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The effective population size (Ne) is a key parameter to quantify the magnitude of genetic drift and inbreeding, with important implications in human evolution. The increasing availability of high-density genetic markers allows the estimation of historical changes in Ne across time using measures of genome diversity or linkage disequilibrium between markers. Directional selection is expected to reduce diversity and Ne, and this reduction is modulated by the heterogeneity of the genome in terms of recombination rate. Here we investigate by computer simulations the consequences of selection (both positive and negative) and recombination rate heterogeneity in the estimation of historical Ne. We also investigate the relationship between diversity parameters and Ne across the different regions of the genome using human marker data. We show that the estimates of historical Ne obtained from linkage disequilibrium between markers (NeLD) are virtually unaffected by selection. In contrast, those estimates obtained by coalescence mutation-recombination-based methods can be strongly affected by it, which could have important consequences for the estimation of human demography. The simulation results are supported by the analysis of human data. The estimates of NeLD obtained for particular genomic regions do not correlate, or they do it very weakly, with recombination rate, nucleotide diversity, proportion of polymorphic sites, background selection statistic, minor allele frequency of SNPs, loss of function and missense variants and gene density. This suggests that NeLD measures mainly reflect demographic changes in population size across generations., Author summary The inference of the demographic history of populations is of great relevance in evolutionary biology. This inference can be made from genomic data using coalescence methods or linkage disequilibrium methods. However, the assessment of these methods is usually made assuming neutrality (absence of selection). Here we show by computer simulations and analyses of human data that the estimates of historical effective population size obtained from linkage disequilibrium between markers are virtually unaffected by natural selection, either positive or negative. In contrast, estimates obtained by coalescence mutation-recombination-based methods can be strongly affected by it, which could have important consequences for recent estimations of human demography.

Insecticide resistance in Anopheles mosquitoes is a major obstacle in maintaining the momentum in reducing the malaria burden; mitigating strategies require improved understanding of the underlying mechanisms. Mutations in the target site of insecticides (the voltage gated sodium channel for the most widely used pyrethroid class) and over-expression of detoxification enzymes are commonly reported, but their relative contribution to phenotypic resistance remain poorly understood. Here we present a genome editing pipeline to introduce single nucleotide polymorphisms in An. gambiae which we have used to study the effect of the classical kdr mutation L1014F (L995F based on An. gambiae numbering), one of the most widely distributed resistance alleles. Introduction of 1014F in an otherwise fully susceptible genetic background increased levels of resistance to all tested pyrethroids and DDT ranging from 9.9-fold for permethrin to >24-fold for DDT. The introduction of the 1014F allele was sufficient to reduce mortality of mosquitoes after exposure to deltamethrin treated bednets, even as the only resistance mechanism present. When 1014F was combined with over-expression of glutathione transferase Gste2, resistance to permethrin increased further demonstrating the critical combined effect between target site resistance and detoxification enzymes in vivo. We also show that mosquitoes carrying the 1014F allele in homozygosity showed fitness disadvantages including increased mortality at the larval stage and a reduction in fecundity and adult longevity, which can have consequences for the strength of selection that will apply to this allele in the field., Author summary Escalation of pyrethroid resistance in Anopheles mosquitoes threatens to reduce the effectiveness of our most important tools in malaria control. Studying the mechanisms underlying insecticide resistance is critical to design mitigation strategies. Here, using genome modified mosquitoes, we functionally characterize the most prevalent mutation in resistant mosquitoes, showing that it confers substantial levels of resistance to all tested pyrethroids and undermines the performance of pyrethroid-treated nets. Furthermore, we show that combining this mutation with elevated levels of a detoxification enzyme further increases resistance. The pipeline we have developed provides a robust approach to quantifying the contribution of different combinations of resistance mechanisms to the overall phenotype, providing the missing link between resistance monitoring and predictions of resistance impact.

Synthetic gene drive constructs could, in principle, provide the basis for highly efficient interventions to control disease vectors and other pest species. This efficiency derives in part from leveraging natural processes of dispersal and gene flow to spread the construct and its impacts from one population to another. However, sometimes (for example, with invasive species) only specific populations are in need of control, and impacts on non-target populations would be undesirable. Many gene drive designs use nucleases that recognise and cleave specific genomic sequences, and one way to restrict their spread would be to exploit sequence differences between target and non-target populations. In this paper we propose and model a series of low threshold double drive designs for population suppression, each consisting of two constructs, one imposing a reproductive load on the population and the other inserted into a differentiated locus and controlling the drive of the first. Simple deterministic, discrete-generation computer simulations are used to assess the alternative designs. We find that the simplest double drive designs are significantly more robust to pre-existing cleavage resistance at the differentiated locus than single drive designs, and that more complex designs incorporating sex ratio distortion can be more efficient still, even allowing for successful control when the differentiated locus is neutral and there is up to 50% pre-existing resistance in the target population. Similar designs can also be used for population replacement, with similar benefits. A population genomic analysis of CRISPR PAM sites in island and mainland populations of the malaria mosquito Anopheles gambiae indicates that the differentiation needed for our methods to work can exist in nature. Double drives should be considered when efficient but localised population genetic control is needed and there is some genetic differentiation between target and non-target populations., Author summary Some disease vectors, invasive species, and other pests cannot be satisfactorily controlled with existing interventions, and new methods are required. Synthetic gene drive systems that are able to spread though populations because they are inherited at a greater-than-Mendelian rate have the potential to form the basis for new, highly efficient pest control measures. The most efficient such strategies use natural gene flow to spread a construct throughout a species’ range, but if control is only desired in a particular location then these approaches may not be appropriate. As some of the most promising gene drive designs use nucleases to target specific DNA sequences, it ought to be possible to exploit sequence differences between target and non-target populations to restrict the spread and impact of a gene drive. In this paper we propose using two-construct “double drive” designs that exploit pre-existing sequence differences between target and non-target populations. Our approaches maintain the efficiencies associated with only small release rates being needed and can work if the differentiated locus is selectively neutral and if the differentiation is far from complete, and therefore expand the range of options to be considered in developing genetic approaches to control pest species.

