effects. Specifically, the strengthof activation mediated by scRNA was strongly influenced by the concurrentexpression of an sgRNA. We hypothesized that this phenomenon was causedby sgRNA and scRNA competing for the limited pool of dCas9 and bytheir differential affinities to dCas9. This hypothesis was supportedby a mathematical model. The model also suggested ways to circumventthis problem. We then experimentally reduced this context-dependenteffect by using scRNAs for both repression and activation, thus improvingthe predictability of synthetic CRISPRa/i circuits.We recently showed that CRISPRi can be used to build dynamicandmultistable synthetic circuits.28 which we had employed to construct multistableand dynamic CRISPRi-based circuits.27 OurCRISPRi system is composed of two plasmids. The first plasmid (colAori) harbors the designed circuit with up to three nodes, one of whichis arabinose-inducible via a pBAD promoter. From the second plasmid(CDF ori), we constitutively express dCas9 and Csy4. We use Csy4 RNase-processingto release parts that are transcribed together in the same operonto act independently once transcribed, such as sgRNAs/scRNAs for CRISPRi/aand mRNAs encoding a fluorescent reporter.We implemented CRISPRa using ourpreviously developed plasmid architecture and cloning strategy,22 We started with a two-node circuit (23 guiding dCas9 andMCP-SoxS to bind and subsequently activate the second node containinga weak promoter (J23117) upstream of a green fluorescent protein (GFP)reporter. As CRISPRa is very sensitive to the distance between thetarget site and the transcriptional start site (TSS), we used a previouslyemployed sequence ranging from the target site to the TSS (J306 andJ3 region).22 We confirmed that the previouslyreported −81 bp distance upstream of the TSS leads to highactivation .For CRISPRa, we addeda third plasmid (pBR322 ori) constitutively expressing (promoter J23119)MCP-SoxS (carrying mutations R93A+S101A). circuit 1A, with 30 to the scRNA scaffold and replaced the sequence 81 nt upstream ofthe TSS with the corresponding binding sites. Four  out of the six tested constructs resulted in at least 2-foldactivation, namely, 2.1–6.1-fold, compared to the noninducedconstruct and 2.5–23.7-fold activation compared to the off-targetcontrol . Together with theoriginal scRNA (number 0), we tested their orthogonality . We attribute this to the previously reported leakiness of ourpBAD promoter.27Once we had successfully integrated CRISPRa intoour framework,we created an orthogonal library of scRNAs 1A. We adcontrol S2. TogetNext, we combined CRISPRaand CRISPRi in the same circuit. We added a third node to our activationcircuit, which in the presence of AHL produces a sgRNA complementaryto a binding site placed downstream of the promoter repressing theexpression of GFP in the second node 1B. We ex31 describing the transcriptionof scRNA and sgRNAs, the formation of the CRISPRa and CRISPRi complexes,their binding to DNA, and subsequent transcriptional activation orrepression, respectively  and binding of the complexesto DNA   and when we have some leaky expressionof sg/scRNAs  2B–E. We g/scRNAs 2E. This ki,j)  are less importantbecause dCas9-sgRNA and dCas9-scRNA-MCP-SoxS complexes do not bindto the same binding sites. However, when the complex formation ratesare unequal (kj > > > ki), a very strong binding of the inhibiting CRISPRicomplex qj compared tothe activatingCRISPRa complex qi leadsto an absence of activation in the on-target circuit  2B,C. The circuit 2E, whilebehavior2D.Figure S3). Increasing theamount of MCP-SoxS helps to increase the activation level but comesat the price of increased leaky activation in the absence of the inducer(arabinose). Increasing the amount of dCas9 allows the correct behaviorof the off-target control but not of the on-target circuit. We hypothesizethat the dCas9 increase does not rescue the behavior because of thegenetic configuration and the use of slightly leaky promoters. Thebinding site for inhibition is downstream of the activation bindingsite. Thus, if both CRISPRa and CRISPRi complexes are bound, thentranscription is repressed. The leaky expression of sgRNA and a highconcentration of dCas9 are sufficient to inhibit transcription evenin the absence of AHL inducer. Therefore, increasing the total amountof dCas9 is not predicted to recover the correct behavior of our circuits.Anyway, high expression levels of dCas9 are known to be toxic to Escherichia coli cells,32 and MCP-SoxS expression was already maximized