An expression-directed linear mixed model discovering low-effect genetic variants.

Detecting genetic variants with low-effect sizes using a moderate sample size is difficult, hindering downstream efforts to learn pathology and estimating heritability. In this work, by utilizing informative weights learned from training genetically predicted gene expression models, we formed an alternative approach to estimate the polygenic term in a linear mixed model. Our linear mixed model estimates the genetic background by incorporating their relevance to gene expression. Our protocol, expression-directed linear mixed model, enables the discovery of subtle signals of low-effect variants using moderate sample size. By applying expression-directed linear mixed model to cohorts of around 5,000 individuals with either binary (WTCCC) or quantitative (NFBC1966) traits, we demonstrated its power gain at the low-effect end of the genetic etiology spectrum. In aggregate, the additional low-effect variants detected by expression-directed linear mixed model substantially improved estimation of missing heritability. Expression-directed linear mixed model moves precision medicine forward by accurately detecting the contribution of low-effect genetic variants to human diseases.

Sequential multi-omics analysis identifies clinical phenotypes and predictive biomarkers for long COVID.

The post-acute sequelae of COVID-19 (PASC), also known as long COVID, is often associated with debilitating symptoms and adverse multisystem consequences. We obtain plasma samples from 117 individuals during and 6 months following their acute phase of infection to comprehensively profile and assess changes in cytokines, proteome, and metabolome. Network analysis reveals sustained inflammatory response, platelet degranulation, and cellular activation during convalescence accompanied by dysregulation in arginine biosynthesis, methionine metabolism, taurine metabolism, and tricarboxylic acid (TCA) cycle processes. Furthermore, we develop a prognostic model composed of 20 molecules involved in regulating T cell exhaustion and energy metabolism that can reliably predict adverse clinical outcomes following discharge from acute infection with 83% accuracy and an area under the curve (AUC) of 0.96. Our study reveals pertinent biological processes during convalescence that differ from acute infection, and it supports the development of specific therapies and biomarkers for patients suffering from long COVID.

Kupffer cell-like syncytia replenish resident macrophage function in the fibrotic liver.

Kupffer cells (KCs) are localized in liver sinusoids but extend pseudopods to parenchymal cells to maintain their identity and serve as the body's central bacterial filter. Liver cirrhosis drastically alters vascular architecture, but how KCs adapt is unclear. We used a mouse model of liver fibrosis and human tissue to examine immune adaptation. Fibrosis forced KCs to lose contact with parenchymal cells, down-regulating "KC identity," which rendered them incapable of clearing bacteria. Commensals stimulated the recruitment of monocytes through CD44 to a spatially distinct vascular compartment. There, recruited monocytes formed large aggregates of multinucleated cells (syncytia) that expressed phenotypical KC markers and displayed enhanced bacterial capture ability. Syncytia formed via CD36 and were observed in human cirrhosis as a possible antimicrobial defense that evolved with fibrosis.

Methylene blue in combination with sunlight as a low cost and effective disinfection method for coronavirus-contaminated PPE.

Using the Murine Hepatitis Virus (MHV) A59 coronavirus as a SARS-CoV-2 animal surrogate, we validated that methylene blue (MB) in combination with sunlight exposure is a robust, fast, and low-cost decontamination method for PPE that should be added to the toolbox of practical pandemic preparedness.

Reconstructing SARS-CoV-2 infection dynamics through the phylogenetic inference of unsampled sources of infection.

The COVID-19 pandemic has illustrated the importance of infection tracking. The role of asymptomatic, undiagnosed individuals in driving infections within this pandemic has become increasingly evident. Modern phylogenetic tools that take into account asymptomatic or undiagnosed individuals can help guide public health responses. We finetuned established phylogenetic pipelines using published SARS-CoV-2 genomic data to examine reasonable estimate transmission networks with the inference of unsampled infection sources. The system utilised Bayesian phylogenetics and TransPhylo to capture the evolutionary and infection dynamics of SARS-CoV-2. Our analyses gave insight into the transmissions within a population including unsampled sources of infection and the results aligned with epidemiological observations. We were able to observe the effects of preventive measures in Canada's "Atlantic bubble" and in populations such as New York State. The tools also inferred the cross-species disease transmission of SARS-CoV-2 transmission from humans to lions and tigers in New York City's Bronx Zoo. These phylogenetic tools offer a powerful approach in response to both the COVID-19 and other emerging infectious disease outbreaks.

