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Pseudogenes are defined as regions of the genome that contain defective copies of genes. They exist across almost all forms of life, and in mammalian genomes are annotated in similar numbers to recognized protein-coding genes. Although often presumed to lack function, growing numbers of pseudogenes are being found to play important biological roles. In consideration of their evolutionary origins and inherent limitations in genome annotation practices, we posit that pseudogenes have been classified on a scientifically unsubstantiated basis. We reflect that a broad misunderstanding of pseudogenes, perpetuated in part by the pejorative inference of the 'pseudogene' label, has led to their frequent dismissal from functional assessment and exclusion from genomic analyses. With the advent of technologies that simplify the study of pseudogenes, we propose that an objective reassessment of these genomic elements will reveal valuable insights into genome function and evolution.

Ancient genomes can inform our understanding of the history of human adaptation through the direct tracking of changes in genetic variant frequency across different geographical locations and time periods. The authors review recent ancient DNA analyses of human, archaic hominin, pathogen, and domesticated animal and plant genomes, as well as the insights gained regarding past human evolution and behaviour. 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.

Transposable elements (TEs) are a prolific source of tightly regulated, biochemically active non-coding elements, such as transcription factor binding sites and non-coding RNAs. A wealth of recent studies reinvigorates the idea that these elements are pervasively co-opted for the regulation of host genes. We argue that the inherent genetic properties of TEs and conflicting relationships with their hosts facilitate their recruitment for regulatory functions in diverse genomes. We review recent findings supporting the long-standing hypothesis that the waves of TE invasions endured by organisms for eons have catalyzed the evolution of gene regulatory networks. We also discuss the challenges of dissecting and interpreting the phenotypic impact of regulatory activities encoded by TEs in health and disease.

Cell types are the basic building blocks of multicellular organisms and are extensively diversified in animals. Despite recent advances in characterizing cell types, classification schemes remain ambiguous. We propose an evolutionary definition of a cell type that allows cell types to be delineated and compared within and between species. Key to cell type identity are evolutionary changes in the 'core regulatory complex' (CoRC) of transcription factors, that make emergent sister cell types distinct, enable their independent evolution and regulate cell type-specific traits termed apomeres. We discuss the distinction between developmental and evolutionary lineages, and present a roadmap for future research.

In this paper, the authors present sequence data from ancient mammoth specimens, including samples more than 1 million years old. The sequences provide insights into mammoth evolution and reveal that distinct mammoth lineages were present in eastern Siberia during the Early Pleistocene.

The recent increase in genomic data is revealing an unexpected perspective of gene loss as a pervasive source of genetic variation that can cause adaptive phenotypic diversity. This novel perspective of gene loss is raising new fundamental questions. How relevant has gene loss been in the divergence of phyla? How do genes change from being essential to dispensable and finally to being lost? Is gene loss mostly neutral, or can it be an effective way of adaptation? These questions are addressed, and insights are discussed from genomic studies of gene loss in populations and their relevance in evolutionary biology and biomedicine.

Differentiated sex chromosomes in mammals and other vertebrates evolved independently but in strikingly similar ways. Vertebrates with differentiated sex chromosomes share the problems of the unequal expression of the genes borne on sex chromosomes, both between the sexes and with respect to autosomes. Dosage compensation of genes on sex chromosomes is surprisingly variable - and can even be absent - in different vertebrate groups. Systems that compensate for different gene dosages include a wide range of global, regional and gene-by-gene processes that differ in their extent and their molecular mechanisms. However, many elements of these control systems are similar across distant phylogenetic divisions and show parallels to other gene silencing systems. These dosage systems cannot be identical by descent but were probably constructed from elements of ancient silencing mechanisms that are ubiquitous among vertebrates and shared throughout eukaryotes.

