This report of independent genome sequences of two natural populations of Drosophila melanogaster (37 from North America and 6 from Africa) provides unique insight into forces shaping genomic polymorphism and divergence. Evidence of interactions between natural selection and genetic linkage is abundant not only in centromere-and telomere-proximal regions, but also throughout the euchromatic arms. Linkage disequilibrium, which decays within 1 kbp, exhibits a strong bias toward coupling of the more frequent alleles and provides a high-resolution map of recombination rate. The juxtaposition of population genetics statistics in small genomic windows with gene structures and chromatin states yields a rich, high-resolution annotation, including the following: (1) 59-and 39-UTRs are enriched for regions of reduced polymorphism relative to lineage-specific divergence; (2) exons overlap with windows of excess relative polymorphism; (3) epigenetic marks associated with active transcription initiation sites overlap with regions of reduced relative polymorphism and relatively reduced estimates of the rate of recombination; (4) the rate of adaptive nonsynonymous fixation increases with the rate of crossing over per base pair; and (5) both duplications and deletions are enriched near origins of replication and their density correlates negatively with the rate of crossing over. Available demographic models of X and autosome descent cannot account for the increased divergence on the X and loss of diversity associated with the out-of-Africa migration. Comparison of the variation among these genomes to variation among genomes from D. simulans suggests that many targets of directional selection are shared between these species. A CCESS to sequenced genomes from natural, outbreeding populations (Begun et al. 2007; Li and Durbin 2011) places our theoretical understanding of the forces that determine patterns of genomic variation within and between taxa in a new empirical light. Alignment of the predictions of classical evolutionary genetic models with richly annotated population genomic survey data is an exciting challenge. Descriptions of the patterns of variation in these first sets of population genomic data can foster efficient sieving of hypotheses and serve as a foundation for the design of subsequent studies. Here we present the description of the genomic sequence assemblies from two collections of natural populations of Drosophila melanogaster. The polymorphism, divergence, and copy-number variation revealed in these data are presented at several scales that all support the hypothesis by Maynard Smith and Haigh (1974) The study of genetic variation in natural populations of D. melanogaster has played an important role in the development of evolutionary theory, largely because of the central role of the species in the advancement of knowledge of genetic inheritance. Our fundamental understanding of the biology of D. melanogaster, as well as the advanced methods and unique resources available for its study, has fuel...
Determining the genetic basis of environmental adaptation is a central problem of evolutionary biology. This issue has been fruitfully addressed by examining genetic differentiation between populations that are recently separated and/or experience high rates of gene flow. A good example of this approach is the decades-long investigation of selection acting along latitudinal clines in Drosophila melanogaster. Here we use next-generation genome sequencing to reexamine the well-studied Australian D. melanogaster cline. We find evidence for extensive differentiation between temperate and tropical populations, with regulatory regions and unannotated regions showing particularly high levels of differentiation. Although the physical genomic scale of geographic differentiation is small-on the order of gene sized-we observed several larger highly differentiated regions. The region spanned by the cosmopolitan inversion polymorphism In(3R)P shows higher levels of differentiation, consistent with the major difference in allele frequencies of Standard and In(3R)P karyotypes in temperate vs. tropical Australian populations. Our analysis reveals evidence for spatially varying selection on a number of key biological processes, suggesting fundamental biological differences between flies from these two geographic regions.
All inferences in comparative biology depend on accurate estimates of evolutionary relationships. Recent phylogenetic analyses have turned away from maximum parsimony towards the probabilistic techniques of maximum likelihood and bayesian Markov chain Monte Carlo (BMCMC). These probabilistic techniques represent a parametric approach to statistical phylogenetics, because their criterion for evaluating a topology--the probability of the data, given the tree--is calculated with reference to an explicit evolutionary model from which the data are assumed to be identically distributed. Maximum parsimony can be considered nonparametric, because trees are evaluated on the basis of a general metric--the minimum number of character state changes required to generate the data on a given tree--without assuming a specific distribution. The shift to parametric methods was spurred, in large part, by studies showing that although both approaches perform well most of the time, maximum parsimony is strongly biased towards recovering an incorrect tree under certain combinations of branch lengths, whereas maximum likelihood is not. All these evaluations simulated sequences by a largely homogeneous evolutionary process in which data are identically distributed. There is ample evidence, however, that real-world gene sequences evolve heterogeneously and are not identically distributed. Here we show that maximum likelihood and BMCMC can become strongly biased and statistically inconsistent when the rates at which sequence sites evolve change non-identically over time. Maximum parsimony performs substantially better than current parametric methods over a wide range of conditions tested, including moderate heterogeneity and phylogenetic problems not normally considered difficult.
