Jo Vandesompele

Bio: Jo Vandesompele is an academic researcher from Ghent University. The author has contributed to research in topics: Neuroblastoma & microRNA. The author has an hindex of 88, co-authored 383 publications receiving 59368 citations. Previous affiliations of Jo Vandesompele include Washington University in St. Louis & Ghent University Hospital.

The RNA Atlas expands the catalog of human non-coding RNAs.

Abstract: Existing compendia of non-coding RNA (ncRNA) are incomplete, in part because they are derived almost exclusively from small and polyadenylated RNAs. Here we present a more comprehensive atlas of the human transcriptome, which includes small and polyA RNA as well as total RNA from 300 human tissues and cell lines. We report thousands of previously uncharacterized RNAs, increasing the number of documented ncRNAs by approximately 8%. To infer functional regulation by known and newly characterized ncRNAs, we exploited pre-mRNA abundance estimates from total RNA sequencing, revealing 316 microRNAs and 3,310 long non-coding RNAs with multiple lines of evidence for roles in regulating protein-coding genes and pathways. Our study both refines and expands the current catalog of human ncRNAs and their regulatory interactions. All data, analyses and results are available for download and interrogation in the R2 web portal, serving as a basis for future exploration of RNA biology and function.

MicroRNA-128-3p is a novel oncomiR targeting PHF6 in T-cell acute lymphoblastic leukemia

Abstract: T-cell acute lymphoblastic leukemia arises from the leukemic transformation of developing thymocytes and results from cooperative genetic lesions. Inactivation of the PHF6 gene is frequently observed in T-cell acute lymphoblastic leukemia, suggesting an important tumor suppressive role for PHF6 in the pathobiology of this leukemia. Although the precise function of PHF6 is still unknown, this gene is most likely involved in chromatin regulation, a strongly emerging theme in T-cell acute lymphoblastic leukemia. In this context, our previous description of a cooperative microRNA regulatory network controlling several well-known T-cell acute lymphoblastic leukemia tumor suppressor genes, including PHF6, is of great importance. Given the high frequency of PHF6 lesions in T-cell acute lymphoblastic leukemia and the integration of PHF6 in this microRNA regulatory network, we aimed to identify novel oncogenic microRNAs in T-cell acute lymphoblastic leukemia which suppress PHF6. To this end, we performed an unbiased PHF6 3'UTR-microRNA library screen and combined the results with microRNA profiling data of samples from patients with T-cell acute lymphoblastic leukemia and normal thymocyte subsets. We selected miR-128-3p as a candidate PHF6-targeting, oncogenic microRNA and demonstrated regulation of PHF6 expression upon modulation of this microRNA in T-cell acute lymphoblastic leukemia cell lines. In vivo evidence of an oncogenic role of this microRNA in T-cell acute lymphoblastic leukemia was obtained through accelerated leukemia onset in a NOTCH1-induced T-cell acute lymphoblastic leukemia mouse model upon miR-128-3p over-expression. We conclude that miR-128-3p is a strong novel candidate oncogenic microRNA in T-cell acute lymphoblastic leukemia which targets the PHF6 tumor suppressor gene.

EVI1 is consistently expressed as principal transcript in common and rare recurrent 3q26 rearrangements

Abstract: In contrast to the well-documented involvement of EVI1 in various 3q26 aberrations, the transcriptional status of EVI1 in rare recurrent or sporadic 3q26 chromosomal defects has remained largely unexplored. Moreover, in a recent report, the association between 3q26 alterations in myeloid proliferations and ectopic EVI1 expression was questioned. Therefore, we performed a detailed physical mapping of 3q26 breakpoints using a 1.3-Mb tiling path BAC contig covering the EVI1 locus and a carefully designed quantification of both EVI1 and MDS/EVI1 transcripts in 30 hematological malignancies displaying 3q26 aberrations. Cases included well-known rare, recurring chromosomal aberrations such as t(3;17)(q26;q22), t(2;3)(p21–22;q26), and t(3;6)(q26;q25), as well as 10 new sporadic cases. Extensive 3q26 breakpoint mapping allowed unequivocal and sensitive FISH detection of EVI1 rearrangements on both metaphases and interphase nuclei. Real-time quantitative PCR analyses indicated that typically both MDS1/EVI1 and EVI1, but not MDS1, were expressed in these malignancies, with EVI1 the primary transcript. In conclusion, we have demonstrated EVI1 involvement in numerous novel sporadic and recurrent 3q26 rearrangements. Our results underscore the feasibility of FISH as an adjunct to PCR for the identification of EVI1 deranged leukemias and identified EVI1 as the principal transcript expressed in these malignancies. © 2005 Wiley-Liss, Inc.

