Evolutionary plasticity of genetic interaction networks

Non-additive genetic interactions contribute to many genetic disorders, but they are extremely difficult to predict. Here we show that genetic interactions identified in yeast, unlike gene functions or protein interactions, are not highly conserved in animals. Genetic interactions are therefore unlikely to represent simple redundancy between genes or pathways, and genetic interactions from yeast do not directly predict genetic interactions in higher eukaryotes, including humans.     

Genome-wide strategies for detecting multiple loci that influence complex diseases

After nearly 10 years of intense academic and commercial research effort, large genome-wide association studies for common complex diseases are now imminent. Although these conditions involve a complex relationship between genotype and phenotype, including interactions between unlinked loci, the prevailing strategies for analysis of such studies focus on the locus-by-locus paradigm. Here we consider analytical methods that explicitly look for statistical interactions between loci. We show first that they are computationally feasible, even for studies of hundreds of thousands of loci, and second that even with a conservative correction for multiple testing, they can be more powerful than traditional analyses under a range of models for interlocus interactions. We also show that plausible variations across populations in allele frequencies among interacting loci can markedly affect the power to detect their marginal effects, which may account in part for the well-known difficulties in replicating association results. These results suggest that searching for interactions among genetic loci can be fruitfully incorporated into analysis strategies for genome-wide association studies.     

DNA helicase gene interaction network defined using synthetic lethality analyzed by microarray

We describe a new synthetic lethality analysis by microarray (SLAM) technique that uses approximately 4,600 Saccharomyces cerevisiae haploid deletion mutants with molecular 'bar codes' (TAGs). We used SGS1 and SRS2, two 3'-->5' DNA helicase genes, as 'queries' to identify their redundant and unique biological functions. We introduced these 'query mutations' into a haploid deletion pool by integrative transformation to disrupt the query gene in every cell, generating a double mutant pool. Optimization of integrative transformation efficiency was essential to the success of SLAM. Synthetic interactions defined a DNA helicase genetic network and predicted a role for SRS2 in processing damaged replication forks but, unlike SGS1, not in rDNA replication, DNA topology or lagging strand synthesis. SGS1 and SRS2 have synthetic defects with MRC1 but not RAD9, suggesting that SGS1 and SRS2 function in a parallel pathway with MRC1 to transduce the DNA replication stress signal to the general DNA damage checkpoint pathway. Both helicase genes have rad51-reversible synthetic defects with 5'-->3' DNA helicase RRM3, suggesting that RRM3 helps prevent formation of toxic recombination intermediates. SLAM detects synthetic lethality efficiently and ranks candidate genetic interactions, making it an especially useful method.     

Progress and prospects in rat genetics: a community view

The rat is an important system for modeling human disease. Four years ago, the rich 150-year history of rat research was transformed by the sequencing of the rat genome, ushering in an era of exceptional opportunity for identifying genes and pathways underlying disease phenotypes. Genome-wide association studies in human populations have recently provided a direct approach for finding robust genetic associations in common diseases, but identifying the precise genes and their mechanisms of action remains problematic. In the context of significant progress in rat genomic resources over the past decade, we outline achievements in rat gene discovery to date, show how these findings have been translated to human disease, and document an increasing pace of discovery of new disease genes, pathways and mechanisms. Finally, we present a set of principles that justify continuing and strengthening genetic studies in the rat model, and further development of genomic infrastructure for rat research.     

Natural variation for sulfate content in Arabidopsis thaliana is highly controlled by APR2

Most agronomic traits of importance, whether physiological (such as nutrient use efficiency) or developmental (such as flowering time), are controlled simultaneously by multiple genes and their interactions with the environment. Here, we show that variation in sulfate content between wild Arabidopsis thaliana accessions Bay-0 and Shahdara is controlled by a major quantitative trait locus that results in a strong interaction with nitrogen availability in the soil. Combining genetic and biochemical results and using a candidate gene approach, we have cloned the underlying gene, showing how a single-amino acid substitution in a key enzyme of the assimilatory sulfate reduction pathway, adenosine 5'-phosphosulfate reductase, is responsible for a decrease in enzyme activity, leading to sulfate accumulation in the plant. This work illustrates the potential of natural variation as a source of new alleles of known genes, which can aid in the study of gene function and metabolic pathway regulation. Our new insights on sulfate assimilation may have an impact on sulfur fertilizer use and stress defense improvement.     

Dysregulation of the TSC-mTOR pathway in human disease

The mammalian target of rapamycin (mTOR) has a central role in the regulation of cell growth. mTOR receives input from multiple signaling pathways, including growth factors and nutrients, to stimulate protein synthesis by phosphorylating key translation regulators such as ribosomal S6 kinase and eukaryote initiation factor 4E binding protein 1. High levels of dysregulated mTOR activity are associated with several hamartoma syndromes, including tuberous sclerosis complex, the PTEN-related hamartoma syndromes and Peutz-Jeghers syndrome. These disorders are all caused by mutations in tumor-suppressor genes that negatively regulate mTOR. Here we discuss the emerging evidence for a functional relationship between the mTOR signaling pathway and several genetic diseases, and we present evidence supporting a model in which dysregulation of mTOR may be a common molecular basis, not only for hamartoma syndromes, but also for other cellular hypertrophic disorders.     

