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We carried out a 200 generation Evolve and Resequence (E&R) experiment initiated from an outbred diploid recombined 18-way synthetic base population. Replicate populations were evolved at large effective population sizes (>105 individuals), exposed to several different chemical challenges over 12 weeks of evolution, and whole-genome resequenced. Weekly forced outcrossing resulted in an average between adjacent-gene per cell division recombination rate of ∼0.0008. Despite attempts to force weekly sex, roughly half of our populations evolved cheaters and appear to be evolving asexually. Focusing on seven chemical stressors and 55 total evolved populations that remained sexual we observed large fitness gains and highly repeatable patterns of genome-wide haplotype change within chemical challenges, with limited levels of repeatability across chemical treatments. Adaptation appears highly polygenic with almost the entire genome showing significant and consistent patterns of haplotype change with little evidence for long-range linkage disequilibrium in a subset of populations for which we sequenced haploid clones. That is, almost the entire genome is under selection or drafting with selected sites. At any given locus adaptation was almost always dominated by one of the 18 founder's alleles, with that allele varying spatially and between treatments, suggesting that selection acts primarily on rare variants private to a founder or haplotype blocks harboring multiple mutations.

We use ATAC-seq to examine chromatin accessibility for four different tissues in Drosophila melanogaster: adult female brain, ovaries, and both wing and eye-antennal imaginal discs from males. Each tissue is assayed in eight different inbred strain genetic backgrounds, seven associated with a reference quality genome assembly. We develop a method for the quantile normalization of ATAC-seq fragments and test for differences in coverage among genotypes, tissues, and their interaction at 44099 peaks throughout the euchromatic genome. For the strains with reference quality genome assemblies, we correct ATAC-seq profiles for read mis-mapping due to nearby polymorphic structural variants (SVs). Comparing coverage among genotypes without accounting for SVs results in a highly elevated rate (55%) of identifying false positive differences in chromatin state between genotypes. After SV correction, we identify 1050, 30383, and 4508 regions whose peak heights are polymorphic among genotypes, among tissues, or exhibit genotype-by-tissue interactions, respectively. Finally, we identify 3988 candidate causative variants that explain at least 80% of the variance in chromatin state at nearby ATAC-seq peaks.AUTHOR SUMMARYChromatin states are well described in Drosophila melanogaster embryos, but adult and pre-adult tissues are poorly studied, as are differences among genotypes. We carried out ATAC-seq on four different tissues in eight different inbred genotypes with biological replicates within tissue and genotype. We discover that apparent differences in coverage, and by inference chromatin openness, are often due to segregating structural variants (SVs) that can only be corrected for if strains are associated with high-quality genome assemblies. After correction for false positives associated with SVs, we identify thousands of regions that appear to vary in chromatin state between genotypes or vary between genotypes in a tissue-dependent manner. It has been widely speculated that cis-regulatory variants contribute to standing variation in complex traits. If this is true, chromatin states that vary between individuals, perhaps in a tissue-dependent manner, are likely to be enriched for quantitative trait loci.

Drosophila melanogaster has proven an effective system with which to understand the evolutionary genetics and molecular mechanisms of insecticide resistance. Insecticide use has left signatures of selection in the fly genome, and both functional and quantitative genetics studies in the system have identified genes and variants associated with resistance. Here, we use D. melanogaster and leverage a bulk phenotyping and pooled sequencing “extreme QTL” approach to genetically dissect variation in resistance to malathion, an organophosphate insecticide. We resolve two QTL (Quantitative Trait Loci), one of which implicates allelic variation at the cytochrome P450 gene Cyp6g1, a strong candidate based on previous work. The second shows no overlap with hits from a previous genomewide association study (GWAS) for malathion resistance, recapitulating other studies showing that different strategies for complex trait dissection in flies can yield apparently different architectures. Notably, we see no genetic signal at the Ace gene. Ace encodes the target of organophosphate insecticide inhibition, and GWAS have identified strong Ace-linked associations with resistance. The absence of QTL implicating Ace here is most likely because our mapping population does not segregate for several of the known functional polymorphisms impacting resistance at Ace, perhaps because our population is derived from flies collected prior to the widespread use of organophosphate insecticides. Our fundamental approach can be an efficient, powerful strategy to dissect genetic variation in resistance traits. Nonetheless, studies seeking to interrogate contemporary insecticide resistance variation may benefit from deriving mapping populations from more recently collected strains.

"Evolve and resequence" (E&R) studies combine experimental evolution and whole-genome sequencing to interrogate the genetics underlying adaptation. Due to ease of handling, E&R work with asexual organisms such as bacteria can employ optimized experimental design, with large experiments and many generations of selection. By contrast, E&R experiments with sexually reproducing organisms are more difficult to implement, and design parameters vary dramatically among studies. Thus, efforts have been made to assess how these differences, such as number of independent replicates, or size of experimental populations, impact inference. We add to this work by investigating the role of time sampling-the number of discrete time points sequence data are collected from evolving populations. Using data from an E&R experiment with outcrossing Saccharomyces cerevisiae in which populations were sequenced 17 times over ~540 generations, we address the following questions: (a) Do more time points improve the ability to identify candidate regions underlying selection? And (b) does high-resolution sampling provide unique insight into evolutionary processes driving adaptation? We find that while time sampling does not improve the ability to identify candidate regions, high-resolution sampling does provide valuable opportunities to characterize evolutionary dynamics. Increased time sampling reveals three distinct trajectories for adaptive alleles: one consistent with classic population genetic theory (i.e., models assuming constant selection coefficients), and two where trajectories suggest more context-dependent responses (i.e., models involving dynamic selection coefficients). We conclude that while time sampling has limited impact on candidate region identification, sampling eight or more time points has clear benefits for studying complex evolutionary dynamics.

