Misexpression of inactive genes in whole blood is associated with nearby rare structural variants.

Gene misexpression is the aberrant transcription of a gene in a context where it is usually inactive. Despite its known pathological consequences in specific rare diseases, we have a limited understanding of its wider prevalence and mechanisms in humans. To address this, we analyzed gene misexpression in 4,568 whole-blood bulk RNA sequencing samples from INTERVAL study blood donors. We found that while individual misexpression events occur rarely, in aggregate they were found in almost all samples and a third of inactive protein-coding genes. Using 2,821 paired whole-genome and RNA sequencing samples, we identified that misexpression events are enriched in cis for rare structural variants. We established putative mechanisms through which a subset of SVs lead to gene misexpression, including transcriptional readthrough, transcript fusions, and gene inversion. Overall, we develop misexpression as a type of transcriptomic outlier analysis and extend our understanding of the variety of mechanisms by which genetic variants can influence gene expression.

AltHapAlignR: improved accuracy of RNA-seq analyses through the use of alternative haplotypes.

Motivation: Reliance on mapping to a single reference haplotype currently limits accurate estimation of allele or haplotype-specific expression using RNA-sequencing, notably in highly polymorphic regions such as the major histocompatibility complex. Results: We present AltHapAlignR, a method incorporating alternate reference haplotypes to generate gene- and haplotype-level estimates of transcript abundance for any genomic region where such information is available. We validate using simulated and experimental data to quantify input allelic ratios for major histocompatibility complex haplotypes, demonstrating significantly improved correlation with ground truth estimates of gene counts compared to standard single reference mapping. We apply AltHapAlignR to RNA-seq data from 462 individuals, showing how significant underestimation of expression of the majority of classical human leukocyte antigen genes using conventional mapping can be corrected using AltHapAlignR to allow more accurate quantification of gene expression for individual alleles and haplotypes. Availability and implementation: Source code freely available at https://github.com/jknightlab/AltHapAlignR. Supplementary information: Supplementary data are available at Bioinformatics online.

Distinct HLA associations of LGI1 and CASPR2-antibody diseases.

The recent biochemical distinction between antibodies against leucine-rich, glioma-inactivated-1 (LGI1), contactin-associated protein-2 (CASPR2) and intracellular epitopes of voltage-gated potassium-channels (VGKCs) demands aetiological explanations. Given established associations between human leucocyte antigen (HLA) alleles and adverse drug reactions, and our clinical observation of frequent adverse drugs reactions in patients with LGI1 antibodies, we compared HLA alleles between healthy controls (n = 5553) and 111 Caucasian patients with VGKC-complex autoantibodies. In patients with LGI1 antibodies (n = 68), HLA-DRB1*07:01 was strongly represented [odds ratio = 27.6 (95% confidence interval 12.9-72.2), P = 4.1 × 10-26]. In contrast, patients with CASPR2 antibodies (n = 31) showed over-representation of HLA-DRB1*11:01 [odds ratio = 9.4 (95% confidence interval 4.6-19.3), P = 5.7 × 10-6]. Other allelic associations for patients with LGI1 antibodies reflected linkage, and significant haplotypic associations included HLA-DRB1*07:01-DQA1*02:01-DQB1*02:02, by comparison to DRB1*11:01-DQA1*05:01-DQB1*03:01 in CASPR2-antibody patients. Conditional analysis in LGI1-antibody patients resolved further independent class I and II associations. By comparison, patients with both LGI1 and CASPR2 antibodies (n = 3) carried yet another complement of HLA variants, and patients with intracellular VGKC antibodies (n = 9) lacked significant HLA associations. Within LGI1- or CASPR2-antibody patients, HLA associations did not correlate with clinical features. In silico predictions identified unique CASPR2- and LGI1-derived peptides potentially presented by the respective over-represented HLA molecules. These highly significant HLA associations dichotomize the underlying immunology in patients with LGI1 or CASPR2 antibodies, and inform T cell specificities and cellular interactions at disease initiation.10.1093/brain/awy109_video1awy109media15796480660001.

Reversion of a fungal genetic code alteration links proteome instability with genomic and phenotypic diversification.

