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Genomic researchers are increasingly utilizing commercial cloud platforms (CCPs) to manage their data and analytics needs. Commercial clouds allow researchers to grow their storage and analytics capacity on demand, keeping pace with expanding project data footprints and enabling researchers to avoid large capital expenditures while paying only for IT capacity consumed by their project. Cloud computing also allows researchers to overcome common network and storage bottlenecks encountered when combining or re-analysing large datasets. However, cloud computing presents a new set of challenges. Without adequate security controls, the risk of unauthorised access may be higher for data stored on the cloud. In addition, regulators are increasingly mandating data access patterns and specific security protocols on the storage and use of genomic data to safeguard rights of the study participants. While CCPs provide tools for security and regulatory compliance, utilising these tools to build the necessary controls required for cloud solutions is not trivial as such skill sets are not commonly found in a genomics lab. The Research Assets Provisioning and Tracking Online Repository (RAPTOR) by the Genome Institute of Singapore is a cloud native genomics data repository and analytics platform focusing on security and regulatory compliance. Using a “five-safes” framework (Safe Purpose, Safe People, Safe Settings, Safe Data and Safe Output), RAPTOR provides security and governance controls to data contributors and users leveraging cloud computing for sharing and analysis of large genomic datasets without the risk of security breaches or running afoul of regulations. RAPTOR can also enable data federation with other genomic data repositories using GA4GH community-defined standards, allowing researchers to boost the statistical power of their work and overcome geographic and ancestry limitations of data sets

Background: Heart Failure (HF) is driven by the interactions of multiple genetic, epigenetic, and environmental factors both within and between the cell types of the heart. Our lab uses the Hybrid Mouse Diversity Panel (HMDP), a large cohort of inbred mouse strains, to perform systems genetics analyses of isoproterenol-induced cardiac hypertrophy and failure by leveraging the benefits of a curated model organism population to identify key drivers of phenotype. We are now expanding this study into the DNA methylome, which has been convincingly linked to cardiac-associated phenotypic changes in prior studies. Methods and Results: Using Reduced Representational Bisulfite Sequencing, we profiled left ventricular tissue samples from 88 HMDP strains subjected to isoproterenol challenge (30 mg/kg/day for 21 days) and matched control animals. We identified nearly 170,000 CpGs whose methylation status varies across the HMDP and 179 significant associations (FDR of 5%) between CpG methylation and phenotypic variation using the epigenome-wide association study algorithm MACAU, including 37 associations linking CpG methylation in unchallenged hearts to 19 post-challenge phenotypes. To identify high-confidence candidate genes, we combined our loci with data from the Wellcome Trust Mouse Genomes Resource, transcriptomic and metabolomic data from the HMDP, Hi-C data, and cell-type-specific gene expression and methylation data from healthy and failing mouse hearts. We are systematically querying the resulting 78 candidates using in silico and in vitro approaches. These genes include Mospd3 , which is associated with right ventricular hypertrophy and whose knockdown in vitro results in reduced cardiomyocyte hypertrophy and changes to hypertrophy-related gene expression. Also observed were Atp9a , whose expression levels are associated with significant global DNA methylation changes between control and ISO-treated animals and whose knockdown likewise causes a reduction in observed cellular hypertrophy, and Mdga1 , whose promoter methylation status is linked to changes in 5% of expressed genes of the heart during heart failure. Further analysis and in vivo study of these loci will further our understanding of the role of DNA methylation in heart failure.

SUMMARY Complex ethological behaviors could be constructed from finite modules that are reproducible functional units of behavior. Here, we test this idea for foraging and develop methods to dissect rich behavior patterns in mice. We uncover discrete modules of foraging behavior reproducible across different strains and ages, as well as nonmodular behavioral sequences. Modules differ in terms of form, expression frequency, and expression timing and are expressed in a probabilistically determined order. Modules shape economic patterns of feeding, exposure, activity, and perseveration responses. The modular architecture of foraging changes developmentally, and different developmental, genetic, and parental effects are found to shape the expression of specific modules. Dissecting modules from complex patterns is powerful for phenotype analysis. We discover that both parental alleles of the imprinted Prader-Willi syndrome gene Magel2 are functional in mice but regulate different modules. Our study found that complex economic patterns are built from finite, genetically controlled modules., Graphical Abstract, In Brief The principles and mechanisms involved in constructing complex behavior patterns are not well defined. Stacher Hörndli et al. find that complex foraging patterns in mice are constructed from finite modules, defined as significantly reproducible behavioral sequences. Modules are expressed in a probabilistically defined order to construct complex patterns and controlled by genetic mechanisms.