Vernal pools are unique in their isolation and the strong selection acting on their resident species. Vernal pool clam shrimp (Eulimnadia texana) are a promising model due to ease of culturing, short generation time, small genomes, and obligate desiccated diapaused eggs. Clam shrimp are also androdioecious (sexes include males and hermaphrodites), and here we use population-scaled recombination rates to support the hypothesis that the heterogametic sex is recombination free in these shrimp. We collected short-read sequence data from pooled samples from different vernal pools to gain insights into local adaptation. We identify genomic regions in which some populations have allele frequencies that differ significantly from the metapopulation. BayPass (Gautier M. 2015. Genome-wide scan for adaptive divergence and association with population-specific covariates. Genetics 201(4):1555–1579.) detected 19 such genomic regions showing an excess of population subdivision. These regions on average are 550 bp in size and had 2.5 genes within 5 kb of them. Genes located near these regions are involved in Malpighian tubule function and osmoregulation, an essential function in vernal pools. It is likely that salinity profiles vary between pools and over time, and variants at these genes are adapted to local salinity conditions.

Although Peromyscus leucopus (deermouse) is not considered a genetic model system, its genus is well suited for addressing several questions of biologist interest, including the genetic bases of longevity, behavior, physiology, adaptation, and it’s ability to serve as a disease vector. Here we explore a diversity outbred approach for dissecting complex traits in Peromyscus leucopus, a non-traditional genetic model system. We take advantage of a closed colony of deer-mice founded from 38 individuals between 1982 and 1985 and subsequently maintained for 35+ years (∼40-60 generations). From 405 low-pass (∼1X) short-read sequenced deermice we accurately imputed genotypes at 17,751,882 SNPs. Conditional on observed genotypes for a subset of 297 individuals, simulations were conducted in which a QTL contributes 5% to a complex trait under three different genetic models. The power of either a haplotype- or marker-based statistical test was estimated to be 15-25% to detect the hidden QTL. Although modest, this power estimate is consistent with that of DO/HS mice and rat experiments for an experiment with ∼300 individuals. This limitation in QTL detection is mostly associated with the stringent significance threshold required to hold the genome-wide false positive rate low, as in all cases we observe considerable linkage signal at the location of simulated QTL, suggesting a larger panel would exhibit greater power. For the subset of cases where a QTL was detected, localization ability appeared very desirable at ∼1-2Mb. We finally carried out a GWAS on a demonstration trait, bleeding time. No tests exceeded the threshold for genome-wide significance, but one of four suggestive regions co-localizes with Von Willebrand factor. Our work suggests that complex traits can be dissected in founders-unknown P. leucopus colony mice in much the same manner as founders-known DO/HS mice and rats, with genotypes obtained from low pass sequencing data. Our results further suggest that the DO/HS approach can be powerfully extended to any system in which a founders-unknown closed colony has been maintained for several dozen generations.

Despite the value of recombinant inbred lines for the dissection of complex traits, large panels can be difficult to maintain, distribute, and phenotype. An attractive alternative to recombinant inbred lines for many traits leverages selecting phenotypically extreme individuals from a segregating population, and subjecting pools of selected and control individuals to sequencing. Under a bulked or extreme segregant analysis paradigm, genomic regions contributing to trait variation are revealed as frequency differences between pools. Here, we describe such an extreme quantitative trait locus, or extreme quantitative trait loci, mapping strategy that builds on an existing multiparental population, the Drosophila Synthetic Population Resource, and involves phenotyping and genotyping a population derived by mixing hundreds of Drosophila Synthetic Population Resource recombinant inbred lines. Simulations demonstrate that challenging, yet experimentally tractable extreme quantitative trait loci designs (≥4 replicates, ≥5,000 individuals/replicate, and selecting the 5–10% most extreme animals) yield at least the same power as traditional recombinant inbred line-based quantitative trait loci mapping and can localize variants with sub-centimorgan resolution. We empirically demonstrate the effectiveness of the approach using a 4-fold replicated extreme quantitative trait loci experiment that identifies 7 quantitative trait loci for caffeine resistance. Two mapped extreme quantitative trait loci factors replicate loci previously identified in recombinant inbred lines, 6/7 are associated with excellent candidate genes, and RNAi knock-downs support the involvement of 4 genes in the genetic control of trait variation. For many traits of interest to drosophilists, a bulked phenotyping/genotyping extreme quantitative trait loci design has considerable advantages.

Little is known about the genetic architecture of antifungal immunity in natural populations. Using two population genetic approaches, quantitative trait locus (QTL) mapping and evolve and resequence (E&R), we explored D. melanogaster immune defense against infection with the fungus Beauveria bassiana. The immune defense was highly variable both in the recombinant inbred lines from the Drosophila Synthetic Population Resource used for our QTL mapping and in the synthetic outbred populations used in our E&R study. Survivorship of infection improved dramatically over just 10 generations in the E&R study, and continued to increase for an additional nine generations, revealing a trade-off with uninfected longevity. Populations selected for increased defense against B. bassiana evolved cross resistance to a second, distinct B. bassiana strain but not to bacterial pathogens. The QTL mapping study revealed that sexual dimorphism in defense depends on host genotype, and the E&R study indicated that sexual dimorphism also depends on the specific pathogen to which the host is exposed. Both the QTL mapping and E&R experiments generated lists of potentially causal candidate genes, although these lists were nonoverlapping.

Many of the molecular mechanisms for antifungal immunity inDrosophila melanogasterhave been defined, but relatively little is known about the genetic basis for variation in antifungal immunity in natural populations. Using two population genetic approaches, Quantitative Trait Locus (QTL) Mapping and Evolve and Resequence (E&R), we explored the genetics underlyingD. melanogasterimmune defense against infection with the fungusBeauveria bassiana. Immune defense was highly variable both in the recombinant inbred lines from the Drosophila Synthetic Population Resource used for our QTL Mapping and in the synthetic outbred populations used in our E&R study. Survivorship of infection improved dramatically over just 10 generations in the E&R study, and continued to increase for an additional 9 generations, revealing a trade-off with uninfected longevity. Populations selected for increased defense againstB. bassianaevolved cross resistance to a second, distinctB. bassianastrain but not to bacterial pathogens. The QTL mapping study revealed that sexual dimorphism in defense depends on host genotype, and the E&R study indicated that dimorphism also depends on the specific pathogen to which the host is exposed. Both the QTL Mapping and E&R experiments generated lists of potentially causal candidate genes, although these lists were non-overlapping.

