Showing papers in "Nature Reviews Genetics in 2019"
TL;DR: Advances in high-throughput RNA sequencing and circRNA-specific computational tools have driven the development of state-of-the-art approaches for their identification, and novel approaches to functional characterization are emerging.
Abstract: Circular RNAs (circRNAs) are covalently closed, endogenous biomolecules in eukaryotes with tissue-specific and cell-specific expression patterns, whose biogenesis is regulated by specific cis-acting elements and trans-acting factors. Some circRNAs are abundant and evolutionarily conserved, and many circRNAs exert important biological functions by acting as microRNA or protein inhibitors ('sponges'), by regulating protein function or by being translated themselves. Furthermore, circRNAs have been implicated in diseases such as diabetes mellitus, neurological disorders, cardiovascular diseases and cancer. Although the circular nature of these transcripts makes their detection, quantification and functional characterization challenging, recent advances in high-throughput RNA sequencing and circRNA-specific computational tools have driven the development of state-of-the-art approaches for their identification, and novel approaches to functional characterization are emerging.
2,372 citations
TL;DR: This Review comprehensively assess the benefits and limitations of GWAS in human populations and discusses the relevance of performing more GWAS, with a focus on the cardiometabolic field.
Abstract: Genome-wide association studies (GWAS) involve testing genetic variants across the genomes of many individuals to identify genotype–phenotype associations. GWAS have revolutionized the field of complex disease genetics over the past decade, providing numerous compelling associations for human complex traits and diseases. Despite clear successes in identifying novel disease susceptibility genes and biological pathways and in translating these findings into clinical care, GWAS have not been without controversy. Prominent criticisms include concerns that GWAS will eventually implicate the entire genome in disease predisposition and that most association signals reflect variants and genes with no direct biological relevance to disease. In this Review, we comprehensively assess the benefits and limitations of GWAS in human populations and discuss the relevance of performing more GWAS. Despite the success of human genome-wide association studies (GWAS) in associating genetic variants and complex diseases or traits, criticisms of the usefulness of this study design remain. This Review assesses the pros and cons of GWAS, with a focus on the cardiometabolic field.
1,002 citations
TL;DR: Advances in RNA-sequencing technologies and methods over the past decade are discussed and adaptations that are enabling a fuller understanding of RNA biology are outlined, from when and where an RNA is expressed to the structures it adopts.
Abstract: Over the past decade, RNA sequencing (RNA-seq) has become an indispensable tool for transcriptome-wide analysis of differential gene expression and differential splicing of mRNAs. However, as next-generation sequencing technologies have developed, so too has RNA-seq. Now, RNA-seq methods are available for studying many different aspects of RNA biology, including single-cell gene expression, translation (the translatome) and RNA structure (the structurome). Exciting new applications are being explored, such as spatial transcriptomics (spatialomics). Together with new long-read and direct RNA-seq technologies and better computational tools for data analysis, innovations in RNA-seq are contributing to a fuller understanding of RNA biology, from questions such as when and where transcription occurs to the folding and intermolecular interactions that govern RNA function.
947 citations
TL;DR: The goal is to illustrate how chromatin accessibility defines regulatory elements within the genome and how these epigenetic features are dynamically established to control gene expression.
Abstract: Physical access to DNA is a highly dynamic property of chromatin that plays an essential role in establishing and maintaining cellular identity. The organization of accessible chromatin across the genome reflects a network of permissible physical interactions through which enhancers, promoters, insulators and chromatin-binding factors cooperatively regulate gene expression. This landscape of accessibility changes dynamically in response to both external stimuli and developmental cues, and emerging evidence suggests that homeostatic maintenance of accessibility is itself dynamically regulated through a competitive interplay between chromatin-binding factors and nucleosomes. In this Review, we examine how the accessible genome is measured and explore the role of transcription factors in initiating accessibility remodelling; our goal is to illustrate how chromatin accessibility defines regulatory elements within the genome and how these epigenetic features are dynamically established to control gene expression.
926 citations
TL;DR: Diverse approaches for integrative single-cell analysis are discussed, including experimental methods for profiling multiple omics types from the same cells, analytical approaches for extracting additional layers of information directly from scRNA-seq data and computational integration of omics data collected across different cell samples.
