Evidence that RNA Viruses Drove Adaptive Introgression between Neanderthals and Modern Humans.

Neanderthals and modern humans interbred at least twice in the past 100,000 years. While there is evidence that most introgressed DNA segments from Neanderthals to modern humans were removed by purifying selection, less is known about the adaptive nature of introgressed sequences that were retained. We hypothesized that interbreeding between Neanderthals and modern humans led to (1) the exposure of each species to novel viruses and (2) the exchange of adaptive alleles that provided resistance against these viruses. Here, we find that long, frequent-and more likely adaptive-segments of Neanderthal ancestry in modern humans are enriched for proteins that interact with viruses (VIPs). We found that VIPs that interact specifically with RNA viruses were more likely to belong to introgressed segments in modern Europeans. Our results show that retained segments of Neanderthal ancestry can be used to detect ancient epidemics.

Development of a Comprehensive Genotype-to-Fitness Map of Adaptation-Driving Mutations in Yeast.

Adaptive evolution plays a large role in generating the phenotypic diversity observed in nature, yet current methods are impractical for characterizing the molecular basis and fitness effects of large numbers of individual adaptive mutations. Here, we used a DNA barcoding approach to generate the genotype-to-fitness map for adaptation-driving mutations from a Saccharomyces cerevisiae population experimentally evolved by serial transfer under limiting glucose. We isolated and measured the fitness of thousands of independent adaptive clones and sequenced the genomes of hundreds of clones. We found only two major classes of adaptive mutations: self-diploidization and mutations in the nutrient-responsive Ras/PKA and TOR/Sch9 pathways. Our large sample size and precision of measurement allowed us to determine that there are significant differences in fitness between mutations in different genes, between different paralogs, and even between different classes of mutations within the same gene.

Single-fly genome assemblies fill major phylogenomic gaps across the Drosophilidae Tree of Life.

Long-read sequencing is driving rapid progress in genome assembly across all major groups of life, including species of the family Drosophilidae, a longtime model system for genetics, genomics, and evolution. We previously developed a cost-effective hybrid Oxford Nanopore (ONT) long-read and Illumina short-read sequencing approach and used it to assemble 101 drosophilid genomes from laboratory cultures, greatly increasing the number of genome assemblies for this taxonomic group. The next major challenge is to address the laboratory culture bias in taxon sampling by sequencing genomes of species that cannot easily be reared in the lab. Here, we build upon our previous methods to perform amplification-free ONT sequencing of single wild flies obtained either directly from the field or from ethanol-preserved specimens in museum collections, greatly improving the representation of lesser studied drosophilid taxa in whole-genome data. Using Illumina Novaseq X Plus and ONT P2 sequencers with R10.4.1 chemistry, we set a new benchmark for inexpensive hybrid genome assembly at US $150 per genome while assembling genomes from as little as 35 ng of genomic DNA from a single fly. We present 183 new genome assemblies for 179 species as a resource for drosophilid systematics, phylogenetics, and comparative genomics. Of these genomes, 62 are from pooled lab strains and 121 from single adult flies. Despite the sample limitations of working with small insects, most single-fly diploid assemblies are comparable in contiguity (>1 Mb contig N50), completeness (>98% complete dipteran BUSCOs), and accuracy (>QV40 genome-wide with ONT R10.4.1) to assemblies from inbred lines. We present a well-resolved multi-locus phylogeny for 360 drosophilid and 4 outgroup species encompassing all publicly available (as of August 2023) genomes for this group. Finally, we present a Progressive Cactus whole-genome, reference-free alignment built from a subset of 298 suitably high-quality drosophilid genomes. The new assemblies and alignment, along with updated laboratory protocols and computational pipelines, are released as an open resource and as a tool for studying evolution at the scale of an entire insect family.

The AMBRA1 E3 ligase adaptor regulates the stability of cyclin D.

