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.     

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.     

Genome-wide association study and mouse model identify interaction between RET and EDNRB pathways in Hirschsprung disease

Genetic studies of Hirschsprung disease, a common congenital malformation, have identified eight genes with mutations that can be associated with this condition. Mutations at individual loci are, however, neither necessary nor sufficient to cause clinical disease. We conducted a genome-wide association study in 43 Mennonite family trios using 2,083 microsatellites and single-nucleotide polymorphisms and a new multipoint linkage disequilibrium method that searches for association arising from common ancestry. We identified susceptibility loci at 10q11, 13q22 and 16q23; the gene at 13q22 is EDNRB, encoding a G protein-coupled receptor (GPCR) and the gene at 10q11 is RET, encoding a receptor tyrosine kinase (RTK). Statistically significant joint transmission of RET and EDNRB alleles in affected individuals and non-complementation of aganglionosis in mouse intercrosses between Ret null and the Ednrb hypomorphic piebald allele are suggestive of epistasis between EDNRB and RET. Thus, genetic interaction between mutations in RET and EDNRB is an underlying mechanism for this complex disorder.     

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.     

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.     

Epistasis analysis with global transcriptional phenotypes

Classical epistasis analysis can determine the order of function of genes in pathways using morphological, biochemical and other phenotypes. It requires knowledge of the pathway's phenotypic output and a variety of experimental expertise and so is unsuitable for genome-scale analysis. Here we used microarray profiles of mutants as phenotypes for epistasis analysis. Considering genes that regulate activity of protein kinase A in Dictyostelium, we identified known and unknown epistatic relationships and reconstructed a genetic network with microarray phenotypes alone. This work shows that microarray data can provide a uniform, quantitative tool for large-scale genetic network analysis.     

Biochemical networking contributes more to genetic buffering in human and mouse metabolic pathways than does gene duplication

During evolution different genes evolve at unequal rates, reflecting the varying functional constraints on phenotype. An important contributor to this variation is genetic buffering, which reduces the potential detrimental effects of mutations. We studied whether gene duplication and redundant metabolic networks affect genetic buffering by comparing the evolutionary rate of 242 human and mouse orthologous genes involved in metabolic pathways. A gene with a redundant network is defined as one for which the structural layout of metabolic pathways provides an alternative metabolic route that can, in principle, compensate for the loss of a protein function encoded by the gene. We found that genes with redundant networks evolve at similar rates as did genes without redundant networks, [corrected] but no significant difference was detected between single-copy genes and gene families. This implies that redundancy in metabolic networks provides significantly more genetic buffering than do gene families. We also found that genes encoding proteins involved in glycolysis and gluconeogenesis showed as a group a distinct pattern of variation, in contrast to genes involved in other pathways. These results suggest that redundant networks provide genetic buffering and contribute to the functional diversification of metabolic pathways.     

Distributions of epistasis in microbes fit predictions from a fitness landscape model

How do the fitness effects of several mutations combine? Despite its simplicity, this question is central to the understanding of multilocus evolution. Epistasis (the interaction between alleles at different loci), especially epistasis for fitness traits such as reproduction and survival, influences evolutionary predictions "almost whenever multilocus genetics matters". Yet very few models have sought to predict epistasis, and none has been empirically tested. Here we show that the distribution of epistasis can be predicted from the distribution of single mutation effects, based on a simple fitness landscape model. We show that this prediction closely matches the empirical measures of epistasis that have been obtained for Escherichia coli and the RNA virus vesicular stomatitis virus. Our results suggest that a simple fitness landscape model may be sufficient to quantitatively capture the complex nature of gene interactions. This model may offer a simple and widely applicable alternative to complex metabolic network models, in particular for making evolutionary predictions.     

Dichotomy of single-nucleotide polymorphism haplotypes in olfactory receptor genes and pseudogenes

Substantial efforts are focused on identifying single-nucleotide polymorphisms (SNPs) throughout the human genome, particularly in coding regions (cSNPs), for both linkage disequilibrium and association studies. Less attention, however, has been directed to the clarification of evolutionary processes that are responsible for the variability in nucleotide diversity among different regions of the genome. We report here the population sequence diversity of genomic segments within a 450-kb cluster of olfactory receptor (OR) genes on human chromosome 17. We found a dichotomy in the pattern of nucleotide diversity between OR pseudogenes and introns on the one hand and the closely interspersed intact genes on the other. We suggest that weak positive selection is responsible for the observed patterns of genetic variation. This is inferred from a lower ratio of polymorphism to divergence in genes compared with pseudogenes or introns, high non-synonymous substitution rates in OR genes, and a small but significant overall reduction in variability in the entire OR gene cluster compared with other genomic regions. The dichotomy among functionally different segments within a short genomic distance requires high recombination rates within this OR cluster. Our work demonstrates the impact of weak positive selection on human nucleotide diversity, and has implications for the evolution of the olfactory repertoire.     

