Nature genetics最新文献

Complete datasets of genetic variants are key to biodiversity genomic studies. Long-read sequencing technologies allow the routine assembly of highly contiguous, haplotype-resolved reference genomes. However, even when complete, reference genomes from a single individual may bias downstream analyses and fail to adequately represent genetic diversity within a population or species. Pangenome graphs assembled from aligned collections of high-quality genomes can overcome representation bias by integrating sequence information from multiple genomes from the same population, species or genus into a single reference. Here, we review the available tools and data structures to build, visualize and manipulate pangenome graphs while providing practical examples and discussing their applications in biodiversity and conservation genomics across the tree of life.

Plant pathogens pose a continuous threat to global food production. Recent discoveries in plant immunity research unveiled a unique protein family characterized by an unusual resistance protein structure that combines two kinase domains. This study demonstrates the widespread occurrence of tandem kinase proteins (TKPs) across the plant kingdom. An examination of 104 plant species’ genomes uncovered 2,682 TKPs. The majority (95.6%) of these kinase domains are part of the receptor-like kinase–Pelle family, which is crucial for cell surface responses in plant immunity. Notably, 90% of TKPs comprise dual kinase domains, with over 50% being pseudokinases. Over 56% of these proteins harbor 127 different integrated domains, and over 47% include a transmembrane domain. TKP pseudokinases and/or integrated domains probably serve as decoys, engaging with pathogen effectors to trigger plant immunity. The TKP Atlas we created sheds light on the mechanisms of TKP convergent molecular evolution and potential function.

Ongoing efforts to improve sheep reference genome assemblies still leave many gaps and incomplete regions, resulting in a few common failures and errors in genomic studies. Here, we report a 2.85-Gb gap-free telomere-to-telomere genome of a ram (T2T-sheep1.0), including all autosomes and the X and Y chromosomes. This genome adds 220.05 Mb of previously unresolved regions and 754 new genes to the most updated reference assembly ARS-UI_Ramb_v3.0; it contains four types of repeat units (SatI, SatII, SatIII and CenY) in centromeric regions. T2T-sheep1.0 has a base accuracy of more than 99.999%, corrects several structural errors in previous reference assemblies and improves structural variant detection in repetitive sequences. Alignment of whole-genome short-read sequences of global domestic and wild sheep against T2T-sheep1.0 identifies 2,664,979 new single-nucleotide polymorphisms in previously unresolved regions, which improves the population genetic analyses and detection of selective signals for domestication (for example, ABCC4) and wool fineness (for example, FOXQ1).

Sequence-based machine-learning models trained on genomics data improve genetic variant interpretation by providing functional predictions describing their impact on the cis-regulatory code. However, current tools do not predict RNA-seq expression profiles because of modeling challenges. Here, we introduce Borzoi, a model that learns to predict cell-type-specific and tissue-specific RNA-seq coverage from DNA sequence. Using statistics derived from Borzoi’s predicted coverage, we isolate and accurately score DNA variant effects across multiple layers of regulation, including transcription, splicing and polyadenylation. Evaluated on quantitative trait loci, Borzoi is competitive with and often outperforms state-of-the-art models trained on individual regulatory functions. By applying attribution methods to the derived statistics, we extract cis-regulatory motifs driving RNA expression and post-transcriptional regulation in normal tissues. The wide availability of RNA-seq data across species, conditions and assays profiling specific aspects of regulation emphasizes the potential of this approach to decipher the mapping from DNA sequence to regulatory function.

Segmental duplications (SDs) contribute significantly to human disease, evolution and diversity but have been difficult to resolve at the sequence level. We present a population genetics survey of SDs by analyzing 170 human genome assemblies (from 85 samples representing 38 Africans and 47 non-Africans) in which the majority of autosomal SDs are fully resolved using long-read sequence assembly. Excluding the acrocentric short arms and sex chromosomes, we identify 173.2 Mb of duplicated sequence (47.4 Mb not present in the telomere-to-telomere reference) distinguishing fixed from structurally polymorphic events. We find that intrachromosomal SDs are among the most variable, with rare events mapping near their progenitor sequences. African genomes harbor significantly more intrachromosomal SDs and are more likely to have recently duplicated gene families with higher copy numbers than non-African samples. Comparison to a resource of 563 million full-length isoform sequencing reads identifies 201 novel, potentially protein-coding genes corresponding to these copy number polymorphic SDs.