The initiation of cell division integrates a large number of intra- and extracellular inputs. D-type cyclins (hereafter, cyclin D) couple these inputs to the initiation of DNA replication1. Increased levels of cyclin D promote cell division by activating cyclin-dependent kinases 4 and 6 (hereafter, CDK4/6), which in turn phosphorylate and inactivate the retinoblastoma tumour suppressor. Accordingly, increased levels and activity of cyclin D-CDK4/6 complexes are strongly linked to unchecked cell proliferation and cancer2,3. However, the mechanisms that regulate levels of cyclin D are incompletely understood4,5. Here we show that autophagy and beclin 1 regulator 1 (AMBRA1) is the main regulator of the degradation of cyclin D. We identified AMBRA1 in a genome-wide screen to investigate the genetic basis of  the response to CDK4/6 inhibition. Loss of AMBRA1 results in high levels of cyclin D in cells and in mice, which promotes proliferation and decreases sensitivity to CDK4/6 inhibition. Mechanistically, AMBRA1 mediates ubiquitylation and proteasomal degradation of cyclin D as a substrate receptor for the cullin 4 E3 ligase complex. Loss of AMBRA1 enhances the growth of lung adenocarcinoma in a mouse model, and low levels of AMBRA1 correlate with worse survival in patients with lung adenocarcinoma. Thus, AMBRA1 regulates cellular levels of cyclin D, and contributes to cancer development and the response of cancer cells to CDK4/6 inhibitors.

Fully accessible fitness landscape of oncogene-negative lung adenocarcinoma.

Cancer genomes are almost invariably complex with genomic alterations cooperating during each step of carcinogenesis. In cancers that lack a single dominant oncogene mutation, cooperation between the inactivation of multiple tumor suppressor genes can drive tumor initiation and growth. Here, we shed light on how the sequential acquisition of genomic alterations generates oncogene-negative lung tumors. We couple tumor barcoding with combinatorial and multiplexed somatic genome editing to characterize the fitness landscapes of three tumor suppressor genes NF1, RASA1, and PTEN, the inactivation of which jointly drives oncogene-negative lung adenocarcinoma initiation and growth. The fitness landscape was surprisingly accessible, with each additional mutation leading to growth advantage. Furthermore, the fitness landscapes remained fully accessible across backgrounds with the inactivation of additional tumor suppressor genes. These results suggest that while predicting cancer evolution will be challenging, acquiring the multiple alterations that drive the growth of oncogene-negative tumors can be facilitated by the lack of constraints on mutational order.

The clarifying role of time series data in the population genetics of HIV.

HIV can evolve remarkably quickly in response to antiretroviral therapies and the immune system. This evolution stymies treatment effectiveness and prevents the development of an HIV vaccine. Consequently, there has been a great interest in using population genetics to disentangle the forces that govern the HIV adaptive landscape (selection, drift, mutation, and recombination). Traditional population genetics approaches look at the current state of genetic variation and infer the processes that can generate it. However, because HIV evolves rapidly, we can also sample populations repeatedly over time and watch evolution in action. In this paper, we demonstrate how time series data can bound evolutionary parameters in a way that complements and informs traditional population genetic approaches. Specifically, we focus on our recent paper (Feder et al., 2016, eLife), in which we show that, as improved HIV drugs have led to fewer patients failing therapy due to resistance evolution, less genetic diversity has been maintained following the fixation of drug resistance mutations. Because soft sweeps of multiple drug resistance mutations spreading simultaneously have been previously documented in response to the less effective HIV therapies used early in the epidemic, we interpret the maintenance of post-sweep diversity in response to poor therapies as further evidence of soft sweeps and therefore a high population mutation rate (θ) in these intra-patient HIV populations. Because improved drugs resulted in rarer resistance evolution accompanied by lower post-sweep diversity, we suggest that both observations can be explained by decreased population mutation rates and a resultant transition to hard selective sweeps. A recent paper (Harris et al., 2018, PLOS Genetics) proposed an alternative interpretation: Diversity maintenance following drug resistance evolution in response to poor therapies may have been driven by recombination during slow, hard selective sweeps of single mutations. Then, if better drugs have led to faster hard selective sweeps of resistance, recombination will have less time to rescue diversity during the sweep, recapitulating the decrease in post-sweep diversity as drugs have improved. In this paper, we use time series data to show that drug resistance evolution during ineffective treatment is very fast, providing new evidence that soft sweeps drove early HIV treatment failure.

