Showing papers on "Gene expression profiling published in 2010"

Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation

Abstract: High-throughput mRNA sequencing (RNA-Seq) promises simultaneous transcript discovery and abundance estimation. However, this would require algorithms that are not restricted by prior gene annotations and that account for alternative transcription and splicing. Here we introduce such algorithms in an open-source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed >430 million paired 75-bp RNA-Seq reads from a mouse myoblast cell line over a differentiation time series. We detected 13,692 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Over the time series, 330 genes showed complete switches in the dominant transcription start site (TSS) or splice isoform, and we observed more subtle shifts in 1,304 other genes. These results suggest that Cufflinks can illuminate the substantial regulatory flexibility and complexity in even this well-studied model of muscle development and that it can improve transcriptome-based genome annotation.

Quantifying E. coli proteome and transcriptome with single-molecule sensitivity in single cells.

Abstract: Protein and messenger RNA (mRNA) copy numbers vary from cell to cell in isogenic bacterial populations. However, these molecules often exist in low copy numbers and are difficult to detect in single cells. We carried out quantitative system-wide analyses of protein and mRNA expression in individual cells with single-molecule sensitivity using a newly constructed yellow fluorescent protein fusion library for Escherichia coli. We found that almost all protein number distributions can be described by the gamma distribution with two fitting parameters which, at low expression levels, have clear physical interpretations as the transcription rate and protein burst size. At high expression levels, the distributions are dominated by extrinsic noise. We found that a single cell's protein and mRNA copy numbers for any given gene are uncorrelated.

Understanding mechanisms underlying human gene expression variation with RNA sequencing

Abstract: Understanding the genetic mechanisms underlying natural variation in gene expression is a central goal of both medical and evolutionary genetics, and studies of expression quantitative trait loci (eQTLs) have become an important tool for achieving this goal. Although all eQTL studies so far have assayed messenger RNA levels using expression microarrays, recent advances in RNA sequencing enable the analysis of transcript variation at unprecedented resolution. We sequenced RNA from 69 lymphoblastoid cell lines derived from unrelated Nigerian individuals that have been extensively genotyped by the International HapMap Project. By pooling data from all individuals, we generated a map of the transcriptional landscape of these cells, identifying extensive use of unannotated untranslated regions and more than 100 new putative protein-coding exons. Using the genotypes from the HapMap project, we identified more than a thousand genes at which genetic variation influences overall expression levels or splicing. We demonstrate that eQTLs near genes generally act by a mechanism involving allele-specific expression, and that variation that influences the inclusion of an exon is enriched within and near the consensus splice sites. Our results illustrate the power of high-throughput sequencing for the joint analysis of variation in transcription, splicing and allele-specific expression across individuals.

Core epithelial-to-mesenchymal transition interactome gene-expression signature is associated with claudin-low and metaplastic breast cancer subtypes

Abstract: The epithelial-to-mesenchymal transition (EMT) produces cancer cells that are invasive, migratory, and exhibit stem cell characteristics, hallmarks of cells that have the potential to generate metastases. Inducers of the EMT include several transcription factors (TFs), such as Goosecoid, Snail, and Twist, as well as the secreted TGF-β1. Each of these factors is capable, on its own, of inducing an EMT in the human mammary epithelial (HMLE) cell line. However, the interactions between these regulators are poorly understood. Overexpression of each of the above EMT inducers up-regulates a subset of other EMT-inducing TFs, with Twist, Zeb1, Zeb2, TGF-β1, and FOXC2 being commonly induced. Up-regulation of Slug and FOXC2 by either Snail or Twist does not depend on TGF-β1 signaling. Gene expression signatures (GESs) derived by overexpressing EMT-inducing TFs reveal that the Twist GES and Snail GES are the most similar, although the Goosecoid GES is the least similar to the others. An EMT core signature was derived from the changes in gene expression shared by up-regulation of Gsc, Snail, Twist, and TGF-β1 and by down-regulation of E-cadherin, loss of which can also trigger an EMT in certain cell types. The EMT core signature associates closely with the claudin-low and metaplastic breast cancer subtypes and correlates negatively with pathological complete response. Additionally, the expression level of FOXC1, another EMT inducer, correlates strongly with poor survival of breast cancer patients.

