Repression of pervasive antisense transcription is the primary role of fission yeast RNA polymerase II CTD serine 2 phosphorylation.

The RNA polymerase II carboxy-terminal domain (CTD) consists of conserved heptapeptide repeats that can be phosphorylated to influence distinct stages of the transcription cycle, including RNA processing. Although CTD-associated proteins have been identified, phospho-dependent CTD interactions have remained elusive. Proximity-dependent biotinylation (PDB) has recently emerged as an alternative approach to identify protein-protein associations in the native cellular environment. In this study, we present a PDB-based map of the fission yeast RNAPII CTD interactome in living cells and identify phospho-dependent CTD interactions by using a mutant in which Ser2 was replaced by alanine in every repeat of the fission yeast CTD. This approach revealed that CTD Ser2 phosphorylation is critical for the association between RNAPII and the histone methyltransferase Set2 during transcription elongation, but is not required for 3' end processing and transcription termination. Accordingly, loss of CTD Ser2 phosphorylation causes a global increase in antisense transcription, correlating with elevated histone acetylation in gene bodies. Our findings reveal that the fundamental role of CTD Ser2 phosphorylation is to establish a chromatin-based repressive state that prevents cryptic intragenic transcription initiation.

Placental IGFBP1 levels during early pregnancy and the risk of insulin resistance and gestational diabetes.

Reduced insulin sensitivity (insulin resistance) is a hallmark of normal physiology in late pregnancy and also underlies gestational diabetes mellitus (GDM). We conducted transcriptomic profiling of 434 human placentas and identified a positive association between insulin-like growth factor binding protein 1 gene (IGFBP1) expression in the placenta and insulin sensitivity at ~26 weeks gestation. Circulating IGFBP1 protein levels rose over the course of pregnancy and declined postpartum, which, together with high gene expression levels in our placenta samples, suggests a placental or decidual source. Higher circulating IGFBP1 levels were associated with greater insulin sensitivity (lesser insulin resistance) at ~26 weeks gestation in the same cohort and in two additional pregnancy cohorts. In addition, low circulating IGFBP1 levels in early pregnancy predicted subsequent GDM diagnosis in two cohorts of pregnant women. These results implicate IGFBP1 in the glycemic physiology of pregnancy and suggest a role for placental IGFBP1 deficiency in GDM pathogenesis.

Higher Maternal Body Mass Index Is Associated With Lower Placental Expression of EPYC: A Genome-Wide Transcriptomic Study.

CONTEXT: Elevated body mass index (BMI) in pregnancy is associated with adverse maternal and fetal outcomes. The placental transcriptome may elucidate molecular mechanisms underlying these associations. OBJECTIVE: We examined the association of first-trimester maternal BMI with the placental transcriptome in the Gen3G prospective cohort. METHODS: We enrolled participants at 5 to 16 weeks of gestation and measured height and weight. We collected placenta samples at delivery. We performed whole-genome RNA sequencing using Illumina HiSeq 4000 and aligned RNA sequences based on the GTEx v8 pipeline. We conducted differential gene expression analysis of over 15 000 genes from 450 placental samples and reported the change in normalized gene expression per 1-unit increase in log2 BMI (kg/m2) as a continuous variable using Limma Voom. We adjusted models for maternal age, fetal sex, gestational age at delivery, gravidity, and surrogate variables accounting for technical variability. We compared participants with BMI of 18.5 to 24.9 mg/kg2 (N = 257) vs those with obesity (BMI ≥30 kg/m2, N = 82) in secondary analyses. RESULTS: Participants' mean ± SD age was 28.2 ± 4.4 years and BMI was 25.4 ± 5.5 kg/m2 in early pregnancy. Higher maternal BMI was associated with lower placental expression of EPYC (slope = -1.94, false discovery rate [FDR]-adjusted P = 7.3 × 10-6 for continuous BMI; log2 fold change = -1.35, FDR-adjusted P = 3.4 × 10-3 for BMI ≥30 vs BMI 18.5-24.9 kg/m2) and with higher placental expression of IGFBP6, CHRDL1, and CXCL13 after adjustment for covariates and accounting for multiple testing (FDR < 0.05). CONCLUSION: Our genome-wide transcriptomic study revealed novel genes potentially implicated in placental biologic response to higher maternal BMI in early pregnancy.