with a strong promoteron a high-copy plasmid. Therefore, equalizing the complex formationrates promised to be the most promising approach.We also investigated the influence of dCas9 and MCP-SoxS quantitiesin our model . Truncated sgRNAs-dCas9 complexes display weaker repression thantheir full-length counterparts,13 but theDNA binding of the CRISPR complex is similar as with a full-lengthsgRNA.34 We observed the correct behavior for theoff-target control but still almost no activation when combined withthe on-site repression . Thisbehavior can be reproduced in our model when sgRNAt4 binds weakerto dCas9 than sgRNA but still stronger than scRNA while DNA bindingaffinities of sgRNAt4 and sgRNA are similar .We thus set out to test the model predictions and attempted tomake the complex formation rates similar for CRISPRa and CRISPRi.We first tested whether truncating the sgRNA by 4 bp (sgRNAt4) wouldlead to the desired behavior . We thus rebuilt the circuits in Next, we used scRNA instead of sgRNA also for theinhibition complex. As observed for other CRISPRa systems,tivation S5. We thtivation S5. We thFigure S6). We thus demonstrated thatCRISPRa and CRISPRi can be successfully combined, but special attentionhas to be paid to different affinities in RNA-dCas9 complex formationand DNA binding.Encouraged by the predictable behaviorwhen scRNA was used for both CRISPRa and CRISPRi complexes, we proceededto combine CRISPRa and CRISPRi in a cascade circuit. Here, the firstnode is induced by arabinose, and it represses the second node (containinga mKate reporter) that activates the third node encoding a GFP reporter4A. This 22 into our framework.35 When we combined CRISPRa withCRISPRi, we observed a strong affinity competition for dCas9, leadingto weak activation in on-target circuits and an incorrect circuitfunction of the off-target controls. This can lead to an undesirablecoupling among circuit branches that theoretically should act orthogonal.Guided by mathematical modeling, we managed to avoid this problemand obtained the circuits’ correct function by using the sameRNA  for CRISPRa and CRISPRi resulting in the same complexaffinities for activation and inhibition.In this work, we successfully implementedthe SoxS-based CRISPRasystem first described by Fontana et al.36 Moreover, it has also been shown that expressing simultaneouslymultiple sgRNAs that compete for the same limited pool of dCas9 canlead to unwanted outcomes.37 Here, we describe yetanother problem related to dCas9 resource competition when combiningCRISPRi (using sgRNA) and CRISPRa (using scRNA) in one bacterial cell.The different guide RNAs have different affinities for dCas9, andthus, competition hampers the correct network function. Previous workby Tickman and colleagues combined CRISPRi and CRISPRa in differentcircuits such as cascades and incoherent feed-forward circuits incell-free extract and in E. coli.24 However, they did not report a resource competitionbetween the two systems. It might be that they had conditions withvery tight sgRNA production and high dCas9 concentrations where competitionwas minimized.Competition for transcriptionaland translational resources isa well-known issue in engineering synthetic circuits.43 In these systems, the competition between CRISPRa and CRISPRi pathswas not observed, as they either used orthogonal Cas proteins40 or scRNAs for CRISPRa and CRISPRi as both functions require regulatordomains.43While building synthetic circuits with CRISPRiand CRISPRa is rathernew in prokaryotes, the combination of CRISPRa and CRISPRi has beenused to control host genes in yeast and mammalian cells.E. coli by using the samecomplex for both CRISPRaand CRISPRi. Depending on whether we place its binding site upstreamor downstream of the promoter, we observe activation or repression,respectively. This is akin to how some protein transcription factors,such as LuxR, have been used as activators and repressors.44 An alternative approach could be to design anew guide RNA with a similar dCas9 affinity as the scRNA, but withoutbinding MCP-SoxS. This would reduce the required expression levelof MCP-SoxS. To further reduce the metabolic burden on the cells,one could express dCas9 and the MCP-SoxS from the genome. This wouldreduce the number of plasmids used and free resources to maintainthem. However, this would require readjusting the strengths of promotersand/or ribosomal binding sites to get a sufficiently high level ofexpression.Here, we present a simple solution to the encounteredproblem