BACKGROUND:Adult mammalian cardiomyocytes have limited proliferative capacity, but in specifically induced contexts they traverse through cell-cycle reentry, offering the potential for heart regeneration. Endogenous cardiomyocyte proliferation is preceded by cardiomyocyte dedifferentiation (CMDD), wherein adult cardiomyocytes revert to a less matured state that is distinct from the classical myocardial fetal stress gene response associated with heart failure. However, very little is known about CMDD as a defined cardiomyocyte cell state in transition. METHODS:Here, we leveraged 2 models of in vitro cultured adult mouse cardiomyocytes and in vivo adeno-associated virus serotype 9 cardiomyocyte-targeted delivery of reprogramming factors (Oct4, Sox2, Klf4, and Myc) in adult mice to study CMDD. We profiled their transcriptomes using RNA sequencing, in combination with multiple published data sets, with the aim of identifying a common denominator for tracking CMDD. RESULTS:RNA sequencing and integrated analysis identified Asparagine Synthetase (Asns) as a unique molecular marker gene well correlated with CMDD, required for increased asparagine and also for distinct fluxes in other amino acids. Although Asns overexpression in Oct4, Sox2, Klf4, and Myc cardiomyocytes augmented hallmarks of CMDD, Asns deficiency led to defective regeneration in the neonatal mouse myocardial infarction model, increased cell death of cultured adult cardiomyocytes, and reduced cell cycle in Oct4, Sox2, Klf4, and Myc cardiomyocytes, at least in part through disrupting the mammalian target of rapamycin complex 1 pathway. CONCLUSIONS:We discovered a novel gene Asns as both a molecular marker and an essential mediator, marking a distinct threshold that appears in common for at least 4 models of CMDD, and revealing an Asns/mammalian target of rapamycin complex 1 axis dependency for dedifferentiating cardiomyocytes. Further study will be needed to extrapolate and assess its relevance to other cell state transitions as well as in heart regeneration.

RATIONALE:Cardiac-expressed long noncoding RNAs (lncRNAs) are important for cardiomyocyte (CM) differentiation and function. Several lncRNAs have been identified and characterized for early CM lineage commitment, however those in later CM lineage specification and maturation remain less well studied. Moreover, unique atrial / ventricular lncRNA expression has never been studied in detail. OBJECTIVES:Here, we characterized a novel ventricular myocyte-restricted lncRNA, not expressed in atrial myocytes, and conserved only in primates. METHODS AND RESULTS:First, we performed single cell RNA-seq on human pluripotent stem cell derived cardiomyocytes (hPSC-CM) at the late stages of 2, 6 and 12 weeks of differentiation. Weighted correlation network analysis identified core gene modules, including a set of lncRNAs highly abundant and predominantly expressed in the human heart. A lncRNA (we call VENTHEART, VHRT) co-expressed with cardiac maturation and ventricular-specific genes MYL2 and MYH7, and was expressed in fetal and adult human ventricles, but not atria. CRISPR-mediated deletion of the VHRT gene led to impaired CM sarcomere formation and significant disruption of the ventricular CM gene program. Indeed, a similar disruption was not observed in VHRT KO hPSC-derived atrial CM, suggesting that VHRT exhibits only ventricular myocyte subtype-specific effects. Optical recordings validated that loss of VHRT significantly prolonged action potential duration at 90 % repolarization (APD90) for ventricular-like, but not atrial-like, CMs. CONCLUSION:This reports the first lncRNA that is exclusively required for proper ventricular, and not atrial, CM specification and function.

PCR-based assays to detect human circulating DNA in mice demonstrate that human PTEGR2 assays are specific (A) and sensitive (B). Human-derived DNA could be detected in plasma of PDX (C).

Aldosterone-producing adenomas (APAs) are the commonest curable cause of hypertension. Most have gain-of-function somatic mutations of ion channels or transporters. Herein we report the discovery, replication and phenotype of mutations in the neuronal cell adhesion gene CADM1. Independent whole exome sequencing of 40 and 81 APAs found intramembranous p.Val380Asp or p.Gly379Asp variants in two patients whose hypertension and periodic primary aldosteronism were cured by adrenalectomy. Replication identified two more APAs with each variant (total, n = 6). The most upregulated gene (10- to 25-fold) in human adrenocortical H295R cells transduced with the mutations (compared to wildtype) was CYP11B2 (aldosterone synthase), and biological rhythms were the most differentially expressed process. CADM1 knockdown or mutation inhibited gap junction (GJ)-permeable dye transfer. GJ blockade by Gap27 increased CYP11B2 similarly to CADM1 mutation. Human adrenal zona glomerulosa (ZG) expression of GJA1 (the main GJ protein) was patchy, and annular GJs (sequelae of GJ communication) were less prominent in CYP11B2-positive micronodules than adjacent ZG. Somatic mutations of CADM1 cause reversible hypertension and reveal a role for GJ communication in suppressing physiological aldosterone production.