Horizontal gene transfer (HGT) is the sharing of genetic material between organisms that are not in a parent-offspring relationship. HGT is a widely recognized mechanism for adaptation in bacteria and archaea. Microbial antibiotic resistance and pathogenicity are often associated with HGT, but the scope of HGT extends far beyond disease-causing organisms. In this Review, we describe how HGT has shaped the web of life using examples of HGT among prokaryotes, between prokaryotes and eukaryotes, and even between multicellular eukaryotes. We discuss replacement and additive HGT, the proposed mechanisms of HGT, selective forces that influence HGT, and the evolutionary impact of HGT on ancestral populations and existing populations such as the human microbiome.

Next-generation sequencing technology has facilitated the discovery of millions of genetic variants in human genomes. A sizeable fraction of these variants are predicted to be deleterious. Here, we review the pattern of deleterious alleles as ascertained in genome sequencing data sets and ask whether human populations differ in their predicted burden of deleterious alleles - a phenomenon known as mutation load. We discuss three demographic models that are predicted to affect mutation load and relate these models to the evidence (or the lack thereof) for variation in the efficacy of purifying selection in diverse human genomes. We also emphasize why accurate estimation of mutation load depends on assumptions regarding the distribution of dominance and selection coefficients - quantities that remain poorly characterized for current genomic data sets.

Whole-genome assemblies of humans and non-human primates are yielding data on the evolutionary origins of the human genome, as well as insights into genetic similarities and differences between species used as models for disease-related research. This Review discusses current knowledge and opportunities for comparative primate genomics created by recent advances in genome sequencing technologies. Advances in genome sequencing technologies have created new opportunities for comparative primate genomics. Genome assemblies have been published for various primate species, and analyses of several others are underway. Whole-genome assemblies for the great apes provide remarkable new information about the evolutionary origins of the human genome and the processes involved. Genomic data for macaques and other non-human primates offer valuable insights into genetic similarities and differences among species that are used as models for disease-related research. This Review summarizes current knowledge regarding primate genome content and dynamics, and proposes a series of goals for the near future.

Examining patterns of molecular genetic variation in both modern-day and ancient humans has proved to be a powerful approach to learn about our origins. Rapid advances in DNA sequencing technology have allowed us to characterize increasing amounts of genomic information. Although this clearly provides unprecedented power for inference, it also introduces more complexity into the way we use and interpret such data. Here, we review ongoing debates that have been influenced by improvements in our ability to sequence DNA and discuss some of the analytical challenges that need to be overcome in order to fully exploit the rich historical information that is contained in the entirety of the human genome.

Identifying the genetic mechanisms of adaptation requires the elucidation of links between the evolution of DNA sequence, phenotype, and fitness1. Convergent evolution can be used as a guide to identify candidate mutations that underlie adaptive traits2–4, and new genome editing technology is facilitating functional validation of these mutations in whole organisms1,5. We combined these approaches to study a classic case of convergence in insects from six orders, including the monarch butterfly (Danaus plexippus), that have independently evolved to colonize plants that produce cardiac glycoside toxins6–11. Many of these insects evolved parallel amino acid substitutions in the α-subunit (ATPα) of the sodium pump (Na+/K+-ATPase)7–11, the physiological target of cardiac glycosides12. Here we describe mutational paths involving three repeatedly changing amino acid sites (111, 119 and 122) in ATPα that are associated with cardiac glycoside specialization13,14. We then performed CRISPR–Cas9 base editing on the native Atpα gene in Drosophila melanogaster flies and retraced the mutational path taken across the monarch lineage11,15. We show in vivo, in vitro and in silico that the path conferred resistance and target-site insensitivity to cardiac glycosides16, culminating in triple mutant ‘monarch flies’ that were as insensitive to cardiac glycosides as monarch butterflies. ‘Monarch flies’ retained small amounts of cardiac glycosides through metamorphosis, a trait that has been optimized in monarch butterflies to deter predators17–19. The order in which the substitutions evolved was explained by amelioration of antagonistic pleiotropy through epistasis13,14,20–22. Our study illuminates how the monarch butterfly evolved resistance to a class of plant toxins, eventually becoming unpalatable, and changing the nature of species interactions within ecological communities2,6–11,15,17–19. CRISPR–Cas9 engineering of the Drosophila Atpα gene (encoding the α-subunit of the sodium pump) is used to study the ability of mutations that evolved independently in several insect orders to confer resistance to keystone plant toxins.

