Major-Effect Alleles at Relatively Few Loci Underlie Distinct Vernalization and Flowering Variation in Arabidopsis Accessions

We have explored the genetic basis of variation in vernalization requirement and response in Arabidopsis accessions, selected on the basis of their phenotypic distinctiveness. Phenotyping of F2 populations in different environments, plus fine mapping, indicated possible causative genes. Our data support the identification of FRI and FLC as candidates for the major-effect QTL underlying variation in vernalization response, and identify a weak FLC allele, caused by a Mutator-like transposon, contributing to flowering time variation in two N. American accessions. They also reveal a number of additional QTL that contribute to flowering time variation after saturating vernalization. One of these was the result of expression variation at the FT locus. Overall, our data suggest that distinct phenotypic variation in the vernalization and flowering response of Arabidopsis accessions is accounted for by variation that has arisen independently at relatively few major-effect loci

Discovery and functional prioritization of Parkinson's disease candidate genes from large-scale whole exome sequencing.

BACKGROUND: Whole-exome sequencing (WES) has been successful in identifying genes that cause familial Parkinson's disease (PD). However, until now this approach has not been deployed to study large cohorts of unrelated participants. To discover rare PD susceptibility variants, we performed WES in 1148 unrelated cases and 503 control participants. Candidate genes were subsequently validated for functions relevant to PD based on parallel RNA-interference (RNAi) screens in human cell culture and Drosophila and C. elegans models. RESULTS: Assuming autosomal recessive inheritance, we identify 27 genes that have homozygous or compound heterozygous loss-of-function variants in PD cases. Definitive replication and confirmation of these findings were hindered by potential heterogeneity and by the rarity of the implicated alleles. We therefore looked for potential genetic interactions with established PD mechanisms. Following RNAi-mediated knockdown, 15 of the genes modulated mitochondrial dynamics in human neuronal cultures and four candidates enhanced α-synuclein-induced neurodegeneration in Drosophila. Based on complementary analyses in independent human datasets, five functionally validated genes-GPATCH2L, UHRF1BP1L, PTPRH, ARSB, and VPS13C-also showed evidence consistent with genetic replication. CONCLUSIONS: By integrating human genetic and functional evidence, we identify several PD susceptibility gene candidates for further investigation. Our approach highlights a powerful experimental strategy with broad applicability for future studies of disorders with complex genetic etiologies

Binding of [H-3] Sch23390 to a Nondopaminergic Site in Bovine Kidney

Binding of the D1 dopamine receptor antagonist [H-3]SCH23390 to bovine renal cortical membranes has been studied. Specific binding of [H-3]SCH23390 was saturable and reversible and stereoisomers of SCH23390 competed stereoselectively. In contrast, competition with the isomers of butaclamol was not stereoselective and dopamine failed to compete for the [H-3]SCH23390 binding site. The site is therefore not a D1 dopamine receptor. Competition studies with a very wide range of compounds failed to define the nature of the [H-3]SCH23390 binding sites in renal cortex whereas in parallel studies the characteristics of [H-3]SCH23390 binding in caudate nucleus were entirely consistent with those of D1 dopamine receptors. The nature of [H-3]SCH23390 binding in preparations of tubular and glomerular membranes was found to be virtually identical to those of crude renal cortical membranes indicating lack of compartmentation of these sites. Autoradiographic studies of [H-3]SCH23390 binding in bovine kidney showed significantly higher levels of binding sites in renal cortex compared with renal medulla and this was confirmed by direct ligand binding studies

Pulmonary vasodilator therapy is associated with greater survival in Eisenmenger syndrome

Objective Eisenmenger syndrome (ES) is a severe form of pulmonary hypertension in adults with congenital heart disease (CHD) and has a poor prognosis. We aimed to understand factors associated with survival in ES and particularly to assess the potential benefits of advanced pulmonary vasodilator therapy (AT)

Multiple emergences of genetically diverse amphibian-infecting chytrids include a globalized hypervirulent recombinant lineage

Batrachochytrium dendrobatidis (Bd) is a globally ubiquitous fungal infection that has emerged to become a primary driver of amphibian biodiversity loss. Despite widespread effort to understand the emergence of this panzootic, the origins of the infection, its patterns of global spread, and principle mode of evolution remain largely unknown. Using comparative population genomics, we discovered three deeply diverged lineages of Bd associated with amphibians. Two of these lineages were found in multiple continents and are associated with known introductions by the amphibian trade. We found that isolates belonging to one clade, the global panzootic lineage (BdGPL) have emerged across at least five continents during the 20th century and are associated with the onset of epizootics in North America, Central America, the Caribbean, Australia, and Europe. The two newly identified divergent lineages, Cape lineage (BdCAPE) and Swiss lineage (BdCH), were found to differ in morphological traits when compared against one another and BdGPL, and we show that BdGPL is hypervirulent. BdGPL uniquely bears the hallmarks of genomic recombination, manifested as extensive intergenomic phylogenetic conflict and patchily distributed heterozygosity. We postulate that contact between previously genetically isolated allopatric populations of Bd may have allowed recombination to occur, resulting in the generation, spread, and invasion of the hypervirulent BdGPL leading to contemporary disease-driven losses in amphibian biodiversity

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers

A Two-Stage Meta-Analysis Identifies Several New Loci for Parkinson's Disease

A previous genome-wide association (GWA) meta-analysis of 12,386 PD cases and 21,026 controls conducted by the International Parkinson's Disease Genomics Consortium (IPDGC) discovered or confirmed 11 Parkinson's disease (PD) loci. This first analysis of the two-stage IPDGC study focused on the set of loci that passed genome-wide significance in the first stage GWA scan. However, the second stage genotyping array, the ImmunoChip, included a larger set of 1,920 SNPs selected on the basis of the GWA analysis. Here, we analyzed this set of 1,920 SNPs, and we identified five additional PD risk loci (combined p <5x10(-10), PARK16/1q32, STX1B/16p11, FGF20/8p22, STBD1/4q21, and GPNMB/7p15). Two of these five loci have been suggested by previous association studies (PARK16/1q32, FGF20/8p22), and this study provides further support for these findings. Using a dataset of post-mortem brain samples assayed for gene expression (n = 399) and methylation (n = 292), we identified methylation and expression changes associated with PD risk variants in PARK16/1q32, GPNMB/7p15, and STX1B/16p11 loci, hence suggesting potential molecular mechanisms and candidate genes at these risk loc