Abstract: The recent maturation of single-cell RNA sequencing (scRNA-seq) technologies has coincided with transformative new methods to profile genetic, epigenetic, spatial, proteomic and lineage information in individual cells. This provides unique opportunities, alongside computational challenges, for integrative methods that can jointly learn across multiple types of data. Integrated analysis can discover relationships across cellular modalities, learn a holistic representation of the cell state, and enable the pooling of data sets produced across individuals and technologies. In this Review, we discuss the recent advances in the collection and integration of different data types at single-cell resolution with a focus on the integration of gene expression data with other types of single-cell measurement.
892 citations
TL;DR: The potential of liquid biopsies is highlighted by studies that show they can track the evolutionary dynamics and heterogeneity of tumours and can detect very early emergence of therapy resistance, residual disease and recurrence, but their analytical validity and clinical utility must be rigorously demonstrated before this potential can be realized.
Abstract: Precision oncology seeks to leverage molecular information about cancer to improve patient outcomes. Tissue biopsy samples are widely used to characterize tumours but are limited by constraints on sampling frequency and their incomplete representation of the entire tumour bulk. Now, attention is turning to minimally invasive liquid biopsies, which enable analysis of tumour components (including circulating tumour cells and circulating tumour DNA) in bodily fluids such as blood. The potential of liquid biopsies is highlighted by studies that show they can track the evolutionary dynamics and heterogeneity of tumours and can detect very early emergence of therapy resistance, residual disease and recurrence. However, the analytical validity and clinical utility of liquid biopsies must be rigorously demonstrated before this potential can be realized.
809 citations
TL;DR: This Review discusses the multiple algorithmic options for clustering scRNA-seq data, including various technical, biological and computational considerations.
Abstract: Single-cell RNA sequencing (scRNA-seq) allows researchers to collect large catalogues detailing the transcriptomes of individual cells. Unsupervised clustering is of central importance for the analysis of these data, as it is used to identify putative cell types. However, there are many challenges involved. We discuss why clustering is a challenging problem from a computational point of view and what aspects of the data make it challenging. We also consider the difficulties related to the biological interpretation and annotation of the identified clusters.
741 citations
TL;DR: The authors describe the latest understanding of piRNA biogenesis and functions across diverse species, highlighting how, despite the universal importance of transposon control, different species have evolved intriguingly distinct mechanistic routes to achieve this.
Abstract: In animals, PIWI-interacting RNAs (piRNAs) of 21–35 nucleotides in length silence transposable elements, regulate gene expression and fight viral infection. piRNAs guide PIWI proteins to cleave target RNA, promote heterochromatin assembly and methylate DNA. The architecture of the piRNA pathway allows it both to provide adaptive, sequence-based immunity to rapidly evolving viruses and transposons and to regulate conserved host genes. piRNAs silence transposons in the germ line of most animals, whereas somatic piRNA functions have been lost, gained and lost again across evolution. Moreover, most piRNA pathway proteins are deeply conserved, but different animals employ remarkably divergent strategies to produce piRNA precursor transcripts. Here, we discuss how a common piRNA pathway allows animals to recognize diverse targets, ranging from selfish genetic elements to genes essential for gametogenesis. PIWI-interacting RNAs (piRNAs) have numerous crucial biological roles, particularly transposon silencing in the germ line. In this Review, the authors describe our latest understanding of piRNA biogenesis and functions across diverse species, highlighting how, despite the universal importance of transposon control, different species have evolved intriguingly distinct mechanistic routes to achieve this.
686 citations
TL;DR: This Review describes different deep learning techniques and how they can be applied to extract biologically relevant information from large, complex genomic data sets.
Abstract: As a data-driven science, genomics largely utilizes machine learning to capture dependencies in data and derive novel biological hypotheses. However, the ability to extract new insights from the exponentially increasing volume of genomics data requires more expressive machine learning models. By effectively leveraging large data sets, deep learning has transformed fields such as computer vision and natural language processing. Now, it is becoming the method of choice for many genomics modelling tasks, including predicting the impact of genetic variation on gene regulatory mechanisms such as DNA accessibility and splicing. This Review describes different deep learning techniques and how they can be applied to extract biologically relevant information from large, complex genomic data sets.