Placental RNA sequencing implicates IGFBP1 in insulin sensitivity during pregnancy and in gestational diabetes.

Reduced insulin sensitivity (or greater insulin resistance) is a hallmark of normal physiology in late pregnancy and also underlies gestational diabetes mellitus (GDM) pathophysiology. We conducted transcriptomic profiling of 434 human placentas and identified a strong positive association between insulin-like growth factor binding protein 1 gene (IGFBP1) expression in the placenta and insulin sensitivity at ~ 26 weeks' gestation. Circulating IGFBP1 protein levels rose over the course of pregnancy and declined postpartum, which together with high placental gene expression levels, suggests a placental source. Higher circulating IGFBP1 levels were strongly associated with greater insulin sensitivity (lesser insulin resistance) at ~ 26 weeks' gestation in the same cohort and two additional pregnancy cohorts. In addition, low circulating IGFBP1 levels in early pregnancy predicted subsequent GDM diagnosis in two cohorts. These results implicate IGFBP1 in the glycemic physiology of pregnancy and suggest a role for placental IGFBP1 deficiency in GDM pathogenesis.

Genome-wide association study of placental weight identifies distinct and shared genetic influences between placental and fetal growth.

A well-functioning placenta is essential for fetal and maternal health throughout pregnancy. Using placental weight as a proxy for placental growth, we report genome-wide association analyses in the fetal (n = 65,405), maternal (n = 61,228) and paternal (n = 52,392) genomes, yielding 40 independent association signals. Twenty-six signals are classified as fetal, four maternal and three fetal and maternal. A maternal parent-of-origin effect is seen near KCNQ1. Genetic correlation and colocalization analyses reveal overlap with birth weight genetics, but 12 loci are classified as predominantly or only affecting placental weight, with connections to placental development and morphology, and transport of antibodies and amino acids. Mendelian randomization analyses indicate that fetal genetically mediated higher placental weight is causally associated with preeclampsia risk and shorter gestational duration. Moreover, these analyses support the role of fetal insulin in regulating placental weight, providing a key link between fetal and placental growth.

Pulse-SILAC and Interactomics Reveal Distinct DDB1-CUL4-Associated Factors, Cellular Functions, and Protein Substrates.

Cullin-RING finger ligases represent the largest family of ubiquitin ligases. They are responsible for the ubiquitination of ∼20% of cellular proteins degraded through the proteasome, by catalyzing the transfer of E2-loaded ubiquitin to a substrate. Seven cullins are described in vertebrates. Among them, cullin 4 (CUL4) associates with DNA damage-binding protein 1 (DDB1) to form the CUL4-DDB1 ubiquitin ligase complex, which is involved in protein ubiquitination and in the regulation of many cellular processes. Substrate recognition adaptors named DDB1/CUL4-associated factors (DCAFs) mediate the specificity of CUL4-DDB1 and have a short structural motif of approximately forty amino acids terminating in tryptophan (W)-aspartic acid (D) dipeptide, called the WD40 domain. Using different approaches (bioinformatics/structural analyses), independent studies suggested that at least sixty WD40-containing proteins could act as adaptors for the DDB1/CUL4 complex. To better define this association and classification, the interaction of each DCAFs with DDB1 was determined, and new partners and potential substrates were identified. Using BioID and affinity purification-mass spectrometry approaches, we demonstrated that seven WD40 proteins can be considered DCAFs with a high confidence level. Identifying protein interactions does not always lead to identifying protein substrates for E3-ubiquitin ligases, so we measured changes in protein stability or degradation by pulse-stable isotope labeling with amino acids in cell culture to identify changes in protein degradation, following the expression of each DCAF. In conclusion, these results provide new insights into the roles of DCAFs in regulating the activity of the DDB1-CUL4 complex, in protein targeting, and characterized the cellular processes involved.