The incidence of the autoimmune disease, type 1 diabetes (T1D), has increased dramatically over the last half century in many developed countries and is particularly high in Finland and other Nordic countries. Along with genetic predisposition, environmental factors are thought to play a critical role in this increase. As with other autoimmune diseases, the gut microbiome is thought to play a potential role in controlling progression to T1D in children with high genetic risk, but we know little about how the gut microbiome develops in children with high genetic risk for T1D. In this study, the early development of the gut microbiomes of 76 children at high genetic risk for T1D was determined using high-throughput 16S rRNA gene sequencing. Stool samples from children born in the same hospital in Turku, Finland were collected at monthly intervals beginning at 4–6 months after birth until 2.2 years of age. Of those 76 children, 29 seroconverted to T1D-related autoimmunity (cases) including 22 who later developed T1D, the remaining 47 subjects remained healthy (controls). While several significant compositional differences in low abundant species prior to seroconversion were found, one highly abundant group composed of two closely related species, Bacteroides dorei and Bacteroides vulgatus, was significantly higher in cases compared to controls prior to seroconversion. Metagenomic sequencing of samples high in the abundance of the B. dorei/vulgatus group before seroconversion, as well as longer 16S rRNA sequencing identified this group as Bacteroides dorei. The abundance of B. dorei peaked at 7.6 months in cases, over 8 months prior to the appearance of the first islet autoantibody, suggesting that early changes in the microbiome may be useful for predicting T1D autoimmunity in genetically susceptible infants. The cause of increased B. dorei abundance in cases is not known but its timing appears to coincide with the introduction of solid food.
Drosophila melanogaster, an ancestrally African species, has recently spread throughout the world, associated with human activity. The species has served as the focus of many studies investigating local adaptation relating to latitudinal variation in non-African populations, especially those from the United States and Australia. These studies have documented the existence of shared, genetically determined phenotypic clines for several life history and morphological traits. However, there are no studies designed to formally address the degree of shared latitudinal differentiation at the genomic level. Here we present our comparative analysis of such differentiation. Not surprisingly, we find evidence of substantial, shared selection responses on the two continents, probably resulting from selection on standing ancestral variation. The polymorphic inversion In(3R)P has an important effect on this pattern, but considerable parallelism is also observed across the genome in regions not associated with inversion polymorphism. Interestingly, parallel latitudinal differentiation is observed even for variants that are not particularly strongly differentiated, which suggests that very large numbers of polymorphisms are targets of spatially varying selection in this species. HOW organisms adapt to the ecological challenges of a new environment remains poorly understood. Indeed, while observations from comparative biology show that organisms often evolve convergent phenotypes when faced with similar selection pressures, we have little insight into how underlying historical and population genetic processes determine the degree of shared or divergent selection responses across populations or species. The latitudinal clines of Drosophila melanogaster provide a rich system for exploring these questions.While there is general agreement that D. melanogaster evolved in Africa, spread through Eurasia several thousand years ago, and only recently colonized the Americas and Australia (David and Capy 1988;Lachaise et al. 1988;Begun and Aquadro 1993;Keller 2007;Stephan and Li 2007;Duchen et al. 2013), our understanding of the species' historical biogeography is incomplete. There are at least two potential clines that have received much attention-one in Australia and one in North America-that likely represent independent samplings of shared ancestral variation (Knibb 1982;Hoffmann and Weeks 2007).Decades of research on D. melanogaster clines have revealed broad shared patterns of adaptive phenotypic divergence along latitudinal transects in the Americas and Australia. For example, several phenotypes including body size, multiple physiological traits, and multiple allozyme variants show parallel clines on these continents (Singh and Long 1992). Paracentric chromosome inversion polymorphism is also well documented as showing similar patterns of clinal variation on the two continents (Voelker et al. 1978;Knibb 1982). Genomic description of the two clines is minimal. The most comprehensive data bearing on the issue of shared clinal...
