Shifts in isoform usage underlie transcriptional differences in regulatory T cells in type 1 diabetes.

Genome-wide association studies have identified numerous loci with allelic associations to Type 1 Diabetes (T1D) risk. Most disease-associated variants are enriched in regulatory sequences active in lymphoid cell types, suggesting that lymphocyte gene expression is altered in T1D. Here we assay gene expression between T1D cases and healthy controls in two autoimmunity-relevant lymphocyte cell types, memory CD4+/CD25+ regulatory T cells (Treg) and memory CD4+/CD25- T cells, using a splicing event-based approach to characterize tissue-specific transcriptomes. Limited differences in isoform usage between T1D cases and controls are observed in memory CD4+/CD25- T-cells. In Tregs, 402 genes demonstrate differences in isoform usage between cases and controls, particularly RNA recognition and splicing factor genes. Many of these genes are regulated by the variable inclusion of exons that can trigger nonsense mediated decay. Our results suggest that dysregulation of gene expression, through shifts in alternative splicing in Tregs, contributes to T1D pathophysiology.

UBASH3A Interacts with PTPN22 to Regulate IL2 Expression and Risk for Type 1 Diabetes.

UBASH3A is a negative regulator of T cell activation and IL-2 production and plays key roles in autoimmunity. Although previous studies revealed the individual effects of UBASH3A on risk for type 1 diabetes (T1D; a common autoimmune disease), the relationship of UBASH3A with other T1D risk factors remains largely unknown. Given that another well-known T1D risk factor, PTPN22, also inhibits T cell activation and IL-2 production, we investigated the relationship between UBASH3A and PTPN22. We found that UBASH3A, via its Src homology 3 (SH3) domain, physically interacts with PTPN22 in T cells, and that this interaction is not altered by the T1D risk coding variant rs2476601 in PTPN22. Furthermore, our analysis of RNA-seq data from T1D cases showed that the amounts of UBASH3A and PTPN22 transcripts exert a cooperative effect on IL2 expression in human primary CD8+ T cells. Finally, our genetic association analyses revealed that two independent T1D risk variants, rs11203203 in UBASH3A and rs2476601 in PTPN22, interact statistically, jointly affecting risk for T1D. In summary, our study reveals novel interactions, both biochemical and statistical, between two independent T1D risk loci, and suggests how these interactions may affect T cell function and increase risk for T1D.

Sex-Biased Expression Is Associated With Chromatin State in Drosophila melanogaster and Drosophila simulans.

In Drosophila melanogaster and D. simulans head tissue, 60% of orthologous genes show evidence of sex-biased expression in at least one species. Of these, ∼39% (2,192) are conserved in direction. We hypothesize enrichment of open chromatin in the sex where we see expression bias and closed chromatin in the opposite sex. Male-biased orthologs are significantly enriched for H3K4me3 marks in males of both species (∼89% of male-biased orthologs vs. ∼76% of unbiased orthologs). Similarly, female-biased orthologs are significantly enriched for H3K4me3 marks in females of both species (∼90% of female-biased orthologs vs. ∼73% of unbiased orthologs). The sex-bias ratio in female-biased orthologs was similar in magnitude between the two species, regardless of the closed chromatin (H3K27me2me3) marks in males. However, in male-biased orthologs, the presence of H3K27me2me3 in both species significantly reduced the correlation between D. melanogaster sex-bias ratio and the D. simulans sex-bias ratio. Male-biased orthologs are enriched for evidence of positive selection in the D. melanogaster group. There are more male-biased genes than female-biased genes in both species. For orthologs with gains/losses of sex-bias between the two species, there is an excess of male-bias compared to female-bias, but there is no consistent pattern in the relationship between H3K4me3 or H3K27me2me3 chromatin marks and expression. These data suggest chromatin state is a component of the maintenance of sex-biased expression and divergence of sex-bias between species is reflected in the complexity of the chromatin status.

Sex-biased expression is associated with chromatin state in D. melanogaster and D. simulans.