AIMS To determine the fetal and maternal outcomes in pregnant women with Glucokinase-Maturity onset diabetes of the young (GCK-MODY). METHODS We studied the obstetric and perinatal outcomes in 99 pregnancies of 34 women with GCK-MODY. The mutation status of the offspring was known in 29 and presumed in 33. Clinical outcomes were determined and compared between affected (n = 39) and unaffected (n = 23) offspring. RESULTS 59% of pregnancies were treated with diet alone and 41% received insulin. Birthweight, percentage of large for gestational age (LGA) and caesarean section (CS) in GCK-unaffected offspring was significantly higher than in GCK-affected offspring (4.0 ± 0.7 vs. 3.4 ± 0.4 kg, p = 0.001), 15 (65%) vs. 5(13%) (p = 0.00006) and 17 (74%) vs. 11 (28%) (p = 0.001), respectively. We observed an earlier gestational age at delivery on insulin in unaffected offspring (38.3 ± 1.0 vs. 39.5 ± 1.5 weeks, p = 0.03) with no significant change in LGA (9 (82%) vs. 6 (50%); p = 0.12), and a higher rate of CS (8 [73%] vs. 3 [11%]; p

Functional connectivity from resting-state functional MRI (rsfMRI) is typically represented as a symmetric positive definite (SPD) matrix. Analysis methods that exploit the Riemannian geometry of SPD matrices appropriately adhere to the positive definite constraint, unlike Euclidean methods. Recently proposed approaches for rsfMRI analysis have achieved high accuracy on public datasets, but are computationally intensive and difficult to interpret. In this paper, we show that we can get comparable results using connectivity matrices under the log-Euclidean and affine-invariant Riemannian metrics with relatively simple and interpretable models. On ABIDE Preprocessed dataset, our methods classify autism versus control subjects with 71.1% accuracy. We also show that Riemannian methods beat baseline in regressing connectome features to subject autism severity scores.

We previously reported a study of heart failure in a large cohort of inbred mouse strains, the Hybrid Mouse Diversity Panel (HMDP), treated with the beta-adrenergic agonist isoproterenol, which identified over 30 genome-wide significant loci for heart failure-related traits. Our approach combined systems-level tools with the benefits of a curated model organism population to identify genetic variations that drive heart failure. We now expand this study into the epigenome. Recent research has demonstrated that DNA methylation affects the progression of cardiovascular phenotypes. This research suggests that DNA methylation may serve as an additional marker of genes involved in heart failure-associated phenotypes. Using Reduced Representational Bisulfite Sequencing, we profiled left ventricular tissue samples from 88 strains of the HMDP both before and after isoproterenol challenge (30 mg/kg/day for 21 days). We identified approximately 168,000 CpGs that vary across the panel and associated them with a set of phenotypes in both control and treated animals using the epigenome-wide association study (EWAS) algorithm MACAU. 179 significant associations were recovered at an FDR of 5%, including loci that associated pre-treatment CpG methylation with 19 different post-treatment phenotypes. By combining these EWAS loci with information from the Wellcome Trust Mouse Genomes Resource and prior work done in the heart failure HMDP, we identify several high-confidence candidate genes, including Coro1a , a gene whose pre-treatment promoter methylation status predicts post-treatment wall thickening and Eprs , which predicts right ventricular weight post-treatment. Mospd3 , a gene that was associated with right ventricular weight post-treatment in both EWAS and GWAS analyses was studied further using neonatal rat ventricular myocytes. This in vitro work demonstrates that Mospd3 knockdown results in reduced cellular hypertrophy and changes to hypertrophy-related gene expression. Further analysis of the EWAS loci using in vitro and in vivo techniques will likely validate additional genes and elucidate how DNA methylation acts to regulate pathways underlying heart failure.