Single-cell genomics technologies have accelerated our understanding of cell-state heterogeneity in diverse contexts. Although single-cell RNA sequencing identifies rare populations that express specific marker transcript combinations, traditional flow sorting requires cell surface markers with high-fidelity antibodies, limiting our ability to interrogate these populations. In addition, many single-cell studies require the isolation of nuclei from tissue, eliminating the ability to enrich learned rare cell states based on extranuclear protein markers. In the present report, we addressed these limitations by developing Programmable Enrichment via RNA FlowFISH by sequencing (PERFF-seq), a scalable assay that enables scRNA-seq profiling of subpopulations defined by the abundance of specific RNA transcripts. Across immune populations (n = 184,126 cells) and fresh-frozen and formalin-fixed, paraffin-embedded brain tissue (n = 33,145 nuclei), we demonstrated that programmable sorting logic via RNA-based cytometry can isolate rare cell populations and uncover phenotypic heterogeneity via downstream, high-throughput, single-cell genomics analyses.

The advent of single-molecule, long-read sequencing (LRS) technologies by Oxford Nanopore Technologies and Pacific Biosciences has revolutionized genomics, transcriptomics and, more recently, epigenomics research. These technologies offer distinct advantages, including the direct detection of methylated DNA and simultaneous assessment of DNA sequences spanning multiple kilobases along with their modifications at the single-molecule level. This has enabled the development of new assays for analyzing chromatin states and made it possible to integrate data for DNA methylation, chromatin accessibility, transcription factor binding and histone modifications, thereby facilitating comprehensive epigenomic profiling. Owing to recent advancements, alternative, nascent and translating transcripts can be detected using LRS approaches. This Review discusses LRS-based experimental and computational strategies for characterizing chromatin states and highlights their advantages over short-read sequencing methods. Furthermore, we demonstrate how various long-read methods can be integrated to design multi-omics studies to investigate the relationship between chromatin states and transcriptional dynamics.

The mutational landscape of TP53, a tumor suppressor mutated in about half of all cancers, includes over 2,000 known missense mutations. To fully leverage TP53 mutation status for personalized medicine, a thorough understanding of the functional diversity of these mutations is essential. We conducted a deep mutational scan using saturation genome editing with CRISPR-mediated homology-directed repair to engineer 9,225 TP53 variants in cancer cells. This high-resolution approach, covering 94.5% of all cancer-associated TP53 missense mutations, precisely mapped the impact of individual mutations on tumor cell fitness, surpassing previous deep mutational scan studies in distinguishing benign from pathogenic variants. Our results revealed even subtle loss-of-function phenotypes and identified promising mutants for pharmacological reactivation. Moreover, we uncovered the roles of splicing alterations and nonsense-mediated messenger RNA decay in mutation-driven TP53 dysfunction. These findings underscore the power of saturation genome editing in advancing clinical TP53 variant interpretation for genetic counseling and personalized cancer therapy.

Convergent transcription, that is, the collision of sense and antisense transcription, is ubiquitous in mammalian genomes and believed to diminish RNA expression. Recently, antisense transcription downstream of promoters was found to be surprisingly prevalent. However, functional characteristics of affected promoters are poorly investigated. Here we show that convergent transcription marks an unexpected positively co-regulated promoter constellation. By assessing transcriptional dynamic systems, we identified co-regulated constituent promoters connected through a distinct chromatin structure. Within these cis-regulatory domains, transcription factors can regulate both constituting promoters by binding to only one of them. Convergent promoters comprise about a quarter of all active transcript start sites and initiate 5′-overlapping antisense RNAs—an RNA class believed previously to be rare. Visualization of nascent RNA molecules reveals convergent cotranscription at these loci. Together, our results demonstrate that co-regulated convergent promoters substantially expand the cis-regulatory repertoire, reveal limitations of the transcription interference model and call for adjusting the promoter concept.

Emil was born in Poland in the town of Buczacz (now located in Ukraine) on 27 August 1941. He miraculously escaped the Nazi death camps as an infant but lost many family members. He was raised by his adoptive Skamene family in the Czech Republic. He obtained his MD and PhD degrees from Charles University in Prague; he then undertook post-doctoral work at Harvard Medical School in Boston and completed his specialty in allergy and immunology at McGill, where he remained.

Emil was a pioneer of, and internationally recognized for, the study of the host genetic basis of susceptibility to infections. His work rejected the then dominating microorganism-centric view of infectious disease and was a watershed for infectious diseases research. He was inspired by the landmark studies of Lurie and Dannenberg, who from the 1930s onward bred inbred strains of rabbits that were inherently resistant and susceptible to aerosol infection with Mycobacterium tuberculosis. He would often refer to similar work on M. tuberculosis by Wright and Lewis in hamsters and Lynch and Dubos in mice as planting the seeds for his own work¹.