Evaluating the effectiveness of ensemble voting in improving the accuracy of consensus signals produced by various DTWA algorithms from step-current signals generated during nanopore sequencing.

Nanopore sequencing device analysis systems simultaneously generate multiple picoamperage current signals representing the passage of DNA or RNA nucleotides ratcheted through a biomolecule nanopore array by motor proteins. Squiggles are a noisy and time-distorted representation of an underlying nucleotide sequence, "gold standard model", due to experimental and algorithmic artefacts. Other research fields use dynamic time warped-space averaging (DTWA) algorithms to produce a consensus signal from multiple time-warped sources while preserving key features distorted by standard, linear-averaging approaches. We compared the ability of DTW Barycentre averaging (DBA), minimize mean (MM) and stochastic sub-gradient descent (SSG) DTWA algorithms to generate a consensus signal from squiggle-space ensembles of RNA molecules Enolase, Sequin R1-71-1 and Sequin R2-55-3 without knowledge of their associated gold standard model. We propose techniques to identify the leader and distorted squiggle features prior to DTWA consensus generation. New visualization and warping-path metrics are introduced to compare consensus signals and the best estimate of the "true" consensus, the study's gold standard model. The DBA consensus was the best match to the gold standard for both Sequin studies but was outperformed in the Enolase study. Given an underlying common characteristic across a squiggle ensemble, we objectively evaluate a novel "voting scheme" that improves the local similarity between the consensus signal and a given fraction of the squiggle ensemble. While the gold standard is not used during voting, the increase in the match of the final voted-on consensus to the underlying Enolase and Sequin gold standard sequences provides an indirect success measure for the proposed voting procedure in two ways: First is the decreased least squares warped distance between the final consensus and the gold model, and second, the voting generates a final consensus length closer to the known underlying RNA biomolecule length. The results suggest considerable potential in marrying squiggle analysis and voted-on DTWA consensus signals to provide low-noise, low-distortion signals. This will lead to improved accuracy in detecting nucleotides and their deviation model due to chemical modifications (a.k.a. epigenetic information). The proposed combination of ensemble voting and DTWA has application in other research fields involving time-distorted, high entropy signals.

Characterization of microglial transcriptomes in the brain and spinal cord of mice in early and late experimental autoimmune encephalomyelitis using a RiboTag strategy.

Microglia play an important role in the pathogenesis of multiple sclerosis and the mouse model of MS, experimental autoimmune encephalomyelitis (EAE). To more fully understand the role of microglia in EAE we characterized microglial transcriptomes before the onset of motor symptoms (pre-onset) and during symptomatic EAE. We compared the transcriptome in brain, where behavioral changes are initiated, and spinal cord, where damage is revealed as motor and sensory deficits. We used a RiboTag strategy to characterize ribosome-bound mRNA only in microglia without incurring possible transcriptional changes after cell isolation. Brain and spinal cord samples clustered separately at both stages of EAE, indicating regional heterogeneity. Differences in gene expression were observed in the brain and spinal cord of pre-onset and symptomatic animals with most profound effects in the spinal cord of symptomatic animals. Canonical pathway analysis revealed changes in neuroinflammatory pathways, immune functions and enhanced cell division in both pre-onset and symptomatic brain and spinal cord. We also observed a continuum of many pathways at pre-onset stage that continue into the symptomatic stage of EAE. Our results provide additional evidence of regional and temporal heterogeneity in microglial gene expression patterns that may help in understanding mechanisms underlying various symptomology in MS.

Oxford nanopore sequencing in clinical microbiology and infection diagnostics.