A subset of Ras proteins, including N-Ras, depend on a palmitoylation/depalmitoylation cycle to regulate their subcellular trafficking and oncogenicity. General lipase inhibitors such as Palmostatin M block N-Ras depalmitoylation, but lack specificity and target several enzymes displaying depalmitoylase activity. Here, we describe ABD957, a potent and selective covalent inhibitor of the ABHD17 family of depalmitoylases, and show that this compound impairs N-Ras depalmitoylation in human acute myeloid leukemia (AML) cells. ABD957 produced partial effects on N-Ras palmitoylation compared to Palmostatin M, but was much more selective across the proteome, reflecting a plasma membrane-delineated action on dynamically palmitoylated proteins. Finally, ABD957 impaired N-Ras signaling and the growth of NRAS-mutant AML cells in a manner that synergizes with MEK inhibition. Our findings uncover a surprisingly restricted role for ABHD17 enzymes in modulating the N-Ras palmitoylation cycle and suggest that ABHD17 inhibitors may have value as targeted therapies for NRAS-mutant cancers.

Advanced generation multi-parent populations (MPPs) are a valuable tool for dissecting complex traits, having more power than GWAS to detect rare variants, and higher resolution than F2linkage mapping. To extend the advantages of MPPs in budding yeast, we describe the creation and characterization of two outbred MPPs derived from eighteen genetically diverse founding strains. We carried outde novoassemblies of the genomes of the eighteen founder strains, such that virtually all variation segregating between these strains is known and represent those assemblies as Santa Cruz Genome Browser tracks. We discover complex patterns of structural variation segregating amongst the founders, including a large deletion within the vacuolar ATPaseVMA1, several different deletions within the osmosensorMSB2, a series of deletions and insertions atPRM7and the adjacentBSC1, as well as copy number variation at the dehydrogenaseALD2. Resequenced haploid recombinant clones from the two MPPs have a median unrecombined block size of 66kb, demonstrating the population are highly recombined. We pool sequenced the two MPPs to 3270X and 2226X coverage and demonstrate that we can accurately estimate local haplotype frequencies using pooled data. We further down-sampled the poolseq data to ~20-40X and show that local haplotype frequency estimates remain accurate, with median error rate 0.8% and 0.6% at 20X and 40X, respectively. Haplotypes frequencies are estimated much more accurately than SNP frequencies obtained directly from the same data. Deep sequencing of the two populations revealed that ten or more founders are present at a detectable frequency for over 98% of the genome, validating the utility of this resource for the exploration of the role of standing variation in the architecture of complex traits.

The cricetine rodents Peromyscus leucopus and P. maniculatus are key reservoirs for several zoonotic diseases in North America. We determined the complete circular mitochondrial genome sequences of representatives of 3 different stock colonies of P. leucopus, one stock colony of P. maniculatus and two wild populations of P. leucopus. The genomes were syntenic with that of the murids Mus musculus and Rattus norvegicus. Phylogenetic analysis confirmed that these two Peromyscus species are sister taxa in a clade with P. polionotus and also uncovered a distinction between P. leucopus populations in the eastern and the central United States. In one P. leucopus lineage four extended regions of mitochondrial pseudogenes were identified in the nuclear genome. RNA-seq analysis revealed transcription of the entire genome and differences from controls in the expression profiles of mitochondrial genes in the blood, but not in liver or brain, of animals infected with the zoonotic pathogen Borrelia hermsii. PCR and sequencing of the D-loop of the mitochondrion identified 32 different haplotypes among 118 wild P. leucopus at a Connecticut field site. These findings help to further establish P. leucopus as a model organism for studies of emerging infectious diseases, ecology, and in other disciplines.

Using two advanced sequencing approaches, Illumina and PacBio, we derive the entire Dscam gene from an M2 assembly of the complete Penaeus monodon genome. The P. monodon Dscam (PmDscam) gene is ~266 kbp, with a total of 44 exons, 5 of which are subject to alternative splicing. PmDscam has a conserved architectural structure consisting of an extracellular region with hypervariable Ig domains, a transmembrane domain, and a cytoplasmic tail. We show that, contrary to a previous report, there are in fact 26, 81 and 26 alternative exons in N-terminal Ig2, N-terminal Ig3 and the entirety of Ig7, respectively. We also identified two alternatively spliced exons in the cytoplasmic tail, with transmembrane domains in exon variants 32.1 and 32.2, and stop codons in exon variants 44.1 and 44.2. This means that alternative splicing is involved in the selection of the stop codon. There are also 7 non-constitutive cytoplasmic tail exons that can either be included or skipped. Alternative splicing and the non-constitutive exons together produce more than 21 million isoform combinations from one PmDscam locus in the P. monodon gene. A public-facing database that allows BLAST searches of all 175 exons in the PmDscam gene has been established at http://pmdscam.dbbs.ncku.edu.tw/.

The rodent Peromyscus leucopus is the natural reservoir of several tick-borne infections, including Lyme disease. To expand the knowledge base for this key species in life cycles of several pathogens, we assembled and scaffolded the P. leucopus genome. The resulting assembly was 2.45 Gb in total length, with 24 chromosome-length scaffolds harboring 97% of predicted genes. RNA sequencing following infection of P. leucopus with Borreliella burgdorferi, a Lyme disease agent, shows that, unlike blood, the skin is actively responding to the infection after several weeks. P. leucopus has a high level of segregating nucleotide variation, suggesting that natural resistance alleles to Crispr gene targeting constructs are likely segregating in wild populations. The reference genome will allow for experiments aimed at elucidating the mechanisms by which this widely distributed rodent serves as natural reservoir for several infectious diseases of public health importance, potentially enabling intervention strategies.