Integrative analysis of the Caenorhabditis elegans genome by the modENCODE project

Abstract: We systematically generated large-scale data sets to improve genome annotation for the nematode Caenorhabditis elegans, a key model organism. These data sets include transcriptome profiling across a developmental time course, genome-wide identification of transcription factor-binding sites, and maps of chromatin organization. From this, we created more complete and accurate gene models, including alternative splice forms and candidate noncoding RNAs. We constructed hierarchical networks of transcription factor-binding and microRNA interactions and discovered chromosomal locations bound by an unusually large number of transcription factors. Different patterns of chromatin composition and histone modification were revealed between chromosome arms and centers, with similarly prominent differences between autosomes and the X chromosome. Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome.

Genome-wide mapping of alternative splicing in Arabidopsis thaliana

Abstract: Alternative splicing can enhance transcriptome plasticity and proteome diversity. In plants, alternative splicing can be manifested at different developmental stages, and is frequently associated with specific tissue types or environmental conditions such as abiotic stress. We mapped the Arabidopsis transcriptome at single-base resolution using the Illumina platform for ultrahigh-throughput RNA sequencing (RNA-seq). Deep transcriptome sequencing confirmed a majority of annotated introns and identified thousands of novel alternatively spliced mRNA isoforms. Our analysis suggests that at least approximately 42% of intron-containing genes in Arabidopsis are alternatively spliced; this is significantly higher than previous estimates based on cDNA/expressed sequence tag sequencing. Random validation confirmed that novel splice isoforms empirically predicted by RNA-seq can be detected in vivo. Novel introns detected by RNA-seq were substantially enriched in nonconsensus terminal dinucleotide splice signals. Alternative isoforms with premature termination codons (PTCs) comprised the majority of alternatively spliced transcripts. Using an example of an essential circadian clock gene, we show that intron retention can generate relatively abundant PTC(+) isoforms and that this specific event is highly conserved among diverse plant species. Alternatively spliced PTC(+) isoforms can be potentially targeted for degradation by the nonsense mediated mRNA decay (NMD) surveillance machinery or regulate the level of functional transcripts by the mechanism of regulated unproductive splicing and translation (RUST). We demonstrate that the relative ratios of the PTC(+) and reference isoforms for several key regulatory genes can be considerably shifted under abiotic stress treatments. Taken together, our results suggest that like in animals, NMD and RUST may be widespread in plants and may play important roles in regulating gene expression.

PrimerBank: a resource of human and mouse PCR primer pairs for gene expression detection and quantification

Abstract: PrimerBank (http://pga.mgh.harvard.edu/primerbank/) is a public resource for the retrieval of human and mouse primer pairs for gene expression analysis by PCR and Quantitative PCR (QPCR). A total of 306 800 primers covering most known human and mouse genes can be accessed from the PrimerBank database, together with information on these primers such as Tm, location on the transcript and amplicon size. For each gene, at least one primer pair has been designed and in many cases alternative primer pairs exist. Primers have been designed to work under the same PCR conditions, thus facilitating high-throughput QPCR. There are several ways to search for primers for the gene(s) of interest, such as by: GenBank accession number, NCBI protein accession number, NCBI gene ID, PrimerBank ID, NCBI gene symbol or gene description (keyword). In all, 26 855 primer pairs covering most known mouse genes have been experimentally validated by QPCR, agarose gel analysis, sequencing and BLAST, and all validation data can be freely accessed from the PrimerBank web site.

Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM

Abstract: Motivation: High-throughput data is providing a comprehensive view of the molecular changes in cancer tissues. New technologies allow for the simultaneous genome-wide assay of the state of genome copy number variation, gene expression, DNA methylation and epigenetics of tumor samples and cancer cell lines. Analyses of current data sets find that genetic alterations between patients can differ but often involve common pathways. It is therefore critical to identify relevant pathways involved in cancer progression and detect how they are altered in different patients. Results: We present a novel method for inferring patient-specific genetic activities incorporating curated pathway interactions among genes. A gene is modeled by a factor graph as a set of interconnected variables encoding the expression and known activity of a gene and its products, allowing the incorporation of many types of omic data as evidence. The method predicts the degree to which a pathway's activities (e.g. internal gene states, interactions or high-level ‘outputs’) are altered in the patient using probabilistic inference. Compared with a competing pathway activity inference approach called SPIA, our method identifies altered activities in cancer-related pathways with fewer false-positives in both a glioblastoma multiform (GBM) and a breast cancer dataset. PARADIGM identified consistent pathway-level activities for subsets of the GBM patients that are overlooked when genes are considered in isolation. Further, grouping GBM patients based on their significant pathway perturbations divides them into clinically-relevant subgroups having significantly different survival outcomes. These findings suggest that therapeutics might be chosen that target genes at critical points in the commonly perturbed pathway(s) of a group of patients. Availability:Source code available at http://sbenz.github.com/Paradigm Contact: jstuart@soe.ucsc.edu Supplementary information:Supplementary data are available at Bioinformatics online.

Aberrant silencing of imprinted genes on chromosome 12qF1 in mouse induced pluripotent stem cells

Abstract: Induced pluripotent stem cells (iPSCs) have been generated by enforced expression of defined sets of transcription factors in somatic cells. It remains controversial whether iPSCs are molecularly and functionally equivalent to blastocyst-derived embryonic stem (ES) cells. By comparing genetically identical mouse ES cells and iPSCs, we show here that their overall messenger RNA and microRNA expression patterns are indistinguishable with the exception of a few transcripts encoded within the imprinted Dlk1-Dio3 gene cluster on chromosome 12qF1, which were aberrantly silenced in most of the iPSC clones. Consistent with a developmental role of the Dlk1-Dio3 gene cluster, these iPSC clones contributed poorly to chimaeras and failed to support the development of entirely iPSC-derived animals ('all-iPSC mice'). In contrast, iPSC clones with normal expression of the Dlk1-Dio3 cluster contributed to high-grade chimaeras and generated viable all-iPSC mice. Notably, treatment of an iPSC clone that had silenced Dlk1-Dio3 with a histone deacetylase inhibitor reactivated the locus and rescued its ability to support full-term development of all-iPSC mice. Thus, the expression state of a single imprinted gene cluster seems to distinguish most murine iPSCs from ES cells and allows for the prospective identification of iPSC clones that have the full development potential of ES cells.

Alternative pre-mRNA splicing regulation in cancer: pathways and programs unhinged

Abstract: Alternative splicing of mRNA precursors is a nearly ubiquitous and extremely flexible point of gene control in humans. It provides cells with the opportunity to create protein isoforms of differing, even opposing, functions from a single gene. Cancer cells often take advantage of this flexibility to produce proteins that promote growth and survival. Many of the isoforms produced in this manner are developmentally regulated and are preferentially re-expressed in tumors. Emerging insights into this process indicate that pathways that are frequently deregulated in cancer often play important roles in promoting aberrant splicing, which in turn contributes to all aspects of tumor biology.

Single-cell NF-κB dynamics reveal digital activation and analogue information processing

Abstract: Cells operate in dynamic environments using extraordinary communication capabilities that emerge from the interactions of genetic circuitry. The mammalian immune response is a striking example of the coordination of different cell types 1 . Cell-to-cell communicationisprimarilymediatedbysignallingmoleculesthat form spatiotemporal concentration gradients, requiring cells to respond to a wide range of signal intensities 2 . Here we use highthroughputmicrofluidiccellculture 3 andfluorescencemicroscopy, quantitative gene expression analysis and mathematical modelling to investigate how single mammalian cells respond to different concentrations of the signalling molecule tumour-necrosis factor (TNF)-a, and relay information to the gene expression programs by means of the transcription factor nuclear factor (NF)-kB. We measured NF-kB activity in thousands of live cells under TNF-a doses covering four orders of magnitude. We find, in contrast to population-level studies with bulk assays 2 , that the activation is heterogeneous and is a digital process at the single-cell level with fewer cells responding at lower doses.Cells also encode a subtle set of analogue parameters to modulate the outcome; these parameters include NF-kB peak intensity, response time and number ofoscillations.Wedevelopedastochasticmathematicalmodelthat reproduces both the digital and analogue dynamics as well as most gene expression profiles at all measured conditions, constituting a broadly applicable model for TNF-a-induced NF-kB signalling in various types of cells. These results highlight the value of highthroughput quantitative measurements with single-cell resolution in understanding how biological systems operate. Most of the information on cell signalling has been obtained from