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., Author summary Whether hard versus soft sweeps dominate adaptation has long been a matter of great debate. Recently, we proposed novel statistics that can identify and differentiate hard and soft sweeps and found that soft sweeps are surprisingly common in North American Drosophila melanogaster. Among our top ranking candidates are three well-known soft sweeps at the loci Cyp6g1, Ace, and CHKov1. Recently, Harris et al. 2018 have claimed that the selective sweeps we identified are false positives and are more likely to be explained by an admixture demographic history. Moreover, they claim that these neutral non-sweeps are more likely to be hard sweeps rather soft sweeps. Here we re-assess our and Harris et al’s work and find that given a reasonably well-fitting demographic model, soft sweeps are a dominant mode of adaptation in North American Drosophila melanogaster.

RNA regulation is essential to successful reproduction. Messenger RNAs delivered from parent to progeny govern early embryonic development. RNA-binding proteins (RBPs) are the key effectors of this process, regulating the translation and stability of parental transcripts to control cell fate specification events prior to zygotic gene activation. The KH-domain RBP MEX-3 is conserved from nematode to human. It was first discovered in Caenorhabditis elegans, where it is essential for anterior cell fate and embryo viability. Here, we show that loss of the endogenous mex-3 3´UTR disrupts its germline expression pattern. An allelic series of 3´UTR deletion variants identify repressing regions of the UTR and demonstrate that repression is not precisely coupled to reproductive success. We also show that several RBPs regulate mex-3 mRNA through its 3´UTR to define its unique germline spatiotemporal expression pattern. Additionally, we find that both poly(A) tail length control and the translation initiation factor IFE-3 contribute to its expression pattern. Together, our results establish the importance of the mex-3 3´UTR to reproductive health and its expression in the germline. Our results suggest that additional mechanisms control MEX-3 function when 3´UTR regulation is compromised., Author summary In sexually reproducing organisms, germ cells undergo meiosis and differentiate to form oocytes or sperm. Coordination of this process requires a gene regulatory program that acts while the genome is undergoing chromatin condensation. As such, RNA regulatory pathways are an important contributor. The germline of the nematode Caenorhabditis elegans is a suitable model system to study germ cell differentiation. Several RNA-binding proteins (RBPs) coordinate each transition in the germline such as the transition from mitosis to meiosis. MEX-3 is a conserved RNA-binding protein found in most animals including humans. In C. elegans, MEX-3 displays a highly restricted pattern of expression. Here, we define the importance of the 3´UTR in regulating MEX-3 expression pattern in vivo and characterize the RNA-binding proteins involved in this regulation. Our results show that deleting various mex-3 3´UTR regions alter the pattern of expression in the germline in various ways. These mutations also reduced—but did not eliminate—reproductive capacity. Finally, we demonstrate that multiple post-transcriptional mechanisms control MEX-3 levels in different domains of the germline. Our data suggest that coordination of MEX-3 activity requires multiple layers of regulation to ensure reproductive robustness.

A thorough reconstruction of historical processes is essential for a comprehensive understanding of the mechanisms shaping patterns of genetic diversity. Indeed, past and current conditions influencing effective population size have important evolutionary implications for the efficacy of selection, increased accumulation of deleterious mutations, and loss of adaptive potential. Here, we gather extensive genome-wide data that represent the extant diversity of the Coho salmon (Oncorhynchus kisutch) to address two objectives. We demonstrate that a single glacial refugium is the source of most of the present-day genetic diversity, with detectable inputs from a putative secondary micro-refugium. We found statistical support for a scenario whereby ancestral populations located south of the ice sheets expanded recently, swamping out most of the diversity from other putative micro-refugia. Demographic inferences revealed that genetic diversity was also affected by linked selection in large parts of the genome. Moreover, we demonstrate that the recent demographic history of this species generated regional differences in the load of deleterious mutations among populations, a finding that mirrors recent results from human populations and provides increased support for models of expansion load. We propose that insights from these historical inferences should be better integrated in conservation planning of wild organisms, which currently focuses largely on neutral genetic diversity and local adaptation, with the role of potentially maladaptive variation being generally ignored., Author summary Reconstruction of a species’ past demographic history from genetic data can highlight historical factors that have shaped the distribution of genetic diversity along its genome and its geographic range. Here, we combine genotyping-by-sequencing with demographic modelling to address these issues in the Coho salmon, a Pacific salmon of conservation concern in some parts of its range, notably in the south. Our demographic reconstructions reveal a linear decrease in genetic diversity toward the north of the species range, supporting the hypothesis of a northern route of postglacial recolonization from a single major southern refugium. As predicted by theory, we also observed a higher proportion of deleterious mutations in the most distant populations from this refugium. Beyond this general pattern, among-site variation in the proportion of deleterious mutations is consistent with different local trends in effective population sizes. Our results highlight the potential importance of understanding historical factors that have shaped geographic patterns of the distribution of deleterious mutations in order to implement effective management programs for the conservation of wild populations. Such fundamental knowledge of human historical demography is now having major impacts on health sciences, and we argue it is time to integrate such approaches in conservation science as well.

Coalescent simulations are widely used to examine the effects of evolution and demographic history on the genetic makeup of populations. Thanks to recent progress in algorithms and data structures, simulators such as the widely-used msprime now provide genome-wide simulations for millions of individuals. However, this software relies on classic coalescent theory and its assumptions that sample sizes are small and that the region being simulated is short. Here we show that coalescent simulations of long regions of the genome exhibit large biases in identity-by-descent (IBD), long-range linkage disequilibrium (LD), and ancestry patterns, particularly when the sample size is large. We present a Wright-Fisher extension to msprime, and show that it produces more realistic distributions of IBD, LD, and ancestry proportions, while also addressing more subtle biases of the coalescent. Further, these extensions are more computationally efficient than state-of-the-art coalescent simulations when simulating long regions, including whole-genome data. For shorter regions, efficiency can be maintained via a hybrid model which simulates the recent past under the Wright-Fisher model and uses coalescent simulations in the distant past., Author summary Coalescent theory has provided deep theoretical insight into patterns of human diversity. Implementations of coalescent models in simulation software such as ms have further provided tools to interpret thousands of genomic studies. Recent technical progress has allowed for a dramatic increase in the scale at which genomes can be both measured and simulated, opening up opportunities for a finer understanding of evolutionary biology. However, we show that coalescent simulations of long regions of the genome exhibit large biases in sample relatedness, distorting haplotype sharing and ancestry patterns in simulated cohorts. We trace these biases to basic assumptions of the coalescent model, and show how the assumptions can be relaxed to provide a better description of the observed patterns of genetic polymorphism at a fraction of the computational cost.

