The effects of height and BMI on prostate cancer incidence and mortality: A Mendelian randomization study in 20,848 cases and 20,214 controls from the PRACTICAL consortium

Background Epidemiological studies suggest a potential role for obesity and determinants of adult stature in prostate cancer risk and mortality, but the relationships described in the literature are complex. To address uncertainty over the causal nature of previous observational findings, we investigated associations of height- and adiposity-related genetic variants with prostate cancer risk and mortality. Methods We conducted a case–control study based on 20,848 prostate cancers and 20,214 controls of European ancestry from 22 studies in the PRACTICAL consortium. We constructed genetic risk scores that summed each man’s number of height and BMI increasing alleles across multiple single nucleotide polymorphisms robustly associated with each phenotype from published genome-wide association studies. Results The genetic risk scores explained 6.31 and 1.46 % of the variability in height and BMI, respectively. There was only weak evidence that genetic variants previously associated with increased BMI were associated with a lower prostate cancer risk (odds ratio per standard deviation increase in BMI genetic score 0.98; 95 % CI 0.96, 1.00; p = 0.07). Genetic variants associated with increased height were not associated with prostate cancer incidence (OR 0.99; 95 % CI 0.97, 1.01; p = 0.23), but were associated with an increase (OR 1.13; 95 % CI 1.08, 1.20) in prostate cancer mortality among low-grade disease (p heterogeneity, low vs. high grade <0.001). Genetic variants associated with increased BMI were associated with an increase (OR 1.08; 95 % CI 1.03, 1.14) in all-cause mortality among men with low-grade disease (p heterogeneity = 0.03). Conclusions We found little evidence of a substantial effect of genetically elevated height or BMI on prostate cancer risk, suggesting that previously reported observational associations may reflect common environmental determinants of height or BMI and prostate cancer risk. Genetically elevated height and BMI were associated with increased mortality (prostate cancer-specific and all-cause, respectively) in men with low-grade disease, a potentially informative but novel finding that requires replication.

Genome-wide DNA methylation profiling of CD8+ T cells shows a distinct epigenetic signature to CD4+ T cells in multiple sclerosis patients

Background Multiple sclerosis (MS) is thought to be a T cell-mediated autoimmune disorder. MS pathogenesis is likely due to a genetic predisposition triggered by a variety of environmental factors. Epigenetics, particularly DNA methylation, provide a logical interface for environmental factors to influence the genome. In this study we aim to identify DNA methylation changes associated with MS in CD8+ T cells in 30 relapsing remitting MS patients and 28 healthy blood donors using Illumina 450K methylation arrays. Findings Seventy-nine differentially methylated CpGs were associated with MS. The methylation profile of CD8+ T cells was distinctive from our previously published data on CD4+ T cells in the same cohort. Most notably, there was no major CpG effect at the MS risk gene HLA-DRB1 locus in the CD8+ T cells. Conclusion CD8+ T cells and CD4+ T cells have distinct DNA methylation profiles. This case–control study highlights the importance of distinctive cell subtypes when investigating epigenetic changes in MS and other complex diseases.

Genome wide chromatin occupancy of mrhl RNA and its role in gene regulation in mouse spermatogonial cells

Mrhl RNA is a nuclear lncRNA encoded in the mouse genome and negatively regulates Wnt signaling in spermatogonial cells through p68/Ddx5 RNA helicase. Mrhl RNA is present in the chromatin fraction of mouse spermatogonial Gc1-Spg cells and genome wide chromatin occupancy of mrhl RNA by ChOP (Chromatin oligo affinity precipitation) technique identified 1370 statistically significant genomic loci. Among these, genes at 37 genomic loci also showed altered expression pattern upon mrhl RNA down regulation which are referred to as GRPAM (Genes Regulated by Physical Association of Mrhl RNA). p68 interacted with mrhl RNA in chromatin at these GRPAM loci. p68 silencing drastically reduced mrhl RNA occupancy at 27 GRPAM loci and also perturbed the expression of GRPAM suggesting a role for p68 mediated mrhl RNA occupancy in regulating GRPAM expression. Wnt3a ligand treatment of Gc1-Spg cells down regulated mrhl RNA expression and also perturbed expression of these 27 GRPAM genes that included genes regulating Wnt signaling pathway and spermatogenesis, one of them being Sox8, a developmentally important transcription factor. We also identified interacting proteins of mrhl RNA associated chromatin fraction which included Pc4, a chromatin organizer protein and hnRNP A/B and hnRNP A2/B1 which have been shown to be associated with lincRNA-Cox2 function in gene regulation. Our findings in the Gc1-Spg cell line also correlate with the results from analysis of mouse testicular tissue which further highlights the in vivo physiological significance of mrhl RNA in the context of gene regulation during mammalian spermatogenesis.

