Identification of novel stem cell markers using gap analysis of gene expression data

A method for the detection of marker genes in large heterogeneous collections of gene expression data is described and applied to DNA microarray data generated from 83 mouse stem cell-related samples

Recent developments in StemBase: a tool to study gene expression in human and murine stem cells

<p>Abstract</p> <p>Background</p> <p>Currently one of the largest online repositories for human and mouse stem cell gene expression data, StemBase was first designed as a simple web-interface to DNA microarray data generated by the Canadian Stem Cell Network to facilitate the discovery of gene functions relevant to stem cell control and differentiation.</p> <p>Findings</p> <p>Since its creation, StemBase has grown in both size and scope into a system with analysis tools that examine either the whole database at once, or slices of data, based on tissue type, cell type or gene of interest. As of September 1, 2008, StemBase contains gene expression data (microarray and Serial Analysis of Gene Expression) from 210 stem cell samples in 60 different experiments.</p> <p>Conclusion</p> <p>StemBase can be used to study gene expression in human and murine stem cells and is available at <url>http://www.stembase.ca</url>.</p

Integration of Expressed Sequence Tag Data Flanking Predicted RNA Secondary Structures Facilitates Novel Non-Coding RNA Discovery

Many computational methods have been used to predict novel non-coding RNAs (ncRNAs), but none, to our knowledge, have explicitly investigated the impact of integrating existing cDNA-based Expressed Sequence Tag (EST) data that flank structural RNA predictions. To determine whether flanking EST data can assist in microRNA (miRNA) prediction, we identified genomic sites encoding putative miRNAs by combining functional RNA predictions with flanking ESTs data in a model consistent with miRNAs undergoing cleavage during maturation. In both human and mouse genomes, we observed that the inclusion of flanking ESTs adjacent to and not overlapping predicted miRNAs significantly improved the performance of various methods of miRNA prediction, including direct high-throughput sequencing of small RNA libraries. We analyzed the expression of hundreds of miRNAs predicted to be expressed during myogenic differentiation using a customized microarray and identified several known and predicted myogenic miRNA hairpins. Our results indicate that integrating ESTs flanking structural RNA predictions improves the quality of cleaved miRNA predictions and suggest that this strategy can be used to predict other non-coding RNAs undergoing cleavage during maturation

Prediction of acute myeloid leukaemia risk in healthy individuals

The incidence of acute myeloid leukaemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 65. Most cases arise without any detectable early symptoms and patients usually present with the acute complications of bone marrow failure(1). The onset of such de novo AML cases is typically preceded by the accumulation of somatic mutations in preleukaemic haematopoietic stem and progenitor cells (HSPCs) that undergo clonal expansion(2,3). However, recurrent AML mutations also accumulate in HSPCs during ageing of healthy individuals who do not develop AML, a phenomenon referred to as age-related clonal haematopoiesis (ARCH)(4-8). Here we use deep sequencing to analyse genes that are recurrently mutated in AML to distinguish between individuals who have a high risk of developing AML and those with benign ARCH. We analysed peripheral blood cells from 95 individuals that were obtained on average 6.3 years before AML diagnosis (pre-AML group), together with 414 unselected age- and gender-matched individuals (control group). Pre-AML cases were distinct from controls and had more mutations per sample, higher variant allele frequencies, indicating greater clonal expansion, and showed enrichment of mutations in specific genes. Genetic parameters were used to derive a model that accurately predicted AML-free survival; this model was validated in an independent cohort of 29 pre-AML cases and 262 controls. Because AML is rare, we also developed an AML predictive model using a large electronic health record database that identified individuals at greater risk. Collectively our findings provide proof-of-concept that it is possible to discriminate ARCH from pre-AML many years before malignant transformation. This could in future enable earlier detection and monitoring, and may help to inform intervention

Landscape of somatic single nucleotide variants and indels in colorectal cancer and impact on survival

Colorectal cancer (CRC) is a biologically heterogeneous disease. To characterize its mutational profile, we conduct targeted sequencing of 205 genes for 2,105 CRC cases with survival data. Our data shows several findings in addition to enhancing the existing knowledge of CRC. We identify PRKCI, SPZ1, MUTYH, MAP2K4, FETUB, and TGFBR2 as additional genes significantly mutated in CRC. We find that among hypermutated tumors, an increased mutation burden is associated with improved CRC-specific survival (HR=0.42, 95% CI: 0.21-0.82). Mutations in TP53 are associated with poorer CRC-specific survival, which is most pronounced in cases carrying TP53 mutations with predicted 0% transcriptional activity (HR=1.53, 95% CI: 1.21-1.94). Furthermore, we observe differences in mutational frequency of several genes and pathways by tumor location, stage, and sex. Overall, this large study provides deep insights into somatic mutations in CRC, and their potential relationships with survival and tumor features. Large scale sequencing study is of paramount importance to unravel the heterogeneity of colorectal cancer. Here, the authors sequenced 205 cancer genes in more than 2000 tumours and identified additional mutated driver genes, determined that mutational burden and specific mutations in TP53 are associated with survival odds

Measurement of the F2 structure function in deep inelastic e+^{+}p scattering using 1994 data from the ZEUS detector at HERA

We present measurements of the structure function \Ft\ in e^+p scattering at HERA in the range 3.5\;\Gevsq < \qsd < 5000\;\Gevsq. A new reconstruction method has allowed a significant improvement in the resolution of the kinematic variables and an extension of the kinematic region covered by the experiment. At \qsd < 35 \;\Gevsq the range in x now spans 6.3\cdot 10^{-5} < x < 0.08 providing overlap with measurements from fixed target experiments. At values of Q^2 above 1000 GeV^2 the x range extends to 0.5. Systematic errors below 5\perc\ have been achieved for most of the kinematic urray, W

Measurement of Elastic ϕ\phi Photoproduction at HERA

The production of $\phi$ mesons in the reaction $e^{+}p \rightarrow e^{+} \phi p$ ($\phi \rightarrow K^{+}K^{-}$) at a median $Q^{2}$ of $10^{-4} \ \rm{GeV^2}$has been studied with the ZEUS detector at HERA. The differential$\phi$photoproduction cross section$d\sigma/dt$has an exponential shape and has been determined in the kinematic range$0.1<|t|<0.5 \ \rm{GeV^2}$and$60 < W < 80 \ \rm{GeV}$. An integrated cross section of$\sigma_{\gamma p \rightarrow \phi p} = 0.96 \pm 0.19^{+0.21}_{-0.18}$$\rm{\mu b}$has been obtained by extrapolating to {\it t} = 0. When compared to lower energy data, the results show a weak energy dependence of both$\sigma_{\gamma p \rightarrow \phi p}$and the slope of the$t$distribution. The$\phi$decay angular distributions are consistent with$s$-channel helicity conservation. From lower energies to HERA energies, the features of$\phi$ photoproduction are compatible with those of a soft diffractive process.Comment: 23 pages, including 6 post script figure