Mitotic Block and Epigenetic Repression Underlie Neurodevelopmental Defects and Neurobehavioral Deficits in Congenital Heart Disease.

Poor neurodevelopment is often observed with congenital heart disease (CHD), especially with mutations in chromatin modifiers. Here analysis of mice with hypoplastic left heart syndrome (HLHS) arising from mutations in Sin3A associated chromatin modifier Sap130 , and adhesion protein Pcdha9, revealed neurodevelopmental and neurobehavioral deficits reminiscent of those in HLHS patients. Microcephaly was associated with impaired cortical neurogenesis, mitotic block, and increased apoptosis. Transcriptional profiling indicated dysregulated neurogenesis by REST, altered CREB signaling regulating memory and synaptic plasticity, and impaired neurovascular coupling modulating cerebral blood flow. Many neurodevelopmental/neurobehavioral disease pathways were recovered, including autism and cognitive impairment. These same pathways emerged from genome-wide DNA methylation and Sap130 chromatin immunoprecipitation sequencing analyses, suggesting epigenetic perturbation. Mice with Pcdha9 mutation or forebrain-specific Sap130 deletion without CHD showed learning/memory deficits and autism-like behavior. These novel findings provide mechanistic insights indicating the adverse neurodevelopment in HLHS may involve cell autonomous/nonautonomous defects and epigenetic dysregulation and suggest new avenues for therapy.

Uncompensated mitochondrial oxidative stress underlies heart failure in an iPSC-derived model of congenital heart disease.

Hypoplastic left heart syndrome (HLHS) is a severe congenital heart disease with 30% mortality from heart failure (HF) in the first year of life, but the cause of early HF remains unknown. Induced pluripotent stem-cell-derived cardiomyocytes (iPSC-CM) from patients with HLHS showed that early HF is associated with increased apoptosis, mitochondrial respiration defects, and redox stress from abnormal mitochondrial permeability transition pore (mPTP) opening and failed antioxidant response. In contrast, iPSC-CM from patients without early HF showed normal respiration with elevated antioxidant response. Single-cell transcriptomics confirmed that early HF is associated with mitochondrial dysfunction accompanied with endoplasmic reticulum (ER) stress. These findings indicate that uncompensated oxidative stress underlies early HF in HLHS. Importantly, mitochondrial respiration defects, oxidative stress, and apoptosis were rescued by treatment with sildenafil to inhibit mPTP opening or TUDCA to suppress ER stress. Together these findings point to the potential use of patient iPSC-CM for modeling clinical heart failure and the development of therapeutics.

Genetic resiliency associated with dominant lethal TPM1 mutation causing atrial septal defect with high heritability.

Analysis of large-scale human genomic data has yielded unexplained mutations known to cause severe disease in healthy individuals. Here, we report the unexpected recovery of a rare dominant lethal mutation in TPM1, a sarcomeric actin-binding protein, in eight individuals with large atrial septal defect (ASD) in a five-generation pedigree. Mice with Tpm1 mutation exhibit early embryonic lethality with disrupted myofibril assembly and no heartbeat. However, patient-induced pluripotent-stem-cell-derived cardiomyocytes show normal beating with mild myofilament defect, indicating disease suppression. A variant in TLN2, another myofilament actin-binding protein, is identified as a candidate suppressor. Mouse CRISPR knock-in (KI) of both the TLN2 and TPM1 variants rescues heart beating, with near-term fetuses exhibiting large ASD. Thus, the role of TPM1 in ASD pathogenesis unfolds with suppression of its embryonic lethality by protective TLN2 variant. These findings provide evidence that genetic resiliency can arise with genetic suppression of a deleterious mutation.

Common deletion variants causing protocadherin-α deficiency contribute to the complex genetics of BAV and left-sided congenital heart disease.