685 citations
TL;DR: The latest understanding of long-range enhancer–promoter crosstalk is discussed, including target-gene specificity, interaction dynamics, protein and RNA architects of interactions, roles of 3D genome organization and the pathological consequences of regulatory rewiring.
Abstract: Spatiotemporal gene expression programmes are orchestrated by transcriptional enhancers, which are key regulatory DNA elements that engage in physical contacts with their target-gene promoters, often bridging considerable genomic distances. Recent progress in genomics, genome editing and microscopy methodologies have enabled the genome-wide mapping of enhancer-promoter contacts and their functional dissection. In this Review, we discuss novel concepts on how enhancer-promoter interactions are established and maintained, how the 3D architecture of mammalian genomes both facilitates and constrains enhancer-promoter contacts, and the role they play in gene expression control during normal development and disease.
646 citations
TL;DR: The cGAS–STING pathway forms a major DNA-sensing mechanism in mammalian cells and emerging evidence of its role in monogenic inflammatory diseases and cancer and new therapeutic opportunities is highlighted.
Abstract: The detection of pathogens through nucleic acid sensors is a defining principle of innate immunity. RNA-sensing and DNA-sensing receptors sample subcellular compartments for foreign nucleic acids and, upon recognition, trigger immune signalling pathways for host defence. Over the past decade, our understanding of how the recognition of nucleic acids is coupled to immune gene expression has advanced considerably, particularly for the DNA-sensing receptor cyclic GMP-AMP synthase (cGAS) and its downstream signalling effector stimulator of interferon genes (STING), as well as the molecular components and regulation of this pathway. Moreover, the ability of self-DNA to engage cGAS has emerged as an important mechanism fuelling the development of inflammation and implicating the cGAS-STING pathway in human inflammatory diseases and cancer. This detailed mechanistic and biological understanding is paving the way for the development and clinical application of pharmacological agonists and antagonists in the treatment of chronic inflammation and cancer.
TL;DR: This Timeline article highlights the key advances that have expanded the views on the mechanistic underpinnings of telomeres and telomerase and their roles in ageing and disease.
Abstract: Many recent advances have emerged in the telomere and telomerase fields. This Timeline article highlights the key advances that have expanded our views on the mechanistic underpinnings of telomeres and telomerase and their roles in ageing and disease. Three decades ago, the classic view was that telomeres protected the natural ends of linear chromosomes and that telomerase was a specific telomere-terminal transferase necessary for the replication of chromosome ends in single-celled organisms. While this concept is still correct, many diverse fields associated with telomeres and telomerase have substantially matured. These areas include the discovery of most of the key molecular components of telomerase, implications for limits to cellular replication, identification and characterization of human genetic disorders that result in premature telomere shortening, the concept that inhibiting telomerase might be a successful therapeutic strategy and roles for telomeres in regulating gene expression. We discuss progress in these areas and conclude with challenges and unanswered questions in the field.
TL;DR: An overview of the theoretical models of tumour evolution is provided and what to consider when inferring evolutionary dynamics from genomic data is discussed.
Abstract: To a large extent, cancer conforms to evolutionary rules defined by the rates at which clones mutate, adapt and grow. Next-generation sequencing has provided a snapshot of the genetic landscape of most cancer types, and cancer genomics approaches are driving new insights into cancer evolutionary patterns in time and space. In contrast to species evolution, cancer is a particular case owing to the vast size of tumour cell populations, chromosomal instability and its potential for phenotypic plasticity. Nevertheless, an evolutionary framework is a powerful aid to understand cancer progression and therapy failure. Indeed, such a framework could be applied to predict individual tumour behaviour and support treatment strategies.
TL;DR: This Review summarizes the progress in iPSC-based disease modelling over the past decade, with a focus on 3D organoid systems and chimeric models being exploited for new therapeutic approaches.
Abstract: The derivation of induced pluripotent stem cells (iPSCs) over a decade ago sparked widespread enthusiasm for the development of new models of human disease, enhanced platforms for drug discovery and more widespread use of autologous cell-based therapy. Early studies using directed differentiation of iPSCs frequently uncovered cell-level phenotypes in monogenic diseases, but translation to tissue-level and organ-level diseases has required development of more complex, 3D, multicellular systems. Organoids and human-rodent chimaeras more accurately mirror the diverse cellular ecosystems of complex tissues and are being applied to iPSC disease models to recapitulate the pathobiology of a broad spectrum of human maladies, including infectious diseases, genetic disorders and cancer.
