A Novel Multilocus Sequence Typing Scheme for the Opportunistic Pathogen Propionibacterium acnes and Characterisation of Type I Cell Surface-Associated Antigens.

We have developed a novel Multilocus Sequence Typing Scheme (MLST) and database (http://pubmlst.org/pacnes/) for Propionibacterium acnes based on the analysis of seven core housekeeping genes. The scheme, which was validated against previously described antibody, single locus and Random Amplification of Polymorphic DNA (RAPD) typing methods, displayed excellent resolution and differentiated 123 isolates into 37 sequence types (ST). An overall clonal population structure was detected with six eBURST groups representing the major clades I, II and III, along with two singletons. Two highly successful and global clonal lineages, ST6 (type IA) and ST10 (type IB1), representing 65% of this current MLST isolate collection were identified. The ST6 clone and closely related single locus variants (SLV), which comprise a large clonal complex CC6, dominated isolates from patients with acne, and were also significantly associated with ophthalmic infections. Our data therefore supports an association between acne and P. acnes strains from the type IA cluster and highlights the role of a widely disseminated clonal genotype in this condition. Characterisation of type I cell surface-associated antigens that are not detected in ST10 or strains of type II and III identified two dermatan-sulphate-binding proteins with putative phase/antigenic variation signatures. We propose that the expression of these proteins by type IA organisms contributes to their role in the pathophysiology of acne and helps explain the recurrent nature of the disease. The MLST scheme and database described in this study should provide a valuable platform for future epidemiological and evolutionary studies of P. acnes.

Pseudomonas aeruginosa exhibits frequent recombination, but only a limited association between genotype and ecological setting

Pseudomonas aeruginosa is an opportunistic pathogen and an important cause of infection, particularly amongst cystic fibrosis (CF) patients. While specific strains capable of patient-to-patient transmission are known, many infections appear to be caused by unique and unrelated strains. There is a need to understand the relationship between strains capable of colonising the CF lung and the broader set of P. aeruginosa isolates found in natural environments. Here we report the results of a multilocus sequence typing (MLST)-based study designed to understand the genetic diversity and population structure of an extensive regional sample of P. aeruginosa isolates from South East Queensland, Australia. The analysis is based on 501 P. aeruginosa isolates obtained from environmental, animal and human (CF and non-CF) sources with particular emphasis on isolates from the Lower Brisbane River and isolates from CF patients obtained from the same geographical region. Overall, MLST identified 274 different sequence types, of which 53 were shared between one or more ecological settings. Our analysis revealed a limited association between genotype and environment and evidence of frequent recombination. We also found that genetic diversity of P. aeruginosa in Queensland, Australia was indistinguishable from that of the global P. aeruginosa population. Several CF strains were encountered frequently in multiple ecological settings; however, the most frequently encountered CF strains were confined to CF patients. Overall, our data confirm a non-clonal epidemic structure and indicate that most CF strains are a random sample of the broader P. aeruginosa population. The increased abundance of some CF strains in different geographical regions is a likely product of chance colonisation events followed by adaptation to the CF lung and horizontal transmission among patients.

Does genotype and equol-production status affect response to isoflavones? Data from a pan-European study on the effects of isoflavones on cardiovascular risk markers in post-menopausal women

The increase in CVD incidence following the menopause is associated with oestrogen loss. Dietary isoflavones are thought to be cardioprotective via their oestrogenic and oestrogen receptor-independent effects, but evidence to support this role is scarce. Individual variation in response to diet may be considerable and can obscure potential beneficial effects in a sample population; in particular, the response to isoflavone treatment may vary according to genotype and equol-production status. The effects of isoflavone supplementation (50hairspmg/d) on a range of established and novel biomarkers of CVD, including markers of lipid and glucose metabolism and inflammatory biomarkers, have been investigated in a placebo-controlled 2x8-week randomised cross-over study in 117 healthy post-menopausal women. Responsiveness to isoflavone supplementation according to (1) single nucleotide polymorphisms in a range of key CVD genes, including oestrogen receptor (ER) alpha and beta and (2) equol-production status has been examined. Isoflavones supplementation was found to have no effect on markers of lipids and glucose metabolism. Isoflavones improve C-reactive protein concentrations but do not affect other plasma inflammatory markers. There are no differences in response to isoflavones according to equol-production status. However, differences in HDL-cholesterol and vascular cell adhesion molecule 1 response to isoflavones v. placebo are evident with specific ER beta genotypes. In conclusion, isoflavones have beneficial effects on C-reactive protein, but not other cardiovascular risk markers. However, specific ER beta gene polymorphic subgroups may benefit from isoflavone supplementation.

