Genome-wide association study of extreme longevity in Drosophila melanogaster

Genetic, Environmental, and Stochastic Components of Lifespan Variability: The Drosophila Paradigm

Lifespan is a complex quantitative trait involving genetic and non-genetic factors as well as the peculiarities of ontogenesis. As with all quantitative traits, lifespan shows considerable variation within populations and between individuals. Drosophila, a favourite object of geneticists, has greatly advanced our understanding of how different forms of variability affect lifespan. This review considers the role of heritable genetic variability, phenotypic plasticity and stochastic variability in controlling lifespan in Drosophila melanogaster. We discuss the major historical milestones in the development of the genetic approach to study lifespan, the breeding of long-lived lines, advances in lifespan QTL mapping, the environmental factors that have the greatest influence on lifespan in laboratory maintained flies, and the mechanisms, by which individual development affects longevity. The interplay between approaches to study ageing and lifespan limitation will also be discussed. Particular attention will be paid to the interaction of different types of variability in the control of lifespan.

Genetic dissection of innate immune memory in Drosophila melanogaster

Current studies have demonstrated that innate immunity possesses memory characteristics. Although the molecular mechanisms underlying innate immune memory have been addressed by numerous studies, genetic variations in innate immune memory and the associated genes remain unclear. Here, we explored innate immune memory in 163 lines of Drosophila melanogaster from the Drosophila Synthetic Population Resource. In our assay system, prior training with low pathogenic bacteria (Micrococcus luteus) increased the survival rate of flies after subsequent challenge with highly pathogenic bacteria (Staphylococcus aureus). This positive training effect was observed in most lines, but some lines exhibited negative training effects. Survival rates under training and control conditions were poorly correlated, suggesting that distinct genetic factors regulate training effects and normal immune responses. Subsequent quantitative trait loci analysis suggested that four loci containing 80 genes may be involved in regulating innate immune memory. Among them, Adgf-A, which encodes an extracellular adenosine deaminase-related growth factor, was shown to be associated with training effects. Our study findings help to elucidate the genetic architecture of innate immune memory in Drosophila and may provide insight for new therapeutic treatments aimed at boosting immunity.

Powerful, efficient QTL mapping in Drosophila melanogaster using bulked phenotyping and pooled sequencing

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.

Evolution of natural lifespan variation and molecular strategies of extended lifespan in yeast

To understand the genetic basis and selective forces acting on longevity, it is useful to examine lifespan variation among closely related species, or ecologically diverse isolates of the same species, within a controlled environment. In particular, this approach may lead to understanding mechanisms underlying natural variation in lifespan. Here, we analyzed 76 ecologically diverse wild yeast isolates and discovered a wide diversity of replicative lifespan (RLS). Phylogenetic analyses pointed to genes and environmental factors that strongly interact to modulate the observed aging patterns. We then identified genetic networks causally associated with natural variation in RLS across wild yeast isolates, as well as genes, metabolites, and pathways, many of which have never been associated with yeast lifespan in laboratory settings. In addition, a combined analysis of lifespan-associated metabolic and transcriptomic changes revealed unique adaptations to interconnected amino acid biosynthesis, glutamate metabolism, and mitochondrial function in long-lived strains. Overall, our multiomic and lifespan analyses across diverse isolates of the same species shows how gene-environment interactions shape cellular processes involved in phenotypic variation such as lifespan.

Consequences of Cryopreservation in Diverse Natural Isolates of Saccharomyces cerevisiae

Experimental evolution allows the observation of change over time as laboratory populations evolve in response to novel, controlled environments. Microbial evolution experiments take advantage of cryopreservation to archive experimental populations in glycerol media, creating a frozen, living "fossil" record. Prior research with Escherichia coli has shown that cryopreservation conditions can affect cell viability and that allele frequencies across the genome can change in response to a freeze-thaw event. We expand on these observations by characterizing fitness and genomic consequences of multiple freeze-thaw cycles in diploid yeast populations. Our study system is a highly recombinant Saccharomyces cerevisiae population (SGRP-4X) that harbors standing genetic variation that cryopreservation may threaten. We also investigate the four parental isogenic strains crossed to create the SGRP-4X. We measure cell viability over five consecutive freeze-thaw cycles; whereas we find that viability increases over time in the evolved recombinant populations, we observe no such viability improvements in the parental strains. We also collect genome-wide sequence data from experimental populations initially, after one freeze-thaw, and after five freeze-thaw cycles. In the recombinant evolved populations, we find a region of significant allele frequency change on chromosome 15 containing the ALR1 gene. In the parental strains, we find little evidence for new mutations. We conclude that cryopreserving yeast populations with standing genetic variation may have both phenotypic and genomic consequences, though the same cryopreservation practices may have only small impacts on populations with little or no initial variation.