Background In pancrustaceans, the Down syndrome cell adhesion molecule (Dscam) is an extraordinarily complex, single-locus gene, with the potential for generating thousands of isoforms by combining alternative splicing exons. In the present study, we used two advanced sequencing approaches, Illumina and PacBio, with hybrid assembly to analyze the entire Dscam genomic structure in Penaeus monodon. Results The P. monodon Dscam (PmDscam) genome was ~250 kbp, with a total of 175 constitutive and alternative splicing exons. Analysis of PmDscam cDNA and genomics revealed a conserved architectural structure consisting of an extracellular region with hypervariable Ig domains, a transmembrane domain, and a cytoplasmic tail. While the number of splicing exon variants in N-terminal Ig2, N-terminal Ig3 and the entirety of Ig7 were previously reported to be 28, 43 and 19, we now show that there are in fact 26, 81 and 26 alternative exons in these regions, respectively. We also identified two alternative variants of two exons in the cytoplasmic tail, as well as 7 cytoplasmic tail elements that can either be included or skipped. The presence of three stop codon sites in the cytoplasmic tail region means that alternative splicing is involved in the selection of the stop codon. Conclusions In total, alternative splicing provides for 54,756 potential combinations in the extracellular region, plus 512 potential combinations in the cytoplasmic tail, all derived from one PmDscam genome locus. We have also established a public-facing PmDscam genome database (http://pmdscam.dbbs.ncku.edu.tw/) to facilitate future research on characterizing the involvement of Dscam in pancrustacean immunity.

Pre-existing and de novo genetic variants can both drive adaptation to environmental changes, but their relative contributions and interplay remain poorly understood. Here we investigated the evolutionary dynamics in drug-treated yeast populations with different levels of pre-existing variation by experimental evolution coupled with time-resolved sequencing and phenotyping. We found a doubling of pre-existing variation alone boosts the adaptation by 64.1% and 51.5% in hydroxyurea and rapamycin, respectively. The causative pre-existing and de novo variants were selected on shared targets: RNR4 in hydroxyurea and TOR1, TOR2 in rapamycin. Interestingly, the pre-existing and de novo TOR variants map to different functional domains and act via distinct mechanisms. The pre-existing TOR variants from two domesticated strains exhibited opposite rapamycin resistance effects, reflecting lineage-specific functional divergence. This study provides a dynamic view on how pre-existing and de novo variants interactively drive adaptation and deepens our understanding of clonally evolving populations.

The genome of the white-footed deer mouse will accelerate our understanding of several tick-borne infections., The rodent Peromyscus leucopus is the natural reservoir of several tick-borne infections, including Lyme disease. To expand the knowledge base for this key species in life cycles of several pathogens, we assembled and scaffolded the P. leucopus genome. The resulting assembly was 2.45 Gb in total length, with 24 chromosome-length scaffolds harboring 97% of predicted genes. RNA sequencing following infection of P. leucopus with Borreliella burgdorferi, a Lyme disease agent, shows that, unlike blood, the skin is actively responding to the infection after several weeks. P. leucopus has a high level of segregating nucleotide variation, suggesting that natural resistance alleles to Crispr gene targeting constructs are likely segregating in wild populations. The reference genome will allow for experiments aimed at elucidating the mechanisms by which this widely distributed rodent serves as natural reservoir for several infectious diseases of public health importance, potentially enabling intervention strategies.

Despite extensive effort to reveal the genetic basis of complex phenotypic variation, studies typically explain only a fraction of trait heritability. It has been hypothesized that individually rare hidden structural variants (SVs) could account for a significant fraction of variation in complex traits. To investigate this hypothesis, we assembled 14 Drosophila melanogaster genomes and systematically identified more than 20,000 euchromatic SVs, of which ∼40% are invisible to high specificity short read genotyping approaches. SVs are common in Drosophila genes, with almost one third of diploid individuals harboring an SV in genes larger than 5kb, and nearly a quarter harboring multiple SVs in genes larger than 10kb. We show that SV alleles are rarer than amino acid polymorphisms, implying that they are more strongly deleterious. A number of functionally important genes harbor previously hidden structural variants that likely affect complex phenotypes (e.g., Cyp6g1, Drsl5, Cyp28d1&2, InR, and Gss1&2).Furthermore, SVs are overrepresented in quantitative trait locus candidate genes from eight Drosophila Synthetic Population Resource (DSPR) mapping experiments. We conclude that SVs are pervasive in genomes, are frequently present as heterogeneous allelic series, and can act as rare alleles of large effect.

Standing and de novo genetic variants can both drive adaptation to environmental changes, but their relative contributions and interplay remain poorly understood. Here we investigated the dynamics of drug adaptation in yeast populations with different levels of standing variation by experimental evolution coupled with time-resolved sequencing and phenotyping. We found a doubling of standing variation alone boost the adaptation by 64.1% and 51.5% in hydroxyuea and rapamycin respectively. The causative standing and de novo variants were selected on shared targets of RNR4 in hydroxyurea and TOR1, TOR2 in rapamycin. The standing and de novo TOR variants map to different functional domains and act via distinct mechanisms. Interestingly, standing TOR variants from two domesticated strains exhibited opposite resistance effects, reflecting lineage-specific functional divergence. This study provides a dynamic view on how standing and de novo variants interactively drive adaptation and deepens our understanding of clonally evolving diseases.

Vernal pool clam shrimp (Eulimnadia texana) are a promising model due to ease of culturing, short generation time, modest genome size, and obligate desiccated diapaused eggs. We collected Illumina data (Poolseq) from eleven pooled wild vernal pool clam shrimp populations. We hypothesized that restricted gene flow between vernal pools, separated by distances of 0.36 to 253 km, in concert with Poolseq data from each population, could be used to identify genes important in local adaptation. We adaptedBayenv2to genome-wide Poolseq data and detected thirteen genomic regions showing a strong excess of population subdivision relative to a genome-wide background. We identified a set of regions that appear to be significantly diverged in allele frequency, above what is expected based on the relationships amongst the populations. Regions identified as significant were on average 9.5 kb in size and harbored 3.8 genes. We attempted to identify correlations between allele frequencies at each genomic region and environmental variables that may influence local adaptation in the sequences populations, but found that there were too many confounding environmental variables to draw strong conclusions. One such genomic region harbored an ortholog ofDrosophila melanogasterCG10413, a gene predicted to have sodium/potassium/chloride activity. Finally, we demonstrate that the identified regions could not have been found with less powerful statistics, i.e.FST, or with a less contiguous genome assembly.