Extended turnaround times and large economic costs hinder the usage of currently applied screening methods for bacterial pathogen identification (ID) and antimicrobial susceptibility testing. This review provides an overview of current detection methods and their usage in a clinical setting. Issues of timeliness and cost could soon be circumvented, however, with the emergence of detection methods involving single molecule sequencing technology. In the context of bringing diagnostics closer to the point of care, we examine the current state of Oxford Nanopore Technologies (ONT) products and their interaction with third-party software/databases to assess their capabilities for ID and antimicrobial resistance (AMR) prediction. We outline and discuss a potential diagnostic workflow, enumerating (1) rapid sample prep kits, (2) ONT hardware/software and (3) third-party software and databases to improve the cost, accuracy and turnaround times for ID and AMR. Multiple studies across a range of infection types support that the speed and accuracy of ONT sequencing is now such that established ID and AMR prediction tools can be used on its outputs, and so it can be harnessed for near real time, close to the point-of-care diagnostics in common clinical circumstances.

Stirred suspension bioreactors maintain naïve pluripotency of human pluripotent stem cells.

Due to their ability to standardize key physiological parameters, stirred suspension bioreactors can potentially scale the production of quality-controlled pluripotent stem cells (PSCs) for cell therapy application. Because of differences in bioreactor expansion efficiency between mouse (m) and human (h) PSCs, we investigated if conversion of hPSCs, from the conventional "primed" pluripotent state towards the "naïve" state prevalent in mPSCs, could be used to enhance hPSC production. Through transcriptomic enrichment of mechano-sensing signaling, the expression of epigenetic regulators, metabolomics, and cell-surface protein marker analyses, we show that the stirred suspension bioreactor environment helps maintain a naïve-like pluripotent state. Our research corroborates that converting hPSCs towards a naïve state enhances hPSC manufacturing and indicates a potentially important role for the stirred suspension bioreactor's mechanical environment in maintaining naïve-like pluripotency.

A shared core microbiome in soda lakes separated by large distances.

In alkaline soda lakes, concentrated dissolved carbonates establish productive phototrophic microbial mats. Here we show how microbial phototrophs and autotrophs contribute to this exceptional productivity. Amplicon and shotgun DNA sequencing data of microbial mats from four Canadian soda lakes indicate the presence of > 2,000 species of Bacteria and Eukaryotes. We recover metagenome-assembled-genomes for a core microbiome of < 100 abundant bacteria, present in all four lakes. Most of these are related to microbes previously detected in sediments of Asian alkaline lakes, showing that common selection principles drive community assembly from a globally distributed reservoir of alkaliphile biodiversity. Detection of > 7,000 proteins show how phototrophic populations allocate resources to specific processes and occupy complementary niches. Carbon fixation proceeds by the Calvin-Benson-Bassham cycle, in Cyanobacteria, Gammaproteobacteria, and, surprisingly, Gemmatimonadetes. Our study provides insight into soda lake ecology, as well as a template to guide efforts to engineer biotechnology for carbon dioxide conversion.

Differential microglia and macrophage profiles in human IDH-mutant and -wild type glioblastoma.

Microglia and macrophages are the largest component of the inflammatory infiltrate in glioblastoma (GBM). However, whether there are differences in their representation and activity in the prognostically-favorable isocitrate dehydrogenase (IDH)-mutated compared to -wild type GBMs is unknown. Studies on human specimens of untreated IDH-mutant GBMs are rare given they comprise 10% of all GBMs and often present at lower grades, receiving treatments prior to dedifferentiation that can drastically alter microglia and macrophage phenotypes. We were able to obtain large samples of four previously untreated IDH-mutant GBM. Using flow cytometry, immunofluorescence techniques with automated segmentation protocols that quantify at the individual-cell level, and comparison between single-cell RNA-sequencing (scRNA-seq) databases of human GBM, we discerned dissimilarities between GBM-associated microglia and macrophages (GAMMs) in IDH-mutant and -wild type GBMs. We found there are significantly fewer GAMM in IDH-mutant GBMs, but they are more pro-inflammatory, suggesting this contributes to the better prognosis of these tumors. Our pro-inflammatory score which combines the expression of inflammatory markers (CD68/HLA-A, -B, -C/TNF/CD163/IL10/TGFB2), Iba1 intensity, and GAMM surface area also indicates that more pro-inflammatory GAMMs are associated with longer overall survival independent of IDH status. Interrogation of scRNA-seq databases demonstrates microglia in IDH-mutants are mainly pro-inflammatory, while anti-inflammatory macrophages that upregulate genes such as FCER1G and TYROBP predominate in IDH-wild type GBM. Taken together, these observations are the first head-to-head comparison of GAMMs in treatment-naïve IDH-mutant versus -wild type GBMs. Our findings highlight biological disparities in the innate immune microenvironment related to IDH prognosis that can be exploited for therapeutic purposes.