We propose a new model for the association of chromatin state and sex-bias in expression. We hypothesize enrichment of open chromatin in the sex where we see expression bias (OS) and closed chromatin in the opposite sex (CO). In this study of D. melanogaster and D. simulans head tissue, sex-bias in expression is associated with H3K4me3 (open mark) in males for male-biased genes and in females for female-biased genes in both species. Sex-bias in expression is also largely conserved in direction and magnitude between the two species on the X and autosomes. In male-biased orthologs, the sex-bias ratio is more divergent between species if both species have H3K27me2me3 marks in females compared to when either or neither species has H3K27me2me3 in females. H3K27me2me3 marks in females are associated with male-bias in expression on the autosomes in both species, but on the X only in D. melanogaster . In female-biased orthologs the relationship between the species for the sex-bias ratio is similar regardless of the H3K27me2me3 marks in males. Female-biased orthologs are more similar in the ratio of sex-bias than male-biased orthologs and there is an excess of male-bias in expression in orthologs that gain/lose sex-bias. There is an excess of male-bias in sex-limited expression in both species suggesting excess male-bias is due to rapid evolution between the species. The X chromosome has an enrichment in male-limited H3K4me3 in both species and an enrichment of sex-bias in expression compared to the autosomes.

Variation in leaf transcriptome responses to elevated ozone corresponds with physiological sensitivity to ozone across maize inbred lines.

We examine the impact of sustained elevated ozone concentration on the leaf transcriptome of 5 diverse maize inbred genotypes, which vary in physiological sensitivity to ozone (B73, Mo17, Hp301, C123, and NC338), using long reads to assemble transcripts and short reads to quantify expression of these transcripts. More than 99% of the long reads, 99% of the assembled transcripts, and 97% of the short reads map to both B73 and Mo17 reference genomes. Approximately 95% of the genes with assembled transcripts belong to known B73-Mo17 syntenic loci and 94% of genes with assembled transcripts are present in all temperate lines in the nested association mapping pan-genome. While there is limited evidence for alternative splicing in response to ozone stress, there is a difference in the magnitude of differential expression among the 5 genotypes. The transcriptional response to sustained ozone stress in the ozone resistant B73 genotype (151 genes) was modest, while more than 3,300 genes were significantly differentially expressed in the more sensitive NC338 genotype. There is the potential for tandem duplication in 30% of genes with assembled transcripts, but there is no obvious association between potential tandem duplication and differential expression. Genes with a common response across the 5 genotypes (83 genes) were associated with photosynthesis, in particular photosystem I. The functional annotation of genes not differentially expressed in B73 but responsive in the other 4 genotypes (789) identifies reactive oxygen species. This suggests that B73 has a different response to long-term ozone exposure than the other 4 genotypes. The relative magnitude of the genotypic response to ozone, and the enrichment analyses are consistent regardless of whether aligning short reads to: long read assembled transcripts; the B73 reference; the Mo17 reference. We find that prolonged ozone exposure directly impacts the photosynthetic machinery of the leaf.

Genetic Control of Splicing at SIRPG Modulates Risk of Type 1 Diabetes.

Signal regulatory protein SIRPγ (CD172G) is expressed on the surface of lymphocytes, where it acts by engaging its ligand, CD47. SIRPG, which encodes SIRPγ, contains a nonsynonymous coding variant, rs6043409, which is significantly associated with risk for type 1 diabetes. SIRPG produces multiple transcript isoforms via alternative splicing, all encoding potentially functional proteins. We show that rs6043409 alters a predicted exonic splicing enhancer, resulting in significant shifts in the distribution of SIRPG transcript isoforms. All of these transcript isoforms produced protein upon transient expression in vitro. However, CRISPR/Cas9 targeting of one of the alternatively spliced exons in SIRPG eliminated all SIRPγ expression in Jurkat T cells. These targeted cells formed fewer cell-cell conjugates with each other than with wild-type Jurkat cells, expressed reduced levels of genes associated with CD47 signaling, and had significantly increased levels of cell-surface CD47. In primary CD4+ and CD8+ T cells, cell-surface SIRPγ levels in response to anti-CD3 stimulation varied quantitatively by rs6043409 genotype. Our results suggest that SIRPG is the most likely causative gene for type 1 diabetes risk in the 20p13 region and highlight the role of alternative splicing in lymphocytes in mediating the genetic risk for autoimmunity.