miR-221 overexpression contributes to liver tumorigenesis

Abstract: MicroRNA (miRNAs) are negative regulators of gene expression and can function as tumor suppressors or oncogenes. Expression patterns of miRNAs and their role in the pathogenesis of hepatocellular carcinoma (HCC) are still poorly understood. We profiled miRNA expression in tissue samples (104 HCC, 90 adjacent cirrhotic livers, 21 normal livers) as well as in 35 HCC cell lines. A set of 12 miRNAs (including miR-21, miR-221/222, miR-34a, miR-519a, miR-93, miR-96, and let-7c) was linked to disease progression from normal liver through cirrhosis to full-blown HCC. miR-221/222, the most up-regulated miRNAs in tumor samples, are shown to target the CDK inhibitor p27 and to enhance cell growth in vitro. Conversely, these activities can be efficiently inhibited by an antagomiR specific for miR-221. In addition, we show, using a mouse model of liver cancer, that miR-221 overexpression stimulates growth of tumorigenic murine hepatic progenitor cells. Finally, we identified DNA damage-inducible transcript 4 (DDIT4), a modulator of mTOR pathway, as a bona fide target of miR-221. Taken together, these data reveal an important contribution for miR-221 in hepatocarcinogenesis and suggest a role for DDIT4 dysregulation in this process. Thus, the use of synthetic inhibitors of miR-221 may prove to be a promising approach to liver cancer treatment.

Non-invasive imaging of human embryos before embryonic genome activation predicts development to the blastocyst stage

Abstract: We report studies of preimplantation human embryo development that correlate time-lapse image analysis and gene expression profiling. By examining a large set of zygotes from in vitro fertilization (IVF), we find that success in progression to the blastocyst stage can be predicted with >93% sensitivity and specificity by measuring three dynamic, noninvasive imaging parameters by day 2 after fertilization, before embryonic genome activation (EGA). These parameters can be reliably monitored by automated image analysis, confirming that successful development follows a set of carefully orchestrated and predictable events. Moreover, we show that imaging phenotypes reflect molecular programs of the embryo and of individual blastomeres. Single-cell gene expression analysis reveals that blastomeres develop cell autonomously, with some cells advancing to EGA and others arresting. These studies indicate that success and failure in human embryo development is largely determined before EGA. Our methods and algorithms may provide an approach for early diagnosis of embryo potential in assisted reproduction.

IDH1 and IDH2 Gene Mutations Identify Novel Molecular Subsets Within De Novo Cytogenetically Normal Acute Myeloid Leukemia: A Cancer and Leukemia Group B Study

Abstract: PURPOSE To analyze the frequency and associations with prognostic markers and outcome of mutations in IDH genes encoding isocitrate dehydrogenases in adult de novo cytogenetically normal acute myeloid leukemia (CN-AML). PATIENTS AND METHODS Diagnostic bone marrow or blood samples from 358 patients were analyzed for IDH1 and IDH2 mutations by DNA polymerase chain reaction amplification/sequencing. FLT3, NPM1, CEBPA, WT1, and MLL mutational analyses and gene- and microRNA-expression profiling were performed centrally. Results IDH mutations were found in 33% of the patients. IDH1 mutations were detected in 49 patients (14%; 47 with R132). IDH2 mutations, previously unreported in AML, were detected in 69 patients (19%; 13 with R172 and 56 with R140). R172 IDH2 mutations were mutually exclusive with all other prognostic mutations analyzed. Younger age (< 60 years), molecular low-risk (NPM1-mutated/FLT3-internal tandem duplication-negative) IDH1-mutated patients had shorter disease-free survival than molecular low-risk IDH1/IDH2-wild-type (wt) patients (P = .046). R172 IDH2-mutated patients had lower complete remission rates than IDH1/IDH2wt patients (P = .007). Distinctive microarray gene- and microRNA-expression profiles accurately predicted R172 IDH2 mutations. The highest expressed gene and microRNAs in R172 IDH2-mutated patients compared with the IDH1/IDH2wt patients were APP (previously associated with complex karyotype AML) and miR-1 and miR-133 (involved in embryonal stem-cell differentiation), respectively. CONCLUSION IDH1 and IDH2 mutations are recurrent in CN-AML and have an unfavorable impact on outcome. The R172 IDH2 mutations, previously unreported in AML, characterize a novel subset of CN-AML patients lacking other prognostic mutations and associate with unique gene- and microRNA-expression profiles that may lead to the discovery of novel, therapeutically targetable leukemogenic mechanisms.

