Gene expression-based high-throughput screening(GE-HTS) and application to leukemia differentiation

Chemical genomics involves generating large collections of small molecules and using them to modulate cellular states. Despite recent progress in the systematic synthesis of structurally diverse compounds, their use in screens of cellular circuitry is still an ad hoc process. Here, we outline a general, efficient approach called gene expression-based high-throughput screening (GE-HTS) in which a gene expression signature is used as a surrogate for cellular states, and we describe its application in a particular setting: the identification of compounds that induce the differentiation of acute myeloid leukemia cells. In screening 1,739 compounds, we identified 8 that reliably induced the differentiation signature and, furthermore, yielded functional evidence of bona fide differentiation. The results indicate that GE-HTS may be a powerful, general approach for chemical screening.     

Functional screening of an asthma QTL in YAC transgenic mice.

Many quantitative trait loci (QTLs) contributing to genetically complex conditions have been discovered, but few causative genes have been identified. This is mainly due to the large size of QTLs and the subtle connection between genotype and quantitative phenotype associated with these conditions. Transgenic mice have been successfully used to analyse well-characterized genes suspected of contributing to quantitative traits. Although this approach is powerful for examining one gene at a time, it can be impractical for surveying the large genomic intervals containing many genes that are typically associated with QTLs. To screen for genes contributing to an asthma QTL mapped to human chromosome 5q3 (refs 6,7), we characterized a panel of large-insert 5q31 transgenics based on studies demonstrating that altering gene dosage frequently affects quantitative phenotypes normally influenced by that gene. This panel of human YAC transgenics, propagating a 1-Mb interval of chromosome 5q31 containing 6 cytokine genes and 17 partially characterized genes, was screened for quantitative changes in several asthma-associated phenotypes. Multiple independent transgenic lines with altered IgE response to antigen treatment shared a 180-kb region containing 5 genes, including those encoding human interleukin 4 (IL4) and interleukin 13 (IL13 ), which induce IgE class switching in B cells. Further analysis of these mice and mice transgenic for mouse Il4 and Il13 demonstrated that moderate changes in Il4 and Il13 expression affect asthma-associated phenotypes in vivo. This functional screen of large-insert transgenics enabled us to identify genes that influence the QTL phenotype in vivo.     

MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia.

Acute lymphoblastic leukemias carrying a chromosomal translocation involving the mixed-lineage leukemia gene (MLL, ALL1, HRX) have a particularly poor prognosis. Here we show that they have a characteristic, highly distinct gene expression profile that is consistent with an early hematopoietic progenitor expressing select multilineage markers and individual HOX genes. Clustering algorithms reveal that lymphoblastic leukemias with MLL translocations can clearly be separated from conventional acute lymphoblastic and acute myelogenous leukemias. We propose that they constitute a distinct disease, denoted here as MLL, and show that the differences in gene expression are robust enough to classify leukemias correctly as MLL, acute lymphoblastic leukemia or acute myelogenous leukemia. Establishing that MLL is a unique entity is critical, as it mandates the examination of selectively expressed genes for urgently needed molecular targets.     

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.     

A single gene network accurately predicts phenotypic effects of gene perturbation in Caenorhabditis elegans

The fundamental aim of genetics is to understand how an organism's phenotype is determined by its genotype, and implicit in this is predicting how changes in DNA sequence alter phenotypes. A single network covering all the genes of an organism might guide such predictions down to the level of individual cells and tissues. To validate this approach, we computationally generated a network covering most C. elegans genes and tested its predictive capacity. Connectivity within this network predicts essentiality, identifying this relationship as an evolutionarily conserved biological principle. Critically, the network makes tissue-specific predictions-we accurately identify genes for most systematically assayed loss-of-function phenotypes, which span diverse cellular and developmental processes. Using the network, we identify 16 genes whose inactivation suppresses defects in the retinoblastoma tumor suppressor pathway, and we successfully predict that the dystrophin complex modulates EGF signaling. We conclude that an analogous network for human genes might be similarly predictive and thus facilitate identification of disease genes and rational therapeutic targets.     

Loss of genomic methylation causes p53-dependent apoptosis and epigenetic deregulation

Cytosine methylation of mammalian DNA is essential for the proper epigenetic regulation of gene expression and maintenance of genomic integrity. To define the mechanism through which demethylated cells die, and to establish a paradigm for identifying genes regulated by DNA methylation, we have generated mice with a conditional allele for the maintenance DNA methyltransferase gene Dnmt1. Cre-mediated deletion of Dnmt1 causes demethylation of cultured fibroblasts and a uniform p53-dependent cell death. Mutational inactivation of Trp53 partially rescues the demethylated fibroblasts for up to five population doublings in culture. Oligonucleotide microarray analysis showed that up to 10% of genes are aberrantly expressed in demethylated fibroblasts. Our results demonstrate that loss of Dnmt1 causes cell-type-specific changes in gene expression that impinge on several pathways, including expression of imprinted genes, cell-cycle control, growth factor/receptor signal transduction and mobilization of retroelements.     

