Yeast microarrays for genome wide parallel genetic and gene expression analysis

We have developed high-density DNA microarrays of yeast ORFs. These microarrays can monitor hybridization to ORFs for applications such as quantitative differential gene expression analysis and screening for sequence polymorphisms. Automated scripts retrieved sequence information from public databases to locate predicted ORFs and select appropriate primers for amplification. The primers were used to amplify yeast ORFs in 96-well plates, and the resulting products were arrayed using an automated micro arraying device. Arrays containing up to 2,479 yeast ORFs were printed on a single slide. The hybridization of fluorescently labeled samples to the array were detected and quantitated with a laser confocal scanning microscope. Applications of the microarrays are shown for genetic and gene expression analysis at the whole genome level.

Cluster analysis and display of genome-wide expression patterns

A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.

Genome-wide expression analysis reveals dysregulation of myelination-related genes in chronic schizophrenia

Neuropathological and brain imaging studies suggest that schizophrenia may result from neurodevelopmental defects. Cytoarchitectural studies indicate cellular abnormalities suggestive of a disruption in neuronal connectivity in schizophrenia, particularly in the dorsolateral prefrontal cortex. Yet, the molecular mechanisms underlying these findings remain unclear. To identify molecular substrates associated with schizophrenia, DNA microarray analysis was used to assay gene expression levels in postmortem dorsolateral prefrontal cortex of schizophrenic and control patients. Genes determined to have altered expression levels in schizophrenics relative to controls are involved in a number of biological processes, including synaptic plasticity, neuronal development, neurotransmission, and signal transduction. Most notable was the differential expression of myelination-related genes suggesting a disruption in oligodendrocyte function in schizophrenia.

Major quantitative trait locus for eosinophil count is located on chromosome 2q

Background: Eosinophils are granulocytic white blood cells implicated in asthma and atopic disease. The degree of eosinophilia in the blood of patients with asthma correlates with the severity of asthmatic symptoms. Quantitative trait loci (QTL) linkage analysis of eosinophil count may be a more powerful strategy of mapping genes involved in asthma than linkage analysis using affected relative pairs. 1 Objective: To identify QTLs responsible for variation in eosinophil count in adolescent twins. Methods: We measured eosinophil count longitudinally in 738 pairs of twins at 12, 14, and 16 years of age. We typed 757 highly polymorphic microsatellite markers at an average spacing of similar to5 centimorgans across the genome. We then used multipoint variance components linkage analysis to test for linkage between marker loci and eosinophil concentrations at each age across the genome. Results: We found highly significant linkage on chromosome 2q33 in 12-year-old twins (logarithm of the odds = 4.6; P = .000002) and suggestive evidence of linkage in the same region in 14-year-olds (logarithm of the odds = 1.0; P = .016). We also found suggestive evidence of linkage at other areas of the genome, including regions on chromosomes 2, 3, 4, 8, 9, 11, 12, 17, 20, and 22. Conclusion: A QTL for eosinophil count is present on chromosome 2q33. This QTL might represent a gene involved in asthma pathophysiology.

Origin and diversity of the Sox transcription factor gene family: genome-wide analysis in Fugu rubripes

The SOX family of transcription factors are found throughout the animal kingdom and are important in a variety of developmental contexts. Genome analysis has identified 20 Sox genes in human and mouse, which can be subdivided into 8 groups, based on sequence comparison and intron-exon structure. Most of the SOX groups identified in mammals are represented by a single SOX sequence in invertebrate model organisms, suggesting a duplication and divergence mechanism has operated during vertebrate evolution. We have now analysed the Sox gene complement in the pufferfish, Fugu rubripes, in order to shed further light on the diversity and origins of the Sox gene family. Major differences were found between the Sox family in Fugu and those in humans and mice. In particular, Fugu does not have orthologues of Sry, Sox,15 and Sox30, which appear to be specific to mammals, while Sox19, found in Fugu and zebrafish but absent in mammals, seems to be specific to fishes. Six mammalian Sox genes are represented by two copies each in Fugu, indicating a large-scale gene duplication in the fish lineage. These findings point to recent Sox gene loss, duplication and divergence occurring during the evolution of tetrapod and teleost lineages, and provide further evidence for large-scale segmental or a whole-genome duplication occurring early in the radiation of teleosts. (C) 2004 Elsevier B.V. All rights reserved.