The ability to reproduce is essential in all branches of life. In metazoans, this process is initiated by formation of the germline, a group of cells that are destined to form the future gonads, the tissue that will produce the gametes. The molecular mechanisms underlying germline formation differs between species. In zebrafish, development of the germline is dependent on the specification, migration and proliferation of progenitors called the primordial germ cells (PGCs). PGC specification is dependent on a maternally provided cytoplasmic complex of ribonucleoproteins (RNPs), the germplasm. Here, we show that the conserved RNA-binding protein (RBP), Igf2bp3, has an essential role during early embryonic development and germline development. Loss of Igf2bp3 leads to an expanded yolk syncytial layer (YSL) in early embryos, reduced germline RNA expression, and mis-regulated germline development. We show that loss of maternal Igf2bp3 function results in translational de-regulation of a Nodal reporter during the mid-blastula transition. Furthermore, maternal igf2bp3 mutants exhibit reduced expression of germplasm transcripts, defects in chemokine guidance, abnormal PGC behavior and germ cell death. Consistently, adult igf2bp3 mutants show a strong male bias. Our findings suggest that Igf2bp3 is essential for normal embryonic and germline development, and acts as a key regulator of sexual development., Author summary Animals develop from a single egg cell that is fertilised by sperm, to form various tissues and organs. How the different tissues form is still not fully understood. In particular, we don’t know precisely how organisms develop to be males or females, or how balanced sex ratios are maintained in populations. However, if these processes are disrupted, either too many males or too many females could arise in populations, which can lead to failure to produce the next generation, eventually resulting in extinction of the species. Therefore, identifying the factors that allow these processes to happen properly and deciphering how they function is crucial. We have identified a protein called Igf2bp3 in the tropical fish, Zebrafish, which if disabled, leads to most of the zebrafish developing as males. In addition, the few females that do make it to adulthood produce eggs that are defective, leading to abnormal progeny that generally do not survive. Our work identifies an important factor in fish that determines normal development and balanced sex ratios. Igf2bp3 has counterparts in other animals and therefore, our work can shed light on how these processes are controlled across organisms.

In many species a fundamental feature of genetic diversity is that genetic similarity decays with geographic distance; however, this relationship is often complex, and may vary across space and time. Methods to uncover and visualize such relationships have widespread use for analyses in molecular ecology, conservation genetics, evolutionary genetics, and human genetics. While several frameworks exist, a promising approach is to infer maps of how migration rates vary across geographic space. Such maps could, in principle, be estimated across time to reveal the full complexity of population histories. Here, we take a step in this direction: we present a method to infer maps of population sizes and migration rates associated with different time periods from a matrix of genetic similarity between every pair of individuals. Specifically, genetic similarity is measured by counting the number of long segments of haplotype sharing (also known as identity-by-descent tracts). By varying the length of these segments we obtain parameter estimates associated with different time periods. Using simulations, we show that the method can reveal time-varying migration rates and population sizes, including changes that are not detectable when using a similar method that ignores haplotypic structure. We apply the method to a dataset of contemporary European individuals (POPRES), and provide an integrated analysis of recent population structure and growth over the last ∼3,000 years in Europe., Author summary We introduce a novel statistical method to infer migration rates and population sizes across space in recent time periods. Our approach builds upon the previously developed EEMS method, which infers effective migration rates under a dense lattice. Similarly, we infer demographic parameters under a lattice and use a (Voronoi) prior to regularize parameters of the model. However, our method differs from EEMS in a few key respects. First, we use the coalescent model parameterized by migration rates and population sizes while EEMS uses a resistance model. As another key difference, our method uses haplotype data while EEMS uses the average genetic distance. A consequence of using haplotype data is that our method can separately estimate migration rates and population sizes, which in essence is done by using a recombination rate map to calibrate the decay of haplotypes over time. An additional useful feature of haplotype data is that, by varying the lengths analyzed, we can infer demography associated with different recent time periods. We call our method MAPS for estimating Migration And Population-size Surfaces. To illustrate MAPS on real data, we analyze a genome-wide SNP dataset on 2224 individuals of European ancestry.

Since the initial description of the genomic patterns expected under models of positive selection acting on standing genetic variation and on multiple beneficial mutations—so-called soft selective sweeps—researchers have sought to identify these patterns in natural population data. Indeed, over the past two years, large-scale data analyses have argued that soft sweeps are pervasive across organisms of very different effective population size and mutation rate—humans, Drosophila, and HIV. Yet, others have evaluated the relevance of these models to natural populations, as well as the identifiability of the models relative to other known population-level processes, arguing that soft sweeps are likely to be rare. Here, we look to reconcile these opposing results by carefully evaluating three recent studies and their underlying methodologies. Using population genetic theory, as well as extensive simulation, we find that all three examples are prone to extremely high false-positive rates, incorrectly identifying soft sweeps under both hard sweep and neutral models. Furthermore, we demonstrate that well-fit demographic histories combined with rare hard sweeps serve as the more parsimonious explanation. These findings represent a necessary response to the growing tendency of invoking parameter-heavy, assumption-laden models of pervasive positive selection, and neglecting best practices regarding the construction of proper demographic null models., Author summary A long-standing debate in evolutionary biology revolves around the role of selective vs. stochastic processes in driving molecular evolution and shaping genetic variation. With the advent of genomics, genome-wide polymorphism data have been utilized to characterize these processes, with a major interest in describing the fraction of genomic variation shaped by positive selection. These genomic scans were initially focused around a hard sweep model, in which selection acts upon rare, newly arising beneficial mutations. Recent years have seen the description of sweeps occurring from both standing and rapidly recurring beneficial mutations, collectively known as soft sweeps. However, common to both hard and soft sweeps is the difficulty in distinguishing these effects from neutral demographic patterns, and disentangling these processes has remained an important field of study within population genetics. Despite this, there is a recent and troubling tendency to neglect these demographic considerations, and to naively fit sweep models to genomic data. Recent realizations of such efforts have resulted in the claim that soft sweeps play a dominant role in shaping genomic variation and in driving adaptation across diverse branches of the tree of life. Here, we reanalyze these findings and demonstrate that a more careful consideration of neutral processes results in highly differing conclusions.