Detection of hard and soft selective sweeps from Drosophila melanogaster population genomic data.

Whether hard sweeps or soft sweeps dominate adaptation has been a matter of much debate. Recently, we developed haplotype homozygosity statistics that (i) can detect both hard and soft sweeps with similar power and (ii) can classify the detected sweeps as hard or soft. The application of our method to population genomic data from a natural population of Drosophila melanogaster (DGRP) allowed us to rediscover three known cases of adaptation at the loci Ace, Cyp6g1, and CHKov1 known to be driven by soft sweeps, and detected additional candidate loci for recent and strong sweeps. Surprisingly, all of the top 50 candidates showed patterns much more consistent with soft rather than hard sweeps. Recently, Harris et al. 2018 criticized this work, suggesting that all the candidate loci detected by our haplotype statistics, including the positive controls, are unlikely to be sweeps at all and that instead these haplotype patterns can be more easily explained by complex neutral demographic models. They also claim that these neutral non-sweeps are likely to be hard instead of soft sweeps. Here, we reanalyze the DGRP data using a range of complex admixture demographic models and reconfirm our original published results suggesting that the majority of recent and strong sweeps in D. melanogaster are first likely to be true sweeps, and second, that they do appear to be soft. Furthermore, we discuss ways to take this work forward given that most demographic models employed in such analyses are necessarily too simple to capture the full demographic complexity, while more realistic models are unlikely to be inferred correctly because they require a large number of free parameters.

Population genomics of transposable elements in Drosophila.

Studies of the population dynamics of transposable elements (TEs) in Drosophila melanogaster indicate that consistent forces are affecting TEs independently of their modes of transposition and regulation. New sequencing technologies enable biologists to sample genomes at an unprecedented scale in order to quantify genome-wide polymorphism for annotated and novel TE insertions. In this review, we first present new insights gleaned from high-throughput data for population genomics studies of D. melanogaster. We then consider the latest population genomics models for TE evolution and present examples of functional evidence revealed by genome-wide studies of TE population dynamics in D. melanogaster. Although most of the TE insertions are deleterious or neutral, some TE insertions increase the fitness of the individual that carries them and play a role in genome adaptation.

Microbiome composition shapes rapid genomic adaptation of Drosophila melanogaster.

Population genomic data has revealed patterns of genetic variation associated with adaptation in many taxa. Yet understanding the adaptive process that drives such patterns is challenging; it requires disentangling the ecological agents of selection, determining the relevant timescales over which evolution occurs, and elucidating the genetic architecture of adaptation. Doing so for the adaptation of hosts to their microbiome is of particular interest with growing recognition of the importance and complexity of host-microbe interactions. Here, we track the pace and genomic architecture of adaptation to an experimental microbiome manipulation in replicate populations of Drosophila melanogaster in field mesocosms. Shifts in microbiome composition altered population dynamics and led to divergence between treatments in allele frequencies, with regions showing strong divergence found on all chromosomes. Moreover, at divergent loci previously associated with adaptation across natural populations, we found that the more common allele in fly populations experimentally enriched for a certain microbial group was also more common in natural populations with high relative abundance of that microbial group. These results suggest that microbiomes may be an agent of selection that shapes the pattern and process of adaptation and, more broadly, that variation in a single ecological factor within a complex environment can drive rapid, polygenic adaptation over short timescales.

Stress response, behavior, and development are shaped by transposable element-induced mutations in Drosophila.

