Robust Hi-C Maps of Enhancer-Promoter Interactions Reveal the Function of Non-coding Genome in Neural Development and Diseases.

Genome-wide mapping of chromatin interactions at high resolution remains experimentally and computationally challenging. Here we used a low-input "easy Hi-C" protocol to map the 3D genome architecture in human neurogenesis and brain tissues and also demonstrated that a rigorous Hi-C bias-correction pipeline (HiCorr) can significantly improve the sensitivity and robustness of Hi-C loop identification at sub-TAD level, especially the enhancer-promoter (E-P) interactions. We used HiCorr to compare the high-resolution maps of chromatin interactions from 10 tissue or cell types with a focus on neurogenesis and brain tissues. We found that dynamic chromatin loops are better hallmarks for cellular differentiation than compartment switching. HiCorr allowed direct observation of cell-type- and differentiation-specific E-P aggregates spanning large neighborhoods, suggesting a mechanism that stabilizes enhancer contacts during development. Interestingly, we concluded that Hi-C loop outperforms eQTL in explaining neurological GWAS results, revealing a unique value of high-resolution 3D genome maps in elucidating the disease etiology.

Liver eQTL meta-analysis illuminates potential molecular mechanisms of cardiometabolic traits.

Understanding the molecular mechanisms of complex traits is essential for developing targeted interventions. We analyzed liver expression quantitative-trait locus (eQTL) meta-analysis data on 1,183 participants to identify conditionally distinct signals. We found 9,013 eQTL signals for 6,564 genes; 23% of eGenes had two signals, and 6% had three or more signals. We then integrated the eQTL results with data from 29 cardiometabolic genome-wide association study (GWAS) traits and identified 1,582 GWAS-eQTL colocalizations for 747 eGenes. Non-primary eQTL signals accounted for 17% of all colocalizations. Isolating signals by conditional analysis prior to coloc resulted in 37% more colocalizations than using marginal eQTL and GWAS data, highlighting the importance of signal isolation. Isolating signals also led to stronger evidence of colocalization: among 343 eQTL-GWAS signal pairs in multi-signal regions, analyses that isolated the signals of interest resulted in higher posterior probability of colocalization for 41% of tests. Leveraging allelic heterogeneity, we predicted causal effects of gene expression on liver traits for four genes. To predict functional variants and regulatory elements, we colocalized eQTL with liver chromatin accessibility QTL (caQTL) and found 391 colocalizations, including 73 with non-primary eQTL signals and 60 eQTL signals that colocalized with both a caQTL and a GWAS signal. Finally, we used publicly available massively parallel reporter assays in HepG2 to highlight 14 eQTL signals that include at least one expression-modulating variant. This multi-faceted approach to unraveling the genetic underpinnings of liver-related traits could lead to therapeutic development.

MagicalRsq-X: A cross-cohort transferable genotype imputation quality metric.

Since genotype imputation was introduced, researchers have been relying on the estimated imputation quality from imputation software to perform post-imputation quality control (QC). However, this quality estimate (denoted as Rsq) performs less well for lower-frequency variants. We recently published MagicalRsq, a machine-learning-based imputation quality calibration, which leverages additional typed markers from the same cohort and outperforms Rsq as a QC metric. In this work, we extended the original MagicalRsq to allow cross-cohort model training and named the new model MagicalRsq-X. We removed the cohort-specific estimated minor allele frequency and included linkage disequilibrium scores and recombination rates as additional features. Leveraging whole-genome sequencing data from TOPMed, specifically participants in the BioMe, JHS, WHI, and MESA studies, we performed comprehensive cross-cohort evaluations for predominantly European and African ancestral individuals based on their inferred global ancestry with the 1000 Genomes and Human Genome Diversity Project data as reference. Our results suggest MagicalRsq-X outperforms Rsq in almost every setting, with 7.3%-14.4% improvement in squared Pearson correlation with true R2, corresponding to 85-218 K variant gains. We further developed a metric to quantify the genetic distances of a target cohort relative to a reference cohort and showed that such metric largely explained the performance of MagicalRsq-X models. Finally, we found MagicalRsq-X saved up to 53 known genome-wide significant variants in one of the largest blood cell trait GWASs that would be missed using the original Rsq for QC. In conclusion, MagicalRsq-X shows superiority for post-imputation QC and benefits genetic studies by distinguishing well and poorly imputed lower-frequency variants.