Sex-biased demographic events (“sex-bias”) involve unequal numbers of females and males. These events are typically inferred from the relative amount of X-chromosomal to autosomal genetic variation and have led to conflicting conclusions about human demographic history. Though population size changes alter the relative amount of X-chromosomal to autosomal genetic diversity even in the absence of sex-bias, this has generally not been accounted for in sex-bias estimators to date. Here, we present a novel method to identify sex-bias from genetic sequence data that models population size changes and estimates the female fraction of the effective population size during each time epoch. Compared to recent sex-bias inference methods, our approach can detect sex-bias that changes on a single population branch without requiring data from an outgroup or knowledge of divergence events. When applied to simulated data, conventional sex-bias estimators are biased by population size changes, especially recent growth or bottlenecks, while our estimator is unbiased. We next apply our method to high-coverage exome data from the 1000 Genomes Project and estimate a male bias in Yorubans (47% female) and Europeans (44%), possibly due to stronger background selection on the X chromosome than on the autosomes. Finally, we apply our method to the 1000 Genomes Project Phase 3 high-coverage Complete Genomics whole-genome data and estimate a female bias in Yorubans (63% female), Europeans (84%), Punjabis (82%), as well as Peruvians (56%), and a male bias in the Southern Han Chinese (45%). Our method additionally identifies a male-biased migration out of Africa based on data from Europeans (20% female). Our results demonstrate that modeling population size change is necessary to estimate sex-bias parameters accurately. Our approach gives insight into signatures of sex-bias in sexual species, and the demographic models it produces can serve as more accurate null models for tests of selection., Author summary Sex-biased demographic events involve unequal numbers of females and males, and is referred to as “sex-bias”. In humans, short-range migrations (e.g., due to marriage practices) are known to be sex-biased, and some long-range migrations, such as the one out of Africa, are hypothesized to be sex-biased. The recent availability of large-scale genomic sequencing data provides a unique opportunity to study sex-bias in human populations. However, existing sex-bias methods do not account for population size changes, like expansions and bottlenecks, or can only estimate a single sex-bias parameter on a population branch, which can lead to incorrect conclusions. We developed a sex-bias method which explicitly models population size changes, and we show that it outperforms competing methods on simulated data. When applied to human genetic data, our method identifies an overall female sex-bias in globally-distributed populations and a male-biased bottleneck in Europeans. Our method can also be used to assess sex-bias in other sexual species.

Populations change in size over time due to factors such as population growth, migration, bottleneck events, natural disasters, and disease. The historical effective size of a population affects the power and resolution of genetic association studies. For admixed populations, it is not only the overall effective population size that is of interest, but also the effective sizes of the component ancestral populations. We use identity by descent and local ancestry inferred from genome-wide genetic data to estimate overall and ancestry-specific effective population size during the past hundred generations for nine admixed American populations from the Hispanic Community Health Study/Study of Latinos, and for African-American and European-American populations from two US cities. In these populations, the estimated pre-admixture effective sizes of the ancestral populations vary by sampled population, suggesting that the ancestors of different sampled populations were drawn from different sub-populations. In addition, we estimate that overall effective population sizes dropped substantially in the generations immediately after the commencement of European and African immigration, reaching a minimum around 12 generations ago, but rebounded within a small number of generations afterwards. Of the populations that we considered, the population of individuals originating from Puerto Rico has the smallest bottleneck size of one thousand, while the Pittsburgh African-American population has the largest bottleneck size of two hundred thousand., Author summary Using genome-wide genetic data on several hundred individuals sampled from a population, we can estimate the current effective size of the population and the changes in effective size that have occurred over the past hundred generations. Many populations in the Americas are admixed, having ancestry from Europe, Africa, and the Americas. In such cases, one can learn not only about the effective population size history of the admixed population since admixture, but also about the effective population size histories of the contributing ancestral populations. In this paper we develop methodology for estimating past effective population size and analyze data from Hispanic, African-American, and European-American populations resident in the United States. We observe differences between populations in their historical effective sizes. These differences are useful for understanding differences in disease incidence between populations and for identifying populations that will maximize power in genetic association studies.

The relative female and male contributions to demography are of great importance to better understand the history and dynamics of populations. While earlier studies relied on uniparental markers to investigate sex-specific questions, the increasing amount of sequence data now enables us to take advantage of tens to hundreds of thousands of independent loci from autosomes and the X chromosome. Here, we develop a novel method to estimate effective sex ratios or ESR (defined as the female proportion of the effective population) from allele count data for each branch of a rooted tree topology that summarizes the history of the populations of interest. Our method relies on Kimura’s time-dependent diffusion approximation for genetic drift, and is based on a hierarchical Bayesian model to integrate over the allele frequencies along the branches. We show via simulations that parameters are inferred robustly, even under scenarios that violate some of the model assumptions. Analyzing bovine SNP data, we infer a strongly female-biased ESR in both dairy and beef cattle, as expected from the underlying breeding scheme. Conversely, we observe a strongly male-biased ESR in early domestication times, consistent with an easier taming and management of cows, and/or introgression from wild auroch males, that would both cause a relative increase in male effective population size. In humans, analyzing a subsample of non-African populations, we find a male-biased ESR in Oceanians that may reflect complex marriage patterns in Aboriginal Australians. Because our approach relies on allele count data, it may be applied on a wide range of species., Author summary The history of populations and their social organization is often intricate due to breeding structures, migration patterns or population bottlenecks. Estimation of the female proportion of the effective population (sex ratio) is therefore important to better understand this underlying social structure and dynamics. This question has been mainly investigated so far by comparing genetic variation of mitochondrial DNA and the Y chromosome, two uniparentally inherited markers that reflect the demographic history of females and males, respectively. To overcome the intrinsic limitations of these genetic markers, and to take advantage of the increasing amount of sequence data, we propose a new approach that uses large numbers of independent polymorphisms from autosomes and the X chromosome to estimate sex ratios, throughout the history of populations. This method allows us to confirm a strongly female-biased sex ratio in modern dairy and beef cattle breeds. Yet, we find a strongly male-biased sex ratio during domestication times, consistent with an easier taming and management of cows, and/or introgression from wild auroch males. Analyzing human data from a sample of non-African populations, we find a male bias in Oceanians, possibly indicating complex marriage patterns among Aboriginal Australian groups.