Deleterious mutations show increasing negative effects with age in Drosophila melanogaster

BACKGROUND

In order for aging to evolve in response to a declining strength of selection with age, a genetic architecture that allows for mutations with age-specific effects on organismal performance is required. Our understanding of how selective effects of individual mutations are distributed across ages is however poor. Established evolutionary theories assume that mutations causing aging have negative late-life effects, coupled to either positive or neutral effects early in life. New theory now suggests evolution of aging may also result from deleterious mutations with increasing negative effects with age, a possibility that has not yet been empirically explored.

RESULTS

To directly test how the effects of deleterious mutations are distributed across ages, we separately measure age-specific effects on fecundity for each of 20 mutations in Drosophila melanogaster. We find that deleterious mutations in general have a negative effect that increases with age and that the rate of increase depends on how deleterious a mutation is early in life.

CONCLUSIONS

Our findings suggest that aging does not exclusively depend on genetic variants assumed by the established evolutionary theories of aging. Instead, aging can result from deleterious mutations with negative effects that amplify with age. If increasing negative effect with age is a general property of deleterious mutations, the proportion of mutations with the capacity to contribute towards aging may be considerably larger than previously believed.

Transposable Elements Are Important Contributors to Standing Variation in Gene Expression in Capsella Grandiflora

Transposable elements (TEs) make up a significant portion of eukaryotic genomes and are important drivers of genome evolution. However, the extent to which TEs affect gene expression variation on a genome-wide scale in comparison with other types of variants is still unclear. We characterized TE insertion polymorphisms and their association with gene expression in 124 whole-genome sequences from a single population of Capsella grandiflora, and contrasted this with the effects of single nucleotide polymorphisms (SNPs). Population frequency of insertions was negatively correlated with distance to genes, as well as density of conserved noncoding elements, suggesting that the negative effects of TEs on gene regulation are important in limiting their abundance. Rare TE variants strongly influence gene expression variation, predominantly through downregulation. In contrast, rare SNPs contribute equally to up- and down-regulation, but have a weaker individual effect than TEs. An expression quantitative trait loci (eQTL) analysis shows that a greater proportion of common TEs are eQTLs as opposed to common SNPs, and a third of the genes with TE eQTLs do not have SNP eQTLs. In contrast with rare TE insertions, common insertions are more likely to increase expression, consistent with recent models of cis-regulatory evolution favoring enhancer alleles. Taken together, these results imply that TEs are a significant contributor to gene expression variation and are individually more likely than rare SNPs to cause extreme changes in gene expression.

Diverse biological processes coordinate the transcriptional response to nutritional changes in a Drosophila melanogaster multiparent population

Background

Environmental variation in the amount of resources available to populations challenge individuals to optimize the allocation of those resources to key fitness functions. This coordination of resource allocation relative to resource availability is commonly attributed to key nutrient sensing gene pathways in laboratory model organisms, chiefly the insulin/TOR signaling pathway. However, the genetic basis of diet-induced variation in gene expression is less clear.