It is increasingly important to improve our understanding of the genetic basis of local adaptation because of its relevance to climate change, crop and animal production, and conservation of genetic resources. Phenotypic patterns that are generated by spatially varying selection have long been observed, and both genetic mapping and field experiments provided initial insights into the genetic architecture of adaptive traits. Genomic tools are now allowing genome-wide studies, and recent theoretical advances can help to design research strategies that combine genomics and field experiments to examine the genetics of local adaptation. These advances are also allowing research in non-model species, the adaptation patterns of which may differ from those of traditional model species.

The recent availability of genomic data has spurred many genome-wide studies of human adaptation in different populations worldwide. Such studies have provided insights into novel candidate genes and pathways that are putatively involved in adaptation to different environments, diets and disease prevalence. However, much work is needed to translate these results into candidate adaptive variants that are biologically interpretable. In this Review, we discuss methods that may help to identify true biological signals of selection and studies that incorporate complementary phenotypic and functional data. We conclude with recommendations for future studies that focus on opportunities to use integrative genomics methodologies in human adaptation studies.

Genes that have originated in recent evolution are present in only a subset of organisms and are often assumed to be dispensable or redundant. This Review discusses our latest understanding of how new genes in diverse species have actually evolved to have important functions in diverse developmental and physiological processes in various organisms. During the course of evolution, genomes acquire novel genetic elements as sources of functional and phenotypic diversity, including new genes that originated in recent evolution. In the past few years, substantial progress has been made in understanding the evolution and phenotypic effects of new genes. In particular, an emerging picture is that new genes, despite being present in the genomes of only a subset of species, can rapidly evolve indispensable roles in fundamental biological processes, including development, reproduction, brain function and behaviour. The molecular underpinnings of how new genes can develop these roles are starting to be characterized. These recent discoveries yield fresh insights into our broad understanding of biological diversity at refined resolution.

A publication in Science reports the sequencing, assembly and comparative analysis of new and improved great ape genomes and provides a stepping stone for the identification of genetic variation specific to humans.

A new study reveals that DNA methylation-mediated repression of gene expression regulates early eye development in blind cave morphs of Astyanax mexicanus.

Wright's F-statistics, and especially F(ST), provide important insights into the evolutionary processes that influence the structure of genetic variation within and among populations, and they are among the most widely used descriptive statistics in population and evolutionary genetics. Estimates of F(ST) can identify regions of the genome that have been the target of selection, and comparisons of F(ST) from different parts of the genome can provide insights into the demographic history of populations. For these reasons and others, F(ST) has a central role in population and evolutionary genetics and has wide applications in fields that range from disease association mapping to forensic science. This Review clarifies how F(ST) is defined, how it should be estimated, how it is related to similar statistics and how estimates of F(ST) should be interpreted.

Although the operation of natural selection requires that genotypes differ in fitness, some geneticists may find it easier to understand natural selection than fitness. Partly this reflects the fact that the word 'fitness' has been used to mean subtly different things. In this Review I distinguish among these meanings (for example, individual fitness, absolute fitness and relative fitness) and explain how evolutionary geneticists use fitness to predict changes in the genetic composition of populations through time. I also review the empirical study of fitness, emphasizing approaches that take advantage of recent genetic and genomic data, and I highlight important unresolved problems in understanding fitness.

Computer simulations are excellent tools for understanding the evolutionary and genetic consequences of complex processes whose interactions cannot be analytically predicted. Simulations have traditionally been used in population genetics by a fairly small community with programming expertise, but the recent availability of dozens of sophisticated, customizable software packages for simulation now makes simulation an accessible option for researchers in many fields. The in silico genetic data produced by simulations, along with greater availability of population-genomics data, are transforming genetic epidemiology, anthropology, evolutionary and population genetics and conservation. In this Review of the state-of-the-art of simulation software, we identify applications of simulations, evaluate simulator capabilities, provide a guide for their use and summarize future directions.