Evolutionary responses to environmental change depend on the time available for adaptation before environmental degradation leads to extinction. Explicit tests of this relationship are limited to microbes where adaptation usually depends on the sequential fixation of de novo mutations, excluding standing variation for genotype-by-environment fitness interactions that should be key for most natural species. For natural species evolving from standing genetic variation, adaptation at slower rates of environmental change may be impeded since the best genotypes at the most extreme environments can be lost during evolution due to genetic drift or founder effects. To address this hypothesis, we perform experimental evolution with self-fertilizing populations of the nematode Caenorhabditis elegans and develop an inference model to describe natural selection on extant genotypes under environmental change. Under a sudden environmental change, we find that selection rapidly increases the frequency of genotypes with high fitness in the most extreme environment. In contrast, under a gradual environmental change selection first favors genotypes that are worse at the most extreme environment. We demonstrate with a second set of evolution experiments that, as a consequence of slower environmental change and thus longer periods to reach the most extreme environments, genetic drift and founder effects can lead to the loss of the most beneficial genotypes. We further find that maintenance of standing genetic variation can retard the fixation of the best genotypes in the most extreme environment because of interference between them. Taken together, these results show that slower environmental change can hamper adaptation from standing genetic variation and they support theoretical models indicating that standing variation for genotype-by-environment fitness interactions critically alters the pace and outcome of adaptation under environmental change., Author summary Adaptation under environmental change is expected to depend on the time available for the sequential fixation of mutations, but also on standing variation in genotype-by-environment fitness interactions. In the later circumstances, some genotypes might be initially favored but then disfavored and overtaken by other genotypes that are better at more extreme environments if they were not lost by genetic drift or founder effects in the meantime. We addressed this idea with experimental evolution in Caenorhabditis elegans populations with standing variation for genotype-by-environment fitness interactions and by developing a model to describe natural selection on extant genotypes during experimental evolution. We find that under slower environmental change, the genotypes that are initially selected are not the best at the most extreme environments, and as a consequence, that these best genotypes can be lost due to genetic drift and founder effects. We further find that the longer polymorphism is maintained the more likely that selective interference will reduce the best genotypes to low frequencies and increase the chances for their loss through genetic drift. We conclude that under slower environmental change adaptation will be deterred if populations can only rely on standing genetic variation.

In many insects, the accessory gland, a secretory tissue of the male reproductive system, is essential for male fertility. Male accessory gland is the major source of proteinaceous secretions, collectively called as seminal proteins (or accessory gland proteins), which upon transfer, manipulate the physiology and behavior of mated females. Insect hormones such as ecdysteroids and juvenoids play a key role in accessory gland development and protein synthesis but little is known about underlying molecular players and their mechanism of action. Therefore, in the present study, we examined the roles of hormone-dependent transcription factors (Nuclear Receptors), in accessory gland development, function and male fertility of a genetically tractable insect model, Drosophila melanogaster. First, we carried out an RNAi screen involving 19 hormone receptors, individually and specifically, in a male reproductive tissue (accessory gland) for their requirement in Drosophila male fertility. Subsequently, by using independent RNAi/ dominant negative forms, we show that Ecdysone Receptor (EcR) is essential for male fertility due to its requirement in the normal development of accessory glands in Drosophila: EcR depleted glands fail to make seminal proteins and have dying cells. Further, our data point to a novel ecdysone receptor that does not include Ultraspiracle but is probably comprised of EcR isoforms in Drosophila male accessory glands. Our data suggest that this novel ecdysone receptor might act downstream of homeodomain transcription factor paired (prd) in the male accessory gland. Overall, the study suggests novel ecdysone receptor as an important player in the hormonal regulation of seminal protein production and insect male fertility., Author summary Insects are the major contributors to biodiversity and have economic, agricultural and health importance. This unparalleled abundance of insects, in part, can be attributed to their high reproductive potential. In many insects, proteins derived from the accessory gland, the secretory tissue of male reproductive system, are critical for fertility. The production of these accessory gland proteins is regulated by insect hormones but the underlying mechanisms/molecular players remain poorly understood. Elucidation of the same has potential applications in designing pest control management strategies and to understand the effect of environmental chemicals on reproduction. In view of this, we analyzed the role, if any, of various insect hormone receptors in development and function of the male accessory gland in a genetically tractable insect model, Drosophila melanogaster. Here, we report the involvement of Ecdysone receptor (EcR with novel composition) in Drosophila male fertility. We show that the depletion of this receptor causes cell death in male accessory glands, which fail to produce seminal fluid proteins leading to sterility/sub-fertility of Drosophila males. These findings will find potential applications in designing insect pest control strategies.

Environmental conditions experienced during animal development are thought to have sustained impact on maturation and adult lifespan. Here we show that in the model organism C. elegans developmental rate and adult lifespan depend on larval population density, and that this effect is mediated by excreted small molecules. By using the time point of first egg laying as a marker for full maturity, we found that wildtype hermaphrodites raised under high density conditions developed significantly faster than animals raised in isolation. Population density-dependent acceleration of development (Pdda) was dramatically enhanced in fatty acid β-oxidation mutants that are defective in the biosynthesis of ascarosides, small-molecule signals that induce developmental diapause. In contrast, Pdda is abolished by synthetic ascarosides and steroidal ligands of the nuclear hormone receptor DAF-12. We show that neither ascarosides nor any known steroid hormones are required for Pdda and that another chemical signal mediates this phenotype, in part via the nuclear hormone receptor NHR-8. Our results demonstrate that C. elegans development is regulated by a push-pull mechanism, based on two antagonistic chemical signals: chemosensation of ascarosides slows down development, whereas population-density dependent accumulation of a different chemical signal accelerates development. We further show that the effects of high larval population density persist through adulthood, as C. elegans larvae raised at high densities exhibit significantly reduced adult lifespan and respond differently to exogenous chemical signals compared to larvae raised at low densities, independent of density during adulthood. Our results demonstrate how inter-organismal signaling during development regulates reproductive maturation and longevity., Author summary The nematode C. elegans is one of the most highly developed models for the elucidation of conserved mechanisms connecting environmental cues to the regulation of animal lifespan and development. Surprisingly, the effects of larval population density on developmental timing and adult lifespan have not been investigated, although population density is known to affect developmental dynamics and survival in many species. We here describe a novel phenotype in C. elegans: population density-dependent acceleration of development. That high population density would accelerate development is unexpected, since at high population density accumulation of dauer pheromone, a developmental arrest signal, would be expected to slow down development. However, we found that C. elegans development is regulated by a pull-push mechanism, based on at least two different types of pheromone-like signals: the developmental acceleration signal we first describe in this manuscript, and its antagonist, the dauer pheromone, whose chemical make-up has gradually emerged over the past 10 years. We further show that both developmental acceleration and deceleration are mediated by two nuclear hormone receptors that have close mammalian homologs. Finally we demonstrate that larval population density predetermines adult lifespan in C. elegans hermaphrodites, including responses to hormonal stimuli during adulthood.

