The lncRNA HOTAIR transcription is controlled by HNF4α-induced chromatin topology modulation

The expression of the long noncoding RNA HOTAIR (HOX Transcript Antisense Intergenic RNA) is largely deregulated in epithelial cancers and positively correlates with poor prognosis and progression of hepatocellular carcinoma and gastrointestinal cancers. Furthermore, functional studies revealed a pivotal role for HOTAIR in the epithelial-to-mesenchymal transition, as this RNA is causal for the repressive activity of the master factor SNAIL on epithelial genes. Despite the proven oncogenic role of HOTAIR, its transcriptional regulation is still poorly understood. Here hepatocyte nuclear factor 4-α (HNF4α), as inducer of epithelial differentiation, was demonstrated to directly repress HOTAIR transcription in the mesenchymal-to epithelial transition. Mechanistically, HNF4α was found to cause the release of a chromatin loop on HOTAIR regulatory elements thus exerting an enhancer-blocking activity

Large-scale associations between the leukocyte transcriptome and BOLD responses to speech differ in autism early language outcome subtypes.

Heterogeneity in early language development in autism spectrum disorder (ASD) is clinically important and may reflect neurobiologically distinct subtypes. Here, we identified a large-scale association between multiple coordinated blood leukocyte gene coexpression modules and the multivariate functional neuroimaging (fMRI) response to speech. Gene coexpression modules associated with the multivariate fMRI response to speech were different for all pairwise comparisons between typically developing toddlers and toddlers with ASD and poor versus good early language outcome. Associated coexpression modules were enriched in genes that are broadly expressed in the brain and many other tissues. These coexpression modules were also enriched in ASD-associated, prenatal, human-specific, and language-relevant genes. This work highlights distinctive neurobiology in ASD subtypes with different early language outcomes that is present well before such outcomes are known. Associations between neuroimaging measures and gene expression levels in blood leukocytes may offer a unique in vivo window into identifying brain-relevant molecular mechanisms in ASD

Genome-wide association study identifies loci associated with liability to alcohol and drug dependence that is associated with variability in reward-related ventral striatum activity in African- and European-Americans.

Genetic influences on alcohol and drug dependence partially overlap, however, specific loci underlying this overlap remain unclear. We conducted a genome-wide association study (GWAS) of a phenotype representing alcohol or illicit drug dependence (ANYDEP) among 7291 European-Americans (EA; 2927 cases) and 3132 African-Americans (AA: 1315 cases) participating in the family-based Collaborative Study on the Genetics of Alcoholism. ANYDEP was heritable (h 2 in EA = 0.60, AA = 0.37). The AA GWAS identified three regions with genome-wide significant (GWS; P < 5E-08) single nucleotide polymorphisms (SNPs) on chromosomes 3 (rs34066662, rs58801820) and 13 (rs75168521, rs78886294), and an insertion-deletion on chromosome 5 (chr5:141988181). No polymorphisms reached GWS in the EA. One GWS region (chromosome 1: rs1890881) emerged from a trans-ancestral meta-analysis (EA + AA) of ANYDEP, and was attributable to alcohol dependence in both samples. Four genes (AA: CRKL, DZIP3, SBK3; EA: P2RX6) and four sets of genes were significantly enriched within biological pathways for hemostasis and signal transduction. GWS signals did not replicate in two independent samples but there was weak evidence for association between rs1890881 and alcohol intake in the UK Biobank. Among 118 AA and 481 EA individuals from the Duke Neurogenetics Study, rs75168521 and rs1890881 genotypes were associated with variability in reward-related ventral striatum activation. This study identified novel loci for substance dependence and provides preliminary evidence that these variants are also associated with individual differences in neural reward reactivity. Gene discovery efforts in non-European samples with distinct patterns of substance use may lead to the identification of novel ancestry-specific genetic markers of risk

A putative genomic island, PGI-1, in Ralstonia solanacearum biovar 2 revealed by subtractive hybridization

