Complex nature of SNP genotype effects on gene expression in primary human leucocytes.

This is a freely-available open access publication. Please cite the published version which is available via the DOI link in this record.BACKGROUND: Genome wide association studies have been hugely successful in identifying disease risk variants, yet most variants do not lead to coding changes and how variants influence biological function is usually unknown. METHODS: We correlated gene expression and genetic variation in untouched primary leucocytes (n = 110) from individuals with celiac disease - a common condition with multiple risk variants identified. We compared our observations with an EBV-transformed HapMap B cell line dataset (n = 90), and performed a meta-analysis to increase power to detect non-tissue specific effects. RESULTS: In celiac peripheral blood, 2,315 SNP variants influenced gene expression at 765 different transcripts (< 250 kb from SNP, at FDR = 0.05, cis expression quantitative trait loci, eQTLs). 135 of the detected SNP-probe effects (reflecting 51 unique probes) were also detected in a HapMap B cell line published dataset, all with effects in the same allelic direction. Overall gene expression differences within the two datasets predominantly explain the limited overlap in observed cis-eQTLs. Celiac associated risk variants from two regions, containing genes IL18RAP and CCR3, showed significant cis genotype-expression correlations in the peripheral blood but not in the B cell line datasets. We identified 14 genes where a SNP affected the expression of different probes within the same gene, but in opposite allelic directions. By incorporating genetic variation in co-expression analyses, functional relationships between genes can be more significantly detected. CONCLUSION: In conclusion, the complex nature of genotypic effects in human populations makes the use of a relevant tissue, large datasets, and analysis of different exons essential to enable the identification of the function for many genetic risk variants in common diseases.Coeliac UKNetherlands Organization for Scientific ResearchCeliac Disease Consortium (an innovative cluster approved by the Netherlands Genomics Initiative and partly funded by the Dutch government)Netherlands Genomics InitiativeWellcome Trus

A 15.65 solar mass black hole in an eclipsing binary in the nearby spiral galaxy Messier 33

Stellar-mass black holes are discovered in X-ray emitting binary systems, where their mass can be determined from the dynamics of their companion stars. Models of stellar evolution have difficulty producing black holes in close binaries with masses >10 solar masses, which is consistent with the fact that the most massive stellar black holes known so all have masses within 1 sigma of 10 solar masses. Here we report a mass of 15.65 +/- 1.45 solar masses for the black hole in the recently discovered system M33 X-7, which is located in the nearby galaxy Messier 33 (M33) and is the only known black hole that is in an eclipsing binary. In order to produce such a massive black hole, the progenitor star must have retained much of its outer envelope until after helium fusion in the core was completed. On the other hand, in order for the black hole to be in its present 3.45 day orbit about its 70.0 +/- 6.9 solar mass companion, there must have been a ``common envelope'' phase of evolution in which a significant amount of mass was lost from the system. We find the common envelope phase could not have occured in M33 X-7 unless the amount of mass lost from the progenitor during its evolution was an order of magnitude less than what is usually assumed in evolutionary models of massive stars.Comment: To appear in Nature October 18, 2007. Four figures (one color figure degraded). Differs slightly from published version. Supplementary Information follows in a separate postin

The Formation and Evolution of the First Massive Black Holes

The first massive astrophysical black holes likely formed at high redshifts (z>10) at the centers of low mass (~10^6 Msun) dark matter concentrations. These black holes grow by mergers and gas accretion, evolve into the population of bright quasars observed at lower redshifts, and eventually leave the supermassive black hole remnants that are ubiquitous at the centers of galaxies in the nearby universe. The astrophysical processes responsible for the formation of the earliest seed black holes are poorly understood. The purpose of this review is threefold: (1) to describe theoretical expectations for the formation and growth of the earliest black holes within the general paradigm of hierarchical cold dark matter cosmologies, (2) to summarize several relevant recent observations that have implications for the formation of the earliest black holes, and (3) to look into the future and assess the power of forthcoming observations to probe the physics of the first active galactic nuclei.Comment: 39 pages, review for "Supermassive Black Holes in the Distant Universe", Ed. A. J. Barger, Kluwer Academic Publisher

Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche.