Cell-type-specific 3D epigenomes in the developing human cortex.

Lineage-specific epigenomic changes during human corticogenesis have been difficult to study owing to challenges with sample availability and tissue heterogeneity. For example, previous studies using single-cell RNA sequencing identified at least 9 major cell types and up to 26 distinct subtypes in the dorsal cortex alone1,2. Here we characterize cell-type-specific cis-regulatory chromatin interactions, open chromatin peaks, and transcriptomes for radial glia, intermediate progenitor cells, excitatory neurons, and interneurons isolated from mid-gestational samples of the human cortex. We show that chromatin interactions underlie several aspects of gene regulation, with transposable elements and disease-associated variants enriched at distal interacting regions in a cell-type-specific manner. In addition, promoters with increased levels of chromatin interactivity-termed super-interactive promoters-are enriched for lineage-specific genes, suggesting that interactions at these loci contribute to the fine-tuning of transcription. Finally, we develop CRISPRview, a technique that integrates immunostaining, CRISPR interference, RNAscope, and image analysis to validate cell-type-specific cis-regulatory elements in heterogeneous populations of primary cells. Our findings provide insights into cell-type-specific gene expression patterns in the developing human cortex and advance our understanding of gene regulation and lineage specification during this crucial developmental window.

MagicalRsq: Machine-learning-based genotype imputation quality calibration.

Whole-genome sequencing (WGS) is the gold standard for fully characterizing genetic variation but is still prohibitively expensive for large samples. To reduce costs, many studies sequence only a subset of individuals or genomic regions, and genotype imputation is used to infer genotypes for the remaining individuals or regions without sequencing data. However, not all variants can be well imputed, and the current state-of-the-art imputation quality metric, denoted as standard Rsq, is poorly calibrated for lower-frequency variants. Here, we propose MagicalRsq, a machine-learning-based method that integrates variant-level imputation and population genetics statistics, to provide a better calibrated imputation quality metric. Leveraging WGS data from the Cystic Fibrosis Genome Project (CFGP), and whole-exome sequence data from UK BioBank (UKB), we performed comprehensive experiments to evaluate the performance of MagicalRsq compared to standard Rsq for partially sequenced studies. We found that MagicalRsq aligns better with true R2 than standard Rsq in almost every situation evaluated, for both European and African ancestry samples. For example, when applying models trained from 1,992 CFGP sequenced samples to an independent 3,103 samples with no sequencing but TOPMed imputation from array genotypes, MagicalRsq, compared to standard Rsq, achieved net gains of 1.4 million rare, 117k low-frequency, and 18k common variants, where net gains were gained numbers of correctly distinguished variants by MagicalRsq over standard Rsq. MagicalRsq can serve as an improved post-imputation quality metric and will benefit downstream analysis by better distinguishing well-imputed variants from those poorly imputed. MagicalRsq is freely available on GitHub.

TOP-LD: A tool to explore linkage disequilibrium with TOPMed whole-genome sequence data.

Current publicly available tools that allow rapid exploration of linkage disequilibrium (LD) between markers (e.g., HaploReg and LDlink) are based on whole-genome sequence (WGS) data from 2,504 individuals in the 1000 Genomes Project. Here, we present TOP-LD, an online tool to explore LD inferred with high-coverage (∼30×) WGS data from 15,578 individuals in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. TOP-LD provides a significant upgrade compared to current LD tools, as the TOPMed WGS data provide a more comprehensive representation of genetic variation than the 1000 Genomes data, particularly for rare variants and in the specific populations that we analyzed. For example, TOP-LD encompasses LD information for 150.3, 62.2, and 36.7 million variants for European, African, and East Asian ancestral samples, respectively, offering 2.6- to 9.1-fold increase in variant coverage compared to HaploReg 4.0 or LDlink. In addition, TOP-LD includes tens of thousands of structural variants (SVs). We demonstrate the value of TOP-LD in fine-mapping at the GGT1 locus associated with gamma glutamyltransferase in the African ancestry participants in UK Biobank. Beyond fine-mapping, TOP-LD can facilitate a wide range of applications that are based on summary statistics and estimates of LD. TOP-LD is freely available online.

Transcriptome-wide association study in UK Biobank Europeans identifies associations with blood cell traits.