TL;DR: Beyond helping to understand disease biology, clinical epigenetics is being incorporated into patient management in oncology, as well as being explored for clinical applicability for other human pathologies such as neurological and infectious diseases and immune system disorders.
Abstract: Biomarker discovery and validation are necessary for improving the prediction of clinical outcomes and patient monitoring. Despite considerable interest in biomarker discovery and development, improvements in the range and quality of biomarkers are still needed. The main challenge is how to integrate preclinical data to obtain a reliable biomarker that can be measured with acceptable costs in routine clinical practice. Epigenetic alterations are already being incorporated as valuable candidates in the biomarker field. Furthermore, their reversible nature offers a promising opportunity to ameliorate disease symptoms by using epigenetic-based therapy. Thus, beyond helping to understand disease biology, clinical epigenetics is being incorporated into patient management in oncology, as well as being explored for clinical applicability for other human pathologies such as neurological and infectious diseases and immune system disorders.
TL;DR: Focusing on sequence-based discovery of antibiotic resistance genes, this Review discusses computational strategies and resources for resistance gene identification in genomic and metagenomic samples, including recent deep-learning approaches.
Abstract: Antimicrobial resistance extracts high morbidity, mortality and economic costs yearly by rendering bacteria immune to antibiotics. Identifying and understanding antimicrobial resistance are imperative for clinical practice to treat resistant infections and for public health efforts to limit the spread of resistance. Technologies such as next-generation sequencing are expanding our abilities to detect and study antimicrobial resistance. This Review provides a detailed overview of antimicrobial resistance identification and characterization methods, from traditional antimicrobial susceptibility testing to recent deep-learning methods. We focus on sequencing-based resistance discovery and discuss tools and databases used in antimicrobial resistance studies.
TL;DR: How DNA can be adopted as a storage medium for custom data, as a potential future complement to current data storage media such as computer hard disks, optical disks and tape is discussed.
Abstract: Molecular data storage is an attractive alternative for dense and durable information storage, which is sorely needed to deal with the growing gap between information production and the ability to store data. DNA is a clear example of effective archival data storage in molecular form. In this Review, we provide an overview of the process, the state of the art in this area and challenges for mainstream adoption. We also survey the field of in vivo molecular memory systems that record and store information within the DNA of living cells, which, together with in vitro DNA data storage, lie at the growing intersection of computer systems and biotechnology.
TL;DR: The maternal-to-zygotic transition (MZT) is the process by which the transcriptionally silent embryonic genome is gradually activated, and recent work indicates that transcriptional activators have an important role.
Abstract: Following fertilization, the two specified gametes must unite to create an entirely new organism. The genome is initially transcriptionally quiescent, allowing the zygote to be reprogrammed into a totipotent state. Gradually, the genome is activated through a process known as the maternal-to-zygotic transition, which enables zygotic gene products to replace the maternal supply that initiated development. This essential transition has been broadly characterized through decades of research in several model organisms. However, we still lack a full mechanistic understanding of how genome activation is executed and how this activation relates to the reprogramming of the zygotic chromatin architecture. Recent work highlights the central role of transcriptional activators and suggests that these factors may coordinate transcriptional activation with other developmental changes.
TL;DR: Current evidence implicating DNA modifications and DNA-modifying enzymes in TE regulation across different species is discussed, and DNA methylation dynamics play a central role in the multilayered epigenetic mechanisms regulating TEs.
Abstract: Maintenance of genome stability requires control over the expression of transposable elements (TEs), whose activity can have substantial deleterious effects on the host. Chemical modification of DNA is a commonly used strategy to achieve this, and it has long been argued that the emergence of 5-methylcytosine (5mC) in many species was driven by the requirement to silence TEs. Potential roles in TE regulation have also been suggested for other DNA modifications, such as N6-methyladenine and oxidation derivatives of 5mC, although the underlying mechanistic relationships are poorly understood. Here, we discuss current evidence implicating DNA modifications and DNA-modifying enzymes in TE regulation across different species.