Genome-wide analysis correlates Ayurveda Prakriti

The practice of Ayurveda, the traditional medicine of India, is based on the concept of three major constitutional types (Vata, Pitta and Kapha) defined as ``Prakriti''. To the best of our knowledge, no study has convincingly correlated genomic variations with the classification of Prakriti. In the present study, we performed genome-wide SNP (single nucleotide polymorphism) analysis (Affymetrix, 6.0) of 262 well-classified male individuals (after screening 3416 subjects) belonging to three Prakritis. We found 52 SNPs (p <= 1 x 10(-5)) were significantly different between Prakritis, without any confounding effect of stratification, after 10(6) permutations. Principal component analysis (PCA) of these SNPs classified 262 individuals into their respective groups (Vata, Pitta and Kapha) irrespective of their ancestry, which represent its power in categorization. We further validated our finding with 297 Indian population samples with known ancestry. Subsequently, we found that PGM1 correlates with phenotype of Pitta as described in the ancient text of Caraka Samhita, suggesting that the phenotypic classification of India's traditional medicine has a genetic basis; and its Prakriti-based practice in vogue for many centuries resonates with personalized medicine.

Genome-wide identification and characterization of cytochrome P450 monooxygenase genes in the ciliate Tetrahymena thermophila

Background: Cytochrome P450 monooxygenases play key roles in the metabolism of a wide variety of substrates and they are closely associated with endocellular physiological processes or detoxification metabolism under environmental exposure. To date, however, none has been systematically characterized in the phylum Ciliophora. T. thermophila possess many advantages as a eukaryotic model organism and it exhibits rapid and sensitive responses to xenobiotics, making it an ideal model system to study the evolutionary and functional diversity of the P450 monooxygenase gene family. Results: A total of 44 putative functional cytochrome P450 genes were identified and could be classified into 13 families and 21 sub-families according to standard nomenclature. The characteristics of both the conserved intron-exon organization and scaffold localization of tandem repeats within each P450 family clade suggested that the enlargement of T. thermophila P450 families probably resulted from recent separate small duplication events. Gene expression patterns of all T. thermophila P450s during three important cell physiological stages (vegetative growth, starvation and conjugation) were analyzed based on EST and microarray data, and three main categories of expression patterns were postulated. Evolutionary analysis including codon usage preference, sit-especific selection and gene-expression evolution patterns were investigated and the results indicated remarkable divergences among the T. thermophila P450 genes. Conclusion: The characterization, expression and evolutionary analysis of T. thermophila P450 monooxygenase genes in the current study provides useful information for understanding the characteristics and diversities of the P450 genes in the Ciliophora, and provides the baseline for functional analyses of individual P450 isoforms in this model ciliate species.