Characterization of a Unique Form of Arrhythmic Cardiomyopathy Caused by Recessive Mutation in LEMD2.

Nuclear envelope proteins have been shown to play an important role in the pathogenesis of inherited dilated cardiomyopathy. Here, we present a remarkable cardiac phenotype caused by a homozygous LEMD2 mutation in patients of the Hutterite population with juvenile cataract. Mutation carriers develop arrhythmic cardiomyopathy with mild impairment of left ventricular systolic function but severe ventricular arrhythmias leading to sudden cardiac death. Affected cardiac tissue from a deceased patient and fibroblasts exhibit elongated nuclei with abnormal condensed heterochromatin at the periphery. The patient fibroblasts demonstrate cellular senescence and reduced proliferation capacity, which may suggest an involvement of LEM domain containing protein 2 in chromatin remodeling processes and premature aging.

Glucocorticoid-driven transcriptomes in human airway epithelial cells: commonalities, differences and functional insight from cell lines and primary cells.

BACKGROUND: Glucocorticoids act on the glucocorticoid receptor (GR; NR3C1) to resolve inflammation and, as inhaled corticosteroids (ICS), are the cornerstone of treatment for asthma. However, reduced efficacy in severe disease or exacerbations indicates a need to improve ICS actions. METHODS: Glucocorticoid-driven transcriptomes were compared using PrimeView microarrays between primary human bronchial epithelial (HBE) cells and the model cell lines, pulmonary type II A549 and bronchial epithelial BEAS-2B cells. RESULTS: In BEAS-2B cells, budesonide induced (≥2-fold, P ≤ 0.05) or, in a more delayed fashion, repressed (≤0.5-fold, P ≤ 0.05) the expression of 63, 133, 240, and 257 or 15, 56, 236, and 344 mRNAs at 1, 2, 6, and 18 h, respectively. Within the early-induced mRNAs were multiple transcriptional activators and repressors, thereby providing mechanisms for the subsequent modulation of gene expression. Using the above criteria, 17 (BCL6, BIRC3, CEBPD, ERRFI1, FBXL16, FKBP5, GADD45B, IRS2, KLF9, PDK4, PER1, RGCC, RGS2, SEC14L2, SLC16A12, TFCP2L1, TSC22D3) induced and 8 (ARL4C, FLRT2, IER3, IL11, PLAUR, SEMA3A, SLC4A7, SOX9) repressed mRNAs were common between A549, BEAS-2B and HBE cells at 6 h. As absolute gene expression change showed greater commonality, lowering the cut-off (≥1.25 or ≤ 0.8-fold) within these groups produced 93 induced and 82 repressed genes in common. Since large changes in few mRNAs and/or small changes in many mRNAs may drive function, gene ontology (GO)/pathway analyses were performed using both stringency criteria. Budesonide-induced genes showed GO term enrichment for positive and negative regulation of transcription, signaling, proliferation, apoptosis, and movement, as well as FOXO and PI3K-Akt signaling pathways. Repressed genes were enriched for inflammatory signaling pathways (TNF, NF-κB) and GO terms for cytokine activity, chemotaxis and cell signaling. Reduced growth factor expression and effects on proliferation and apoptosis were highlighted. CONCLUSIONS: While glucocorticoids repress mRNAs associated with inflammation, prior induction of transcriptional activators and repressors may explain longer-term responses to these agents. Furthermore, positive and negative effects on signaling, proliferation, migration and apoptosis were revealed. Since many such gene expression changes occurred in human airways post-ICS inhalation, the effects observed in cell lines and primary HBE cells in vitro may be relevant to ICS in vivo.