Testcrosses are an efficient strategy for identifying cis-regulatory variation: Bayesian analysis of allele-specific expression (BayesASE).

Allelic imbalance (AI) occurs when alleles in a diploid individual are differentially expressed and indicates cis acting regulatory variation. What is the distribution of allelic effects in a natural population? Are all alleles the same? Are all alleles distinct? The approach described applies to any technology generating allele-specific sequence counts, for example for chromatin accessibility and can be applied generally including to comparisons between tissues or environments for the same genotype. Tests of allelic effect are generally performed by crossing individuals and comparing expression between alleles directly in the F1. However, a crossing scheme that compares alleles pairwise is a prohibitive cost for more than a handful of alleles as the number of crosses is at least (n2-n)/2 where n is the number of alleles. We show here that a testcross design followed by a hypothesis test of AI between testcrosses can be used to infer differences between nontester alleles, allowing n alleles to be compared with n crosses. Using a mouse data set where both testcrosses and direct comparisons have been performed, we show that the predicted differences between nontester alleles are validated at levels of over 90% when a parent-of-origin effect is present and of 60%-80% overall. Power considerations for a testcross, are similar to those in a reciprocal cross. In all applications, the testing for AI involves several complex bioinformatics steps. BayesASE is a complete bioinformatics pipeline that incorporates state-of-the-art error reduction techniques and a flexible Bayesian approach to estimating AI and formally comparing levels of AI between conditions. The modular structure of BayesASE has been packaged in Galaxy, made available in Nextflow and as a collection of scripts for the SLURM workload manager on github (https://github.com/McIntyre-Lab/BayesASE).

tappAS: a comprehensive computational framework for the analysis of the functional impact of differential splicing.

Recent advances in long-read sequencing solve inaccuracies in alternative transcript identification of full-length transcripts in short-read RNA-Seq data, which encourages the development of methods for isoform-centered functional analysis. Here, we present tappAS, the first framework to enable a comprehensive Functional Iso-Transcriptomics (FIT) analysis, which is effective at revealing the functional impact of context-specific post-transcriptional regulation. tappAS uses isoform-resolved annotation of coding and non-coding functional domains, motifs, and sites, in combination with novel analysis methods to interrogate different aspects of the functional readout of transcript variants and isoform regulation. tappAS software and documentation are available at https://app.tappas.org.

Event Analysis: Using Transcript Events To Improve Estimates of Abundance in RNA-seq Data.

Alternative splicing leverages genomic content by allowing the synthesis of multiple transcripts and, by implication, protein isoforms, from a single gene. However, estimating the abundance of transcripts produced in a given tissue from short sequencing reads is difficult and can result in both the construction of transcripts that do not exist, and the failure to identify true transcripts. An alternative approach is to catalog the events that make up isoforms (splice junctions and exons). We present here the Event Analysis (EA) approach, where we project transcripts onto the genome and identify overlapping/unique regions and junctions. In addition, all possible logical junctions are assembled into a catalog. Transcripts are filtered before quantitation based on simple measures: the proportion of the events detected, and the coverage. We find that mapping to a junction catalog is more efficient at detecting novel junctions than mapping in a splice aware manner. We identify 99.8% of true transcripts while iReckon identifies 82% of the true transcripts and creates more transcripts not included in the simulation than were initially used in the simulation. Using PacBio Iso-seq data from a mouse neural progenitor cell model, EA detects 60% of the novel junctions that are combinations of existing exons while only 43% are detected by STAR. EA further detects ∼5,000 annotated junctions missed by STAR. Filtering transcripts based on the proportion of the transcript detected and the number of reads on average supporting that transcript captures 95% of the PacBio transcriptome. Filtering the reference transcriptome before quantitation, results in is a more stable estimate of isoform abundance, with improved correlation between replicates. This was particularly evident when EA is applied to an RNA-seq study of type 1 diabetes (T1D), where the coefficient of variation among subjects (n = 81) in the transcript abundance estimates was substantially reduced compared to the estimation using the full reference. EA focuses on individual transcriptional events. These events can be quantitate and analyzed directly or used to identify the probable set of expressed transcripts. Simple rules based on detected events and coverage used in filtering result in a dramatic improvement in isoform estimation without the use of ancillary data (e.g., ChIP, long reads) that may not be available for many studies.

Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling.

Schizophrenia (SCZ) is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells). Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70) by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM) was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology of SCZ.

Variable selection in omics data: A practical evaluation of small sample sizes.

In omics experiments, variable selection involves a large number of metabolites/ genes and a small number of samples (the n < p problem). The ultimate goal is often the identification of one, or a few features that are different among conditions- a biomarker. Complicating biomarker identification, the p variables often contain a correlation structure due to the biology of the experiment making identifying causal compounds from correlated compounds difficult. Additionally, there may be elements in the experimental design (blocks, batches) that introduce structure in the data. While this problem has been discussed in the literature and various strategies proposed, the over fitting problems concomitant with such approaches are rarely acknowledged. Instead of viewing a single omics experiment as a definitive test for a biomarker, an unrealistic analytical goal, we propose to view such studies as screening studies where the goal of the study is to reduce the number of features present in the second round of testing, and to limit the Type II error. Using this perspective, the performance of LASSO, ridge regression and Elastic Net was compared with the performance of an ANOVA via a simulation study and two real data comparisons. Interestingly, a dramatic increase in the number of features had no effect on Type I error for the ANOVA approach. ANOVA, even without multiple test correction, has a low false positive rates in the scenarios tested. The Elastic Net has an inflated Type I error (from 10 to 50%) for small numbers of features which increases with sample size. The Type II error rate for the ANOVA is comparable or lower than that for the Elastic Net leading us to conclude that an ANOVA is an effective analytical tool for the initial screening of features in omics experiments.

Disease-specific biases in alternative splicing and tissue-specific dysregulation revealed by multitissue profiling of lymphocyte gene expression in type 1 diabetes.

Genome-wide association studies (GWAS) have identified multiple, shared allelic associations with many autoimmune diseases. However, the pathogenic contributions of variants residing in risk loci remain unresolved. The location of the majority of shared disease-associated variants in noncoding regions suggests they contribute to risk of autoimmunity through effects on gene expression in the immune system. In the current study, we test this hypothesis by applying RNA sequencing to CD4+, CD8+, and CD19+ lymphocyte populations isolated from 81 subjects with type 1 diabetes (T1D). We characterize and compare the expression patterns across these cell types for three gene sets: all genes, the set of genes implicated in autoimmune disease risk by GWAS, and the subset of these genes specifically implicated in T1D. We performed RNA sequencing and aligned the reads to both the human reference genome and a catalog of all possible splicing events developed from the genome, thereby providing a comprehensive evaluation of the roles of gene expression and alternative splicing (AS) in autoimmunity. Autoimmune candidate genes displayed greater expression specificity in the three lymphocyte populations relative to other genes, with significantly increased levels of splicing events, particularly those predicted to have substantial effects on protein isoform structure and function (e.g., intron retention, exon skipping). The majority of single-nucleotide polymorphisms within T1D-associated loci were also associated with one or more cis-expression quantitative trait loci (cis-eQTLs) and/or splicing eQTLs. Our findings highlight a substantial, and previously underrecognized, role for AS in the pathogenesis of autoimmune disorders and particularly for T1D.

UBASH3A Mediates Risk for Type 1 Diabetes Through Inhibition of T-Cell Receptor-Induced NF-κB Signaling.