Vernal pool clam shrimp (Eulimnadia texana) are a promising model system due to their ease of culturing in the lab, short generation time, modest sized genome, a somewhat rare stable androdioecious sex determination system, and a requirement to reproduce via desiccated diapaused eggs. We generated a highly contiguous genome assembly of E. texana using 46X of PacBio long read data and 216X of Illumina short read data; and annotate the genome using Illumina RNAseq data obtained from adult males or hermaphrodites. 85% of the 120Mb genome is contained in the largest 8 contigs of the assembly, the smallest of which is 4.6Mb. Furthermore, the assembly contains 98% of transcripts predicted via RNAseq. This assembly is qualitatively different from scaffolded Illumina assemblies because it is produced from long reads that contain valid sequence data along their entire length, and thus is free of gaps. The contiguity and correctness of the assembly is such that we are able to identify and order the HOX genes within the genome, identifying two loci that contain HOX gene orthologs, and which approximately maintain the order observed in other arthropods. Intriguingly, we identified a partial duplication of the Antennapedia gene adjacent to the few genes homologous to the Bithorax locus. Because the sex chromosome of an androdioecious species is of special interest, we used existing allozyme and microsatellite markers to identify the E. texana sex chromosome, and find that it comprises nearly half of the genome of this species. Linkage patterns indicate that recombination is extremely rare and perhaps absent in hermaphrodites, and as a result the location of the sex determining locus will be difficult to refine using recombination mapping.

Fixation probability, the probability that the frequency of a newly arising mutation in a population will eventually reach unity, is a fundamental quantity in evolutionary genetics. Here we use a number of models (several versions of the Moran model and the haploid Wright-Fisher model) to examine fixation probabilities for a constant size population where the fitness is a random function of both allelic state and spatial position, despite neither allele being favored on average. The concept of fitness varying with respect to both genotype and environment is important in models of cancer initiation and progression, bacterial dynamics, and drug resistance. Under our model spatial heterogeneity redefines the notion of neutrality for a newly arising mutation, as such mutations fix at a higher rate than that predicted under neutrality. The increased fixation probability appears to be due to rare alleles having an advantage. The magnitude of this effect can be large, and is an increasing function of the spatial variance and skew in fitness. The effect is largest when the fitness values of the mutants and wild types are anti-correlated across environments. We discuss results for both a spatial ring geometry of cells (such as that of a colonic crypt), a 2D lattice and a mass-action (complete graph) arrangement.

The genetic component of complex disease risk in humans remains largely unexplained. A corollary is that the allelic spectrum of genetic variants contributing to complex disease risk is unknown. Theoretical models that relate population genetic processes to the maintenance of genetic variation for quantitative traits may suggest profitable avenues for future experimental design. Here we use forward simulation to model a genomic region evolving under a balance between recurrent deleterious mutation and Gaussian stabilizing selection. We consider multiple genetic and demographic models, and several different methods for identifying genomic regions harboring variants associated with complex disease risk. We demonstrate that the model of gene action, relating genotype to phenotype, has a qualitative effect on several relevant aspects of the population genetic architecture of a complex trait. In particular, the genetic model impacts genetic variance component partitioning across the allele frequency spectrum and the power of statistical tests. Models with partial recessivity closely match the minor allele frequency distribution of significant hits from empirical genome-wide association studies without requiring homozygous effect sizes to be small. We highlight a particular gene-based model of incomplete recessivity that is appealing from first principles. Under that model, deleterious mutations in a genomic region partially fail to complement one another. This model of gene-based recessivity predicts the empirically observed inconsistency between twin and SNP based estimated of dominance heritability. Furthermore, this model predicts considerable levels of unexplained variance associated with intralocus epistasis. Our results suggest a need for improved statistical tools for region based genetic association and heritability estimation., Author Summary Gene action determines how mutations affect phenotype. When placed in an evolutionary context, the details of the genotype-to-phenotype model can impact the maintenance of genetic variation for complex traits. Likewise, non-equilibrium demographic history may affect patterns of genetic variation. Here, we explore the impact of genetic model and population growth on distribution of genetic variance across the allele frequency spectrum underlying risk for a complex disease. Using forward-in-time population genetic simulations, we show that the genetic model has important impacts on the composition of variation for complex disease risk in a population. We explicitly simulate genome-wide association studies (GWAS) and perform heritability estimation on population samples. A particular model of gene-based partial recessivity, based on allelic non-complementation, aligns well with empirical results. This model is congruent with the dominance variance estimates from both SNPs and twins, and the minor allele frequency distribution of GWAS hits.

For most complex traits we have a poor understanding of the positions, phenotypic effects, and population frequencies of the underlying genetic variants contributing to their variation. Recently, several groups have developed multi-parent advanced intercross mapping panels in different model organisms in an attempt to improve our ability to characterize causative genetic variants. These panels are powerful and are particularly well suited to the dissection of phenotypic variation generated by rare alleles and loci segregating multiple functional alleles. We describe studies using one such panel, the Drosophila Synthetic Population Resource (DSPR), and the implications for our understanding of the genetic basis of complex traits. In particular, we note that many loci of large effect appear to be multiallelic. If multiallelism is a general rule, analytical approaches designed to identify multiallelic variants should be a priority for both genome-wide association studies (GWASs) and multi-parental panels.

Transposable elements are a common source of genetic variation that may play a substantial role in contributing to gene expression variation. However, the contribution of transposable elements to expression variation thus far consists of a handful of examples. We used previously published gene expression data from 37 inbred Drosophila melanogaster lines from the Drosophila Genetic Reference Panel to perform a genome-wide assessment of the effects of transposable elements on gene expression. We found thousands of transcripts with transposable element insertions in or near the transcript and that the presence of a transposable element in or near a transcript is significantly associated with reductions in expression. We estimate that within this example population, ∼2.2% of transcripts have a transposable element insertion, which significantly reduces expression in the line containing the transposable element. We also find that transcripts with insertions within 500 bp of the transcript show on average a 0.67 standard deviation decrease in expression level. These large decreases in expression level are most pronounced for transposable element insertions close to transcripts and the effect diminishes for more distant insertions. This work represents the first genome-wide analysis of gene expression variation due to transposable elements and suggests that transposable elements are an important class of mutation underlying expression variation in Drosophila and likely in other systems, given the ubiquity of these mobile elements in eukaryotic genomes.