Previous genome-wide association studies (GWAS) of hematological traits have identified over 10 000 distinct trait-specific risk loci. However, at these loci, the underlying causal mechanisms remain incompletely characterized. To elucidate novel biology and better understand causal mechanisms at known loci, we performed a transcriptome-wide association study (TWAS) of 29 hematological traits in 399 835 UK Biobank (UKB) participants of European ancestry using gene expression prediction models trained from whole blood RNA-seq data in 922 individuals. We discovered 557 gene-trait associations for hematological traits distinct from previously reported GWAS variants in European populations. Among the 557 associations, 301 were available for replication in a cohort of 141 286 participants of European ancestry from the Million Veteran Program. Of these 301 associations, 108 replicated at a strict Bonferroni adjusted threshold ($\alpha$= 0.05/301). Using our TWAS results, we systematically assigned 4261 out of 16 900 previously identified hematological trait GWAS variants to putative target genes. Compared to coloc, our TWAS results show reduced specificity and increased sensitivity in external datasets to assign variants to target genes.

A systematic evaluation of Hi-C data enhancement methods for enhancing PLAC-seq and HiChIP data.

The three-dimensional organization of chromatin plays a critical role in gene regulation. Recently developed technologies, such as HiChIP and proximity ligation-assisted ChIP-Seq (PLAC-seq) (hereafter referred to as HP for brevity), can measure chromosome spatial organization by interrogating chromatin interactions mediated by a protein of interest. While offering cost-efficiency over genome-wide unbiased high-throughput chromosome conformation capture (Hi-C) data, HP data remain sparse at kilobase (Kb) resolution with the current sequencing depth in the order of 108 reads per sample. Deep learning models, including HiCPlus, HiCNN, HiCNN2, DeepHiC and Variationally Encoded Hi-C Loss Enhancer (VEHiCLE), have been developed to enhance the sequencing depth of Hi-C data, but their performance on HP data has not been benchmarked. Here, we performed a comprehensive evaluation of HP data sequencing depth enhancement using models developed for Hi-C data. Specifically, we analyzed various HP data, including Smc1a HiChIP data of the human lymphoblastoid cell line GM12878, H3K4me3 PLAC-seq data of four human neural cell types as well as of mouse embryonic stem cells (mESC), and mESC CCCTC-binding factor (CTCF) PLAC-seq data. Our evaluations lead to the following three findings: (i) most models developed for Hi-C data achieve reasonable performance when applied to HP data (e.g. with Pearson correlation ranging 0.76-0.95 for pairs of loci within 300 Kb), and the enhanced datasets lead to improved statistical power for detecting long-range chromatin interactions, (ii) models trained on HP data outperform those trained on Hi-C data and (iii) most models are transferable across cell types. Our results provide a general guideline for HP data enhancement using existing methods designed for Hi-C data.

Rare tandem repeat expansions associate with genes involved in synaptic and neuronal signaling functions in schizophrenia.

Tandem repeat expansions (TREs) are associated with over 60 monogenic disorders and have recently been implicated in complex disorders such as cancer and autism spectrum disorder. The role of TREs in schizophrenia is now emerging. In this study, we have performed a genome-wide investigation of TREs in schizophrenia. Using genome sequence data from 1154 Swedish schizophrenia cases and 934 ancestry-matched population controls, we have detected genome-wide rare (<0.1% population frequency) TREs that have motifs with a length of 2-20 base pairs. We find that the proportion of individuals carrying rare TREs is significantly higher in the schizophrenia group. There is a significantly higher burden of rare TREs in schizophrenia cases than in controls in genic regions, particularly in postsynaptic genes, in genes overlapping brain expression quantitative trait loci, and in brain-expressed genes that are differentially expressed between schizophrenia cases and controls. We demonstrate that TRE-associated genes are more constrained and primarily impact synaptic and neuronal signaling functions. These results have been replicated in an independent Canadian sample that consisted of 252 schizophrenia cases of European ancestry and 222 ancestry-matched controls. Our results support the involvement of rare TREs in schizophrenia etiology.

Health-related quality of life of people with type 1 diabetes: An IMI2 SOPHIA post hoc analysis of FUTURE and ADJUNCT-ONE.

