When investigating Mendelian disease using exome or genome sequencing, distinguishing disease-causing genetic variants from the multitude of candidate variants is a complex, multidimensional task. Many prioritization tools and online interpretation resources exist, and professional organizations have offered clinical guidelines for review and return of prioritization results. In this Review, we describe the strengths and weaknesses of widely used computational approaches, explain their roles in the diagnostic and discovery process and discuss how they can inform (and misinform) expert reviewers. We place variant prioritization in the wider context of gene prioritization, burden testing and genotype–phenotype association, and we discuss opportunities and challenges introduced by whole-genome sequencing.

Genetic architecture describes the characteristics of genetic variation that are responsible for heritable phenotypic variability. It depends on the number of genetic variants affecting a trait, their frequencies in the population, the magnitude of their effects and their interactions with each other and the environment. Defining the genetic architecture of a complex trait or disease is central to the scientific and clinical goals of human genetics, which are to understand disease aetiology and aid in disease screening, diagnosis, prognosis and therapy. Recent technological advances have enabled genome-wide association studies and emerging next-generation sequencing studies to begin to decipher the nature of the heritable contribution to traits and disease. Here, we describe the types of genetic architecture that have been observed, how architecture can be measured and why an improved understanding of genetic architecture is central to future advances in the field.

Taxonomic and functional changes to the composition of the gut microbiome have been implicated in multiple human diseases. Recent microbiome genome-wide association studies reveal that variants in many human genes involved in immunity and gut architecture are associated with an altered composition of the gut microbiome. Although many factors can affect the microbial organisms residing in the gut, a number of recent findings support the hypothesis that certain host genetic variants predispose an individual towards microbiome dysbiosis. This condition, in which the normal microbiome population structure is disturbed, is a key feature in disorders of metabolism and immunity.

Exciting new technologies are often self-limiting in their rollout, as access to state-of-the-art instrumentation or the need for years of hands-on experience, for better or worse, ensures slow adoption by the community. CRISPR technology, however, presents the opposite dilemma, where the simplicity of the system enabled the parallel development of many applications, improvements and derivatives, and new users are now presented with an almost paralyzing abundance of choices. This Review intends to guide users through the process of applying CRISPR technology to their biological problems of interest, especially in the context of discovering gene function at scale.

The past several years have witnessed an explosion of successful ancient human genome-sequencing projects, with genomic-scale ancient DNA data sets now available for more than 1,100 ancient human and archaic hominin (for example, Neandertal) individuals. Recent 'evolution in action' analyses have started using these data sets to identify and track the spatiotemporal trajectories of genetic variants associated with human adaptations to novel and changing environments, agricultural lifestyles, and introduced or co-evolving pathogens. Together with evidence of adaptive introgression of genetic variants from archaic hominins to humans and emerging ancient genome data sets for domesticated animals and plants, these studies provide novel insights into human evolution and the evolutionary consequences of human behaviour that go well beyond those that can be obtained from modern genomic data or the fossil and archaeological records alone.

Chromatin, the template for epigenetic regulation, is a highly dynamic entity that is constantly reshaped during early development and differentiation. Epigenetic modification of chromatin provides the necessary plasticity for cells to respond to environmental and positional cues, and enables the maintenance of acquired information without changing the DNA sequence. The mechanisms involve, among others, chemical modifications of chromatin, changes in chromatin constituents and reconfiguration of chromatin interactions and 3D structure. New advances in genome-wide technologies have paved the way towards an integrative view of epigenome dynamics during cell state transitions, and recent findings in embryonic stem cells highlight how the interplay between different epigenetic layers reshapes the transcriptional landscape.

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When investigating Mendelian disease using exome or genome sequencing, distinguishing disease-causing genetic variants from the multitude of candidate variants is a complex, multidimensional task. Many prioritization tools and online interpretation resources exist, and professional organizations have offered clinical guidelines for review and return of prioritization results. In this Review, we describe the strengths and weaknesses of widely used computational approaches, explain their roles in the diagnostic and discovery process and discuss how they can inform (and misinform) expert reviewers. We place variant prioritization in the wider context of gene prioritization, burden testing and genotype–phenotype association, and we discuss opportunities and challenges introduced by whole-genome sequencing.

Genetic architecture describes the characteristics of genetic variation that are responsible for heritable phenotypic variability. It depends on the number of genetic variants affecting a trait, their frequencies in the population, the magnitude of their effects and their interactions with each other and the environment. Defining the genetic architecture of a complex trait or disease is central to the scientific and clinical goals of human genetics, which are to understand disease aetiology and aid in disease screening, diagnosis, prognosis and therapy. Recent technological advances have enabled genome-wide association studies and emerging next-generation sequencing studies to begin to decipher the nature of the heritable contribution to traits and disease. Here, we describe the types of genetic architecture that have been observed, how architecture can be measured and why an improved understanding of genetic architecture is central to future advances in the field.

Taxonomic and functional changes to the composition of the gut microbiome have been implicated in multiple human diseases. Recent microbiome genome-wide association studies reveal that variants in many human genes involved in immunity and gut architecture are associated with an altered composition of the gut microbiome. Although many factors can affect the microbial organisms residing in the gut, a number of recent findings support the hypothesis that certain host genetic variants predispose an individual towards microbiome dysbiosis. This condition, in which the normal microbiome population structure is disturbed, is a key feature in disorders of metabolism and immunity.

Exciting new technologies are often self-limiting in their rollout, as access to state-of-the-art instrumentation or the need for years of hands-on experience, for better or worse, ensures slow adoption by the community. CRISPR technology, however, presents the opposite dilemma, where the simplicity of the system enabled the parallel development of many applications, improvements and derivatives, and new users are now presented with an almost paralyzing abundance of choices. This Review intends to guide users through the process of applying CRISPR technology to their biological problems of interest, especially in the context of discovering gene function at scale.

The past several years have witnessed an explosion of successful ancient human genome-sequencing projects, with genomic-scale ancient DNA data sets now available for more than 1,100 ancient human and archaic hominin (for example, Neandertal) individuals. Recent 'evolution in action' analyses have started using these data sets to identify and track the spatiotemporal trajectories of genetic variants associated with human adaptations to novel and changing environments, agricultural lifestyles, and introduced or co-evolving pathogens. Together with evidence of adaptive introgression of genetic variants from archaic hominins to humans and emerging ancient genome data sets for domesticated animals and plants, these studies provide novel insights into human evolution and the evolutionary consequences of human behaviour that go well beyond those that can be obtained from modern genomic data or the fossil and archaeological records alone.

Chromatin, the template for epigenetic regulation, is a highly dynamic entity that is constantly reshaped during early development and differentiation. Epigenetic modification of chromatin provides the necessary plasticity for cells to respond to environmental and positional cues, and enables the maintenance of acquired information without changing the DNA sequence. The mechanisms involve, among others, chemical modifications of chromatin, changes in chromatin constituents and reconfiguration of chromatin interactions and 3D structure. New advances in genome-wide technologies have paved the way towards an integrative view of epigenome dynamics during cell state transitions, and recent findings in embryonic stem cells highlight how the interplay between different epigenetic layers reshapes the transcriptional landscape.

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