Bacteria have evolved various inducible genetic programs to face many types of stress that challenge their growth and survival. Competence is one such program. It enables genetic transformation, a major horizontal gene transfer process. Competence development in liquid cultures of Streptococcus pneumoniae is synchronized within the whole cell population. This collective behavior is known to depend on an exported signaling Competence Stimulating Peptide (CSP), whose action generates a positive feedback loop. However, it is unclear how this CSP-dependent population switch is coordinated. By monitoring spontaneous competence development in real time during growth of four distinct pneumococcal lineages, we have found that competence shift in the population relies on a self-activated cell fraction that arises via a growth time-dependent mechanism. We demonstrate that CSP remains bound to cells during this event, and conclude that the rate of competence development corresponds to the propagation of competence by contact between activated and quiescent cells. We validated this two-step cell-contact sensing mechanism by measuring competence development during co-cultivation of strains with altered capacity to produce or respond to CSP. Finally, we found that the membrane protein ComD retains the CSP, limiting its free diffusion in the medium. We propose that competence initiator cells originate stochastically in response to stress, to form a distinct subpopulation that then transmits the CSP by cell-cell contact., Author Summary Development of competence for genetic transformation by cultures of pneumococcal cells has been considered till now as a classic example of quorum sensing, whereby a culture attaining a sufficient cell density detects a diffusible signaling molecule (in this case, Competence-Stimulating Peptide (CSP)) and switches en masse to a distinct physiological state. We find that the competence shift is dictated not by cell density but by growth for a time allowing emergence of a competence-initiator sub-population, and spreads by transmission of CSP through cell contact. This behaviour reflects the survival benefits of allowing subsets of the population to respond to environmental stress by generating signalling capacity, which prepares the entire population for a rapid and appropriate response to threatening conditions.

Failure of the human heart to maintain sufficient output of blood for the demands of the body, heart failure, is a common condition with high mortality even with modern therapeutic alternatives. To identify molecular determinants of mortality in patients with new-onset heart failure, we performed a meta-analysis of genome-wide association studies and follow-up genotyping in independent populations. We identified and replicated an association for a genetic variant on chromosome 5q22 with 36% increased risk of death in subjects with heart failure (rs9885413, P = 2.7x10⁻⁹. We provide evidence from reporter gene assays, computational predictions and epigenomic marks that this polymorphism increases activity of an enhancer region active in multiple human tissues. The polymorphism was further reproducibly associated with a DNA methylation signature in whole blood (P = 4.5x10⁻⁴⁰) that also associated with allergic sensitization and expression in blood of the cytokine TSLP (P = 1.1x10⁻⁴). Knockdown of the transcription factor predicted to bind the enhancer region (NHLH1) in a human cell line (HEK293) expressing NHLH1 resulted in lower TSLP expression. In addition, we observed evidence of recent positive selection acting on the risk allele in populations of African descent. Our findings provide novel genetic leads to factors that influence mortality in patients with heart failure., National Heart, Lung, and Blood Institute (HHSN268201100005C), National Heart, Lung, and Blood Institute (HHSN268201100006C), National Heart, Lung, and Blood Institute (HHSN268201100007C), National Heart, Lung, and Blood Institute (HHSN268201100008C), National Heart, Lung, and Blood Institute (HHSN268201100009C), National Heart, Lung, and Blood Institute (HHSN268201100010C), National Heart, Lung, and Blood Institute (HHSN268201100011C), National Heart, Lung, and Blood Institute (HHSN268201100012C), National Heart, Lung, and Blood Institute (N01-HC-55015), National Heart, Lung, and Blood Institute (N01-HC-55016), National Heart, Lung, and Blood Institute (N01-HC-55018), National Heart, Lung, and Blood Institute (N01-HC-55019), National Heart, Lung, and Blood Institute (N01-HC-55020), National Heart, Lung, and Blood Institute (N01-HC-55021), National Heart, Lung, and Blood Institute (N01-HC-55022), National Heart, Lung, and Blood Institute (R01HL087641), National Heart, Lung, and Blood Institute (R01HL59367), National Heart, Lung, and Blood Institute (R01HL086694), National Human Genome Research Institute (U.S.) (U01HG004402), United States. National Institutes of Health (HHSN268200625226C), United States. National Institutes of Health (UL1RR025005), National Heart, Lung, and Blood Institute (HHSN268201200036C), National Heart, Lung, and Blood Institute (N01HC55222), National Heart, Lung, and Blood Institute (HHSN268200800007C), National Heart, Lung, and Blood Institute (N01HC85079), National Heart, Lung, and Blood Institute (N01HC85080), National Heart, Lung, and Blood Institute (N01HC85081), National Heart, Lung, and Blood Institute (N01HC85082), National Heart, Lung, and Blood Institute (N01HC85083), National Heart, Lung, and Blood Institute (N01HC85086), National Heart, Lung, and Blood Institute (U01HL080295), National Science Foundation (U.S.) (R01HL087652), National Heart, Lung, and Blood Institute (R01HL105756), National Heart, Lung, and Blood Institute (R01HL103612), National Heart, Lung, and Blood Institute (R01HL120393), National Institute on Aging (R01AG023629), National Center for Advancing Translational Sciences (U.S.) (UL1TR000124), National Institute of Diabetes and Digestive and Kidney Diseases (U.S.) (DK063491), National Heart, Lung, and Blood Institute (N01-HC-25195), National Heart, Lung, and Blood Institute (2K24HL04334), National Heart, Lung, and Blood Institute (R01HL077477), National Heart, Lung, and Blood Institute (R01HL093328), National Heart, Lung, and Blood Institute (NIH R01HL105993), National Institute on Aging (N01AG62101), National Heart, Lung, and Blood Institute (N01AG62103), National Heart, Lung, and Blood Institute (N01AG62106), National Institute on Aging (1R01AG032098-01A1), United States. National Institutes of Health (HHSN268200782096C), National Cancer Institute (U.S.) (CA-34944), National Cancer Institute (U.S.) (CA-40360), National Cancer Institute (U.S.) (CA-097193), National Heart, Lung, and Blood Institute (HL-26490), National Heart, Lung, and Blood Institute (HL-34595)

Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey), PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles., Author Summary Molecular data sampled from extant individuals contains considerable information about their demographic history. In particular, one classical question in population genetics is to reconstruct past population size changes from such data. Relating these changes to various climatic, geological or anthropogenic events allows characterizing the main factors driving genetic diversity and can have major outcomes for conservation. Until recently, mostly very simple histories, including one or two population size changes, could be estimated from genetic data. This has changed with the sequencing of entire genomes in many species, and several methods allow now inferring complex histories consisting of several tens of population size changes. However, analyzing entire genomes, while accounting for recombination, remains a statistical and numerical challenge. These methods, therefore, can only be applied to small samples with a few diploid genomes. We overcome this limitation by using an approximate estimation approach, where observed genomes are summarized using a small number of statistics related to allele frequencies and linkage disequilibrium. In contrast to previous approaches, we show that our method allows us to reconstruct also the most recent part (the last 100 generations) of the population size history. As an illustration, we apply it to large samples of whole-genome sequences in four cattle breeds.

Do the frequencies of disease mutations in human populations reflect a simple balance between mutation and purifying selection? What other factors shape the prevalence of disease mutations? To begin to answer these questions, we focused on one of the simplest cases: recessive mutations that alone cause lethal diseases or complete sterility. To this end, we generated a hand-curated set of 417 Mendelian mutations in 32 genes reported to cause a recessive, lethal Mendelian disease. We then considered analytic models of mutation-selection balance in infinite and finite populations of constant sizes and simulations of purifying selection in a more realistic demographic setting, and tested how well these models fit allele frequencies estimated from 33,370 individuals of European ancestry. In doing so, we distinguished between CpG transitions, which occur at a substantially elevated rate, and three other mutation types. Intriguingly, the observed frequency for CpG transitions is slightly higher than expectation but close, whereas the frequencies observed for the three other mutation types are an order of magnitude higher than expected, with a bigger deviation from expectation seen for less mutable types. This discrepancy is even larger when subtle fitness effects in heterozygotes or lethal compound heterozygotes are taken into account. In principle, higher than expected frequencies of disease mutations could be due to widespread errors in reporting causal variants, compensation by other mutations, or balancing selection. It is unclear why these factors would have a greater impact on disease mutations that occur at lower rates, however. We argue instead that the unexpectedly high frequency of disease mutations and the relationship to the mutation rate likely reflect an ascertainment bias: of all the mutations that cause recessive lethal diseases, those that by chance have reached higher frequencies are more likely to have been identified and thus to have been included in this study. Beyond the specific application, this study highlights the parameters likely to be important in shaping the frequencies of Mendelian disease alleles., Author summary What determines the frequencies of disease mutations in human populations? To begin to answer this question, we focus on one of the simplest cases: mutations that cause completely recessive, lethal Mendelian diseases. We first review theory about what to expect from mutation and selection in a population of finite size and generate predictions based on simulations using a plausible demographic scenario of recent human evolution. For a highly mutable type of mutation, transitions at CpG sites, we find that the predictions are close to the observed frequencies of recessive lethal disease mutations. For less mutable types, however, predictions substantially under-estimate the observed frequency. We discuss possible explanations for the discrepancy and point to a complication that, to our knowledge, is not widely appreciated: that there exists ascertainment bias in disease mutation discovery. Specifically, we suggest that alleles that have been identified to date are likely the ones that by chance have reached higher frequencies and are thus more likely to have been mapped. More generally, our study highlights the factors that influence the frequencies of Mendelian disease alleles.

Can genetic adaptation in reef-building corals keep pace with the current rate of sea surface warming? Here we combine population genomics, biophysical modeling, and evolutionary simulations to predict future adaptation of the common coral Acropora millepora on the Great Barrier Reef (GBR). Genomics-derived migration rates were high (0.1–1% of immigrants per generation across half the latitudinal range of the GBR) and closely matched the biophysical model of larval dispersal. Both genetic and biophysical models indicated the prevalence of southward migration along the GBR that would facilitate the spread of heat-tolerant alleles to higher latitudes as the climate warms. We developed an individual-based metapopulation model of polygenic adaptation and parameterized it with population sizes and migration rates derived from the genomic analysis. We find that high migration rates do not disrupt local thermal adaptation, and that the resulting standing genetic variation should be sufficient to fuel rapid region-wide adaptation of A. millepora populations to gradual warming over the next 20–50 coral generations (100–250 years). Further adaptation based on novel mutations might also be possible, but this depends on the currently unknown genetic parameters underlying coral thermal tolerance and the rate of warming realized. Despite this capacity for adaptation, our model predicts that coral populations would become increasingly sensitive to random thermal fluctuations such as ENSO cycles or heat waves, which corresponds well with the recent increase in frequency of catastrophic coral bleaching events., Author summary Coral reefs worldwide are suffering high mortality from severe thermal stress episodes induced by acute ocean warming events. Under the current rate of warming, will corals be gone before the end of this century? Here we combine population genomics with biophysical and evolutionary modeling to investigate adaptive potential of a common reef-building coral from the Great Barrier Reef. To approach this task, we have developed a predictive model of polygenic adaptation in a system of multiple inter-connected populations that exist in a heterogeneous and changing environment. Applying this model to our coral species, we find that populations successfully adapt to diverse local temperatures along the range of the Great Barrier Reef despite high migrant exchange and should collectively harbor enough adaptive genetic variants to fuel region-wide thermal adaptation for another century and perhaps longer. In the same time, the model predicts that random thermal fluctuations will induce increasingly severe coral mortality episodes, which aligns well with observations over the last few decades.