AIM: To characterize and stratify health-related quality of life in individuals with type 1 diabetes (T1D) using body mass index (BMI) and clustering analysis. MATERIAL AND METHODS: Baseline data on individuals with T1D were pooled from two studies. A post hoc analysis of health-related quality of life, measured using the 36-item Short-Form questionnaire, was performed, referenced to the 2010 US general population. Descriptive statistics were presented for the pooled cohort and per BMI category. K-means clustering was performed. One-way analysis of variance was conducted to examine differences in clinical characteristics between clusters. RESULTS: The pooled cohort consisted of 2256 individuals with T1D (age: 45.4 ± 15.0 years, BMI: 26.2 ± 4.6 kg/m2, diabetes duration: 22.7 ± 13.5 years). All quality-of-life domains were slightly lower than 50(the general population's mean), except for vitality. Individuals with a BMI ≥30 kg/m2 reported lower scores for bodily pain, physical functioning, general health, and vitality. A first cluster with a high and a second cluster with a low quality of life were identified, with significant differences in the mental (Cluster 1: 53.8 ± 6.8 vs. Cluster 2: 39.5 ± 10.7; p < 0.001) and physical component summary scores (Cluster 1: 49.6 ± 6.3 vs. Cluster 2: 35.2 ± 12.0; p < 0.001), which exceeded differences found between BMI categories. CONCLUSIONS: In our population of people living with T1D, higher BMI may have adversely impacted physical domains of quality of life, but larger differences between the high- and low-quality-of-life cluster indicate that more factors play a role.

A large-scale transcriptome-wide association study (TWAS) of 10 blood cell phenotypes reveals complexities of TWAS fine-mapping.

Hematological measures are important intermediate clinical phenotypes for many acute and chronic diseases and are highly heritable. Although genome-wide association studies (GWAS) have identified thousands of loci containing trait-associated variants, the causal genes underlying these associations are often uncertain. To better understand the underlying genetic regulatory mechanisms, we performed a transcriptome-wide association study (TWAS) to systematically investigate the association between genetically predicted gene expression and hematological measures in 54,542 Europeans from the Genetic Epidemiology Research on Aging cohort. We found 239 significant gene-trait associations with hematological measures; we replicated 71 associations at p < 0.05 in a TWAS meta-analysis consisting of up to 35,900 Europeans from the Women's Health Initiative, Atherosclerosis Risk in Communities Study, and BioMe Biobank. Additionally, we attempted to refine this list of candidate genes by performing conditional analyses, adjusting for individual variants previously associated with hematological measures, and performed further fine-mapping of TWAS loci. To facilitate interpretation of our findings, we designed an R Shiny application to interactively visualize our TWAS results by integrating them with additional genetic data sources (GWAS, TWAS from multiple reference panels, conditional analyses, known GWAS variants, etc.). Our results and application highlight frequently overlooked TWAS challenges and illustrate the complexity of TWAS fine-mapping.

Gangs, violence, and fear: punitive Darwinism in El Salvador.

This article evaluates the factors impacting support for tough on crime policies in El Salvador. Examining theoretical and empirical scholarly work, we look at how fear, together with social and political contexts drive public appetite for punitive policies towards criminals. We show that President Nayib Bukele is responding to public opinion and has implemented tough on crime policies at the expense of human rights violations and democratic institutions. Society favors candidates who are the "toughest" against criminal actors. Political candidates from all sides of the ideological spectrum tap into the fear of the populace to win votes, leading to punitive Darwinism. We provide an empirical assessment of which theoretically relevant factors are statistically associated with punitivism in the Salvadoran context, using multiple regression analysis of high-quality public opinion survey data from LAPOP.

Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations.

Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11-34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count <10 (including singletons) in the imputation target samples, average information content rescued was >86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10-15] in African populations, rs11549407 with lower HGB [p = 1.5x10-12] and HCT [p = 8.8x10-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations.

HPRep: Quantifying Reproducibility in HiChIP and PLAC-Seq Datasets.

