Evolutionary History of Oxysterol-Binding Proteins Reveals Complex History of Duplication and Loss in Animals and Fungi.

Cells maintain the specific lipid composition of distinct organelles by vesicular transport as well as non-vesicular lipid trafficking via lipid transport proteins. Oxysterol-binding proteins (OSBPs) are a family of lipid transport proteins that transfer lipids at various membrane contact sites (MCSs). OSBPs have been extensively investigated in human and yeast cells where 12 have been identified in Homo sapiens and 7 in Saccharomyces cerevisiae. The evolutionary relationship between these well-characterized OSBPs is still unclear. By reconstructing phylogenies of eukaryote OSBPs, we show that the ancestral Saccharomycotina had four OSBPs, the ancestral fungus had five OSBPs, and the ancestral animal had six OSBPs, whereas the shared ancestor of animals and fungi as well as the ancestral eukaryote had only three OSBPs. Our analyses identified three undescribed ancient OSBP orthologues, one fungal OSBP (Osh8) lost in the lineage leading to yeast, one animal OSBP (ORP12) lost in the lineage leading to vertebrates, and one eukaryotic OSBP (OshEu) lost in both the animal and fungal lineages.

Single-Cell Genomics Reveals the Divergent Mitochondrial Genomes of Retaria (Foraminifera and Radiolaria).

Mitochondria originated from an ancient bacterial endosymbiont that underwent reductive evolution by gene loss and endosymbiont gene transfer to the nuclear genome. The diversity of mitochondrial genomes published to date has revealed that gene loss and transfer processes are ongoing in many lineages. Most well-studied eukaryotic lineages are represented in mitochondrial genome databases, except for the superphylum Retaria-the lineage comprising Foraminifera and Radiolaria. Using single-cell approaches, we determined two complete mitochondrial genomes of Foraminifera and two nearly complete mitochondrial genomes of radiolarians. We report the complete coding content of an additional 14 foram species. We show that foraminiferan and radiolarian mitochondrial genomes contain a nearly fully overlapping but reduced mitochondrial gene complement compared to other sequenced rhizarians. In contrast to animals and fungi, many protists encode a diverse set of proteins on their mitochondrial genomes, including several ribosomal genes; however, some aerobic eukaryotic lineages (euglenids, myzozoans, and chlamydomonas-like algae) have reduced mitochondrial gene content and lack all ribosomal genes. Similar to these reduced outliers, we show that retarian mitochondrial genomes lack ribosomal protein and tRNA genes, contain truncated and divergent small and large rRNA genes, and contain only 14 or 15 protein-coding genes, including nad1, -3, -4, -4L, -5, and -7, cob, cox1, -2, and -3, and atp1, -6, and -9, with forams and radiolarians additionally carrying nad2 and nad6, respectively. In radiolarian mitogenomes, a noncanonical genetic code was identified in which all three stop codons encode amino acids. Collectively, these results add to our understanding of mitochondrial genome evolution and fill in one of the last major gaps in mitochondrial sequence databases. IMPORTANCE We present the reduced mitochondrial genomes of Retaria, the rhizarian lineage comprising the phyla Foraminifera and Radiolaria. By applying single-cell genomic approaches, we found that foraminiferan and radiolarian mitochondrial genomes contain an overlapping but reduced mitochondrial gene complement compared to other sequenced rhizarians. An alternative genetic code was identified in radiolarian mitogenomes in which all three stop codons encode amino acids. Collectively, these results shed light on the divergent nature of the mitochondrial genomes from an ecologically important group, warranting further questions into the biological underpinnings of gene content variability and genetic code variation between mitochondrial genomes.

Molecular asymmetry of a photosynthetic supercomplex from green sulfur bacteria.