Genotype and antibiotic resistance analyses of Campylobacter isolates from ceca and carcasses of slaughtered broiler flocks

To obtain genetic information about Campylobacter jejuni and Campylobacter coli from broilers and carcasses at slaughterhouses, we analyzed and compared 340 isolates that were collected in 2008 from the cecum right after slaughter or from the neck skin after processing. We performed rpoB sequence-based identification, multilocus sequence typing (MLST), and flaB sequence-based typing; we additionally analyzed mutations within the 23S rRNA and gyrA genes that confer resistance to macrolide and quinolone antibiotics, respectively. The rpoB-based identification resulted in a distribution of 72.0% C. jejuni and 28.0% C. coli. The MLST analysis revealed that there were 59 known sequence types (STs) and 6 newly defined STs. Most of the STs were grouped into 4 clonal complexes (CC) that are typical for poultry (CC21, CC45, CC257, and CC828), and these represented 61.8% of all of the investigated isolates. The analysis of 95 isolates from the cecum and from the corresponding carcass neck skin covered 44 different STs, and 54.7% of the pairs had matching genotypes. The data indicate that cross-contamination from various sources during slaughter may occur, although the majority of Campylobacter contamination on carcasses appeared to originate from the slaughtered flock itself. Mutations in the 23S rRNA gene were found in 3.1% of C. coli isolates, although no mutations were found in C. jejuni isolates. Mutations in the gyrA gene were observed in 18.9% of C. jejuni and 26.8% of C. coli isolates, which included two C. coli strains that carried mutations conferring resistance to both classes of antibiotics. A relationship between specific genotypes and antibiotic resistance/susceptibility was observed.

EXPLORATION, NORMALIZATION, AND GENOTYPE CALLS OF HIGH DENSITY OLIGONUCLEOTIDE SNP ARRAY DATA

In most microarray technologies, a number of critical steps are required to convert raw intensity measurements into the data relied upon by data analysts, biologists and clinicians. These data manipulations, referred to as preprocessing, can influence the quality of the ultimate measurements. In the last few years, the high-throughput measurement of gene expression is the most popular application of microarray technology. For this application, various groups have demonstrated that the use of modern statistical methodology can substantially improve accuracy and precision of gene expression measurements, relative to ad-hoc procedures introduced by designers and manufacturers of the technology. Currently, other applications of microarrays are becoming more and more popular. In this paper we describe a preprocessing methodology for a technology designed for the identification of DNA sequence variants in specific genes or regions of the human genome that are associated with phenotypes of interest such as disease. In particular we describe methodology useful for preprocessing Affymetrix SNP chips and obtaining genotype calls with the preprocessed data. We demonstrate how our procedure improves existing approaches using data from three relatively large studies including one in which large number independent calls are available. Software implementing these ideas are avialble from the Bioconductor oligo package.

