Exome sequencing in amyotrophic lateral sclerosis implicates a novel gene, DNAJC7, encoding a heat-shock protein

To discover novel genes underlying amyotrophic lateral sclerosis (ALS), we aggregated exomes from 3,864 cases and 7,839 ancestry-matched controls. We observed a significant excess of rare protein-truncating variants among ALS cases, and these variants were concentrated in constrained genes. Through gene level analyses, we replicated known ALS genes including SOD1, NEK1 and FUS. We also observed multiple distinct protein-truncating variants in a highly constrained gene, DNAJC7. The signal in DNAJC7 exceeded genome-wide significance, and immunoblotting assays showed depletion of DNAJC7 protein in fibroblasts in a patient with ALS carrying the p.Arg156Ter variant. DNAJC7 encodes a member of the heat-shock protein family, HSP40, which, along with HSP70 proteins, facilitates protein homeostasis, including folding of newly synthesized polypeptides and clearance of degraded proteins. When these processes are not regulated, misfolding and accumulation of aberrant proteins can occur and lead to protein aggregation, which is a pathological hallmark of neurodegeneration. Our results highlight DNAJC7 as a novel gene for ALS

Expanding the genetic architecture of nicotine dependence and its shared genetics with multiple traits

Cigarette smoking is the leading cause of preventable morbidity and mortality. Genetic variation contributes to initiation, regular smoking, nicotine dependence, and cessation. We present a Fagerström Test for Nicotine Dependence (FTND)-based genome-wide association study in 58,000 European or African ancestry smokers. We observe five genome-wide significant loci, including previously unreported loci MAGI2/GNAI1 (rs2714700) and TENM2 (rs1862416), and extend loci reported for other smoking traits to nicotine dependence. Using the heaviness of smoking index from UK Biobank (N = 33,791), rs2714700 is consistently associated; rs1862416 is not associated, likely reflecting nicotine dependence features not captured by the heaviness of smoking index. Both variants influence nearby gene expression (rs2714700/MAGI2-AS3 in hippocampus; rs1862416/TENM2 in lung), and expression of genes spanning nicotine dependence-associated variants is enriched in cerebellum. Nicotine dependence (SNP-based heritability = 8.6%) is genetically correlated with 18 other smoking traits (r(g) = 0.40-1.09) and co-morbidities. Our results highlight nicotine dependence-specific loci, emphasizing the FTND as a composite phenotype that expands genetic knowledge of smoking

Age at first birth in women is genetically associated with increased risk of schizophrenia

Prof. Paunio on PGC:n jäsenPrevious studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.Peer reviewe

Comparative genetic architectures of schizophrenia in East Asian and European populations

Schizophrenia is a debilitating psychiatric disorder with approximately 1% lifetime risk globally. Large-scale schizophrenia genetic studies have reported primarily on European ancestry samples, potentially missing important biological insights. Here, we report the largest study to date of East Asian participants (22,778 schizophrenia cases and 35,362 controls), identifying 21 genome-wide-significant associations in 19 genetic loci. Common genetic variants that confer risk for schizophrenia have highly similar effects between East Asian and European ancestries (genetic correlation = 0.98 ± 0.03), indicating that the genetic basis of schizophrenia and its biology are broadly shared across populations. A fixed-effect meta-analysis including individuals from East Asian and European ancestries identified 208 significant associations in 176 genetic loci (53 novel). Trans-ancestry fine-mapping reduced the sets of candidate causal variants in 44 loci. Polygenic risk scores had reduced performance when transferred across ancestries, highlighting the importance of including sufficient samples of major ancestral groups to ensure their generalizability across populations