The photochemical reaction center (RC) features a dimeric architecture for charge separation across the membrane. In green sulfur bacteria (GSB), the trimeric Fenna-Matthews-Olson (FMO) complex mediates the transfer of light energy from the chlorosome antenna complex to the RC. Here we determine the structure of the photosynthetic supercomplex from the GSB Chlorobaculum tepidum using single-particle cryogenic electron microscopy (cryo-EM) and identify the cytochrome c subunit (PscC), two accessory protein subunits (PscE and PscF), a second FMO trimeric complex, and a linker pigment between FMO and the RC core. The protein subunits that are assembled with the symmetric RC core generate an asymmetric photosynthetic supercomplex. One linker bacteriochlorophyll (BChl) is located in one of the two FMO-PscA interfaces, leading to differential efficiencies of the two energy transfer branches. The two FMO trimeric complexes establish two different binding interfaces with the RC cytoplasmic surface, driven by the associated accessory subunits. This structure of the GSB photosynthetic supercomplex provides mechanistic insight into the light excitation energy transfer routes and a possible evolutionary transition intermediate of the bacterial photosynthetic supercomplex from the primitive homodimeric RC.

Structural and Functional Analysis of Disease-Linked p97 ATPase Mutant Complexes.

IBMPFD/ALS is a genetic disorder caused by a single amino acid mutation on the p97 ATPase, promoting ATPase activity and cofactor dysregulation. The disease mechanism underlying p97 ATPase malfunction remains unclear. To understand how the mutation alters the ATPase regulation, we assembled a full-length p97R155H with its p47 cofactor and first visualized their structures using single-particle cryo-EM. More than one-third of the population was the dodecameric form. Nucleotide presence dissociates the dodecamer into two hexamers for its highly elevated function. The N-domains of the p97R155H mutant all show up configurations in ADP- or ATPγS-bound states. Our functional and structural analyses showed that the p47 binding is likely to impact the p97R155H ATPase activities via changing the conformations of arginine fingers. These functional and structural analyses underline the ATPase dysregulation with the miscommunication between the functional modules of the p97R155H.

Sample Preparation and Data Collection for Electron Crystallographic Studies on Membrane Protein Structures and Lipid-Protein Interaction.

Electron crystallography is a unique tool to study membrane protein structures and lipid-protein interactions in their native-like environments. Two-dimensional (2D) protein crystallization enables the lipids immobilized by the proteins, and the generated high-resolution density map allows us to model the atomic coordinates of the surrounding lipids to study lipid-protein interaction. This protocol describes the sample preparation for electron crystallographic studies, including back-injection method and carbon sandwich method. The protocols of data collection for electron crystallography, including electron imaging and diffraction, of the 2D membrane crystal will be followed.

Mutations in Influenza A Virus Neuraminidase and Hemagglutinin Confer Resistance against a Broadly Neutralizing Hemagglutinin Stem Antibody.

Influenza A virus (IAV), a major cause of human morbidity and mortality, continuously evolves in response to selective pressures. Stem-directed, broadly neutralizing antibodies (sBnAbs) targeting the influenza virus hemagglutinin (HA) are a promising therapeutic strategy, but neutralization escape mutants can develop. We used an integrated approach combining viral passaging, deep sequencing, and protein structural analyses to define escape mutations and mechanisms of neutralization escape in vitro for the F10 sBnAb. IAV was propagated with escalating concentrations of F10 over serial passages in cultured cells to select for escape mutations. Viral sequence analysis revealed three mutations in HA and one in neuraminidase (NA). Introduction of these specific mutations into IAV through reverse genetics confirmed their roles in resistance to F10. Structural analyses revealed that the selected HA mutations (S123G, N460S, and N203V) are away from the F10 epitope but may indirectly impact influenza virus receptor binding, endosomal fusion, or budding. The NA mutation E329K, which was previously identified to be associated with antibody escape, affects the active site of NA, highlighting the importance of the balance between HA and NA function for viral survival. Thus, whole-genome population sequencing enables the identification of viral resistance mutations responding to antibody-induced selective pressure.IMPORTANCE Influenza A virus is a public health threat for which currently available vaccines are not always effective. Broadly neutralizing antibodies that bind to the highly conserved stem region of the influenza virus hemagglutinin (HA) can neutralize many influenza virus strains. To understand how influenza virus can become resistant or escape such antibodies, we propagated influenza A virus in vitro with escalating concentrations of antibody and analyzed viral populations by whole-genome sequencing. We identified HA mutations near and distal to the antibody binding epitope that conferred resistance to antibody neutralization. Additionally, we identified a neuraminidase (NA) mutation that allowed the virus to grow in the presence of high concentrations of the antibody. Virus carrying dual mutations in HA and NA also grew under high antibody concentrations. We show that NA mutations mediate the escape of neutralization by antibodies against HA, highlighting the importance of a balance between HA and NA for optimal virus function.

