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Survey of postzygotic mosaic mutations (PZMs) in 5,947 trios with autism spectrum disorders (ASD) discovers differences in mutational properties between germline mutations and PZMs. Spatiotemporal analyses of the PZMs also revealed the association of the amygdala with ASD and implicated risk genes, including recurrent potential gain-of-function mutations in SMARCA4 . We systematically analyzed postzygotic mutations (PZMs) in whole-exome sequences from the largest collection of trios (5,947) with autism spectrum disorder (ASD) available, including 282 unpublished trios, and performed resequencing using multiple independent technologies. We identified 7.5% of de novo mutations as PZMs, 83.3% of which were not described in previous studies. Damaging, nonsynonymous PZMs within critical exons of prenatally expressed genes were more common in ASD probands than controls ( P < 1 × 10 −6 ), and genes carrying these PZMs were enriched for expression in the amygdala ( P = 5.4 × 10 −3 ). Two genes ( KLF16 and MSANTD2 ) were significantly enriched for PZMs genome-wide, and other PZMs involved genes ( SCN2A , HNRNPU and SMARCA4 ) whose mutation is known to cause ASD or other neurodevelopmental disorders. PZMs constitute a significant proportion of de novo mutations and contribute importantly to ASD risk.

Community microattribution review of the evidence for colon cancer risk conferred by constitutional variants in MLH1 , MSH2 , MSH6 and PMS2 has resulted in the reclassification of two-thirds of the variants reported in existing databases and led to clinical recommendations for the interpretation of 1,370 variants that do not result in obvious protein truncation. The clinical classification of hereditary sequence variants identified in disease-related genes directly affects clinical management of patients and their relatives. The International Society for Gastrointestinal Hereditary Tumours (InSiGHT) undertook a collaborative effort to develop, test and apply a standardized classification scheme to constitutional variants in the Lynch syndrome–associated genes MLH1 , MSH2 , MSH6 and PMS2 . Unpublished data submission was encouraged to assist in variant classification and was recognized through microattribution. The scheme was refined by multidisciplinary expert committee review of the clinical and functional data available for variants, applied to 2,360 sequence alterations, and disseminated online. Assessment using validated criteria altered classifications for 66% of 12,006 database entries. Clinical recommendations based on transparent evaluation are now possible for 1,370 variants that were not obviously protein truncating from nomenclature. This large-scale endeavor will facilitate the consistent management of families suspected to have Lynch syndrome and demonstrates the value of multidisciplinary collaboration in the curation and classification of variants in public locus-specific databases.

The most popular repository for sharing SARS-CoV-2 sequence data has come under increasing scrutiny. Scientists and funders around the world must now consider what lies ahead for the open sharing of genome data. The most popular repository for sharing SARS-CoV-2 sequence data has come under increasing scrutiny. Scientists and funders around the world must now consider what lies ahead for the open sharing of genome data.

Efforts to protect people’s privacy in a massive international cancer project offer lessons for data sharing. Efforts to protect people’s privacy in a massive international cancer project offer lessons for data sharing. Coloured scanning electron micrograph of a migrating breast cancer cell

Existing benchmark datasets for use in evaluating variant-calling accuracy are constructed from a consensus of known short-variant callers, and they are thus biased toward easy regions that are accessible by these algorithms. We derived a new benchmark dataset from the de novo PacBio assemblies of two fully homozygous human cell lines, which provides a relatively more accurate and less biased estimate of small-variant-calling error rates in a realistic context.

Public variant databases support the curation, clinical interpretation, and sharing of genomic data, thus reducing harmful errors or delays in diagnosis. As variant databases are increasingly relied on in the clinical context, there is concern that negligent variant interpretation will harm patients and attract liability. This article explores the evolving legal duties of laboratories, public variant databases, and physicians in clinical genomics and recommends a governance framework for databases to promote responsible data sharing. Genet Med advance online publication 15 December 2016

Major funding agencies should ensure that large biological data sets are stored in cloud services to enable easy access and fast analysis, say Lincoln D. Stein and colleagues.