TL;DR: Interactions between the genome, the epigenome and the environment in germ cells and early embryos have an impact on developmental outcomes and on the heritability of imprinting disorders.
Abstract: Genomic imprinting, the monoallelic and parent-of-origin-dependent expression of a subset of genes, is required for normal development, and its disruption leads to human disease. Imprinting defects can involve isolated or multilocus epigenetic changes that may have no evident genetic cause, or imprinting disruption can be traced back to alterations of cis-acting elements or trans-acting factors that control the establishment, maintenance and erasure of germline epigenetic imprints. Recent insights into the dynamics of the epigenome, including the effect of environmental factors, suggest that the developmental outcomes and heritability of imprinting disorders are influenced by interactions between the genome, the epigenome and the environment in germ cells and early embryos.
TL;DR: The experimental and computational methods that have enabled the global mapping of mRNA and of long non-coding RNA 3ʹ ends, quantification of the resulting isoforms and the discovery of regulators of alternative cleavage and polyadenylation (APA) are reviewed.
Abstract: Most human genes have multiple sites at which RNA 3' end cleavage and polyadenylation can occur, enabling the expression of distinct transcript isoforms under different conditions. Novel methods to sequence RNA 3' ends have generated comprehensive catalogues of polyadenylation (poly(A)) sites; their analysis using innovative computational methods has revealed how poly(A) site choice is regulated by core RNA 3' end processing factors, such as cleavage factor I and cleavage and polyadenylation specificity factor, as well as by other RNA-binding proteins, particularly splicing factors. Here, we review the experimental and computational methods that have enabled the global mapping of mRNA and of long non-coding RNA 3' ends, quantification of the resulting isoforms and the discovery of regulators of alternative cleavage and polyadenylation (APA). We highlight the different types of APA-derived isoforms and their functional differences, and illustrate how APA contributes to human diseases, including cancer and haematological, immunological and neurological diseases.
TL;DR: Improved methodologies have enabled genetic correlations to be estimated for almost any trait pair, which can improve the understanding of the shared biology and causal relationships between traits.
Abstract: The genetic correlation describes the genetic relationship between two traits and can contribute to a better understanding of the shared biological pathways and/or the causality relationships between them. The rarity of large family cohorts with recorded instances of two traits, particularly disease traits, has made it difficult to estimate genetic correlations using traditional epidemiological approaches. However, advances in genomic methodologies, such as genome-wide association studies, and widespread sharing of data now allow genetic correlations to be estimated for virtually any trait pair. Here, we review the definition, estimation, interpretation and uses of genetic correlations, with a focus on applications to human disease.
TL;DR: Genomic information of increasing complexity (including genomic, epigenomic, transcriptomic and microbiome data), combined with technological advances for its cost-effective collection and use, will make a major contribution to tackling the looming food crisis.
Abstract: The world demand for animal-based food products is anticipated to increase by 70% by 2050. Meeting this demand in a way that has a minimal impact on the environment will require the implementation of advanced technologies, and methods to improve the genetic quality of livestock are expected to play a large part. Over the past 10 years, genomic selection has been introduced in several major livestock species and has more than doubled genetic progress in some. However, additional improvements are required. Genomic information of increasing complexity (including genomic, epigenomic, transcriptomic and microbiome data), combined with technological advances for its cost-effective collection and use, will make a major contribution.
TL;DR: Recent experimental progress in areas as different as the evolution of drug resistance in cancer cells and the rewiring of transcriptional regulation circuits in vertebrates is reviewed, revealing the importance of multiple genetic and non-genetic mechanisms to generate phenotypic diversity, robustness in genetic systems, and adaptive landscape topography.
Abstract: Evolvability is the ability of a biological system to produce phenotypic variation that is both heritable and adaptive. It has long been the subject of anecdotal observations and theoretical work. In recent years, however, the molecular causes of evolvability have been an increasing focus of experimental work. Here, we review recent experimental progress in areas as different as the evolution of drug resistance in cancer cells and the rewiring of transcriptional regulation circuits in vertebrates. This research reveals the importance of three major themes: multiple genetic and non-genetic mechanisms to generate phenotypic diversity, robustness in genetic systems, and adaptive landscape topography. We also discuss the mounting evidence that evolvability can evolve and the question of whether it evolves adaptively.