The lifelong impact of fetal growth restriction on cardiac development.

BACKGROUND: Maternal nutrient restriction (MNR) is a widespread cause of fetal growth restriction (FGR), an independent predictor of heart disease and cardiovascular mortality. Our objective was to examine the developmental and long-term impact of MNR-induced FGR on cardiac structure in a model that closely mimics human development. METHODS: A reduction in total caloric intake spanning pregestation through to lactation in guinea pig sows was used to induce FGR. Proliferation, differentiation, and apoptosis of cardiomyocytes were assessed in late-gestation fetal, neonatal, and adult guinea pig hearts. Proteomic analysis and pathway enrichment were performed on fetal hearts. RESULTS: Cardiomyocyte proliferation and the number of mononucleated cells were enhanced in the MNR-FGR fetal and neonatal heart, suggesting a delay in cardiomyocyte differentiation. In fetal hearts of MNR-FGR animals, apoptosis was markedly elevated and the total number of cardiomyocytes reduced, the latter remaining so throughout neonatal and into adult life. A reduction in total cardiomyocyte number in adult MNR-FGR hearts was accompanied by exaggerated hypertrophy and a disorganized architecture. Pathway analysis identified genes related to cell proliferation, differentiation, and survival. CONCLUSIONS: FGR influences cardiomyocyte development during critical windows of development, leading to a permanent deficiency in cardiomyocyte number and compensatory hypertrophy in a rodent model that recapitulates human development.

Transgenic mice overexpressing desmocollin-2 (DSC2) develop cardiomyopathy associated with myocardial inflammation and fibrotic remodeling.

BACKGROUND: Arrhythmogenic cardiomyopathy is an inherited heart muscle disorder leading to ventricular arrhythmias and heart failure, mainly as a result of mutations in cardiac desmosomal genes. Desmosomes are cell-cell junctions mediating adhesion of cardiomyocytes; however, the molecular and cellular mechanisms underlying the disease remain widely unknown. Desmocollin-2 is a desmosomal cadherin serving as an anchor molecule required to reconstitute homeostatic intercellular adhesion with desmoglein-2. Cardiac specific lack of desmoglein-2 leads to severe cardiomyopathy, whereas overexpression does not. In contrast, the corresponding data for desmocollin-2 are incomplete, in particular from the view of protein overexpression. Therefore, we developed a mouse model overexpressing desmocollin-2 to determine its potential contribution to cardiomyopathy and intercellular adhesion pathology. METHODS AND RESULTS: We generated transgenic mice overexpressing DSC2 in cardiac myocytes. Transgenic mice developed a severe cardiac dysfunction over 5 to 13 weeks as indicated by 2D-echocardiography measurements. Corresponding histology and immunohistochemistry demonstrated fibrosis, necrosis and calcification which were mainly localized in patches near the epi- and endocardium of both ventricles. Expressions of endogenous desmosomal proteins were markedly reduced in fibrotic areas but appear to be unchanged in non-fibrotic areas. Furthermore, gene expression data indicate an early up-regulation of inflammatory and fibrotic remodeling pathways between 2 to 3.5 weeks of age. CONCLUSION: Cardiac specific overexpression of desmocollin-2 induces necrosis, acute inflammation and patchy cardiac fibrotic remodeling leading to fulminant biventricular cardiomyopathy.

An Algorithm Measuring Donor Cell-Free DNA in Plasma of Cellular and Solid Organ Transplant Recipients That Does Not Require Donor or Recipient Genotyping.