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

A novel multilocus sequence typing scheme for the opportunistic pathogen Propionibacterium acnes and characterisation of type 1 cell surface-associated antigens

We have developed a novel multilocus sequence typing (MLST) scheme and database (http://pubmlst.org/pacnes/) for Propionibacterium acnes based on the analysis of seven core housekeeping genes. The scheme, which was validated against previously described antibody, single locus and random amplification of polymorphic DNA typing methods, displayed excellent resolution and differentiated 123 isolates into 37 sequence types (STs). An overall clonal population structure was detected with six eBURST groups representing the major clades I, II and III, along with two singletons. Two highly successful and global clonal lineages, ST6 (type IA) and ST10 (type IB1), representing 64?% of this current MLST isolate collection were identified. The ST6 clone and closely related single locus variants, which comprise a large clonal complex CC6, dominated isolates from patients with acne, and were also significantly associated with ophthalmic infections. Our data therefore support an association between acne and P. acnes strains from the type IA cluster and highlight the role of a widely disseminated clonal genotype in this condition. Characterization of type I cell surface-associated antigens that are not detected in ST10 or strains of type II and III identified two dermatan-sulphate-binding proteins with putative phase/antigenic variation signatures. We propose that the expression of these proteins by type IA organisms contributes to their role in the pathophysiology of acne and helps explain the recurrent nature of the disease. The MLST scheme and database described in this study should provide a valuable platform for future epidemiological and evolutionary studies of P. acnes.

The association between MC1R genotype and BRAF mutation status in cutaneous melanoma : findings from an Australian population

There is increasing epidemiological and molecular evidence that cutaneous melanomas arise through multiple causal pathways. The purpose of this study was to explore the relationship between germline and somatic mutations in a population-based series of melanoma patients to reshape and refine the divergent pathway model for melanoma. Melanomas collected from 123 Australian patients were analyzed for melanocortin-1 receptor (MC1R) variants and mutations in the BRAF and NRAS genes. Detailed phenotypic and sun exposure data were systematically collected from all patients. We found that BRAF-mutant melanomas were significantly more likely from younger patients and those with high nevus counts, and were more likely in melanomas with adjacent neval remnants. Conversely, BRAF-mutant melanomas were significantly less likely in people with high levels of lifetime sun exposure. We observed no association between germline MC1R status and somatic BRAF mutations in melanomas from this population. BRAF-mutant melanomas have different origins from other cutaneous melanomas. These data support the divergent pathways hypothesis for melanoma, which may require a reappraisal of targeted cancer prevention activities.

Induction of antioxidative Nrf2 gene transcription by coffee in humans : depending on genotype?

The Nrf2/ARE pathway is a major cellular defense mechanism that prevents damage by reactive oxygen species through induction of antioxidative phase II enzymes. However, the activity of the Nrf2/ARE system is not uniform with variability in response presumed to be dependent on the Nrf2 genotype. We recently completed a pilot human coffee intervention trial with healthy humans, where large interindividual differences in the antioxidative response to the study coffee were examined. Here, we address the question whether differences in the modulation of Nrf2 gene transcription, assessed as an induction of Nrf2 gene transcription by Q-PCR, might be correlated with specific Nrf2 genotypes. To date, nine single nucleotide polymorphisms (SNPs) have been identified in the Nrf2 (NFE2L2) gene. Two of these, the -617C/A and -651G/A SNPs are located within the promoter region and have previously been reported to influence the activity of the Nrf2/ARE pathway by reducing Nrf2 transcriptional activity. Sequencing of the critical Nrf2 gene promoter region not only confirmed the existence of these SNPs within the participants of the trial at the expected frequency (33% carrying the -617C/A, 17% the -651G/A and 56% the -653A/G SNP) but also indicated reduced Nrf2 gene transcription associated with a normal diet if the SNPs at position -617, -651 or -653 were present. Of note, the data also indicated the study coffee increased Nrf2 gene transcription even in SNP carriers. This further highlights the relevance of genotype-dependent induction of Nrf2 gene transcription that appears to be largely influenced by dietary factors.