Genome-wide survey of putative serine/threonine protein kinases in cyanobacteria

Background: Serine/threonine kinases (STKs) have been found in an increasing number of prokaryotes, showing important roles in signal transduction that supplement the well known role of two-component system. Cyanobacteria are photoautotrophic prokaryotes able to grow in a wide range of ecological environments, and their signal transduction systems are important in adaptation to the environment. Sequence information from several cyanobacterial genomes offers a unique opportunity to conduct a comprehensive comparative analysis of this kinase family. In this study, we extracted information regarding Ser/Thr kinases from 21 species of sequenced cyanobacteria and investigated their diversity, conservation, domain structure, and evolution. Results: 286 putative STK homologues were identified. STKs are absent in four Prochlorococcus strains and one marine Synechococcus strain and abundant in filamentous nitrogen-fixing cyanobacteria. Motifs and invariant amino acids typical in eukaryotic STKs were conserved well in these proteins, and six more cyanobacteria- or bacteria-specific conserved residues were found. These STK proteins were classified into three major families according to their domain structures. Fourteen types and a total of 131 additional domains were identified, some of which are reported to participate in the recognition of signals or substrates. Cyanobacterial STKs show rather complicated phylogenetic relationships that correspond poorly with phylogenies based on 16S rRNA and those based on additional domains. Conclusion: The number of STK genes in different cyanobacteria is the result of the genome size, ecophysiology, and physiological properties of the organism. Similar conserved motifs and amino acids indicate that cyanobacterial STKs make use of a similar catalytic mechanism as eukaryotic STKs. Gene gain-and-loss is significant during STK evolution, along with domain shuffling and insertion. This study has established an overall framework of sequence-structure-function interactions for the STK gene family, which may facilitate further studies of the role of STKs in various organisms.

Genome-wide survey of putative serine/threonine protein kinases in cyanobacteria

Background: Serine/threonine kinases (STKs) have been found in an increasing number of prokaryotes, showing important roles in signal transduction that supplement the well known role of two-component system. Cyanobacteria are photoautotrophic prokaryotes able to grow in a wide range of ecological environments, and their signal transduction systems are important in adaptation to the environment. Sequence information from several cyanobacterial genomes offers a unique opportunity to conduct a comprehensive comparative analysis of this kinase family. In this study, we extracted information regarding Ser/Thr kinases from 21 species of sequenced cyanobacteria and investigated their diversity, conservation, domain structure, and evolution. Results: 286 putative STK homologues were identified. STKs are absent in four Prochlorococcus strains and one marine Synechococcus strain and abundant in filamentous nitrogen-fixing cyanobacteria. Motifs and invariant amino acids typical in eukaryotic STKs were conserved well in these proteins, and six more cyanobacteria- or bacteria-specific conserved residues were found. These STK proteins were classified into three major families according to their domain structures. Fourteen types and a total of 131 additional domains were identified, some of which are reported to participate in the recognition of signals or substrates. Cyanobacterial STKs show rather complicated phylogenetic relationships that correspond poorly with phylogenies based on 16S rRNA and those based on additional domains. Conclusion: The number of STK genes in different cyanobacteria is the result of the genome size, ecophysiology, and physiological properties of the organism. Similar conserved motifs and amino acids indicate that cyanobacterial STKs make use of a similar catalytic mechanism as eukaryotic STKs. Gene gain-and-loss is significant during STK evolution, along with domain shuffling and insertion. This study has established an overall framework of sequence-structure-function interactions for the STK gene family, which may facilitate further studies of the role of STKs in various organisms.

Computational Inference of Genome-Wide Protein-DNA Interactions Using High-Throughput Genomic Data

Transcriptional regulation has been studied intensively in recent decades. One important aspect of this regulation is the interaction between regulatory proteins, such as transcription factors (TF) and nucleosomes, and the genome. Different high-throughput techniques have been invented to map these interactions genome-wide, including ChIP-based methods (ChIP-chip, ChIP-seq, etc.), nuclease digestion methods (DNase-seq, MNase-seq, etc.), and others. However, a single experimental technique often only provides partial and noisy information about the whole picture of protein-DNA interactions. Therefore, the overarching goal of this dissertation is to provide computational developments for jointly modeling different experimental datasets to achieve a holistic inference on the protein-DNA interaction landscape.

We first present a computational framework that can incorporate the protein binding information in MNase-seq data into a thermodynamic model of protein-DNA interaction. We use a correlation-based objective function to model the MNase-seq data and a Markov chain Monte Carlo method to maximize the function. Our results show that the inferred protein-DNA interaction landscape is concordant with the MNase-seq data and provides a mechanistic explanation for the experimentally collected MNase-seq fragments. Our framework is flexible and can easily incorporate other data sources. To demonstrate this flexibility, we use prior distributions to integrate experimentally measured protein concentrations.

