A First-Stage Approximation to Identify New Imprinted Genes through Sequence Analysis of Its Coding Regions

In the present study, a positive training set of 30 known human imprinted gene coding regions are compared with a set of 72 randomly sampled human nonimprinted gene coding regions (negative training set) to identify genomic features common to human imprinted genes. The most important feature of the...

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Bibliographic Details
Published in:Comparative and functional genomics 2009-01, Vol.2009 (2009), p.1-7
Main Authors: Daura-Oller, Elias, Cabré, Maria, Montero, Miguel A., Paternáin, José L., Romeu, Antoni
Format: Article
Language:English
Subjects:
Genomic imprinting
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Summary:In the present study, a positive training set of 30 known human imprinted gene coding regions are compared with a set of 72 randomly sampled human nonimprinted gene coding regions (negative training set) to identify genomic features common to human imprinted genes. The most important feature of the present work is its ability to use multivariate analysis to look at variation, at coding region DNA level, among imprinted and non-imprinted genes. There is a force affecting genomic parameters that appears through the use of the appropriate multivariate methods (principle components analysis (PCA) and quadratic discriminant analysis (QDA) to analyse quantitative genomic data. We show that variables, such as CG content, [bp]% CpG islands, [bp]% Large Tandem Repeats, and [bp]% Simple Repeats, are able to distinguish coding regions of human imprinted genes.
ISSN:1531-6912
2314-436X
1532-6268
2314-4378
DOI:10.1155/2009/549387