Microarrays: Use in Gene Identification


Gene prediction by computer algorithms and approaches based on comparative genomics identifies the presence of potential genes in a genomic sequence. By placing these predicted genes onto microarrays and searching for interactions with complementary DNA from different types of tissue or cell, novel genes are discovered.

Keywords: gene prediction; comparative genomics; chromosome 22; myosin; open reading frame

Figure 1.

Workflow of microarray design.

Figure 2.

A screen capture of the visual display tool ‘Mondrian’ showing gene expression in the genomic region that contains the myosin‐like gene. The top of the screen shows the combinations of data from which the user can select to customize the view. The genomic chromosome sequence is shown running from left to right. The amplicon squares indicate the position of each amplicon on the genomic sequence. Beneath the amplicon is indicated the gene expression of that sequence in each of the tissues and cell lines listed. The intensity of shading indicates the expression of the gene relative to that of the control, which in this example is a pool of tissue types. In each square is a white circle, with the size of this circle representing the relative intensity of the signal. Beneath the gene expression data, information from the gene prediction programs (Grail, GeneFinder and Genscan) is represented, along with data on the full‐length clones generated by the in‐house effort. Note that additional tissues were examined with microarrays (and are thus shown on the ‘Mondrian’), after the initial confirmatory data were collected in Figures

Figure 3.

Expression data for the myosin‐like gene: (a) microarray; (b) RT‐PCR using RapidScanTM Gene Expression tissues from Origene Technologies Inc. and (c) Northern blot analysis.

Figure 4.

Gene structure of the myosin‐like gene from human heart.



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Further Reading

Gieser P, Bloom GC, Lazaridis EN (2002) Introduction to microarray experimentation and analysis. Methods of Molecular Biology 184: 29–49.

Jaffé HLC (1985) Piet Mondrian (Masters of Art Series) New York, NY: Harry N Abrams.

Knudsen S (2002) A Biologist's Guide to Analysis of DNA Microarray Data, 1st edn Chichester, UK: John Wiley & Sons.

Mount DW (2001) Bioinformatics: Sequence and Genome Analysis, 1st edn. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory Press.

Nees M and Woodworth CD (2001) Microarrays: spotlight on gene function and pharmacogenomics. Current Cancer Drug Targets, 1(2): 155–75.

Schena M (2002) Microarray Analysis Hoboken, NJ: Wiley‐Liss.

Web Links

RefSeq http://www.ncbi.nlm.nih.gov/LocusLink/refseq.html

Unigene http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=unigene

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How to Cite close
Rank, David R, Hanzel, David K, Jenkins, David, Thomas, Russell S, Shannon, Mark, Guo, Jinjiao, Corrigan, Amy, Zhang, Jian, Gu, Yizhong, Chen, Wensheng, Ji, Yonggang, Hu, Tianhua, Barker, David L, and Penn, Sharron G(Jan 2006) Microarrays: Use in Gene Identification. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1038/npg.els.0005952]