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Finally, we further integrated DE and network results to prioritize genes by its functional importance and identified a top-ranked novel gene, LOC107773232, as a potential regulator involved in the carotenoid metabolism pathway. Thus, the results and systems-biology approaches provide a new avenue to understand the molecular mechanisms underlying complex genetic and environmental perturbations in tobacco. © The Author(s) 2020. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.Hepatocellular carcinoma (HCC) is one of the most lethal cancers in the world. MicroRNAs play a pivotal role in the progression of various cancers. To date, very little attention has been paid to miR-4458. Therefore, the aim of our study was to explore the function and underlying molecular mechanism of miR-4458 in HCC. We found that the expression of miR-4458 was reduced in HCC tissues and cell lines. Forced overexpression of miR-4458 inhibited the migration, invasion, and epithelial-mesenchymal transition (EMT) of HCC cells, while downregulation of miR-4458 promoted the aggressive phenotype. Furthermore, transforming growth factor beta receptor 1 (TGFBR1), the modulator of the TGF-β signaling pathway, was verified to be a novel target gene of miR-4458 by dual-luciferase reporter gene assay. Upregulated miR-4458 dramatically abolished TGFBR1 and p-Smad2/3 expression, thus blocking the TGF-β signaling pathway. Moreover, restoration of TGFBR1 partially rescued the miR-4458-mediated suppressive effect on the migration, invasion, and EMT and reactivated the TGF-β signaling pathway in HCC cells. In summary, our findings first demonstrated a mechanism of miR-4458 in HCC cell migration, invasion, and EMT by regulating the TGF-β signaling pathway via directly targeting TGFBR1. © The Author(s) 2020. Published by Oxford University Press on behalf of the Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences. All rights reserved. For permissions, please email journals.permissions@oup.com.Monocyte-to-macrophage trans-differentiation has long been studied to better understand this immunological response and aspects of developmental processes more generally. A key question is the nature of the corresponding changes in chromatin conformation and its relationship to the transcriptome during this process. This question is especially intriguing since this trans-differentiation is not associated with progression through mitosis, often considered a necessary step for gross changes in chromosomal structure. Here, we characterized the transcriptional and genomic structural changes during macrophage development of primary human monocytes using RNA-seq and in situ Hi-C. Pyridostatin clinical trial We found that, during this transition, the genome architecture undergoes a massive remodeling to a degree not observed before between structured genomes, with changes in ~90% of the topologically associating domains (TADs). These changes in the TADs are associated with changed expression of immunological genes. These structural changes, however, differ extensively from those described recently in a study of the leukemia cell line, THP-1. Furthermore, up-regulation of the AP-1 family of genes that effected functionally important changes in the genomic structure during the differentiation of the THP-1 cells was not corroborated with the primary cells. Taken together, our results provide a comprehensive characterization of the changes in genomic structure during the monocyte-to-macrophage transition, establish a framework for the elucidation of processes underlying differentiation without proliferation, and demonstrate the importance of verifying with primary cells the mechanisms discovered with cultured cells. © The Author(s) 2020. Published by Oxford University Press on behalf of the Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences. All rights reserved. For permissions, please email journals.permissions@oup.com.SUMMARY Single cell RNA sequencing is a technology to measure gene expression in single cells. It has enabled discovery of new cell types and established cell type atlases of tissues and organs. The widespread adoption of single cell RNA-seq has created a need for user-friendly software for data analysis. We have developed a web server, alona, that incorporates several of the most popular single cell analysis algorithms into a flexible pipeline. alona can perform quality filtering, normalization, batch correction, clustering, cell type annotation, and differential gene expression analysis. Data are visualized in the web browser using an interface based on JavaScript, allowing the user to query genes of interest and visualize the cluster structure. alona accepts a compressed gene expression matrix and identifies cell clusters with a graph-based clustering strategy. Cell types are identified from a comprehensive collection of marker genes or by specifying a custom set of marker genes. AVAILABILITY AND IMPLEMENTATION The service runs at https//alona.panglaodb.se and the Python package can be downloaded from https//oscar-franzen.github.io/adobo/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online. © The Author(s) 2020. Published by Oxford University Press.Ready-to-eat (RTE) meat and poultry product samples collected between 2005 and 2017 from RTE producing establishments for the Food Safety and Inspection Service's (FSIS's) ALLRTE/RTEPROD_RAND (random) and RTE001/RTEPROD_RISK (risk-based) sampling projects were tested for Listeria monocytogenes ( Lm ). Data for 45,897 ALLRTE/RTEPROD_RAND samples collected from 3607 unique establishments and 112,347 RTE001/RTEPROD_RISK samples collected from 3283 unique establishments were analyzed for the presence of Lm . These data were also analyzed based upon the percentages of establishments with positive samples, as well as annual production volume, sanitation control alternative, geographic location and season/month of sample collection.  Results showed low occurrences of Lm -positive samples from the random and risk-based sampling projects, with 152 positive samples (0.33%) for ALLRTE/RTEPROD_RAND and 403 positive samples (0.36%) for RTE001/RTEPROD_RISK, respectively. The percentages of positive samples significantly decreased over time, from about 0.