List of 40 genes in next-generation sequencing (NGS) panel

Doxorubicin is an anthracycline widely used for the treatment of various cancers; however, the drug has a common deleterious side effect, namely a dose-dependent cardiotoxicity. Doxorubicin treatment increases the generation of reactive oxygen species, which leads to oxidative stress in the cardiac cells and ultimately DNA damage and cell death. The most common DNA lesion produced by oxidative stress is 7,8-dihydro-8-oxoguanine (8-oxoguanine), and the enzyme responsible for its repair is the 8-oxoguanine DNA glycosylase (OGG1), a base excision repair enzyme. Here, we show that the OGG1 deficiency has no major effect on cardiac function at baseline or with pressure overload; however, we found an exacerbation of cardiac dysfunction as well as a higher mortality in Ogg1 knockout mice treated with doxorubicin. Our transcriptomic analysis also showed a more extensive dysregulation of genes in the hearts of Ogg1 knockout mice with an enrichment of genes involved in inflammation. These results demonstrate that OGG1 attenuates doxorubicin-induced cardiotoxicity and thus plays a role in modulating drug-induced cardiomyopathy.

Loss of insulin-secreting pancreatic β cells through apoptosis contributes to the progression of type 2 diabetes, but underlying mechanisms remain elusive. Here, we identify a pathway in which the cell death inhibitor ARC paradoxically becomes a killer during diabetes. While cytoplasmic ARC maintains β cell viability and pancreatic architecture, a pool of ARC relocates to the nucleus to induce β cell apoptosis in humans with diabetes and several pathophysiologically distinct mouse models. β cell death results through the coordinate downregulation of serpins (serine protease inhibitors) not previously known to be synthesized and secreted by β cells. Loss of the serpin α1-antitrypsin from the extracellular space unleashes elastase, triggering the disruption of β cell anchorage and subsequent cell death. Administration of α1-antitrypsin to mice with diabetes prevents β cell death and metabolic abnormalities. These data uncover a pathway for β cell loss in type 2 diabetes and identify an FDA-approved drug that may impede progression of this syndrome.

BACKGROUND:Biomechanical stimuli are known to be important to cardiac development, but the mechanisms are not fully understood. Here, we pharmacologically disrupted the biomechanical environment of wild-type zebrafish embryonic hearts for an extended duration and investigated the consequent effects on cardiac function, morphological development, and gene expression.RESULTS:Myocardial contractility was significantly diminished or abolished in zebrafish embryonic hearts treated for 72 hours from 2 dpf with 2,3-butanedione monoxime (BDM). Image-based flow simulations showed that flow wall shear stresses were abolished or significantly reduced with high oscillatory shear indices. At 5 dpf, after removal of BDM, treated embryonic hearts were maldeveloped, having disrupted cardiac looping, smaller ventricles, and poor cardiac function (lower ejected flow, bulboventricular regurgitation, lower contractility, and slower heart rate). RNA sequencing of cardiomyocytes of treated hearts revealed 922 significantly up-regulated genes and 1,698 significantly down-regulated genes. RNA analysis and subsequent qPCR and histology validation suggested that biomechanical disruption led to an up-regulation of inflammatory and apoptotic genes and down-regulation of ECM remodeling and ECM-receptor interaction genes. Biomechanics disruption also prevented the formation of ventricular trabeculation along with notch1 and erbb4a down-regulation.CONCLUSIONS:Extended disruption of biomechanical stimuli caused maldevelopment, and potential genes responsible for this are identified.

Most aldosterone-producing adenomas (APAs) have gain-of-function somatic mutations of ion channels or transporters. However, their frequency in aldosterone-producing cell clusters of normal adrenal gland suggests a requirement for codriver mutations in APAs. Here we identified gain-of-function mutations in both CTNNB1 and GNA11 by whole-exome sequencing of 3/41 APAs. Further sequencing of known CTNNB1-mutant APAs led to a total of 16 of 27 (59%) with a somatic p.Gln209His, p.Gln209Pro or p.Gln209Leu mutation of GNA11 or GNAQ. Solitary GNA11 mutations were found in hyperplastic zona glomerulosa adjacent to double-mutant APAs. Nine of ten patients in our UK/Irish cohort presented in puberty, pregnancy or menopause. Among multiple transcripts upregulated more than tenfold in double-mutant APAs was LHCGR, the receptor for luteinizing or pregnancy hormone (human chorionic gonadotropin). Transfections of adrenocortical cells demonstrated additive effects of GNA11 and CTNNB1 mutations on aldosterone secretion and expression of genes upregulated in double-mutant APAs. In adrenal cortex, GNA11/Q mutations appear clinically silent without a codriver mutation of CTNNB1.

