Pervasive joint influence of epistasis and plasticity on mutational effects in Escherichia coli

The effects of mutations on phenotype and fitness may depend on the environment (phenotypic plasticity), other mutations (genetic epistasis) or both. Here we examine the fitness effects of 18 random insertion mutations in E. coli in two resource environments and five genetic backgrounds. We tested each mutation for plasticity and epistasis by comparing its fitness effects across these ecological and genetic contexts. Some mutations had no measurable effect in any of these contexts. None of the mutations had effects on phenotypic plasticity that were independent of genetic background. However, half the mutations had epistatic interactions such that their effects differed among genetic backgrounds, usually in an environment-dependent manner. Also, the pattern of mutational effects across backgrounds indicated that epistasis had been shaped primarily by unique events in the evolutionary history of a population rather than by repeatable events associated with shared environmental history.     

An empirical test of the mutational landscape model of adaptation using a single-stranded DNA virus

The primary impediment to formulating a general theory for adaptive evolution has been the unknown distribution of fitness effects for new beneficial mutations. By applying extreme value theory, Gillespie circumvented this issue in his mutational landscape model for the adaptation of DNA sequences, and Orr recently extended Gillespie's model, generating testable predictions regarding the course of adaptive evolution. Here we provide the first empirical examination of this model, using a single-stranded DNA bacteriophage related to phiX174, and find that our data are consistent with Orr's predictions, provided that the model is adjusted to incorporate mutation bias. Orr's work suggests that there may be generalities in adaptive molecular evolution that transcend the biological details of a system, but we show that for the model to be useful as a predictive or inferential tool, some adjustments for the biology of the system will be necessary.     

Genomic buffering mitigates the effects of deleterious mutations in bacteria

The relationship between the number of randomly accumulated mutations in a genome and fitness is a key parameter in evolutionary biology. Mutations may interact such that their combined effect on fitness is additive (no epistasis), reinforced (synergistic epistasis) or mitigated (antagonistic epistasis). We measured the decrease in fitness caused by increasing mutation number in the bacterium Salmonella typhimurium using a regulated, error-prone DNA polymerase (polymerase IV, DinB). As mutations accumulated, fitness costs increased at a diminishing rate. This suggests that random mutations interact such that their combined effect on fitness is mitigated and that the genome is buffered against the fitness reduction caused by accumulated mutations. Levels of the heat shock chaperones DnaK and GroEL increased in lineages that had accumulated many mutations, and experimental overproduction of GroEL further increased the fitness of lineages containing deleterious mutations. These findings suggest that overexpression of chaperones contributes to antagonistic epistasis.     

Distribution of fitness effects among beneficial mutations before selection in experimental populations of bacteria

The extent to which a population diverges from its ancestor through adaptive evolution depends on variation supplied by novel beneficial mutations. Extending earlier work, recent theory makes two predictions that seem to be robust to biological details: the distribution of fitness effects among beneficial mutations before selection should be (i) exponential and (ii) invariant, meaning it is always exponential regardless of the fitness rank of the wild-type allele. Here we test these predictions by assaying the fitness of 665 independently derived single-step mutations in the bacterium Pseudomonas fluorescens across a range of environments. We show that the distribution of fitness effects among beneficial mutations is indistinguishable from an exponential despite marked variation in the fitness rank of the wild type across environments. These results suggest that the initial step in adaptive evolution--the production of novel beneficial mutants from which selection sorts--is very general, being characterized by an approximately exponential distribution with many mutations of small effect and few of large effect. We also document substantial variation in the pleiotropic costs of antibiotic resistance, a result that may have implications for strategies aimed at eliminating resistant pathogens in animal and human populations.     

Modular epistasis in yeast metabolism

Epistatic interactions, manifested in the effects of mutations on the phenotypes caused by other mutations, may help uncover the functional organization of complex biological networks. Here, we studied system-level epistatic interactions by computing growth phenotypes of all single and double knockouts of 890 metabolic genes in Saccharomyces cerevisiae, using the framework of flux balance analysis. A new scale for epistasis identified a distinctive trimodal distribution of these epistatic effects, allowing gene pairs to be classified as buffering, aggravating or noninteracting. We found that the ensuing epistatic interaction network could be organized hierarchically into function-enriched modules that interact with each other 'monochromatically' (i.e., with purely aggravating or purely buffering epistatic links). This property extends the concept of epistasis from single genes to functional units and provides a new definition of biological modularity, which emphasizes interactions between, rather than within, functional modules. Our approach can be used to infer functional gene modules from purely phenotypic epistasis measurements.     