in Figure S3). This is due to the leaky production of sgRNA andthe dominant effect of repression over activation caused by the circuitarchitecture. While increasing the concentration of dCas9 may helpin other cases of dCas9 competition, overproduction of dCas9 can leadto toxicity, reduced growth rates, and morphological defects.37 Reported solutions to address this problem include the use of anontoxic variant of dCas937 and regulatedproduction of dCas9 adapting to the current circuit load.45 For future work, it would be interesting totest some of these approaches in CRISPRa/i circuits. Moreover, tofurther increase the complexity of functions that can be programmed,it would be exciting to combine these circuits with guide RNAs thatcan be controlled by small molecules46 orRNAs.47 We hope our work paves the wayfor building more complex bacterial CRISPRa/i circuits and their applicationsfor studying the function of native genes, cellular reprogramming,and metabolic engineering.50Our model suggests that simply increasing the dCas9pool cannotrestore the correct function in our circuits (28 The different parts containprefix (CAGCCTGCGGTCCGG) and suffix (TCGCTGGGACGCCCG) sequences,51 which can be PCR-amplified  with a set of primers (ordered from Microsynthor Sigma-Aldrich) to add a unique variable linker. Backbones werelinearized with PCR or with restriction enzymes .PCR-amplified or digested products were purified . Then, the parts were assembled with Gibsonassembly  with the linkers providing sequence overlaps. Finally,1 μL of the assembly mixes were transformed into competent cells(NEB5α cell) by electroporation and plated on LB agar platecontaining appropriate antibiotics . The obtained plasmids weresequenced (Microsynth) to confirm that they contained the correctconstructs. A list of all plasmids and complete plasmid sequencesis provided as Supporting Information.Circuits were built as previouslydescribed.E. coli cells.52 Single colonies were incubated in 200 μLof EZ medium with 0.4% glycerol as carbon source (Teknova) with appropriateantibiotics  at 37 °C, 200 rpm, for 4–5h. Then, cells were diluted to 0.05 OD600 in a 96-wellCytoOne plate (Starlab) with or without inducers, as indicated inthe figures. Plates were incubated at 37 °C with double-orbitalshaking .Fluorescence was determined after 16 h with 479 nm excitation and520 nm emission for GFP and 588 nm excitation and 633 nm emissionfor mKate2. We subtracted a blank (medium only) from all fluorescenceand absorbance values, and the resulting cellular fluorescence valueswere divided by the absorbance at 600 nm of the same sample to correctfor differences in bacterial concentration. After that, the bacterialautofluorescence of a control with nonfluorescent cells (3 replicates)was subtracted. In particular, we used the following formula: (GFP– blankGFP)/(OD – blankOD) - mean((autofluoGFP –blankGFP)/(autofluoOD – blankOD)). Subsequent data were analyzed and visualized with R.Plasmids were cotransformedinto Mk01 53 QSSA laws state that the concentration of enzyme–substratecomplexes remains almost constant, and the rate of change of saidenzyme–substrate complexes is extremely small.54 This approximation enables us to not go into the detailsof forward and backward reactions in complex formations and figureout their steady-state concentrations by using mass action law kinetics.Moreover, we assume that the binding of sgRNA/scRNA in inhibitingand activating edges is independent of each other. The model is explainedbelow, where the set of equations with subscript i refers to activation due to arabinose, and j refersto inhibition due to AHL. The parameters used are explained in https://github.com/SchaerliLab/CRISPRa-i-circuitsThe model is based on mass action law kineticsand quasi-steady-state approximations (QSSA) accounting for variousmolecular steps and constraints such as copy number of plasmids andsteady-state protein levels. Mass action law kinetics states thatrates of reactions are dependent on the concentrations of the reactants.RNA).Rate of change of scRNA and sgRNA from arabinose andAHL induction,respectivelyFormationof CRISPRa and CRISPRi complexes (lacking DNA bindingsites)Formation of CRISPRa and CRISPRi complexes with DNA binding sitesDitotal and Djtotal). Some ofthese sites are free of any transcriptional complex (Di and Dj), while others are sites of transcriptional repressionor activation (Ci and Cj). After transcriptional complexconcentrations were inserted from Constraints on DNA binding sitesRate of