Annual review of genomics and human genetics最新文献

Genetic data contain a record of our evolutionary history. The availability of large-scale datasets of human populations from various geographic areas and timescales, coupled with advances in the computational methods to analyze these data, has transformed our ability to use genetic data to learn about our evolutionary past. Here, we review some of the widely used statistical methods to explore and characterize population relationships and history using genomic data. We describe the intuition behind commonly used approaches, their interpretation, and important limitations. For illustration, we apply some of these techniques to genome-wide autosomal data from 929 individuals representing 53 worldwide populations that are part of the Human Genome Diversity Project. Finally, we discuss the new frontiers in genomic methods to learn about population history. In sum, this review highlights the power (and limitations) of DNA to infer features of human evolutionary history, complementing the knowledge gleaned from other disciplines, such as archaeology, anthropology, and linguistics.

The Human Cell Atlas (HCA) is striving to build an open community that is inclusive of all researchers adhering to its principles and as open as possible with respect to data access and use. However, open data sharing can pose certain challenges. For instance, being a global initiative, the HCA must contend with a patchwork of local and regional privacy rules. A notable example is the implementation of the European Union General Data Protection Regulation (GDPR), which caused some concern in the biomedical and genomic data-sharing community. We examine how the HCA's large, international group of researchers is investing tremendous efforts into ensuring appropriate sharing of data. We describe the HCA's objectives and governance, how it defines open data sharing, and ethico-legal challenges encountered early in its development; in particular, we describe the challenges prompted by the GDPR. Finally, we broaden the discussion to address tools and strategies that can be used to address ethical data governance.

DECIPHER (Database of Genomic Variation and Phenotype in Humans Using Ensembl Resources) shares candidate diagnostic variants and phenotypic data from patients with genetic disorders to facilitate research and improve the diagnosis, management, and therapy of rare diseases. The platform sits at the boundary between genomic research and the clinical community. DECIPHER aims to ensure that the most up-to-date data are made rapidly available within its interpretation interfaces to improve clinical care. Newly integrated cardiac case-control data that provide evidence of gene-disease associations and inform variant interpretation exemplify this mission. New research resources are presented in a format optimized for use by a broad range of professionals supporting the delivery of genomic medicine. The interfaces within DECIPHER integrate and contextualize variant and phenotypic data, helping to determine a robust clinico-molecular diagnosis for rare-disease patients, which combines both variant classification and clinical fit. DECIPHER supports discovery research, connecting individuals within the rare-disease community to pursue hypothesis-driven research.

The p-arms of the five human acrocentric chromosomes bear nucleolar organizer regions (NORs) comprising ribosomal gene (rDNA) repeats that are organized in a homogeneous tandem array and transcribed in a telomere-to-centromere direction. Precursor ribosomal RNA transcripts are processed and assembled into ribosomal subunits, the nucleolus being the physical manifestation of this process. I review current understanding of nucleolar chromosome biology and describe current exploration into a role for the NOR chromosomal context. Full DNA sequences for acrocentric p-arms are now emerging, aided by the current revolution in long-read sequencing and genome assembly. Acrocentric p-arms vary from 10.1 to 16.7 Mb, accounting for ∼2.2% of the genome. Bordering rDNA arrays, distal junctions, and proximal junctions are shared among the p-arms, with distal junctions showing evidence of functionality. The remaining p-arm sequences comprise multiple satellite DNA classes and segmental duplications that facilitate recombination between heterologous chromosomes, which is likely also involved in Robertsonian translocations.

Recent advancements in single-cell technologies have enabled expression quantitative trait locus (eQTL) analysis across many individuals at single-cell resolution. Compared with bulk RNA sequencing, which averages gene expression across cell types and cell states, single-cell assays capture the transcriptional states of individual cells, including fine-grained, transient, and difficult-to-isolate populations at unprecedented scale and resolution. Single-cell eQTL (sc-eQTL) mapping can identify context-dependent eQTLs that vary with cell states, including some that colocalize with disease variants identified in genome-wide association studies. By uncovering the precise contexts in which these eQTLs act, single-cell approaches can unveil previously hidden regulatory effects and pinpoint important cell states underlying molecular mechanisms of disease. Here, we present an overview of recently deployed experimental designs in sc-eQTL studies. In the process, we consider the influence of study design choices such as cohort, cell states, and ex vivo perturbations. We then discuss current methodologies, modeling approaches, and technical challenges as well as future opportunities and applications.

