Characterization of basal and lipopolysaccharide-induced microRNA expression in equine peripheral blood mononuclear cells using Next-Generation Sequencing

The innate immune response to lipopolysaccharide contributes substantially to the morbidity and mortality of gram-negative sepsis. Horses and humans share an exquisite sensitivity to lipopolysaccharide and thus the horse may provide valuable comparative insights into this aspect of the inflammatory response. MicroRNAs, small non-coding RNA molecules acting as post-transcriptional regulators of gene expression, have key roles in toll-like receptor signaling regulation but have not been studied in this context in horses. The central hypothesis of this study was that lipopolysaccharide induces differential microRNA expression in equine peripheral blood mononuclear cells in a manner comparable to humans. Illumina Next Generation Sequencing was used to characterize the basal microRNA transcriptome in isolated peripheral blood mononuclear cells from healthy adult horses, and to evaluate LPS-induced changes in microRNA expression in cells cultured for up to four hours. Selected expression changes were validated using quantitative reverse-transcriptase PCR. Only miR-155 was significantly upregulated by LPS, changing in parallel with supernatant tumor necrosis factor-α concentration. Eight additional microRNAs, including miR-146a and miR-146b, showed significant expression change with time in culture without a clear LPS effect. Target predictions indicated a number of potential immunity-associated targets for miR-155 in the horse, including SOCS1, TAB2 and elements of the PI3K signaling pathway, suggesting that it is likely to influence the acute inflammatory response to LPS. Gene alignment showed extensive conservation of the miR-155 precursor gene and associated promoter regions between horses and humans. The basal and LPS-stimulated microRNA expression pattern characterized here were similar to those described in human leukocytes. As well as providing a resource for further research into the roles of microRNAs in immune responses in horses, this will facilitate inter-species comparative study of the role of microRNAs in the inflammatory cascade during endotoxemia and sepsis

Oporność Acidithiobacillus ferrooxidans wobec jonów As(III) oraz Sb(III)

The influence of the Sb(III) and As(III) ions on metabolic activity of acidophilic bacteria Acidithiobacillus ferrooxidans isolated from the zinc-lead post-flotation tailings have been studied. It may be stated that these bacteria feature high resistance to the As(III) ions and lack of the Sb(III) ions tolerance. Bacteria tolerate the As(III) at concentrations up to 50 mg/dm3 but do not tolerate Sb(III) even at concentration of 10 mg/dm3. Thus, the strain being tested cannot be used in processes of the feed electrolyte treatment and cleaning.Badano wpływ jonów Sb(III) i As(III) na aktywność metaboliczną kwasolubnych bakterii Acidithiobacillus ferrooxidans, izolowanych z odpadów poflotacyjnych rud cynku i ołowiu. Ustalono, że bakterie te wykazują dużą oporność na jony As(III) i brak tolerancji Sb(III). Bakterie tolerują As(III) w stężeniach do 50 mg/dm3, ale nie tolerują Sb(III) nawet w stężeniu 10 mg/dm3. Tak więc testowany szczep nie może być wykorzystany w procesach przeróbki i oczyszczania nadawy elektrolitu

Pig chromosome X long non-coding RNA annotation and expression

International audienceThe advent of high-throughput sequencing technologies has revealed a wealth of long RNAs not encoding proteins, called long non coding RNAs (lncRNAs). In human, the number of lncRNA genes annotated by Gencode has kept increasing, and has now reached 15,000, a number very close to the one of protein coding genes (mRNA, 20,000). Although function is known for only a small fraction of them, the few well studied lncRNAs point to a wide variety of functions: transcriptional activators or repressors of mRNAs, miRNA blockers, or regulators of RNA degradation.Here we present an expression study of lncRNAs in pig using RNA-seq from 8 tissues (liver, spleen, testis, brain frontal lobe, muscle, olfactory bulb, lung and lymph node) from 3 breeds (Duroc, Large White, Pietrain). After applying our standard pipeline, we restricted our expression analysis to the better assembled chromosome X from the Wellcome Trust Sanger Institute, and found 127 bona fide lncRNA genes. Of those, 88 are in the sense orientation compared to their partner mRNA (mostly intronic), and 39 are in the antisense orientation (mostly intergenic). LncRNA gene expression analysis reveals 4 classes of genes: testis-specific, brain-specific, highly expressed in all tissues and lowly expressed in all tissues. Co-expression analysis of lncRNA genes with their partner mRNAs reveals 6 clusters of lncRNAs whose expression is either very anti-correlated or very correlated to their mRNA partner’s expression. An ubiquitous lncRNA underexpressed in liver and associated to the OTC liver specific gene seems particularly interesting, however additional data is needed to confirm the importance and function of these cases

Oncogenic role and target properties of the lysine-specific demethylase KDM1A in chronic lymphocytic leukemia