Although over 40 type 1 diabetes (T1D) risk loci have been mapped in humans, the causative genes and variants for T1D are largely unknown. Here, we investigated a candidate gene in the 21q22.3 risk locus-UBASH3A, which is primarily expressed in T cells where it is thought to play a largely redundant role. Genetic variants in UBASH3A have been shown to be associated with several autoimmune diseases in addition to T1D. However, the molecular mechanism underlying these genetic associations is unresolved. Our study reveals a previously unrecognized role of UBASH3A in human T cells: UBASH3A attenuates the NF-κB signal transduction upon T-cell receptor (TCR) stimulation by specifically suppressing the activation of the IκB kinase complex. We identify novel interactions of UBASH3A with nondegradative polyubiquitin chains, TAK1 and NEMO, suggesting that UBASH3A regulates the NF-κB signaling pathway by an ubiquitin-dependent mechanism. Finally, we show that risk alleles at rs11203203 and rs80054410, two T1D-associated variants in UBASH3A, increase UBASH3A expression in human primary CD4+ T cells upon TCR stimulation, inhibiting NF-κB signaling via its effects on the IκB kinase complex and resulting in reduced IL2 gene expression.

RNA-seq analysis of impact of PNN on gene expression and alternative splicing in corneal epithelial cells.

PURPOSE: The specialized corneal epithelium requires differentiated properties, specific for its role at the anterior surface of the eye. Thus, tight maintenance of the differentiated qualities of the corneal epithelial is essential. Pinin (PNN) is an exon junction component (EJC) that has dramatic implications for corneal epithelial cell differentiation and may act as a stabilizer of the corneal epithelial cell phenotype. Our studies revealed that PNN is involved in transcriptional repression complexes and spliceosomal complexes, placing PNN at the fulcrum between chromatin and mRNA splicing. Transcriptome analysis of PNN-knockdown cells revealed clear and reproducible alterations in transcript profiles and splicing patterns of a subset of genes that would significantly impact the epithelial cell phenotype. We further investigated PNN's role in the regulation of gene expression and alternative splicing (AS) in a corneal epithelial context. METHODS: Human corneal epithelial (HCET) cells that carry the doxycycline-inducible PNN-knockdown shRNA vector were used to perform RNA-seq to determine differential gene expression and differential AS events. RESULTS: Multiple genes and AS events were identified as differentially expressed between PNN-knockdown and control cells. Genes upregulated by PNN knockdown included a large proportion of genes that are associated with enhanced cell migration and ECM remodeling processes, such as MMPs, ADAMs, HAS2, LAMA3, CXCRs, and UNC5C. Genes downregulated in response to PNN depletion included IGFBP5, FGD3, FGFR2, PAX6, RARG, and SOX10. AS events in PNN-knockdown cells compared to control cells were also more likely to be detected, and upregulated. In particular, 60% of exon-skipping events, detected in only one condition, were detected in PNN-knockdown cells and of the shared exon-skipping events, 92% of those differentially expressed were more frequent in the PNN knockdown. CONCLUSIONS: These data suggest that lowering of PNN levels in epithelial cells results in dramatic transformation in the number and composition of splicing variants and that PNN plays a crucial role in the selection of which RNA isoforms differentiating cells produce. Many of the genes affected by PNN knockdown are known to affect the epithelial phenotype. This window into the complexity of RNA splicing in the corneal epithelium implies that PNN exerts broad influence over the regulation and maintenance of the epithelial cell phenotype.

Comprehensive assessment of genetic sequence variants in the antioxidant 'master regulator' NRF2 in idiopathic Parkinson's disease.

Parkinson's disease (PD) is a complex neurodegenerative disorder influenced by a combination of genetic and environmental factors. The molecular mechanisms that underlie PD are unknown; however, oxidative stress and impairment of antioxidant defence mechanisms have been implicated as major contributors to disease pathogenesis. Previously, we have reported a PD patient-derived cellular model generated from biopsies of the olfactory mucosa, termed hONS cells, in which the NRF2-mediated antioxidant response pathway genes were among the most differentially-expressed. To date, few studies have examined the role of the NRF2 encoding gene, NFE2L2, and PD. In this study, we comprehensibly assessed whether rare and common NFE2L2 genetic variations modify susceptibility to PD using a large Australian case-control sample (PD=1338, controls=1379). We employed a haplotype-tagging approach that identified an association with the tagging SNP rs2364725 and PD (OR = 0.849 (0.760-0.948), P = 0.004). Further genetic screening in hONS cell lines produced no obvious pathogenic variants in the coding regions of NFE2L2. Finally, we investigated the relationship between xenobiotic exposures and NRF2 function, through gene-environment interactions, between NFE2L2 SNPs and smoking or pesticide exposure. Our results demonstrated a significant interaction between rs2706110 and pesticide exposure (OR = 0.597 (0.393-0.900), P = 0.014). In addition, we were able to identify some age-at-onset modifying SNPs and replicate an 'early-onset' haplotype that contains a previously identified 'functional promoter' SNP (rs6721961). Our results suggest a role of NFE2L2 genetic variants in modifying PD susceptibility and onset. Our findings also support the utility of testing gene-environment interactions in genetic studies of PD.

