Wild emmer wheat (Triticum turgidum ssp. dicoccoides, BBAA), the wild progenitor of cultivated tetraploid and hexaploid wheats, provides an important reference for investigating centromere reorganization during polyploidization and domestication. Here we generated a near-complete genome assembly of wild emmer wheat, including centromeric regions for all 14 centromeres. Comparative analyses with cultivated tetraploid and hexaploid wheats revealed extensive variation in centromere-associated sequences and centromere-proximal structure, as well as distinct subgenome-associated patterns in the A and B subgenomes. The A subgenome was characterized by positional shifts and sequence turnover of CRW-rich centromere-derived blocks, whereas the B subgenome showed reduced CentT566 satellite abundance accompanied by localized retention or expansion on specific chromosomes. These results provide a high-resolution tetraploid wheat reference and reveal subgenome-associated patterns of centromere remodeling during wheat polyploid evolution. A near-complete genome assembly of wild emmer wheat with resolved centromeric regions across 14 chromosomes highlights subgenome-associated patterns of centromere remodeling during wheat polyploid evolution.
Co-regulation of gene expression profiles across cell types arising from linkage disequilibrium makes it challenging to distinguish causal variants from nearby tagging variants. A study now quantifies the effect of this confounding factor on the direction of the gene–disease association in transcriptome-wide association studies.
Traditional genome-wide association studies have primarily focused on detecting main genotype effects, often overlooking genotype–environment interactions (GxE), which are essential for understanding context-specific genetic effects and refining disease etiology. Here we present fast genotype–environment interaction analysis (fastGxE), a scalable and effective genome-wide GxE method designed to identify genetic variants that interact with environmental factors to influence traits of interest. fastGxE controls for polygenic effects, polygenic interaction effects and noise heterogeneity; it remains robust to the number of environmental factors involved in GxE interactions; and it ensures scalability for genome-wide GxE analysis in large biobank studies, achieving speed improvements of 32.98–126.49 times over existing approaches. We illustrate the benefits of fastGxE through extensive simulations and an in-depth analysis of 32 physical traits and 67 blood biomarkers from the UK Biobank. In real-data applications, fastGxE identifies 7 genomic loci associated with physical traits, including 4 novel ones, and 18 genomic loci associated with blood biomarkers, 12 of which are novel. The new discoveries highlight the dynamic interplay between genetics and the environment, uncovering potentially clinically relevant pathways that could inform personalized interventions and treatment strategies. fastGxE is a powerful and computationally efficient method for genome-wide detection of genotype–environment interactions across multiple environmental factors at biobank scale.
We performed a large-scale genome-wide association study meta-analysis of magnetic resonance imaging-derived liver triglyceride content across 71,488 European-ancestry participants from the UK Biobank, approximately doubling the sample size of previous genome-wide association studies1. We identified 60 independent loci, including 31 not previously reported, and estimated the single nucleotide polymorphism-based heritability of liver triglyceride content at 25%. Integrative fine-mapping and gene-prioritization analyses nominated candidate effector genes for 48 loci. Of the 31 newly identified variants, 14 were validated in meta-analyses of clinically diagnosed metabolic dysfunction-associated steatotic liver disease (42,163 cases and 1,646,254 controls). People in the highest versus lowest decile of a polygenic risk score for liver triglyceride content had 2.71-fold higher odds of cirrhosis and 7.47-fold higher odds of hepatocellular carcinoma. Plasma proteins associated with the liver triglyceride polygenic risk score were enriched for metabolic remodeling and inflammatory pathways, with liver-enriched protein signatures increasing and visceral adipose signatures decreasing with higher genetic risk. Together, these findings refine the genetic architecture of liver triglyceride content, linking polygenic susceptibility to downstream metabolic and inflammatory pathways and providing insights into the genetic basis of steatotic liver disease. Genome-wide association analyses of liver triglyceride content in 71,488 UK Biobank participants identify 60 independent loci and yield polygenic scores correlated with higher risk of cirrhosis and hepatocellular carcinoma.
Patterns of gene and sequence preservation across species provide insight into gene essentiality under natural selection. Here we developed two interspecies constraint metrics across 462 mammalian species: Gene Identity Score of Mammalian Orthologs (GISMO), which quantifies gene loss weighted by evolutionary distance to humans, and GISMO-mis, which measures missense constraint using the ratio of missense to synonymous variation across mammals. Both metrics are strongly correlated with human loss of function, missense and dosage constraint derived from large-scale sequencing studies, yet are largely independent of coding sequence length. GISMO and GISMO-mis identify essential genes missed by existing human-only metrics, particularly short genes. Genes in the most constrained deciles are enriched for rare variant associations in disorders linked to reduced fecundity, including schizophrenia, autism and neurodevelopmental disorders, and show strong enrichment for common variant heritability. These deciles also exhibit reduced copy number variation, consistent with dosage sensitivity. In addition, GISMO improves prioritization of recessive disease genes and captures signatures of homozygous selection across the mammalian tree. Taken together, GISMO and GISMO-mis leverage deep mammalian evolution to provide complementary, length-robust measures of gene essentiality that strengthen disease–gene prioritization and illuminate the selective forces shaping human biology. GISMO and GISMO-mis are new metrics of evolutionary constraint developed across 462 mammalian species. These metrics provide complementary measures of gene essentiality and improve prioritization of human disease genes.
