Спинальная анестезия при оперативном родоразрешении беременных с гестозом

БЕРЕМЕННОСТИ ОСЛОЖНЕНИЯПРЕЭКЛАМПСИЯРОДОВСПОМОЖЕНИЕАКУШЕРСКИЕ ХИРУРГИЧЕСКИЕ ОПЕРАЦИИАНЕСТЕЗИЯ СПИННОМОЗГОВАЯРОДОРАЗРЕШЕНИЯ ПРОЦЕС

RN7SK small nuclear RNA controls bidirectional transcription of highly expressed gene pairs in skin.

Funder: Wellcome TrustFunder: Medical Research CouncilPausing of RNA polymerase II (Pol II) close to promoters is a common regulatory step in RNA synthesis, and is coordinated by a ribonucleoprotein complex scaffolded by the noncoding RNA RN7SK. The function of RN7SK-regulated gene transcription in adult tissue homoeostasis is currently unknown. Here, we deplete RN7SK during mouse and human epidermal stem cell differentiation. Unexpectedly, loss of this small nuclear RNA specifically reduces transcription of numerous cell cycle regulators leading to cell cycle exit and differentiation. Mechanistically, we show that RN7SK is required for efficient transcription of highly expressed gene pairs with bidirectional promoters, which in the epidermis co-regulated cell cycle and chromosome organization. The reduction in transcription involves impaired splicing and RNA decay, but occurs in the absence of chromatin remodelling at promoters and putative enhancers. Thus, RN7SK is directly required for efficient Pol II transcription of highly transcribed bidirectional gene pairs, and thereby exerts tissue-specific functions, such as maintaining a cycling cell population in the epidermis

Codon usage optimization in pluripotent embryonic stem cells

Abstract: Background: The uneven use of synonymous codons in the transcriptome regulates the efficiency and fidelity of protein translation rates. Yet, the importance of this codon bias in regulating cell state-specific expression programmes is currently debated. Here, we ask whether different codon usage controls gene expression programmes in self-renewing and differentiating embryonic stem cells. Results: Using ribosome and transcriptome profiling, we identify distinct codon signatures during human embryonic stem cell differentiation. We find that cell state-specific codon bias is determined by the guanine-cytosine (GC) content of differentially expressed genes. By measuring the codon frequencies at the ribosome active sites interacting with transfer RNAs (tRNA), we further discover that self-renewing cells optimize translation of codons that depend on the inosine tRNA modification in the anticodon wobble position. Accordingly, inosine levels are highest in human pluripotent embryonic stem cells. This effect is conserved in mice and is independent of the differentiation stimulus. Conclusions: We show that GC content influences cell state-specific mRNA levels, and we reveal how translational mechanisms based on tRNA modifications change codon usage in embryonic stem cells

Complementary Activity of ETV5, RBPJ, and TCF3 Drives Formative Transition from Naive Pluripotency.

The gene regulatory network (GRN) of naive mouse embryonic stem cells (ESCs) must be reconfigured to enable lineage commitment. TCF3 sanctions rewiring by suppressing components of the ESC transcription factor circuitry. However, TCF3 depletion only delays and does not prevent transition to formative pluripotency. Here, we delineate additional contributions of the ETS-family transcription factor ETV5 and the repressor RBPJ. In response to ERK signaling, ETV5 switches activity from supporting self-renewal and undergoes genome relocation linked to commissioning of enhancers activated in formative epiblast. Independent upregulation of RBPJ prevents re-expression of potent naive factors, TBX3 and NANOG, to secure exit from the naive state. Triple deletion of Etv5, Rbpj, and Tcf3 disables ESCs, such that they remain largely undifferentiated and locked in self-renewal, even in the presence of differentiation stimuli. Thus, genetic elimination of three complementary drivers of network transition stalls developmental progression, emulating environmental insulation by small-molecule inhibitors.This research was funded by the Wellcome Trust, the Biotechnology and Biological Sciences Research Council, European Commission (contract no. 200720, EuroSyStem) and the Louis Jeantet Foundation. The Cambridge Stem Cell Institute receives core support from the Wellcome Trust and the Medical Research Council. AS is a Medical Research Council Professor

Duplication of chicken defensin7 gene generated by gene conversion and homologous recombination