We also study the ability of DNase-seq data to position nucleosomes. Traditionally, DNase-seq has only been widely used to identify DNase hypersensitive sites, which tend to be open chromatin regulatory regions devoid of nucleosomes. We reveal for the first time that DNase-seq datasets also contain substantial information about nucleosome translational positioning, and that existing DNase-seq data can be used to infer nucleosome positions with high accuracy. We develop a Bayes-factor-based nucleosome scoring method to position nucleosomes using DNase-seq data. Our approach utilizes several effective strategies to extract nucleosome positioning signals from the noisy DNase-seq data, including jointly modeling data points across the nucleosome body and explicitly modeling the quadratic and oscillatory DNase I digestion pattern on nucleosomes. We show that our DNase-seq-based nucleosome map is highly consistent with previous high-resolution maps. We also show that the oscillatory DNase I digestion pattern is useful in revealing the nucleosome rotational context around TF binding sites.

Finally, we present a state-space model (SSM) for jointly modeling different kinds of genomic data to provide an accurate view of the protein-DNA interaction landscape. We also provide an efficient expectation-maximization algorithm to learn model parameters from data. We first show in simulation studies that the SSM can effectively recover underlying true protein binding configurations. We then apply the SSM to model real genomic data (both DNase-seq and MNase-seq data). Through incrementally increasing the types of genomic data in the SSM, we show that different data types can contribute complementary information for the inference of protein binding landscape and that the most accurate inference comes from modeling all available datasets.

This dissertation provides a foundation for future research by taking a step toward the genome-wide inference of protein-DNA interaction landscape through data integration.

Significant correlation in linkage signals from genome-wide scans of schizophrenia and schizotypy

Prior family and adoption studies have suggested a genetic relationship between schizophrenia and schizotypy. However, this has never been verified using linkage methods. We therefore attempted to test for a correlation in linkage signals from genome-wide scans of schizophrenia and schizotypy. The Irish study of high-density schizophrenia families comprises 270 families with at least two members with schizophrenia or poor-outcome schizoaffective disorder (n = 637). Non-psychotic relatives were assessed using the structured interview for schizotypy (n = 746). A 10-cM multipoint, non-parametric, autosomal genomewide scan of schizophrenia was performed in Merlin. A scan of a quantitative trait comprising ratings of DSM-III-R criteria for schizotypal personality disorder in non-psychotic relatives was also performed. Schizotypy logarithm of the odds (LOD) scores were regressed onto schizophrenia LOD scores at all loci, with adjustment for spatial autocorrelation. To assess empirical significance, this was also carried out using 1000 null scans of schizotypy. The number of jointly linked loci in the real data was compared to distribution of jointly linked loci in the null scans. No markers were suggestively linked to schizotypy based on strict Lander Kruglyak criteria. Schizotypy LODs predicted schizophrenia LODs above chance expectation genome wide (empirical P = 0.04). Two and four loci yielded nonparametric LOD (NPLs) > 1.0 and > 0.75, respectively, for both schizophrenia and schizotypy (genome-wide empirical P = 0.04 and 0.02, respectively). These results suggest that at least a subset of schizophrenia susceptibility genes also affects schizotypy in non-psychotic relatives. Power may therefore be increased in molecular genetic studies of schizophrenia if they incorporate measures of schizotypy in non-psychotic relatives.

Characterisation of Genome-Wide PLZF/RARA Target Genes

The PLZF/RARA fusion protein generated by the t(11;17)(q23;q21) translocation in acute promyelocytic leukaemia (APL) is believed to act as an oncogenic transcriptional regulator recruiting epigenetic factors to genes important for its transforming potential. However, molecular mechanisms associated with PLZF/RARA-dependent leukaemogenesis still remain unclear. We searched for specific PLZF/RARA target genes by ChIP-on-chip in the haematopoietic cell line U937 conditionally expressing PLZF/RARA. By comparing bound regions found in U937 cells expressing endogenous PLZF with PLZF/RARA-induced U937 cells, we isolated specific PLZF/RARA target gene promoters. We next analysed gene expression profiles of our identified target genes in PLZF/RARA APL patients and analysed DNA sequences and epigenetic modification at PLZF/RARA binding sites. We identify 413 specific PLZF/RARA target genes including a number encoding transcription factors involved in the regulation of haematopoiesis. Among these genes, 22 were significantly down regulated in primary PLZF/RARA APL cells. In addition, repressed PLZF/RARA target genes were associated with increased levels of H3K27me3 and decreased levels of H3K9K14ac. Finally, sequence analysis of PLZF/RARA bound sequences reveals the presence of both consensus and degenerated RAREs as well as enrichment for tissue-specific transcription factor motifs, highlighting the complexity of targeting fusion protein to chromatin. Our study suggests that PLZF/RARA directly targets genes important for haematopoietic development and supports the notion that PLZF/RARA acts mainly as an epigenetic regulator of its direct target genes.