Results

To describe the natural genetic variation underlying nutrient-dependent differences, we used an outbred panel derived from a multiparental population, the Drosophila Synthetic Population Resource. We analyzed RNA sequence data from multiple female tissue samples dissected from flies reared in three nutritional conditions: high sugar (HS), dietary restriction (DR), and control (C) diets. A large proportion of genes in the experiment (19.6% or 2471 genes) were significantly differentially expressed for the effect of diet, and 7.8% (978 genes) for the effect of the interaction between diet and tissue type (LRT, P_adj. < 0.05). Interestingly, we observed similar patterns of gene expression relative to the C diet, in the DR and HS treated flies, a response likely reflecting diet component ratios. Hierarchical clustering identified 21 robust gene modules showing intra-modularly similar patterns of expression across diets, all of which were highly significant for diet or diet-tissue interaction effects (FDR P_adj. < 0.05). Gene set enrichment analysis for different diet-tissue combinations revealed a diverse set of pathways and gene ontology (GO) terms (two-sample t-test, FDR < 0.05). GO analysis on individual co-expressed modules likewise showed a large number of terms encompassing many cellular and nuclear processes (Fisher exact test, P_adj. < 0.01). Although a handful of genes in the IIS/TOR pathway including Ilp5, Rheb, and Sirt2 showed significant elevation in expression, many key genes such as InR, chico, most insulin peptide genes, and the nutrient-sensing pathways were not observed.

Conclusions

Our results suggest that a more diverse network of pathways and gene networks mediate the diet response in our population. These results have important implications for future studies focusing on diet responses in natural populations.

Life-History Evolution and the Genetics of Fitness Components in Drosophila melanogaster

Life-history traits or "fitness components"-such as age and size at maturity, fecundity and fertility, age-specific rates of survival, and life span-are the major phenotypic determinants of Darwinian fitness. Analyzing the evolution and genetics of these phenotypic targets of selection is central to our understanding of adaptation. Due to its simple and rapid life cycle, cosmopolitan distribution, ease of maintenance in the laboratory, well-understood evolutionary genetics, and its versatile genetic toolbox, the "vinegar fly" Drosophila melanogaster is one of the most powerful, experimentally tractable model systems for studying "life-history evolution." Here, I review what has been learned about the evolution and genetics of life-history variation in D. melanogaster by drawing on numerous sources spanning population and quantitative genetics, genomics, experimental evolution, evolutionary ecology, and physiology. This body of work has contributed greatly to our knowledge of several fundamental problems in evolutionary biology, including the amount and maintenance of genetic variation, the evolution of body size, clines and climate adaptation, the evolution of senescence, phenotypic plasticity, the nature of life-history trade-offs, and so forth. While major progress has been made, important facets of these and other questions remain open, and the D. melanogaster system will undoubtedly continue to deliver key insights into central issues of life-history evolution and the genetics of adaptation.

Identification of novel genes associated with longevity in Drosophila melanogaster - a computational approach

Despite a growing number of studies on longevity in Drosophila, genetic factors influencing lifespan are still poorly understood. In this paper we propose a conceptually new approach for the identification of novel longevity-associated genes and potential target genes for SNPs in non-coding regions by utilizing the knowledge of co-location of various loci, governed by the three-dimensional architecture of the Drosophila genome. Firstly, we created networks between genes/genomic regions harboring SNPs deemed to be significant in two longevity GWAS summary statistics datasets using intra- and inter-chromosomal interaction frequencies (Hi-C data) as a measure of co-location. These networks were further extended to include regions strongly interacting with previously selected regions. Using various network measures, literature search and additional bioinformatics resources, we investigated the plausibility of genes found to have genuine association with longevity. Several of the newly identified genes were common between the two GWAS datasets and these possessed human orthologs. We also found that the proportion of non-coding SNPs in borders between topologically associated domains is significantly higher than expected by chance. Assuming co-location, we investigated potential target genes for non-coding SNPs. This approach therefore offers a stepping stone to identification of novel genes and SNP targets linked to human longevity.

Multiple genetic loci affect place learning and memory performance in Drosophila melanogaster

Learning and memory are critical functions for all animals, giving individuals the ability to respond to changes in their environment. Within populations, individuals vary, however the mechanisms underlying this variation in performance are largely unknown. Thus, it remains to be determined what genetic factors cause an individual to have high learning ability and what factors determine how well an individual will remember what they have learned. To genetically dissect learning and memory performance, we used the Drosophila synthetic population resource (DSPR), a multiparent mapping resource in the model system Drosophila melanogaster, consisting of a large set of recombinant inbred lines (RILs) that naturally vary in these and other traits. Fruit flies can be trained in a "heat box" to learn to remain on one side of a chamber (place learning) and can remember this (place memory) over short timescales. Using this paradigm, we measured place learning and memory for ~49 000 individual flies from over 700 DSPR RILs. We identified 16 different loci across the genome that significantly affect place learning and/or memory performance, with 5 of these loci affecting both traits. To identify transcriptomic differences associated with performance, we performed RNA-Seq on pooled samples of seven high performing and seven low performing RILs for both learning and memory and identified hundreds of genes with differences in expression in the two sets. Integrating our transcriptomic results with the mapping results allowed us to identify nine promising candidate genes, advancing our understanding of the genetic basis underlying natural variation in learning and memory performance.