Background Heart failure is associated with altered gene expression and DNA methylation. De novo DNA methylation is associated with gene silencing, but its role in cardiac pathology remains incompletely understood. We hypothesized that inhibition of DNA methyltransferases (DNMT) might prevent the deregulation of gene expression and the deterioration of cardiac function under pressure overload (PO). To test this hypothesis, we evaluated a DNMT inhibitor in PO in rats and analysed DNA methylation in cardiomyocytes. Methods and results Young male Wistar rats were subjected to PO by transverse aortic constriction (TAC) or to sham surgery. Rats from both groups received solvent or 12.5 mg/kg body weight of the non-nucleosidic DNMT inhibitor RG108, initiated on the day of the intervention. After 4 weeks, we analysed cardiac function by MRI, fibrosis with Sirius Red staining, gene expression by RNA sequencing and qPCR, and DNA methylation by reduced representation bisulphite sequencing (RRBS). RG108 attenuated the ~70% increase in heart weight/body weight ratio of TAC over sham to 47% over sham, partially rescued reduced contractility, diminished the fibrotic response and the downregulation of a set of genes including Atp2a2 (SERCA2a) and Adrb1 (beta1-adrenoceptor). RG108 was associated with significantly lower global DNA methylation in cardiomyocytes by ~2%. The differentially methylated pathways were “cardiac hypertrophy”, “cell death” and “xenobiotic metabolism signalling”. Among these, “cardiac hypertrophy” was associated with significant methylation differences in the group comparison sham vs. TAC, but not significant between sham+RG108 and TAC+RG108 treatment, suggesting that RG108 partially prevented differential methylation. However, when comparing TAC and TAC+RG108, the pathway cardiac hypertrophy was not significantly differentially methylated. Conclusions DNMT inhibitor treatment is associated with attenuation of cardiac hypertrophy and moderate changes in cardiomyocyte DNA methylation. The potential mechanistic link between these two effects and the role of non-myocytes need further clarification.

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. As a potential epigenetic biomarker, DNA methylation differs between healthy and diseased hearts. However, its association according to disease severity has not yet been studied. Here, we sought to investigate how DNA methylation (DNAm) differs across HF disease severity, and study the use of a DNMT methyltransferase inhibitor RG108 on DNAm and its effect on heart function. A fixed dose of Isoprenaline (ISO), or saline control (SAL), administered to a hybrid mouse diversity panel (HMDP) consisting of 85 classical and recombinant inbred mouse strains produced a range of cardiac hypertrophy and/or LV dilatation. Left ventricles were harvested and subjected to genome-wide cardiac DNAm profiling by Reduced Representation Bisulfite Sequencing (RRBS). Unsupervised clustering of the top 1% most variable CpG methylation segregated strains to their genetic origin. Disregarding strain-specific methylation differences, differential methylation between ISO and SAL unexpectedly categorised mice into mild and severe disease responders. In the severe-responder strain BTBRT, the pharmacological DNMT methyltransferase inhibitor, RG108, rescued disease from ISO-response, with accompanying evidence of gene expression recovery. This work establishes the range of cardiac differential DNAm correlating according to disease severity. It displays the involvement of DNA methylation-dependent gene expression changes that turns out to be unique, despite different mouse strain backgrounds. This gives further proof of principle that cardiac DNAm changes represent novel biomarkers for disease stratification and consequent targeted therapy.

Identifying genetic markers for heterogeneous complex diseases such as heart failure has been challenging, and may require prohibitively large cohort sizes in genome-wide association studies (GWAS) in order to meet genome-wide statistical significance. On the other hand, chromatin quantitative trait loci (QTL), elucidated by direct epigenetic profiling of specific human tissues, may contribute towards prioritising sub-threshold variants for disease-association. Here, we captured non-coding genetic variants by performing enhancer H3K27ac ChIP-seq in 70 human control and end-stage failing hearts, mapping out a comprehensive catalogue of 47,321 putative human heart enhancers. 3,897 differential acetylation peaks (FDR 5%) pointed to pathways altered in heart failure (HF). To identify cardiac histone acetylation QTLs (haQTLs), we regressed out confounding factors including HF disease status, and employed the G-SCI test to call out 1,680 haQTLs (FDR 10%). RNA-seq performed on the same heart samples proved a subset of haQTLs to have significant association also to gene expression (expression QTLs), either in cis (180), or through long range interactions (81), identified by Hi-C and Hi-ChIP performed on a subset of hearts. We validated 2 of the haQTLs through base editing to show that the presence of those SNPs indeed affects gene expression in human embryonic stem cells-derived cardiomyocytes. Furthermore, a concordant relationship between the gain or disruption of transcription factor (TF) binding motifs, inferred from alternative alleles at the haQTLs, implied a surprising direct association between these specific TF and local histone acetylation in human hearts. Finally, 62 unique loci were identified by colocalisation of haQTLs with heart-related GWAS datasets. Disease-association for these new loci may indeed be mediated through modification of H3K27-acetylation enrichment and their corresponding gene expression differences.