Ralstonia solanacearum biovar 2, a key bacterial pathogen of potato, has recently established in temperate climate waters. On the basis of isolates obtained from diseased (potato) plants, its genome has been assumed to be virtually clonal, but information on environmental isolates has been lacking. Based on differences in pulsed-field gel electrophoresis patterns, we compared the genomes of two biovar 2 strains with different life histories. Thus, genomic DNA of the novel environmental strain KZR-5 (The Netherlands) was compared to that of reference potato strain 715 (Bangladesh) by suppressive subtractive hybridization. Various strain-specific sequences were found, all being homologous to those found in the genome of reference potato strain 1609. Approximately 20% of these were related to genes involved in recombinational processes. We found a deletion of a 17.6-Kb region, denoted as a putative genomic island PGI-1, in environmental strain KZR-5. The deleted region was, at both extremes, flanked by a composite of two insertion sequence (IS) elements, identified as ISRso2 and ISRso3. The PGI-1 region contained open reading frames that putatively encoded a (p)ppGpp synthetase, a transporter protein, a transcriptional regulator, a cellobiohydrolase, a site-specific integrase/recombinase, a phage-related protein and seven hypothetical proteins. As yet, no phenotype could be assigned to the loss of PGI-1. The ecological behavior of strain KZR-5 was compared to that of reference strain 715. Strain KZR-5 showed enhanced tolerance to 4°C as compared to the reference strain, but was not affected in its virulence on tomato

Recent decreases in fossil-fuel emissions of ethane and methane derived from firn air

Methane and ethane are the most abundant hydrocarbons in the atmosphere and they affect both atmospheric chemistry and climate. Both gases are emitted from fossil fuels and biomass burning, whereas methane (CH(4)) alone has large sources from wetlands, agriculture, landfills and waste water. Here we use measurements in firn (perennial snowpack) air from Greenland and Antarctica to reconstruct the atmospheric variability of ethane (C(2)H(6)) during the twentieth century. Ethane levels rose from early in the century until the 1980s, when the trend reversed, with a period of decline over the next 20 years. We find that this variability was primarily driven by changes in ethane emissions from fossil fuels; these emissions peaked in the 1960s and 1970s at 14-16 teragrams per year (1 Tg = 10(12) g) and dropped to 8-10 Tg  yr(-1) by the turn of the century. The reduction in fossil-fuel sources is probably related to changes in light hydrocarbon emissions associated with petroleum production and use. The ethane-based fossil-fuel emission history is strikingly different from bottom-up estimates of methane emissions from fossil-fuel use, and implies that the fossil-fuel source of methane started to decline in the 1980s and probably caused the late twentieth century slow-down in the growth rate of atmospheric methane

Post-GWAS Functional Characterization of Susceptibility Variants for Chronic Lymphocytic Leukemia

Recent genome-wide association studies (GWAS) have identified several gene variants associated with sporadic chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL). Many of these CLL/SLL susceptibility loci are located in non-coding or intergenic regions, posing a significant challenge to determine their potential functional relevance. Here, we review the literature of all CLL/SLL GWAS and validation studies, and apply eQTL analysis to identify putatively functional SNPs that affect gene expression that may be causal in the pathogenesis of CLL/SLL. We tested 12 independent risk loci for their potential to alter gene expression through cis-acting mechanisms, using publicly available gene expression profiles with matching genotype information. Sixteen SNPs were identified that are linked to differential expression of SP140, a putative tumor suppressor gene previously associated with CLL/SLL. Three additional SNPs were associated with differential expression of DACT3 and GNG8, which are involved in the WNT/β-catenin- and G protein-coupled receptor signaling pathways, respectively, that have been previously implicated in CLL/SLL pathogenesis. Using in silico functional prediction tools, we found that 14 of the 19 significant eQTL SNPs lie in multiple putative regulatory elements, several of which have prior implications in CLL/SLL or other hematological malignancies. Although experimental validation is needed, our study shows that the use of existing GWAS data in combination with eQTL analysis and in silico methods represents a useful starting point to screen for putatively causal SNPs that may be involved in the etiology of CLL/SLL

A computational evaluation of over-representation of regulatory motifs in the promoter regions of differentially expressed genes

BACKGROUND: Observed co-expression of a group of genes is frequently attributed to co-regulation by shared transcription factors. This assumption has led to the hypothesis that promoters of co-expressed genes should share common regulatory motifs, which forms the basis for numerous computational tools that search for these motifs. While frequently explored for yeast, the validity of the underlying hypothesis has not been assessed systematically in mammals. This demonstrates the need for a systematic and quantitative evaluation to what degree co-expressed genes share over-represented motifs for mammals. RESULTS: We identified 33 experiments for human and mouse in the ArrayExpress Database where transcription factors were manipulated and which exhibited a significant number of differentially expressed genes. We checked for over-representation of transcription factor binding sites in up- or down-regulated genes using the over-representation analysis tool oPOSSUM. In 25 out of 33 experiments, this procedure identified the binding matrices of the affected transcription factors. We also carried out de novo prediction of regulatory motifs shared by differentially expressed genes. Again, the detected motifs shared significant similarity with the matrices of the affected transcription factors. CONCLUSIONS: Our results support the claim that functional regulatory motifs are over-represented in sets of differentially expressed genes and that they can be detected with computational methods