The evolutionary potential of diet-dependent effects on lifespan and fecundity in a multi-parental population of Drosophila melanogaster

The nutritional conditions experienced by a population have a major role in shaping trait evolution in many taxa. Constraints exerted by nutrient limitation or nutrient imbalance can influence the maximal value that fitness components such as reproduction and lifespan attains, and organisms may shift how resources are allocated to different structures and functions in response to changes in nutrition. Whether the phenotypic changes associated with changes in nutrition represent an adaptive response is largely unknown. Further, it is unclear whether the response of fitness components to diet even has the potential to evolve in most systems. In this study, we use an admixed multi-parental population of Drosophila melanogaster reared in three different diet conditions to estimate quantitative genetic parameters for lifespan and fecundity. We find significant genetic variation for both traits in our population and show that lifespan has moderate to high heritabilities within diets. Genetic correlations for lifespan between diets were significantly less than one, demonstrating a strong genotype by diet interaction. These findings demonstrate substantial standing genetic variation in our population that is comparable to natural populations and highlights the potential for adaptation to changing nutritional environments.

Horizons in the evolution of aging

Between the 1930s and 50s, evolutionary biologists developed a successful theory of why organisms age, firmly rooted in population genetic principles. By the 1980s the evolution of aging had a secure experimental basis. Since the force of selection declines with age, aging evolves due to mutation accumulation or a benefit to fitness early in life. Here we review major insights and challenges that have emerged over the last 35 years: selection does not always necessarily decline with age; higher extrinsic (i.e., environmentally caused) mortality does not always accelerate aging; conserved pathways control aging rate; senescence patterns are more diverse than previously thought; aging is not universal; trade-offs involving lifespan can be 'broken'; aging might be 'druggable'; and human life expectancy continues to rise but compressing late-life morbidity remains a pressing challenge.

A Genomic Reference Panel for Drosophila serrata

Here we describe a collection of re-sequenced inbred lines of Drosophila serrata, sampled from a natural population situated deep within the species endemic distribution in Brisbane, Australia. D. serrata is a member of the speciose montium group whose members inhabit much of south east Asia and has been well studied for aspects of climatic adaptation, sexual selection, sexual dimorphism, and mate recognition. We sequenced 110 lines that were inbred via 17-20 generations of full-sib mating at an average coverage of 23.5x with paired-end Illumina reads. 15,228,692 biallelic SNPs passed quality control after being called using the Joint Genotyper for Inbred Lines (JGIL). Inbreeding was highly effective and the average levels of residual heterozygosity (0.86%) were well below theoretical expectations. As expected, linkage disequilibrium decayed rapidly, with r² dropping below 0.1 within 100 base pairs. With the exception of four closely related pairs of lines which may have been due to technical errors, there was no statistical support for population substructure. Consistent with other endemic populations of other Drosophila species, preliminary population genetic analyses revealed high nucleotide diversity and, on average, negative Tajima’s D values. A preliminary GWAS was performed on a cuticular hydrocarbon trait, 2-Me-C₂₈ revealing 4 SNPs passing Bonferroni significance residing in or near genes. One gene Cht9 may be involved in the transport of CHCs from the site of production (oenocytes) to the cuticle. Our panel will facilitate broader population genomic and quantitative genetic studies of this species and serve as an important complement to existing D. melanogaster panels that can be used to test for the conservation of genetic architectures across the Drosophila genus.