A systematic approach to classify and characterize genomic islands driven by conjugative mobility using protein signatures.

Genomic islands (GIs) play a crucial role in the spread of antibiotic resistance, virulence factors and antiviral defense systems in a broad range of bacterial species. However, the characterization and classification of GIs are challenging due to their relatively small size and considerable genetic diversity. Predicting their intercellular mobility is of utmost importance in the context of the emerging crisis of multidrug resistance. Here, we propose a large-scale classification method to categorize GIs according to their mobility profile and, subsequently, analyze their gene cargo. We based our classification decision scheme on a collection of mobility protein motif definitions available in publicly accessible databases. Our results show that the size distribution of GI classes correlates with their respective structure and complexity. Self-transmissible GIs are usually the largest, except in Bacillota and Actinomycetota, accumulate antibiotic and phage resistance genes, and favour the use of a tyrosine recombinase to insert into a host's replicon. Non-mobilizable GIs tend to use a DDE transposase instead. Finally, although tRNA genes are more frequently targeted as insertion sites by GIs encoding a tyrosine recombinase, most GIs insert in a protein-encoding gene. This study is a stepping stone toward a better characterization of mobile GIs in bacterial genomes and their mechanism of mobility.

Chronic treatment with ATR and CHK1 inhibitors does not substantially increase the mutational burden of human cells.

DNA replication stress (RS) entails the frequent slow down and arrest of replication forks by a variety of conditions that hinder accurate and processive genome duplication. Elevated RS leads to genome instability, replication catastrophe and eventually cell death. RS is particularly prevalent in cancer cells and its exacerbation to unsustainable levels by chemotherapeutic agents remains a cornerstone of cancer treatments. The adverse consequences of RS are normally prevented by the ATR and CHK1 checkpoint kinases that stabilize stressed forks, suppress origin firing and promote cell cycle arrest when replication is perturbed. Specific inhibitors of these kinases have been developed and shown to potentiate RS and cell death in multiple in vitro cancer settings. Ongoing clinical trials are now probing their efficacy against various cancer types, either as single agents or in combination with mainstay chemotherapeutics. Despite their promise as valuable additions to the anti-cancer pharmacopoeia, we still lack a genome-wide view of the potential mutagenicity of these new drugs. To investigate this question, we performed chronic long-term treatments of TP53-depleted human cancer cells with ATR and CHK1 inhibitors (ATRi, AZD6738/ceralasertib and CHK1i, MK8776/SCH-900776). ATR or CHK1 inhibition did not significantly increase the mutational burden of cells, nor generate specific mutational signatures. Indeed, no notable changes in the numbers of base substitutions, short insertions/deletions and larger scale rearrangements were observed despite induction of replication-associated DNA breaks during treatments. Interestingly, ATR inhibition did induce a slight increase in closely-spaced mutations, a feature previously attributed to translesion synthesis DNA polymerases. The results suggest that ATRi and CHK1i do not have substantial mutagenic effects in vitro when used as standalone agents.

Enabling low-cost and robust essentiality studies with high-throughput transposon mutagenesis (HTTM).

Transposon-insertion sequencing (TIS) methods couple high density transposon mutagenesis with next-generation sequencing and are commonly used to identify essential or important genes in bacteria. However, this approach can be work-intensive and sometimes expensive depending on the selected protocol. The difficulty to process a high number of samples in parallel using standard TIS protocols often restricts the number of replicates that can be performed and limits the deployment of this technique to large-scale projects studying gene essentiality in various strains or growth conditions. Here, we report the development of a robust and inexpensive High-Throughput Transposon Mutagenesis (HTTM) protocol and validate the method using Escherichia coli strain BW25113, the parental strain of the KEIO collection. HTTM reliably provides high insertion densities with an average of one transposon every ≤20bp along with impressive reproducibility (Spearman correlation coefficients >0.94). A detailed protocol is available at protocol.io and a graphical version is also included with this article.