Global mapping of binding sites for Nrf2 identifies novel targets in cell survival response through ChIP-Seq profiling and network analysis

Abstract: The Nrf2 (nuclear factor E2 p45-related factor 2) transcription factor responds to diverse oxidative and electrophilic environmental stresses by circumventing repression by Keap1, translocating to the nucleus, and activating cytoprotective genes. Nrf2 responses provide protection against chemical carcinogenesis, chronic inflammation, neurodegeneration, emphysema, asthma and sepsis in murine models. Nrf2 regulates the expression of a plethora of genes that detoxify oxidants and electrophiles and repair or remove damaged macromolecules, such as through proteasomal processing. However, many direct targets of Nrf2 remain undefined. Here, mouse embryonic fibroblasts (MEF) with either constitutive nuclear accumulation (Keap1−/−) or depletion (Nrf2−/−) of Nrf2 were utilized to perform chromatin-immunoprecipitation with parallel sequencing (ChIP-Seq) and global transcription profiling. This unique Nrf2 ChIP-Seq dataset is highly enriched for Nrf2-binding motifs. Integrating ChIP-Seq and microarray analyses, we identified 645 basal and 654 inducible direct targets of Nrf2, with 244 genes at the intersection. Modulated pathways in stress response and cell proliferation distinguish the inducible and basal programs. Results were confirmed in an in vivo stress model of cigarette smoke-exposed mice. This study reveals global circuitry of the Nrf2 stress response emphasizing Nrf2 as a central node in cell survival response.

Gene expression-based classification of non-small cell lung carcinomas and survival prediction.

Abstract: Background: Current clinical therapy of non-small cell lung cancer depends on histo-pathological classification. This approach poorly predicts clinical outcome for individual patients. Gene expression profiling holds promise to improve clinical stratification, thus paving the way for individualized therapy. Methodology and Principal Findings:A genome-wide gene expression analysis was performed on a cohort of 91 patients. We used 91 tumor- and 65 adjacent normal lung tissue samples. We defined sets of predictor genes (probe sets) with the expression profiles. The power of predictor genes was evaluated using an independent cohort of 96 non-small cell lung cancer- and 6 normal lung samples. We identified a tumor signature of 5 genes that aggregates the 156 tumor and normal samples into the expected groups. We also identified a histology signature of 75 genes, which classifies the samples in the major histological subtypes of non-small cell lung cancer. Correlation analysis identified 17 genes which showed the best association with post-surgery survival time. This signature was used for stratification of all patients in two risk groups. Kaplan-Meier survival curves show that the two groups display a significant difference in post-surgery survival time (p = 5.6E-6). The performance of the signatures was validated using a patient cohort of similar size (Duke University, n = 96). Compared to previously published prognostic signatures for NSCLC, the 17 gene signature performed well on these two cohorts. Conclusions:The gene signatures identified are promising tools for histo-pathological classification of non-small cell lung cancer, and may improve the prediction of clinical outcome.

Genetics and Beyond – The Transcriptome of Human Monocytes and Disease Susceptibility

Abstract: Background Variability of gene expression in human may link gene sequence variability and phenotypes; however, non-genetic variations, alone or in combination with genetics, may also influence expression traits and have a critical role in physiological and disease processes.

