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The Taiwanese people are composed of diverse indigenous populations and the Taiwanese Han. About 95% of the Taiwanese identify themselves as Taiwanese Han, but this may not be a homogeneous population because they migrated to the island from various regions of continental East Asia over a period of 400 years. Little is known about the underlying patterns of genetic ancestry, population admixture, and evolutionary adaptation in the Taiwanese Han people. Here, we analyzed the whole-genome single-nucleotide polymorphism genotyping data from 14,401 individuals of Taiwanese Han collected by the Taiwan Biobank and the whole-genome sequencing data for a subset of 772 people. We detected four major genetic ancestries with distinct geographic distributions (i.e., Northern, Southeastern, Japonic, and Island Southeast Asian ancestries) and signatures of population mixture contributing to the genomes of Taiwanese Han. We further scanned for signatures of positive natural selection that caused unusually long-range haplotypes and elevations of hitchhiked variants. As a result, we identified 16 candidate loci in which selection signals can be unambiguously localized at five single genes: CTNNA2, LRP1B, CSNK1G3, ASTN2, and NEO1. Statistical associations were examined in 16 metabolic-related traits to further elucidate the functional effects of each candidate gene. All five genes appear to have pleiotropic connections to various types of disease susceptibility and significant associations with at least one metabolic-related trait. Together, our results provide critical insights for understanding the evolutionary history and adaption of the Taiwanese Han population.

Background Many multicellular eukaryotes have two types of spliceosomes for the removal of introns from messenger RNA precursors. The major (U2) spliceosome processes the vast majority of introns, referred to as U2-type introns, while the minor (U12) spliceosome removes a small fraction (less than 0.5%) of introns, referred to as U12-type introns. U12-type introns have distinct sequence elements and usually occur together in genes with U2-type introns. A phylogenetic distribution of U12-type introns shows that the minor splicing pathway appeared very early in eukaryotic evolution and has been lost repeatedly. Results We have investigated the evolution of U12-type introns among eighteen metazoan genomes by analyzing orthologous U12-type intron clusters. Examination of gain, loss, and type switching shows that intron type is remarkably conserved among vertebrates. Among 180 intron clusters, only eight show intron loss in any vertebrate species and only five show conversion between the U12 and the U2-type. Although there are only nineteen U12-type introns in Drosophila melanogaster , we found one case of U2 to U12-type conversion, apparently mediated by the activation of cryptic U12 splice sites early in the dipteran lineage. Overall, loss of U12-type introns is more common than conversion to U2-type and the U12 to U2 conversion occurs more frequently among introns of the GT-AG subtype than among introns of the AT-AC subtype. We also found support for natural U12-type introns with non-canonical terminal dinucleotides (CT-AC, GG-AG, and GA-AG) that have not been previously reported. Conclusions Although complete loss of the U12-type spliceosome has occurred repeatedly, U12 introns are extremely stable in some taxa, including eutheria. Loss of U12 introns or the genes containing them is more common than conversion to the U2-type. The degeneracy of U12-type terminal dinucleotides among natural U12-type introns is higher than previously thought.

Exome sequencing of 175 autism spectrum disorder parent–child trios reveals that few de novo point mutations have a role in autism spectrum disorder and those that do are distributed across many genes and are incompletely penetrant, further supporting extreme genetic heterogeneity of this spectrum disorder. Heterogeneity in the genetics of autism Although it is well accepted that genetics makes a strong contribution to autism spectrum disorder, most of the underlying causes of the condition remain unknown. Three groups present large-scale exome-sequencing studies of individuals with sporadic autism spectrum disorder, including many parent–child trios and unaffected siblings. The overall message from the three papers is that there is extreme locus heterogeneity among autistic individuals, with hundreds of genes involved in the condition, and with no single gene contributing to more than a small fraction of cases. Sanders et al . report the association of the gene SCN2A , previously identified in epilepsy syndromes, with the risk of autism. Neale et al . find strong evidence that CHD8 and KATNAL2 are autism risk factors. O'Roak et al . observe that a large proportion of the mutated proteins have crucial roles in fundamental developmental pathways, including β-catenin and p53 signalling. Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified 1 , 2 . To identify further genetic risk factors, here we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents ( n = 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant, and the overall rate of mutation is only modestly higher than the expected rate. In contrast, the proteins encoded by genes that harboured de novo missense or nonsense mutations showed a higher degree of connectivity among themselves and to previous ASD genes 3 as indexed by protein-protein interaction screens. The small increase in the rate of de novo events, when taken together with the protein interaction results, are consistent with an important but limited role for de novo point mutations in ASD, similar to that documented for de novo copy number variants. Genetic models incorporating these data indicate that most of the observed de novo events are unconnected to ASD; those that do confer risk are distributed across many genes and are incompletely penetrant (that is, not necessarily sufficient for disease). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5- to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case–control study provide strong evidence in favour of CHD8 and KATNAL2 as genuine autism risk factors.

Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10-6) and 14 (IGHV1-67 p = 7.9×10-8) which indexed novel susceptibility loci. The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.