Genome-wide scans of three independent sets of 90 Irish multiplex schizophrenia families and follow-up of selected regions in all families provides evidence for multiple susceptibility genes

From our linkage study of Irish families with a high density of schizophrenia, we have previously reported evidence for susceptibility genes in regions 5q21-31, 6p24-21, 8p22-21, and 10p15-p11. In this report, we describe the cumulative results from independent genome scans of three a priori random subsets of 90 families each, and from multipoint analysis of all 270 families in ten regions. Of these ten regions, three (13q32, 18p11-q11, and 18q22-23) did not generate scores above the empirical baseline pairwise scan results, and one (6q13-26) generated a weak signal. Six other regions produced more positive pairwise and multipoint results. They showed the following maximum multipoint H-LOD (heterogeneity LOD) and NPL scores: 2p14-13: 0.89 (P = 0.06) and 2.08 (P = 0.02), 4q24-32: 1.84 (P = 0.007) and 1.67 (P = 0.03), 5q21-31: 2.88 (P= 0.0007), and 2.65 (P = 0.002), 6p25-24: 2.13 (P = 0.005) and 3.59 (P = 0.0005), 6p23: 2.42 (P = 0.001) and 3.07 (P = 0.001), 8p22-21: 1.57 (P = 0.01) and 2.56 (P = 0.005), 10p15-11: 2.04 (P = 0.005) and 1.78 (P = 0.03). The degree of 'internal replication' across subsets differed, with 5q, 6p, and 8p being most consistent and 2p and 10p being least consistent. On 6p, the data suggested the presence of two susceptibility genes, in 6p25-24 and 6p23-22. Very few families were positive on more than one region, and little correlation between regions was evident, suggesting substantial locus heterogeneity. The levels of statistical significance were modest, as expected from loci contributing to complex traits. However, our internal replications, when considered along with the positive results obtained in multiple other samples, suggests that most of these six regions are likely to contain genes that influence liability to schizophrenia.

Next-generation sequencing of the mitochondrial genome and association with IgA nephropathy in a renal transplant population

Kidneys are highly aerobic organs that are critically dependent on the normal functioning of mitochondria. Genetic variations disrupting mitochondrial function are associated with multifactorial disorders including kidney disease. This study sequenced the entire mitochondrial genome in a renal transplant cohort of 64 individuals, using next-generation sequencing, to evaluate the association of genetic variants with IgA nephropathy and end-stage renal disease (ESRD, n = 100).

Meta-analysis and imputation refines the association of 15q25 with smoking quantity.

Smoking is a leading global cause of disease and mortality. We established the Oxford-GlaxoSmithKline study (Ox-GSK) to perform a genome-wide meta-analysis of SNP association with smoking-related behavioral traits. Our final data set included 41,150 individuals drawn from 20 disease, population and control cohorts. Our analysis confirmed an effect on smoking quantity at a locus on 15q25 (P = 9.45 x 10(-19)) that includes CHRNA5, CHRNA3 and CHRNB4, three genes encoding neuronal nicotinic acetylcholine receptor subunits. We used data from the 1000 Genomes project to investigate the region using imputation, which allowed for analysis of virtually all common SNPs in the region and offered a fivefold increase in marker density over HapMap2 (ref. 2) as an imputation reference panel. Our fine-mapping approach identified a SNP showing the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.