Age at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P < 5 × 10(-8)) for 123 signals at 106 genomic loci associated with age at menarche. Many loci were associated with other pubertal traits in both sexes, and there was substantial overlap with genes implicated in body mass index and various diseases, including rare disorders of puberty. Menarche signals were enriched in imprinted regions, with three loci (DLK1-WDR25, MKRN3-MAGEL2 and KCNK9) demonstrating parent-of-origin-specific associations concordant with known parental expression patterns. Pathway analyses implicated nuclear hormone receptors, particularly retinoic acid and γ-aminobutyric acid-B2 receptor signalling, among novel mechanisms that regulate pubertal timing in humans. Our findings suggest a genetic architecture involving at least hundreds of common variants in the coordinated timing of the pubertal transition

Genome-wide association and functional follow-up reveals new loci for kidney function

Chronic kidney disease (CKD) is an important public health problem with a genetic component. We performed genome-wide association studies in up to 130,600 European ancestry participants overall, and stratified for key CKD risk factors. We uncovered 6 new loci in association with estimated glomerular filtration rate (eGFR), the primary clinical measure of CKD, in or near MPPED2, DDX1, SLC47A1, CDK12, CASP9, and INO80. Morpholino knockdown of mpped2 and casp9 in zebrafish embryos revealed podocyte and tubular abnormalities with altered dextran clearance, suggesting a role for these genes in renal function. By providing new insights into genes that regulate renal function, these results could further our understanding of the pathogenesis of CKD

Inactivation of the dnaK gene in Clostridium difficile 630 Δerm yields a temperature-sensitive phenotype and increases biofilm-forming ability

Abstract Clostridium difficile infection is a growing problem in healthcare settings worldwide and results in a considerable socioeconomic impact. New hypervirulent strains and acquisition of antibiotic resistance exacerbates pathogenesis; however, the survival strategy of C. difficile in the challenging gut environment still remains incompletely understood. We previously reported that clinically relevant heat-stress (37–41 °C) resulted in a classical heat-stress response with up-regulation of cellular chaperones. We used ClosTron to construct an insertional mutation in the dnaK gene of C. difficile 630 Δerm. The dnaK mutant exhibited temperature sensitivity, grew more slowly than C. difficile 630 Δerm and was less thermotolerant. Furthermore, the mutant was non-motile, had 4-fold lower expression of the fliC gene and lacked flagella on the cell surface. Mutant cells were some 50% longer than parental strain cells, and at optimal growth temperatures, they exhibited a 4-fold increase in the expression of class I chaperone genes including GroEL and GroES. Increased chaperone expression, in addition to the non-flagellated phenotype of the mutant, may account for the increased biofilm formation observed. Overall, the phenotype resulting from dnaK disruption is more akin to that observed in Escherichia coli dnaK mutants, rather than those in the Gram-positive model organism Bacillus subtilis

Reduced Expression of IFIH1 Is Protective for Type 1 Diabetes

IFIH1 (interferon induced with helicase C domain 1), also known as MDA5 (melanoma differentiation-associated protein 5), is one of a family of intracellular proteins known to recognise viral RNA and mediate the innate immune response. IFIH1 is causal in type 1 diabetes based on the protective associations of four rare variants, where the derived alleles are predicted to reduce gene expression or function. Originally, however, T1D protection was mapped to the common IFIH1 nsSNP, rs1990760 or Thr946Ala. This common amino acid substitution does not cause a loss of function and evidence suggests the protective allele, Ala946, may mark a haplotype with reduced expression of IFIH1 in line with the protection conferred by the four rare loss of function alleles. We have performed allele specific expression analysis that supports this hypothesis: the T1D protective haplotype correlates with reduced IFIH1 transcription in interferon-β stimulated peripheral blood mononuclear cells (overall p = 0.012). In addition, we have used multiflow cytometry analysis and quantitative PCR assays to prove reduced expression of IFIH1 in individuals heterozygous for three of the T1D-associated rare alleles: a premature stop codon, rs35744605 (Glu627X) and predicted splice variants, rs35337543 (IVS8+1) and rs35732034 (IVS14+1). We also show that the nsSNP, Ile923V, does not alter pre-mRNA levels of IFIH1. These results confirm and extend the new autoimmune disease pathway of reduced IFIH1 expression and protein function protecting from T1D