Motif conservation, stability, and host gene expression are the main drivers of snoRNA expression across vertebrates.

Small nucleolar RNAs (snoRNAs) are structured noncoding RNAs present in multiple copies within eukaryotic genomes. snoRNAs guide chemical modifications on their target RNA and regulate processes like ribosome assembly and splicing. Most human snoRNAs are embedded within host gene introns, the remainder being independently expressed from intergenic regions. We recently characterized the abundance of snoRNAs and their host gene across several healthy human tissues and found that the level of most snoRNAs does not correlate with that of their host gene, with the observation that snoRNAs embedded within the same host gene often differ drastically in abundance. To better understand the determinants of snoRNA expression, we trained machine learning models to predict whether snoRNAs are expressed or not in human tissues based on more than 30 collected features related to snoRNAs and their genomic context. By interpreting the models' predictions, we find that snoRNAs rely on conserved motifs, a stable global structure and terminal stem, and a transcribed locus to be expressed. We observe that these features explain well the varying abundance of snoRNAs embedded within the same host gene. By predicting the expression status of snoRNAs across several vertebrates, we notice that only one-third of all annotated snoRNAs are expressed per genome, as in humans. Our results suggest that ancestral snoRNAs disseminated within vertebrate genomes, sometimes leading to the development of new functions and a probable gain in fitness and thereby conserving features favorable to the expression of these few snoRNAs, the large remainder often degenerating into pseudogenes.

The mutational impact of Illudin S on human cells.

Illudin S (ILS) is a fungal sesquiterpene secondary metabolite with potent genotoxic and cytotoxic properties. Early genetic studies and more recent genome-wide CRISPR screens showed that Illudin-induced lesions are preferentially repaired by transcription-coupled nucleotide excision repair (TC-NER) with some contribution from post-replication repair pathways. In line with these results, Irofulven, a semi-synthetic ILS analog was recently shown to be particularly effective on cell lines and patient-derived xenografts with impaired NER (e.g. ERCC2/3 mutations), raising hope that ILS-derived molecules may soon enter the clinic. Despite the therapeutic potential of ILS and its analogs, we still lack a global understanding of their mutagenic potential. Here, we characterize the mutational signatures associated with chronic exposure to ILS in human cells. ILS treatment rapidly stalls DNA replication and transcription, leading to the activation of the replication stress response and the accumulation of DNA damage. Novel single and double base substitution signatures as well as a characteristic indel signature indicate that ILS treatment preferentially alkylates purine residues and induces oxidative stress, confirming prior in vitro data. Many mutation contexts exhibit a strong transcriptional strand bias, highlighting the contribution of TC-NER to the repair of ILS lesions. Finally, collateral mutations are also observed in response to ILS, suggesting a contribution of translesion synthesis pathways to ILS tolerance. Accordingly, ILS treatment led to the rapid recruitment of the Y-family DNA polymerase kappa onto chromatin, supporting its preferential use for ILS lesion bypass. Altogether, our work provides the first global assessment of the genomic impact of ILS, demonstrating the contribution of multiple DNA repair pathways to ILS resistance and mutagenicity.

First Trimester Plasma MicroRNA Levels Predict Risk of Developing Gestational Diabetes Mellitus.