Genome wide search for genetic determinants of habitual alcohol, tobacco and coffee use, obesity-related traits, response to mental and physical stress and hemodynamic traits

Les habitudes de consommation de substances psychoactives, le stress, l’obésité et les traits cardiovasculaires associés seraient en partie reliés aux mêmes facteurs génétiques. Afin d’explorer cette hypothèse, nous avons effectué, chez 119 familles multi-générationnelles québécoises de la région du Saguenay-Lac-St-Jean, des études d’association et de liaison pangénomiques pour les composantes génétiques : de la consommation usuelle d’alcool, de tabac et de café, de la réponse au stress physique et psychologique, des traits anthropométriques reliés à l’obésité, ainsi que des mesures du rythme cardiaque (RC) et de la pression artérielle (PA). 58000 SNPs et 437 marqueurs microsatellites ont été utilisés et l’annotation fonctionnelle des gènes candidats identifiés a ensuite été réalisée. Nous avons détecté des corrélations phénotypiques significatives entre les substances psychoactives, le stress, l’obésité et les traits hémodynamiques. Par exemple, les consommateurs d’alcool et de tabac ont montré un RC significativement diminué en réponse au stress psychologique. De plus, les consommateurs de tabac avaient des PA plus basses que les non-consommateurs. Aussi, les hypertendus présentaient des RC et PA systoliques accrus en réponse au stress psychologique et un indice de masse corporelle (IMC) élevé, comparativement aux normotendus. D’autre part, l’utilisation de tabac augmenterait les taux corporels d’épinéphrine, et des niveaux élevés d’épinéphrine ont été associés à des IMC diminués. Ainsi, en accord avec les corrélations inter-phénotypiques, nous avons identifié plusieurs gènes associés/liés à la consommation de substances psychoactives, à la réponse au stress physique et psychologique, aux traits reliés à l’obésité et aux traits hémodynamiques incluant CAMK4, CNTN4, DLG2, DAG1, FHIT, GRID2, ITPR2, NOVA1, NRG3 et PRKCE. Ces gènes codent pour des protéines constituant un réseau d’interactions, impliquées dans la plasticité synaptique, et hautement exprimées dans le cerveau et ses tissus associés. De plus, l’analyse des sentiers de signalisation pour les gènes identifiés (P = 0,03) a révélé une induction de mécanismes de Potentialisation à Long Terme. Les variations des traits étudiés seraient en grande partie liées au sexe et au statut d’hypertension. Pour la consommation de tabac, nous avons noté que le degré et le sens des corrélations avec l’obésité, les traits hémodynamiques et le stress sont spécifiques au sexe et à la pression artérielle. Par exemple, si des variations ont été détectées entre les hommes fumeurs et non-fumeurs (anciens et jamais), aucune différence n’a été observée chez les femmes. Nous avons aussi identifié de nombreux traits reliés à l’obésité dont la corrélation avec la consommation de tabac apparaît essentiellement plus liée à des facteurs génétiques qu’au fait de fumer en lui-même. Pour le sexe et l’hypertension, des différences dans l’héritabilité de nombreux traits ont également été observées. En effet, des analyses génétiques sur des sous-groupes spécifiques ont révélé des gènes additionnels partageant des fonctions synaptiques : CAMK4, CNTN5, DNM3, KCNAB1 (spécifique à l’hypertension), CNTN4, DNM3, FHIT, ITPR1 and NRXN3 (spécifique au sexe). Ces gènes codent pour des protéines interagissant avec les protéines de gènes détectés dans l’analyse générale. De plus, pour les gènes des sous-groupes, les résultats des analyses des sentiers de signalisation et des profils d’expression des gènes ont montré des caractéristiques similaires à celles de l’analyse générale. La convergence substantielle entre les déterminants génétiques des substances psychoactives, du stress, de l’obésité et des traits hémodynamiques soutiennent la notion selon laquelle les variations génétiques des voies de plasticité synaptique constitueraient une interface commune avec les différences génétiques liées au sexe et à l’hypertension. Nous pensons, également, que la plasticité synaptique interviendrait dans de nombreux phénotypes complexes influencés par le mode de vie. En définitive, ces résultats indiquent que des approches basées sur des sous-groupes et des réseaux amélioreraient la compréhension de la nature polygénique des phénotypes complexes, et des processus moléculaires communs qui les définissent.