Aims: Direct cardiac reprogramming represents an attractive way to reversing heart damage caused by myocardial infarction because it removes fibroblasts, while also generating new functional cardiomyocytes. Yet, the main hurdle for bringing this technique to the clinic is the lack of efficacy with current reprogramming protocols. Here, we describe our unexpected discovery that DMSO is capable of significantly augmenting direct cardiac reprogramming in vitro. Methods and results: Upon induction with cardiac transcription factors- Gata4, Hand2, Mef2c and Tbx5 (GHMT), the treatment of mouse embryonic fibroblasts (MEFs) with 1% DMSO induced similar to 5 fold increase in Myh6-mCherry+ cells, and significantly upregulated global expression of cardiac genes, including Myh6, Ttn, Nppa, Myh7 and Ryr2. RNA-seq confirmed upregulation of cardiac gene programmes and downregulation of extracellular matrix-related genes. Treatment of TGF-beta 1, DMSO, or SB431542, and the combination thereof, revealed that DMSO most likely targets a separate but parallel pathway other than TGF-beta signalling. Subsequent experiments using small molecule screening revealed that DMSO enhances direct cardiac reprogramming through inhibition of the CBP/p300 bromodomain, and not its acetyltransferase property. Conclusion: In conclusion, our work points to a direct molecular target of DMSO, which can be used for augmenting GHMT-induced direct cardiac reprogramming and possibly other cell fate conversion processes.

Nicotinamide adenine dinucleotide (NAD) is a critical metabolite and coenzyme for multiple metabolic pathways and cellular processes ( [1][1]-[4][2] ). In this study, we identified Singheart, SGHRT as a nuclear genome-encoded NAD+-binding mitochondrial micropeptide. SGHRT, present in both monomeric and dimeric forms, binds directly to NAD, but not NADH or flavin adenine dinucleotide (FAD). Localized to the inner mitochondrial membrane and mitochondrial matrix, SGHRT interacts with the mitochondrial enzymes Succinate-CoA Ligase and Succinate Dehydrogenase. SGHRT deletion in human embryonic stem cell derived cardiomyocytes disrupted mitochondria morphology, decreased total NAD and ATP abundance, and resulted in defective TCA cycle metabolism, the electron transport chain and in Ox-Phos processes. These results comprise the first report of an NAD+-binding micropeptide, SGHRT, required for mitochondrial function and metabolism. ### Competing Interest Statement The authors have declared no competing interest. [1]: #ref-1 [2]: #ref-4

Most aldosterone-producing adenomas (APA) have gain-of-function somatic mutations of ion channels or transporters. However, their frequency in aldosterone-producing cell-clusters of normal adrenals suggests the existence of co-driver mutations which influence the development or phenotype of APAs. Gain-of-function mutations in both CTNNB1 and GNA11 were found by whole exome sequencing in 3 of 41 APAs from a UK/Irish cohort. Targeted sequencing for exon 3 mutations of CTNNB1 and p.Gln209 mutations of either GNA11 or closely homologous GNAQ confirmed these and 7 further double mutant APAs in this discovery cohort. The presence of GNA11/Q p.Gln209 mutations in CTNNB1 mutant APAs were replicated in 2 cohorts from France (n=14) and Sweden (n=3). In total, 16 (59%) of the 27 CTNNB1 mutant APAs investigated had a mutation at p.Gln209 of GNA11 (n=11) or GNAQ (n=5). Interestingly, CTNNB1-mutant APAs were more commonly present in women (23/27), and of these, those with GNA11/Q mutations were all women except for a pubertal boy. To also note, 9 of 10 of the UK/Irish double mutant APAs in the discovery cohort presented in puberty, pregnancy, or menopause. Mutation of p.Gln209, or homologous p.Gln in GNAS, GNA12-14, impair hydrogen bonds between G-protein α and β subunits. Transfection of H295R cells, an immortalised adrenocortical cell line heterozygous for the p.Ser45Pro mutation of CTNNB1 but wild-type for GNA11-14/Q/S, by each of the GNA11/Q mutations increased aldosterone secretion and CYP11B2 expression (encoding aldosterone synthase) by 1.93-6.1-fold and 8.0-9.8-fold respectively, compared to vector or wild-type -transfected cells. In ZG, GNA11/Q mediate the aldosterone response to angiotensin II, via stimulation of intracellular Ca2+ release by inositol trisphosphate. In the mutant-transfected cells, the stimulatory effect of angiotensin II 10 nM was retained. In order to determine whether the p.Gln209 mutations stimulate aldosterone production even in the absence of CTNNB1 activation, the transfections of H295R cells were repeated after either 24-h treatment with the CTNNB1 inhibitor, ICG-001, or silencing of CTNNB1 using the ONTARGETplus SMARTpool SiRNAs (Dharmacon). Both interventions reduced the aldosterone production relative to vehicle/control-treated cells; however neither ICG-001 nor silencing of CTNNB1 blunted the fold-increase in aldosterone secretion seen in mutant-transfected cells compared to wild-type. In summary, we report the discovery of gain-of-function mutations of the G-protein, GNA11, or its close homologue, GNAQ, in multiple APAs which majority presented during periods of high LH/HCG. To date, the mutation is always residue p.Gln209, and associated with a gain-of-function mutation of CTNNB1. These GNA11/Q p.Gln209 mutations increase aldosterone and CYP11B2 production both in the presence and in the absence of CTNNB1 activation.