Analysis of motility in multicellular Chlamydomonas reinhardtii evolved under predation

The advent of multicellularity was a watershed event in the history of life, yet the transition from unicellularity to multicellularity is not well understood. Multicellularity opens up opportunities for innovations in intercellular communication, cooperation, and specialization, which can provide selective advantages under certain ecological conditions. The unicellular alga Chlamydomonas reinhardtii has never had a multicellular ancestor yet it is closely related to the volvocine algae, a clade containing taxa that range from simple unicells to large, specialized multicellular colonies. Simple multicellular structures have been observed to evolve in C. reinhardtii in response to predation or to settling rate-based selection. Structures formed in response to predation consist of individual cells confined within a shared transparent extracellular matrix. Evolved isolates form such structures obligately under culture conditions in which their wild type ancestors do not, indicating that newly-evolved multicellularity is heritable. C. reinhardtii is capable of photosynthesis, and possesses an eyespot and two flagella with which it moves towards or away from light in order to optimize input of radiant energy. Motility contributes to C. reinhardtii fitness because it allows cells or colonies to achieve this optimum. Utilizing phototaxis to assay motility, we determined that newly evolved multicellular strains do not exhibit significant directional movement, even though the flagellae of their constituent unicells are present and active. In C. reinhardtii the first steps towards multicellularity in response to predation appear to result in a trade-off between motility and differential survivorship, a trade-off that must be overcome by further genetic change to ensure long-term success of the new multicellular organism.

Genetic Dissection of Nutrition-Induced Plasticity in Insulin/Insulin-Like Growth Factor Signaling and Median Life Span in a Drosophila Multiparent Population

The nutritional environments that organisms experience are inherently variable, requiring tight coordination of how resources are allocated to different functions relative to the total amount of resources available. A growing body of evidence supports the hypothesis that key endocrine pathways play a fundamental role in this coordination. In particular, the insulin/insulin-like growth factor signaling (IIS) and target of rapamycin (TOR) pathways have been implicated in nutrition-dependent changes in metabolism and nutrient allocation. However, little is known about the genetic basis of standing variation in IIS/TOR or how diet-dependent changes in expression in this pathway influence phenotypes related to resource allocation. To characterize natural genetic variation in the IIS/TOR pathway, we used >250 recombinant inbred lines (RILs) derived from a multiparental mapping population, the Drosophila Synthetic Population Resource, to map transcript-level QTL of genes encoding 52 core IIS/TOR components in three different nutritional environments [dietary restriction (DR), control (C), and high sugar (HS)]. Nearly all genes, 87%, were significantly differentially expressed between diets, though not always in ways predicted by loss-of-function mutants. We identified cis (i.e., local) expression QTL (eQTL) for six genes, all of which are significant in multiple nutrient environments. Further, we identified trans (i.e., distant) eQTL for two genes, specific to a single nutrient environment. Our results are consistent with many small changes in the IIS/TOR pathways. A discriminant function analysis for the C and DR treatments identified a pattern of gene expression associated with the diet treatment. Mapping the composite discriminant function scores revealed a significant global eQTL within the DR diet. A correlation between the discriminant function scores and the median life span (r = 0.46) provides evidence that gene expression changes in response to diet are associated with longevity in these RILs.

How to get the most bang for your buck: the evolution and physiology of nutrition-dependent resource allocation strategies

All organisms use resources to grow, survive and reproduce. The supply of these resources varies widely across landscapes and time, imposing ultimate constraints on the maximal trait values for allocation-related traits. In this review, we address three key questions fundamental to our understanding of the evolution of allocation strategies and their underlying mechanisms. First, we ask: how diverse are flexible resource allocation strategies among different organisms? We find there are many, varied, examples of flexible strategies that depend on nutrition. However, this diversity is often ignored in some of the best-known cases of resource allocation shifts, such as the commonly observed pattern of lifespan extension under nutrient limitation. A greater appreciation of the wide variety of flexible allocation strategies leads directly to our second major question: what conditions select for different plastic allocation strategies? Here, we highlight the need for additional models that explicitly consider the evolution of phenotypically plastic allocation strategies and empirical tests of the predictions of those models in natural populations. Finally, we consider the question: what are the underlying mechanisms determining resource allocation strategies? Although evolutionary biologists assume differential allocation of resources is a major factor limiting trait evolution, few proximate mechanisms are known that specifically support the model. We argue that an integrated framework can reconcile evolutionary models with proximate mechanisms that appear at first glance to be in conflict with these models. Overall, we encourage future studies to: (i) mimic ecological conditions in which those patterns evolve, and (ii) take advantage of the 'omic' opportunities to produce multi-level data and analytical models that effectively integrate across physiological and evolutionary theory.