Bicuspid aortic valve (BAV) with ~1%-2% prevalence is the most common congenital heart defect (CHD). It frequently results in valve disease and aorta dilation and is a major cause of adult cardiac surgery. BAV is genetically linked to rare left-heart obstructions (left ventricular outflow tract obstructions [LVOTOs]), including hypoplastic left heart syndrome (HLHS) and coarctation of the aorta (CoA). Mouse and human studies indicate LVOTO is genetically heterogeneous with a complex genetic etiology. Homozygous mutation in the Pcdha protocadherin gene cluster in mice can cause BAV, and also HLHS and other LVOTO phenotypes when accompanied by a second mutation. Here we show two common deletion copy number variants (delCNVs) within the PCDHA gene cluster are associated with LVOTO. Analysis of 1,218 white individuals with LVOTO versus 463 disease-free local control individuals yielded odds ratios (ORs) at 1.47 (95% confidence interval [CI], 1.13-1.92; p = 4.2 × 10-3) for LVOTO, 1.47 (95% CI, 1.10-1.97; p = 0.01) for BAV, 6.13 (95% CI, 2.75-13.7; p = 9.7 × 10-6) for CoA, and 1.49 (95% CI, 1.07-2.08; p = 0.019) for HLHS. Increased OR was observed for all LVOTO phenotypes in homozygous or compound heterozygous PCDHA delCNV genotype comparison versus wild type. Analysis of an independent white cohort (381 affected individuals, 1,352 control individuals) replicated the PCDHA delCNV association with LVOTO. Generalizability of these findings is suggested by similar observations in Black and Chinese individuals with LVOTO. Analysis of Pcdha mutant mice showed reduced PCDHA expression at regions of cell-cell contact in aortic smooth muscle and cushion mesenchyme, suggesting potential mechanisms for BAV pathogenesis and aortopathy. Together, these findings indicate common variants causing PCDHA deficiency play a significant role in the genetic etiology of common and rare LVOTO-CHD.

Single-cell RNA sequencing reveals differential cell cycle activity in key cell populations during nephrogenesis.

The kidney is a complex organ composed of more than 30 terminally differentiated cell types that all are required to perform its numerous homeostatic functions. Defects in kidney development are a significant cause of chronic kidney disease in children, which can lead to kidney failure that can only be treated by transplant or dialysis. A better understanding of molecular mechanisms that drive kidney development is important for designing strategies to enhance renal repair and regeneration. In this study, we profiled gene expression in the developing mouse kidney at embryonic day 14.5 at single-cell resolution. Consistent with previous studies, clusters with distinct transcriptional signatures clearly identify major compartments and cell types of the developing kidney. Cell cycle activity distinguishes between the "primed" and "self-renewing" sub-populations of nephron progenitors, with increased expression of the cell cycle-related genes Birc5, Cdca3, Smc2 and Smc4 in "primed" nephron progenitors. In addition, augmented expression of cell cycle related genes Birc5, Cks2, Ccnb1, Ccnd1 and Tuba1a/b was detected in immature distal tubules, suggesting cell cycle regulation may be required for early events of nephron patterning and tubular fusion between the distal nephron and collecting duct epithelia.

Mitochondrial Respiration Defects in Single-Ventricle Congenital Heart Disease.

Background: Congenital heart disease (CHD) with single-ventricle (SV) physiology is now survivable with a three-stage surgical course ending with Fontan palliation. However, 10-year transplant-free survival remains at 39-50%, with ventricular dysfunction progressing to heart failure (HF) being a common sequela. For SV-CHD patients who develop HF, undergoing the surgical course would not be helpful and could even be detrimental. As HF risk cannot be predicted and metabolic defects have been observed in Ohia SV-CHD mice, we hypothesized that respiratory defects in peripheral blood mononuclear cells (PBMCs) may allow HF risk stratification in SV-CHD. Methods: SV-CHD (n = 20), biventricular CHD (BV-CHD; n = 16), or healthy control subjects (n = 22) were recruited, and PBMC oxygen consumption rate (OCR) was measured using the Seahorse Analyzer. Respiration was similarly measured in Ohia mouse heart tissue. Results: Post-Fontan SV-CHD patients with HF showed higher maximal respiratory capacity (p = 0.004) and respiratory reserve (p < 0.0001), parameters important for cell stress adaptation, while the opposite was found for those without HF (reserve p = 0.037; maximal p = 0.05). This was observed in comparison to BV-CHD or healthy controls. However, respiration did not differ between SV patients pre- and post-Fontan or between pre- or post-Fontan SV-CHD patients and BV-CHD. Reminiscent of these findings, heart tissue from Ohia mice with SV-CHD also showed higher OCR, while those without CHD showed lower OCR. Conclusion: Elevated mitochondrial respiration in PBMCs is correlated with HF in post-Fontan SV-CHD, suggesting that PBMC respiration may have utility for prognosticating HF risk in SV-CHD. Whether elevated respiration may reflect maladaptation to altered hemodynamics in SV-CHD warrants further investigation.