3D-structures for GNAQ and 600 GNAS Somatic or mosaic mutation of p.Gln inhibits GTPase activity 601 and constitutively activates downstream signalling. We find that p.Gln mutation of GNA11/Q 602 stimulates aldosterone production, and, in the adrenal, always co-exists with somatic mutation in 603 exon 3 of CTNNB1 . This prevents inactivation by phosphorylation (e.g. of p.Ser33, in purple, in the 604 partial 3D sequence). Double-mutation of GNA11/Q and CTNNB1 induces high expression of multiple 605 genes, including LHCGR, the G α s/cyclic AMP coupled receptor of luteinizing and pregnancy 606 hormones. The 3D structures of CTNNB1, GNAS, GNAQ, AT1-receptor, renin, ACE were downloaded from models 6M93, 3C14, 4QJ3, 6YV1, 2V0Z, 1O8A, respectively, at www.rcsb.org/.

Abstract The Peranakan Chinese are culturally unique descendants of immigrants from China who settled in the Malay Archipelago ∼300–500 years ago. Today, among large communities in Southeast Asia, the Peranakans have preserved Chinese traditions with strong influence from the local indigenous Malays. Yet, whether or to what extent genetic admixture co-occurred with the cultural mixture has been a topic of ongoing debate. We performed whole-genome sequencing (WGS) on 177 Singapore (SG) Peranakans and analyzed the data jointly with WGS data of Asian and European populations. We estimated that Peranakan Chinese inherited ∼5.62% (95% confidence interval [CI]: 4.76–6.49%) Malay ancestry, much higher than that in SG Chinese (1.08%, 0.65–1.51%), southern Chinese (0.86%, 0.50–1.23%), and northern Chinese (0.25%, 0.18–0.32%). A sex-biased admixture history, in which the Malay ancestry was contributed primarily by females, was supported by X chromosomal variants, and mitochondrial (MT) and Y haplogroups. Finally, we identified an ancient admixture event shared by Peranakan Chinese and SG Chinese ∼1,612 (95% CI: 1,345–1,923) years ago, coinciding with the settlement history of Han Chinese in southern China, apart from the recent admixture event with Malays unique to Peranakan Chinese ∼190 (159–213) years ago. These findings greatly advance our understanding of the dispersal history of Chinese and their interaction with indigenous populations in Southeast Asia.