Most of the current knowledge on the genetic basis of adaptive evolution is based on the analysis of single nucleotide polymorphisms (SNPs). Despite increasing evidence for their causal role, the contribution of structural variants to adaptive evolution remains largely unexplored. In this work, we analyzed the population frequencies of 1,615 Transposable Element (TE) insertions annotated in the reference genome of Drosophila melanogaster, in 91 samples from 60 worldwide natural populations. We identified a set of 300 polymorphic TEs that are present at high population frequencies, and located in genomic regions with high recombination rate, where the efficiency of natural selection is high. The age and the length of these 300 TEs are consistent with relatively young and long insertions reaching high frequencies due to the action of positive selection. Besides, we identified a set of 21 fixed TEs also likely to be adaptive. Indeed, we, and others, found evidence of selection for 84 of these reference TE insertions. The analysis of the genes located nearby these 84 candidate adaptive insertions suggested that the functional response to selection is related with the GO categories of response to stimulus, behavior, and development. We further showed that a subset of the candidate adaptive TEs affects expression of nearby genes, and five of them have already been linked to an ecologically relevant phenotypic effect. Our results provide a more complete understanding of the genetic variation and the fitness-related traits relevant for adaptive evolution. Similar studies should help uncover the importance of TE-induced adaptive mutations in other species as well.

Historical trends and new surveillance of Plasmodium falciparum drug resistance markers in Angola.

BACKGROUND: Plasmodium falciparum resistance to chloroquine (CQ) and sulfadoxine-pyrimethamine (SP) has historically posed a major threat to malaria control throughout the world. The country of Angola officially replaced CQ with artemisinin-based combination therapy (ACT) as a first-line treatment in 2006, but malaria cases and deaths have recently been rising. Many classic resistance mutations are relevant for the efficacy of currently available drugs, making it important to continue monitoring their frequency in Angola. METHODS: Plasmodium falciparum DNA was sampled from the blood of 50 hospital patients in Cabinda, Angola from October-December of 2018. Each infection was genotyped for 13 alleles in the genes crt, mdr1, dhps, dhfr, and kelch13, which are collectively involved in resistance to six common anti-malarials. To compare frequency patterns over time, P. falciparum genotype data were also collated from studies published from across Angola in the last two decades. RESULTS: The two most important alleles for CQ resistance, crt 76T and mdr1 86Y, were found at respective frequencies of 71.4% and 6.5%. Historical data suggest that mdr1 N86 has been steadily replacing 86Y throughout Angola in the last decade, while the frequency of crt 76T has been more variable across studies. Over a third of new samples from Cabinda were 'quintuple mutants' for SP resistance in dhfr/dhps, with a sixth mutation at dhps A581G present at 9.6% frequency. The markers dhfr 51I, dhfr 108N, and dhps 437G have been nearly fixed in Angola since the early 2000s, whereas dhfr 59R may have risen to high frequency more recently. Finally, no non-synonymous polymorphisms were detected in kelch13, which is involved in artemisinin resistance in Southeast Asia. CONCLUSIONS: Genetic markers of P. falciparum resistance to CQ are likely declining in frequency in Angola, consistent with the official discontinuation of CQ in 2006. The high frequency of multiple genetic markers of SP resistance is consistent with the continued public and private use of SP. In the future, more complete haplotype data from mdr1, dhfr, and dhps will be critical for understanding the changing efficacy of multiple anti-malarial drugs. These data can be used to support effective drug policy decisions in Angola.

Quantitative evolutionary dynamics using high-resolution lineage tracking.

Evolution of large asexual cell populations underlies ∼30% of deaths worldwide, including those caused by bacteria, fungi, parasites, and cancer. However, the dynamics underlying these evolutionary processes remain poorly understood because they involve many competing beneficial lineages, most of which never rise above extremely low frequencies in the population. To observe these normally hidden evolutionary dynamics, we constructed a sequencing-based ultra high-resolution lineage tracking system in Saccharomyces cerevisiae that allowed us to monitor the relative frequencies of ∼500,000 lineages simultaneously. In contrast to some expectations, we found that the spectrum of fitness effects of beneficial mutations is neither exponential nor monotonic. Early adaptation is a predictable consequence of this spectrum and is strikingly reproducible, but the initial small-effect mutations are soon outcompeted by rarer large-effect mutations that result in variability between replicates. These results suggest that early evolutionary dynamics may be deterministic for a period of time before stochastic effects become important.

