Widespread aneuploidy revealed by DNA microarray expression profiling

Expression profiling using DNA microarrays holds great promise for a variety of research applications, including the systematic characterization of genes discovered by sequencing projects. To demonstrate the general usefulness of this approach, we recently obtained expression profiles for nearly 300 Saccharomyces cerevisiae deletion mutants. Approximately 8% of the mutants profiled exhibited chromosome-wide expression biases, leading to spurious correlations among profiles. Competitive hybridization of genomic DNA from the mutant strains and their isogenic parental wild-type strains showed they were aneuploid for whole chromosomes or chromosomal segments. Expression profile data published by several other laboratories also suggest the use of aneuploid strains. In five separate cases, the extra chromosome harboured a close homologue of the deleted gene; in two cases, a clear growth advantage for cells acquiring the extra chromosome was demonstrated. Our results have implications for interpreting whole-genome expression data, particularly from cells known to suffer genomic instability, such as malignant or immortalized cells.     

Exome sequencing identifies somatic mutations of DNA methyltransferase gene DNMT3A in acute monocytic leukemia

Abnormal epigenetic regulation has been implicated in oncogenesis. We report here the identification of somatic mutations by exome sequencing in acute monocytic leukemia, the M5 subtype of acute myeloid leukemia (AML-M5). We discovered mutations in DNMT3A (encoding DNA methyltransferase 3A) in 23 of 112 (20.5%) cases. The DNMT3A mutants showed reduced enzymatic activity or aberrant affinity to histone H3 in vitro. Notably, there were alterations of DNA methylation patterns and/or gene expression profiles (such as HOXB genes) in samples with DNMT3A mutations as compared with those without such changes. Leukemias with DNMT3A mutations constituted a group of poor prognosis with elderly disease onset and of promonocytic as well as monocytic predominance among AML-M5 individuals. Screening other leukemia subtypes showed Arg882 alterations in 13.6% of acute myelomonocytic leukemia (AML-M4) cases. Our work suggests a contribution of aberrant DNA methyltransferase activity to the pathogenesis of acute monocytic leukemia and provides a useful new biomarker for relevant cases.     

Systematic pathway analysis using high-resolution fitness profiling of combinatorial gene deletions

Systematic genetic interaction studies have illuminated many cellular processes. Here we quantitatively examine genetic interactions among 26 Saccharomyces cerevisiae genes conferring resistance to the DNA-damaging agent methyl methanesulfonate (MMS), as determined by chemogenomic fitness profiling of pooled deletion strains. We constructed 650 double-deletion strains, corresponding to all pairings of these 26 deletions. The fitness of single- and double-deletion strains were measured in the presence and absence of MMS. Genetic interactions were defined by combining principles from both statistical and classical genetics. The resulting network predicts that the Mph1 helicase has a role in resolving homologous recombination-derived DNA intermediates that is similar to (but distinct from) that of the Sgs1 helicase. Our results emphasize the utility of small molecules and multifactorial deletion mutants in uncovering functional relationships and pathway order.     

Genome-wide analysis of DNA copy-number changes using cDNA microarrays.

Gene amplifications and deletions frequently contribute to tumorigenesis. Characterization of these DNA copy-number changes is important for both the basic understanding of cancer and its diagnosis. Comparative genomic hybridization (CGH) was developed to survey DNA copy-number variations across a whole genome. With CGH, differentially labelled test and reference genomic DNAs are co-hybridized to normal metaphase chromosomes, and fluorescence ratios along the length of chromosomes provide a cytogenetic representation of DNA copy-number variation. CGH, however, has a limited ( approximately 20 Mb) mapping resolution, and higher-resolution techniques, such as fluorescence in situ hybridization (FISH), are prohibitively labour-intensive on a genomic scale. Array-based CGH, in which fluorescence ratios at arrayed DNA elements provide a locus-by-locus measure of DNA copy-number variation, represents another means of achieving increased mapping resolution. Published array CGH methods have relied on large genomic clone (for example BAC) array targets and have covered only a small fraction of the human genome. cDNAs representing over 30,000 radiation-hybrid (RH)-mapped human genes provide an alternative and readily available genomic resource for mapping DNA copy-number changes. Although cDNA microarrays have been used extensively to characterize variation in human gene expression, human genomic DNA is a far more complex mixture than the mRNA representation of human cells. Therefore, analysis of DNA copy-number variation using cDNA microarrays would require a sensitivity of detection an order of magnitude greater than has been routinely reported. We describe here a cDNA microarray-based CGH method, and its application to DNA copy-number variation analysis in breast cancer cell lines and tumours. Using this assay, we were able to identify gene amplifications and deletions genome-wide and with high resolution, and compare alterations in DNA copy number and gene expression.     

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.     

A framework for variation discovery and genotyping using next-generation DNA sequencing data

Recent advances in sequencing technology make it possible to comprehensively catalog genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious, and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (i) initial read mapping; (ii) local realignment around indels; (iii) base quality score recalibration; (iv) SNP discovery and genotyping to find all potential variants; and (v) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We here discuss the application of these tools, instantiated in the Genome Analysis Toolkit, to deep whole-genome, whole-exome capture and multi-sample low-pass (～4×) 1000 Genomes Project datasets.     

Estimate of human gene number provided by genome-wide analysis using Tetraodon nigroviridis DNA sequence

The number of genes in the human genome is unknown, with estimates ranging from 50,000 to 90,000 (refs 1, 2), and to more than 140,000 according to unpublished sources. We have developed 'Exofish', a procedure based on homology searches, to identify human genes quickly and reliably. This method relies on the sequence of another vertebrate, the pufferfish Tetraodon nigroviridis, to detect conserved sequences with a very low background. Similar to Fugu rubripes, a marine pufferfish proposed by Brenner et al. as a model for genomic studies, T. nigroviridis is a more practical alternative with a genome also eight times more compact than that of human. Many comparisons have been made between F. rubripes and human DNA that demonstrate the potential of comparative genomics using the pufferfish genome. Application of Exofish to the December version of the working draft sequence of the human genome and to Unigene showed that the human genome contains 28,000-34,000 genes, and that Unigene contains less than 40% of the protein-coding fraction of the human genome.     

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.     

Somatic integration and long-term transgene expression in normal and haemophilic mice using a DNA transposon system

The development of non-viral gene-transfer technologies that can support stable chromosomal integration and persistent gene expression in vivo is desirable. Here we describe the successful use of transposon technology for the nonhomologous insertion of foreign genes into the genomes of adult mammals using naked DNA. We show that the Sleeping Beauty transposase can efficiently insert transposon DNA into the mouse genome in approximately 5-6% of transfected mouse liver cells. Chromosomal transposition resulted in long-term expression (>5 months) of human blood coagulation factor IX at levels that were therapeutic in a mouse model of haemophilia B. Our results establish DNA-mediated transposition as a new genetic tool for mammals, and provide new strategies to improve existing non-viral and viral vectors for human gene therapy applications.