Epistatic buffering of fitness loss in yeast double deletion strains

Interactions between deleterious mutations have been insufficiently studied, despite the fact that their strength and direction are critical for understanding the evolution of genetic recombination and the buildup of mutational load in populations. We compiled a list of 758 yeast gene deletions causing growth defects (from the Munich Information Center for Protein Sequences database and ref. 7). Using BY4741 and BY4742 single-deletion strains, we carried out 639 random crosses and assayed growth curves of the resulting progeny. We show that the maximum growth rate averaged over strains lacking deletions and those with double deletions is higher than that of strains with single deletions, indicating a positive epistatic effect. This tendency is shared by genes belonging to a variety of functional classes. Based on our data and former theoretical work, we suggest that epistasis is likely to diminish the negative effects of mutations when the ability to produce biomass at high rates contributes significantly to fitness.     

Pleiotropic fitness effects of the Tre1-Gr5a region in Drosophila melanogaster

The abundance of transposable elements and DNA repeat sequences in mammalian genomes raises the question of whether such insertions represent passive evolutionary baggage or may influence the expression of complex traits. We addressed this question in Drosophila melanogaster, in which the effects of single transposable elements on complex traits can be assessed in genetically identical individuals reared in controlled environments. Here we demonstrate that single P-element insertions in the intergenic region between the gustatory receptor 5a (Gr5a, also known as Tre) and trapped in endoderm 1 (Tre1), which encodes an orphan receptor, exert complex pleiotropic effects on fitness traits, including selective nutrient intake, life span, and resistance to starvation and heat stress. Mutations in this region interact epistatically with downstream components of the insulin signaling pathway. Transposon-induced sex-specific and sex-antagonistic effects further accentuate the complex influences that intergenic transposable elements can contribute to quantitative trait phenotypes.     

Bayesian inference of epistatic interactions in case-control studies

Epistatic interactions among multiple genetic variants in the human genome may be important in determining individual susceptibility to common diseases. Although some existing computational methods for identifying genetic interactions have been effective for small-scale studies, we here propose a method, denoted 'bayesian epistasis association mapping' (BEAM), for genome-wide case-control studies. BEAM treats the disease-associated markers and their interactions via a bayesian partitioning model and computes, via Markov chain Monte Carlo, the posterior probability that each marker set is associated with the disease. Testing this on an age-related macular degeneration genome-wide association data set, we demonstrate that the method is significantly more powerful than existing approaches and that genome-wide case-control epistasis mapping with many thousands of markers is both computationally and statistically feasible.     

Common deletions and SNPs are in linkage disequilibrium in the human genome

Humans show great variation in phenotypic traits such as height, eye color and susceptibility to disease. Genomic DNA sequence differences among individuals are responsible for the inherited components of these complex traits. Reports suggest that intermediate and large-scale DNA copy number and structural variations are prevalent enough to be an important source of genetic variation between individuals. Because association studies to identify genomic loci associated with particular phenotypic traits have focused primarily on genotyping SNPs, it is important to determine whether common structural polymorphisms are in linkage disequilibrium with common SNPs, and thus can be assessed indirectly in SNP-based studies. Here we examine 100 deletion polymorphisms ranging from 70 bp to 7 kb. We show that common deletions and SNPs ascertained with similar criteria have essentially the same distribution of linkage disequilibrium with surrounding SNPs, indicating that these polymorphisms may share evolutionary history and that most deletion polymorphisms are effectively assayed by proxy in SNP-based association studies.     

On the subspecific origin of the laboratory mouse

The genome of the laboratory mouse is thought to be a mosaic of regions with distinct subspecific origins. We have developed a high-resolution map of the origin of the laboratory mouse by generating 25,400 phylogenetic trees at 100-kb intervals spanning the genome. On average, 92% of the genome is of Mus musculus domesticus origin, and the distribution of diversity is markedly nonrandom among the chromosomes. There are large regions of extremely low diversity, which represent blind spots for studies of natural variation and complex traits, and hot spots of diversity. In contrast with the mosaic model, we found that most of the genome has intermediate levels of variation of intrasubspecific origin. Finally, mouse strains derived from the wild that are supposed to represent different mouse subspecies show substantial intersubspecific introgression, which has strong implications for evolutionary studies that assume these are pure representatives of a given subspecies.     