Many fungi restructured their proteomes through incorporation of serine (Ser) at thousands of protein sites coded by the leucine (Leu) CUG codon. How these fungi survived this potentially lethal genetic code alteration and its relevance for their biology are not understood. Interestingly, the human pathogen Candida albicans maintains variable Ser and Leu incorporation levels at CUG sites, suggesting that this atypical codon assignment flexibility provided an effective mechanism to alter the genetic code. To test this hypothesis, we have engineered C. albicans strains to misincorporate increasing levels of Leu at protein CUG sites. Tolerance to the misincorporations was very high, and one strain accommodated the complete reversion of CUG identity from Ser back to Leu. Increasing levels of Leu misincorporation decreased growth rate, but production of phenotypic diversity on a phenotypic array probing various metabolic networks, drug resistance, and host immune cell responses was impressive. Genome resequencing revealed an increasing number of genotype changes at polymorphic sites compared with the control strain, and 80% of Leu misincorporation resulted in complete loss of heterozygosity in a large region of chromosome V. The data unveil unanticipated links between gene translational fidelity, proteome instability and variability, genome diversification, and adaptive phenotypic diversity. They also explain the high heterozygosity of the C. albicans genome and open the door to produce microorganisms with genetic code alterations for basic and applied research.

eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis.

Sepsis is a clinical syndrome of life-threatening organ dysfunction caused by a dysregulated response to infection, for which disease heterogeneity is a major obstacle to developing targeted treatments. We have previously identified gene-expression-based patient subgroups (sepsis response signatures [SRS]) informative for outcome and underlying pathophysiology. Here, we aimed to investigate the role of genetic variation in determining the host transcriptomic response and to delineate regulatory networks underlying SRS. Using genotyping and RNA-sequencing data on 638 adult sepsis patients, we report 16,049 independent expression (eQTLs) and 32 co-expression module (modQTLs) quantitative trait loci in this disease context. We identified significant interactions between SRS and genotype for 1,578 SNP-gene pairs and combined transcription factor (TF) binding site information (SNP2TFBS) and predicted regulon activity (DoRothEA) to identify candidate upstream regulators. Overall, these approaches identified putative mechanistic links between host genetic variation, cell subtypes, and the individual transcriptomic response to infection.

FGDB: revisiting the genome annotation of the plant pathogen Fusarium graminearum.

The MIPS Fusarium graminearum Genome Database (FGDB) was established as a comprehensive genome database on one of the most devastating fungal plant pathogens of wheat, barley and maize. The current version of FGDB v3.1 provides information on the full manually revised gene set based on the Broad Institute assembly FG3 genome sequence. The results of gene prediction tools were integrated with the help of comparative data on related species to result in a set of 13.718 annotated protein coding genes. This rigorous approach involved adding or modifying gene models and represents a coding sequence gold standard for the genus Fusarium. The gene loci improvements results in 2461 genes which either are new or have different structures compared to the Broad Institute assembly 3 gene set. Moreover the database serves as a convenient entry point to explore expression data results and to obtain information on the Affymetrix GeneChip probe sets. The resource is accessible on http://mips.gsf.de/genre/proj/FGDB/.

CCancer: a bird's eye view on gene lists reported in cancer-related studies.

CCancer is an automatically collected database of gene lists, which were reported mostly by experimental studies in various biological and clinical contexts. At the moment, the database covers 3369 gene lists extracted from 2644 papers published in approximately 80 peer-reviewed journals. As input, CCancer accepts a gene list. An enrichment analyses is implemented to generate, as output, a highly informative survey over recently published studies that report gene lists, which significantly intersect with the query gene list. A report on gene pairs from the input list which were frequently reported together by other biological studies is also provided. CCancer is freely available at http://mips.helmholtz-muenchen.de/proj/ccancer.

Natural Killer cells demonstrate distinct eQTL and transcriptome-wide disease associations, highlighting their role in autoimmunity.

Natural Killer cells are innate lymphocytes with central roles in immunosurveillance and are implicated in autoimmune pathogenesis. The degree to which regulatory variants affect Natural Killer cell gene expression is poorly understood. Here we perform expression quantitative trait locus mapping of negatively selected Natural Killer cells from a population of healthy Europeans (n = 245). We find a significant subset of genes demonstrate expression quantitative trait loci specific to Natural Killer cells and these are highly informative of human disease, in particular autoimmunity. A Natural Killer cell transcriptome-wide association study across five common autoimmune diseases identifies further novel associations at 27 genes. In addition to these cis observations, we find novel master-regulatory regions impacting expression of trans gene networks at regions including 19q13.4, the Killer cell Immunoglobulin-like Receptor region, GNLY, MC1R and UVSSA. Our findings provide new insights into the unique biology of Natural Killer cells, demonstrating markedly different expression quantitative trait loci from other immune cells, with implications for disease mechanisms.