Genome-wide analysis of mammalian promoter architecture and evolution

Mammalian promoters can be separated into two classes, conserved TATA box-enriched promoters, which initiate at a welldefined site, and more plastic, broad and evolvable CpG-rich promoters. We have sequenced tags corresponding to several hundred thousand transcription start sites (TSSs) in the mouse and human genomes, allowing precise analysis of the sequence architecture and evolution of distinct promoter classes. Different tissues and families of genes differentially use distinct types of promoters. Our tagging methods allow quantitative analysis of promoter usage in different tissues and show that differentially regulated alternative TSSs are a common feature in protein-coding genes and commonly generate alternative N termini. Among the TSSs, we identified new start sites associated with the majority of exons and with 3' UTRs. These data permit genome-scale identification of tissue-specific promoters and analysis of the cis-acting elements associated with them.

Genome-wide analysis identifies a general requirement for polarity proteins in endocytic traffic

In a genome-wide RNA-mediated interference screen for genes required in membrane traffic - including endocytic uptake, recycling from endosomes to the plasma membrane, and secretion - we identified 168 candidate endocytosis regulators and 100 candidate secretion regulators. Many of these candidates are highly conserved among metazoans but have not been previously implicated in these processes. Among the positives from the screen, we identified PAR-3, PAR-6, PKC-3 and CDC-42, proteins that are well known for their importance in the generation of embryonic and epithelial-cell polarity. Further analysis showed that endocytic transport in Caenorhabditis elegans coelomocytes and human HeLa cells was also compromised after perturbation of CDC-42/Cdc42 or PAR-6/Par6 function, indicating a general requirement for these proteins in regulating endocytic traffic. Consistent with these results, we found that tagged CDC-42/Cdc42 is enriched on recycling endosomes in C. elegans and mammalian cells, suggesting a direct function in the regulation of transport.

Genome-wide association analysis identifies novel loci for chronotype in 100,420 individuals from the UK Biobank

Our sleep timing preference, or chronotype, is a manifestation of our internal biological clock. Variation in chronotype has been linked to sleep disorders, cognitive and physical performance, and chronic disease. Here we perform a genome-wide association study of self-reported chronotype within the UK Biobank cohort (n=100,420). We identify 12 new genetic loci that implicate known components of the circadian clock machinery and point to previously unstudied genetic variants and candidate genes that might modulate core circadian rhythms or light-sensing pathways. Pathway analyses highlight central nervous and ocular systems and fear-response-related processes. Genetic correlation analysis suggests chronotype shares underlying genetic pathways with schizophrenia, educational attainment and possibly BMI. Further, Mendelian randomization suggests that evening chronotype relates to higher educational attainment. These results not only expand our knowledge of the circadian system in humans but also expose the influence of circadian characteristics over human health and life-history variables such as educational attainment.

Genome-wide association of multiple complex traits in outbred mice by ultra low-coverage sequencing