production of GFP from activationdue to CRISPRa, leakyexpression, and first-order RNA degradationCi), and thereis no inhibition due to CRISPRi (complex Dj). In our model, we implement this using principlesof conditional probability and obtain the net number of such sitesas Ki) to captureleaky expression in our model. We assume that any presence of theCRISPRi complex will lead to a complete block of transcription. Itis important to note that the values of Ditotal and Djtotal are the same in our system, as bothour sites are present on the same plasmid.In our experimental system, we wouldexpect the maximum productionof GFP when CRISPRa is causing proper activation of the promoter  and sgRNA(j), ci is the concentration of scRNA,dCas9, and MCP-SoxS complex, cj is the concentration of the sgRNA and dCas9 complex, Ci,j is theactivation or inhibition complex bound to DNA, Di,j is the amount of freeDNA binding sites, d is the concentration of freedCas9, and m is the concentration of free MCP-SoxS.The descriptions and values of the different parameters are summarizedin In the equations above,


However, the functional significances of IREs in mammals remain elusive. Moreover, whether the transcriptional responses elicited by IREs upon injury are conserved or specialized in different species, and what sequence features may underlie the functional variations of IREs have not been elucidated.Injury induces profound transcriptional remodeling events, which could lead to only wound healing, partial tissue repair, or perfect regeneration in different species. Injury-responsive enhancers (IREs) are We identified a set of IREs that are activated in both regenerative and non-regenerative neonatal mouse hearts upon myocardial ischemia-induced damage by integrative epigenomic and transcriptomic analyses. Motif enrichment analysis showed that AP-1 and ETS transcription factor binding motifs are significantly enriched in both zebrafish and mouse IREs. However, the IRE-associated genes vary considerably between the two species. We further found that the IRE-related sequences in zebrafish and mice diverge greatly, with the loss of IRE inducibility accompanied by a reduction in AP-1 and ETS motif frequencies. The functional turnover of IREs between zebrafish and mice is correlated with changes in transcriptional responses of the IRE-associated genes upon injury. Using mouse cardiomyocytes as a model, we demonstrated that the reduction in AP-1 or ETS motif frequency attenuates the activation of IREs in response to hypoxia-induced damage.By performing comparative genomics analyses on IREs, we demonstrated that inter-species variations in AP-1 and ETS motifs may play an important role in defining the functions of enhancers during injury response. Our findings provide important insights for understanding the molecular mechanisms of transcriptional remodeling in response to injury across species.The online version contains supplementary material available at 10.1186/s12864-023-09283-8. Proper responses to the injury caused by a variety of potentially deleterious factors, which minimize the tissue damage and promote the healing processes, are essential for living organisms to survive and thrive. The heart is one of the most vital organs of the body, and heart disease is the leading cause of mortality worldwide . In respcis by recruiting transcription factors and coactivators [lepb locus, named LEN, is required for the dramatic increase in the expression level of lepb and the effective regeneration of zebrafish fins and hearts [Drosophila, thousands of enhancers are identified during the recovery process of wing imaginal discs, and some of these elements have been validated as bona fide regeneration enhancers [Induction of cell proliferation and cell fate transitions upon injury requires precise regulation and remodeling of gene expression programs. Previous studies have revealed the critical roles of transcription factors, epigenetic regulators and transcriptional enhancers in injury responses , 6. Enhativators . Enhanced hearts . In Drosnhancers . Importanhancers .The mammalian heart exhibits a progressive decline in regenerative abilities after birth. Neonatal mice on the day of birth (P1) can regenerate cardiac tissues efficiently after injury, but this regenerative response is lost at postnatal day 7 (P8) . In lineHere, we address these questions by employing a comparative genomic approach. We compared the epigenome and transcriptome changes of P1 and P8 mouse hearts in response to myocardial