HomeCirculationVol. 142, No. 9Assigning Distal Genomic Enhancers to Cardiac Disease–Causing Genes Free AccessLetterPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyRedditDiggEmail Jump toFree AccessLetterPDF/EPUBAssigning Distal Genomic Enhancers to Cardiac Disease–Causing Genes Chukwuemeka George Anene-Nzelu, MD, PhD Wilson Lek Wen Tan, PhD Chang Jie Mick Lee, BSc Zheng Wenhao, BSc Arnaud Perrin, MSc Albert Dashi, PhD Zenia Tiang, BSc Matias Ilmari Autio, PhD Bram Lim, BSc Eleanor Wong, PhD Hui San Tan, BSc Bangfen Pan, MSc Michael P. Morley, BA Kenneth B. Margulies, MD Thomas P. Cappola, MD, ScM Roger S-Y. FooMD Chukwuemeka George Anene-NzeluChukwuemeka George Anene-Nzelu Cardiovascular Research Institute, National University Health System, Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Genome Institute of Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). *Dr Anene-Nzelu, W.L.W. Tan, and C.J.M. Lee contributed equally. Search for more papers by this author , Wilson Lek Wen TanWilson Lek Wen Tan Cardiovascular Research Institute, National University Health System, Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Genome Institute of Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). *Dr Anene-Nzelu, W.L.W. Tan, and C.J.M. Lee contributed equally. Search for more papers by this author , Chang Jie Mick LeeChang Jie Mick Lee Cardiovascular Research Institute, National University Health System, Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Genome Institute of Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). *Dr Anene-Nzelu, W.L.W. Tan, and C.J.M. Lee contributed equally. Search for more papers by this author , Zheng WenhaoZheng Wenhao Cardiovascular Research Institute, National University Health System, Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Genome Institute of Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Search for more papers by this author , Arnaud PerrinArnaud Perrin Cardiovascular Research Institute, National University Health System, Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Genome Institute of Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Search for more papers by this author , Albert DashiAlbert Dashi Cardiovascular Research Institute, National University Health System, Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Genome Institute of Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Search for more papers by this author , Zenia TiangZenia Tiang https://orcid.org/0000-0003-1182-0023 Cardiovascular Research Institute, National University Health System, Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Genome Institute of Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Search for more papers by this author , Matias Ilmari AutioMatias Ilmari Autio https://orcid.org/0000-0001-9579-9617 Cardiovascular Research Institute, National University Health System, Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Genome Institute of Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Search for more papers by this author , Bram LimBram Lim https://orcid.org/0000-0002-8763-6436 Cardiovascular Research Institute, National University Health System, Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Genome Institute of Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Search for more papers by this author , Eleanor WongEleanor Wong Cardiovascular Research Institute, National University Health System, Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Genome Institute of Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Search for more papers by this author , Hui San TanHui San Tan Cardiovascular Research Institute, National University Health System, Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Genome Institute of Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Search for more papers by this author , Bangfen PanBangfen Pan Cardiovascular Research Institute, National University Health System, Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Genome Institute of Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Search for more papers by this author , Michael P. MorleyMichael P. Morley https://orcid.org/0000-0002-0958-7376 Cardiovascular Institute, Perlman School of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia (M.P.M., K.B.M., T.P.C.). Search for more papers by this author , Kenneth B. MarguliesKenneth B. Margulies Cardiovascular Institute, Perlman School of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia (M.P.M., K.B.M., T.P.C.). Search for more papers by this author , Thomas P. CappolaThomas P. Cappola Cardiovascular Institute, Perlman School of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia (M.P.M., K.B.M., T.P.C.). Search for more papers by this author , Roger S-Y. FooRoger S-Y. Foo Roger S.-Y. Foo, MD, Genome Institute of Singapore, 60 Biopolis Street, Singapore 138672. Email E-mail Address: [email protected] https://orcid.org/0000-0002-8079-4618 Cardiovascular Research Institute, National University Health System, Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Genome Institute of Singapore (C.G.A.-N., W.L.W.T., C.J.M.L., Z.W., A.P., A.D., Z.T., M.I.A., B.L., E.W., H.S.T., B.P., R.S.-Y.F.). Search for more papers by this author Originally published31 Aug 2020https://doi.org/10.1161/CIRCULATIONAHA.120.046040Circulation. 2020;142:910–912The human genome is replete with noncoding regulatory elements that control how genes are expressed in different cell types and cell states.1 It is now widely accepted that regulatory loci harbor genetic variants that influence phenotype and disease causality.1 Genomic enhancers are the prime example of regulatory elements, each exerting its influence on different genes at a time or sharing regulatory functions with other enhancers on the same gene.1 Although some enhancers are located adjacent to their target genes, others are located kilobases away, sometimes skipping over nearby genes, because of the 3-dimensional chromatin looping architecture that packs the genome into the nuclear space.2 Identifying regulatory loci for disease-relevant genes is the subject of numerous studies.1 Chromatin immuno-precipitation with sequencing, assay for transposase-accessible chromatin using sequencing, and DNase-sequencing identify enhancer loci but do not provide information on their corresponding target genes.1 Chromatin conformation assays, on the other hand, map interactions,2 linking enhancers to their target genes.3 However, physical proximity alone does not confirm their regulatory impact because an enhancer may be inactive even when in close proximity.1 Recent evidence points to the need to operationally define functional enhancers through a combination of assays and validations because enhancers nominated only through chromatin conformation–based methodologies do not always lead to detectable changes in gene expression when perturbed by CRISPR interference.1The Activity-by-Contact (ABC) algorithm2 tackles this issue by multiplying measures of enhancer activity and enhancer-promoter 3-dimensional contacts, thus predicting weighted enhancer-gene connections in a given cell type. Different enhancer loci that correspond to a gene are scored. Scores >0.05 are predicted to have a functional regulatory effect on their target genes, and higher scores indicate stronger contribution to the gene.2 Evidence suggests that ABC outperforms other models of predicting target genes of enhancers, including H3K27ac HiChIP, polymerase II, chromatin interaction analysis with paired-end tag, and TargetFinder.2 Hence, to annotate and prioritize a global catalog of cardiac-relevant gene enhancers, we applied the ABC algorithm to data sets of human whole left ventricles Figure (A). The study was approved by an institutional review committee and subjects gave informed consent. For in vitro validation, we applied ABC to human embryonic stem cell–derived cardiomyocytes. ABC scores in human embryonic stem cell–derived cardiomyocytes and human heart were highly correlated with a correlation coefficient R of 0.87 (Figure [B]). The Figure (C and D) illustrates ACTC1, SCN5A, KCNQ1, and KCNH2 and their distal enhancers. As anticipated, some enhancers are intergenic, others are intronic, and some are located at the promoter of another distant gene. ABC scores rank each set of gene enhancers on the basis of their regulatory impact on the target gene. Figure (E) lists more disease-causing genes and their respective top-scoring enhancers. Enhancers interacting with SCN5A and KCNH2 each harbor genome-wide association study single nucleotide polymorphisms that have been associated with altering electric activity of the heart.4Download figureDownload PowerPointFigure. Top distal enhancers for cardiac genes.A, Schematic illustrating the workflow to apply the Activity-by-Contact (ABC) algorithm. Data sets were taken from human left ventricular (LV) assay for transposase-accessible chromatin using sequencing (ATAC-seq), H3K27ac chromatin immuno-precipitation with sequencing (ChIP-seq), and HiChIP.2 For human embryonic stem cell–derived cardiomyocytes (hESC-CMs), ChIP-seq and ATAC-seq were performed on 2 independents replicates for each technique. B, Correlation plot showing close similarity between the ABC scores from human LV and hESC-CM. Pearson correlation coefficient R=0.87. C, University of California, Santa Cruz (UCSC) genome browser screenshot showing an example of the ACTC1 gene and its top 3 distal enhancers. The top enhancer E1 (≈75 kb away) is intergenic and skips the proximal gene GJD2 to interact with ACTC1. E1 scores higher than the next enhancer (E2), and E3 is a distal enhancer located in the promoter of another cardiomyocyte-expressed gene (AQR). D, Circos plots showing the distal enhancers of 3 genes: KCNQ1, SCN5A, and KCNH2. Some enhancers are located within the introns of their respective genes; others are located in distal intergenic regions. Red represents top enhancers E1; yellow represents the other lower ranked enhancers starting from E2 and below. E, Locations of top-scoring enhancers for 10 cardiac genes. F, UCSC browser screenshot showing the locations of top enhancers for 3 genes selected for CRISPR-mediated enhancer deletion (top enhancer for ACTC1, Chr15:35,012,859–35,016,282; for MYL2, Chr12:111,364,206–111,368,031; for MTSS1, Chr8:125,859,000–125,862,000). G, Quantitative reverse transcriptase–polymer chain reaction for gene expression after deletion of their respective enhancers from F, showing ≈50%, 80%, and 20% downregulation for ACTC1, MYL2, and MTSS1, respectively. Quantification was calculated normalized to the housekeeping gene PPIA and compared with control (random nontargeting guide RNA). Three independent biological replicates of independently targeted hESC-CM lines for each enhancer deletion were analyzed. KO indicates knockout. Unpaired Student t test, *P<0.05.As validation that we have annotated high-scoring enhancers, we selected 3 examples (Figure [F]) and performed CRISPR-mediated enhancer excisions for each. Deletion of each unique enhancer resulted in 20% to 80% downregulation in their corresponding target genes (Figure [G]). Furthermore, to assess the utility of ABC in identifying target genes of enhancer expression quantitative trait loci (eQTLs), we downloaded the catalog of left ventricle (LV) Genotype-Tissue Expression eQTLs5 and compared the ability of 3 models to accurately predict distal target genes of eQTLs. We compared (1) published human embryonic stem cell–derived cardiomyocytes Capture Hi-C,3 (2) our HiChIP in human LV, and (3) ABC-scored enhancers processed from our analysis using human LV. We curated the LV eQTL list to contain only eQTLs that localized to H3K27ac-marked cardiac enhancers. From 340 enhancer eQTLs, Capture Hi-C accurately predicted distal target genes of 74 eQTLs (22%), whereas HiChIP loops predicted 156 eQTLs (45%). Taking the 0.05 cutoff for ABC scores, 122 enhancer eQTLs were present in our ABC list, and of these, distal target genes were predicted for 87 (71%). By this comparison, the ABC algorithm succeeds well at refining the identity of functional enhancers by reducing false-positive associations. Last, we intersected our ABC list with hits from the atrial fibrillation genome-wide association study meta-analysis4 and identified distal target genes corresponding to noncoding genome-wide association study single nucleotide polymorphism that localized to the distal enhancer sites for MTSS1, CASQ2, and KCNH2 and lesser known genes such as MLST8 and STC2.In summary, we have applied the ABC algorithm to assign top distal enhancers to cardiac genes. CRISPR-mediated deletion of top ABC ranking enhancers results in the significant downregulation of distal target genes. Although the whole LVs used in this analysis contain other cardiac cell types and likely affect the cellular specificity of enhancers, this data set provides high-confidence enhancer-gene pairs and ABC scores that can be mined deeply as an easily accessible open resource for loci of disease-causing genetic variants and target gene expression control.Sources of FundingThis work was funded by the Biomedical Research Council, Agency for Science, Technology and Research Special Positioning Fund (SPF2014/004), individual research grants and a Clinician Scientist Award from the National Medical Research Council of Singapore (Dr Foo), and RO1-HL105993 (Drs Cappola and Margulies).DisclosuresNone.Footnotes*Dr Anene-Nzelu, W.L.W. Tan, and C.J.M. Lee contributed equally.https://www.ahajournals.org/journal/circThe full list of ABC enhancers and their distal interacting genes is publicly available at NCBI Bioproject ID PRJNA602171 and searchable at https://foo-lab.com/data.Roger S.-Y. Foo, MD, Genome Institute of Singapore, 60 Biopolis Street, Singapore 138672. Email [email protected]a-star.edu.sgReferences1. Gasperini M, Tome JM, Shendure J. Towards a comprehensive catalogue of validated and target-linked human enhancers.Nat Rev Genet. 2020; 21:292–310. doi: 10.1038/s41576-019-0209-0CrossrefMedlineGoogle Scholar2. Fulco CP, Nasser J, Jones TR, Munson G, Bergman DT, Subramanian V, Grossman SR, Anyoha R, Doughty BR, Patwardhan TA, et al.. Activity-by-contact model of enhancer-promoter regulation from thousands of CRISPR perturbations.Nat Genet. 2019; 51:1664–1669. doi: 10.1038/s41588-019-0538-0CrossrefMedlineGoogle Scholar3. Choy MK, Javierre BM, Williams SG, Baross SL, Liu Y, Wingett SW, Akbarov A, Wallace C, Freire-Pritchett P, Rugg-Gunn PJ, et al.. Promoter interactome of human embryonic stem cell-derived cardiomyocytes connects GWAS regions to cardiac gene networks.Nat Commun. 2018; 9:2526. doi: 10.1038/s41467-018-04931-0CrossrefMedlineGoogle Scholar4. Roselli C, Chaffin MD, Weng LC, Aeschbacher S, Ahlberg G, Albert CM, Almgren P, Alonso A, Anderson CD, Aragam KG, et al.. Multi-ethnic genome-wide association study for atrial fibrillation.Nat Genet. 2018; 50:1225–1233. doi: 10.1038/s41588-018-0133-9CrossrefMedlineGoogle Scholar5. Genotype-Tissue Consortium. The Genotype-Tissue Expression (GTEx) project.Nat Genet. 2013; 45:580–585. doi: 10.1038/ng.2653CrossrefMedlineGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetails September 1, 2020Vol 142, Issue 9Article InformationMetrics Download: 900 © 2020 American Heart Association, Inc.https://doi.org/10.1161/CIRCULATIONAHA.120.046040PMID: 32866060 Originally publishedAugust 31, 2020 Keywordsepigeneticschromatingenomecardiovascular systemenhancer elementsPDF download SubjectsTranslational StudiesEtiologyBasic Science ResearchMechanisms