Defensins constitute an evolutionary conserved family of cationic antimicrobial peptides that play a key role in host innate immune responses to infection. Defensin genes generally reside in complex genomic regions that are prone to structural variation, and defensin genes exhibit extensive copy number variation in humans and in other species. Copy number variation of defensin genes was examined in inbred lines of Leghorn and Fayoumi chickens, and a duplication of defensin7 was discovered in the Fayoumi breed. Analysis of junction sequences confirmed the occurrence of a simple tandem duplication of defensin7 with sequence identity at the junction, suggesting nonallelic homologous recombination between defensin7 and defensin6. The duplication event generated two chimeric promoters that are best explained by gene conversion followed by homologous recombination. Expression of defensin7 was not elevated in animals with two genes despite both genes being transcribed in the tissues examined. Computational prediction of promoter regions revealed the presence of several putative transcription factor binding sites generated by the duplication event. These data provide insight into the evolution and possible function of large gene families and specifically, the defensins

Loss of 5-methylcytosine alters the biogenesis of vault-derived small RNAs to coordinate epidermal differentiation.

The presence and absence of RNA modifications regulates RNA metabolism by modulating the binding of writer, reader, and eraser proteins. For 5-methylcytosine (m5C) however, it is largely unknown how it recruits or repels RNA-binding proteins. Here, we decipher the consequences of m5C deposition into the abundant non-coding vault RNA VTRNA1.1. Methylation of cytosine 69 in VTRNA1.1 occurs frequently in human cells, is exclusively mediated by NSUN2, and determines the processing of VTRNA1.1 into small-vault RNAs (svRNAs). We identify the serine/arginine rich splicing factor 2 (SRSF2) as a novel VTRNA1.1-binding protein that counteracts VTRNA1.1 processing by binding the non-methylated form with higher affinity. Both NSUN2 and SRSF2 orchestrate the production of distinct svRNAs. Finally, we discover a functional role of svRNAs in regulating the epidermal differentiation programme. Thus, our data reveal a direct role for m5C in the processing of VTRNA1.1 that involves SRSF2 and is crucial for efficient cellular differentiation.We thank everybody who provided us with reagents, in particular we thank James Stevenin for sending us recombinant SRSF2. We gratefully acknowledge the support of all the WT-MRC Stem Cell Institute core facility managers. This work was funded by Cancer Research UK (CR-630 UK) and the European Research Council (ERC). Parts of this research in Michaela Frye's laboratory was supported by core funding from Wellcome and MRC to the Wellcome-MRC Cambridge Stem Cell Institute. Juri Rappsilber’s laboratory was supported by Wellcome Trust Senior Research Fellowship (084229). Gracjan Michlewski’s laboratory was supported by the MRC Career Development Award (G10000564), Wellcome Trust Seed Award (210144/Z/18/Z) and Wellcome Trust Centre for Cell Biology Core Grants (077707 and 092076). Abdulrahim Sajini was supported by a scholarship from the University of Tabuk and Khalifa University of Science and Technology Faculty start-up award number FSU-2018-01. Rebecca Wagner was supported by the Wellcome Trust PhD Programme in Stem Cell Biology & Medicine

Sequence- and structure-specific cytosine-5 mRNA methylation by NSUN6.

The highly abundant N6-methyladenosine (m6A) RNA modification affects most aspects of mRNA function, yet the precise function of the rarer 5-methylcytidine (m5C) remains largely unknown. Here, we map m5C in the human transcriptome using methylation-dependent individual-nucleotide resolution cross-linking and immunoprecipitation (miCLIP) combined with RNA bisulfite sequencing. We identify NSUN6 as a methyltransferase with strong substrate specificity towards mRNA. NSUN6 primarily targeted three prime untranslated regions (3'UTR) at the consensus sequence motif CTCCA, located in loops of hairpin structures. Knockout and rescue experiments revealed enhanced mRNA and translation levels when NSUN6-targeted mRNAs were methylated. Ribosome profiling further demonstrated that NSUN6-specific methylation correlated with translation termination. While NSUN6 was dispensable for mouse embryonic development, it was down-regulated in human tumours and high expression of NSUN6 indicated better patient outcome of certain cancer types. In summary, our study identifies NSUN6 as a methyltransferase targeting mRNA, potentially as part of a quality control mechanism involved in translation termination fidelity

Comparative omics and feeding manipulations in chicken indicate a shift of the endocrine role of visceral fat towards reproduction.