Tripolar chromosome segregation drives the association between maternal genotype at variants spanning PLK4 and aneuploidy in human preimplantation embryos.

Aneuploidy is prevalent in human embryos and is the leading cause of pregnancy loss. Many aneuploidies arise during oogenesis, increasing with maternal age. Superimposed on these meiotic aneuploidies are frequent errors occurring during early mitotic divisions, contributing to widespread chromosomal mosaicism. Here we reanalyzed a published dataset comprising preimplantation genetic testing for aneuploidy in 24 653 blastomere biopsies from day-3 cleavage-stage embryos, as well as 17 051 trophectoderm biopsies from day-5 blastocysts. We focused on complex abnormalities that affected multiple chromosomes simultaneously, seeking insights into their formation. In addition to well-described patterns such as triploidy and haploidy, we identified 4.7% of blastomeres possessing characteristic hypodiploid karyotypes. We inferred this signature to have arisen from tripolar chromosome segregation in normally fertilized diploid zygotes or their descendant diploid cells. This could occur via segregation on a tripolar mitotic spindle or by rapid sequential bipolar mitoses without an intervening S-phase. Both models are consistent with time-lapse data from an intersecting set of 77 cleavage-stage embryos, which were enriched for the tripolar signature among embryos exhibiting abnormal cleavage. The tripolar signature was strongly associated with common maternal genetic variants spanning the centrosomal regulator PLK4, driving the association we previously reported with overall mitotic errors. Our findings are consistent with the known capacity of PLK4 to induce tripolar mitosis or precocious M-phase upon dysregulation. Together, our data support tripolar chromosome segregation as a key mechanism generating complex aneuploidy in cleavage-stage embryos and implicate maternal genotype at a quantitative trait locus spanning PLK4 as a factor influencing its occurrence.

Deep sequencing of natural and experimental populations of Drosophila melanogaster reveals biases in the spectrum of new mutations.

Mutations provide the raw material of evolution, and thus our ability to study evolution depends fundamentally on having precise measurements of mutational rates and patterns. We generate a data set for this purpose using (1) de novo mutations from mutation accumulation experiments and (2) extremely rare polymorphisms from natural populations. The first, mutation accumulation (MA) lines are the product of maintaining flies in tiny populations for many generations, therefore rendering natural selection ineffective and allowing new mutations to accrue in the genome. The second, rare genetic variation from natural populations allows the study of mutation because extremely rare polymorphisms are relatively unaffected by the filter of natural selection. We use both methods in Drosophila melanogaster, first generating our own novel data set of sequenced MA lines and performing a meta-analysis of all published MA mutations (∼2000 events) and then identifying a high quality set of ∼70,000 extremely rare (≤0.1%) polymorphisms that are fully validated with resequencing. We use these data sets to precisely measure mutational rates and patterns. Highlights of our results include: a high rate of multinucleotide mutation events at both short (∼5 bp) and long (∼1 kb) genomic distances, showing that mutation drives GC content lower in already GC-poor regions, and using our precise context-dependent mutation rates to predict long-term evolutionary patterns at synonymous sites. We also show that de novo mutations from independent MA experiments display similar patterns of single nucleotide mutation and well match the patterns of mutation found in natural populations.

Seeking Goldilocks During Evolution of Drug Resistance.