ischemia-induced injury, and found that the same IREs activated in regenerative P1 mouse hearts are also induced in non-regenerative P8 heart tissues. By comparing the mouse cardiac IREs versus the IREs activated during zebrafish heart regeneration, we showed that AP-1 and ETS transcription factor binding motifs are highly enriched in IREs for both species. However, the genes associated with IREs vary considerably between zebrafish and mice. Cross-species comparison between IREs and their orthologous sequences reveals that the turnover of IREs is accompanied by alterations in AP-1 and ETS binding motif frequencies. For zebrafish and mice, the IREs specific to one species harbor relatively higher frequencies of AP-1 or ETS motifs than their non-injury-responsive orthologous sequences in the other species. Using mouse cardiomyocytes as a model, we showed that sufficient AP-1 or ETS motifs are indeed required for the effective activation of IREs upon hypoxia-induced damage. Together, our results suggest that shuffling of AP-1 and ETS binding motifs within IREs during evolution leads to diverse transcriptional changes in response to similar injury signals, which may contribute to the differential regeneration abilities in different organisms.To investigate enhancer dynamics during tissue injury and regeneration in mammals, we first analyzed previously published H3K27ac ChIP-seq data of neonatal mouse hearts subjected to permanent ligation of the left anterior descending (LAD) artery or sham surgery at P1 . By compcis-regulatory element) annotations derived from ENCODE [To better understand the nature of IREs, we classified the states of enhancers in uninjured P1 mouse hearts based on their H3K4me1, H3K27ac, and H3K27me3 levels , 16, andm ENCODE , we furtCtss, which can function as a regulator in antigen processing and T cell-mediated immune responses [Ctss expression level  [Cxcl1   [Notably, we found that the extent of IRE activation, which was indicated by the fold changes of H3K27ac signals, was markedly higher in P1 than in P8 mouse hearts  , the imm46 fold) , that fuCompared to mice, zebrafish retain a robust ability of heart regeneration upon injury throughout their lifespan . Previoup-value < 1 × 10–10), we found that AP-1 and ETS families of transcription factors binding motifs were preferentially enriched in IREs for both zebrafish and mouse heart  and their mouse orthologs  exhibited transcriptional upregulation following cardiac injury in zebrafish and mice, respectively  to compare the sequence composition of zebrafish and mouse cardiac IREs. By using a relatively stringent cutoff  data of cardiac tissues in zebrafish  and miceTo examine the epigenome signatures of IREs in the cell types mentioned above, we analyzed mouse histone modification ChIP-seq data (zebrafish-related data are not available) that are currently available in the Cistrome Data Browser . We founThe differences in IRE-gene regulatory networks between zebrafish and mice can be partly attributed to the loss or gain of genes during evolution. Among the 559 zebrafish IRE-associated genes, 376 (67.3%) have orthologs in mice Fig. S and KEGGWe then took a closer examination of the most enriched biological functions for IRE-associated genes in zebrafish and mice. Among the ten most significantly enriched GO terms in zebrafish, seven are also significantly enriched in mouse IRE-associated genes , including “cell activation”, “positive regulation of cell death”, and “positive regulation of locomotion” Fig. C. HoweveNext, we checked IRE-gene regulatory relationship for the genes that have orthologs in both zebrafish and mice and are associated with the IREs in at least one species. For the 376 mouse orthologs of the zebrafish IRE-associated genes, only 10.1% are associated with mouse cardiac IREs Fig. SA, left. We further assessed how the species-specific association with IREs influences injury-induced gene expression. We found that the 338 genes only associated with IREs in zebrafish exhibited increased gene expression as well as promoter H3K27ac signals only in zebrafish, but not in mice Fig. B. Thus, Unexpectedly, the 423 genes that are associated with IREs only in mice exhibited comparable transcription upregulation upon cardiac injury in zebrafish despite the lack of association with the IREs Fig. , and KEGOur findings together paint a picture that while the emergence of mouse-specific IREs does not necessarily increase the induction of their associated genes upon injury, the loss of zebrafish-specific