Identifying genetic markers for heterogeneous complex diseases such as heart failure has been challenging, and may require prohibitively large cohort sizes in genome-wide association studies (GWAS) in order to demonstrate statistical significance1. On the other hand, chromatin quantitative trait loci (QTL), elucidated by direct epigenetic profiling of specific human tissues, may contribute towards prioritising variants for disease-association. Here, we captured non-coding genetic variants by performing enhancer H3K27ac ChIP-seq in 70 human control and end-stage failing hearts, mapping out a comprehensive catalogue of 47,321 putative human heart enhancers. 3,897 differential acetylation peaks (FDR < 0.05) pointed to recognizable pathways altered in heart failure (HF). To identify cardiac histone acetylation QTLs (haQTLs), we regressed out confounding factors including HF disease status, and employed the G-SCI test2 to call out 1,680 haQTLs (FDR < 0.1). A subset of these showed significant association to gene expression, either in cis (180), or through long range interactions (81), identified by Hi-C and Hi-ChIP performed on a subset of hearts. Furthermore, a concordant relationship was found between the gain or disruption of specific transcription factor (TF) binding motifs, inferred from alternative alleles at the haQTLs, associated with altered H3K27ac peak heights. Finally, colocalisation of our haQTLs with heart-related GWAS datasets allowed us to identify 62 unique loci. Disease-association for these new loci may indeed be mediated through modification of H3K27-acetylation enrichment and their corresponding gene expression differences.

SUMMARYComplex ethological behaviors could be constructed from modules that are discrete functional units of behavior with a genetic basis. Here, we test this idea for foraging, and develop a paradigm to dissect foraging patterns in mice. We uncover discrete behavioral modules linked to round trip excursions from the home. Machine learning reveals 59 modules across different genetic backgrounds and ages. Different modules develop at different ages and are linked to different aspects of economic behavior, including memory, reward, risk and effort responses. Crosses of distant mouse strains reveal that parental and genetic effects shape foraging differently, and parental effects grow stronger with age. Specific behavioral modules, genes and pathways are found to be sensitive to parental effects. One candidate gene, Magel2, is linked to Prader-Willi Syndrome and shaped the expression of discrete modules in an age-dependent manner. Our results reveal building blocks for normal and abnormal economic behavior patterns.HIGHLIGHTSIdentification of 59 economic behavior modules underlying foragingDiscrete modules are linked to memory, reward, risk and effort responsesGenetic and parental effects shape foraging by changing module expressionMagel2, a Prader-Willi Syndrome gene, affects specific modules at specific ages

Complex ethological behavior patterns could be constructed from modules that are discrete functional units of behavior. Here, we test this idea for foraging and develop a paradigm to dissect rich foraging patterns in mice. We uncover discrete behavioral modules linked to round trip excursions from the home. Machine learning reveals 59 modules across different genetic backgrounds and ages. Different modules develop at different ages and are linked to different aspects of economic behavior, including memory, reward, risk and effort responses. Crosses of distant mouse strains reveal that parental and genetic effects shape different foraging patterns by altering module expression, and parental effects grow stronger with age. Specific modules, genes and pathways are found to be sensitive to parental effects. One candidate gene, Magel2, is linked to Prader-Willi Syndrome and shaped the expression of specific modules at later ages. Our results reveal building blocks for normal and abnormal economic behavior patterns.

