Uwe Völker

Systematic identification of trans eQTLs as putative drivers of known disease associations

Identifying the downstream effects of disease-associated SNPs is challenging. To help overcome this problem, we performed expression quantitative trait locus (eQTL) meta-analysis in non-transformed peripheral blood samples from 5,311 individuals with replication in 2,775 individuals. We identified and replicated trans eQTLs for 233 SNPs (reflecting 103 independent loci) that were previously associated with complex traits at genome-wide significance. Some of these SNPs affect multiple genes in trans that are known to be altered in individuals with disease: rs4917014, previously associated with systemic lupus erythematosus (SLE), altered gene expression of C1QB and five type I interferon response genes, both hallmarks of SLE. DeepSAGE RNA sequencing showed that rs4917014 strongly alters the 3′ UTR levels of IKZF1 in cis, and chromatin immunoprecipitation and sequencing analysis of the trans-regulated genes implicated IKZF1 as the causal gene. Variants associated with cholesterol metabolism and type 1 diabetes showed similar phenomena, indicating that large-scale eQTL mapping provides insight into the downstream effects of many trait-associated variants.

Cohort Profile: The Study of Health in Pomerania

Henry Volzke, y Dietrich Alte,1y Carsten Oliver Schmidt, Dorte Radke, Roberto Lorbeer, Nele Friedrich, Nicole Aumann, Katharina Lau, Michael Piontek, Gabriele Born, Christoph Havemann, Till Ittermann, Sabine Schipf, Robin Haring, Sebastian E Baumeister, Henri Wallaschofski, Matthias Nauck, Stephanie Frick, Andreas Arnold, Michael Junger, Julia Mayerle, Matthias Kraft, Markus M Lerch, Marcus Dorr, Thorsten Reffelmann, Klaus Empen, Stephan B Felix, Anne Obst, Beate Koch, Sven Glaser, Ralf Ewert, Ingo Fietze, Thomas Penzel, Martina Doren, Wolfgang Rathmann, Johannes Haerting, Mario Hannemann, Jurgen Ropcke, Ulf Schminke, Clemens Jurgens, Frank Tost, Rainer Rettig, Jan A Kors, Saskia Ungerer, Katrin Hegenscheid, Jens-Peter Kuhn, Julia Kuhn, Norbert Hosten, Ralf Puls, Jorg Henke, Oliver Gloger, Alexander Teumer, Georg Homuth, Uwe Volker, Christian Schwahn, Birte Holtfreter, Ines Polzer, Thomas Kohlmann, Hans J Grabe, Dieter Rosskopf, Heyo K Kroemer, Thomas Kocher, Reiner Biffar,17,y Ulrich John20y and Wolfgang Hoffmann1y

Heat-shock and general stress response in Bacillus subtilis.

The induction of stress proteins is an important component of the adaptional network of a non‐growing cell of Bacillus subtilis. A diverse range of stresses such as heat shock, salt stress, ethanol, starvation for oxygen or nutrients etc. induce the same set of proteins, called general stress proteins. Although the adaptive functions of these proteins are largely unknown, they are proposed to provide general and rather non‐specific protection of the cell under these adverse conditions. In addition to these non‐specific general stress proteins, all extracellular signals induce a set of specific stress proteins that may confer specific protection against a particular stress factor. In B. subtilis at least three different classes of heat‐inducible genes can be defined by their common regulatory characteristics: Class I genes, as exemplified by the dnaK and groE operons, are most efficiently induced by heat stress. Their expression involves a σA‐dependent promoter, an inverted repeat (called the CIRCE element) highly conserved among eubacteria, and probably a repressor interacting with the CIRCE element. The majority of general stress genes (class II, more than 40) are induced at σB‐dependent promoters by different growth‐inhibiting conditions. The activation of σB by stress or starvation is the crucial event in the induction of this large stress regulon. Only a few genes, including lonclpCclpP, and ftsH, can respond to different stress factors independently of σB or CIRCE (class III). Stress induction of these genes occurs at promoters presumably recognized by σA and probably involves additional regulatory elements which remain to be defined.

Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations

Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2×10−201), ABCG2 (p = 3.1×10−26), SLC17A1 (p = 3.0×10−14), SLC22A11 (p = 6.7×10−14), SLC22A12 (p = 2.0×10−9), SLC16A9 (p = 1.1×10−8), GCKR (p = 1.4×10−9), LRRC16A (p = 8.5×10−9), and near PDZK1 (p = 2.7×10−9). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0×10−26) and propionyl-L-carnitine (p = 5.0×10−8) concentrations, which in turn were associated with serum UA levels (p = 1.4×10−57 and p = 8.1×10−54, respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels.

Condition-Dependent Transcriptome Reveals High-Level Regulatory Architecture in Bacillus subtilis

Outside In Acquisition and analysis of large data sets promises to move us toward a greater understanding of the mechanisms by which biological systems are dynamically regulated to respond to external cues. Now, two papers explore the responses of a bacterium to changing nutritional conditions (see the Perspective by Chalancon et al.). Nicolas et al. (p. 1103) measured transcriptional regulation for more than 100 different conditions. Greater amounts of antisense RNA were generated than expected and appeared to be produced by alternative RNA polymerase targeting subunits called sigma factors. One transition, from malate to glucose as the primary nutrient, was studied in more detail by Buescher et al. (p. 1099) who monitored RNA abundance, promoter activity in live cells, protein abundance, and absolute concentrations of intracellular and extracellular metabolites. In this case, the bacteria responded rapidly and largely without transcriptional changes to life on malate, but only slowly adapted to use glucose, a shift that required changes in nearly half the transcription network. These data offer an initial understanding of why certain regulatory strategies may be favored during evolution of dynamic control systems. A horizontal analysis reveals the breadth of genes turned on and off as nutrients change. Bacteria adapt to environmental stimuli by adjusting their transcriptomes in a complex manner, the full potential of which has yet to be established for any individual bacterial species. Here, we report the transcriptomes of Bacillus subtilis exposed to a wide range of environmental and nutritional conditions that the organism might encounter in nature. We comprehensively mapped transcription units (TUs) and grouped 2935 promoters into regulons controlled by various RNA polymerase sigma factors, accounting for ~66% of the observed variance in transcriptional activity. This global classification of promoters and detailed description of TUs revealed that a large proportion of the detected antisense RNAs arose from potentially spurious transcription initiation by alternative sigma factors and from imperfect control of transcription termination.

A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium.

The number and volume of cells in the blood affect a wide range of disorders including cancer and cardiovascular, metabolic, infectious and immune conditions. We consider here the genetic variation in eight clinically relevant hematological parameters, including hemoglobin levels, red and white blood cell counts and platelet counts and volume. We describe common variants within 22 genetic loci reproducibly associated with these hematological parameters in 13,943 samples from six European population-based studies, including 6 associated with red blood cell parameters, 15 associated with platelet parameters and 1 associated with total white blood cell count. We further identified a long-range haplotype at 12q24 associated with coronary artery disease and myocardial infarction in 9,479 cases and 10,527 controls. We show that this haplotype demonstrates extensive disease pleiotropy, as it contains known risk loci for type 1 diabetes, hypertension and celiac disease and has been spread by a selective sweep specific to European and geographically nearby populations.

Global Analysis of the General Stress Response of Bacillus subtilis

Gene arrays containing all currently known open reading frames of Bacillus subtilis were used to examine the general stress response of Bacillus. By proteomics, transcriptional analysis, transposon mutagenesis, and consensus promoter-based screening, 75 genes had previously been described as sigma(B)-dependent general stress genes. The present gene array-based analysis confirmed 62 of these already known general stress genes and detected 63 additional genes subject to control by the stress sigma factor sigma(B). At least 24 of these 125 sigma(B)-dependent genes seemed to be subject to a second, sigma(B)-independent stress induction mechanism. Therefore, this transcriptional profiling revealed almost four times as many regulon members as the proteomic approach, but failure of confirmation of all known members of the sigma(B) regulon indicates that even this approach has not yet elucidated the entire regulon. Most of the sigma(B)-dependent general stress proteins are probably located in the cytoplasm, but 25 contain at least one membrane-spanning domain, and at least 6 proteins appear to be secreted. The functions of most of the newly described genes are still unknown. However, their classification as sigma(B)-dependent stress genes argues that their products most likely perform functions in stress management and help to provide the nongrowing cell with multiple stress resistance. A comprehensive screening program analyzing the multiple stress resistance of mutants with mutations in single stress genes is in progress. The first results of this program, showing the diminished salt resistance of yjbC and yjbD mutants compared to that of the wild type, are presented. Only a few new sigma(B)-dependent proteins with already known functions were found, among them SodA, encoding a superoxide dismutase. In addition to analysis of the sigma(B)-dependent general stress regulon, a comprehensive list of genes induced by heat, salt, or ethanol stress in a sigma(B)-independent manner is presented. Perhaps the most interesting of the sigma(B)-independent stress phenomena was the induction of the extracytoplasmic function sigma factor sigma(W) and its entire regulon by salt shock.