Increasing evidence indicates that non-DNA sequence-based epigenetic information can be inherited across several generations in organisms ranging from yeast to plants to humans. This raises the possibility of heritable ‘epimutations’ contributing to heritable phenotypic variation and thus to evolution. Recent work has shed light on both the signals that underpin these epimutations, including DNA methylation, histone modifications and non-coding RNAs, and the mechanisms by which they are transmitted across generations at the molecular level. These mechanisms can vary greatly among species and have a more limited effect in mammals than in plants and other animal species. Nevertheless, common principles are emerging, with transmission occurring either via direct replicative mechanisms or indirect reconstruction of the signal in subsequent generations. As these processes become clearer we continue to improve our understanding of the distinctive features and relative contribution of DNA sequence and epigenetic variation to heritable differences in phenotype.In this Review, Fitz-James and Cavalli discuss the diverse and often multilayered mechanisms by which transgenerational epigenetic inheritance can occur in different species.

Key Points Over the past decade, high-throughput gene expression experiments have generated data from millions of assays. Data sets linked to publications are stored in functional genomics data archives: ArrayExpress at the European Bioinformatics Institute, Gene Expression Omnibus at the US National Center for Biotechnology Information and at the DNA Databank of Japan Omics Archive. Secondary added-value and topical databases process data from the primary archives, adding analysis and annotation to make these data accessible to every biologist by allowing queries such as 'in which tissue is a particular gene expressed?' or 'which genes are differentially expressed between a particular disease and normal samples?' Public gene expression data are commonly reused to study biological questions, both by reanalysis of primary data and by queries to secondary resources. Approximately half of the studies that use public gene expression data rely solely on existing data without adding newly generated data, and half of them use the public data in combination with new data. The reproducibility of published microarray-based studies is limited, mostly owing to insufficient experiment annotation and sometimes to unavailability of the raw or processed data. A stricter enforcement of Minimum Information About a Microarray Experiment (MIAME) requirements and also development of easy-to-use experiment annotation tools are needed to achieve a better reproducibility. Although most of the public gene expression data still are based on microarray experiments, the contribution of high-throughput-sequencing-based expression studies, known as RNA sequencing (RNA-seq), are growing rapidly. Reuse of RNA-seq data can potentially be even more valuable than reuse of microarray data, partly owing to the costs of experiments and data storage but even more importantly because of a more quantitative nature of sequencing-based expression data. Community standards such as Minimum Information about Sequencing Experiments (MINSEQE) should be adopted to make RNA-seq data maximally reusable. The bioinformatics resources that store and manage public data are sensitive to short-term funding changes, complicating the maintenance of important databases. The development of long-term infrastructure in bioinformatics, such as the ELIXIR project in Europe, is needed to ensure the long term availability of public data. A wealth of microarray gene expression data and a growing volume of RNA sequencing data are now available in public databases. The authors look at how these data are being used and discuss considerations for how such data should be analysed and deposited and how data reuse could be improved. Our understanding of gene expression has changed dramatically over the past decade, largely catalysed by technological developments. High-throughput experiments — microarrays and next-generation sequencing — have generated large amounts of genome-wide gene expression data that are collected in public archives. Added-value databases process, analyse and annotate these data further to make them accessible to every biologist. In this Review, we discuss the utility of the gene expression data that are in the public domain and how researchers are making use of these data. Reuse of public data can be very powerful, but there are many obstacles in data preparation and analysis and in the interpretation of the results. We will discuss these challenges and provide recommendations that we believe can improve the utility of such data.

Multi-million efforts are underway to fill long-standing gaps in genomic data from minority groups. Multi-million efforts are underway to fill long-standing gaps in genomic data from minority groups. A 14 year old girl with Hodgkins Lymphoma is to be treated at St. Jude in Memphis, Tennessee