Genetic analysis of variation in lifespan using a multiparental advanced intercross Drosophila mapping population

BACKGROUND

Considerable natural variation for lifespan exists within human and animal populations. Genetically dissecting this variation can elucidate the pathways and genes involved in aging, and help uncover the genetic mechanisms underlying risk for age-related diseases. Studying aging in model systems is attractive due to their relatively short lifespan, and the ability to carry out programmed crosses under environmentally-controlled conditions. Here we investigate the genetic architecture of lifespan using the Drosophila Synthetic Population Resource (DSPR), a multiparental advanced intercross mapping population.

RESULTS

We measured lifespan in females from 805 DSPR lines, mapping five QTL (Quantitative Trait Loci) that each contribute 4-5 % to among-line lifespan variation in the DSPR. Each of these QTL co-localizes with the position of at least one QTL mapped in 13 previous studies of lifespan variation in flies. However, given that these studies implicate >90 % of the genome in the control of lifespan, this level of overlap is unsurprising. DSPR QTL intervals harbor 11-155 protein-coding genes, and we used RNAseq on samples of young and old flies to help resolve pathways affecting lifespan, and identify potentially causative loci present within mapped QTL intervals. Broad age-related patterns of expression revealed by these data recapitulate results from previous work. For example, we see an increase in antimicrobial defense gene expression with age, and a decrease in expression of genes involved in the electron transport chain. Several genes within QTL intervals are highlighted by our RNAseq data, such as Relish, a critical immune response gene, that shows increased expression with age, and UQCR-14, a gene involved in mitochondrial electron transport, that has reduced expression in older flies.

CONCLUSIONS

The five QTL we isolate collectively explain a considerable fraction of the genetic variation for female lifespan in the DSPR, and implicate modest numbers of genes. In several cases the candidate loci we highlight reside in biological pathways already implicated in the control of lifespan variation. Thus, our results provide further evidence that functional genetics tests targeting these genes will be fruitful, lead to the identification of natural sequence variants contributing to lifespan variation, and help uncover the mechanisms of aging.

Genome-Wide Association Study Identifies Novel Candidate Genes for Aggressiveness, Deoxynivalenol Production, and Azole Sensitivity in Natural Field Populations of Fusarium graminearum

Genome-wide association studies can identify novel genomic regions and genes that affect quantitative traits. Fusarium head blight is a destructive disease caused by Fusarium graminearum that exhibits several quantitative traits, including aggressiveness, mycotoxin production, and fungicide resistance. Restriction site-associated DNA sequencing was performed for 220 isolates of F. graminearum. A total of 119 isolates were phenotyped for aggressiveness and deoxynivalenol (DON) production under natural field conditions across four environments. The effective concentration of propiconazole that inhibits isolate growth in vitro by 50% was calculated for 220 strains. Approximately 29,000 single nucleotide polymorphism markers were associated to each trait, resulting in 50, 29, and 74 quantitative trait nucleotides (QTNs) that were significantly associated to aggressiveness, DON production, and propiconazole sensitivity, respectively. Approximately 41% of these QTNs caused nonsynonymous substitutions in predicted exons, while the remainder were synonymous substitutions or located in intergenic regions. Three QTNs associated with propiconazole sensitivity were significant after Bonferroni correction. These QTNs were located in genes not previously associated with azole sensitivity. The majority of the detected QTNs were located in genes with predicted regulatory functions, suggesting that nucleotide variation in regulatory genes plays a major role in the corresponding quantitative trait variation.