On the prospect of identifying adaptive loci in recently bottlenecked populations.

Identifying adaptively important loci in recently bottlenecked populations - be it natural selection acting on a population following the colonization of novel habitats in the wild, or artificial selection during the domestication of a breed - remains a major challenge. Here we report the results of a simulation study examining the performance of available population-genetic tools for identifying genomic regions under selection. To illustrate our findings, we examined the interplay between selection and demography in two species of Peromyscus mice, for which we have independent evidence of selection acting on phenotype as well as functional evidence identifying the underlying genotype. With this unusual information, we tested whether population-genetic-based approaches could have been utilized to identify the adaptive locus. Contrary to published claims, we conclude that the use of the background site frequency spectrum as a null model is largely ineffective in bottlenecked populations. Results are quantified both for site frequency spectrum and linkage disequilibrium-based predictions, and are found to hold true across a large parameter space that encompasses many species and populations currently under study. These results suggest that the genomic footprint left by selection on both new and standing variation in strongly bottlenecked populations will be difficult, if not impossible, to find using current approaches.

Influenza virus drug resistance: a time-sampled population genetics perspective.

The challenge of distinguishing genetic drift from selection remains a central focus of population genetics. Time-sampled data may provide a powerful tool for distinguishing these processes, and we here propose approximate Bayesian, maximum likelihood, and analytical methods for the inference of demography and selection from time course data. Utilizing these novel statistical and computational tools, we evaluate whole-genome datasets of an influenza A H1N1 strain in the presence and absence of oseltamivir (an inhibitor of neuraminidase) collected at thirteen time points. Results reveal a striking consistency amongst the three estimation procedures developed, showing strongly increased selection pressure in the presence of drug treatment. Importantly, these approaches re-identify the known oseltamivir resistance site, successfully validating the approaches used. Enticingly, a number of previously unknown variants have also been identified as being positively selected. Results are interpreted in the light of Fisher's Geometric Model, allowing for a quantification of the increased distance to optimum exerted by the presence of drug, and theoretical predictions regarding the distribution of beneficial fitness effects of contending mutations are empirically tested. Further, given the fit to expectations of the Geometric Model, results suggest the ability to predict certain aspects of viral evolution in response to changing host environments and novel selective pressures.

Evolution of the influenza A virus genome during development of oseltamivir resistance in vitro.

Influenza A virus (IAV) is a major cause of morbidity and mortality throughout the world. Current antiviral therapies include oseltamivir, a neuraminidase inhibitor that prevents the release of nascent viral particles from infected cells. However, the IAV genome can evolve rapidly, and oseltamivir resistance mutations have been detected in numerous clinical samples. Using an in vitro evolution platform and whole-genome population sequencing, we investigated the population genomics of IAV during the development of oseltamivir resistance. Strain A/Brisbane/59/2007 (H1N1) was grown in Madin-Darby canine kidney cells with or without escalating concentrations of oseltamivir over serial passages. Following drug treatment, the H274Y resistance mutation fixed reproducibly within the population. The presence of the H274Y mutation in the viral population, at either a low or a high frequency, led to measurable changes in the neuraminidase inhibition assay. Surprisingly, fixation of the resistance mutation was not accompanied by alterations of viral population diversity or differentiation, and oseltamivir did not alter the selective environment. While the neighboring K248E mutation was also a target of positive selection prior to H274Y fixation, H274Y was the primary beneficial mutation in the population. In addition, once evolved, the H274Y mutation persisted after the withdrawal of the drug, even when not fixed in viral populations. We conclude that only selection of H274Y is required for oseltamivir resistance and that H274Y is not deleterious in the absence of the drug. These collective results could offer an explanation for the recent reproducible rise in oseltamivir resistance in seasonal H1N1 IAV strains in humans.