TL;DR: Current understanding of the molecular, genetic and epigenetic regulation of normal placentation is summarized, largely based on insights from the mouse model, and the new opportunities provided by recent successes in deriving human trophoblast stem cells are outlined.
Abstract: The importance of the placenta in supporting mammalian development has long been recognized, but our knowledge of the molecular, genetic and epigenetic requirements that underpin normal placentation has remained remarkably under-appreciated. Both the in vivo mouse model and in vitro-derived murine trophoblast stem cells have been invaluable research tools for gaining insights into these aspects of placental development and function, with recent studies starting to reshape our view of how a unique epigenetic environment contributes to trophoblast differentiation and placenta formation. These advances, together with recent successes in deriving human trophoblast stem cells, open up new and exciting prospects in basic and clinical settings that will help deepen our understanding of placental development and associated disorders of pregnancy.
TL;DR: Recent insights into the genetic models and mechanisms that lead to sex differences in complex traits are discussed, including genomic evidence for sex-dependent genetic architecture, models and molecular mechanisms of sexually differentiated phenotypes and implications for health care.
Abstract: Nearly all human complex traits and disease phenotypes exhibit some degree of sex differences, including differences in prevalence, age of onset, severity or disease progression. Until recently, the underlying genetic mechanisms of such sex differences have been largely unexplored. Advances in genomic technologies and analytical approaches are now enabling a deeper investigation into the effect of sex on human health traits. In this Review, we discuss recent insights into the genetic models and mechanisms that lead to sex differences in complex traits. This knowledge is critical for developing deeper insight into the fundamental biology of sex differences and disease processes, thus facilitating precision medicine.
TL;DR: Two new spatial transcriptomics techniques published in Nature and Science bring an important step closer to the goal of achieving transcriptome-wide data at single-cell resolution.
Abstract: Two new spatial transcriptomics techniques published in Nature and Science bring us an important step closer to the goal of achieving transcriptome-wide data at single-cell resolution.
TL;DR: The many ways human retrotransposons contribute to genome function, their dysregulation in diseases including cancer and how they affect genetic disease are reviewed.
Abstract: Transposable elements are abundant in the human genome, and great strides have been made in pinpointing variations in these repetitive sequences using whole-genome sequencing. Now, the focus is shifting to understanding their expression and regulation, and the functional consequences of their insertion and retention in the genome over time. Whereas transposable element insertions have been known to cause human genetic disease since the 1980s, the scope of their contributions to heritable phenotypes is now starting to be uncovered. Here, we review the many ways human retrotransposons contribute to genome function, their dysregulation in diseases including cancer and how they affect genetic disease.
TL;DR: The value of examining diverse populations to better understand genetic contributors to disease risk and trait variation is considered.
Abstract: Risk of disease is multifactorial and can be shaped by socio-economic, demographic, cultural, environmental and genetic factors. Our understanding of the genetic determinants of disease risk has greatly advanced with the advent of genome-wide association studies (GWAS), which detect associations between genetic variants and complex traits or diseases by comparing populations of cases and controls. However, much of this discovery has occurred through GWAS of individuals of European ancestry, with limited representation of other populations, including from Africa, The Americas, Asia and Oceania. Population demography, genetic drift and adaptation to environments over thousands of years have led globally to the diversification of populations. This global genomic diversity can provide new opportunities for discovery and translation into therapies, as well as a better understanding of population disease risk. Large-scale multi-ethnic and representative biobanks and population health resources provide unprecedented opportunities to understand the genetic determinants of disease on a global scale.
TL;DR: The main methods of DNA nanostructure assembly are reviewed, recent advances in building increasingly complex molecular structures are described and strategies for creating machine-like nanostructures that can be actuated and move are discussed.
Abstract: In nature, DNA molecules carry the hereditary information. But DNA has physical and chemical properties that make it attractive for uses beyond heredity. In this Review, we discuss the potential of DNA for creating machines that are both encoded by and built from DNA molecules. We review the main methods of DNA nanostructure assembly, describe recent advances in building increasingly complex molecular structures and discuss strategies for creating machine-like nanostructures that can be actuated and move. We highlight opportunities for applications of custom DNA nanostructures as scientific tools to address challenges across biology, chemistry and engineering.