Aims: Our objective is to identify first-trimester plasmatic miRNAs associated with and predictive of GDM. Methods: We quantified miRNA using next-generation sequencing in discovery (Gen3G: n = 443/GDM = 56) and replication (3D: n = 139/GDM = 76) cohorts. We have diagnosed GDM using a 75-g oral glucose tolerance test and the IADPSG criteria. We applied stepwise logistic regression analysis among replicated miRNAs to build prediction models. Results: We identified 17 miRNAs associated with GDM development in both cohorts. The prediction performance of hsa-miR-517a-3p|hsa-miR-517b-3p, hsa-miR-218-5p, and hsa-let7a-3p was slightly better than GDM classic risk factors (age, BMI, familial history of type 2 diabetes, history of GDM or macrosomia, and HbA1c) (AUC 0.78 vs. 0.75). MiRNAs and GDM classic risk factors together further improved the prediction values [AUC 0.84 (95% CI 0.73-0.94)]. These results were replicated in 3D, although weaker predictive values were obtained. We suggest very low and higher risk GDM thresholds, which could be used to identify women who could do without a diagnostic test for GDM and women most likely to benefit from an early GDM prevention program. Conclusions: In summary, three miRNAs combined with classic GDM risk factors provide excellent prediction values, potentially strong enough to improve early detection and prevention of GDM.

Maternal Body Mass Index Is Associated with Profile Variation in Circulating MicroRNAs at First Trimester of Pregnancy.

Many women enter pregnancy with overweight and obesity, which are associated with complications for both the expectant mother and her child. MicroRNAs (miRNAs) are short non-coding RNAs that regulate many biological processes, including energy metabolism. Our study aimed to identify first trimester plasmatic miRNAs associated with maternal body mass index (BMI) in early pregnancy. We sequenced a total of 658 plasma samples collected between the 4th and 16th week of pregnancy from two independent prospective birth cohorts (Gen3G and 3D). In each cohort, we assessed associations between early pregnancy maternal BMI and plasmatic miRNAs using DESeq2 R package, adjusting for sequencing run and lane, gestational age, maternal age at the first trimester of pregnancy and parity. A total of 38 miRNAs were associated (FDR q < 0.05) with BMI in the Gen3G cohort and were replicated (direction and magnitude of the fold change) in the 3D cohort, including 22 with a nominal p-value < 0.05. Some of these miRNAs were enriched in fatty acid metabolism-related pathways. We identified first trimester plasmatic miRNAs associated with maternal BMI. These miRNAs potentially regulate fatty acid metabolism-related pathways, supporting the hypothesis of their potential contribution to energy metabolism regulation in early pregnancy.

Investigating the role of RNA structures in transcriptional pausing using in vitro assays and in silico analyses.

Transcriptional pausing occurs across the bacterial genome but the importance of this mechanism is still poorly understood. Only few pauses were observed during the previous decades, leaving an important gap in understanding transcription mechanisms. Using the well-known Escherichia coli hisL and trpL pause sites as models, we describe here the relation of pause sites with upstream RNA structures suspected to stabilize pausing. We find that the transcription factor NusA influences the pause half-life at leuL, pheL and thrL pause sites. Using a mutagenesis approach, we observe that transcriptional pausing is affected in all tested pause sites, suggesting that the upstream RNA sequence is important for transcriptional pausing. Compensatory mutations assessing the presence of RNA hairpins did not yield clear conclusions, indicating that complex RNA structures or transcriptional features may be playing a role in pausing. Moreover, using a bioinformatic approach, we explored the relation between a DNA consensus sequence important for pausing and putative hairpins among thousands of pause sites in E. coli. We identified 2125 sites presenting hairpin-dependent transcriptional pausing without consensus sequence, suggesting that this mechanism is widespread across E. coli. This study paves the way to understand the role of RNA structures in transcriptional pausing.

First trimester plasma microRNAs levels predict Matsuda Index-estimated insulin sensitivity between 24th and 29th week of pregnancy.