Transcriptome analysis of nitrate assimilation in Aspergillus nidulans reveals connections to nitric oxide metabolism.

Nitrate is a dominant form of inorganic nitrogen (N) in soils and can be efficiently assimilated by bacteria, fungi and plants. We studied here the transcriptome of the short-term nitrate response using assimilating and non-assimilating strains of the model ascomycete Aspergillus nidulans. Among the 72 genes positively responding to nitrate, only 18 genes carry binding sites for the pathway-specific activator NirA. Forty-five genes were repressed by nitrate metabolism. Because nirA(-) strains are N-starved at nitrate induction conditions, we also compared the nitrate transcriptome with N-deprived conditions and found a partial overlap of differentially regulated genes between these conditions. Nitric oxide (NO)-metabolizing flavohaemoglobins were found to be co-regulated with nitrate assimilatory genes. Subsequent molecular characterization revealed that the strongly inducible FhbA is required for full activity of nitrate and nitrite reductase enzymes. The co-regulation of NO-detoxifying and nitrate/nitrite assimilating systems may represent a conserved mechanism, which serves to neutralize nitrosative stress imposed by an external NO source in saprophytic and pathogenic fungi. Our analysis using membrane-permeable NO donors suggests that signalling for NirA activation only indirectly depends on the nitrate transporters NrtA (CrnA) and NrtB (CrnB).

Context-specific regulation of surface and soluble IL7R expression by an autoimmune risk allele.

IL-7 is a key factor in T cell immunity and common variants at IL7R, encoding its receptor, are associated with autoimmune disease susceptibility. IL7R mRNA is induced in stimulated monocytes, yet a function for IL7R in monocyte biology remains unexplored. Here we characterize genetic regulation of IL7R at the protein level in healthy individuals, and find that monocyte surface and soluble IL7R (sIL7R) are markedly induced by lipopolysaccharide. In monocytes, both surface IL7R and sIL7R expression strongly associate with allelic carriage of rs6897932, a disease-associated IL7R polymorphism. Monocytes produce more sIL7R than CD4 + T cells, and the amount is additionally correlated with the expression of DDX39A, encoding a splicing factor. Synovial fluid-derived monocytes from patients with spondyloarthritis are enriched for IL7R+ cells with a unique transcriptional profile that overlaps with IL-7-induced gene sets. Our data thus suggest a previously unappreciated function for monocytes in IL-7 biology and IL7R-associated diseases.

High resolution HLA haplotyping by imputation for a British population bioresource.

This study aimed to establish the occurrence and frequency of HLA alleles and haplotypes for a healthy British Caucasian population bioresource from Oxfordshire. We present the results of imputation from HLA SNP genotyping data using SNP2HLA for 5553 individuals from Oxford Biobank, defining one- and two-field alleles together with amino acid polymorphisms. We show that this achieves a high level of accuracy with validation using sequence-specific primer amplification PCR. We define six- and eight-locus HLA haplotypes for this population by Bayesian methods implemented using PHASE. We determine patterns of linkage disequilibrium and recombination for these individuals involving classical HLA loci and show how analysis within a haplotype block structure may be more tractable for imputed data. Our findings contribute to knowledge of HLA diversity in healthy populations and further validate future large-scale use of HLA imputation as an informative approach in population bioresources.

Adaptive Mistranslation Accelerates the Evolution of Fluconazole Resistance and Induces Major Genomic and Gene Expression Alterations in Candida albicans.