We thank the High-Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics and the Wellcome Trust Sanger Institute for the generation of the sequencing data. This work was funded by Wellcome Trust grant 090532/Z/09/Z (J.F.). Primary phenotyping of the mice was supported by the Mary Lyon Centre and Mammalian Genetics Unit (Medical Research Council, UK Hub grant G0900747 91070 and Medical Research Council, UK grant MC U142684172). D.A.B acknowledges support from NIH R01AR056280. The sleep work was supported by the state of Vaud (Switzerland) and the Swiss National Science Foundation (SNF 14694 and 136201 to P.F.). The ECG work was supported by the Netherlands CardioVascular Research Initiative (Dutch Heart Foundation, Dutch Federation of University Medical Centres, the Netherlands Organization for Health Research and Development, and the Royal Netherlands Academy of Sciences) PREDICT project, InterUniversity Cardiology Institute of the Netherlands (ICIN; 061.02; C.A.R., C.R.B). Na Cai is supported by the Agency of Science, Technology and Research (A*STAR) Graduate Academy. The authors wish to acknowledge excellent technical assistance from: Ayako Kurioka, Leo Swadling, Catherine de Lara, James Ussher, Rachel Townsend, Sima Lionikaite, Ausra S. Lionikiene, Rianne Wolswinkel and Inge van der Made. We would like to thank Thomas M Keane and Anthony G Doran for their help in annotating variants and adding the FVB/NJ strain to the Mouse Genomes Project.

Genome-wide association studies in oesophageal adenocarcinoma and Barrett's oesophagus: a large-scale meta-analysis

Background: Esophageal adenocarcinoma (EA) is one of the fastest rising cancers in western countries. Barrett’s Esophagus (BE) is the premalignant precursor of EA. However, only a subset of BE patients develop EA, which complicates the clinical management in the absence of valid predictors. Genetic risk factors for BE and EA are incompletely understood. This study aimed to identify novel genetic risk factors for BE and EA.Methods: Within an international consortium of groups involved in the genetics of BE/EA, we performed the first meta-analysis of all genome-wide association studies (GWAS) available, involving 6,167 BE patients, 4,112 EA patients, and 17,159 representative controls, all of European ancestry, genotyped on Illumina high-density SNP-arrays, collected from four separate studies within North America, Europe, and Australia. Meta-analysis was conducted using the fixed-effects inverse variance-weighting approach. We used the standard genome-wide significant threshold of 5×10-8 for this study. We also conducted an association analysis following reweighting of loci using an approach that investigates annotation enrichment among the genome-wide significant loci. The entire GWAS-data set was also analyzed using bioinformatics approaches including functional annotation databases as well as gene-based and pathway-based methods in order to identify pathophysiologically relevant cellular pathways.Findings: We identified eight new associated risk loci for BE and EA, within or near the CFTR (rs17451754, P=4·8×10-10), MSRA (rs17749155, P=5·2×10-10), BLK (rs10108511, P=2·1×10-9), KHDRBS2 (rs62423175, P=3·0×10-9), TPPP/CEP72 (rs9918259, P=3·2×10-9), TMOD1 (rs7852462, P=1·5×10-8), SATB2 (rs139606545, P=2·0×10-8), and HTR3C/ABCC5 genes (rs9823696, P=1·6×10-8). A further novel risk locus at LPA (rs12207195, posteriori probability=0·925) was identified after re-weighting using significantly enriched annotations. This study thereby doubled the number of known risk loci. The strongest disease pathways identified (P<10-6) belong to muscle cell differentiation and to mesenchyme development/differentiation, which fit with current pathophysiological BE/EA concepts. To our knowledge, this study identified for the first time an EA-specific association (rs9823696, P=1·6×10-8) near HTR3C/ABCC5 which is independent of BE development (P=0·45).Interpretation: The identified disease loci and pathways reveal new insights into the etiology of BE and EA. Furthermore, the EA-specific association at HTR3C/ABCC5 may constitute a novel genetic marker for the prediction of transition from BE to EA. Mutations in CFTR, one of the new risk loci identified in this study, cause cystic fibrosis (CF), the most common recessive disorder in Europeans. Gastroesophageal reflux (GER) belongs to the phenotypic CF-spectrum and represents the main risk factor for BE/EA. Thus, the CFTR locus may trigger a common GER-mediated pathophysiology.