RNA interference (RNAi) is a eukaryotic molecular system that serves two primary functions: 1) gene regulation and 2) protection against selfish elements such as viruses and transposable DNA. Although the biochemistry of RNAi has been detailed in model organisms, very little is known about the broad-scale patterns and forces that have shaped RNAi evolution. Here, we provide a comprehensive evolutionary analysis of the Dicer protein family, which carries out the initial RNA recognition and processing steps in the RNAi pathway. We show that Dicer genes duplicated and diversified independently in early animal and plant evolution, coincident with the origins of multicellularity. We identify a strong signature of long-term protein-coding adaptation that has continually reshaped the RNA-binding pocket of the plant Dicer responsible for antiviral immunity, suggesting an evolutionary arms race with viral factors. We also identify key changes in Dicer domain architecture and sequence leading to specialization in either gene-regulatory or protective functions in animal and plant paralogs. As a whole, these results reveal a dynamic picture in which the evolution of Dicer function has driven elaboration of parallel RNAi functional pathways in animals and plants.
Ancestral sequence reconstruction (ASR) is widely used to formulate and test hypotheses about the sequences, functions, and structures of ancient genes. Ancestral sequences are usually inferred from an alignment of extant sequences using a maximum likelihood (ML) phylogenetic algorithm, which calculates the most likely ancestral sequence assuming a probabilistic model of sequence evolution and a specific phylogeny—typically the tree with the ML. The true phylogeny is seldom known with certainty, however. ML methods ignore this uncertainty, whereas Bayesian methods incorporate it by integrating the likelihood of each ancestral state over a distribution of possible trees. It is not known whether Bayesian approaches to phylogenetic uncertainty improve the accuracy of inferred ancestral sequences. Here, we use simulation-based experiments under both simplified and empirically derived conditions to compare the accuracy of ASR carried out using ML and Bayesian approaches. We show that incorporating phylogenetic uncertainty by integrating over topologies very rarely changes the inferred ancestral state and does not improve the accuracy of the reconstructed ancestral sequence. Ancestral state reconstructions are robust to uncertainty about the underlying tree because the conditions that produce phylogenetic uncertainty also make the ancestral state identical across plausible trees; conversely, the conditions under which different phylogenies yield different inferred ancestral states produce little or no ambiguity about the true phylogeny. Our results suggest that ML can produce accurate ASRs, even in the face of phylogenetic uncertainty. Using Bayesian integration to incorporate this uncertainty is neither necessary nor beneficial.
The nitrogenase metalloenzyme family, essential for supplying fixed nitrogen to the biosphere, is one of life's key biogeochemical innovations. The three forms of nitrogenase differ in their metal dependence, each binding either a FeMo-, FeV-, or FeFecofactor where the reduction of dinitrogen takes place. The history of nitrogenase metal dependence has been of particular interest due to the possible implication that ancient marine metal availabilities have significantly constrained nitrogenase evolution over geologic time. Here, we reconstructed the evolutionary history of nitrogenases, and combined phylogenetic reconstruction, ancestral sequence inference, and structural homology modeling to evaluate the potential metal dependence of ancient nitrogenases. We find that active-site sequence features can reliably distinguish extant Mo-nitrogenases from V-and Fe-nitrogenases and that inferred ancestral sequences at the deepest nodes of the phylogeny suggest these ancient proteins most resemble modern Mo-nitrogenases. Taxa representing early-branching nitrogenase lineages lack one or more biosynthetic nifE and nifN genes that both contribute to the assembly of the FeMo-cofactor in studied organisms, suggesting that early Monitrogenases may have utilized an alternate and/or simplified pathway for cofactor biosynthesis. Our results underscore the profound impacts that protein-level innovations likely had on shaping global biogeochemical cycles throughout the Precambrian, in contrast to organism-level innovations that characterize the Phanerozoic Eon. K E Y W O R D Sancestral sequence reconstruction, metal cofactor, metalloenzyme, nitrogen fixation, nitrogenase This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.