Literature DB >> 15718107

Coupled analysis of gene expression and chromosomal location.

Yajun Yi1, Janni Mirosevich, Yu Shyr, Robert Matusik, Alfred L George.   

Abstract

Microarray technology can be used to assess simultaneously global changes in expression of mRNA or genomic DNA copy number among thousands of genes in different biological states. In many cases, it is desirable to determine if altered patterns of gene expression correlate with chromosomal abnormalities or assess expression of genes that are contiguous in the genome. We describe a method, differential gene locus mapping (DIGMAP), which aligns the known chromosomal location of a gene to its expression value deduced by microarray analysis. The method partitions microarray data into subsets by chromosomal location for each gene interrogated by an array. Microarray data in an individual subset can then be clustered by physical location of genes at a subchromosomal level based upon ordered alignment in genome sequence. A graphical display is generated by representing each genomic locus with a colored cell that quantitatively reflects its differential expression value. The clustered patterns can be viewed and compared based on their expression signatures as defined by differential values between control and experimental samples. In this study, DIGMAP was tested using previously published studies of breast cancer analyzed by comparative genomic hybridization (CGH) and prostate cancer gene expression profiles assessed by cDNA microarray experiments. Analysis of the breast cancer CGH data demonstrated the ability of DIGMAP to deduce gene amplifications and deletions. Application of the DIGMAP method to the prostate data revealed several carcinoma-related loci, including one at 16q13 with marked differential expression encompassing 19 known genes including 9 encoding metallothionein proteins. We conclude that DIGMAP is a powerful computational tool enabling the coupled analysis of microarray data with genome location.

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Year:  2005        PMID: 15718107     DOI: 10.1016/j.ygeno.2004.11.011

Source DB:  PubMed          Journal:  Genomics        ISSN: 0888-7543            Impact factor:   5.736


  18 in total

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2.  Molecular alterations in primary prostate cancer after androgen ablation therapy.

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Journal:  Clin Cancer Res       Date:  2005-10-01       Impact factor: 12.531

3.  Functional remodeling of benign human prostatic tissues in vivo by spontaneously immortalized progenitor and intermediate cells.

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4.  Integrated genomic and transcriptional profiling identifies chromosomal loci with altered gene expression in cervical cancer.

Authors:  Saskia M Wilting; Jillian de Wilde; Chris J L M Meijer; Johannes Berkhof; Yajun Yi; Wessel N van Wieringen; Boudewijn J M Braakhuis; Gerrit A Meijer; Bauke Ylstra; Peter J F Snijders; Renske D M Steenbergen
Journal:  Genes Chromosomes Cancer       Date:  2008-10       Impact factor: 5.006

5.  Detecting cancer gene networks characterized by recurrent genomic alterations in a population.

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6.  A graphical assessment of p-values from sliding window haplotype tests of association to identify asthma susceptibility loci on chromosome 11q.

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7.  Candidate metastasis suppressor genes uncovered by array comparative genomic hybridization in a mouse allograft model of prostate cancer.

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Journal:  Mol Cytogenet       Date:  2009-09-26       Impact factor: 2.009

8.  Differences in X-chromosome transcriptional activity and cholesterol metabolism between placentae from swine breeds from Asian and Western origins.

Authors:  Steve R Bischoff; Shengdar Q Tsai; Nicholas E Hardison; Alison A Motsinger-Reif; Bradley A Freking; Dan J Nonneman; Gary A Rohrer; Jorge A Piedrahita
Journal:  PLoS One       Date:  2013-01-31       Impact factor: 3.240

9.  Microarray analysis of gliomas reveals chromosomal position-associated gene expression patterns and identifies potential immunotherapy targets.

Authors:  Oscar Persson; Morten Krogh; Lao H Saal; Elisabet Englund; Jian Liu; Ramon Parsons; Nils Mandahl; Ake Borg; Bengt Widegren; Leif G Salford
Journal:  J Neurooncol       Date:  2007-07-17       Impact factor: 4.506

10.  Quantification of normal cell fraction and copy number neutral LOH in clinical lung cancer samples using SNP array data.

Authors:  Hanna Göransson; Karolina Edlund; Maria Rydåker; Markus Rasmussen; Johan Winquist; Simon Ekman; Michael Bergqvist; Andrew Thomas; Mats Lambe; Richard Rosenquist; Lars Holmberg; Patrick Micke; Johan Botling; Anders Isaksson
Journal:  PLoS One       Date:  2009-06-26       Impact factor: 3.240

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