A novel approach for dissecting complex traits is to experimentally evolve laboratory populations under a controlled environment shift, resequence the resulting populations, and identify single nucleotide polymorphisms (SNPs) and/or genomic regions highly diverged in allele frequency. To better understand the power and localization ability of such an evolve and resequence (E&R) approach, we carried out forward-in-time population genetics simulations of 1 Mb genomic regions under a large combination of experimental conditions, then attempted to detect significantly diverged SNPs. Our analysis indicates that the ability to detect differentiation between populations is primarily affected by selection coefficient, population size, number of replicate populations, and number of founding haplotypes. We estimate that E&R studies can detect and localize causative sites with 80% success or greater when the number of founder haplotypes is over 500, experimental populations are replicated at least 25-fold, population size is at least 1,000 diploid individuals, and the selection coefficient on the locus of interest is at least 0.1. More achievable experimental designs (less replicated, fewer founder haplotypes, smaller effective population size, and smaller selection coefficients) can have power of greater than 50% to identify a handful of SNPs of which one is likely causative. Similarly, in cases where s 0.2, less demanding experimental designs can yield high power. © 2014 The Author.

Experimental evolutionary genomics now allows biologists to test fundamental theories concerning the genetic basis of adaptation. We have conducted one of the longest laboratory evolution experiments with any sexually-reproducing metazoan, Drosophila melanogaster. We used next-generation resequencing data from this experiment to examine genome-wide patterns of genetic variation over an evolutionary time-scale that approaches 1,000 generations. We also compared measures of variation within and differentiation between our populations to simulations based on a variety of evolutionary scenarios. Our analysis yielded no clear evidence of hard selective sweeps, whereby natural selection acts to increase the frequency of a newly-arising mutation in a population until it becomes fixed. We do find evidence for selection acting on standing genetic variation, as independent replicate populations exhibit similar population-genetic dynamics, without obvious fixation of candidate alleles under selection. A hidden-Markov model test for selection also found widespread evidence for selection. We found more genetic variation genome-wide, and less differentiation between replicate populations genome-wide, than arose in any of our simulated evolutionary scenarios.

Human genome-wide association studies (GWAS) of longevity attempt to identify alleles at different frequencies in the extremely old, relative to a younger control sample. Here, we apply a GWAS approach to "synthetic" populations of Drosophila melanogaster derived from a small number of inbred founders. We used next-generation DNA sequencing to estimate allele and haplotype frequencies in the oldest surviving individuals of an age cohort and compared these frequencies with those of randomly sampled individuals from the same cohort. We used this case-control strategy in four independent cohorts and identified eight significantly differentiated regions of the genome potentially harboring genes with relevance for longevity. By modeling the effects of local haplotypes, we have more power to detect regions enriched for longevity genes than marker-based GWAS. Most significant regions occur near chromosome ends or centromeres where recombination is infrequent, consistent with these regions harboring unconditionally deleterious alleles impacting longevity. Genes in regions of normal recombination are enriched for those relevant to immune function and a gene family involved in oxidative stress response. Genetic differentiation between our experimental cohorts is comparable to that between human populations, suggesting in turn that our results may help explain heterogeneous signals in human association studies of extreme longevity when panels have diverse ancestry.

Here we present computational machinery to efficiently and accurately identify transposable element (TE) insertions in 146 next-generation sequenced inbred strains of Drosophila melanogaster. The panel of lines we use in our study is composed of strains from a pair of genetic mapping resources: The Drosophila Genetic Reference Panel (DGRP) and the Drosophila Synthetic Population Resource (DSPR). We identified 23,087 TE insertions in these lines, of which 83.3% are found in only one line. There are marked differences in the distribution of elements over the genome, with TEs found at higher densities on the X chromosome, and in regions of low recombination. We also identified many more TEs per base pair of intronic sequence and fewer TEs per base pair of exonic sequence than expected if TEs are located at random locations in the euchromatic genome. There was substantial variation in TE load across genes. For example, the paralogs derailed and derailed-2 show a significant difference in the number of TE insertions, potentially reflecting differences in the selection acting on these loci. When considering TE families, we find a very weak effect of gene family size on TE insertions per gene, indicating that as gene family size increases the number of TE insertions in a given gene within that family also increases. TEs are known to be associated with certain phenotypes, and our data will allow investigators using the DGRP and DSPR to assess the functional role of TE insertions in complex trait variation more generally. Notably, because most TEs are very rare and often private to a single line, causative TEs resulting in phenotypic differences among individuals may typically fail to replicate across mapping panels since individual elements are unlikely to segregate in both panels. Our data suggest that "burden tests" that test for the effect of TEs as a class may be more fruitful. © The Author 2013. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved.

Genome-wide association studies (GWAS) have associated many single variants with complex disease, yet the better part of heritable complex disease risk remains unexplained. Analytical tools designed to work under specific population genetic models are needed. Rare variants are increasingly shown to be important in human complex disease, but most existing GWAS data do not cover rare variants. Explicit population genetic models predict that genes contributing to complex traits and experiencing recurrent, unconditionally deleterious, mutation will harbor multiple rare, causative mutations of subtle effect. It is difficult to identify genes harboring rare variants of large effect that contribute to complex disease risk via the single marker association tests typically used in GWAS. Gene/region-based association tests may have the power detect associations by combining information from multiple markers, but have yielded limited success in practice. This is partially because many methods have not been widely applied. Here, we empirically demonstrate the utility of a procedure based on the rank truncated product (RTP) method, filtered to reduce the effects of linkage disequilibrium. We apply the procedure to the Wellcome Trust Case Control Consortium (WTCCC) data set, and uncover previously unidentified associations, some of which have been replicated in much larger studies. We show that, in the absence of significant rare variant coverage, RTP based methods still have the power to detect associated genes. We recommend that RTP-based methods be applied to all existing GWAS data to maximize the usefulness of those data. For this, we provide efficient software implementing our procedure.