Speciation can occur when a population is split and the resulting subpopulations evolve independently, accumulating mutations over time that make them incompatible with one another. It is thought that such incompatible mutations, known as Bateson-Dobzhansky-Muller (BDM) incompatibilities, may arise when the two populations face different environments, which impose different selective pressures. However, a new study in PLOS Biology by Ono et al. finds that the first-step mutations selected in yeast populations evolving in parallel in the presence of the antifungal drug nystatin are frequently incompatible with one another. This incompatibility is environment dependent, such that the combination of two incompatible alleles can become advantageous under increasing drug concentrations. This suggests that the activity for the affected pathway must have an optimum level, the value of which varies according to the drug concentration. It is likely that many biological processes similarly have an optimum under a given environment and many single-step adaptive ways to reach it; thus, not only should BDM incompatibilities commonly arise during parallel evolution, they might be virtually inevitable, as the combination of two such steps is likely to overshoot the optimum.

High rate of adaptation of mammalian proteins that interact with Plasmodium and related parasites.

Plasmodium parasites, along with their Piroplasm relatives, have caused malaria-like illnesses in terrestrial mammals for millions of years. Several Plasmodium-protective alleles have recently evolved in human populations, but little is known about host adaptation to blood parasites over deeper evolutionary timescales. In this work, we analyze mammalian adaptation in ~500 Plasmodium- or Piroplasm- interacting proteins (PPIPs) manually curated from the scientific literature. We show that (i) PPIPs are enriched for both immune functions and pleiotropy with other pathogens, and (ii) the rate of adaptation across mammals is significantly elevated in PPIPs, compared to carefully matched control proteins. PPIPs with high pathogen pleiotropy show the strongest signatures of adaptation, but this pattern is fully explained by their immune enrichment. Several pieces of evidence suggest that blood parasites specifically have imposed selection on PPIPs. First, even non-immune PPIPs that lack interactions with other pathogens have adapted at twice the rate of matched controls. Second, PPIP adaptation is linked to high expression in the liver, a critical organ in the parasite life cycle. Finally, our detailed investigation of alpha-spectrin, a major red blood cell membrane protein, shows that domains with particularly high rates of adaptation are those known to interact specifically with P. falciparum. Overall, we show that host proteins that interact with Plasmodium and Piroplasm parasites have experienced elevated rates of adaptation across mammals, and provide evidence that some of this adaptation has likely been driven by blood parasites.

Extremely Rare Polymorphisms in Saccharomyces cerevisiae Allow Inference of the Mutational Spectrum.

The characterization of mutational spectra is usually carried out in one of three ways-by direct observation through mutation accumulation (MA) experiments, through parent-offspring sequencing, or by indirect inference from sequence data. Direct observations of spontaneous mutations with MA experiments are limited, given (i) the rarity of spontaneous mutations, (ii) applicability only to laboratory model species with short generation times, and (iii) the possibility that mutational spectra under lab conditions might be different from those observed in nature. Trio sequencing is an elegant solution, but it is not applicable in all organisms. Indirect inference, usually from divergence data, faces no such technical limitations, but rely upon critical assumptions regarding the strength of natural selection that are likely to be violated. Ideally, new mutational events would be directly observed before the biased filter of selection, and without the technical limitations common to lab experiments. One approach is to identify very young mutations from population sequencing data. Here we do so by leveraging two characteristics common to all new mutations-new mutations are necessarily rare in the population, and absent in the genomes of immediate relatives. From 132 clinical yeast strains, we were able to identify 1,425 putatively new mutations and show that they exhibit extremely low signatures of selection, as well as display a mutational spectrum that is similar to that identified by a large scale MA experiment. We verify that population sequencing data are a potential wealth of information for inferring mutational spectra, and should be considered for analysis where MA experiments are infeasible or especially tedious.

Seasonally fluctuating selection can maintain polymorphism at many loci via segregation lift.