scds: computational annotation of doublets in single-cell RNA sequencing data.

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) technologies enable the study of transcriptional heterogeneity at the resolution of individual cells and have an increasing impact on biomedical research. However, it is known that these methods sometimes wrongly consider two or more cells as single cells, and that a number of so-called doublets is present in the output of such experiments. Treating doublets as single cells in downstream analyses can severely bias a study's conclusions, and therefore computational strategies for the identification of doublets are needed. RESULTS: With scds, we propose two new approaches for in silico doublet identification: Co-expression based doublet scoring (cxds) and binary classification based doublet scoring (bcds). The co-expression based approach, cxds, utilizes binarized (absence/presence) gene expression data and, employing a binomial model for the co-expression of pairs of genes, yields interpretable doublet annotations. bcds, on the other hand, uses a binary classification approach to discriminate artificial doublets from original data. We apply our methods and existing computational doublet identification approaches to four datasets with experimental doublet annotations and find that our methods perform at least as well as the state of the art, at comparably little computational cost. We observe appreciable differences between methods and across datasets and that no approach dominates all others. In summary, scds presents a scalable, competitive approach that allows for doublet annotation of datasets with thousands of cells in a matter of seconds. AVAILABILITY AND IMPLEMENTATION: scds is implemented as a Bioconductor R package (doi: 10.18129/B9.bioc.scds). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Enhancing regeneration after acute kidney injury by promoting cellular dedifferentiation in zebrafish.

Acute kidney injury (AKI) is a serious disorder for which there are limited treatment options. Following injury, native nephrons display limited regenerative capabilities, relying on the dedifferentiation and proliferation of renal tubular epithelial cells (RTECs) that survive the insult. Previously, we identified 4-(phenylthio)butanoic acid (PTBA), a histone deacetylase inhibitor (HDI), as an enhancer of renal recovery, and showed that PTBA treatment increased RTEC proliferation and reduced renal fibrosis. Here, we investigated the regenerative mechanisms of PTBA in zebrafish models of larval renal injury and adult cardiac injury. With respect to renal injury, we showed that delivery of PTBA using an esterified prodrug (UPHD25) increases the reactivation of the renal progenitor gene Pax2a, enhances dedifferentiation of RTECs, reduces Kidney injury molecule-1 (Kim-1) expression, and lowers the number of infiltrating macrophages. Further, we found that the effects of PTBA on RTEC proliferation depend upon retinoic acid signaling and demonstrate that the therapeutic properties of PTBA are not restricted to the kidney but also increase cardiomyocyte proliferation and decrease fibrosis following cardiac injury in adult zebrafish. These studies provide key mechanistic insights into how PTBA enhances tissue repair in models of acute injury and lay the groundwork for translating this novel HDI into the clinic.This article has an associated First Person interview with the joint first authors of the paper.

The complex genetics of hypoplastic left heart syndrome.