In chronic lymphocytic leukemia (CLL), epigenetic alterations are considered to centrally shape the transcriptional signatures that drive disease evolution and that underlie its biological and clinical subsets. Characterizations of epigenetic regulators, particularly histone-modifying enzymes, are very rudimentary in CLL. In efforts to establish effectors of the CLL-associated oncogene T-cell leukemia 1A (TCL1A), we identified here the lysine-specific histone demethylase KDM1A to interact with the TCL1A protein in B-cells in conjunction with an increased catalytic activity of KDM1A. We demonstrate that KDM1A is upregulated in malignant B-cells. Elevated KDM1A and associated gene expression signatures correlated with aggressive disease features and adverse clinical outcomes in a large prospective CLL trial cohort. Genetic Kdm1a knockdown (Kdm1a-KD) in Eμ-TCL1A mice reduced leukemic burden and prolonged animal survival, accompanied by upregulated p53 and pro-apoptotic pathways. Genetic KDM1A depletion also affected milieu components (T-, stromal, monocytic cells), resulting in significant reductions of their capacity to support CLL cell survival and proliferation. Integrated analyses of differential global transcriptomes (RNA-seq) and H3K4me3 marks (ChIP-seq) in Eµ-TCL1A vs. iKdm1aKD;Eµ-TCL1A mice (confirmed in human CLL) implicate KDM1A as an oncogenic transcriptional repressor in CLL by altering histone methylation patterns with pronounced effects on defined cell death and motility pathways. Finally, pharmacologic KDM1A inhibition altered H3K4/9 target methylation and revealed marked anti-B-cell-leukemic synergisms. Overall, we established the pathogenic role and effector networks of KDM1A in CLL, namely via tumor-cell intrinsic mechanisms and impacts in cells of the microenvironment. Our data also provide rationales to further investigate therapeutic KDM1A targeting in CLL

Additional file 1: of eQTL discovery and their association with severe equine asthma in European Warmblood horses

Figure S1. Minimum D-statistics determine mean read count cutoffs. Figure S2. PCA plots of normalized variance stabilized RNAseq counts after KS test filter. Figure S3. PCA plots of 1,056,195 SNP genotypes and colored by cohort. Figure S4. Matrix eQTL histograms and QQ-plots for all p-values for all cis and trans eQTL analyses using tag SNPs for the MCK1 treatment. Figure S5. Low confidence cis eQTLs. Figure S6. Joint modeling with eQTLBMA with possible overestimation of shared eQTLs across all PBMC treatments. Figure S7. Distance between eSNPs with the lowest FDR values per gene is small. Figure S8.. Enrichment of SNPs in trans regulatory hotspots genome wide. Figure S9. GWAS for RAO. Figure S10. Loss of DEXI gene expression regulation in HDE. Figure S11. Cis trans eQTL plot for all eQTLs for treatment HDE9. Table S1. High confidence additive linear cis eQTLs from the MCK treatment. Table S2. Low confidence additive linear cis eQTLs from the MCK treatment. Table S3. High confidence additive linear trans eQTLs from the MCK treatment. Table S4. Low confidence additive linear trans eQTLs from the MCK treatment. Table S5. High confidence additive linear cis eQTLs from the LPS treatment. Table S6. Low confidence additive linear cis eQTLs from the LPS treatment. Table S7. High confidence additive linear trans eQTLs from the LPS treatment. Table S8. Low confidence additive linear trans eQTLs from the LPS treatment. Table S9. High confidence additive linear cis eQTLs from the RCA treatment. Table S10. Low confidence additive linear cis eQTLs from the RCA treatment. Table S11. High confidence additive linear trans eQTLs from the RCA treatment. The eQTLs reported are limited to one eQTL per gene, representing the eSNP with the lowest FDR value for each gene. Table S12. Low confidence additive linear trans eQTLs from the RCA treatment. Table S13. High confidence additive linear cis eQTLs from the HDE treatment. Table S14. Low confidence additive linear cis eQTLs from the HDE treatment. Table S15. High confidence additive linear trans eQTLs from the HDE treatment. Table S16. Low confidence additive linear trans eQTLs from the HDE treatment. Table S17. Two proportion z-test calculation. Table S18. 4157 significant eQTLs discovered with eQTLBMA. Table S19. Trans eQTL results for the trans regulatory hotspot on chromosome 11 (SNP MNEc.2.11.60892596.PC). Table S20. Trans eQTL results for the trans regulatory hotspot on chromosome 13 (SNP MNEc.2.13.18333037.PC). Table S21. Panther gene enrichment GO process results for genes regulated by the trans regulatory hotpot on chromosome 11 (MNEc.2.11.60892596.PC). Table S22. Panther gene enrichment GO process results for genes regulated by the trans regulatory hotpot on chromosome 13 (MNEc.2.13.18333037.PC). Table S23. GWAS results. Table S24. All significant cis eQTLs for the MCK treatment. Table S25. All significant cis eQTLs for the LPS treatment. Table S26. All significant cis eQTLs for the RCA treatment. Table S27. All significant cis eQTLs for the HDE treatment. Table S28. Linkage disequilibrium and allele frequencies between RAO associated SNPs on chromosome 13 positions 32,843,309 – 33,502,488. Table S29. Sample information for 82 individuals used in eQTL analyses. Table S30. Sample information for all 379 individuals. (ZIP 51963 kb