Cell-free DNA (cfDNA) has significant potential in the diagnosis and monitoring of clinical conditions. However, accurately and easily distinguishing the relative proportion of DNA molecules in a mixture derived from two different sources (i.e., donor and recipient tissues after transplantation) is challenging. In human cellular transplantation, there is currently no useable method to detect in vivo engraftment, and blood-based non-invasive tests for allograft rejection in solid organ transplantation are either non-specific or absent. Elevated levels of donor cfDNA have been shown to correlate with solid organ rejection, but complex methodology limits implementation of this promising biomarker. We describe a cost-effective method to quantify donor cfDNA in recipient plasma using a panel of high-frequency single nucleotide polymorphisms, next-generation (semiconductor) sequencing, and a novel mixture model algorithm. In vitro, our method accurately and rapidly determined donor:recipient DNA admixture. For in vivo testing, donor cfDNA was serially quantified in an infant with a urea cycle disorder after receiving six daily infusions of donor liver cells. Donor cfDNA isolated from 1 to 2 ml of recipient plasma was detected as late as 24 weeks after infusion suggesting engraftment. The percentage of circulating donor cfDNA was also assessed in pediatric and adult heart transplant recipients undergoing routine endomyocardial biopsy with levels observed to be stable over time and generally measuring <1% in cases without moderate or severe cellular rejection. Unlike existing non-invasive methods used to define the proportion of donor cfDNA in solid organ transplant patients, our assay does not require sex mismatch, donor genotyping, or whole-genome sequencing and potentially has broad application to detect cellular engraftment or allograft injury after transplantation.

Rapid-Onset Obesity with Hypothalamic Dysfunction, Hypoventilation, and Autonomic Dysregulation (ROHHAD): exome sequencing of trios, monozygotic twins and tumours.

BACKGROUND: Rapid-onset Obesity with Hypothalamic Dysfunction, Hypoventilation, and Autonomic Dysregulation (ROHHAD) is thought to be a genetic disease caused by de novo mutations, though causative mutations have yet to be identified. We searched for de novo coding mutations among a carefully-diagnosed and clinically homogeneous cohort of 35 ROHHAD patients. METHODS: We sequenced the exomes of seven ROHHAD trios, plus tumours from four of these patients and the unaffected monozygotic (MZ) twin of one (discovery cohort), to identify constitutional and somatic de novo sequence variants. We further analyzed this exome data to search for candidate genes under autosomal dominant and recessive models, and to identify structural variations. Candidate genes were tested by exome or Sanger sequencing in a replication cohort of 28 ROHHAD singletons. RESULTS: The analysis of the trio-based exomes found 13 de novo variants. However, no two patients had de novo variants in the same gene, and additional patient exomes and mutation analysis in the replication cohort did not provide strong genetic evidence to implicate any of these sequence variants in ROHHAD. Somatic comparisons revealed no coding differences between any blood and tumour samples, or between the two discordant MZ twins. Neither autosomal dominant nor recessive analysis yielded candidate genes for ROHHAD, and we did not identify any potentially causative structural variations. CONCLUSIONS: Clinical exome sequencing is highly unlikely to be a useful diagnostic test in patients with true ROHHAD. As ROHHAD has a high risk for fatality if not properly managed, it remains imperative to expand the search for non-exomic genetic risk factors, as well as to investigate other possible mechanisms of disease. In so doing, we will be able to confirm objectively the ROHHAD diagnosis and to contribute to our understanding of obesity, respiratory control, hypothalamic function, and autonomic regulation.

SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models.