Congenital heart disease (CHD) affects up to 1% of live births. Although a genetic etiology is indicated by an increased recurrence risk, sporadic occurrence suggests that CHD genetics is complex. Here, we show that hypoplastic left heart syndrome (HLHS), a severe CHD, is multigenic and genetically heterogeneous. Using mouse forward genetics, we report what is, to our knowledge, the first isolation of HLHS mutant mice and identification of genes causing HLHS. Mutations from seven HLHS mouse lines showed multigenic enrichment in ten human chromosome regions linked to HLHS. Mutations in Sap130 and Pcdha9, genes not previously associated with CHD, were validated by CRISPR-Cas9 genome editing in mice as being digenic causes of HLHS. We also identified one subject with HLHS with SAP130 and PCDHA13 mutations. Mouse and zebrafish modeling showed that Sap130 mediates left ventricular hypoplasia, whereas Pcdha9 increases penetrance of aortic valve abnormalities, both signature HLHS defects. These findings show that HLHS can arise genetically in a combinatorial fashion, thus providing a new paradigm for the complex genetics of CHD.

Novel modeling of combinatorial miRNA targeting identifies SNP with potential role in bone density.

MicroRNAs (miRNAs) are post-transcriptional regulators that bind to their target mRNAs through base complementarity. Predicting miRNA targets is a challenging task and various studies showed that existing algorithms suffer from high number of false predictions and low to moderate overlap in their predictions. Until recently, very few algorithms considered the dynamic nature of the interactions, including the effect of less specific interactions, the miRNA expression level, and the effect of combinatorial miRNA binding. Addressing these issues can result in a more accurate miRNA:mRNA modeling with many applications, including efficient miRNA-related SNP evaluation. We present a novel thermodynamic model based on the Fermi-Dirac equation that incorporates miRNA expression in the prediction of target occupancy and we show that it improves the performance of two popular single miRNA target finders. Modeling combinatorial miRNA targeting is a natural extension of this model. Two other algorithms show improved prediction efficiency when combinatorial binding models were considered. ComiR (Combinatorial miRNA targeting), a novel algorithm we developed, incorporates the improved predictions of the four target finders into a single probabilistic score using ensemble learning. Combining target scores of multiple miRNAs using ComiR improves predictions over the naïve method for target combination. ComiR scoring scheme can be used for identification of SNPs affecting miRNA binding. As proof of principle, ComiR identified rs17737058 as disruptive to the miR-488-5p:NCOA1 interaction, which we confirmed in vitro. We also found rs17737058 to be significantly associated with decreased bone mineral density (BMD) in two independent cohorts indicating that the miR-488-5p/NCOA1 regulatory axis is likely critical in maintaining BMD in women. With increasing availability of comprehensive high-throughput datasets from patients ComiR is expected to become an essential tool for miRNA-related studies.

High throughput determination of TGFß1/SMAD3 targets in A549 lung epithelial cells.

BACKGROUND: Transforming growth factor beta 1 (TGFß1) plays a major role in many lung diseases including lung cancer, pulmonary hypertension, and pulmonary fibrosis. TGFß1 activates a signal transduction cascade that results in the transcriptional regulation of genes in the nucleus, primarily through the DNA-binding transcription factor SMAD3. The objective of this study is to identify genome-wide scale map of SMAD3 binding targets and the molecular pathways and networks affected by the TGFß1/SMAD3 signaling in lung epithelial cells. METHODOLOGY: We combined chromatin immunoprecipitation with human promoter region microarrays (ChIP-on-chip) along with gene expression microarrays to study global transcriptional regulation of the TGFß1/SMAD3 pathway in human A549 alveolar epithelial cells. The molecular pathways and networks associated with TGFß1/SMAD3 signaling were identified using computational approaches. Validation of selected target gene expression and direct binding of SMAD3 to promoters were performed by quantitative real time RT-PCR and electrophoretic mobility shift assay on A549 and human primary lung epithelial cells. RESULTS AND CONCLUSIONS: Known TGFß1 target genes such as SERPINE1, SMAD6, SMAD7, TGFB1 and LTBP3, were found in both ChIP-on-chip and gene expression analyses as well as some previously unrecognized targets such as FOXA2. SMAD3 binding of FOXA2 promoter and changed expression were confirmed. Computational approaches combining ChIP-on-chip and gene expression microarray revealed multiple target molecular pathways affected by the TGFß1/SMAD3 signaling. Identification of global targets and molecular pathways and networks associated with TGFß1/SMAD3 signaling allow for a better understanding of the mechanisms that determine epithelial cell phenotypes in fibrogenesis and carcinogenesis as does the discovery of the direct effect of TGFß1 on FOXA2.