Multilocus sequence analysis provides insights into molecular epidemiology of Chlamydia pecorum infections in Australian sheep, cattle and koalas

Chlamydia pecorum is a significant pathogen of domestic livestock and wildlife. We have developed a C. pecorum-specific multilocus sequence analysis (MLSA) scheme to examine the genetic diversity of and relationships between Australian sheep, cattle, and koala isolates. An MLSA of seven concatenated housekeeping gene fragments was performed using 35 isolates, including 18 livestock isolates (11 Australian sheep, one Australian cow, and six U.S. livestock isolates) and 17 Australian koala isolates. Phylogenetic analyses showed that the koala isolates formed a distinct clade, with limited clustering with C. pecorum isolates from Australian sheep. We identified 11 MLSA sequence types (STs) among Australian C. pecorum isolates, 10 of them novel, with koala and sheep sharing at least one identical ST (designated ST2013Aa). ST23, previously identified in global C. pecorum livestock isolates, was observed here in a subset of Australian bovine and sheep isolates. Most notably, ST23 was found in association with multiple disease states and hosts, providing insights into the transmission of this pathogen between livestock hosts. The complexity of the epidemiology of this disease was further highlighted by the observation that at least two examples of sheep were infected with different C. pecorum STs in the eyes and gastrointestinal tract. We have demonstrated the feasibility of our MLSA scheme for understanding the host relationship that exists between Australian C. pecorum strains and provide the first molecular epidemiological data on infections in Australian livestock hosts.

Molecular data extend Australian Cricotopus midge (Chironomidae) species diversity, and provide a phylogenetic hypothesis for biogeography and freshwater monitoring

Resolving species relationships and confirming diagnostic morphological characters for insect clades that are highly plastic, and/or include morphologically cryptic species, is crucial for both academic and applied reasons. Within the true fly (Diptera) family Chironomidae, a most ubiquitous freshwater insect group, the genera CricotopusWulp, 1874 and ParatrichocladiusSantos-Abreu, 1918 have long been taxonomically confusing. Indeed, until recently the Australian fauna had been examined in just two unpublished theses: most species were known by informal manuscript names only, with no concept of relationships. Understanding species limits, and the associated ecology and evolution, is essential to address taxonomic sufficiency in biomonitoring surveys. Immature stages are collected routinely, but tolerance is generalized at the genus level, despite marked variation among species. Here, we explored this issue using a multilocus molecular phylogenetic approach, including the standard mitochondrial barcode region, and tested explicitly for phylogenetic signal in ecological tolerance of species. Additionally, we addressed biogeographical patterns by conducting Bayesian divergence time estimation. We sampled all but one of the now recognized Australian Cricotopus species and tested monophyly using representatives from other austral and Asian locations. Cricotopus is revealed as paraphyletic by the inclusion of a nested monophyletic Paratrichocladius, with in-group diversification beginning in the Eocene. Previous morphological species concepts are largely corroborated, but some additional cryptic diversity is revealed. No significant relationship was observed between the phylogenetic position of a species and its ecology, implying either that tolerance to deleterious environmental impacts is a convergent trait among many Cricotopus species or that sensitive and restricted taxa have diversified into more narrow niches from a widely tolerant ancestor.

A "Candidate-Interactome" Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms. © 2013 Mechelli et al.

Crop and environmental attributes underpinning genotype by environment interaction in synthetic-derived bread wheat evaluated in Mexico and Australia

Synthetic backcrossed-derived bread wheats (SBWs) from CIMMYT were grown in the north-west of Mexico (CIANO) and sites across Australia during 3 seasons. A different set of lines was evaluated each season, as new materials became available from the CIMMYT crop enhancement program. Previously, we have evaluated both the performance of genotypes across environments and the genotype x environment interaction (G x E). The objective of this study was to interpret the G x E for yield in terms of crop attributes measured at individual sites and to identify the potential environmental drivers of this interaction. Groups of SBWs with consistent yield performance were identified, often comprising closely related lines. However, contrasting performance was also relatively common among sister lines or between a recurrent parent and its SBWs. Early flowering was a common feature among lines with broad adaptation and/or high yield in the northern Australian wheatbelt, while yields in the southern region did not show any association with the maturity type. Lines with high yields in the southern and northern regions had cooler canopies during flowering and early grain filling. Among the SBWs with Australian genetic backgrounds, lines best adapted to CIANO were tall (>100 cm), with a slightly higher ground cover. These lines also displayed a higher concentration of water-soluble carbohydrates in the stem at flowering, which was negatively correlated with stem number per unit area when evaluated in southern Australia (Horsham). Possible reasons for these patterns are discussed. Selection for yield at CIANO did not specifically identify the lines best adapted to northern Australia, although they were not the most poorly adapted either. In addition, groups of lines with specific adaptation to the south would not have been selected by choosing the highest yielding lines at CIANO. These findings suggest that selection at CIMMYT for Australian environments may be improved by either trait based selection or yield data combined with trait information. Flowering date, canopy temperature around flowering, tiller density, and water-soluble carbohydrate concentration in the stem at flowering seem likely candidates.

