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Genomic analyses applied to 14 childhood- and adult-onset psychiatric disorders identifies five underlying genomic factors that explain the majority of the genetic variance of the individual disorders.

The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 cancer whole genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.

A genome-wide association study including over 76,000 individuals with schizophrenia and over 243,000 control individuals identifies common variant associations at 287 genomic loci, and further fine-mapping analyses highlight the importance of genes involved in synaptic processes.

A genome-wide-association meta-analysis of 18,381 austim spectrum disorder (ASD) cases and 27,969 controls identifies five risk loci. The authors find quantitative and qualitative polygenic heterogeneity across ASD subtypes.

A genome-wide association study of age at onset of walking in over 70,000 infants found 11 significant loci. Age at onset of walking showed SNP heritability of 24%, a reliable polygenic score and genetic overlap with ADHD and brain phenotypes.

Understanding deregulation of biological pathways in cancer can provide insight into disease etiology and potential therapies. Here, as part of the PanCancer Analysis of Whole Genomes (PCAWG) consortium, the authors present pathway and network analysis of 2583 whole cancer genomes from 27 tumour types.

There’s an emerging body of evidence to show how biological sex impacts cancer incidence, treatment and underlying biology. Here, using a large pan-cancer dataset, the authors further highlight how sex differences shape the cancer genome.

Analyses of 2,658 whole genomes across 38 types of cancer identify the contribution of non-coding point mutations and structural variants to driving cancer.

In somatic cells the mechanisms maintaining the chromosome ends are normally inactivated; however, cancer cells can re-activate these pathways to support continuous growth. Here, the authors characterize the telomeric landscapes across tumour types and identify genomic alterations associated with different telomere maintenance mechanisms.

With the generation of large pan-cancer whole-exome and whole-genome sequencing projects, a question remains about how comparable these datasets are. Here, using The Cancer Genome Atlas samples analysed as part of the Pan-Cancer Analysis of Whole Genomes project, the authors explore the concordance of mutations called by whole exome sequencing and whole genome sequencing techniques.

Integrative analyses of transcriptome and whole-genome sequencing data for 1,188 tumours across 27 types of cancer are used to provide a comprehensive catalogue of RNA-level alterations in cancer.

Whole-genome sequencing data from more than 2,500 cancers of 38 tumour types reveal 16 signatures that can be used to classify somatic structural variants, highlighting the diversity of genomic rearrangements in cancer.

Viral pathogen load in cancer genomes is estimated through analysis of sequencing data from 2,656 tumors across 35 cancer types using multiple pathogen-detection pipelines, identifying viruses in 382 genomic and 68 transcriptome datasets.

Analysis of cancer genome sequencing data has enabled the discovery of driver mutations. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium the authors present DriverPower, a software package that identifies coding and non-coding driver mutations within cancer whole genomes via consideration of mutational burden and functional impact evidence.

A pan-cancer genomic analysis reports the effects of structural variations on chromatin domains (TADs). Most TAD disruptions do not result in appreciable changes in expression of nearby genes.

An analysis of 2,954 genomes from 38 cancer subtypes identified 19,166 retrotransposition events in 35% of samples. Aberrant LINE-1 retrotranspositions can lead to the deletion of tumor-suppressor genes as well as the amplification of oncogenes.

Whole-genome sequencing data for 2,778 cancer samples from 2,658 unique donors across 38 cancer types is used to reconstruct the evolutionary history of cancer, revealing that driver mutations can precede diagnosis by several years to decades.

Some cancer patients first present with metastases where the location of the primary is unidentified; these are difficult to treat. In this study, using machine learning, the authors develop a method to determine the tissue of origin of a cancer based on whole sequencing data.

The authors present SVclone, a computational method for inferring the cancer cell fraction of structural variants from whole-genome sequencing data.

Many tumours exhibit hypoxia (low oxygen) and hypoxic tumours often respond poorly to therapy. Here, the authors quantify hypoxia in 1188 tumours from 27 cancer types, showing elevated hypoxia links to increased mutational load, directing evolutionary trajectories.

Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery.

The characterization of 4,645 whole-genome and 19,184 exome sequences, covering most types of cancer, identifies 81 single-base substitution, doublet-base substitution and small-insertion-and-deletion mutational signatures, providing a systematic overview of the mutational processes that contribute to cancer development.

In this study the authors consider the structural variants (SVs) present within cancer cases of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. They report hundreds of genes, including known cancer-associated genes for which the nearby presence of a SV breakpoint is associated with altered expression.

Cancers evolve as they progress under differing selective pressures. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, the authors present the method TrackSig the estimates evolutionary trajectories of somatic mutational processes from single bulk tumour data.

