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A new method called polymerase error rate sequencing (PER-seq) can measure the nucleotide misincorporation rate of DNA polymerases. DNA polymerase ε mutants produce an excess of CpG<TpG errors during DNA replication in a deamination-independent manner resembling the mutation spectrum in tumors.

C-to-T mutations in CpG dinucleotides are widespread in cancers and are also observed in normal cells. By developing and using a technique to quantify DNA polymerase errors (polymerase error rate sequencing, PER-seq), we reveal that C-to-T mutations in CpG dinucleotides constitute part of the error signature of both wild-type and mutant cancer-associated DNA polymerase ε.

Genome-wide analyses identify common variants associated with 11 distinct neuropathology endophenotypes, providing insights into the mechanisms underlying the genetic risk of Alzheimer’s disease and related dementias.

Rare variant analyses identify a new type 2 diabetes risk allele near the LEP gene, which encodes leptin, and other risk alleles of intermediate penetrance in genes previously implicated in monogenic forms of diabetes.

Analyses of height and body mass index in 119,000 sibling pairs show that linkage and genome-wide association signals colocalize. Further analyses suggest that family-based linkage signals are fully consistent with a highly polygenic architecture.

African American patients were under-represented in the studies that led to the current patient classification system for acute myeloid leukemia (AML). A new in-depth analysis of the genetics of AML in African Americans suggests that this omission has implications for patient care.

Analysis of exomes and transcriptomes from 100 African American patients with acute myeloid leukemia identifies ancestry-related variation in mutation profiles and survival. Refined risk classification suggests clinical relevance of these ancestry-associated differences.

To understand the genetic basis of disease, it is essential to study diverse populations. We conducted the largest study to date of African men to evaluate the evolutionary genetics and causes of prostate cancer. Our findings reveal novel genetic associations, including those that were not observed in studies of non-African populations.

Genome-wide association and fine-mapping analyses in approximately 260,000 Japanese individuals combined with a newly constructed Japanese-specific genotype reference panel identify hundreds of new loci and putative causal variants for 63 quantitative traits.

This study identifies context-only transcription factors (TFs), a TF class that enhances DNA accessibility initiated by cell type-specific TFs and establishes cooperative environments. Enhancers enriched with motifs of both TF classes show high coactivator binding, enhanced coordination and sensitivity to bromodomain inhibitors.

Immune recognition of cancers can be inhibited if the molecules that present cancer cell-specific antigens are disrupted. We have developed a tool that can detect four different types of disruption. Overall, we find that both genetic and non-genetic disruption of these molecules is common in lung and breast tumors.

Accurate naming of genetic variants is essential to identify clinical data that interpret the consequences of such variants. In partnership with the Human Genome Organization, we advocate for integration of VariantValidator in publishing of journals and databases, to improve the quality of shared genetic data and ultimately patient outcomes.

Genome-wide association analyses of prostate cancer in men from sub-Saharan Africa identify population-specific risk variants and regional differences in effect sizes. Founder effects contribute to continental differences in the genetic architecture of prostate cancer.

This Review discusses recurrent aneuploidies driving human cancer, methods to identify them and strategies to uncover underlying driver genes. It highlights genomic and experimental approaches to study and ultimately target driver aneuploidies.

Major histocompatibility complex (MHC) loss of heterozygosity, allele-specific mutation and measurement of expression and repression (MHC Hammer) detects disruption to human leukocyte antigens due to mutations, loss of heterogeneity, altered gene expression or alternative splicing. Applied to lung and breast cancer datasets, the tool shows that these aberrations are common across cancer and can have clinical implications.

Post-prediction genome-wide association study (POP-GWAS) is a statistical framework that uses summary statistics from labeled samples with both observed and imputed phenotypes to debias single-nucleotide polymorphism effect size estimates for unlabeled samples with imputed phenotypes only, leading to valid and powerful inference.