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Breast cancers are complex cellular ecosystems where heterotypic interactions play central roles in disease progression and response to therapy. However, our knowledge of their cellular composition and organization is limited. Here we present a single-cell and spatially resolved transcriptomics analysis of human breast cancers. We developed a single-cell method of intrinsic subtype classification (SCSubtype) to reveal recurrent neoplastic cell heterogeneity. Immunophenotyping using cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) provides high-resolution immune profiles, including new PD-L1/PD-L2 + macrophage populations associated with clinical outcome. Mesenchymal cells displayed diverse functions and cell-surface protein expression through differentiation within three major lineages. Stromal-immune niches were spatially organized in tumors, offering insights into antitumor immune regulation. Using single-cell signatures, we deconvoluted large breast cancer cohorts to stratify them into nine clusters, termed 'ecotypes', with unique cellular compositions and clinical outcomes. This study provides a comprehensive transcriptional atlas of the cellular architecture of breast cancer., (© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Loci discovered by genome-wide association studies predominantly map outside protein-coding genes. The interpretation of the functional consequences of non-coding variants can be greatly enhanced by catalogs of regulatory genomic regions in cell lines and primary tissues. However, robust and readily applicable methods are still lacking by which to systematically evaluate the contribution of these regions to genetic variation implicated in diseases or quantitative traits. Here we propose a novel approach that leverages genome-wide association studies' findings with regulatory or functional annotations to classify features relevant to a phenotype of interest. Within our framework, we account for major sources of confounding not offered by current methods. We further assess enrichment of genome-wide association studies for 19 traits within Encyclopedia of DNA Elements- and Roadmap-derived regulatory regions. We characterize unique enrichment patterns for traits and annotations driving novel biological insights. The method is implemented in standalone software and an R package, to facilitate its application by the research community.

This corrects the article DOI: 10.1038/ng.3771.

Animal promoters initiate transcription either at precise positions (narrow promoters) or dispersed regions (broad promoters), a distinction referred to as promoter shape. Although highly conserved, the functional properties of promoters with different shapes and the genetic basis of their evolution remain unclear. Here we used natural genetic variation across a panel of 81 Drosophila lines to measure changes in transcriptional start site (TSS) usage, identifying thousands of genetic variants affecting transcript levels (strength) or the distribution of TSSs within a promoter (shape). Our results identify promoter shape as a molecular trait that can evolve independently of promoter strength. Broad promoters typically harbor shape-associated variants, with signatures of adaptive selection. Single-cell measurements demonstrate that variants modulating promoter shape often increase expression noise, whereas heteroallelic interactions with other promoter variants alleviate these effects. These results uncover new functional properties of natural promoters and suggest the minimization of expression noise as an important factor in promoter evolution.

Somatic rearrangements contribute to the mutagenized landscape of cancer genomes. Here, we systematically interrogated rearrangements in 560 breast cancers by using a piecewise constant fitting approach. We identified 33 hotspots of large (>100 kb) tandem duplications, a mutational signature associated with homologous-recombination-repair deficiency. Notably, these tandem-duplication hotspots were enriched in breast cancer germline susceptibility loci (odds ratio (OR) = 4.28) and breast-specific 'super-enhancer' regulatory elements (OR = 3.54). These hotspots may be sites of selective susceptibility to double-strand-break damage due to high transcriptional activity or, through incrementally increasing copy number, may be sites of secondary selective pressure. The transcriptomic consequences ranged from strong individual oncogene effects to weak but quantifiable multigene expression effects. We thus present a somatic-rearrangement mutational process affecting coding sequences and noncoding regulatory elements and contributing a continuum of driver consequences, from modest to strong effects, thereby supporting a polygenic model of cancer development.

We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.

Genome-wide association studies have previously identified variants in SLC30A8, encoding the zinc transporter ZnT8, associated with diabetes risk. A rare variant association study has now established the direction of effect, surprisingly showing that loss-of-function mutations in SLC30A8 are protective against diabetes.

Migraine is the most common brain disorder, affecting approximately 14% of the adult population, but its molecular mechanisms are poorly understood. We report the results of a meta-analysis across 29 genome-wide association studies, including a total of 23,285 individuals with migraine (cases) and 95,425 population-matched controls. We identified 12 loci associated with migraine susceptibility (P<5×10(-8)). Five loci are new: near AJAP1 at 1p36, near TSPAN2 at 1p13, within FHL5 at 6q16, within C7orf10 at 7p14 and near MMP16 at 8q21. Three of these loci were identified in disease subgroup analyses. Brain tissue expression quantitative trait locus analysis suggests potential functional candidate genes at four loci: APOA1BP, TBC1D7, FUT9, STAT6 and ATP5B.

The laboratory rat is one of the most extensively studied model organisms. Inbred laboratory rat strains originated from limited Rattus norvegicus founder populations, and the inherited genetic variation provides an excellent resource for the correlation of genotype to phenotype. Here, we report a survey of genetic variation based on almost 3 million newly identified SNPs. We obtained accurate and complete genotypes for a subset of 20,238 SNPs across 167 distinct inbred rat strains, two rat recombinant inbred panels and an F2 intercross. Using 81% of these SNPs, we constructed high-density genetic maps, creating a large dataset of fully characterized SNPs for disease gene mapping. Our data characterize the population structure and illustrate the degree of linkage disequilibrium. We provide a detailed SNP map and demonstrate its utility for mapping of quantitative trait loci. This community resource is openly available and augments the genetic tools for this workhorse of physiological studies.

It has been four years since the original publication of the draft sequence of the rat genome. Five groups are now working together to assemble, annotate and release an updated version of the rat genome. As the prevailing model for physiology, complex disease and pharmacological studies, there is an acute need for the rat's genomic resources to keep pace with the rat's prominence in the laboratory. In this commentary, we describe the current status of the rat genome sequence and the plans for its impending 'upgrade'. We then cover the key online resources providing access to the rat genome, including the new SNP views at Ensembl, the RefSeq and Genes databases at the US National Center for Biotechnology Information, Genome Browser at the University of California Santa Cruz and the disease portals for cardiovascular disease and obesity at the Rat Genome Database.

There has been an explosion of data describing newly recognized structural variants in the human genome. In the flurry of reporting, there has been no standard approach to collecting the data, assessing its quality or describing identified features. This risks becoming a rampant problem, in particular with respect to surveys of copy number variation and their application to disease studies. Here, we consider the challenges in characterizing and documenting genomic structural variants. From this, we derive recommendations for standards to be adopted, with the aim of ensuring the accurate presentation of this form of genetic variation to facilitate ongoing research.