Exposing the fitness contribution of duplicated genes

Duplicate genes from the whole-genome duplication (WGD) in yeast are often dispensable--removing one copy has little or no phenotypic consequence. It is unknown, however, whether such dispensability reflects insignificance of the ancestral function or compensation from paralogs. Here, using precise competition-based measurements of the fitness cost of single and double deletions, we estimate the exposed fitness contribution of WGD duplicate genes in metabolism and bound the importance of their ancestral pre-duplication function. We find that the functional overlap between paralogs sufficiently explains the apparent dispensability of individual WGD genes. Furthermore, the lower bound on the fitness value of the ancestral function, which is estimated by the degree of synergistic epistasis, is at least as large as the average fitness cost of deleting single non-WGD genes. These results suggest that most metabolic functions encoded by WGD genes are important today and were also important at the time of duplication.     

Real ribozymes suggest a relaxed error threshold

The error threshold for replication, the critical copying fidelity below which the fittest genotype deterministically disappears, limits the length of the genome that can be maintained by selection. Primordial replication must have been error-prone, and so early replicators are thought to have been necessarily short. The error threshold also depends on the fitness landscape. In an RNA world, many neutral and compensatory mutations can raise the threshold, below which the functional phenotype, rather than a particular sequence, is still present. Here we show, on the basis of comparative analysis of two extensively mutagenized ribozymes, that with a copying fidelity of 0.999 per digit per replication the phenotypic error threshold rises well above 7,000 nucleotides, which permits the selective maintenance of a functionally rich riboorganism with a genome of more than 100 different genes, the size of a tRNA. This requires an order of magnitude of improvement in the accuracy of in vitro-generated polymerase ribozymes. Incidentally, this genome size coincides with that estimated for a minimal cell achieved by top-down analysis, omitting the genes dealing with translation.     

Evidence that positive selection drives Y-chromosome degeneration in Drosophila miranda

Why does the Y chromosome harbor so few functional loci? Evolutionary theory predicts that Y chromosomes degenerate because they lack genetic recombination. Both positive and negative selection models have been invoked to explain this degeneration, as both can result in the recurrent fixation of linked deleterious mutations on a nonrecombining Y chromosome. To distinguish between these models, I investigated patterns of nucleotide variability along 37 kb of the recently formed neo-Y chromosome in Drosophila miranda. Levels of nucleotide variability on this chromosome are 30 times lower than in highly recombining portions of the genome. Both positive and negative selection models can result in reduced variability levels, but their effects on the frequency spectrum of mutations differ. Using coalescent simulations, I show that the patterns of nucleotide variability on the neo-Y chromosome are unlikely under deleterious mutation models (including background selection and Muller's ratchet) but are expected under recent positive selection. These results implicate positive selection as an important force driving the degeneration of Y chromosomes; adaptation at a few loci, possibly increasing male fitness, occurs at the cost of most other genes on this chromosome.     

Mutant glycosyltransferase and altered glycosylation of alpha-dystroglycan in the myodystrophy mouse

Spontaneous and engineered mouse mutants have facilitated our understanding of the pathogenesis of muscular dystrophy and they provide models for the development of therapeutic approaches. The mouse myodystrophy (myd) mutation produces an autosomal recessive, neuromuscular phenotype. Homozygotes have an abnormal gait, show abnormal posturing when suspended by the tail and are smaller than littermate controls. Serum creatine kinase is elevated and muscle histology is typical of a progressive myopathy with focal areas of acute necrosis and clusters of regenerating fibers. Additional aspects of the phenotype include sensorineural deafness, reduced lifespan and decreased reproductive fitness. The myd mutation maps to mouse chromosome 8 at approximately 33 centimorgans (cM) (refs. 2, 4-7). Here we show that the gene mutated in myd encodes a glycosyltransferase, Large. The human homolog of this gene (LARGE) maps to chromosome 22q. In myd, an intragenic deletion of exons 4-7 causes a frameshift in the resultant mRNA and a premature termination codon before the first of the two catalytic domains. On immunoblots, a monoclonal antibody to alpha-dystroglycan (a component of the dystrophin-associated glycoprotein complex) shows reduced binding in myd, which we attribute to altered glycosylation of this protein. We speculate that abnormal post-translational modification of alpha-dystroglycan may contribute to the myd phenotype.     