In meiosis, homologous chromosome synapsis is mediated by a supramolecular protein structure, the synaptonemal complex (SC), that assembles between homologous chromosome axes. The mammalian SC comprises at least eight largely coiled-coil proteins that interact and self-assemble to generate a long, zipper-like structure that holds homologous chromosomes in close proximity and promotes the formation of genetic crossovers and accurate meiotic chromosome segregation. In recent years, numerous mutations in human SC genes have been associated with different types of male and female infertility. Here, we integrate structural information on the human SC with mouse and human genetics to describe the molecular mechanisms by which SC mutations can result in human infertility. We outline certain themes in which different SC proteins are susceptible to different types of disease mutation and how genetic variants with seemingly minor effects on SC proteins may act as dominant-negative mutations in which the heterozygous state is pathogenic.

The transforming growth factor β (TGF-β) and bone morphogenetic protein (BMP) signaling pathways play a pivotal role in bone development and skeletal health. More than 30 different types of skeletal dysplasia are now known to be caused by pathogenic variants in genes that belong to the TGF-β superfamily and/or regulate TGF-β/BMP bioavailability. This review describes the latest advances in skeletal dysplasia that is due to impaired TGF-β/BMP signaling and results in short stature (acromelic dysplasia and cardiospondylocarpofacial syndrome) or tall stature (Marfan syndrome). We thoroughly describe the clinical features of the patients, the underlying genetic findings, and the pathomolecular mechanisms leading to disease, which have been investigated mainly using patient-derived skin fibroblasts and mouse models. Although no pharmacological treatment is yet available for skeletal dysplasia due to impaired TGF-β/BMP signaling, in recent years advances in the use of drugs targeting TGF-β have been made, and we also discuss these advances.

Sickle cell disease (SCD) is a monogenic blood disease caused by a point mutation in the gene coding for β-globin. The abnormal hemoglobin [sickle hemoglobin (HbS)] polymerizes under low-oxygen conditions and causes red blood cells to sickle. The clinical presentation varies from very severe (with acute pain, chronic pain, and early mortality) to normal (few complications and a normal life span). The variability of SCD might be due (in part) to various genetic modulators. First, we review the main genetic factors, polymorphisms, and modifier genes that influence the expression of globin or otherwise modulate the severity of SCD. Considering SCD as a complex, multifactorial disorder is important for the development of appropriate pharmacological and genetic treatments. Second, we review the characteristics, advantages, and disadvantages of the latest advances in gene therapy for SCD, from lentiviral-vector-based approaches to gene-editing strategies.

Genome sequencing is increasingly used in research and integrated into clinical care. In the research domain, large-scale analyses, including whole genome sequencing with variant interpretation and curation, virtually guarantee identification of variants that are pathogenic or likely pathogenic and actionable. Multiple guidelines recommend that findings associated with actionable conditions be offered to research participants in order to demonstrate respect for autonomy, reciprocity, and participant interests in health and privacy. Some recommendations go further and support offering a wider range of findings, including those that are not immediately actionable. In addition, entities covered by the US Health Insurance Portability and Accountability Act (HIPAA) may be required to provide a participant's raw genomic data on request. Despite these widely endorsed guidelines and requirements, the implementation of return of genomic results and data by researchers remains uneven. This article analyzes the ethical and legal foundations for researcher duties to offer adult participants their interpreted results and raw data as the new normal in genomic research.

Continued advances in precision medicine rely on the widespread sharing of data that relate human genetic variation to disease. However, data sharing is severely limited by legal, regulatory, and ethical restrictions that safeguard patient privacy. Federated analysis addresses this problem by transferring the code to the data-providing the technical and legal capability to analyze the data within their secure home environment rather than transferring the data to another institution for analysis. This allows researchers to gain new insights from data that cannot be moved, while respecting patient privacy and the data stewards' legal obligations. Because federated analysis is a technical solution to the legal challenges inherent in data sharing, the technology and policy implications must be evaluated together. Here, we summarize the technical approaches to federated analysis and provide a legal analysis of their policy implications.