Systems biology approaches to studying heart failure in humans are hampered by numerous environmental factors and inciting incidents which combine to complicate the application of standard population-based tools and algorithms to the syndrome. We recently reported a study of heart failure in a large cohort of inbred mouse strains (the Hybrid Mouse Diversity Panel; HMDP) treated with the beta-adrenergic agonist isoproterenol. We demonstrated that it was possible to combine systems-level tools with the benefits of an animal model to capture and identify numerous genetic variations which drive heart failure. Recent research on the epigenome has identified changes to DNA methylation which affect the progression of cardiovascular diseases and suggests that DNA methylation may serve as an important additional marker or even driver of genes involved in heart failure-associated phenotypes. We have supplemented our prior study by completing reduced representational bisulfite sequencing on 88 strains from our panel both with and without catecholamine challenge. We have identified 75,000 CpGs which vary among the strains of the HMDP across the genome. Each CpG was mapped to the genome using GWAS to identify methylation quantitative trait loci (mQTLs). These mQTLs were then grouped together to identify mQTL hotspots, regions on the genome which regulate a sizable fractions of all observed CpGs. We then overlapped these hotspots with hotspots which regulate the expression of gene transcripts. Three genomic regions were identified as multi-omic master regulators which affect both DNA methylation and gene expression for over 5% of the expressed transcripts and varying CpGs. Closer examination of these loci identified the serine peptidase inhibitor Serpina3n as a likely candidate gene for the regulation of DNA methylation, gene expression and cardiac phenotypes. Subsequent in vitro and in vivo work demonstrate that Serpina3n knockdown results in reduced cellular hypertrophy and changes to hypertrophy-related gene expression. Further analysis of the other master regulatory regions will likely reveal additional genes which will improve our understanding of how DNA methylation acts to regulate pathways underlying heart failure.

Our study explored evaluative beliefs of failure to see whether positive and negative beliefs of failure are bivariate in nature within three domains of an adolescent's life (academic, social, and athletic) and how such beliefs are differentially linked to the importance of a domain, the frequency of failure in a domain, and the extremity of negative emotions experienced when encountering failure in a domain. A total of 163 Chinese Singaporean students in Secondary 3 and 4 (Grades 9 and 10) from two Singapore schools participated in the study by completing a questionnaire. Results from various analyses converged to demonstrate that evaluative beliefs could be distinguished by both valence (positive and negative) and domain (academic, social, and athletic). The six evaluative beliefs were also distinguished from failure attributions. While there was consensus in what constituted negative beliefs of failure across domains, positive beliefs of failure showed some domain specificity, with unique aspects in particular domains (e.g., the inevitability of failure only in the academic domain). Positive and negative beliefs in the different domains were correlated among themselves, but positive and negative beliefs were uncorrelated within (except for academic) and across domains. Positive and negative beliefs were also differentially linked to domain importance, failure frequency, and extremity of negative emotion. Unexpectedly, domain importance was not linked to negative beliefs but was linked to positive beliefs, while positive and negative beliefs showed domain-specific links with failure frequency. As expected, however, negative beliefs were (positively) linked to extremity of negative emotions while positive beliefs were not linked to such extremity. The conceptual, substantive, and practical implications of these results are discussed.

The patency of synthetic cardiovascular grafts in the long run is synonymous with their ability to inhibit the processes of intimal hyperplasia, thrombosis and calcification. In the human body, the endothelium of blood vessels exhibits characteristics that inhibit such processes. As such it is not surprising that research in tissue engineering is directed towards replicating the functionality of the natural endothelium in cardiovascular grafts. This can be done either by seeding the endothelium within the lumen of the grafts prior to implantation or by designing the graft such that in situ endothelialisation takes place after implantation. Due to certain difficulties identified with in vitro endothelialisation, in situ endothelialisation, which will be the focus of this article, has garnered interest in the last years. To promote in situ endothelialisation, the following aspects can be taken into account: (1) Endothelial progenital cell mobilization, adhesion and proliferation; (2) Regulating differentiation of progenitor cells to mature endothelium; (3) Preventing thrombogenesis and inflammation during endothelialisation. This article aims to review and compile recent developments to promote the in situ endothelialisation of cardiovascular grafts and subsequently improve their patency, which can also have widespread implications in the field of tissue engineering.