Objective Use next-generation sequencing (NGS) technology to improve our diagnostic yield in patients with suspected genetic disorders in the Asian setting. Design A diagnostic study conducted between 2014 and 2019 (and ongoing) under the Singapore Undiagnosed Disease Program. Date of last analysis was 1 July 2019. Setting Inpatient and outpatient genetics service at two large academic centres in Singapore. Patients Inclusion criteria: patients suspected of genetic disorders, based on abnormal antenatal ultrasound, multiple congenital anomalies and developmental delay. Exclusion criteria: patients with known genetic disorders, either after clinical assessment or investigations (such as karyotype or chromosomal microarray). Interventions Use of NGS technology—whole exome sequencing (WES) or whole genome sequencing (WGS). Main outcome measures (1) Diagnostic yield by sequencing type, (2) diagnostic yield by phenotypical categories, (3) reduction in time to diagnosis and (4) change in clinical outcomes and management. Results We demonstrate a 37.8% diagnostic yield for WES (n=172) and a 33.3% yield for WGS (n=24). The yield was higher when sequencing was conducted on trios (40.2%), as well as for certain phenotypes (neuromuscular, 54%, and skeletal dysplasia, 50%). In addition to aiding genetic counselling in 100% of the families, a positive result led to a change in treatment in 27% of patients. Conclusion Genomic sequencing is an effective method for diagnosing rare disease or previous ‘undiagnosed’ disease. The clinical utility of WES/WGS is seen in the shortened time to diagnosis and the discovery of novel variants. Additionally, reaching a diagnosis significantly impacts families and leads to alteration in management of these patients.