Regulated erroneous protein translation (adaptive mistranslation) increases proteome diversity and produces advantageous phenotypic variability in the human pathogen Candida albicans. It also increases fitness in the presence of fluconazole, but the underlying molecular mechanism is not understood. To address this question, we evolved hypermistranslating and wild-type strains in the absence and presence of fluconazole and compared their fluconazole tolerance and resistance trajectories during evolution. The data show that mistranslation increases tolerance and accelerates the acquisition of resistance to fluconazole. Genome sequencing, array-based comparative genome analysis, and gene expression profiling revealed that during the course of evolution in fluconazole, the range of mutational and gene deregulation differences was distinctively different and broader in the hypermistranslating strain, including multiple chromosome duplications, partial chromosome deletions, and polyploidy. Especially, the increased accumulation of loss-of-heterozygosity events, aneuploidy, translational and cell surface modifications, and differences in drug efflux seem to mediate more rapid drug resistance acquisition under mistranslation. Our observations support a pivotal role for adaptive mistranslation in the evolution of drug resistance in C. albicans. IMPORTANCE Infectious diseases caused by drug-resistant fungi are an increasing threat to public health because of the high mortality rates and high costs associated with treatment. Thus, understanding of the molecular mechanisms of drug resistance is of crucial interest for the medical community. Here we investigated the role of regulated protein mistranslation, a characteristic mechanism used by C. albicans to diversify its proteome, in the evolution of fluconazole resistance. Such codon ambiguity is usually considered highly deleterious, yet recent studies found that mistranslation can boost adaptation in stressful environments. Our data reveal that CUG ambiguity diversifies the genome in multiple ways and that the full spectrum of drug resistance mechanisms in C. albicans goes beyond the traditional pathways that either regulate drug efflux or alter the interactions of drugs with their targets. The present work opens new avenues to understand the molecular and genetic basis of microbial drug resistance.

Characterisation of the global transcriptional response to heat shock and the impact of individual genetic variation.

BACKGROUND: The heat shock transcriptional response is essential to effective cellular function under stress. This is a highly heritable trait but the nature and extent of inter-individual variation in heat shock response remains unresolved. METHODS: We determined global transcription profiles of the heat shock response for a panel of lymphoblastoid cell lines established from 60 founder individuals in the Yoruba HapMap population. We explore the observed differentially expressed gene sets following heat shock, establishing functional annotations, underlying networks and nodal genes involving heat shock factor 1 recruitment. We define a multivariate phenotype for the global transcriptional response to heat shock using partial least squares regression and map this quantitative trait to associated genetic variation in search of the major genomic modulators. RESULTS: A comprehensive dataset of differentially expressed genes following heat shock in humans is presented. We identify nodal genes downstream of heat shock factor 1 in this gene set, notably involving ubiquitin C and small ubiquitin-like modifiers together with transcription factors. We dissect a multivariate phenotype for the global heat shock response which reveals distinct clustering of individuals in terms of variance of the heat shock response and involves differential expression of genes involved in DNA replication and cell division in some individuals. We find evidence of genetic associations for this multivariate response phenotype that involves trans effects modulating expression of genes following heat shock, including HSF1 and UBQLN1. CONCLUSION: This study defines gene expression following heat shock for a cohort of individuals, establishing insights into the biology of the heat shock response and hypotheses for how variation in this may be modulated by underlying genetic diversity.

Gene expression analysis of peroxisome proliferators- and phenytoin-induced hepatotoxicity using cDNA microarray.

The recent DNA microarray technology enables us to understand a large number of gene expression profiling. The technology has potential possibility to comprehend mechanism of multiple genes were related to compounds which have toxicity in biological system. So, the toxicogenomics through this technology may be very powerful for understanding the effect of unknown toxic mechanisms in biological system. We have studied that the effect of compounds related to hepatotoxin in vivo system using DNA microarray and classified chemicals which have been well characterized. We have studied three compounds; 2 peroxisome proliferators: Clofibrate (ethyl-p-chlorophenoxyisobutyrate), gemfibrozil (5-2[2,5-dimethyl-phenoxy]2-2-dimethyl-pentanonic), and an antiepileptic drug: phenytoin (5,5-diphenylhydantoin). Male Sprague-Dawely VAF(+) albino rats of 5-6 weeks old were treated with each compound for 24 hr and 2 weeks. 4.8 K cDNA microarray in house has been used for gene expression profiling. We found that the clustering of gene expression had similarity like as the toxic phenotype of compounds.

The intelligent data management system for toxicogenomics.

Toxicogenomics is now emerging as one of the most important genomic application because the toxicity test based on gene expression profiles is expected to be more precise and efficient than current histopathological approaches in a pre-clinical phase. One of the challenging issues in toxicogenomics is the construction of intelligent database management system which can deal with heterogeneous and complex data from many different experimental and information sources. TEST(Toxicogenomics for Efficient Safety Test) database is especially focused on the connectivity of heterogeneous data and the intelligent query system which enable users to obtain relevant useful information from the complex data sets. The database deals with four kinds of information; compound, histopathology, gene expression, and annotation information. Currently, TEST database maintains toxicogenomics information for 16 compounds, 45 microarrays, 190 animal experiments, and customized 4.8 K rat clone set. Our presented system is expected to be a good information source for studying of toxicology mechanism in the genome-wide level and can also be applied to the designing toxicity test chip.

cDNA microarray gene expression analysis and toxicological phenotype for anticancer drug.