A chromatin interaction analysis with paired-end tagging (ChIA-PET) approach is used to delineate chromatin interactions mediated by RNA polymerase II in several different stem-cell populations; putative long-range promoter–enhancer interactions are inferred, indicating that linear juxtaposition does not necessarily guide enhancer target selection and prevalent cell-specific enhancer usage. Gene transcription requires dynamic chromatin connectivity between promoters bound by RNA polymerase II and their corresponding distal-acting enhancers. In this paper the authors use the ChIA-PET (chromatin interaction analysis with paired-end tagging) approach to delineate chromatin interactions mediated by RNA polymerase II in embryonic stem cells, neural stem cells and neurosphere progenitor cells. Putative enhancer–promoter interactions can be inferred, and many enhancers associate with promoters located beyond their nearest active genes, indicating that linear juxtaposition does not necessarily guide enhancer target selection. This work illustrates the possible importance of underlying chromatin structures in nuclear function. In multicellular organisms, transcription regulation is one of the central mechanisms modelling lineage differentiation and cell-fate determination1. Transcription requires dynamic chromatin configurations between promoters and their corresponding distal regulatory elements2. It is believed that their communication occurs within large discrete foci of aggregated RNA polymerases termed transcription factories in three-dimensional nuclear space3. However, the dynamic nature of chromatin connectivity has not been characterized at the genome-wide level. Here, through a chromatin interaction analysis with paired-end tagging approach3,4,5 using an antibody that primarily recognizes the pre-initiation complexes of RNA polymerase II6, we explore the transcriptional interactomes of three mouse cells of progressive lineage commitment, including pluripotent embryonic stem cells7, neural stem cells8 and neurosphere stem/progenitor cells9. Our global chromatin connectivity maps reveal approximately 40,000 long-range interactions, suggest precise enhancer–promoter associations and delineate cell-type-specific chromatin structures. Analysis of the complex regulatory repertoire shows that there are extensive colocalizations among promoters and distal-acting enhancers. Most of the enhancers associate with promoters located beyond their nearest active genes, indicating that the linear juxtaposition is not the only guiding principle driving enhancer target selection. Although promoter–enhancer interactions exhibit high cell-type specificity, promoters involved in interactions are found to be generally common and mostly active among different cells. Chromatin connectivity networks reveal that the pivotal genes of reprogramming functions are transcribed within physical proximity to each other in embryonic stem cells, linking chromatin architecture to coordinated gene expression. Our study sets the stage for the full-scale dissection of spatial and temporal genome structures and their roles in orchestrating development.

DNA methylation, a well-known epigenetic modification in mammalian genomes, is important for development and health. Dysregulation of DNA methylation can cause abnormal gene regulation, leading to anomalous development and diseases. Until recently, the ability to understand the functions and dynamics of DNA methylation was limited by the availability of technologies for comprehensively characterizing methylation on a genome-wide scale. Rapid advances in high-throughput approaches (particularly next-generation sequencing), coupled with molecular techniques, have enabled unbiased genome-wide profiling of DNA modifications at single-base resolution and helped to elucidate their impact on gene regulation. Here, we discuss the development of genomic approaches to decipher the global methylome at single-base resolution, the challenges faced, and the emerging new insights. Our ability to decipher this important epigenetic modification and how it impacts gene expression will provide a framework for understanding numerous disease mechanisms, and suggest means to treat or prevent them in the future.

Mammalian genomes are viewed as functional organizations that orchestrate spatial and temporal gene regulation. CTCF, the most characterized insulator-binding protein, has been implicated as a key genome organizer. However, little is known about CTCF-associated higher-order chromatin structures at a global scale. Here we applied chromatin interaction analysis by paired-end tag (ChIA-PET) sequencing to elucidate the CTCF-chromatin interactome in pluripotent cells. From this analysis, we identified 1,480 cis- and 336 trans-interacting loci with high reproducibility and precision. Associating these chromatin interaction loci with their underlying epigenetic states, promoter activities, enhancer binding and nuclear lamina occupancy, we uncovered five distinct chromatin domains that suggest potential new models of CTCF function in chromatin organization and transcriptional control. Specifically, CTCF interactions demarcate chromatin-nuclear membrane attachments and influence proper gene expression through extensive cross-talk between promoters and regulatory elements. This highly complex nuclear organization offers insights toward the unifying principles that govern genome plasticity and function.

DNA methylation, a well-known epigenetic modification in mammalian genomes, is important for development and health. Dysregulation of DNA methylation can cause abnormal gene regulation, leading to anomalous development and diseases. Until recently, the ability to understand the functions and dynamics of DNA methylation was limited by the availability of technologies for comprehensively characterizing methylation on a genome-wide scale. Rapid advances in high-throughput approaches (particularly next-generation sequencing), coupled with molecular techniques, have enabled unbiased genome-wide profiling of DNA modifications at single-base resolution and helped to elucidate their impact on gene regulation. Here, we discuss the development of genomic approaches to decipher the global methylome at single-base resolution, the challenges faced, and the emerging new insights. Our ability to decipher this important epigenetic modification and how it impacts gene expression will provide a framework for understanding numerous disease mechanisms, and suggest means to treat or prevent them in the future.

