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Related Experiment Videos

Whole-body gene expression by data mining.

R Pires Martins1, R E Leach, S A Krawetz

  • 1Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, Michigan 48201, USA.

Genomics
|March 15, 2001
PubMed
Summary
This summary is machine-generated.

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This study introduces an in silico data mining strategy to efficiently survey gene expression across human tissues. This method overcomes the limitations of in vitro studies for lysyl oxidase (LOX) family genes and CGI-15.

Area of Science:

  • Bioinformatics
  • Molecular Biology
  • Genomics

Background:

  • Comprehensive expression profiling of lysyl oxidase (LOX), lysyl oxidase-like 1 (LOXL1), and lysyl oxidase-like 2 (LOXL2) is lacking.
  • In vitro methods for gene expression surveys are time-consuming and costly.

Purpose of the Study:

  • To develop and present a novel in silico data mining strategy for gene expression analysis.
  • To survey the expression patterns of LOX, LOXL1, LOXL2, and CGI-15 across human tissues.
  • To establish relative mRNA transcript levels efficiently.

Main Methods:

  • In silico data mining strategy utilizing 3' untranslated regions (UTRs) of target genes.
  • Querying sequences against the human expressed sequence tag database (dbEST).
  • Validation of the in silico method using semiquantitative PCR analysis.

Related Experiment Videos

Main Results:

  • Successfully surveyed the entire tissue repertoire available in dbEST for LOX family genes and CGI-15.
  • Provided estimates of mRNA transcript levels in various adult and fetal human tissues.
  • Demonstrated the utility of the in silico strategy for determining gene expression patterns.

Conclusions:

  • The developed in silico data mining strategy is a time- and cost-effective alternative to in vitro methods.
  • This approach enables comprehensive gene expression profiling across a wide range of human tissues.
  • The strategy's application is scalable with the growth of genomic databases like GenBank and UniGene.