Toxicogenomics, the subdiscipline that merges genomics with toxicology, hold the promise to contributing toward the goal of elucidating mechanism by studying genomic profiling related with various drugs. The application of gene expression profiling technology to examine multiple genes and signaling pathways promises a significant advance in understanding the toxic mechanisms of various drugs and prediction of new drug candidate. Toxicogenomics is emerging field combining genomics and bioinformatics to identify and characterize mechanisms of toxicity of drug and various compounds. The principal hypothesis underlying on this field is that chemical-specific pattern of altered gene expression is related with each chemicals properties, especially toxicological property, and it will be revealed using high-density microarray analysis of sample from exposed organisms. So, in this study we compare the gene expression pattern of two anticancer drugs paclitaxel and orally absorbable paclitaxel, using the cDNA microarray. And from the result of this study, it is possible to provide the new possibility for genome-wide insight into mechanism of their anticancer activity and toxicological phenotype.

Genomic mapping of the MHC transactivator CIITA using an integrated ChIP-seq and genetical genomics approach.

BACKGROUND: The master transactivator CIITA is essential to the regulation of Major Histocompatibility Complex (MHC)class II genes and an effective immune response. CIITA is known to modulate a small number of non-MHC genes involved in antigen presentation such as CD74 and B2M but its broader genome-wide function and relationship with underlying genetic diversity has not been resolved. RESULTS: We report the first genome-wide ChIP-seq map for CIITA and complement this by mapping inter-individual variation in CIITA expression as a quantitative trait. We analyse CIITA recruitment for pathophysiologically relevant primary human B cells and monocytes, resting and treated with interferon-gamma, in the context of the epigenomic regulatory landscape and DNA-binding proteins associated with the CIITA enhanceosome including RFX, CREB1/ATF1 and NFY. We confirm recruitment to proximal promoter sequences in MHC class II genes and more distally involving the canonical CIITA enhanceosome. Overall, we map 843 CIITA binding intervals involving 442 genes and find 95% of intervals are located outside the MHC and 60% not associated with RFX5 binding. Binding intervals are enriched for genes involved in immune function n and infectious disease with novel loci including major histone gene clusters. Were solve differentially expressed genes associated in trans with a CIITA intronic sequence variant, integrate with CIITA recruitment and show how this is mediated by allele-specific recruitment of NF-kB. CONCLUSIONS: Our results indicate a broader role for CIITA beyond the MHC involving immune-related genes.We provide new insights into allele-specific regulation of CIITA informative for understanding gene function and disease.

The Fusarium graminearum genome reveals more secondary metabolite gene clusters and hints of horizontal gene transfer.

Fungal secondary metabolite biosynthesis genes are of major interest due to the pharmacological properties of their products (like mycotoxins and antibiotics). The genome of the plant pathogenic fungus Fusarium graminearum codes for a large number of candidate enzymes involved in secondary metabolite biosynthesis. However, the chemical nature of most enzymatic products of proteins encoded by putative secondary metabolism biosynthetic genes is largely unknown. Based on our analysis we present 67 gene clusters with significant enrichment of predicted secondary metabolism related enzymatic functions. 20 gene clusters with unknown metabolites exhibit strong gene expression correlation in planta and presumably play a role in virulence. Furthermore, the identification of conserved and over-represented putative transcription factor binding sites serves as additional evidence for cluster co-regulation. Orthologous cluster search provided insight into the evolution of secondary metabolism clusters. Some clusters are characteristic for the Fusarium phylum while others show evidence of horizontal gene transfer as orthologs can be found in representatives of the Botrytis or Cochliobolus lineage. The presented candidate clusters provide valuable targets for experimental examination.

Systems biology of infectious diseases: a focus on fungal infections.

The study of infectious disease concerns the interaction between the host species and a pathogen organism. The analysis of such complex systems is improving with the evolution of high-throughput technologies and advanced computational resources. This article reviews integrative, systems-oriented approaches to understanding mechanisms underlying infection, immune response and inflammation to find biomarkers of disease and design new drugs. We focus on the systems biology process, especially the data gathering and analysis techniques rather than the experimental technologies or latest computational resources.