A human ortholog of archaeal DNA repair protein Hef is defective in Fanconi anemia complementation group M

Fanconi anemia is a genetic disease characterized by genomic instability and cancer predisposition. Nine genes involved in Fanconi anemia have been identified; their products participate in a DNA damage-response network involving BRCA1 and BRCA2 (refs. 2,3). We previously purified a Fanconi anemia core complex containing the FANCL ubiquitin ligase and six other Fanconi anemia-associated proteins. Each protein in this complex is essential for monoubiquitination of FANCD2, a key reaction in the Fanconi anemia DNA damage-response pathway. Here we show that another component of this complex, FAAP250, is mutant in individuals with Fanconi anemia of a new complementation group (FA-M). FAAP250 or FANCM has sequence similarity to known DNA-repair proteins, including archaeal Hef, yeast MPH1 and human ERCC4 or XPF. FANCM can dissociate DNA triplex, possibly owing to its ability to translocate on duplex DNA. FANCM is essential for monoubiquitination of FANCD2 and becomes hyperphosphorylated in response to DNA damage. Our data suggest an evolutionary link between Fanconi anemia-associated proteins and DNA repair; FANCM may act as an engine that translocates the Fanconi anemia core complex along DNA.     

An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations

Population structure causes genome-wide linkage disequilibrium between unlinked loci, leading to statistical confounding in genome-wide association studies. Mixed models have been shown to handle the confounding effects of a diffuse background of large numbers of loci of small effect well, but they do not always account for loci of larger effect. Here we propose a multi-locus mixed model as a general method for mapping complex traits in structured populations. Simulations suggest that our method outperforms existing methods in terms of power as well as false discovery rate. We apply our method to human and Arabidopsis thaliana data, identifying new associations and evidence for allelic heterogeneity. We also show how a priori knowledge from an A. thaliana linkage mapping study can be integrated into our method using a Bayesian approach. Our implementation is computationally efficient, making the analysis of large data sets (n > 10,000) practicable.     

An integrated approach to characterize genetic interaction networks in yeast metabolism

Although experimental and theoretical efforts have been applied to globally map genetic interactions, we still do not understand how gene-gene interactions arise from the operation of biomolecular networks. To bridge the gap between empirical and computational studies, we i, quantitatively measured genetic interactions between ～185,000 metabolic gene pairs in Saccharomyces cerevisiae, ii, superposed the data on a detailed systems biology model of metabolism and iii, introduced a machine-learning method to reconcile empirical interaction data with model predictions. We systematically investigated the relative impacts of functional modularity and metabolic flux coupling on the distribution of negative and positive genetic interactions. We also provide a mechanistic explanation for the link between the degree of genetic interaction, pleiotropy and gene dispensability. Last, we show the feasibility of automated metabolic model refinement by correcting misannotations in NAD biosynthesis and confirming them by in vivo experiments.     

Stochastic switching as a survival strategy in fluctuating environments

A classic problem in population and evolutionary biology is to understand how a population optimizes its fitness in fluctuating environments. A population might enhance its fitness by allowing individual cells to stochastically transition among multiple phenotypes, thus ensuring that some cells are always prepared for an unforeseen environmental fluctuation. Here we experimentally explore how switching affects population growth by using the galactose utilization network of Saccharomyces cerevisiae. We engineered a strain that randomly transitions between two phenotypes as a result of stochastic gene expression. Each phenotype was designed to confer a growth advantage over the other phenotype in a certain environment. When we compared the growth of two populations with different switching rates, we found that fast-switching populations outgrow slow switchers when the environment fluctuates rapidly, whereas slow-switching phenotypes outgrow fast switchers when the environment changes rarely. These results suggest that cells may tune inter-phenotype switching rates to the frequency of environmental changes.     

Genome-wide association study of leaf architecture in the maize nested association mapping population

US maize yield has increased eight-fold in the past 80 years, with half of the gain attributed to selection by breeders. During this time, changes in maize leaf angle and size have altered plant architecture, allowing more efficient light capture as planting density has increased. Through a genome-wide association study (GWAS) of the maize nested association mapping panel, we determined the genetic basis of important leaf architecture traits and identified some of the key genes. Overall, we demonstrate that the genetic architecture of the leaf traits is dominated by small effects, with little epistasis, environmental interaction or pleiotropy. In particular, GWAS results show that variations at the liguleless genes have contributed to more upright leaves. These results demonstrate that the use of GWAS with specially designed mapping populations is effective in uncovering the basis of key agronomic traits.