Disruption of Bardet-Biedl syndrome ciliary proteins perturbs planar cell polarity in vertebrates

The evolutionarily conserved planar cell polarity (PCP) pathway (or noncanonical Wnt pathway) drives several important cellular processes, including epithelial cell polarization, cell migration and mitotic spindle orientation. In vertebrates, PCP genes have a vital role in polarized convergent extension movements during gastrulation and neurulation. Here we show that mice with mutations in genes involved in Bardet-Biedl syndrome (BBS), a disorder associated with ciliary dysfunction, share phenotypes with PCP mutants including open eyelids, neural tube defects and disrupted cochlear stereociliary bundles. Furthermore, we identify genetic interactions between BBS genes and a PCP gene in both mouse (Ltap, also called Vangl2) and zebrafish (vangl2). In zebrafish, the augmented phenotype results from enhanced defective convergent extension movements. We also show that Vangl2 localizes to the basal body and axoneme of ciliated cells, a pattern reminiscent of that of the BBS proteins. These data suggest that cilia are intrinsically involved in PCP processes.     

Global diversity and evidence for coevolution of KIR and HLA

The killer immunoglobulin-like receptor (KIR) gene cluster shows extensive genetic diversity, as do the HLA class I loci, which encode ligands for KIR molecules. We genotyped 1,642 individuals from 30 geographically distinct populations to examine population-level evidence for coevolution of these two functionally related but unlinked gene clusters. We observed strong negative correlations between the presence of activating KIR genes and their corresponding HLA ligand groups across populations, especially KIR3DS1 and its putative HLA-B Bw4-80I ligands (r = -0.66, P = 0.038). In contrast, we observed weak positive relationships between the various inhibitory KIR genes and their ligands. We observed a negative correlation between distance from East Africa and frequency of activating KIR genes and their corresponding ligands, suggesting a balance between selection on HLA and KIR loci. Most KIR-HLA genetic association studies indicate a primary influence of activating KIR-HLA genotypes in disease risk; concomitantly, activating receptor-ligand pairs in this study show the strongest signature of coevolution of these two complex genetic systems as compared with inhibitory receptor-ligand pairs.     

Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes

Bacterial pathogens evolve during the infection of their human host(1-8), but separating adaptive and neutral mutations remains challenging(9-11). Here we identify bacterial genes under adaptive evolution by tracking recurrent patterns of mutations in the same pathogenic strain during the infection of multiple individuals. We conducted a retrospective study of a Burkholderia dolosa outbreak among subjects with cystic fibrosis, sequencing the genomes of 112 isolates collected from 14 individuals over 16 years. We find that 17 bacterial genes acquired nonsynonymous mutations in multiple individuals, which indicates parallel adaptive evolution. Mutations in these genes affect important pathogenic phenotypes, including antibiotic resistance and bacterial membrane composition and implicate oxygen-dependent regulation as paramount in lung infections. Several genes have not previously been implicated in pathogenesis and may represent new therapeutic targets. The identification of parallel molecular evolution as a pathogen spreads among multiple individuals points to the key selection forces it experiences within human hosts.     

Ru2 and Ru encode mouse orthologs of the genes mutated in human Hermansky-Pudlak syndrome types 5 and 6

Hermansky-Pudlak syndrome (HPS) is a genetically heterogeneous disease involving abnormalities of melanosomes, platelet dense granules and lysosomes. Here we have used positional candidate and transgenic rescue approaches to identify the genes mutated in ruby-eye 2 and ruby-eye mice (ru2 and ru, respectively), two 'mimic' mouse models of HPS. We also show that these genes are orthologs of the genes mutated in individuals with HPS types 5 and 6, respectively, and that their protein products directly interact. Both genes are previously unknown and are found only in higher eukaryotes, and together represent a new class of genes that have evolved in higher organisms to govern the synthesis of highly specialized lysosome-related organelles.     

Genome-wide association analysis identifies 20 loci that influence adult height

Adult height is a model polygenic trait, but there has been limited success in identifying the genes underlying its normal variation. To identify genetic variants influencing adult human height, we used genome-wide association data from 13,665 individuals and genotyped 39 variants in an additional 16,482 samples. We identified 20 variants associated with adult height (P < 5 x 10(-7), with 10 reaching P < 1 x 10(-10)). Combined, the 20 SNPs explain approximately 3% of height variation, with a approximately 5 cm difference between the 6.2% of people with 17 or fewer 'tall' alleles compared to the 5.5% with 27 or more 'tall' alleles. The loci we identified implicate genes in Hedgehog signaling (IHH, HHIP, PTCH1), extracellular matrix (EFEMP1, ADAMTSL3, ACAN) and cancer (CDK6, HMGA2, DLEU7) pathways, and provide new insights into human growth and developmental processes. Finally, our results provide insights into the genetic architecture of a classic quantitative trait.     