Environment characterization as an aid to wheat improvement: interpreting genotype-environment interactions by modelling water-deficit patterns in North-Eastern Australia.

Genotype-environment interactions (GEI) limit genetic gain for complex traits such as tolerance to drought. Characterization of the crop environment is an important step in understanding GEI. A modelling approach is proposed here to characterize broadly (large geographic area, long-term period) and locally (field experiment) drought-related environmental stresses, which enables breeders to analyse their experimental trials with regard to the broad population of environments that they target. Water-deficit patterns experienced by wheat crops were determined for drought-prone north-eastern Australia, using the APSIM crop model to account for the interactions of crops with their environment (e.g. feedback of plant growth on water depletion). Simulations based on more than 100 years of historical climate data were conducted for representative locations, soils, and management systems, for a check cultivar, Hartog. The three main environment types identified differed in their patterns of simulated water stress around flowering and during grain-filling. Over the entire region, the terminal drought-stress pattern was most common (50% of production environments) followed by a flowering stress (24%), although the frequencies of occurrence of the three types varied greatly across regions, years, and management. This environment classification was applied to 16 trials relevant to late stages testing of a breeding programme. The incorporation of the independently-determined environment types in a statistical analysis assisted interpretation of the GEI for yield among the 18 representative genotypes by reducing the relative effect of GEI compared with genotypic variance, and helped to identify opportunities to improve breeding and germplasm-testing strategies for this region.

Statistical analysis of the associations of hereditary factors with the risk of Type 1 diabetes and Diabetic Nephropathy based on the familial data collected through ascertaiment from population-based registers

In genetic epidemiology, population-based disease registries are commonly used to collect genotype or other risk factor information concerning affected subjects and their relatives. This work presents two new approaches for the statistical inference of ascertained data: a conditional and full likelihood approaches for the disease with variable age at onset phenotype using familial data obtained from population-based registry of incident cases. The aim is to obtain statistically reliable estimates of the general population parameters. The statistical analysis of familial data with variable age at onset becomes more complicated when some of the study subjects are non-susceptible, that is to say these subjects never get the disease. A statistical model for a variable age at onset with long-term survivors is proposed for studies of familial aggregation, using latent variable approach, as well as for prospective studies of genetic association studies with candidate genes. In addition, we explore the possibility of a genetic explanation of the observed increase in the incidence of Type 1 diabetes (T1D) in Finland in recent decades and the hypothesis of non-Mendelian transmission of T1D associated genes. Both classical and Bayesian statistical inference were used in the modelling and estimation. Despite the fact that this work contains five studies with different statistical models, they all concern data obtained from nationwide registries of T1D and genetics of T1D. In the analyses of T1D data, non-Mendelian transmission of T1D susceptibility alleles was not observed. In addition, non-Mendelian transmission of T1D susceptibility genes did not make a plausible explanation for the increase in T1D incidence in Finland. Instead, the Human Leucocyte Antigen associations with T1D were confirmed in the population-based analysis, which combines T1D registry information, reference sample of healthy subjects and birth cohort information of the Finnish population. Finally, a substantial familial variation in the susceptibility of T1D nephropathy was observed. The presented studies show the benefits of sophisticated statistical modelling to explore risk factors for complex diseases.