Exome sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in chronic lymphocytic leukemia

Here we perform whole-exome sequencing of samples from 105 individuals with chronic lymphocytic leukemia (CLL), the most frequent leukemia in adults in Western countries. We found 1,246 somatic mutations potentially affecting gene function and identified 78 genes with predicted functional alterations in more than one tumor sample. Among these genes, SF3B1, encoding a subunit of the spliceosomal U2 small nuclear ribonucleoprotein (snRNP), is somatically mutated in 9.7% of affected individuals. Further analysis in 279 individuals with CLL showed that SF3B1 mutations were associated with faster disease progression and poor overall survival. This work provides the first comprehensive catalog of somatic mutations in CLL with relevant clinical correlates and defines a large set of new genes that may drive the development of this common form of leukemia. The results reinforce the idea that targeting several well-known genetic pathways, including mRNA splicing, could be useful in the treatment of CLL and other malignancies.     

Natural variation in cardiac metabolism and gene expression in Fundulus heteroclitus

Individual variation in gene expression is important for evolutionary adaptation and susceptibility to diseases and pathologies. In this study, we address the functional importance of this variation by comparing cardiac metabolism to patterns of mRNA expression using microarrays. There is extensive variation in both cardiac metabolism and the expression of metabolic genes among individuals of the teleost fish Fundulus heteroclitus from natural outbred populations raised in a common environment: metabolism differed among individuals by a factor of more than 2, and expression levels of 94% of genes were significantly different (P < 0.01) between individuals in a population. This unexpectedly high variation in metabolic gene expression explains much of the variation in metabolism, suggesting that it is biologically relevant. The patterns of gene expression that are most important in explaining cardiac metabolism differ between groups of individuals. Apparently, the variation in metabolism seems to be related to different patterns of gene expression in the different groups of individuals. The magnitude of differences in gene expression in these groups is not important; large changes in expression have no greater predictive value than small changes. These data suggest that variation in physiological performance is related to the subtle variation in gene expression and that this relationship differs among individuals.     

X-linked inheritance of Fanconi anemia complementation group B

Fanconi anemia is an autosomal recessive syndrome characterized by diverse clinical symptoms, hypersensitivity to DNA crosslinking agents, chromosomal instability and susceptibility to cancer. Fanconi anemia has at least 11 complementation groups (A, B, C, D1, D2, E, F, G, I, J, L); the genes mutated in 8 of these have been identified. The gene BRCA2 was suggested to underlie complementation group B, but the evidence is inconclusive. Here we show that the protein defective in individuals with Fanconi anemia belonging to complementation group B is an essential component of the nuclear protein 'core complex' responsible for monoubiquitination of FANCD2, a key event in the DNA-damage response pathway associated with Fanconi anemia and BRCA. Unexpectedly, the gene encoding this protein, FANCB, is localized at Xp22.31 and subject to X-chromosome inactivation. X-linked inheritance has important consequences for genetic counseling of families with Fanconi anemia belonging to complementation group B. Its presence as a single active copy and essentiality for a functional Fanconi anemia-BRCA pathway make FANCB a potentially vulnerable component of the cellular machinery that maintains genomic integrity.     

Clustering of housekeeping genes provides a unified model of gene order in the human genome

It is often supposed that, except for tandem duplicates, genes are randomly distributed throughout the human genome. However, recent analyses suggest that when all the genes expressed in a given tissue (notably placenta and skeletal muscle) are examined, these genes do not map to random locations but instead resolve to clusters. We have asked three questions: (i) is this clustering true for most tissues, or are these the exceptions; (ii) is any clustering simply the result of the expression of tandem duplicates and (iii) how, if at all, does this relate to the observed clustering of genes with high expression rates? We provide a unified model of gene clustering that explains the previous observations. We examined Serial Analysis of Gene Expression (SAGE) data for 14 tissues and found significant clustering, in each tissue, that persists even after the removal of tandem duplicates. We confirmed clustering by analysis of independent expressed-sequence tag (EST) data. We then tested the possibility that the human genome is organized into subregions, each specializing in genes needed in a given tissue. By comparing genes expressed in different tissues, we show that this is not the case: those genes that seem to be tissue-specific in their expression do not, as a rule, cluster. We report that genes that are expressed in most tissues (housekeeping genes) show strong clustering. In addition, we show that the apparent clustering of genes with high expression rates is a consequence of the clustering of housekeeping genes.