The impact of equilibrium assumptions on tests of selection.

With the increasing availability and quality of whole genome population data, various methodologies of population genetic inference are being utilized in order to identify and quantify recent population-level selective events. Though there has been a great proliferation of such methodology, the type-I and type-II error rates of many proposed statistics have not been well-described. Moreover, the performance of these statistics is often not evaluated for different biologically relevant scenarios (e.g., population size change, population structure), nor for the effect of differing data sizes (i.e., genomic vs. sub-genomic). The absence of the above information makes it difficult to evaluate newly available statistics relative to one another, and thus, difficult to choose the proper toolset for a given empirical analysis. Thus, we here describe and compare the performance of four widely used tests of selection: SweepFinder, SweeD, OmegaPlus, and iHS. In order to consider the above questions, we utilize simulated data spanning a variety of selection coefficients and beneficial mutation rates. We demonstrate that the LD-based OmegaPlus performs best in terms of power to reject the neutral model under both equilibrium and non-equilibrium conditions-an important result regarding the relative effectiveness of linkage disequilibrium relative to site frequency spectrum based statics. The results presented here ought to serve as a useful guide for future empirical studies, and provides a guide for statistical choice depending on the history of the population under consideration. Moreover, the parameter space investigated and the Type-I and Type-II error rates calculated, represent a natural benchmark by which future statistics may be assessed.

Recurrent and recent selective sweeps in the piRNA pathway.

Uncontrolled transposable element (TE) insertions and excisions can cause chromosome breaks and mutations with dramatic deleterious effects. The PIWI interacting RNA (piRNA) pathway functions as an adaptive TE silencing system during germline development. Several essential piRNA pathway proteins appear to be rapidly evolving, suggesting that TEs and the silencing machinery may be engaged in a classical "evolutionary arms race." Using a variety of molecular evolutionary and population genetic approaches, we find that the piRNA pathway genes rhino, krimper, and aubergine show patterns suggestive of extensive recurrent positive selection across Drosophila species. We speculate that selection on these proteins reflects crucial roles in silencing unfamiliar elements during vertical and horizontal transmission of TEs into naïve populations and species, respectively.

Adaptive evolution of multiple traits through multiple mutations at a single gene.

The identification of precise mutations is required for a complete understanding of the underlying molecular and evolutionary mechanisms driving adaptive phenotypic change. Using plasticine models in the field, we show that the light coat color of deer mice that recently colonized the light-colored soil of the Nebraska Sand Hills provides a strong selective advantage against visually hunting predators. Color variation in an admixed population suggests that this light Sand Hills phenotype is composed of multiple traits. We identified distinct regions within the Agouti locus associated with each color trait and found that only haplotypes associated with light trait values have evidence of selection. Thus, local adaptation is the result of independent selection on many mutations within a single locus, each with a specific effect on an adaptive phenotype, thereby minimizing pleiotropic consequences.

Population genomic analysis of base composition evolution in Drosophila melanogaster.

The relative importance of mutation, selection, and biased gene conversion to patterns of base composition variation in Drosophila melanogaster, and to a lesser extent, D. simulans, has been investigated for many years. However, genomic data from sufficiently large samples to thoroughly characterize patterns of base composition polymorphism within species have been lacking. Here, we report a genome-wide analysis of coding and noncoding polymorphism in a large sample of inbred D. melanogaster strains from Raleigh, North Carolina. Consistent with previous results, we observed that AT mutations fix more frequently than GC mutations in D. melanogaster. Contrary to predictions of previous models of codon usage in D. melanogaster, we found that synonymous sites segregating for derived AT polymorphisms were less skewed toward low frequencies compared with sites segregating a derived GC polymorphism. However, no such pattern was observed for comparable base composition polymorphisms in noncoding DNA. These results suggest that AT-ending codons could currently be favored by natural selection in the D. melanogaster lineage.

Evidence of adaptation from ancestral variation in young populations of beach mice.