DNA methylation is a critical epigenetic regulator in mammalian development. Here, we present a whole-genome comparative view of DNA methylation using bisulfite sequencing of three cultured cell types representing progressive stages of differentiation: human embryonic stem cells (hESCs), a fibroblastic differentiated derivative of the hESCs, and neonatal fibroblasts. As a reference, we compared our maps with a methylome map of a fully differentiated adult cell type, mature peripheral blood mononuclear cells (monocytes). We observed many notable common and cell-type-specific features among all cell types. Promoter hypomethylation (both CG and CA) and higher levels of gene body methylation were positively correlated with transcription in all cell types. Exons were more highly methylated than introns, and sharp transitions of methylation occurred at exon–intron boundaries, suggesting a role for differential methylation in transcript splicing. Developmental stage was reflected in both the level of global methylation and extent of non-CpG methylation, with hESC highest, fibroblasts intermediate, and monocytes lowest. Differentiation-associated differential methylation profiles were observed for developmentally regulated genes, including the HOX clusters, other homeobox transcription factors, and pluripotence-associated genes such as POU5F1, TCF3, and KLF4. Our results highlight the value of high-resolution methylation maps, in conjunction with other systems-level analyses, for investigation of previously undetectable developmental regulatory mechanisms.

Characterization of the functional components in mammalian genomes depends on our ability to completely elucidate the genetic and epigenetic regulatory networks of chromatin states and nuclear architecture. Such endeavors demand the availability of robust and effective approaches to characterizing protein-DNA associations in their native chromatin environments. Consider able progress has been made through the applica tion of chromatin immunoprecipitation (ChIP) to study chromatin biology in cells. Coupled with genome-wide analyses, ChIP-based assays enable us to take a global, unbiased and comprehensive view of transcriptional control, epigenetic regulation and chromatin structures, with high precision and versatility. The integrated knowledge derived from these studies is used to decipher gene regulatory networks and define genome organization. In this review, we discuss this powerful approach and its current advances. We also explore the possible future developments of ChIP-based approaches to interrogating long-range chromatin interactions and their impact on the mechanisms regulating gene expression.

In 2001, the Faculty of Law at the National University of Singapore embarked on a bold initiative to teach legal skills in a more determined and focused way than ever before in its L.L.B. Programme. This paper documents how the experience of teaching skills in the United States was adapted and re-created for Singapore. It describes the challenges and the responses fashioned to deal with intensive and interactive small group teaching, research and mooting. The paper calls for student and learning centeredness and a keen appreciation of their cultural and social assumptions.

DNA methylation plays a crucial role in higher organisms. Coupling bisulfite treatment with next generation sequencing enables the interrogation of 5-methylcytosine sites in the genome. However, bisulfite conversion introduces mismatches between the reads and the reference genome, which makes mapping of Illumina and SOLiD reads slow and inaccurate. BatMeth is an algorithm that integrates novel Mismatch Counting, List Filtering, Mismatch Stage Filtering and Fast Mapping onto Two Indexes components to improve unique mapping rate, speed and precision. Experimental results show that BatMeth is faster and more accurate than existing tools. BatMeth is freely available at http://code.google.com/p/batmeth/.

Nat. Genet. 43, 630–638 (2011); published online 19 June; corrected after print 11 July 2011 In the version of this article initially published, the accession codes section contained inaccuracies. The raw sequences and processed data generated from this study can be downloaded with accession number GSE28247.

SummaryTranscription factors (TFs) and their specific interactions with targets are crucial for specifying gene-expression programs. To gain insights into the transcriptional regulatory networks in embryonic stem (ES) cells, we use chromatin immunoprecipitation coupled with ultra-high-throughput DNA sequencing (ChIP-seq) to map the locations of 13 sequence-specific TFs (Nanog, Oct4, STAT3, Smad1, Sox2, Zfx, c-Myc, n-Myc, Klf4, Esrrb, Tcfcp2l1, E2f1, and CTCF) and 2 transcription regulators (p300 and Suz12). These factors are known to play different roles in ES-cell biology as components of the LIF and BMP signaling pathways, self-renewal regulators, and key reprogramming factors. Our study provides insights into the integration of the signaling pathways into the ES-cell-specific transcription circuitries. Intriguingly, we find specific genomic regions extensively targeted by different TFs. Collectively, the comprehensive mapping of TF-binding sites identifies important features of the transcriptional regulatory networks that define ES-cell identity.