Detection of regulatory variation in mouse genes

Functional polymorphism in genes can be classified as coding variation, altering the amino-acid sequence of the encoded protein, or regulatory variation, affecting the level or pattern of expression of the gene. Coding variation can be recognized directly from DNA sequence, and consequently its frequency and characteristics have been extensively described. By contrast, virtually nothing is known about the extent to which gene regulation varies in populations. Yet it is likely that regulatory variants are important in modulating gene function: alterations in gene regulation have been proposed to influence disease susceptibility and to have been the primary substrate for the evolution of species. Here, we report a systematic study to assess the extent of cis-acting regulatory variation in 69 genes across four inbred mouse strains. We find that at least four of these genes show allelic differences in expression level of 1.5-fold or greater, and that some of these differences are tissue specific. The results show that the impact of regulatory variants can be detected at a significant frequency in a genomic survey and suggest that such variation may have important consequences for organismal phenotype and evolution. The results indicate that larger-scale surveys in both mouse and human could identify a substantial number of genes with common regulatory variation.     

PDGF signaling specificity is mediated through multiple immediate early genes

Growth factor signaling leads to the induction or repression of immediate early genes, but how these genes act collectively as effectors of downstream processes remains unresolved. We have used gene trap-coupled microarray analysis to identify and mutate multiple platelet-derived growth factor (PDGF) intermediate early genes in mice. Mutations in these genes lead to a high frequency of phenotypes that affect the same cell types and processes as those controlled by the PDGF pathway. We conclude that these genes form a network that controls specific processes downstream of PDGF signaling.     

PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes

DNA microarrays can be used to identify gene expression changes characteristic of human disease. This is challenging, however, when relevant differences are subtle at the level of individual genes. We introduce an analytical strategy, Gene Set Enrichment Analysis, designed to detect modest but coordinate changes in the expression of groups of functionally related genes. Using this approach, we identify a set of genes involved in oxidative phosphorylation whose expression is coordinately decreased in human diabetic muscle. Expression of these genes is high at sites of insulin-mediated glucose disposal, activated by PGC-1alpha and correlated with total-body aerobic capacity. Our results associate this gene set with clinically important variation in human metabolism and illustrate the value of pathway relationships in the analysis of genomic profiling experiments.     

Identification of acquired somatic mutations in the gene encoding chromatin-remodeling factor ATRX in the alpha-thalassemia myelodysplasia syndrome (ATMDS)

Inherited mutations of specific genes have elucidated the normal roles of the proteins they encode by relating specific mutations to particular phenotypes. But many potentially informative mutations in such genes are lethal early in development. Consequently, inherited mutations may not reflect all the functional roles of such proteins. Acquired, somatic defects should reflect a wider spectrum of mutations because they are not prone to negative selection in development. It has been difficult to identify such mutations so far, but microarray analysis provides a new opportunity to do so. Using this approach, we have shown that in individuals with myelodysplasia associated with alpha-thalassemia (ATMDS), somatic mutations of the gene encoding the chromatin remodeling factor ATRX cause an unexpectedly severe hematological phenotype compared with the wide spectrum of inherited mutations affecting this gene. These findings cast new light on this pleiotropic cofactor, which appears to be an essential component rather than a mere facilitator of globin gene expression.     

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.     

Predicting phenotypic variation in yeast from individual genome sequences

A central challenge in genetics is to predict phenotypic variation from individual genome sequences. Here we construct and evaluate phenotypic predictions for 19 strains of Saccharomyces cerevisiae. We use conservation-based methods to predict the impact of protein-coding variation within genes on protein function. We then rank strains using a prediction score that measures the total sum of function-altering changes in different sets of genes reported to influence over 100 phenotypes in genome-wide loss-of-function screens. We evaluate our predictions by comparing them with the observed growth rate and efficiency of 15 strains tested across 20 conditions in quantitative experiments. The median predictive performance, as measured by ROC AUC, was 0.76, and predictions were more accurate when the genes reported to influence a trait were highly connected in a functional gene network.     

Adaptive evolution of a duplicated pancreatic ribonuclease gene in a leaf-eating monkey

Although the complete genome sequences of over 50 representative species have revealed the many duplicated genes in all three domains of life, the roles of gene duplication in organismal adaptation and biodiversity are poorly understood. In addition, the evolutionary forces behind the functional divergence of duplicated genes are often unknown, leading to disagreement on the relative importance of positive Darwinian selection versus relaxation of functional constraints in this process. The methodology of earlier studies relied largely on DNA sequence analysis but lacked functional assays of duplicated genes, frequently generating contentious results. Here we use both computational and experimental approaches to address these questions in a study of the pancreatic ribonuclease gene (RNASE1) and its duplicate gene (RNASE1B) in a leaf-eating colobine monkey, douc langur. We show that RNASE1B has evolved rapidly under positive selection for enhanced ribonucleolytic activity in an altered microenvironment, a response to increased demands for the enzyme for digesting bacterial RNA. At the same time, the ability to degrade double-stranded RNA, a non-digestive activity characteristic of primate RNASE1, has been lost in RNASE1B, indicating functional specialization and relaxation of purifying selection. Our findings demonstrate the contribution of gene duplication to organismal adaptation and show the power of combining sequence analysis and functional assays in delineating the molecular basis of adaptive evolution.     