Most natural populations are affected by seasonal changes in temperature, rainfall, or resource availability. Seasonally fluctuating selection could potentially make a large contribution to maintaining genetic polymorphism in populations. However, previous theory suggests that the conditions for multilocus polymorphism are restrictive. Here, we explore a more general class of models with multilocus seasonally fluctuating selection in diploids. In these models, the multilocus genotype is mapped to fitness in two steps. The first mapping is additive across loci and accounts for the relative contributions of heterozygous and homozygous loci-that is, dominance. The second step uses a nonlinear fitness function to account for the strength of selection and epistasis. Using mathematical analysis and individual-based simulations, we show that stable polymorphism at many loci is possible if currently favored alleles are sufficiently dominant. This general mechanism, which we call "segregation lift," requires seasonal changes in dominance, a phenomenon that may arise naturally in situations with antagonistic pleiotropy and seasonal changes in the relative importance of traits for fitness. Segregation lift works best under diminishing-returns epistasis, is not affected by problems of genetic load, and is robust to differences in parameters across loci and seasons. Under segregation lift, loci can exhibit conspicuous seasonal allele-frequency fluctuations, but often fluctuations may be small and hard to detect. An important direction for future work is to formally test for segregation lift in empirical data and to quantify its contribution to maintaining genetic variation in natural populations.

A spatio-temporal assessment of simian/human immunodeficiency virus (SHIV) evolution reveals a highly dynamic process within the host.

The process by which drug-resistant HIV-1 arises and spreads spatially within an infected individual is poorly understood. Studies have found variable results relating how HIV-1 in the blood differs from virus sampled in tissues, offering conflicting findings about whether HIV-1 throughout the body is homogeneously distributed. However, most of these studies sample only two compartments and few have data from multiple time points. To directly measure how drug resistance spreads within a host and to assess how spatial structure impacts its emergence, we examined serial sequences from four macaques infected with RT-SHIVmne027, a simian immunodeficiency virus encoding HIV-1 reverse transcriptase (RT), and treated with RT inhibitors. Both viral DNA and RNA (vDNA and vRNA) were isolated from the blood (including plasma and peripheral blood mononuclear cells), lymph nodes, gut, and vagina at a median of four time points and RT was characterized via single-genome sequencing. The resulting sequences reveal a dynamic system in which vRNA rapidly acquires drug resistance concomitantly across compartments through multiple independent mutations. Fast migration results in the same viral genotypes present across compartments, but not so fast as to equilibrate their frequencies immediately. The blood and lymph nodes were found to be compartmentalized rarely, while both the blood and lymph node were more frequently different from mucosal tissues. This study suggests that even oft-sampled blood does not fully capture the viral dynamics in other parts of the body, especially the gut where vRNA turnover was faster than the plasma and vDNA retained fewer wild-type viruses than other sampled compartments. Our findings of transient compartmentalization across multiple tissues may help explain the varied results of previous compartmentalization studies in HIV-1.

Rapid seasonal evolution in innate immunity of wild Drosophila melanogaster.

Understanding the rate of evolutionary change and the genetic architecture that facilitates rapid adaptation is a current challenge in evolutionary biology. Comparative studies show that genes with immune function are among the most rapidly evolving genes across a range of taxa. Here, we use immune defence in natural populations of Drosophila melanogaster to understand the rate of evolution in natural populations and the genetics underlying rapid change. We probed the immune system using the natural pathogens Enterococcus faecalis and Providencia rettgeri to measure post-infection survival and bacterial load of wild D. melanogaster populations collected across seasonal time along a latitudinal transect along eastern North America (Massachusetts, Pennsylvania and Virginia). There are pronounced and repeatable changes in the immune response over the approximately 10 generations between spring and autumn collections, with a significant but less distinct difference observed among geographical locations. Genes with known immune function are not enriched among alleles that cycle with seasonal time, but the immune function of a subset of seasonally cycling alleles in immune genes was tested using reconstructed outbred populations. We find that flies containing seasonal alleles in Thioester-containing protein 3 (Tep3) have different functional responses to infection and that epistatic interactions among seasonal Tep3 and Drosomycin-like 6 (Dro6) alleles underlie the immune phenotypes observed in natural populations. This rapid, cyclic response to seasonal environmental pressure broadens our understanding of the complex ecological and genetic interactions determining the evolution of immune defence in natural populations.