Using SCN2A haploinsufficiency as a proof-of-concept, upregulation of the existing functional gene copy through CRISPR activation was able to rescue neurological-associated phenotypes in Scn2a haploinsufficient mice and human neurons.

MPRAs and in vivo transgenic mouse assays are two potentially complementary ways to assay the impact of noncoding variants. Here, authors find a strong and specific correlation between the assays in neural cells. Mouse assays also reveal pleiotropic effects not observed in MPRA.

Most genomics research cohorts are made up of participants of European ancestry, which limits the reach of precision medicine. Here, the authors describe the genetic diversity in the All of Us research program, which is enriched in underrepresented ancestries.

Analysis of rare protein-truncating, damaging missense and copy number variants from exome sequencing of 63,237 individuals identifies 72 genes associated with autism spectrum disorder.

The authors defined a roadmap for investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders. Their proof-of-concept study using the largest available common variant data sets for schizophrenia and volumes of several (mainly subcortical) brain structures did not find evidence of genetic overlap.

Scalable CRISPRa screening of cis-regulatory elements in non-cancer cell lines has proved challenging. Here, the authors describe a scalable, CRISPR activation screening framework to identify regulatory element-gene pairs in diverse cell types including cancer cells and neurons.

The V3-crown of the HIV-1 envelope protein largely elicits non-neutralizing antibodies. Here, the authors show that the V3-crown can be targeted by broadly neutralizing designed ankyrin repeat proteins recognizing two conformations one of which resembles CCR5- bound V3.

The non-coding RNA RNU4-2, which is highly expressed in the developing human brain, is identified as a syndromic neurodevelopmental disorder gene, and, using RNA sequencing, 5′ splice-site use is shown to be systematically disrupted in individuals with RNU4-2 variants.

Autism genes converge in midfetal cortical co-expression networks, and chromatin regulators such as CHD8 are increasingly associated with autism spectrum disorder (ASD). Here the authors map CHD8 targets in developing brain, and find that CHD8 directly regulates other ASD risk genes during human neurodevelopment.

Family-based exome sequencing in a large autism study has identified 27 high-confidence gene targets and accurately estimates the contribution of both de novo gene-disrupting and missense mutations to the incidence of simplex autism, with target genes in affected females overlapping those in males of lower but not higher IQ; targets also overlap known targets for intellectual disability and schizophrenia, and are enriched for chromatin modifiers, FMRP-associated genes and embryonically expressed genes.

Analysis of human hippocampus identifies two modules of coexpressed genes that are conserved throughout the human cortex and in mouse hippocampi. These modules are enriched for genetic variants associated with both cognitive phenotypes and neuropsychiatric disorders.

Analysis of whole-genome sequencing data across 2,658 tumors spanning 38 cancer types shows that chromothripsis is pervasive, with a frequency of more than 50% in several cancer types, contributing to oncogene amplification, gene inactivation and cancer genome evolution.

Analysis of mitochondrial genomes (mtDNA) by using whole-genome sequencing data from 2,658 cancer samples across 38 cancer types identifies hypermutated mtDNA cases, frequent somatic nuclear transfer of mtDNA and high variability of mtDNA copy number in many cancers.

Efficient, large-scale genomic analysis is facilitated on the cloud by a computational tool with error-diagnosing and self-healing capabilities.

Here, Swarte et al. use metagenomics to investigate the association between the gut microbiome and Health-Related Quality of Life (HRQoL) in kidney transplant recipients, showing evidence for the association of multiple taxonomic, metabolic and neuroactive pathways (gut brain modules) with lower HRQoL, together suggesting potential modifiable gut microbial factors to improve HRQoL.

Ruth Loos and colleagues report results of a large genome-wide association study for body mass index. They identify 18 new loci associated with this trait, some of which map near key hypothalamic regulators of energy balance.

This study presents a framework to evaluate rare and de novo variation from whole-genome sequencing (WGS). The work suggests that robust results from WGS studies will require large cohorts and strategies that consider the substantial multiple-testing burden.

The molecular genetic landscape of leiomyosarcoma (LMS) is largely unknown. Here, the authors identify frequent DNA copy number alterations, whole-genome duplication, TP53 and RB1 inactivation, alternative telomere lengthening, and genomic imprints of defective DNA repair via homologous recombination as a potential therapeutic target in LMS patients.

Patrick Sullivan and colleagues report a multi-stage genome-wide association study for schizophrenia in a Swedish population. They identify 13 loci newly associated with schizophrenia.

Stratified medicine promises to tailor treatment for individual patients, however it remains a major challenge to leverage genetic risk data to aid patient stratification. Here the authors introduce an approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue-specific gene expression levels, and highlight its ability to identify biologically meaningful and clinically actionable patient subgroups, supporting the notion of different patient ‘biotypes’ characterized by partially distinct disease mechanisms.

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.