Combining experimental evolution with whole-genome resequencing is a promising new strategy for investigating the dynamics of evolutionary change. Published studies that have resequenced laboratory-selected populations of sexual organisms have typically focused on populations sampled at the end of an evolution experiment. These studies have attempted to associate particular alleles with phenotypic change and attempted to distinguish between different theoretical models of adaptation. However, neither the population used to initiate the experiment nor multiple time points sampled during the evolutionary trajectory are generally available for examination. In this issue of Molecular Ecology, Orozco-terWengel et al. (2012) take a significant step forward by estimating genome-wide allele frequencies at the start, 15 generations into and at the end of a 37-generation Drosophila experimental evolution study. The authors identify regions of the genome that have responded to laboratory selection and describe the temporal dynamics of allele frequency change. They identify two common trajectories for putatively adaptive alleles: alleles either gradually increase in frequency throughout the entire 37 generations or alleles plateau at a new frequency by generation 15. The identification of complex trajectories of alleles under selection contributes to a growing body of literature suggesting that simple models of adaptation, whereby beneficial alleles arise and increase in frequency unimpeded until they become fixed, may not adequately describe short-term response to selection.

Although animals display a rich variety of shapes and patterns, the genetic changes that explain how complex forms arise are still unclear. Here we take advantage of the extensive diversity of Heliconius butterflies to identify a gene that causes adaptive variation of black wing patterns within and between species. Linkage mapping in two species groups, gene-expression analysis in seven species, and pharmacological treatments all indicate that cis -regulatory evolution of the WntA ligand underpins discrete changes in color pattern features across the Heliconius genus. These results illustrate how the direct modulation of morphogen sources can generate a wide array of unique morphologies, thus providing a link between natural genetic variation, pattern formation, and adaptation.

Objectives—Identifying the genes responsible for chemotherapy toxicity in Drosophila melanogaster may allow for the identification of human orthologs that similarly mediate toxicity in humans. In order to develop Drosophila melanogaster as a model of dissecting chemotoxicity, we first need to develop standardized high throughput toxicity assays and prove that interindividual variation in toxicity as measured by such assays is highly heritable. Methods—We developed a method for the oral delivery of commonly used chemotherapy drugs to Drosophila. Post-treatment female fecundity displayed a dose dependent response to varying levels of the chemotherapy drug delivered. We fixed the dose for each drug at a level that resulted in a 50% reduction in fecundity and used a paternal half-sibling heritability design to calculate the heritability attributable to chemotherapy toxicity assayed via a decrease in female fecundity. Chemotherapy agents tested were carboplatin, floxuridine, gemcitabine hydrochloride, methotrexate, mitomycin C, and topotecan hydrochloride. Results—We found that six currently widely prescribed chemotherapeutic agents lowered fecundity in D. melanogaster in both a dose dependent and highly heritable manner. The following heritability estimates were found: carboplatin – 0.72, floxuridine – 0.52, gemcitabine hydrochloride – 0.72, methotrexate – 0.99, mitomycin C – 0.64, and topotecan hydrochloride – 0.63. Conclusions—The high heritability estimates observed in this study, irrespective of the particular class of drug examined, suggest that human toxicity may also have a sizable genetic component.

Currently, the relevance of common genetic variants—particularly those significantly associated with phenotypic variation in laboratory studies—to standing phenotypic variation in the wild is poorly understood. To address this, we quantified the relationship between achaete–scute complex (ASC) polymorphisms and Drosophila bristle number phenotypes in several new population samples. MC22 is a biallelic, nonrepetitive-length polymorphism 97 bp downstream of the scute transcript. It has been previously shown to be associated with sternopleural bristle number variation in both sexes in a set of isogenic lines. We replicated this association in a large cohort of wild-caught Drosophila melanogaster. We also detected a significant association at MC22 in an outbred population maintained under laboratory conditions for ∼25 years, but the phenotypic effects in this sample were opposite from the direction estimated in the initial study. Finally, no significant associations were detected in a second large wild-caught cohort or in a set of 134 nearly isogenic lines. Our ability to repeat the initial association in wild samples suggests that it was not spurious. Nevertheless, inconsistent results from the other three panels suggest that the relationship between polymorphic genetic markers and loci contributing to continuous variation is not a simple one.

Genome assemblies that are accurate, complete, and contiguous are essential for identifying important structural and functional elements of genomes and for identifying genetic variation. Nevertheless, most recent genome assemblies remain incomplete and fragmented. While long molecule sequencing promises to deliver more complete genome assemblies with fewer gaps, concerns about error rates, low yields, stringent DNA requirements, and uncertainty about best practices may discourage many investigators from adopting this technology. Here, in conjunction with the platinum standard Drosophila melanogaster reference genome, we analyze recently published long molecule sequencing data to identify what governs completeness and contiguity of genome assemblies. We also present a hybrid meta-assembly approach that achieves remarkable assembly contiguity for both Drosophila and human assemblies with only modest long molecule sequencing coverage. Our results motivate a set of preliminary best practices for obtaining accurate and contiguous assemblies, a “missing manual” that guides key decisions in building high quality de novo genome assemblies, from DNA isolation to polishing the assembly.

© 2015 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. Evolve and resequence (E&R) experiments use experimental evolution to adapt populations to a novel environment, then next-generation sequencing to analyse genetic changes. They enable molecular evolution to be monitored in real time on a genome-wide scale. Here, we review the field of E&R experiments across diverse systems, ranging from simple non-living RNA to bacteria, yeast and the complex multicellular organism Drosophila melanogaster. We explore how different evolutionary outcomes in these systems are largely consistent with common population genetics principles. Differences in outcomes across systems are largely explained by different starting population sizes, levels of pre-existing genetic variation, recombination rates and adaptive landscapes. We highlight emerging themes and inconsistencies that future experiments must address.