In silico identification of a core regulatory network of OCT4 in human embryonic stem cells using an integrated approach.

BACKGROUND: The transcription factor OCT4 is highly expressed in pluripotent embryonic stem cells which are derived from the inner cell mass of mammalian blastocysts. Pluripotency and self renewal are controlled by a transcription regulatory network governed by the transcription factors OCT4, SOX2 and NANOG. Recent studies on reprogramming somatic cells to induced pluripotent stem cells highlight OCT4 as a key regulator of pluripotency. RESULTS: We have carried out an integrated analysis of high-throughput data (ChIP-on-chip and RNAi experiments along with promoter sequence analysis of putative target genes) and identified a core OCT4 regulatory network in human embryonic stem cells consisting of 33 target genes. Enrichment analysis with these target genes revealed that this integrative analysis increases the functional information content by factors of 1.3 - 4.7 compared to the individual studies. In order to identify potential regulatory co-factors of OCT4, we performed a de novo motif analysis. In addition to known validated OCT4 motifs we obtained binding sites similar to motifs recognized by further regulators of pluripotency and development; e.g. the heterodimer of the transcription factors C-MYC and MAX, a prerequisite for C-MYC transcriptional activity that leads to cell growth and proliferation. CONCLUSION: Our analysis shows how heterogeneous functional information can be integrated in order to reconstruct gene regulatory networks. As a test case we identified a core OCT4-regulated network that is important for the analysis of stem cell characteristics and cellular differentiation. Functional information is largely enriched using different experimental results. The de novo motif discovery identified well-known regulators closely connected to the OCT4 network as well as potential new regulators of pluripotency and differentiation. These results provide the basis for further targeted functional studies.

Incorporating evolution of transcription factor binding sites into annotated alignments.

Identifying transcription factor binding sites (TFBSs) is essential to elucidate putative regulatory mechanisms. A common strategy is to combine cross-species conservation with single sequence TFBS annotation to yield "conserved TFBSs". Most current methods in this field adopt a multi-step approach that segregates the two aspects. Again, it is widely accepted that the evolutionary dynamics of binding sites differ from those of the surrounding sequence. Hence, it is desirable to have an approach that explicitly takes this factor into account. Although a plethora of approaches have been proposed for the prediction of conserved TFBSs, very few explicitly model TFBS evolutionary properties, while additionally being multi-step. Recently, we introduced a novel approach to simultaneously align and annotate conserved TFBSs in a pair of sequences. Building upon the standard Smith-Waterman algorithm for local alignments, SimAnn introduces additional states for profiles to output extended alignments or annotated alignments. That is, alignments with parts annotated as gaplessly aligned TFBSs (pair-profile hits)are generated. Moreover,the pair- profile related parameters are derived in a sound statistical framework. In this article, we extend this approach to explicitly incorporate evolution of binding sites in the SimAnn framework. We demonstrate the extension in the theoretical derivations through two position-specific evolutionary models, previously used for modelling TFBS evolution. In a simulated setting, we provide a proof of concept that the approach works given the underlying assumptions,as compared to the original work. Finally, using a real dataset of experimentally verified binding sites in human-mouse sequence pairs,we compare the new approach (eSimAnn) to an existing multi-step tool that also considers TFBS evolution. Although it is widely accepted that binding sites evolve differently from the surrounding sequences, most comparative TFBS identification methods do not explicitly consider this.Additionally, prediction of conserved binding sites is carried out in a multi-step approach that segregates alignment from TFBS annotation. In this paper, we demonstrate how the simultaneous alignment and annotation approach of SimAnn can be further extended to incorporate TFBS evolutionary relationships. We study how alignments and binding site predictions interplay at varying evolutionary distances and for various profile qualities.