To understand how organisms adapt to novel habitats, which involves both demographic and selective events, we require knowledge of the evolutionary history of populations and also selected alleles. There are still few cases in which the precise mutations (and hence, defined alleles) that contribute to adaptive change have been identified in nature; one exception is the genetic basis of camouflaging pigmentation of oldfield mice (Peromyscus polionotus) that have colonized the sandy dunes of Florida's Gulf Coast. To quantify the genomic impact of colonization as well as the signature of selection, we resequenced 5000 1.5-kb noncoding loci as well as a 160-kb genomic region surrounding the melanocortin-1 receptor (Mc1r), a gene that contributes to pigmentation differences, in beach and mainland populations. Using a genome-wide phylogenetic approach, we recovered a single monophyletic group comprised of beach mice, consistent with a single colonization event of the Gulf Coast. We also found evidence of a severe founder event, estimated to have occurred less than 3000 years ago. In this demographic context, we show that all beach subspecies share a single derived light Mc1r allele, which was likely selected from standing genetic variation that originated in the mainland. Surprisingly, we were unable to identify a clear signature of selection in the Mc1r region, despite independent evidence that this locus contributes to adaptive coloration. Nonetheless, these data allow us to reconstruct and compare the evolutionary history of populations and alleles to better understand how adaptive evolution, following the colonization of a novel habitat, proceeds in nature.

Recent progress in polymorphism-based population genetic inference.

The recent availability of whole-genome sequencing data affords tremendous power for statistical inference. With this, there has been great interest in the development of polymorphism-based approaches for the estimation of population genetic parameters. These approaches seek to estimate, for example, recently fixed or sweeping beneficial mutations, the rate of recurrent positive selection, the distribution of selection coefficients, and the demographic history of the population. Yet despite estimating similar parameters using similar data sets, results between methodologies are far from consistent. We here summarize the current state of the field, compare existing approaches, and attempt to reconcile emerging discrepancies. We also discuss the biases in selection estimators introduced by ignoring the demographic history of the population, discuss the biases in demographic estimators introduced by assuming neutrality, and highlight the important challenge to the field of achieving a true joint estimation procedure to circumvent these confounding effects.

On detecting selective sweeps using single genomes.

Identifying the genetic basis of human adaptation has remained a central focal point of modern population genetics. One major area of interest has been the use of polymorphism data to detect so-called "footprints" of selective sweeps - patterns produced as a beneficial mutation arises and rapidly fixes in the population. Based on numerous simulation studies and power analyses, the necessary sample size for achieving appreciable power has been shown to vary from a few individuals to a few dozen, depending on the test statistic. And yet, the sequencing of multiple copies of a single region, or of multiple genomes as is now often the case, incurs considerable cost. Enard et al. (2010) have recently proposed a method to identify patterns of selective sweeps using a single genome - and apply this approach to human and non-human primates (chimpanzee, orangutan, and macaque). They employ essentially a modification of the Hudson, Kreitman, and Aguade test - using heterozygous single nucleotide polymorphisms from single individuals, and divergence data from two closely related species (human-chimpanzee, human-orangutan, and human-macaque). Given the potential importance of this finding, we here investigate the properties of this statistic. We demonstrate through simulation that this approach is neither robust to demography nor background selection; nor is it robust to variable recombination rates.

Population genomics: whole-genome analysis of polymorphism and divergence in Drosophila simulans.

The population genetic perspective is that the processes shaping genomic variation can be revealed only through simultaneous investigation of sequence polymorphism and divergence within and between closely related species. Here we present a population genetic analysis of Drosophila simulans based on whole-genome shotgun sequencing of multiple inbred lines and comparison of the resulting data to genome assemblies of the closely related species, D. melanogaster and D. yakuba. We discovered previously unknown, large-scale fluctuations of polymorphism and divergence along chromosome arms, and significantly less polymorphism and faster divergence on the X chromosome. We generated a comprehensive list of functional elements in the D. simulans genome influenced by adaptive evolution. Finally, we characterized genomic patterns of base composition for coding and noncoding sequence. These results suggest several new hypotheses regarding the genetic and biological mechanisms controlling polymorphism and divergence across the Drosophila genome, and provide a rich resource for the investigation of adaptive evolution and functional variation in D. simulans.