Natural populations exhibit a great deal of interindividual genetic variation in the response to toxins, exemplified by the variable clinical efficacy of pharmaceutical drugs in humans, and the evolution of pesticide resistant insects. Such variation can result from several phenomena, including variable metabolic detoxification of the xenobiotic, and differential sensitivity of the molecular target of the toxin. Our goal is to genetically dissect variation in the response to xenobiotics, and characterize naturally-segregating polymorphisms that modulate toxicity. Here, we use the Drosophila Synthetic Population Resource (DSPR), a multiparent advanced intercross panel of recombinant inbred lines, to identify QTL (Quantitative Trait Loci) underlying xenobiotic resistance, and employ caffeine as a model toxic compound. Phenotyping over 1,700 genotypes led to the identification of ten QTL, each explaining 4.5–14.4% of the broad-sense heritability for caffeine resistance. Four QTL harbor members of the cytochrome P450 family of detoxification enzymes, which represent strong a priori candidate genes. The case is especially strong for Cyp12d1, with multiple lines of evidence indicating the gene causally impacts caffeine resistance. Cyp12d1 is implicated by QTL mapped in both panels of DSPR RILs, is significantly upregulated in the presence of caffeine, and RNAi knockdown robustly decreases caffeine tolerance. Furthermore, copy number variation at Cyp12d1 is strongly associated with phenotype in the DSPR, with a trend in the same direction observed in the DGRP (Drosophila Genetic Reference Panel). No additional plausible causative polymorphisms were observed in a full genomewide association study in the DGRP, or in analyses restricted to QTL regions mapped in the DSPR. Just as in human populations, replicating modest-effect, naturally-segregating causative variants in an association study framework in flies will likely require very large sample sizes., Author Summary A striking feature of biology is that within populations there is substantial interindividual phenotypic variation for traits of biomedical significance. Some fraction of this variation is due to environmental factors, but for many traits segregating genetic differences contribute significantly to phenotypic variation. Elucidating those causative sequence changes that result in complex trait variation is of central importance to biology, and requires the coordinated use of multiple approaches. Here we employ a multi-level strategy to dissect genetic variation in caffeine resistance in Drosophila melanogaster, leveraging powerful genetic screening in a multiparental mapping panel, a genomewide association study, high-throughput RNA sequencing, and gene knockdowns using RNA interference. We identify several short genomic regions that collectively explain a substantial portion of the heritable variation for caffeine resistance, and find that several of these regions harbor members of known detoxification enzyme families. One such gene—Cyp12d1—shows increased expression on exposure to caffeine, and experimentally reducing gene expression leads to a reduction in caffeine resistance. We additionally show that variation in the number of copies of Cyp12d1 is positively associated with resistance. These compelling lines of evidence imply that structural variation at this gene causally contributes to xenobiotic resistance in Drosophila.

Drosophila melanogaster males perform a courtship ritual consisting of a series of dependent fixed-action patterns. The yellow (y) gene is required for normal male courtship behavior and subsequent mating success. To better characterize the requirement for y in the manifestation of innate male sexual behavior, we measured the male mating success (MMS) of 12 hypomorphic y mutants and matched-outbred-background controls using a y+ rescue element on a freely segregating minichromosome. We found that 4 hypomorphs significantly reduced MMS to varying degrees. Reduced MMS was largely independent of adult pigmentation patterns. These mutations defined a 300-bp regulatory region upstream of the transcription start, the mating-success regulatory sequence (MRS), whose function is required for normal MMS. Visualization of gene action via GFP and a Yellow antibody suggests that the MRS directs y transcription in a small number of cells in the third instar CNS, the developmental stage previously implicated in the role of y with regard to male courtship behavior. The presence of Yellow protein in these cells positively correlates with MMS in a subset of mutants. The MRS contains a regulatory sequence controlling larval pigmentation and a 35-bp sequence that is highly conserved within the genus Drosophila and is predicted to bind known transcription factors.

The genetic factors contributing to complex trait variation may reside in regulatory, rather than protein-coding portions of the genome. Within noncoding regions, SNPs in regulatory elements are more likely to contribute to phenotypic variation than those in nonregulatory regions. Thus, it is important to be able to identify and annotate noncoding regulatory elements. DNA conservation among diverged species successfully identifies noncoding regulatory regions. However, because rapidly evolving regulatory regions will not generally be conserved across species, these will not detected by using purely conservation-based methods. Here we describe additional approaches that can be used to identify putative regulatory elements via signatures of nonneutral evolution. An examination of the pattern of polymorphism both within and between populations of Drosophila melanogaster , as well as divergence with its sibling species Drosophila simulans , across 24.2 kb of noncoding DNA identifies several nonneutrally evolving regions not identified by conservation. Because different methods tag different regions, it appears that the methods are complementary. Patterns of variation at different elements are consistent with the action of selective sweeps, balancing selection, or population differentiation. Together with regions conserved between D. melanogaster and Drosophila pseudoobscura , we tag 5.3 kb of noncoding DNA as potentially regulatory. Ninety-seven of the 408 common noncoding SNPs surveyed are within putatively regulatory regions. If these methods collectively identify the majority of functional noncoding polymorphisms, genotyping only these SNPs in an association mapping framework would reduce genotyping effort for noncoding regions 4-fold.

Summary Understanding the generation of phenotypic variation is an important challenge for modern evolutionary biology, and butterfly wing patterns are an exciting system that can shed some light on this issue. Here, we report on recent advances in the genetics of Bicyclus anynana butterflies. This system provides the potential for a fully integrated study of the evolutionary and developmental processes underlying diversity in morphology.

To extend results from laboratory genetic mapping experiments to natural populations it is necessary to estimate the phenotypic effects attributable to laboratory-identified genetic factors in nature. We retested a polymorphism found to be strongly associated with an increase of 0.35 sternopleural bristles in laboratory strains in two large samples of wild-caught Drosophila melanogaster. Despite >90% power to detect effects as low as 0.27 bristles (

We test the hypothesis that naturally occurring nonsynonymous variants in the Delta ligand of the Notch signaling pathway contribute to standing variation in sternopleural and/or abdominal bristle number in Drosophila melanogaster, for both a large cohort of wild-caught flies and previously described laboratory lines. We sequenced the transcribed region of Delta for 16 naturally occurring chromosomes and 65 SNPs, including 7 nonsynonymous SNPs (nsSNPs), were observed. Identified nsSNPs and 6 additional common SNPs, all located in exon 6 and the 3′ UTR, were genotyped in 2060 wild-caught flies using an OLA-based methodology and genotyped in 38 additional natural chromosomes via DNA sequencing. None of the genotyped nsSNPs were significantly associated with natural variation in bristle number as assessed by a permutation test. A 95% upper bound on the additive genetic variance attributable to each genotyped SNP in the large natural cohort is

Flowering time varies among Arabidopsis accessions. Some of the genes that contribute to this polygenic trait have been localized using quantitative trait loci (QTL) mapping, eventually leading to the identification of genetic variants that contribute to observed differences in flowering time ([El