BACKGROUND: The mammalian adipose tissue plays a central role in energy-balance control, whereas the avian visceral fat hardly expresses leptin, the key adipokine in mammals. Therefore, to assess the endocrine role of adipose tissue in birds, we compared the transcriptome and proteome between two metabolically different types of chickens, broilers and layers, bred towards efficient meat and egg production, respectively. RESULTS: Broilers and layer hens, grown up to sexual maturation under free-feeding conditions, differed 4.0-fold in weight and 1.6-fold in ovarian-follicle counts, yet the relative accumulation of visceral fat was comparable. RNA-seq and mass-spectrometry (MS) analyses of visceral fat revealed differentially expressed genes between broilers and layers, 1106 at the mRNA level (FDR ≤ 0.05), and 203 at the protein level (P ≤ 0.05). In broilers, Ingenuity Pathway Analysis revealed activation of the PTEN-pathway, and in layers increased response to external signals. The expression pattern of genes encoding fat-secreted proteins in broilers and layers was characterized in the RNA-seq and MS data, as well as by qPCR on visceral fat under free feeding and 24 h-feed deprivation. This characterization was expanded using available RNA-seq data of tissues from red junglefowl, and of visceral fat from broilers of different types. These comparisons revealed expression of new adipokines and secreted proteins (LCAT, LECT2, SERPINE2, SFTP1, ZP1, ZP3, APOV1, VTG1 and VTG2) at the mRNA and/or protein levels, with dynamic gene expression patterns in the selected chicken lines (except for ZP1; FDR/P ≤ 0.05) and feed deprivation (NAMPT, SFTPA1 and ZP3) (P ≤ 0.05). In contrast, some of the most prominent adipokines in mammals, leptin, TNF, IFNG, and IL6 were expressed at a low level (FPKM/RPKM< 1) and did not show differential mRNA expression neither between broiler and layer lines nor between fed vs. feed-deprived chickens. CONCLUSIONS: Our study revealed that RNA and protein expression in visceral fat changes with selective breeding, suggesting endocrine roles of visceral fat in the selected phenotypes. In comparison to gene expression in visceral fat of mammals, our findings points to a more direct cross talk of the chicken visceral fat with the reproductive system and lower involvement in the regulation of appetite, inflammation and insulin resistance.The study was supported by the Israel Academy of Sciences grants no. 876/ 14 and 1294/17, and Chief Scientist of the Israeli Ministry of Agriculture 0469/14 (to MFE and ES)

R.ROSETTA: an interpretable machine learning framework.

Funder: Uppsala Universitet; doi: http://dx.doi.org/10.13039/501100007051Funder: Polska Akademia Nauk; doi: http://dx.doi.org/10.13039/501100004382Funder: Uppsala UniversityBACKGROUND: Machine learning involves strategies and algorithms that may assist bioinformatics analyses in terms of data mining and knowledge discovery. In several applications, viz. in Life Sciences, it is often more important to understand how a prediction was obtained rather than knowing what prediction was made. To this end so-called interpretable machine learning has been recently advocated. In this study, we implemented an interpretable machine learning package based on the rough set theory. An important aim of our work was provision of statistical properties of the models and their components. RESULTS: We present the R.ROSETTA package, which is an R wrapper of ROSETTA framework. The original ROSETTA functions have been improved and adapted to the R programming environment. The package allows for building and analyzing non-linear interpretable machine learning models. R.ROSETTA gathers combinatorial statistics via rule-based modelling for accessible and transparent results, well-suited for adoption within the greater scientific community. The package also provides statistics and visualization tools that facilitate minimization of analysis bias and noise. The R.ROSETTA package is freely available at https://github.com/komorowskilab/R.ROSETTA . To illustrate the usage of the package, we applied it to a transcriptome dataset from an autism case-control study. Our tool provided hypotheses for potential co-predictive mechanisms among features that discerned phenotype classes. These co-predictors represented neurodevelopmental and autism-related genes. CONCLUSIONS: R.ROSETTA provides new insights for interpretable machine learning analyses and knowledge-based systems. We demonstrated that our package facilitated detection of dependencies for autism-related genes. Although the sample application of R.ROSETTA illustrates transcriptome data analysis, the package can be used to analyze any data organized in decision tables