Leukaemia disease genes: large-scale cloning and pathway predictions

Retroviral insertional mutagenesis in BXH2 and AKXD recombinant inbred mice induces a high incidence of myeloid or B- and T-cell leukaemia and the proviral integration sites in the leukaemias provide powerful genetic tags for disease gene identification. Some of the disease genes identified by proviral tagging are also associated with human disease, validating this approach for human disease gene identification. Although many leukaemia disease genes have been identified over the years, many more remain to be cloned. Here we describe an inverse PCR (IPCR) method for proviral tagging that makes use of automated DNA sequencing and the genetic tools provided by the Mouse Genome Project, which increases the throughput for disease gene identification. We also use this IPCR method to clone and analyse more than 400 proviral integration sites from AKXD and BXH2 leukaemias and, in the process, identify more than 90 candidate disease genes. Some of these genes function in pathways already implicated in leukaemia, whereas others are likely to define new disease pathways. Our studies underscore the power of the mouse as a tool for gene discovery and functional genomics.     

Functional classification of drugs by properties of their pairwise interactions

Multidrug treatments are increasingly important in medicine and for probing biological systems. Although many studies have focused on interactions between specific drugs, little is known about the system properties of a full drug interaction network. Like their genetic counterparts, two drugs may have no interaction, or they may interact synergistically or antagonistically to increase or suppress their individual effects. Here we use a sensitive bioluminescence technique to provide quantitative measurements of pairwise interactions among 21 antibiotics that affect growth rate in Escherichia coli. We find that the drug interaction network possesses a special property: it can be separated into classes of drugs such that any two classes interact either purely synergistically or purely antagonistically. These classes correspond directly to the cellular functions affected by the drugs. This network approach provides a new conceptual framework for understanding the functional mechanisms of drugs and their cellular targets and can be applied in systems intractable to mutant screening, biochemistry or microscopy.     

A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance

Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and β-cell dysfunction but have contributed little to the understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways might be uncovered by accounting for differences in body mass index (BMI) and potential interactions between BMI and genetic variants. We applied a joint meta-analysis approach to test associations with fasting insulin and glucose on a genome-wide scale. We present six previously unknown loci associated with fasting insulin at P < 5 × 10(-8) in combined discovery and follow-up analyses of 52 studies comprising up to 96,496 non-diabetic individuals. Risk variants were associated with higher triglyceride and lower high-density lipoprotein (HDL) cholesterol levels, suggesting a role for these loci in insulin resistance pathways. The discovery of these loci will aid further characterization of the role of insulin resistance in T2D pathophysiology.     

A single EFEMP1 mutation associated with both Malattia Leventinese and Doyne honeycomb retinal dystrophy.

Malattia Leventinese (ML) and Doyne honeycomb retinal dystrophy (DHRD) refer to two autosomal dominant diseases characterized by yellow-white deposits known as drusen that accumulate beneath the retinal pigment epithelium (RPE). Both loci were mapped to chromosome 2p16-21 (refs 5,6) and this genetic interval has been subsequently narrowed. The importance of these diseases is due in large part to their close phenotypic similarity to age-related macular degeneration (AMD), a disorder with a strong genetic component that accounts for approximately 50% of registered blindness in the Western world. Just as in ML and DHRD, the early hallmark of AMD is the presence of drusen. Here we use a combination of positional and candidate gene methods to identify a single non-conservative mutation (Arg345Trp) in the gene EFEMP1 (for EGF-containing fibrillin-like extracellular matrix protein 1) in all families studied. This change was not present in 477 control individuals or in 494 patients with age-related macular degeneration. Identification of this mutation may aid in the development of an animal model for drusen, as well as in the identification of other genes involved in human macular degeneration.     

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.     

Recurrent DNA copy number variation in the laboratory mouse

Different species, populations and individuals vary considerably in the copy number of discrete segments of their genomes. The manner and frequency with which these genetic differences arise over generational time is not well understood. Taking advantage of divergence among lineages sharing a recent common ancestry, we have conducted a genome-wide analysis of spontaneous copy number variation (CNV) in the laboratory mouse. We used high-resolution microarrays to identify 38 CNVs among 14 colonies of the C57BL/6 strain spanning approximately 967 generations of inbreeding, and we examined these loci in 12 additional strains. It is clear from our results that many CNVs arise through a highly nonrandom process: 18 of 38 were the product of recurrent mutation, and rates of change varied roughly four orders of magnitude across different loci. Recurrent CNVs are found throughout the genome, affect 43 genes and fluctuate in copy number over mere hundreds of generations, observations that raise questions about their contribution to natural variation.