IREs in mice may abrogate the activation of genes involved in certain biological functions. Indeed, we found that the IRE-associated genes in the GO terms or KEGG pathways that are enriched for both zebrafish and mice, such as “cell activation” or “TNF signaling pathway”, exhibited significant upregulation after injury in both species, as well as increased H3K27ac signals at the promoters Fig. D-E. MoreTo further understand how the lost or gained IREs between zebrafish and mice lead to different outcomes in injury-induced transcriptional responses, we performed a cross-species comparison of the functional properties and sequence features of IREs. We first searched the orthologous sequences for IREs in the different species. Among the 646 zebrafish IREs, 437 (67.6%) are associated with genes that have mouse orthologs Fig. A, left. To better characterize the functional divergence of the IRE-related sequences in different species, we selected all the cardiac IREs in zebrafish and mice that can be assigned with orthologous sequences in the other species, and classified these IREs into three categories: shared IREs, zebrafish-specific IREs, and mouse-specific IREs Table S. As expezeb2a is located near an intronic IRE which contains only ETS motifs. The ortholog of zeb2a in mouse is Zeb2, which encodes a transcription factor that regulates nervous system development [zeb2a IRE in mice is located ~ 80 kb upstream of the Zeb2 promoter, contains a similar frequency of ETS motifs, and exhibits a significant increase in H3K27ac signal upon cardiac injury, suggesting this sequence also functions as an IRE in mice  and E2 (Gda) were significantly up-regulated upon injury in mouse hearts  for functional validation. Both enhancers exhibited significant upregulation of H3K27ac level upon cardiac injury in mice, whereas their orthologous sequences in zebrafish showed no changes Fig. C. Consists Fig. SB. In HL-xia Fig. D, indicaxia Fig. C. Using xia Fig. F-G, thusTo explicitly test the functional contribution of ETS and AP-1 motifs in the induction of IREs, we mutated all ETS motifs or AP-1 motifs in both enhancers to AAAAAAAA or AAAAAAA, respectively. For both enhancers, mutating either the ETS or the AP-1 motifs led to a reduction in the enhancer activation following hypoxia treatment Fig. F-G, suggDrosophila [Enhancer elements play critical roles in orchestrating the transcriptional landscapes in development and tissue homeostasis , 46. Preosophila . Howeverosophila . We furtThe type, number, and combination of transcription factor binding sites (TFBSs) are critical features that govern enhancer functions . Our anaWe further revealed that the inter-species variations in IREs between zebrafish and mice are intimately linked to the alterations in frequencies of AP-1 and ETS transcription factor binding motifs. Enhancers undergo rapid changes in sequence and turnover in function during evolution . ConsistThe variations in IREs between different species are linked with different transcriptome responses upon cardiac injury. Of particular note, the transcriptional activation for genes associated with zebrafish-specific IREs was dampened in mice, which may partially contribute to the reduced regeneration capacity in mice Fig. H, middleWe note that several limitations associated with the currently available datasets may hinder the precise interpretation of the functions of IREs. First, the lack of stage-matched scRNA-seq and scATAC-seq datasets for mouse and zebrafish heart regeneration led us to use bulk genomic and epigenomic data in this study, which represent the averaged gene expression and enhancer activities of all cell types within the cardiac tissue compartments. This may lead to the underestimation of IRE-driven gene activation, and prevent us from assessing the cell-type-specific functions of IREs. Second, the transcriptomic and epigenetic profiling for both mouse and zebrafish hearts was only performed at limited time points post-injury. The lack of temporal resolution of the data may lead to the omission of transiently activated IREs, and also cause underestimation in the induction of IRE activity and gene expression.Importantly, while most enhancers preferentially regulate target genes within their vicinity, enhancers are known to exert long-range regulatory effects by forming 3D interactions with their target genes. However, how 3D genome architecture changes during the process of regeneration and wound repair, and how the IREs interact with their targets have not