SeqGene: a comprehensive software solution for mining exome- and transcriptome- sequencing data

Abstract Background The popularity of massively parallel exome and transcriptome sequencing projects demands new data mining tools with a comprehensive set of features to support a wide range of analysis tasks. Results SeqGene, a new data mining tool, supports mutation detection and annotation, dbSNP and 1000 Genome data integration, RNA-Seq expression quantification, mutation and coverage visualization, allele specific expression (ASE), differentially expressed genes (DEGs) identification, copy number variation (CNV) analysis, and gene expression quantitative trait loci (eQTLs) detection. We also developed novel methods for testing the association between SNP and expression and identifying genotype-controlled DEGs. We showed that the results generated from SeqGene compares favourably to other existing methods in our case studies. Conclusion SeqGene is designed as a general-purpose software package. It supports both paired-end reads and single reads generated on most sequencing platforms; it runs on all major types of computers; it supports arbitrary genome assemblies for arbitrary organisms; and it scales well to support both large and small scale sequencing projects. The software homepage is http://seqgene.sourceforge.net.</p

Protocol Dependence of Sequencing-Based Gene Expression Measurements

RNA Seq provides unparalleled levels of information about the transcriptome including precise expression levels over a wide dynamic range. It is essential to understand how technical variation impacts the quality and interpretability of results, how potential errors could be introduced by the protocol, how the source of RNA affects transcript detection, and how all of these variations can impact the conclusions drawn. Multiple human RNA samples were used to assess RNA fragmentation, RNA fractionation, cDNA synthesis, and single versus multiple tag counting. Though protocols employing polyA RNA selection generate the highest number of non-ribosomal reads and the most precise measurements for coding transcripts, such protocols were found to detect only a fraction of the non-ribosomal RNA in human cells. PolyA RNA excludes thousands of annotated and even more unannotated transcripts, resulting in an incomplete view of the transcriptome. Ribosomal-depleted RNA provides a more cost-effective method for generating complete transcriptome coverage. Expression measurements using single tag counting provided advantages for assessing gene expression and for detecting short RNAs relative to multi-read protocols. Detection of short RNAs was also hampered by RNA fragmentation. Thus, this work will help researchers choose from among a range of options when analyzing gene expression, each with its own advantages and disadvantages

HMMSplicer: A Tool for Efficient and Sensitive Discovery of Known and Novel Splice Junctions in RNA-Seq Data

Background: High-throughput sequencing of an organism’s transcriptome, or RNA-Seq, is a valuable and versatile new strategy for capturing snapshots of gene expression. However, transcriptome sequencing creates a new class of alignment problem: mapping short reads that span exon-exon junctions back to the reference genome, especially in the case where a splice junction is previously unknown. Methodology/Principal Findings: Here we introduce HMMSplicer, an accurate and efficient algorithm for discovering canonical and non-canonical splice junctions in short read datasets. HMMSplicer identifies more splice junctions than currently available algorithms when tested on publicly available A. thaliana, P. falciparum, and H. sapiens datasets without a reduction in specificity. Conclusions/Significance: HMMSplicer was found to perform especially well in compact genomes and on genes with low expression levels, alternative splice isoforms, or non-canonical splice junctions. Because HHMSplicer does not rely on prebuilt gene models, the products of inexact splicing are also detected. For H. sapiens, we find 3.6 % of 39 splice sites and 1.4% of 59 splice sites are inexact, typically differing by 3 bases in either direction. In addition, HMMSplicer provides a score for every predicted junction allowing the user to set a threshold to tune false positive rates depending on the needs of the experiment. HMMSplicer is implemented in Python. Code and documentation are freely available a