INTRODUCTION: Gestational diabetes mellitus (GDM) is a consequence of an imbalance between insulin sensitivity (IS) and secretion during pregnancy. MicroRNAs (miRNAs) are small and secreted RNA molecules stable in blood and known to regulate physiological processes including glucose homeostasis. The aim of this study was to identify plasmatic miRNAs detectable in early pregnancy predicting IS at 24th-29th week of pregnancy. RESEARCH DESIGN AND METHODS: We quantified circulating miRNAs in 421 women in plasma collected at 9.6±2.2 weeks of pregnancy using next-generation sequencing. RESULTS: we detected 2170 miRNAs: 39 (35 positively and 4 negatively) were associated with IS as estimated by the Matsuda Index at 26.4±1.0 weeks of pregnancy. Lasso regression identified 18 miRNAs independently predicting Matsuda Index-estimated IS. Together with gestational age, maternal age and body mass index at first trimester, they explain 36% of IS variance in late second trimester of pregnancy. These miRNAs regulate fatty acid biosynthesis and metabolism among other pathways. CONCLUSIONS: In summary, we have identified first trimester plasmatic miRNAs predictive of Matsuda Index-estimated IS in late second trimester of pregnancy. These miRNAs could also contribute to initiate and support IS adaptation to pregnancy potentially through lipid metabolism regulation.

Human plasma pregnancy-associated miRNAs and their temporal variation within the first trimester of pregnancy.

BACKGROUND: During pregnancy, maternal metabolism undergoes substantial changes to support the developing fetus. Such changes are finely regulated by different mechanisms carried out by effectors such as microRNAs (miRNAs). These small non-coding RNAs regulate numerous biological functions, mostly through post-transcriptional repression of gene expression. miRNAs are also secreted in circulation by numerous organs, such as the placenta. However, the complete plasmatic microtranscriptome of pregnant women has still not been fully described, although some miRNA clusters from the chromosome 14 (C14MC) and the chromosome 19 (C19MC and miR-371-3 cluster) have been proposed as being specific to pregnancy. Our aims were thus to describe the plasma microtranscriptome during the first trimester of pregnancy, by assessing the differences with non-pregnant women, and how it varies between the 4th and the 16th week of pregnancy. METHODS: Plasmatic miRNAs from 436 pregnant (gestational week 4 to 16) and 15 non-pregnant women were quantified using Illumina HiSeq next-generation sequencing platform. Differentially abundant miRNAs were identified using DESeq2 package (FDR q-value ≤ 0.05) and their targeted biological pathways were assessed with DIANA-miRpath. RESULTS: A total of 2101 miRNAs were detected, of which 191 were differentially abundant (fold change < 0.05 or > 2, FDR q-value ≤ 0.05) between pregnant and non-pregnant women. Of these, 100 miRNAs were less and 91 miRNAs were more abundant in pregnant women. Additionally, the abundance of 57 miRNAs varied according to gestational age at first trimester, of which 47 were positively and 10 were negatively associated with advancing gestational age. miRNAs from the C19MC were positively associated with both pregnancy and gestational age variation during the first trimester. Biological pathway analysis revealed that these 191 (pregnancy-specific) and 57 (gestational age markers) miRNAs targeted genes involved in fatty acid metabolism, ECM-receptor interaction and TGF-beta signaling pathways. CONCLUSION: We have identified circulating miRNAs specific to pregnancy and/or that varied with gestational age in first trimester. These miRNAs target biological pathways involved in lipid metabolism as well as placenta and embryo development, suggesting a contribution to the maternal metabolic adaptation to pregnancy and fetal growth.

Inactivation of the riboswitch-controlled GMP synthase GuaA in Clostridioides difficile is associated with severe growth defects and poor infectivity in a mouse model of infection.