Human pluripotent stem cells (hPSCs)-derived cardiovascular progenitor cells (CVPCs) are a promising source for myocardial repair, while the mechanisms remain largely unknown. Extracellular vesicles (EVs) are known to mediate cell–cell communication, however, the efficacy and mechanisms of hPSC-CVPC-secreted EVs (hCVPC-EVs) in the infarct healing when given at the acute phase of myocardial infarction (MI) are unknown. Here, we report the cardioprotective effects of the EVs secreted from hESC-CVPCs under normoxic (EV-N) and hypoxic (EV-H) conditions in the infarcted heart and the long noncoding RNA (lncRNA)-related mechanisms. The hCVPC-EVs were confirmed by electron microscopy, nanoparticle tracking, and immunoblotting analysis. Injection of hCVPC-EVs into acutely infracted murine myocardium significantly improved cardiac function and reduced fibrosis at day 28 post MI, accompanied with the improved vascularization and cardiomyocyte survival at border zones. Consistently, hCVPC-EVs enhanced the tube formation and migration of human umbilical vein endothelial cells (HUVECs), improved the cell viability, and attenuated the lactate dehydrogenase release of neonatal rat cardiomyocytes (NRCMs) with oxygen glucose deprivation (OGD) injury. Moreover, the improvement of the EV-H in cardiomyocyte survival and tube formation of HUVECs was significantly better than these in the EV-N. RNA-seq analysis revealed a high abundance of the lncRNA MALAT1 in the EV-H. Its abundance was upregulated in the infarcted myocardium and cardiomyocytes treated with hCVPC-EVs. Overexpression of human MALAT1 improved the cell viability of NRCM with OGD injury, while knockdown of MALAT1 inhibited the hCVPC-EV-promoted tube formation of HUVECs. Furthermore, luciferase activity assay, RNA pull-down, and manipulation of miR-497 levels showed that MALAT1 improved NRCMs survival and HUVEC tube formation through targeting miR-497. These results reveal that hCVPC-EVs promote the infarct healing through improvement of cardiomyocyte survival and angiogenesis. The cardioprotective effects of hCVPC-EVs can be enhanced by hypoxia-conditioning of hCVPCs and are partially contributed by MALAT1 via targeting the miRNA.