Risk factors for idiopathic dystonia in Queensland, Australia.

It is currently hypothesised that a combination of genetic and environmental factors underlies the development of idiopathic isolated dystonia (IID). In this study, we examined several possible environmental or other non-genetic factors that may influence the risk for IID in Queensland, Australia. We surveyed several environmental exposures, lifestyle factors, medical and family histories to investigate potential risk factors for IID. Associations between putative risk factors and IID were assessed using a total of 184 dystonia patients and 1048 neurologically-normal control subjects sampled from Queensland between 2005 and 2012. Our analyses revealed that anxiety disorders, depression, tremor, cigarette smoking and head injuries with a loss of consciousness were associated with increased risk for IID (p<0.05), all of which remained statistically significant following an adjustment for multiple hypothesis testing except for depression. We also observed that the risk for dystonia increased with higher cigarette smoking pack-year quartiles in our analyses. Our results suggest possible environmental factors that influence the development of IID and complement the findings of similar dystonia risk factor studies. Further investigation defining the environmental and other non-genetic risk factors for IID may provide insight into the development of the disorder in genetically-susceptible individuals.

Common polymorphisms in dystonia-linked genes and susceptibility to the sporadic primary dystonias.

Genes involved in familial dystonia syndromes (DYT genes) are ideal candidates for investigating whether common genetic variants influence the susceptibility to sporadic primary dystonia. To date, there have been few candidate gene studies for primary dystonia and only two DYT genes, TOR1A and THAP1, have been assessed. We therefore employed a haplotype-tagging strategy to comprehensively assess if common polymorphisms in eight DYT genes (TOR1A, TAF1, GCH1, THAP1, MR-1 (PNKD), SGCE, ATP1A3 and PRKRA) confer risk for sporadic primary dystonia. The 230 primary dystonia cases were matched for age and gender to 228 controls, recruited from movement disorder clinics in Brisbane, Australia and the Australian electoral roll. All subjects were genotyped for 56 tagging SNPs and genotype associations were investigated. Modest genotypic associations (P<0.05) were observed for three GCH1 SNPs (rs12147422, rs3759664 and rs10483639) when comparing all cases against controls. Associations were also seen when the cases were stratified based on presentation. Overall, our findings do not support the hypothesis that common TOR1A variants affect susceptibility for sporadic primary dystonia, and that it is unlikely that common variants around the DYT genes confer substantial risk for sporadic primary dystonia. Further work is warranted to follow up the GCH1 SNPs and the subgroup analyses.

Haplotype analysis of the PARK 11 gene, GIGYF2, in sporadic Parkinson's disease.

Familial Parkinsonism (PARK) genes are strong candidates for conferring susceptibility to common forms of PD. However, most studies to date have provided little evidence that their common variants substantially influence disease risk. Recently, mutations were described in the gene, GIGYF2 (TNRC15), located at the PARK11 locus (2q37.1). Here, we use a haplotype tagging approach to examine common variation in the GIGYF2 gene and PD risk. PD cases (n = 568) and age and gender-matched control subjects (n = 568) were recruited from three specialist movement disorder clinics in Brisbane (Australia) and the Australian electoral roll. Twelve tagging SNPs were assessed in all subjects and haplotype and genotype associations were explored. Overall our findings suggest that common genetic variants of GIGYF2 do not significantly affect sporadic PD risk in Australian Caucasians.