Clostridioides difficile is the main cause of nosocomial antibiotic-associated diarrhoea. There is a need for new antimicrobials to tackle this pathogen. Guanine riboswitches have been proposed as promising new antimicrobial targets, but experimental evidence of their importance in C. difficile is missing. The genome of C. difficile encodes four distinct guanine riboswitches, each controlling a single gene involved in purine metabolism and transport. One of them controls the expression of guaA, encoding a guanosine monophosphate (GMP) synthase. Here, using in-line probing and GusA reporter assays, we show that these riboswitches are functional in C. difficile and cause premature transcription termination upon binding of guanine. All riboswitches exhibit a high affinity for guanine characterized by Kd values in the low nanomolar range. Xanthine and guanosine also bind the guanine riboswitches, although with less affinity. Inactivating the GMP synthase (guaA) in C. difficile strain 630 led to cell death in minimal growth conditions, but not in rich medium. Importantly, the capacity of a guaA mutant to colonize the mouse gut was significantly reduced. Together, these results demonstrate the importance of de novo GMP biosynthesis in C. difficile during infection, suggesting that targeting guanine riboswitches with analogues could be a viable therapeutic strategy.

Genome-scale metabolic modeling reveals key features of a minimal gene set.

Mesoplasma florum, a fast-growing near-minimal organism, is a compelling model to explore rational genome designs. Using sequence and structural homology, the set of metabolic functions its genome encodes was identified, allowing the reconstruction of a metabolic network representing ˜ 30% of its protein-coding genes. Growth medium simplification enabled substrate uptake and product secretion rate quantification which, along with experimental biomass composition, were integrated as species-specific constraints to produce the functional iJL208 genome-scale model (GEM) of metabolism. Genome-wide expression and essentiality datasets as well as growth data on various carbohydrates were used to validate and refine iJL208. Discrepancies between model predictions and observations were mechanistically explained using protein structures and network analysis. iJL208 was also used to propose an in silico reduced genome. Comparing this prediction to the minimal cell JCVI-syn3.0 and its parent JCVI-syn1.0 revealed key features of a minimal gene set. iJL208 is a stepping-stone toward model-driven whole-genome engineering.

MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights.

Since its first release over a decade ago, the MetaboAnalyst web-based platform has become widely used for comprehensive metabolomics data analysis and interpretation. Here we introduce MetaboAnalyst version 5.0, aiming to narrow the gap from raw data to functional insights for global metabolomics based on high-resolution mass spectrometry (HRMS). Three modules have been developed to help achieve this goal, including: (i) a LC-MS Spectra Processing module which offers an easy-to-use pipeline that can perform automated parameter optimization and resumable analysis to significantly lower the barriers to LC-MS1 spectra processing; (ii) a Functional Analysis module which expands the previous MS Peaks to Pathways module to allow users to intuitively select any peak groups of interest and evaluate their enrichment of potential functions as defined by metabolic pathways and metabolite sets; (iii) a Functional Meta-Analysis module to combine multiple global metabolomics datasets obtained under complementary conditions or from similar studies to arrive at comprehensive functional insights. There are many other new functions including weighted joint-pathway analysis, data-driven network analysis, batch effect correction, merging technical replicates, improved compound name matching, etc. The web interface, graphics and underlying codebase have also been refactored to improve performance and user experience. At the end of an analysis session, users can now easily switch to other compatible modules for a more streamlined data analysis. MetaboAnalyst 5.0 is freely available at https://www.metaboanalyst.ca.

Comparative epigenome-wide analysis highlights placenta-specific differentially methylated regions.

Aim: The placenta undergoes DNA methylation (DNAm) programming that is unique compared with all other fetal tissues. We aim to decipher some of the physiologic roles of the placenta by comparing its DNAm profile with that of another fetal tissue. Materials & methods: We performed a comparative analysis of genome-wide DNAm of 444 placentas paired with cord blood samples collected at birth. Gene ontology term analyses were conducted on the resulting differentially methylated regions. Results: Genomic regions upstream of transcription start sites showing lower DNAm in the placenta were enriched with terms related to miRNA functions and genes encoding G-protein-coupled receptors. Conclusion: These results highlight genomic regions that are differentially methylated in the placenta in contrast to fetal blood.