been experimentally characterized. We anticipate that the application of 3C-based techniques, such as Hi-C , capturecis-regulatory elements during injury responses. Our findings are informative for understanding the molecular mechanisms of transcriptional remodeling in response to injury across different species, which will be potentially beneficial for developing new therapeutic strategies in regenerative medicine.In this study, we performed comparative genomic analyses on IREs during heart regeneration in zebrafish and mice, and revealed that the inter-species variations in the distribution of AP-1 and ETS transcription factor binding motifs may play an important role in defining the functions of http://broadinstitute.github.io/picard/). Genomic tracks with bigwig format were generated using bamCoverage in deepTools v3.5.1 [Neonatal mouse heart regeneration associated H3K27ac and H3K27me3 ChIP-seq data from GSE123867  were alis v3.5.1 .To identify IREs for P1 mouse hearts, we first merged bam files from two biological replicates (1.5 dpi ChIP or 1.5 dpi input), and used MACS2 v2.2.7.1  to call p-value < 0.01.H3K27ac ChIP-seq data of zebrafish heart regeneration from GSE75894 [To generate H3K27ac density plots of genomic regions of interest, we used computeMatrix and plotProfile or plotHeatmap from deepTools v3.5.1 . Smoothei is defined as following formula:qi is read counts mapped to transcript, li denotes the transcript length, and Single-end sequencing reads from RNA-seq during neonatal mouse heart regeneration from GSE123863  were map v1.26.0 .Zebrafish heart regeneration-associated RNA-seq data from GSE75894 [To define IRE-associated genes, we used the closest function from BEDTools v2.30.0  to find For scRNA-seq data analysis, we first downloaded the count matrices of gene expression from GSE159032 for zebrafish  and GSE1https://ftp.ncbi.nlm.nih.gov/geo/series/GSE82nnn/GSE82736/suppl/GSE82736_ENCFF099IOG_peaks_mm10.bed.gz), and annotated these peaks by annotatePeaks in HOMER v4.11.1 [We downloaded the H3K4me1 peak file from GSE82736 ( v4.11.1 . Peaks t v4.11.1  to perfohttps://api.wenglab.org/screen_v13/fdownloads/mm10-ccREs.bed) and extracted potential enhancer elements using the command “grep ELS” for further analysis.To annotate the inactive IREs, we downloaded cCRE data from ENCODE Encyclopedia , c represents motif counts, and s is sequence size of the IRE.Genomic sequences of IREs were scanned to find and count AP-1 and ETS transcription factor binding motifs using a custom python script. The International Union of Pure and Applied Chemistry (IUPAC) codes for AP-1 and ETS motifs summarized by results of motif enrichment analysis are as follows: AP-1 (TKASTMA), and ETS (VVGGAWVY). For 14 transcription factors from ETS family, IUPAC codes are listed below: EHF (DNVMGGAAR), ELF1 (SCGGAAGY), ELF3 (WNVMGGAARY), ELF4 (VMGGAAG), ELF5 (WNVMGGAAGT), ERG (CMGGAARY), ETS1 (RVMGGAWRY), ETV1 (CMGGAWG), ETV2 (VMGGAWR), ETV4 (SMGGAWRB), FLI1 (VMGGAWR), GABPα (VMGGAAG), PU.1 (DVRGGAAGTG), and SPIB (DWDVRGAAVYS). IUPAC codes for 7 transcription factors from AP-1 family are as follows: ATF3 (VTKANTCAB), BATF (TKASTMA), FOS (TKANTYA), FRA1 (VTKANTMAB), FRA2 (TKWSYMA), JUN (TGASTCA), and JUNB (TKASTCA). Motif frequency was calculated asr is relative overlapping ratio, ni denotes the number of sequence with certain motif frequency intersecting with true (or random) peaks, and ni=0 represents the number of sequence without AP-1 or ETS motif overlapping with true (or random) peaks. The intersection was performed using intersect function from BEDTools v2.30.0 [To reveal relationship between motif frequency and binding sites of transcription factor, we randomly generated 10,000 genomic sequences with the length of 1 kb using random and getfasta function from BEDTools v2.30.0 . Peaks o v2.30.0 .p-value cutoff = 1 and min enrichment = 1. All genes were set as the enrichment background. Terms with q-value less than 0.05 were considered significantly enriched.To compare biological functions of IRE-associated genes, including GO biological process (BP) and KEGG pathway, between mice and zebrafish as comprehensively as possible, we used Metascape  with folTo characterize orthologous sequences of zebrafish IREs in mice, we first identified orthologs of zebrafish IRE-associated genes in mice using Ensembl BioMart . If a giPrediction of orthologous genes or enhancers in zebrafish of mouse IREs was performed with the same procedure as described above.http://genome.ucsc.edu) as bigwig