Viruses in close associations with free-living amoebae

As both groups of organisms, free-living amoebae (FLA) and viruses, can be found in aquatic environments side by side, it appears obvious that there are multiple interactions with respect to host-endocytobiont relationships. Several relationships between viruses and protozoan hosts are described and it was the discovery of the so called "giant viruses," associated with amoebae, which gave another dimension to these interactions. Mimiviruses, Pandoraviruses and Pithoviruses are examples for interesting viral endocytobionts within FLA. In the Mimivirus viral factories, viral DNA undergoes replication and transcription, and the DNA is prepared to be packed in procapsids. Theses Mimivirus factories can be considered as efficient "production lines" where, at any given moment, all stages of viral generation including membrane biogenesis, capsid assembly and genome encapsidation, are occurring concomitantly. There are some hints that similar replication factories are involved as well during the Pandoravirus development. Some scientists favour the assumption that the giant viruses have received many of their genes from their hosts or from sympatric occurring endocytobionts via lateral gene transfer. This hypothesis would mean that this type of transfer has been an important process in the evolution of genomes in the context of the intracellular parasitic or endocytobiotic lifestyle. In turn, that would migitate against hypothesizing development of a new branch in the tree of life. Based on the described scenarios to explain the presence of genes related to translation, it is also possible that earlier ancestors of today's DNA viruses were involved in the origin of eukaryotes. That possibly could in turn support the idea that cellular organisms could have evolved from viruses with growing autarkic properties. In future we expect the discovery of further (giant) viruses within free-living amoebae and other protozoa through genomic, transcriptomic and proteomic analyses.

The use of genetic information in the prediction of Type 2 diabetes

Type 2 diabetes (T2D) is a metabolic disorder characterized by high blood glucose levels and elevated risk of cardiovascular events. The progression of T2D can be delayed, or prevented, so early prediction is of high importance. More than 70 genetic loci are associated with T2D risk, raising the possibility of early identification of future cases. Results show that the benefits in discrimination by including genes in current risk models are uncertain. Improvements have been shown in reclassification but are too modest for clinical use. Given the current guidelines for T2D risk assessment and the increasing availability of genotyped individuals, we could soon be able to use genetics, not to quantify risk, but to inform clinicians on those requiring earlier observation.

Standing genetic variation drives repeatable experimental evolution in outcrossing populations of Saccharomyces cerevisiae

In "evolve-and-resequence" (E&R) experiments, whole-genome sequence data from laboratory-evolved populations can potentially uncover mechanisms of adaptive change. E&R experiments with initially isogenic, asexually reproducing microbes have repeatedly shown that beneficial de novo mutations drive adaptation, and these mutations are not shared among independently evolving replicate populations. Recent E&R experiments with higher eukaryotes that maintain genetic variation via sexual reproduction implicate largely different mechanisms; adaptation may act primarily on pre-existing genetic variation and occur in parallel among independent populations. But this is currently a debated topic, and generalizing these conclusions is problematic because E&R experiments with sexual species are difficult to implement and important elements of experimental design suffer for practical reasons. We circumvent potentially confounding limitations with a yeast model capable of shuffling genotypes via sexual recombination. Our starting population consisted of a highly intercrossed diploid Saccharomyces cerevisiae initiated from four wild haplotypes. We imposed a laboratory domestication treatment on 12 independent replicate populations for 18 weeks, where each week included 2 days as diploids in liquid culture and a forced recombination/mating event. We then sequenced pooled population samples at weeks 0, 6, 12, and 18. We show that adaptation is highly parallel among replicate populations, and can be localized to a modest number of genomic regions. We also demonstrate that despite hundreds of generations of evolution and large effective population sizes, de novo beneficial mutations do not play a large role in this adaptation. Further, we have high power to detect the signal of change in these populations but show how this power is dramatically reduced when fewer timepoints are sampled, or fewer replicate populations are analyzed. As ours is the most highly replicated and sampled E&R study in a sexual species to date, this evokes important considerations for past and future experiments.

Genome-wide analysis in Drosophila reveals age-specific effects of SNPs on fitness traits

Most organisms exhibit senescence; a decline in physiological function with age. In nature, rates of senescence vary extensively among individuals and this variation has a significant genetic component; however, we know little about the genes underlying senescence. Here we show the first evidence that individual alleles influence fecundity in an age-specific manner and so the genetic basis of natural variation in fecundity changes dramatically with age. We complete a genome-wide association to identify single-nucleotide polymorphisms (SNPs) affecting lifespan and age-specific fecundity using the Drosophila melanogaster Genetic Reference Panel. We identify 1,031 SNPs affecting fecundity and 52 influencing lifespan. Only one SNP is associated with both early- and late-age fecundity. The age-specific effect of candidate genes on fecundity is validated using RNA interference. In addition, there is a dramatic increase in the number of SNPs influencing fecundity with age. This result provides support for the mutation accumulation theory of aging.