Genome-wide association study reveals three susceptibility loci for common migraine in the general population

Migraine is a common, heterogeneous and heritable neurological disorder. Its pathophysiology is incompletely understood, and its genetic influences at the population level are unknown. In a population-based genome-wide analysis including 5,122 migraineurs and 18,108 non-migraineurs, rs2651899 (1p36.32, PRDM16), rs10166942 (2q37.1, TRPM8) and rs11172113 (12q13.3, LRP1) were among the top seven associations (P < 5 × 10(-6)) with migraine. These SNPs were significant in a meta-analysis among three replication cohorts and met genome-wide significance in a meta-analysis combining the discovery and replication cohorts (rs2651899, odds ratio (OR) = 1.11, P = 3.8 × 10(-9); rs10166942, OR = 0.85, P = 5.5 × 10(-12); and rs11172113, OR = 0.90, P = 4.3 × 10(-9)). The associations at rs2651899 and rs10166942 were specific for migraine compared with non-migraine headache. None of the three SNP associations was preferential for migraine with aura or without aura, nor were any associations specific for migraine features. TRPM8 has been the focus of neuropathic pain models, whereas LRP1 modulates neuronal glutamate signaling, plausibly linking both genes to migraine pathophysiology.

Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data

Background: Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. Methods: We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. Results: In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/ signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant difference (F = 2.75, P = 0.04) was detected for age of disease onset between the affected misclassified as controls (mean = 36 years) and the other three groups (high, 33.5 years; medium, 33.4 years; low, 33.1 years). Conclusions: The results are consistent with the polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of current knowledge in MS genetics.

A genome-wide scan provides evidence for loci influencing a severe heritable form of common migraine

Migraine is a prevalent neurovascular disease with a significant genetic component. Linkage studies have so far identified migraine susceptibility loci on chromosomes 1, 4, 6, 11, 14, 19 and X. We performed a genome-wide scan of 92 Australian pedigrees phenotyped for migraine with and without aura and for a more heritable form of “severe” migraine. Multipoint non-parametric linkage analysis revealed suggestive linkage on chromosome 18p11 for the severe migraine phenotype (LOD*=2.32, P=0.0006) and chromosome 3q (LOD*=2.28, P=0.0006). Excess allele sharing was also observed at multiple different chromosomal regions, some of which overlap with, or are directly adjacent to, previously implicated migraine susceptibility regions. We have provided evidence for two loci involved in severe migraine susceptibility and conclude that dissection of the “migraine” phenotype may be helpful for identifying susceptibility genes that influence the more heritable clinical (symptom) profiles in affected pedigrees. Also, we concluded that the genetic aetiology of the common (International Headache Society) forms of the disease is probably comprised of a number of low to moderate effect susceptibility genes, perhaps acting synergistically, and this effect is not easily detected by traditional single-locus linkage analyses of large samples of affected pedigrees.

Complete genomic sequence of a Rubus yellow net virus isolate and detection of genome-wide pararetrovirus-derived small RNAs

Rubus yellow net virus (RYNV) was cloned and sequenced from a red raspberry (Rubus idaeus L.) plant exhibiting symptoms of mosaic and mottling in the leaves. Its genomic sequence indicates that it is a distinct member of the genus Badnavirus, with 7932. bp and seven ORFs, the first three corresponding in size and location to the ORFs found in the type member Commelina yellow mottle virus. Bioinformatic analysis of the genomic sequence detected several features including nucleic acid binding motifs, multiple zinc finger-like sequences and domains associated with cellular signaling. Subsequent sequencing of the small RNAs (sRNAs) from RYNV-infected R. idaeus leaf tissue was used to determine any RYNV sequences targeted by RNA silencing and identified abundant virus-derived small RNAs (vsRNAs). The majority of the vsRNAs were 22-nt in length. We observed a highly uneven genome-wide distribution of vsRNAs with strong clustering to small defined regions distributed over both strands of the RYNV genome. Together, our data show that sequences of the aphid-transmitted pararetrovirus RYNV are targeted in red raspberry by the interfering RNA pathway, a predominant antiviral defense mechanism in plants. © 2013.