RNA-Seq Atlas of Glycine max: a guide to the soybean transcriptome.

Abstract: Next generation sequencing is transforming our understanding of transcriptomes. It can determine the expression level of transcripts with a dynamic range of over six orders of magnitude from multiple tissues, developmental stages or conditions. Patterns of gene expression provide insight into functions of genes with unknown annotation. The RNA Seq-Atlas presented here provides a record of high-resolution gene expression in a set of fourteen diverse tissues. Hierarchical clustering of transcriptional profiles for these tissues suggests three clades with similar profiles: aerial, underground and seed tissues. We also investigate the relationship between gene structure and gene expression and find a correlation between gene length and expression. Additionally, we find dramatic tissue-specific gene expression of both the most highly-expressed genes and the genes specific to legumes in seed development and nodule tissues. Analysis of the gene expression profiles of over 2,000 genes with preferential gene expression in seed suggests there are more than 177 genes with functional roles that are involved in the economically important seed filling process. Finally, the Seq-atlas also provides a means of evaluating existing gene model annotations for the Glycine max genome. This RNA-Seq atlas extends the analyses of previous gene expression atlases performed using Affymetrix GeneChip technology and provides an example of new methods to accommodate the increase in transcriptome data obtained from next generation sequencing. Data contained within this RNA-Seq atlas of Glycine max can be explored at http://www.soybase.org/soyseq .

Integrated Molecular Genetic Profiling of Pediatric High-Grade Gliomas Reveals Key Differences With the Adult Disease

Abstract: Purpose To define copy number alterations and gene expression signatures underlying pediatric high-grade glioma (HGG). Patients and Methods We conducted a high-resolution analysis of genomic imbalances in 78 de novo pediatric HGGs, including seven diffuse intrinsic pontine gliomas, and 10 HGGs arising in children who received cranial irradiation for a previous cancer using single nucleotide polymorphism microarray analysis. Gene expression was analyzed with gene expression microarrays for 53 tumors. Results were compared with publicly available data from adult tumors. Results Significant differences in copy number alterations distinguish childhood and adult glioblastoma. PDGFRA was the predominant target of focal amplification in childhood HGG, including diffuse intrinsic pontine gliomas, and gene expression analyses supported an important role for deregulated PDGFRα signaling in pediatric HGG. No IDH1 hotspot mutations were found in pediatric tumors, highlighting molecular differences with adult secondar...

Clinical Utility of Microarray-Based Gene Expression Profiling in the Diagnosis and Subclassification of Leukemia: Report From the International Microarray Innovations in Leukemia Study Group

Abstract: Purpose The Microarray Innovations in Leukemia study assessed the clinical utility of gene expression profiling as a single test to subtype leukemias into conventional categories of myeloid and lymphoid malignancies. Methods The investigation was performed in 11 laboratories across three continents and included 3,334 patients. An exploratory retrospective stage I study was designed for biomarker discovery and generated whole-genome expression profiles from 2,143 patients with leukemias and myelodysplastic syndromes. The gene expression profiling–based diagnostic accuracy was further validated in a prospective second study stage of an independent cohort of 1,191 patients. Results On the basis of 2,096 samples, the stage I study achieved 92.2% classification accuracy for all 18 distinct classes investigated (median specificity of 99.7%). In a second cohort of 1,152 prospectively collected patients, a classification scheme reached 95.6% median sensitivity and 99.8% median specificity for 14 standard subtypes...

Pilot Study Using Molecular Profiling of Patients' Tumors to Find Potential Targets and Select Treatments for Their Refractory Cancers

Abstract: Purpose To compare the progression-free survival (PFS) using a treatment regimen selected by molecular profiling (MP) of a patient's tumor with the PFS for the most recent regimen on which the patient had experienced progression (ie, patient as his own control). Patients and Methods Patients with refractory metastatic cancer had tissue samples submitted for MP in two formats including formalin-fixed tissue for immunohistochemistry and fluorescent in situ hybridization assays and immediately frozen tissue for oligonucleotide microarray (MA) gene expression assays (all performed in a Clinical Laboratory Improvement Amendments [CLIA] –certified laboratory). The MP approach was deemed of clinical benefit for the individual patient who had a PFS ratio (PFS on MP-selected therapy/PFS on prior therapy) of ≥ 1.3. Results In 86 patients who had MP attempted, there was a molecular target detected in 84 (98%). Sixty-six of the 84 patients were treated according to MP results. Eighteen (27%) of 66 patients had a PFS ...