Individuals choose their mates so as to maximize reproductive success, and one important component of this choice is assessment of traits reflecting mate quality. Little is known about why specific traits are used for mate quality assessment nor about how they reflect it. We have previously shown that global manipulation of insulin signaling, a nutrient-sensing pathway governing investment in survival versus reproduction, affects female sexual attractiveness in the fruit fly, Drosophila melanogaster. Here we demonstrate that these effects on attractiveness derive from insulin signaling in the fat body and ovarian follicle cells, whose signals are integrated by pheromone-producing cells called oenocytes. Functional ovaries were required for global insulin signaling effects on attractiveness, and manipulations of insulin signaling specifically in late follicle cells recapitulated effects of global manipulations. Interestingly, modulation of insulin signaling in the fat body produced opposite effects on attractiveness, suggesting a competitive relationship with the ovary. Furthermore, all investigated tissue-specific insulin signaling manipulations that changed attractiveness also changed fecundity in the corresponding direction, pointing to insulin pathway activity as a reliable link between fecundity and attractiveness cues. The cues themselves, cuticular hydrocarbons, responded distinctly to fat body and follicle cell manipulations, indicating independent readouts of the pathway activity from these two tissues. Thus, here we describe a system in which female attractiveness results from an apparent connection between attractiveness cues and an organismal state of high fecundity, both of which are created by lowered insulin signaling in the fat body and increased insulin signaling in late follicle cells., Author summary Animals choose their mates based on specific attractive traits, like song and plumage characteristics in birds, or smell and call features in mammals. These traits often reflect the beneficial qualities of their bearer, including parasite resistance, parental care, and fecundity, all of which increase the success of a chooser in siring more and healthier progeny. Why certain traits rather than others are used in assessing the mate quality is not clear. In this article, we show that insulin signaling–a conserved nutrient-sensing pathway that affects female metabolic status—acts specifically in certain tissues to increase fecundity and, at the same time, increases attractiveness of female pheromones in the fruitfly, Drosophila melanogaster. Our discoveries support the idea that reliability in mate assessment depends on the activity of an underlying molecular pathway that affects both attractiveness and fecundity. This work provides a foundation for investigating the mechanistic links between an attractive trait (pheromones) and evolutionary fitness (egg production).

Recent advances in single-cell time-lapse microscopy have revealed non-genetic heterogeneity and temporal fluctuations of cellular phenotypes. While different phenotypic traits such as abundance of growth-related proteins in single cells may have differential effects on the reproductive success of cells, rigorous experimental quantification of this process has remained elusive due to the complexity of single cell physiology within the context of a proliferating population. We introduce and apply a practical empirical method to quantify the fitness landscapes of arbitrary phenotypic traits, using genealogical data in the form of population lineage trees which can include phenotypic data of various kinds. Our inference methodology for fitness landscapes determines how reproductivity is correlated to cellular phenotypes, and provides a natural generalization of bulk growth rate measures for single-cell histories. Using this technique, we quantify the strength of selection acting on different cellular phenotypic traits within populations, which allows us to determine whether a change in population growth is caused by individual cells’ response, selection within a population, or by a mixture of these two processes. By applying these methods to single-cell time-lapse data of growing bacterial populations that express a resistance-conferring protein under antibiotic stress, we show how the distributions, fitness landscapes, and selection strength of single-cell phenotypes are affected by the drug. Our work provides a unified and practical framework for quantitative measurements of fitness landscapes and selection strength for any statistical quantities definable on lineages, and thus elucidates the adaptive significance of phenotypic states in time series data. The method is applicable in diverse fields, from single cell biology to stem cell differentiation and viral evolution., Author summary Selection is a ubiquitous process in biological populations in which individuals are endowed with heterogeneous reproductive abilities, and it occurs even among genetically homogeneous cells due to the existence of phenotypic noise. Unlike genotypes, which can remain stable for many generations, phenotypic fluctuations at the single cell level are often comparable to cellular generation times. For this reason, quantifying the contribution of specific phenotypic states to cellular fitness remains a major challenge. Here, we develop a method to measure the fitness landscape and selection strength acting on diverse cellular phenotypes by employing a novel conceptual framework in which cellular histories are regarded as a basic unit of selection. With this framework, one can tell quantitatively whether a population adapts to environmental changes by selection or through individual responses. This new analytical approach to genetics reveals the roles of heterogeneous expression patterns and dynamics without directly perturbing genes. Applications in diverse fields including stem cell differentiation and viral evolution are discussed.

Woolly mammoths (Mammuthus primigenius) populated Siberia, Beringia, and North America during the Pleistocene and early Holocene. Recent breakthroughs in ancient DNA sequencing have allowed for complete genome sequencing for two specimens of woolly mammoths (Palkopoulou et al. 2015). One mammoth specimen is from a mainland population ~45,000 years ago when mammoths were plentiful. The second, a 4300 yr old specimen, is derived from an isolated population on Wrangel island where mammoths subsisted with small effective population size more than 43-fold lower than previous populations. These extreme differences in effective population size offer a rare opportunity to test nearly neutral models of genome architecture evolution within a single species. Using these previously published mammoth sequences, we identify deletions, retrogenes, and non-functionalizing point mutations. In the Wrangel island mammoth, we identify a greater number of deletions, a larger proportion of deletions affecting gene sequences, a greater number of candidate retrogenes, and an increased number of premature stop codons. This accumulation of detrimental mutations is consistent with genomic meltdown in response to low effective population sizes in the dwindling mammoth population on Wrangel island. In addition, we observe high rates of loss of olfactory receptors and urinary proteins, either because these loci are non-essential or because they were favored by divergent selective pressures in island environments. Finally, at the locus of FOXQ1 we observe two independent loss-of-function mutations, which would confer a satin coat phenotype in this island woolly mammoth., Comment: 43 pages, 2 main figures, 7 supplementary figures, 2 main tables, 10 supplementary tables