Reviews & Analysis

Identifying genetic risk factors for binge-eating disorder (BED) is vital to understand its etiology and develop effective prevention and intervention strategies. To overcome under-reporting of clinical BED diagnosis, a new study uses machine learning to identify genetic variants associated with quantitative BED risk scores and finds evidence for a pathological role of heme metabolism.

Incidence of keratinocyte skin cancer varies markedly between populations living in different areas of the world. A detailed analysis of somatic mutations in the normal skin of individuals from the UK and Singapore reveals different patterns of clonal mutational landscapes that could contribute to differential risk.

Across multiple cancer types, hotspot mutations in SF3B1 confer selective sensitivity to multiple clinically available PARP inhibitors. This sensitivity is due to reduced levels of CINP specifically in SF3B1-mutant cells, which leads to a loss of the canonical replication stress response after challenge with PARP inhibitors.

Through whole-genome sequencing of single molecules of circulating cell-free DNA, we found that tumor-derived mutations in cancer genomes are associated with regions of late replication timing and other chromatin features. These genome-wide analyses identified altered regional mutation profiles in people with cancer that distinguished them from people without cancer and reflected tumor burden during therapy.

Matched single-cell transcriptomic and epigenomic profiles obtained from human scalp reveal gene regulatory maps of diverse cell types in the hair follicle niche. Integrating these data with existing genome-wide association studies enabled prioritization of cell types, genes, and causal variants implicated in the pathobiology of androgenetic alopecia, eczema, and other complex traits.

How the chromatin states of transposable elements (TEs) are controlled in development and disease is unclear. We present CARGO-BioID, a CRISPR-based proteomic approach to identify TE-associated proteins, and reveal an interplay between RNA N6-methyladenosine (m⁶A) and DNA methylation that is crucial for regulating TE activation and human embryonic stem cell (hESC) fate.

The three-dimensional organization of mammalian chromosomes can regulate transcription. Whether transcription itself influences genome structure has remained a source of debate. Using sensitive genome-wide readouts, two recent studies describe the involvement of transcription on genome architecture by different mechanisms.

Identifying the ways that a study sample is not representative is essential for maximizing the generalizability of findings to the population. A new method proposes discerning non-representativeness in large-scale genetic studies by comparing the genotypes of closely related participants.

Single large-scale mitochondrial DNA deletions cause a spectrum of disease with differing severities and tissue expressivity. Quantification of single-cell deletion levels with multi-modal cellular readouts provides insights into hematopoietic cell fate and disease manifestation.

Cross-ancestry genome-wide association meta-analyses of neuroimaging genetics data from European and East Asian populations identified 339 genetic variant–hippocampal volumetric trait associations (23 new). Further cross-ancestry analyses revealed similar genetic effects on hippocampal volumetric traits between ancestries, with improved fine-mapping precision and predictive accuracy of polygenic scores in the under-represented East Asian population.

Genome-wide association studies (GWAS) of type 2 diabetes have identified few loci connected to muscle biology. A GWAS of post-glucose-challenge measures of insulin has now identified loci related to insulin resistance and GLUT4 regulation in skeletal muscle, illustrating the benefit of studying dynamic glycemic measures.

An extra copy of a chromosome region that includes four genes encoding interferon receptors contributes to immune dysregulation, heart malformations, developmental delays, cognitive deficits and craniofacial abnormalities in a mouse model of Down syndrome.

Meta-analysis of genome-wide association studies of spontaneous coronary artery dissection (SCAD), an important cause of myocardial infarction, identified 11 risk loci that involve genes related to artery integrity and tissue-mediated coagulation. Evidence supports SCAD as a genetically distinct condition from atherosclerotic coronary artery disease.

Two studies describe kinase fusion proteins (KFPs) that regulate the perception and deception of wheat pathogens. These highlight the emergence of KFPs as plant immune regulators and emphasize the importance of crop wild relatives as a reservoir for resistance breeding and global food security.

Tumors develop mechanisms to escape immune destruction. A systematic analysis of large genome sequencing datasets shows that one in four tumors develop genetic immune escape and its prevalence is remarkably similar between primary and metastatic tumors, suggesting that immune escape is an early event during tumor evolution.

Single-cell RNA-sequencing analysis combined with host genetic data for a Japanese population reveals the dysfunction of innate immune cells, particularly non-classical monocytes, in individuals with severe COVID-19, as well as enrichment of host genetic risk factors for severe COVID-19 in monocytes and dendritic cells.

We introduce scEC&T-seq, a new single-cell sequencing method that enables parallel profiling of extrachromosomal circular DNA and mRNAs in single cells. Using scEC&T-seq, we characterized all types of circular DNA elements in single human cancer cells and profiled the intercellular heterogeneity and structural dynamics of cancer-specific extrachromosomal DNA.

Aberrant RNA splicing events resulting from DNA variations are common causes of genetic disorders. Two studies published in Nature Genetics independently describe methods to decipher DNA-variant-associated aberrant splicing using high-throughput RNA sequencing data.

A new method infers huge gene trees and tests the tree branches for phenotypic associations. This improves power to map the effects of rare variants that are missing from genotype arrays and imputation panels.

Liability scores for chronic obstructive pulmonary disease obtained from our deep learning model improve genetic association discovery and risk prediction. We trained our model using full spirograms and noisy medical record labels obtained from self-reporting and hospital diagnostic codes, and demonstrated that the machine-learning-based phenotyping approach can be generalized to diseases that lack expert-defined annotations.