A census of amplified and overexpressed human cancer genes

Abstract: Integrated genome-wide screens of DNA copy number and gene expression in human cancers have accelerated the rate of discovery of amplified and overexpressed genes. However, the biological importance of most of the genes identified in such studies remains unclear. In this Analysis, we propose a weight-of-evidence based classification system for identifying individual genes in amplified regions that are selected for during tumour development. In a census of the published literature we have identified 77 genes for which there is good evidence of involvement in the development of human cancer.

Aneuploidy confers quantitative proteome changes and phenotypic variation in budding yeast.

Abstract: Aneuploidy, referring here to genome contents characterized by abnormal numbers of chromosomes, has been associated with developmental defects, cancer and adaptive evolution in experimental organisms. However, it remains unresolved how aneuploidy impacts gene expression and whether aneuploidy could directly bring about phenotypic variation and improved fitness over that of euploid counterparts. Here we show, using quantitative mass spectrometry-based proteomics and phenotypic profiling, that levels of protein expression in aneuploid yeast strains largely scale with chromosome copy numbers, following the same trend as that observed for the transcriptome, and that aneuploidy confers diverse phenotypes. We designed a novel scheme to generate, through random meiotic segregation, 38 stable and fully isogenic aneuploid yeast strains with distinct karyotypes and genome contents between 1N and 3N without involving any genetic selection. Through quantitative growth assays under various conditions or in the presence of a panel of chemotherapeutic or antifungal drugs, we found that some aneuploid strains grew significantly better than euploid control strains under conditions suboptimal for the latter. These results provide strong evidence that aneuploidy directly affects gene expression at both the transcriptome and proteome levels and can generate significant phenotypic variation that could bring about fitness gains under diverse conditions. Our findings suggest that the fitness ranking between euploid and aneuploid cells is dependent on context and karyotype, providing the basis for the notion that aneuploidy can directly underlie phenotypic evolution and cellular adaptation.

High-Resolution Analysis of Parent-of-Origin Allelic Expression in the Mouse Brain

Abstract: Genomic imprinting results in preferential expression of the paternal or maternal allele of certain genes. We have performed a genome-wide characterization of imprinting in the mouse embryonic and adult brain. This approach uncovered parent-of-origin allelic effects of more than 1300 loci. We identified parental bias in the expression of individual genes and of specific transcript isoforms, with differences between brain regions. Many imprinted genes are expressed in neural systems associated with feeding and motivated behaviors, and parental biases preferentially target genetic pathways governing metabolism and cell adhesion. We observed a preferential maternal contribution to gene expression in the developing brain and a major paternal contribution in the adult brain. Thus, parental expression bias emerges as a major mode of epigenetic regulation in the brain.

Microfluidic isolation and transcriptome analysis of serum microvesicles

Abstract: Microvesicles (exosomes) shed from both normal and cancerous cells may serve as means of intercellular communication. These microvesicles carry proteins, lipids and nucleic acids derived from the host cell. Their isolation and analysis from blood samples have the potential to provide information about state and progression of malignancy and should prove of great clinical importance as biomarkers for a variety of disease states. However, current protocols for isolation of microvesicles from blood require high-speed centrifugation and filtration, which are cumbersome and time consuming. In order to take full advantage of the potential of microvesicles as biomarkers for clinical applications, faster and simpler methods of isolation will be needed. In this paper, we present an easy and rapid microfluidic immunoaffinity method to isolate microvesicles from small volumes of both serum from blood samples and conditioned medium from cells in culture. RNA of high quality can be extracted from these microvesicles providing a source of information about the genetic status of tumors to serve as biomarkers for diagnosis and prognosis of cancer.