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Genome-wide association analyses using data from 19 biobanks identify variants influencing risk of thyroid diseases and yield polygenic risk scores associated with features of aggressive thyroid cancer.

KRAB-zinc finger proteins repress retrotransposons and rapidly evolve in mammals. Here, the authors show that ERV insertions drive the emergence and diversification of new KZFP genes in mice, revealing a co-evolutionary mechanism between retroviruses and host repressors.

Genome-wide association meta-analyses identify 26 risk loci for epilepsy, including 19 loci specific to genetic generalized epilepsy. Prioritized candidate genes implicate synaptic processes and overlap with targets of antiseizure medications.

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.

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.

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.

This report from the 1000 Genomes Project describes the genomes of 1,092 individuals from 14 human populations, providing a resource for common and low-frequency variant analysis in individuals from diverse populations; hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites, can be found in each individual.

Invasive extravillous trophoblast cells are a key feature of placentation and successful pregnancy. Here, the authors identify transcription factors and regulatory mechanisms critical for extravillous trophoblast cell lineage development.

Maternal genome-wide analyses identify variants associated with gestational duration and preterm delivery. Maternal alleles positively associated with gestational duration exhibit negative fetal effects on birth weight, likely reflecting antagonistic pleiotropy.

Results for the final phase of the 1000 Genomes Project are presented including whole-genome sequencing, targeted exome sequencing, and genotyping on high-density SNP arrays for 2,504 individuals across 26 populations, providing a global reference data set to support biomedical genetics.

Genome-wide analyses using fetal and parental genotypes identify 40 independent associations influencing placental weight and highlight the role of the fetus in preeclampsia risk and placental growth regulation via insulin signaling.

Proper brain function depends on the correct assembly of excitatory and inhibitory neurons into neural circuits. Here the authors show that during early postnatal development in mice, NMDAR signaling via activity of long-range synaptic inputs onto neurogliaform cells is required for their appropriate integration into the hippocampal circuitry.

Metabolomic profiling identified widespread adrenal insufficiency in patients with asthma receiving inhaled corticosteroids, which is a mainstay of asthma treatment, arguing for the need for regular monitoring of such patients to avoid adverse effects of adrenal suppression.

Heterozygous deletions in the ANKS1B gene cause ANKS1B neurodevelopmental syndrome. Here the authors show this syndrome is associated with impaired white matter integrity, and that Anks1b-deficient mouse models display deficits in oligodendrocyte maturation, myelination, and Rac1 function.

Genome-wide analysis of copy number variants in 2,824 cases across the phenotypic spectrum of CAKUT sheds light on the genomic architecture of disease and identifies TBX6 as a driver for CAKUT subphenotypes in the 16p11.2 microdeletion syndrome.

In this study, the authors show that MGE- and CGE-derived GABAergic interneurons exhibit differences in their synaptic receptor composition. In particular, they find that MGE-derived interneuron synapses are dominated by calcium-permeable, GluA2-lacking AMPARs, whereas CGE-derived interneurons use both NMDARs and GluA2-containing AMPARs.

Epilepsies are common brain disorders and are classified based on clinical phenotyping, imaging and genetics. Here, the authors perform genome-wide association studies for 3 broad and 7 subtypes of epilepsy and identify 16 loci - 11 novel - that are further annotated by eQTL and partitioned heritability analyses.

There is a diverse set of cortical interneurons that uniquely participate in the computations of large cell assemblies. Here the authors show that the same type of interneuron within the hippocampus, those projecting to the oriens-lacunosum moleculare, can have distinct developmental origins and different circuit functions.

Ancestry and socioeconomic factors influence predictable changes in the vaginal microbiome that occur early in pregnancy in women who experience normal term birth.

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.

1000 Genomes imputation can increase the power of genome-wide association studies to detect genetic variants associated with human traits and diseases. Here, the authors develop a method to integrate and analyse low-coverage sequence data and SNP array data, and show that it improves imputation performance.

How genetic variation contributes to brain morphology is still poorly understood. Here Chenet al. combine brain imaging with single-nucleotide polymorphism data to discover that a substantial degree of cortical variation is derived from underlying genetic differences.