BACKGROUND: Locating the protein-coding genes in novel genomes is essential to understanding and exploiting the genomic information but it is still difficult to accurately predict all the genes. The recent availability of detailed information about transcript structure from high-throughput sequencing of messenger RNA (RNA-Seq) delineates many expressed genes and promises increased accuracy in gene prediction. Computational gene predictors have been intensively developed for and tested in well-studied animal genomes. Hundreds of fungal genomes are now or will soon be sequenced. The differences of fungal genomes from animal genomes and the phylogenetic sparsity of well-studied fungi call for gene-prediction tools tailored to them. RESULTS: SnowyOwl is a new gene prediction pipeline that uses RNA-Seq data to train and provide hints for the generation of Hidden Markov Model (HMM)-based gene predictions and to evaluate the resulting models. The pipeline has been developed and streamlined by comparing its predictions to manually curated gene models in three fungal genomes and validated against the high-quality gene annotation of Neurospora crassa; SnowyOwl predicted N. crassa genes with 83% sensitivity and 65% specificity. SnowyOwl gains sensitivity by repeatedly running the HMM gene predictor Augustus with varied input parameters and selectivity by choosing the models with best homology to known proteins and best agreement with the RNA-Seq data. CONCLUSIONS: SnowyOwl efficiently uses RNA-Seq data to produce accurate gene models in both well-studied and novel fungal genomes. The source code for the SnowyOwl pipeline (in Python) and a web interface (in PHP) is freely available from http://sourceforge.net/projects/snowyowl/.

Titin mutation in familial restrictive cardiomyopathy.

BACKGROUND: Familial restrictive cardiomyopathy (RCM) caused by a single gene mutation is the least common of the inherited cardiomyopathies. Only a few RCM-causing mutations have been described. Most mutations causing RCM are located in sarcomere protein genes which also cause hypertrophic cardiomyopathy (HCM). Other genes associated with RCM include the desmin and familial amyloidosis genes. In the present study we describe familial RCM with severe heart failure triggered by a de novo mutation in TTN, encoding the huge muscle filament protein titin. METHODS AND RESULTS: Family members underwent physical examination, ECG and Doppler echocardiogram studies. The family comprised 6 affected individuals aged 12-35 years. Linkage to candidate loci was performed, followed by gene sequencing. Candidate loci/gene analysis excluded 18 candidate genes but showed segregation with a common haplotype surrounding the TTN locus. Sequence analysis identified a de novo mutation within exon 266 of the TTN gene, resulting in the replacement of tyrosine by cysteine. p.Y7621C affects a highly conserved region in the protein within a fibronectin-3 domain, belonging to the A/I junction region of titin. No other disease-causing mutation was identified in cardiomyopathy genes by whole exome sequencing. CONCLUSIONS: Our study shows, for the first time, that mutations in TTN can cause restrictive cardiomyopathy. The giant filament titin is considered to be a determinant of a resting tension of the sarcomere and this report provides genetic evidence of its crucial role in diastolic function.

Genomic compartmentalization of gene families encoding core components of metazoan signaling systems.

To investigate the role of gene localization and genome organization in cell-cell signalling and regulation, we mapped the distribution pattern of gene families that comprise core components of intercellular communication networks. Our study is centered on the distinct evolutionarily conserved metazoan signalling pathways that employ proteins in the receptor tyrosine kinase, WNT, hedgehog, NOTCH, Janus kinase/STAT, transforming growth factor beta, and nuclear hormone receptor protein families. Aberrant activity of these signalling pathways is closely associated with the promotion and maintenance of human cancers. The cataloguing and mapping of genes encoding these signalling proteins and comparisons across species has led us to propose that the genome can be subdivided into six genome-wide primary linkage groups (PLGs). PLGs are composed of assemblages of gene families that are often mutually exclusive, raising the possibility of unique functional identities for each group. Examination of the localization patterns of genes with distinct functions in signal transduction demonstrates dichotomous segregation patterns. For example, gene families of cell-surface receptors localize to genomic compartments that are distinct from the locations of their cognate ligand gene families. Additionally, genes encoding negative-acting components of signalling pathways (inhibitors and antagonists) are topologically separated from their positive regulators and other signal transducer genes. We, therefore, propose the existence of conserved genomic territories that encode key proteins required for the proper activity of metazoan signaling and regulatory systems. Disruption in this pattern of topologic genomic organization may contribute to aberrant regulation in hereditary or acquired diseases such as cancer. We further propose that long-range looping genomic regulatory interactions may provide a mechanism favouring the remarkable retention of these conserved gene clusters during chordate evolution.