files. The average conservation scores in 1 kb centering IRE or non-IRE midpoint were computed using subcommand computeMatrix and plotted by plotProfile from deepTools v3.5.1 [The evolutionary conservation scores quantified by phastCons60way  or phylo2 at 37 °C.HL-1 mouse cardiomyocytes  were cultured in RPMI 1640 medium  containing 10% fetal bovine serum (FBS) , 100 U/mL penicillin, and 0.1 mg/mL streptomycin in 5% CO2 and 5% CO2 for 24 h.HL-1 cells  were grown under standard conditions to approximately 80% confluency, and maintained in a quiescent state for 12 h. To induce hypoxia, HL-1 cells were transferred to a chamber  and flushed with a gas mixture of 95% NGapdh was as endogenous control. Primer sequences are as follows (from 5’ to 3’): Hif1α forward primer: GTTACGATTGTGAAGTTA, reverse primer: AAGGAATGAGATTAGGAA; Pde1a forward primer: ATCTTATCAACCGCTTCAA, reverse primer: TGCTGTAACCAACTTCTAA; Gda forward primer: AGGAATAGCAGTGGTAAT, reverse primer: AACAAGCATAGGTAACATT; Gapdh forward primer: CCTGGTCACCAGGGCTGC, reverse primer: CGCTCCTGGAAGATGGTGATG.Total RNA was isolated with TRIzol Reagent  according to manufacturer’s instructions, and cDNA was synthesized with PrimeScript RT Master Mix Kit . Real time qPCR was performed using LightCycler 480 II (Roche). We used ∆∆CT method to quantify relative gene expression level, and The protein extracts were prepared in RIPA lysis buffer containing 100 U protease inhibitors . Samples were run on 10% SDS-PAGE gels, and then transferred to PVDF membranes . The membranes were blocked with 5% no-fat milk in TBS with 0.1% Tween 20, and incubated with primary antibodies  at 4 °C overnight. HRP-conjugated goat anti-rabbit IgG  secondary antibodies were used. The signals were recorded with ECL reagents (Millipore ECL plus kit), and visualized using an ImageQuant LAS4000 .FC denotes relative activation level of the sequence , si(H) and si(N) are average relative luciferase signal of samples under hypoxia and normal condition, respectively. Similarly, sc(H) and sc(N) are mean relative luciferase activity of samples with control (empty vector) under hypoxic and normal condition.Luciferase reporter plasmid constructs cloned with synthetic enhancer sequences were confirmed by Sanger sequencing. HL-1 cells were transfected with related plasmid using Lipo8000 . Firefly and renilla luciferase activity were measured by Dual-Luciferase Reporter Assay System (Promega) according to the manufacturer’s instructions. Renilla luciferase was used as an internal control to facilitate normalization for transfection efficiency. For each enhancer candidate and construct, we used the average of the replicates as the final activity together with the standard error of mean (SEM). Enhancer activation level quantified by relative fold change of average relative luciferase activity was calculated as follows:Additional file 1: Fig. S1. Comparison of enhancer landscapes between mouse P1 and P8 hearts.Additional file 2: Fig. S2. Motif associated analyses of zebrafish and mouse cardiac IREs.Additional file 3: Fig. S3. Comparison of IRE-gene pairs between zebrafish and mice.Additional file 4: Fig. S4. Analyses of IRE-associated genes involved in different biological functions between zebrafish and mice.Additional file 5: Fig. S5. Sequence conservation and motif frequency analyses of zebrafish and mouse cardiac IREs.Additional file 6: Fig. S6. Two mouse IREs tested in HL-1 cells with hypoxia treatment.Additional file 7: Table S1. Coordinates of IREs and non-IREs in neonatal P1 mouse hearts.Additional file 8: Table S2. Locations of IREs identified during zebrafish heart regeneration.Additional file 9: Table S3. Results of motif enrichment analysis for zebrafish and mouse IREs.Additional file 10: Table S4. Significantly enriched GO terms for IRE-associated genes that have orthologous genes in both zebrafish and mice.Additional file 11: Table S5. Significantly enriched KEGG pathways for IRE-associated genes that have orthologous genes in both zebrafish and mice.Additional file 12: Table S6. Three types of genes associated with IREs in zebrafish and mice.Additional file 13: Table S7. Significantly enriched GO terms for three types of IRE-associated genes in zebrafish and mice.Additional file 14: Table S8. Significantly enriched KEGG pathways for three types of IRE-associated genes in zebrafish and mice.Additional file 15: Table S9. Coordinates of three classes of zebrafish and mouse cardiac IREs.Additional file 16: Table S10. Public datasets analyzed in this paper.