Parkinson's disease (PD) is a neurodegenerative disorder characterized by degeneration of dopaminergic neurons in the substantia nigra. We previously mapped a locus for a rare familial form of PD to chromosome 1p36 (PARK6). Here we show that mutations in PINK1 (PTEN-induced kinase 1) are associated with PARK6. We have identified two homozygous mutations affecting the PINK1 kinase domain in three consanguineous PARK6 families: a truncating nonsense mutation and a missense mutation at a highly conserved amino acid. Cell culture studies suggest that PINK1 is mitochondrially located and may exert a protective effect on the cell that is abrogated by the mutations, resulting in increased susceptibility to cellular stress. These data provide a direct molecular link between mitochondria and the pathogenesis of PD.

As part of a study into the molecular genetics of sexually dimorphic complex traits, we used high-throughput sequencing to obtain data on genomic variation in an outbred laboratory-adapted fruit fly (Drosophila melanogaster) population. We successfully resequenced the whole genome of 220 hemiclonal females that were heterozygous for the same Berkeley reference line genome (BDGP6/dm6), and a unique haplotype from the outbred base population (LHM). The use of a static and known genetic background enabled us to obtain sequences from whole-genome phased haplotypes. We used a BWA-Picard-GATK pipeline for mapping sequence reads to the dm6 reference genome assembly, at a median depth-of coverage of 31X, and have made the resulting data publicly-available in the NCBI Short Read Archive (Accession number SRP058502). We used Haplotype Caller to discover and genotype 1,726,931 small genomic variants (SNPs and indels, <200bp). Additionally we detected and genotyped 167 large structural variants (1-100Kb in size) using GenomeStrip/2.0. Sequence and genotype data are publicly-available at the corresponding NCBI databases: Short Read Archive, dbSNP and dbVar (BioProject PRJNA282591). We have also released the unfiltered genotype data, and the code and logs for data processing and summary statistics.

There is long‐standing evidence for the gene‐by‐sex interactions in disease risk, which can now be tested in genome‐wide association studies with participant numbers in the hundreds of thousands. The current methods start with a separate test for each sex, but a more powerful approach is to use sex as an interaction term in a combined sample. The most compelling evidence is for adiposity (predictive of cardiac disease) as well as type II diabetes, asthma and inflammatory bowel disease. Autism exhibits a different kind of sex difference, with hypermasculinisation of the brain, and the intriguing enrichment of structural variants in females. Sexually dimorphic gene expression varies exquisitely and unexpectedly, by tissue, age and chromosome, so sex‐dependent genetic effects are expected for a wide range of diseases. Because natural selection against sex‐dependent risk alleles is in one sex only, their effect size is expected to be greater than conventional risk loci.

Understanding the genetic architecture of disease is an enormous challenge, and should be guided by evolutionary principles. Recent studies in evolutionary genetics show that sexual selection can have a profound influence on the genetic architecture of complex traits. Here, we summarise data from heritability studies and genomewide association studies (GWASs) showing that common genetic variation influences many diseases and medically relevanttraits in a sex-dependent manner. In addition, we discuss how the discovery of sex-dependent effects in population samples is improved by joint interaction analysis (rather than separate-sex), as well as by recently developed software. Finally, we argue that although genetic variation that has sex-dependent effects on disease risk could be maintained by mutation–selection balance and genetic drift, recent evidence indicates that intralocus sexual conflict could be a powerful influence on complex trait architecture, and maintain sex-dependent disease risk alleles in a population because they are beneficial to the opposite sex.

Understanding the genetic architecture of disease is an enormous challenge, and should be guided by evolutionary principles. Recent studies in evolutionary genetics show that sexual selection can have a profound influence on the genetic architecture of complex traits. Here, we summarise data from heritability studies and genome-wide association studies (GWASs) showing that common genetic variation influences many diseases and medically relevant traits in a sex-dependent manner. In addition, we discuss how the discovery of sex-dependent effects in population samples is improved by joint interaction analysis (rather than separate-sex), as well as by recently developed software. Finally, we argue that although genetic variation that has sex-dependent effects on disease risk could be maintained by mutation-selection balance and genetic drift, recent evidence indicates that intra-locus sexual conflict could be a powerful influence on complex trait architecture, and maintain sex-dependent disease risk alleles in a population because they are beneficial to the opposite sex.

Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene have been shown to cause autosomal dominant Parkinson's disease. Few mutations in this gene have been identified. We investigated the frequency of a common heterozygous mutation, 2877510 g-->A, which produces a glycine to serine aminoacid substitution at codon 2019 (Gly2019 ser), in idiopathic Parkinson's disease. We assessed 482 patients with the disorder, of whom 263 had pathologically confirmed disease, by direct sequencing for mutations in exon 41 of LRRK2. The mutation was present in eight (1.6%) patients. We have shown that a common single Mendelian mutation is implicated in sporadic Parkinson's disease. We suggest that testing for this mutation will be important in the management and genetic counselling of patients with Parkinson's disease.

Screening large numbers of target regions in multiple DNA samples for sequence variation is an important application of next-generation sequencing but an efficient method to enrich the samples in parallel has yet to be reported. We describe an advanced method that combines DNA samples using indexes or barcodes prior to target enrichment to facilitate this type of experiment. Sequencing libraries for multiple individual DNA samples, each incorporating a unique 6-bp index, are combined in equal quantities, enriched using a single in-solution target enrichment assay and sequenced in a single reaction. Sequence reads are parsed based on the index, allowing sequence analysis of individual samples. We show that the use of indexed samples does not impact on the efficiency of the enrichment reaction. For three- and nine-indexed HapMap DNA samples, the method was found to be highly accurate for SNP identification. Even with sequence coverage as low as 8x, 99% of sequence SNP calls were concordant with known genotypes. Within a single experiment, this method can sequence the exonic regions of hundreds of genes in tens of samples for sequence and structural variation using as little as 1 μg of input DNA per sample.

Objectives: SNP rs2473277 upstream of the cell division cycle 42 (CDC42) gene was associated with schizophrenia in a recent genome-wide association study (GWAS). Reduced expression of CDC42 in schizophrenia has previously been reported. Our objective was to test whether the associated SNP affected CDC42 expression.

Methods: Two available SNP × gene expression datasets were accessed to test the effect of rs2473277 on CDC42 expression: (i) the mRNA by SNP Browser, which presents results of a genome-wide linkage study of gene expression, and (ii) the Genevar HapMap expression dataset. rs2473277 is in strong linkage disequilibrium (LD) with the SNP rs2473307 (r(2) = 0.96), which is predicted to affect transcription factor binding. rs2473307 was directly tested for allelic effects on gene expression using a gene reporter assay in a human neuronal cell line.

Results: In both datasets, the schizophrenia risk allele at rs2473277 was associated with a reduction in CDC42 mRNA levels. In the reporter gene assay the risk allele at rs2473307 similarly reduced gene expression.

Conclusions: We found evidence that rs2473307, in strong LD with the schizophrenia associated SNP rs2473277, is a functional variant at CDC42 that may increase risk for schizophrenia by reducing expression of CDC42.

Schizophrenia is a heritable mental disorder with a complex genetic aetiology potentially implicating glutamatergic dysfunction. Following a search for functionally relevant genes with evidence of linkage to schizophrenia, we selected HOMER2 for as a candidate gene for investigation using a multi-stage association design. Twenty-six tagging SNPs were genotyped in 401 cases and 812 controls and associated SNPs were analysed in an independent sample of 408 cases and 804 controls, all from Ireland. Secondary replication analysis was undertaken using the International Schizophrenia Consortium (ISC) European sample of 1287 cases and 1128 controls. Significant associations were found at five SNPs in the first Irish sample (p < 0.05), but were not replicated in the second Irish sample. SNP rs2306428 was significantly associated when the two samples were combined (p = 0.008, OR = 0.73) and also by proxy in the ISC sample (rs17158184, r2 = 1.0, p = 0.019, OR = 0.75). The protective allele at rs2306428 removes a predicted splice-enhancer binding site where Homer2 is naturally truncated. We did not detect an allelic effect of rs2306428 on neuropsychological function nor on HOMER2 splicing. This study supports a role for HOMER2 gene in schizophrenia susceptibility. Further work is required to confirm and elucidate the role of HOMER2 and interacting genes in schizophrenia aetiology.