Mapping and characterization of structural variation in 17,795 human genomes

A key goal of whole-genome sequencing for studies of human genetics is to interrogate all forms of variation, including single-nucleotide variants, small insertion or deletion (indel) variants and structural variants. However, tools and resources for the study of structural variants have lagged behind those for smaller variants. Here we used a scalable pipeline1 to map and characterize structural variants in 17,795 deeply sequenced human genomes. We publicly release site-frequency data to create the largest, to our knowledge, whole-genome-sequencing-based structural variant resource so far. On average, individuals carry 2.9 rare structural variants that alter coding regions; these variants affect the dosage or structure of 4.2 genes and account for 4.0–11.2% of rare high-impact coding alleles. Using a computational model, we estimate that structural variants account for 17.2% of rare alleles genome-wide, with predicted deleterious effects that are equivalent to loss-of-function coding alleles; approximately 90% of such structural variants are noncoding deletions (mean 19.1 per genome). We report 158,991 ultra-rare structural variants and show that 2% of individuals carry ultra-rare megabase-scale structural variants, nearly half of which are balanced or complex rearrangements. Finally, we infer the dosage sensitivity of genes and noncoding elements, and reveal trends that relate to element class and conservation. This work will help to guide the analysis and interpretation of structural variants in the era of whole-genome sequencing

Landscape genomics of North American conifers

The long‐term interest of my lab is to understand the molecular basis of plant adaptation to the environment in forest tree populations. A rich history of common garden experimentation has show genetic control of adaptive traits and precise patterning of adaptation across heterogeneous environments. Adaptive traits are assumed to be highly polygenetic but the exact underlying genes were unknown. We have used QTL mapping and association studies in loblolly pine (Pinus taeda L.) and Douglas‐fir (Pseudotsuga menziesii (Mirb.) Franco) to begin to dissect these complex traits to their individual genes. This approach has led to many candidate genes for adaptive traits such as cold‐hardiness and water‐use efficiency. Next we have conducted candidate gene resequencing (Sanger) to discover SNPs. These studies have been done in a large number of North American and European conifers. Gene and SNP annotations are performed and measures of nucleotide diversity and departures from neutrality are estimated. Finally, large populations of geo‐referenced trees are genotyped for SNPs and patterns of demographic and adaptive diversity are estimated

Effects of climate on fine-scale spatial genetic structure in four alpine keystone species

Genetic responses to environmental changes can take place at different spatial scales. While the effect of climate on the wide-range distribution of genetic diversity has been the focus of several recent studies, studies of genetic responses to climate at local scales are relatively scarce. Fine-scale spatial genetic structure (SGS) was investigated in four Alpine conifers (4 to 8 natural populations per species) in the Eastern Italian Alps. SNP assays were used to characterize SGS in Abies alba and Picea abies (384 SNPs), Larix decidua (528 SNPs) and Pinus cembra (768 SNPs). Significant SGS was found for 11 out of 25 populations tested, varying from Sp of 0.0018 in P. cembra to 0.0035 in Larix decidua. Several linear models were constructed to associate SGS with climate variables. Once corrected by confounding effects (e.g. differences of SGS across species due, for instance, to dispersal capability), the best model identified April minimum temperature and spring precipitation as the most relevant climatic variables associated with differences in SGS across populations. To study the potential effect of winter temperature in relation to plant physiology, two ecological indexes related to vegetation growth (chilling-degree-day, CDD, and freezing-degree-day, FDD) were also tested for association to SGS. A significant association was found between SGS and CDD across species. This study provides new insights on the expected genetic responses of four coniferous species to climate change at local scales, suggesting that climate change, through altering SGS, could also have relevant impacts in plant microevolutio

Alpine forest genomics network (AForGeN): a report of the first annual meeting

The Alpine Forest Genomics Network was formed in 2011 and held its first annual meeting on June 24-26, 2012, in the Natural Park Adamello Brenta in Trentino Region, Italy. The meeting was attended by 30 researchers from the alpine region of Europe and had two primary goals: (1) for researchers to introduce each other to current and planned research activities in forest landscape genomics and (2) to develop a strategic vision for the network. A steering committee was elected and will develop a white paper over the next year. The next annual meeting will be held in Austria in June 201