Background: The human genome folds in 3 dimensions to form thousands of chromatin loops inside the nucleus, encasing genes and cis-regulatory elements for accurate gene expression control. Physical tethers of loops are anchored by the DNA-binding protein CTCF and the cohesin ring complex. Because heart failure is characterized by hallmark gene expression changes, it was recently reported that substantial CTCF-related chromatin reorganization underpins the myocardial stress–gene response, paralleled by chromatin domain boundary changes observed in CTCF knockout. Methods: We undertook an independent and orthogonal analysis of chromatin organization with mouse pressure-overload model of myocardial stress (transverse aortic constriction) and cardiomyocyte-specific knockout of Ctcf. We also downloaded published data sets of similar cardiac mouse models and subjected them to independent reanalysis. Results: We found that the cardiomyocyte chromatin architecture remains broadly stable in transverse aortic constriction hearts, whereas Ctcf knockout resulted in ≈99% abolition of global chromatin loops. Disease gene expression changes correlated instead with differential histone H3K27-acetylation enrichment at their respective proximal and distal interacting genomic enhancers confined within these static chromatin structures. Moreover, coregulated genes were mapped out as interconnected gene sets on the basis of their multigene 3D interactions. Conclusions: This work reveals a more stable genome-wide chromatin framework than previously described. Myocardial stress–gene transcription responds instead through H3K27-acetylation enhancer enrichment dynamics and gene networks of coregulation. Robust and intact CTCF looping is required for the induction of a rapid and accurate stress response.