HiChIP and PLAC-Seq are emerging technologies for studying genome-wide long-range chromatin interactions mediated by the protein of interest, enabling more sensitive and cost-efficient interrogation of protein-centric chromatin conformation. However, due to the unbalanced read distribution introduced by protein immunoprecipitation, existing reproducibility measures developed for Hi-C data are not appropriate for the analysis of HiChIP and PLAC-Seq data. Here, we present HPRep, a stratified and weighted correlation metric derived from normalized contact counts, to quantify reproducibility in HiChIP and PLAC-Seq data. We applied HPRep to multiple real datasets and demonstrate that HPRep outperforms existing reproducibility measures developed for Hi-C data. Specifically, we applied HPRep to H3K4me3 PLAC-Seq data from mouse embryonic stem cells and mouse brain tissues as well as H3K27ac HiChIP data from human lymphoblastoid cell line GM12878 and leukemia cell line K562, showing that HPRep can more clearly separate among pseudo-replicates, real replicates, and non-replicates. Furthermore, in an H3K4me3 PLAC-Seq dataset consisting of 11 samples from four human brain cell types, HPRep demonstrated the expected clustering of data that could not be achieved by existing methods developed for Hi-C data, highlighting the need for a reproducibility metric tailored to HiChIP and PLAC-Seq data.

The disaster worker resiliency training program: a randomized clinical trial.

OBJECTIVES: Disaster workers are at elevated risk for mental health problems as a result of trauma exposures during response efforts. One possible way to prevent mental health problems is to build-up coping resources that promote resilience to the effects of disaster work. The primary aim of this study was to evaluate the efficacy of a resilience building workshop, the Disaster Worker Resiliency Training Program (DWRT), in disaster workers previously exposed to Hurricane Sandy. METHODS: Disaster workers (N = 167) were randomly assigned to the DWRT workshop (n = 78) or a waitlist (n = 89). Workers completed self-report measures on healthy lifestyle behaviors, perceived stress, depression, and Posttraumatic Stress Disorder (PTSD) symptoms at baseline and 3-month follow-up. They also completed a measure assessing subsequent trauma-exposure between the baseline and 3-month post-intervention. RESULTS: Participants in the workshop condition, as compared to those in a waitlist control, reported significantly greater improvements from pre-intervention (T1) to 3-month follow-up (T2) in healthy lifestyle behaviors (η2 = .03; p = .03), stress management (η2 = .03, p = .04), and spiritual growth (η2 = .03, p = .02). Among participants reporting subsequent trauma exposures between T1 and T2  (n = 101), participants in the waitlist condition, were more likely to report significant increases in perceived stress (η2 = .07, p < .01), PTSD (η2 = .05, p = .03), and depression (η2 = .07, p < .01) symptoms. CONCLUSIONS: Participation in the resilience workshop promoted engagement in positive health behaviors and reduced the incidence of mental health symptoms, especially when administered prior to a repeat trauma exposure. Further research is needed to evaluate the long-term health effects of participation in the program.

Age and African-American race impact the validity and reliability of the asthma control test in persistent asthmatics.

BACKGROUND: The Asthma Control Test (ACT) is widely used to assess asthma control, yet the validity and reliability of the test have not been specifically evaluated in adolescents or African-Americans. We conducted a prospective psychometric study of the ACT in African-American (AA) and non-African-American (nAA) adolescents with persistent asthma, with emphasis on the clinical utility of the test for medical decision making. METHODS: Participants completed the ACT and performed spirometry. A physician conducted a guidelines-based assessment of asthma control, blinded to the ACT score. Study procedures were repeated 6-8 weeks later. The ACT-based asthma control assessment was compared to physician assessment. RESULTS: For baseline and follow-up visits, internal consistency, as measured using Cronbach's alpha, was 0.80 and 0.81 in AA teens and 0.80 and 0.83 in nAA teens. Intraclass correlation coefficients were 0.59 and 0.76 in AA and nAA teens, respectively, with stable asthma control over time. Agreement between ACT and physician assessment was moderate in AA teens and fair in nAA teens. An ACT score of ≤19 showed reduced sensitivity for not well controlled asthma in both groups, while a score of ≤21 had the greatest area under the ROC curve. ACT scores were marginally responsive to change in control status. CONCLUSIONS: Concerns for the ACT's ability to detect uncontrolled asthma in adolescents emphasizes the need for a more comprehensive evaluation of asthma control in clinical settings. A higher threshold ACT score to define not well controlled asthma may be needed if the ACT is to be used for medical decision making. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02671643 , NCT02662413 .

The Central Role of Bicarbonate in the Electrochemical Reduction of Carbon Dioxide on Gold.