In October 2019, 46 scientists from around the world participated in the first National Center for Biotechnology Information (NCBI) Structural Variation (SV) Codeathon at Baylor College of Medicine. The charge of this first annual working session was to identify ongoing challenges around the topics of SV and graph genomes, and in response to design reliable methods to facilitate their study. Over three days, seven working groups each designed and developed new open-sourced methods to improve the bioinformatic analysis of genomic SVs represented in next-generation sequencing (NGS) data. The groups' approaches addressed a wide range of problems in SV detection and analysis, including quality control (QC) assessments of metagenome assemblies and population-scale VCF files, de novo copy number variation (CNV) detection based on continuous long sequence reads, the representation of sequence variation using graph genomes, and the development of an SV annotation pipeline. A summary of the questions and developments that arose during the daily discussions between groups is outlined. The new methods are publicly available at https://github.com/NCBI-Codeathons/, and demonstrate that a codeathon devoted to SV analysis can produce valuable new insights both for participants and for the broader research community.

Although mutation, genetic drift, and natural selection are well established as determinants of genome evolution, the importance (frequency and magnitude) of parameter fluctuations in molecular evolution is less understood. DNA sequence comparisons among closely related species allow specific substitutions to be assigned to lineages on a phylogenetic tree. In this study, we compare patterns of codon usage and protein evolution in 22 genes (>11,000 codons) among Drosophila melanogaster and five relatives within the D. melanogaster subgroup. We assign changes to eight lineages using a maximum-likelihood approach to infer ancestral states. Uncertainty in ancestral reconstructions is taken into account, at least to some extent, by weighting reconstructions by their posterior probabilities. Four of the eight lineages show potentially genomewide departures from equilibrium synonymous codon usage; three are decreasing and one is increasing in major codon usage. Several of these departures are consistent with lineage-specific changes in selection intensity (selection coefficients scaled to effective population size) at silent sites. Intron base composition and rates and patterns of protein evolution are also heterogeneous among these lineages. The magnitude of forces governing silent, intron, and protein evolution appears to have varied frequently, and in a lineage-specific manner, within the D. melanogaster subgroup.

Factors affecting splicing of plant U12-dependent introns have been examined by extensive mutational analyses in an in vivo tobacco (Nicotiana tabacum) protoplast system using introns from three different Arabidopsis thaliana genes: CBP20, GSH2, and LD. The results provide evidence that splicing efficiency of plant U12 introns depends on a combination of factors, including UA content, exon bridging interactions between the U12 intron and flanking U2-dependent introns, and exon splicing enhancer sequences (ESEs). Unexpectedly, all three plant U12 introns required an adenosine at the upstream purine position in the branchpoint consensus UCCUURAUY. The exon upstream of the LD U12 intron is a major determinant of its higher level of splicing efficiency and potentially contains two ESE regions. These results suggest that in plants, U12 introns represent a level at which expression of their host genes can be regulated.

Effective implementation of precision medicine will be enhanced by a thorough understanding of each patient’s genetic composition to better treat his or her presenting symptoms or mitigate the onset of disease. This ideally includes the sequence information of a complete genome for each individual. At Partners HealthCare Personalized Medicine, we have developed a clinical process for whole genome sequencing (WGS) with application in both healthy individuals and those with disease. In this manuscript, we will describe our bioinformatics strategy to efficiently process and deliver genomic data to geneticists for clinical interpretation. We describe the handling of data from FASTQ to the final variant list for clinical review for the final report. We will also discuss our methodology for validating this workflow and the cost implications of running WGS.

The genetic architecture of autism spectrum disorder involves the interplay of common and rare variants and their impact on hundreds of genes. Using exome sequencing, here we show that analysis of rare coding variation in 3,871 autism cases and 9,937 ancestry-matched or parental controls implicates 22 autosomal genes at a false discovery rate (FDR) < 0.05, plus a set of 107 autosomal genes strongly enriched for those likely to affect risk (FDR < 0.30). These 107 genes, which show unusual evolutionary constraint against mutations, incur de novo loss-of-function mutations in over 5% of autistic subjects. Many of the genes implicated encode proteins for synaptic formation, transcriptional regulation and chromatin-remodelling pathways. These include voltage-gated ion channels regulating the propagation of action potentials, pacemaking and excitability–transcription coupling, as well as histone-modifying enzymes and chromatin remodellers—most prominently those that mediate post-translational lysine methylation/demethylation modifications of histones. Whole-exome sequencing in a large autism study identifies over 100 autosomal genes that are likely to affect risk for the disorder; these genes, which show unusual evolutionary constraint against mutations, carry de novo loss-of-function mutations in over 5% of autistic subjects and many function in synaptic, transcriptional and chromatin-remodelling pathways. Autism-linked genetic factors analysed Autism spectrum disorder (ASD) is a broad group of brain development disorders, including autism, childhood disintegrative disorder and Asperger's syndrome, characterized by impaired social interaction and communication, repetitive behaviour and restricted interests. Two groups reporting in this issue of Nature have used large-scale whole-exome sequencing to examine the contribution of inherited and germline de novo mutations to ASD risk. Silvia De Rubeis et al . analysed DNA samples from 3,871 autism cases and 9,937 ancestry-matched or parental controls and identify more than 100 autosomal genes that are likely to affect risk for the disease. De novo loss-of-function mutations were detected in more than 5% of autistic subjects. Many of the associated gene products appear to function in synaptic, transcriptional, and chromatin remodelling pathways. Ivan Iossifov et al . sequenced exomes from more than 2,500 families, each with one child with ASD. They identify 27 high-confidence gene targets and estimate that 13% of de novo missense mutations and 43% of de novo 'likely gene-disrupting' (LGD) mutations contribute to 12% and 9% of diagnoses, respectively.