Positional gene enrichment analysis of gene sets for high-resolution identification of overrepresented chromosomal regions.

Abstract: The search for feature enrichment is a widely used method to characterize a set of genes. While several tools have been designed for nominal features such as Gene Ontology annotations or KEGG Pathways, very little has been proposed to tackle numerical features such as the chromosomal positions of genes. For instance, microarray studies typically generate gene lists that are differentially expressed in the sample subgroups under investigation, and when studying diseases caused by genome alterations, it is of great interest to delineate the chromosomal regions that are significantly enriched in these lists. In this article, we present a positional gene enrichment analysis method (PGE) for the identification of chromosomal regions that are significantly enriched in a given set of genes. The strength of our method relies on an original query optimization approach that allows to virtually consider all the possible chromosomal regions for enrichment, and on the multiple testing correction which discriminates truly enriched regions versus those that can occur by chance. We have developed a Web tool implementing this method applied to the human genome (http://www.esat.kuleuven.be/~bioiuser/pge). We validated PGE on published lists of differentially expressed genes. These analyses showed significant overrepresentation of known aberrant chromosomal regions.

The long noncoding RNA lncNB1 promotes tumorigenesis by interacting with ribosomal protein RPL35.

Abstract: The majority of patients with neuroblastoma due to MYCN oncogene amplification and consequent N-Myc oncoprotein over-expression die of the disease. Here our analyses of RNA sequencing data identify the long noncoding RNA lncNB1 as one of the transcripts most over-expressed in MYCN-amplified, compared with MYCN-non-amplified, human neuroblastoma cells and also the most over-expressed in neuroblastoma compared with all other cancers. lncNB1 binds to the ribosomal protein RPL35 to enhance E2F1 protein synthesis, leading to DEPDC1B gene transcription. The GTPase-activating protein DEPDC1B induces ERK protein phosphorylation and N-Myc protein stabilization. Importantly, lncNB1 knockdown abolishes neuroblastoma cell clonogenic capacity in vitro and leads to neuroblastoma tumor regression in mice, while high levels of lncNB1 and RPL35 in human neuroblastoma tissues predict poor patient prognosis. This study therefore identifies lncNB1 and its binding protein RPL35 as key factors for promoting E2F1 protein synthesis, N-Myc protein stability and N-Myc-driven oncogenesis, and as therapeutic targets.

limma powers differential expression analyses for RNA-sequencing and microarray studies

Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

Cutadapt removes adapter sequences from high-throughput sequencing reads

Abstract: When small RNA is sequenced on current sequencing machines, the resulting reads are usually longer than the RNA and therefore contain parts of the 3' adapter. That adapter must be found and removed error-tolerantly from each read before read mapping. Previous solutions are either hard to use or do not offer required features, in particular support for color space data. As an easy to use alternative, we developed the command-line tool cutadapt, which supports 454, Illumina and SOLiD (color space) data, offers two adapter trimming algorithms, and has other useful features. Cutadapt, including its MIT-licensed source code, is available for download at http://code.google.com/p/cutadapt/

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes

Abstract: Gene-expression analysis is increasingly important in biological research, with real-time reverse transcription PCR (RT-PCR) becoming the method of choice for high-throughput and accurate expression profiling of selected genes. Given the increased sensitivity, reproducibility and large dynamic range of this methodology, the requirements for a proper internal control gene for normalization have become increasingly stringent. Although housekeeping gene expression has been reported to vary considerably, no systematic survey has properly determined the errors related to the common practice of using only one control gene, nor presented an adequate way of working around this problem. We outline a robust and innovative strategy to identify the most stably expressed control genes in a given set of tissues, and to determine the minimum number of genes required to calculate a reliable normalization factor. We have evaluated ten housekeeping genes from different abundance and functional classes in various human tissues, and demonstrated that the conventional use of a single gene for normalization leads to relatively large errors in a significant proportion of samples tested. The geometric mean of multiple carefully selected housekeeping genes was validated as an accurate normalization factor by analyzing publicly available microarray data. The normalization strategy presented here is a prerequisite for accurate RT-PCR expression profiling, which, among other things, opens up the possibility of studying the biological relevance of small expression differences.