Currently, many studies on neuropsychiatric disorders have utilized massive trio-based whole-exome sequencing (WES) and whole-genome sequencing (WGS) to identify numerous de novo mutations (DNMs). Here, we retrieved 17,104 DNMs from 3,555 trios across four neuropsychiatric disorders: autism spectrum disorder (ASD), epileptic encephalopathy (EE), intellectual disability (ID), schizophrenia (SCZ), in addition to unaffected siblings (Control), from 36 studies by WES/WGS. After eliminating non-exonic variants, we focused on 3,334 exonic DNMs for evaluation their association with these diseases. Our results revealed a higher prevalence of DNMs in the probands of all four disorders than the one in the controls (P < 1.3 × 10-7). The elevated DNM frequency is dominated by loss-of-function/deleterious single nucleotide variants and frameshift indels (i.e., extreme mutations, P < 4.5 × 10-5). With extensive annotation of these “extreme” mutations, we prioritized 764 candidate genes in these four disorders. A combined analysis of Gene Ontology, microRNA targets, and transcription factor targets revealed shared biological process and non-coding regulatory elements of candidate genes in the pathology of neuropsychiatric disorders. In addition, weighted gene co-expression network analysis (WGCNA) of human laminar-specific neocortical expression data showed that candidate genes are convergent on eight shared modules with specific layer-enrichment and biological process features. Furthermore, we identified that 53 candidate genes are associated with more than one disorder (P < 0.000001), suggesting a possibly shared genetic etiology underlying these disorders. Particularly, DNMs of the SCN2A gene are frequently occurred across all four disorders. Finally, we constructed a freely available NPdenovo database, which provides a comprehensive catalog of the DNMs identified in neuropsychiatric disorders.

This article reports an analysis of the first detailed chemistry direct numerical simulation (DNS) of a high Karlovitz number laboratory premixed flame. The DNS results are first compared with those from laser-based diagnostics with good agreement. The subsequent analysis focuses on a detailed investigation of the flame area, its local thickness and their rates of change in isosurface following reference frames, quantities that are intimately connected. The net flame stretch is demonstrated to be a small residual of large competing terms: the positive tangential strain term and the negative curvature stretch term. The latter is found to be driven by flame speed–curvature correlations and dominated in net by low probability highly curved regions. Flame thickening is demonstrated to be substantial on average, while local regions of flame thinning are also observed. The rate of change of the flame thickness (as measured by the scalar gradient magnitude) is demonstrated, analogously to flame stretch, to be a competition between straining tending to increase gradients and flame speed variations in the normal direction tending to decrease them. The flame stretch and flame thickness analyses are connected by the observation that high positive tangential strain rate regions generally correspond with low curvature regions; these regions tend to be positively stretched in net and are relatively thinner compared with other regions. High curvature magnitude regions (both positive and negative) generally correspond with lower tangential strain; these regions are in net negatively stretched and thickened substantially.

N 6 -methyladenosine (m 6 A) plays important roles in regulating mRNA processing. Despite rapid progress in this field, little is known about genetic determinants of m 6 A modification and their role in common diseases. In this work, we mapped quantitative trait loci (QTLs) of m 6 A peaks in 60 Yoruba lymphoblast cell lines (LCLs). We find that m 6 A-QTLs are largely independent of expression and splicing QTLs, and are enriched with binding sites of RNA-binding proteins (RBPs), RNA structure-changing variants and transcriptional features. Joint analysis of QTLs of m 6 A and related molecular traits suggests that downstream effects of m 6 A are heterogeneous and context-dependent. We identified proteins that mediate m 6 A effects on translation. Integrating with data from genome-wide association studies (GWAS), we show that m 6 A-QTLs contribute to heritability of various immune and blood-related traits at levels comparable to splicing-QTLs and roughly half of eQTLs. Leveraging m 6 A-QTLs in a transcriptome-wide association study (TWAS) framework, we identified putative risk genes of these traits.

Cross-ethnic genetic studies can leverage power from differences in disease epidemiology and population-specific genetic architecture. In particular, the differences in linkage disequilibrium and allele frequency patterns across ethnic groups may increase gene-mapping resolution. Here we use cross-ethnic genetic data in sporadic amyotrophic lateral sclerosis (ALS), an adult-onset, rapidly progressing neurodegenerative disease. We report analyses of novel genome-wide association study data of 1,234 ALS cases and 2,850 controls. We find a significant association of rs10463311 spanning GPX3-TNIP1 with ALS (p = 1.3 × 10−8), with replication support from two independent Australian samples (combined 576 cases and 683 controls, p = 1.7 × 10−3). Both GPX3 and TNIP1 interact with other known ALS genes (SOD1 and OPTN, respectively). In addition, GGNBP2 was identified using gene-based analysis and summary statistics-based Mendelian randomization analysis, although further replication is needed to confirm this result. Our results increase our understanding of genetic aetiology of ALS.