Gains of glycosylation comprise an unexpectedly large group of pathogenic mutations

Mutations involving gains of glycosylation have been considered rare, and the pathogenic role of the new carbohydrate chains has never been formally established. We identified three children with mendelian susceptibility to mycobacterial disease who were homozygous with respect to a missense mutation in IFNGR2 creating a new N-glycosylation site in the IFNgammaR2 chain. The resulting additional carbohydrate moiety was both necessary and sufficient to abolish the cellular response to IFNgamma. We then searched the Human Gene Mutation Database for potential gain-of-N-glycosylation missense mutations; of 10,047 mutations in 577 genes encoding proteins trafficked through the secretory pathway, we identified 142 candidate mutations ( approximately 1.4%) in 77 genes ( approximately 13.3%). Six mutant proteins bore new N-linked carbohydrate moieties. Thus, an unexpectedly high proportion of mutations that cause human genetic disease might lead to the creation of new N-glycosylation sites. Their pathogenic effects may be a direct consequence of the addition of N-linked carbohydrate.     

Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data

Much of a cell's activity is organized as a network of interacting modules: sets of genes coregulated to respond to different conditions. We present a probabilistic method for identifying regulatory modules from gene expression data. Our procedure identifies modules of coregulated genes, their regulators and the conditions under which regulation occurs, generating testable hypotheses in the form 'regulator X regulates module Y under conditions W'. We applied the method to a Saccharomyces cerevisiae expression data set, showing its ability to identify functionally coherent modules and their correct regulators. We present microarray experiments supporting three novel predictions, suggesting regulatory roles for previously uncharacterized proteins.     

Robustness against mutations in genetic networks of yeast

There are two principal mechanisms that are responsible for the ability of an organism's physiological and developmental processes to compensate for mutations. In the first, genes have overlapping functions, and loss-of-function mutations in one gene will have little phenotypic effect if there are one or more additional genes with similar functions. The second mechanism has its origin in interactions between genes with unrelated functions, and has been documented in metabolic and regulatory gene networks. Here I analyse, on a genome-wide scale, which of these mechanisms of robustness against mutations is more prevalent. I used functional genomics data from the yeast Saccharomyces cerevisiae to test hypotheses related to the following: if gene duplications are mostly responsible for robustness, then a correlation is expected between the similarity of two duplicated genes and the effect of mutations in one of these genes. My results demonstrate that interactions among unrelated genes are the major cause of robustness against mutations. This type of robustness is probably an evolved response of genetic networks to stabilizing selection.     

Genotype-based screen for ENU-induced mutations in mouse embryonic stem cells

The ability to generate mutations is a prerequisite to functional genetic analysis. Despite a long history of using mice as a model system for genetic analysis, the scientific community has not generated a comprehensive collection of multiple alleles for most mouse genes. The chemical mutagen of choice for mouse has been N-ethyl-N-nitrosourea (ENU), an alkylating agent that mainly causes base substitutions in DNA, and therefore allows for recovery of complete and partial loss-, as well as gain-, of-function alleles . Specific locus tests designed to detect recessive mutations showed that ENU is the most efficient mutagen in mouse with an approximate mutation rate of 1 in 1,000 gametes. In fact, several genome-wide and region-specific screens based on phenotypes have been carried out. The anticipation of the completion of the human and mouse genome projects, however, now emphasizes genotype-driven genetics--from sequence to mutants. To take advantage of the mutagenicity of ENU and its ability to create allelic series of mutations, we have developed a complementary approach to generating mutations using mouse embryonic stem (ES) cells. We show that a high mutation frequency can be achieved and that modulating DNA-repair activities can enhance this frequency. The treated cells retain germline competency, thereby rendering this approach applicable for efficient generation of an allelic series of mutations pivotal to a fine-tuned dissection of biological pathways.     

A genetic approach to understanding auditory function

Little is known of the molecular basis of normal auditory function. In contrast to the visual or olfactory senses, in which reasonable amounts of sensory tissue can be gathered, the auditory system has proven difficult to access through biochemical routes, mainly because such small amounts of tissue are available for analysis. Key molecules, such as the transduction channel, may be present in only a few tens of copies per sensory hair cell, compounding the difficulty. Moreover, fundamental differences in the mechanism of stimulation and, most importantly, the speed of response of audition compared with other senses means that we have no well-understood models to provide good candidate molecules for investigation. For these reasons, a genetic approach is useful for identifying the key components of auditory transduction, as it makes no assumptions about the nature or expression level of molecules essential for hearing. We review here some of the major advances in our understanding of auditory function resulting from the recent rapid progress in identification of genes involved in deafness.     

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.     

Integrated analysis of somatic mutations and focal copy-number changes identifies key genes and pathways in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy. Here, we performed high-resolution copy-number analysis on 125 HCC tumors and whole-exome sequencing on 24 of these tumors. We identified 135 homozygous deletions and 994 somatic mutations of genes with predicted functional consequences. We found new recurrent alterations in four genes (ARID1A, RPS6KA3, NFE2L2 and IRF2) not previously described in HCC. Functional analyses showed tumor suppressor properties for IRF2, whose inactivation, exclusively found in hepatitis B virus (HBV)-related tumors, led to impaired TP53 function. In contrast, inactivation of chromatin remodelers was frequent and predominant in alcohol-related tumors. Moreover, association of mutations in specific genes (RPS6KA3-AXIN1 and NFE2L2-CTNNB1) suggested that Wnt/β-catenin signaling might cooperate in liver carcinogenesis with both oxidative stress metabolism and Ras/mitogen-activated protein kinase (MAPK) pathways. This study provides insight into the somatic mutational landscape in HCC and identifies interactions between mutations in oncogene and tumor suppressor gene mutations related to specific risk factors.