Meta-analysis identifies six new susceptibility loci for atrial fibrillation

Atrial fibrillation is a highly prevalent arrhythmia and a major risk factor for stroke, heart failure and death. We conducted a genome-wide association study (GWAS) in individuals of European ancestry, including 6,707 with and 52,426 without atrial fibrillation. Six new atrial fibrillation susceptibility loci were identified and replicated in an additional sample of individuals of European ancestry, including 5,381 subjects with and 10,030 subjects without atrial fibrillation (P < 5 × 10−8). Four of the loci identified in Europeans were further replicated in silico in a GWAS of Japanese individuals, including 843 individuals with and 3,350 individuals without atrial fibrillation. The identified loci implicate candidate genes that encode transcription factors related to cardiopulmonary development, cardiac-expressed ion channels and cell signaling molecules.

Analysis of the induction of general stress proteins of Bacillus subtilis.

In Bacillus subtilis stress proteins are induced in response to different environmental conditions such as heat shock, salt stress, glucose and oxygen limitation or oxidative stress. These stress proteins have been previously grouped into general stress proteins (Gsps) and heat-specific stress proteins (Hsps). In this investigation the N-terminal sequences of 13 stress proteins of B. subtilis were determined. The quantification of the mRNA and the analysis of the protein synthesis pattern support the initial hypothesis that the chaperones DnaK and GroEL are Hsps in B. subtilis. In contrast, the recently described proteins GsiB, Ctc and RsbW belong to a class of Gsps that are induced by various stresses including heat shock. The main part of the Gsps described in this study failed to be induced in the sigB deletion mutant ML6 in response to heat shock. However, all the five Hsps were induced in this mutant in response to heat shock. These data indicate that SigB plays a crucial role in the induction of general stress genes, but is dispensable for the induction of Hsps.

General stress response of Bacillus subtilis and other bacteria

One of the strongest and most noticeable responses of a Bacillus subtilis cell to a range of stress and starvation conditions is the dramatic induction of a large number of general stress proteins. The alternative sigma factor sigma B is responsible for the induction of the genes encoding these general stress proteins that occurs following heat, ethanol, salt or acid stress, or during energy depletion. sigma B was detected more than 20 years ago by Richard Losick and William Haldenwang as the first alternative sigma factor of bacteria, but interest in sigma B declined after it was realized that sigma B is not involved in sporulation. It later turned out that sigma B, whose activity itself is tightly controlled, is absolutely required for the induction of this regulon, not only in B. subtilis, but also in other Gram-positive bacteria. These findings may have been responsible for the recent revival of interest in sigma B. This chapter summarizes the current information on this sigma B response including the latest results on the signal transduction pathways, the structure of the regulon and its physiological role. More than 150 general stress proteins/genes belong to this sigma B regulon, which is believed to provide the non-growing cell with a non-specific, multiple and preventive stress resistance. sigma B-dependent stress proteins are involved in non-specific protection against oxidative stress and also protect cells against heat, acid, alkaline or osmotic stress. A cell in the transition from a growing to a non-growing state induced by energy depletion will be equipped with a comprehensive stress resistance machine to protect it against future stress. The protection against oxidative stress may be an essential part of this response. In addition, preloading of cells with sigma B-dependent stress proteins, induced by mild heat or salt stress, will protect cells against a severe, potentially lethal, future stress. Both the specific protection against an acute emerging stress, as well as the non-specific, prospective protection against future stress, are adaptive functions crucial for surviving stress and starvation in nature. We suggest that the sigma B response is one essential component of a survival strategy that ensures survival in a quiescent, vegetative state as an alternative to sporulation. The role of sigma B in related Gram-positive bacteria (including cyanobacteria) with special emphasis on pathogenic bacteria is discussed.