Much effort has been devoted in the development of efficient catalysts for electrochemical reduction of CO2. Molecular level understanding of electrode-mediated process, particularly the role of bicarbonate in increasing CO2 reduction rates, is still lacking due to the difficulty of directly probing the electrochemical interface. We developed a protocol to observe normally invisible reaction intermediates with a surface enhanced spectroscopy by applying square-wave potential profiles. Further, we demonstrate that bicarbonate, through equilibrium exchange with dissolved CO2, rather than the supplied CO2, is the primary source of carbon in the CO formed at the Au electrode by a combination of in situ spectroscopic, isotopic labeling, and mass spectroscopic investigations. We propose that bicarbonate enhances the rate of CO production on Au by increasing the effective concentration of dissolved CO2 near the electrode surface through rapid equilibrium between bicarbonate and dissolved CO2.

Syd/JIP3 and JNK signaling are required for myonuclear positioning and muscle function.

Highlighting the importance of proper intracellular organization, many muscle diseases are characterized by mispositioned myonuclei. Proper positioning of myonuclei is dependent upon the microtubule motor proteins, Kinesin-1 and cytoplasmic Dynein, and there are at least two distinct mechanisms by which Kinesin and Dynein move myonuclei. The motors exert forces both directly on the nuclear surface and from the cell cortex via microtubules. How these activities are spatially segregated yet coordinated to position myonuclei is unknown. Using Drosophila melanogaster, we identified that Sunday Driver (Syd), a homolog of mammalian JNK-interacting protein 3 (JIP3), specifically regulates Kinesin- and Dynein-dependent cortical pulling of myonuclei without affecting motor activity near the nucleus. Specifically, Syd mediates Kinesin-dependent localization of Dynein to the muscle ends, where cortically anchored Dynein then pulls microtubules and the attached myonuclei into place. Proper localization of Dynein also requires activation of the JNK signaling cascade. Furthermore, Syd functions downstream of JNK signaling because without Syd, JNK signaling is insufficient to promote Kinesin-dependent localization of Dynein to the muscle ends. The significance of Syd-dependent myonuclear positioning is illustrated by muscle-specific depletion of Syd, which impairs muscle function. Moreover, both myonuclear spacing and locomotive defects in syd mutants can be rescued by expression of mammalian JIP3 in Drosophila muscle tissue, indicating an evolutionarily conserved role for JIP3 in myonuclear movement and highlighting the utility of Drosophila as a model for studying mammalian development. Collectively, we implicate Syd/JIP3 as a novel regulator of myogenesis that is required for proper intracellular organization and tissue function.

Ion channel-kinase TRPM7 is required for maintaining cardiac automaticity.

Sick sinus syndrome and atrioventricular block are common clinical problems, often necessitating permanent pacemaker placement, yet the pathophysiology of these conditions remains poorly understood. Here we show that Transient Receptor Potential Melastatin 7 (TRPM7), a divalent-permeant channel-kinase of unknown function, is highly expressed in embryonic myocardium and sinoatrial node (SAN) and is required for cardiac automaticity in these specialized tissues. TRPM7 disruption in vitro, in cultured embryonic cardiomyocytes, significantly reduces spontaneous Ca(2+) transient firing rates and is associated with robust down-regulation of Hcn4, Cav3.1, and SERCA2a mRNA. TRPM7 knockdown in zebrafish, global murine cardiac Trpm7 deletion (KO(αMHC-Cre)), and tamoxifen-inducible SAN restricted Trpm7 deletion (KO(HCN4-CreERT2)) disrupts cardiac automaticity in vivo. Telemetered and sedated KO(αMHC-Cre) and KO(HCN4-CreERT2) mice show episodes of sinus pauses and atrioventricular block. Isolated SAN from KO(αMHC-Cre) mice exhibit diminished Ca(2+) transient firing rates with a blunted diastolic increase in Ca(2+). Action potential firing rates are diminished owing to slower diastolic depolarization. Accordingly, Hcn4 mRNA and the pacemaker current, I(f), are diminished in SAN from both KO(αMHC-Cre) and KO(HCN4-CreERT2) mice. Moreover, heart rates of KO(αMHC-Cre) mice are less sensitive to the selective I(f) blocker ivabradine, and acute application of the recently identified TRPM7 blocker FTY720 has no effect on action potential firing rates of wild-type SAN cells. We conclude that TRPM7 influences diastolic membrane depolarization and automaticity in SAN indirectly via regulation of Hcn4 expression.