Nature genetics最新文献

Alfalfa (Medicago sativa L.), a globally important forage crop, is valued for its high nutritional quality and nitrogen-fixing capacity. Here, we present a high-quality pan-genome constructed from 24 diverse alfalfa accessions, encompassing a wide range of genetic backgrounds. This comprehensive analysis identified 433,765 structural variations and characterized 54,002 pan-gene families, highlighting the pivotal role of genomic diversity in alfalfa domestication and adaptation. Key structural variations associated with salt tolerance and quality traits were discovered, with functional analysis implicating genes such as MsMAP65 and MsGA3ox1. Notably, overexpression of MsGA3ox1 led to a reduced stem–leaf ratio and enhanced forage quality. The integration of genomic selection and marker-assisted breeding strategies improved genomic estimated breeding values across multiple traits, offering valuable genomic resources for advancing alfalfa breeding. These findings provide insights into the genetic basis of important agronomic traits and establish a solid foundation for future crop improvement.

There is a sex bias in the incidence and progression of many kidney diseases. To better understand such sexual dimorphism, we integrated data from six platforms, characterizing 76 kidney samples from 68 mice at six developmental and adult time points, creating a molecular atlas of the mouse kidney across the lifespan for both sexes. We show that proximal tubules have the most sex-biased differentially expressed genes emerging after 3 weeks of age and are associated with hormonal regulations. We reveal potential mechanisms involving both direct and indirect regulation by androgens and estrogens. Spatial profiling identifies distinct sex-biased spatial patterns in the cortex and outer stripe of the outer medulla. Additionally, older mice exhibit more aging-related gene alterations in loops of Henle, proximal tubules and collecting ducts in a sex-dependent manner. Our results enhance the understanding of spatially resolved gene expression and hormone regulation underlying kidney sexual dimorphism across the lifespan.

Single-cell CRISPR screens such as Perturb-seq enable transcriptomic profiling of genetic perturbations at scale. However, the data produced by these screens are noisy, and many effects may go undetected. Here we introduce transcriptome-wide analysis of differential expression (TRADE)—a statistical model for the distribution of true differential expression effects that accounts for estimation error appropriately. TRADE estimates the ‘transcriptome-wide impact’, which quantifies the total effect of a perturbation across the transcriptome. Analyzing several large Perturb-seq datasets, we show that many transcriptional effects remain undetected in standard analyses but emerge in aggregate using TRADE. A typical gene perturbation affects an estimated 45 genes, whereas a typical essential gene affects over 500. We find moderate consistency of perturbation effects across cell types, identify perturbations where transcriptional responses vary qualitatively across dosage levels and clarify the relationship between genetic and transcriptomic correlations across neuropsychiatric disorders.

Circular RNA (circRNA) represents a type of RNA molecule characterized by a closed-loop structure that is distinct from linear RNA counterparts. Recent studies have revealed the emerging role of these circular transcripts in gene regulation and disease pathogenesis. However, their low expression levels and high sequence similarity to linear RNAs present substantial challenges for circRNA detection and characterization. Recent advances in long-read and single-cell RNA sequencing technologies, coupled with sophisticated deep learning-based algorithms, have revolutionized the investigation of circRNAs at unprecedented resolution and scale. This Review summarizes recent breakthroughs in circRNA discovery, characterization and functional analysis algorithms. We also discuss the challenges associated with integrating large-scale circRNA sequencing data and explore the potential future development of artificial intelligence (AI)-driven algorithms to unlock the full potential of circRNA research in biomedical applications.

Desmosomes are transmembrane protein complexes that contribute to cell–cell adhesion in epithelia and other tissues. Here, we report the discovery of frequent genetic alterations in the desmosome in human cancers, with the strongest signal seen in cutaneous melanoma, where desmosomes are mutated in more than 70% of cases. In primary but not metastatic melanoma biopsies, the burden of coding mutations in desmosome genes is associated with a strong reduction in desmosome gene expression. Analysis by spatial transcriptomics and protein immunofluorescence suggests that these decreases in expression occur in keratinocytes in the microenvironment rather than in primary melanoma cells. In further support of a microenvironmental origin, we find that desmosome gene knockdown in keratinocytes yields markedly increased proliferation of adjacent melanoma cells in keratinocyte and melanoma cocultures. Similar increases in melanoma proliferation are observed in media preconditioned with desmosome-deficient keratinocytes. Thus, gradual accumulation of desmosome mutations in neighboring cells may prime melanoma cells for neoplastic transformation.

Malus Mill., a genus of temperate perennial trees with great agricultural and ecological value, has diversified through hybridization, polyploidy and environmental adaptation. Limited genomic resources for wild Malus species have hindered the understanding of their evolutionary history and genetic diversity. We sequenced and assembled 30 high-quality Malus genomes, representing 20 diploids and 10 polyploids across major evolutionary lineages and geographical regions. Phylogenomic analyses revealed ancient gene duplications and conversions, while six newly defined genome types, including an ancestral type shared by polyploid species, facilitated the detection of strong signals for extensive introgressions. The graph-based pan-genome captured shared and species-specific structural variations, facilitating the development of a molecular marker for apple scab resistance. Our pipeline for analyzing selective sweep identified a mutation in MdMYB5 having reduced cold and disease resistance during domestication. This study advances Malus genomics, uncovering genetic diversity and evolutionary insights while enhancing breeding for desirable traits.

Genome-wide association studies (GWASs) may help inform the etiology of infertility. Here, we perform GWAS meta-analyses across seven cohorts in up to 42,629 cases and 740,619 controls and identify 25 genetic risk loci for male and female infertility. We additionally identify up to 269 genetic loci associated with follicle-stimulating hormone, luteinizing hormone, estradiol and testosterone through sex-specific GWAS meta-analyses (n = 6,095–246,862). Exome sequencing analyses reveal that women carrying testosterone-lowering rare variants in some genes are at risk of infertility. However, we find no local or genome-wide genetic correlation between female infertility and reproductive hormones. While infertility is genetically correlated with endometriosis and polycystic ovary syndrome, we find limited genetic overlap between infertility and obesity. Finally, we show that the evolutionary persistence of infertility-risk alleles may be explained by directional selection. Taken together, we provide a comprehensive view of the genetic determinants of infertility across multiple diagnostic criteria.

High-risk neuroblastoma, a leading cause of pediatric cancer mortality, exhibits substantial intratumoral heterogeneity, contributing to therapeutic resistance. To understand tumor microenvironment evolution during therapy, we longitudinally profiled 22 patients with high-risk neuroblastoma before and after induction chemotherapy using single-nucleus RNA and ATAC sequencing and whole-genome sequencing. This revealed profound shifts in tumor and immune cell subpopulations after therapy and identified enhancer-driven transcriptional regulators of neuroblastoma neoplastic states. Poor outcome correlated with proliferative and metabolically active neoplastic states, whereas more differentiated neuronal-like states predicted better prognosis. Proportions of mesenchymal neoplastic cells increased after therapy and a high proportion correlated with a poorer chemotherapy response. Macrophages significantly expanded towards pro-angiogenic, immunosuppressive and metabolic phenotypes. We identified paracrine signaling networks and validated the HB-EGF–ERBB4 axis between macrophage and neoplastic subsets, which promoted tumor growth through the induction of ERK signaling. These findings collectively reveal intrinsic and extrinsic regulators of therapy response in high-risk neuroblastoma.