In vivo selection using a cell-growth switch

A major obstacle to stem-cell gene therapy rests in the inability to deliver a gene into a therapeutically relevant fraction of stem cells. One way to circumvent this obstacle is to use selection. Vectors containing two linked genes serve as the basis for selection, with one gene encoding a selectable product and the other, a therapeutic protein. Applying selection in vivo has the potential to bring a minor population of genetically corrected cells into the therapeutic range. But strategies for achieving in vivo selection have traditionally relied on genes that confer resistance to cytotoxic drugs and are encumbered by toxicity. Here we describe a new system for in vivo selection that uses a 'cell-growth switch', allowing a minor population of genetically corrected cells into the therapeutic range. But strategies for achieving in vivo selection have traditionally relied on genes that confer resistance to cytotoxic drugs and are encumbered by toxicity. Here we describe a new system for in vivo selection that uses a 'cell-growth switch', allowing a minor population of genetically modified cells to be inducibly amplified, thereby averting the risks associated with cytotoxic drugs. This system provides a general platform for conditionally expanding genetically modified cell populations in vivo, and may have widespread applications in gene and cell therapy.     

Construction of a mouse yeast artificial chromosome library in a recombination-deficient strain of yeast.

We have constructed a new generation yeast artificial chromosome (YAC) library from female C57BL/10 mice in a recombination-deficient strain of Saccharomyces cerevisiae carrying a mutation in the RAD52 gene. The YAC library contains 41,568 clones with an average insert size of 240 kilobases, representing a greater than threefold coverage of the mouse genome. Currently, the library can be screened by polymerase chain reaction and we have isolated positive clones at a number of loci in the mouse genome. This rad52 library should enable a long-term assessment of the effect of one of the yeast recombination pathway genes on both, genome-wide YAC clone stability and the frequency of chimaeric clones.     

Integrated genomic and epigenomic analyses pinpoint biallelic gene inactivation in tumors

Aberrant methylation of CpG islands and genomic deletion are two predominant mechanisms of gene inactivation in tumorigenesis, but the extent to which they interact is largely unknown. The lack of an integrated approach to study these mechanisms has limited the understanding of tumor genomes and cancer genes. Restriction landmark genomic scanning (RLGS; ref. 1) is useful for global analysis of aberrant methylation of CpG islands, but has not been amenable to alignment with deletion maps because the identity of most RLGS fragments is unknown. Here, we determined the nucleotide sequence and exact chromosomal position of RLGS fragments throughout the genome using the whole chromosome of origin of the fragments and in silico restriction digestion of the human genome sequence. To study the interaction of these gene-inactivation mechanisms in primary brain tumors, we integrated RLGS-based methylation analysis with high-resolution deletion maps from microarray-based comparative genomic hybridization (array CGH; ref. 3). Certain subsets of gene-associated CpG islands were preferentially affected by convergent methylation and deletion, including genes that exhibit tumor-suppressor activity, such as CISH1 (encoding SOCS1; ref. 4), as well as genes such as COE3 that have been missed by traditional non-integrated approaches. Our results show that most aberrant methylation events are focal and independent of deletions, and the rare convergence of these mechanisms can pinpoint biallelic gene inactivation without the use of positional cloning.     

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.     

Population genomics of human gene expression

Genetic variation influences gene expression, and this variation in gene expression can be efficiently mapped to specific genomic regions and variants. Here we have used gene expression profiling of Epstein-Barr virus-transformed lymphoblastoid cell lines of all 270 individuals genotyped in the HapMap Consortium to elucidate the detailed features of genetic variation underlying gene expression variation. We find that gene expression is heritable and that differentiation between populations is in agreement with earlier small-scale studies. A detailed association analysis of over 2.2 million common SNPs per population (5% frequency in HapMap) with gene expression identified at least 1,348 genes with association signals in cis and at least 180 in trans. Replication in at least one independent population was achieved for 37% of cis signals and 15% of trans signals, respectively. Our results strongly support an abundance of cis-regulatory variation in the human genome. Detection of trans effects is limited but suggests that regulatory variation may be the key primary effect contributing to phenotypic variation in humans. We also explore several methodologies that improve the current state of analysis of gene expression variation.