Map of differential transcript expression in the normal human large intestine.

  • LaPointe L
  • Dunne R
  • Brown G
 et al. 
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Abstract

While there is considerable research related to using differential gene expression to predict disease phenotype classification, e.g., neoplastic tissue from nonneoplastic controls, there is little understanding of the range of expression in normal tissues. Understanding patterns of gene expression in nonneoplastic tissue, including regional anatomic expression changes within an organ, is vital to understanding gene expression changes in diseased tissue. To explore the gene expression change along the proximal-distal axis of the large intestine, we analyzed microarray data in 184 normal human specimens using univariate and multivariate techniques. We found 219 probe sets that were differentially expressed between the proximal and distal colorectal regions and 115 probe sets that were differentially expressed between the terminal segments, i.e., the cecum and rectum. We did not observe any probe sets that were statistically different between any two contiguous colorectal segments. The dominant expression pattern (65 probe sets) follows a dichotomous expression pattern consistent with the midgut-hindgut embryonic origins of the gut while a second pattern (50 probe sets) depicts a gradual change in transcript levels from the cecum to the rectum. While the dichotomous pattern includes roughly equal numbers of probe sets that are elevated proximally and distally, nearly all probe sets that show a gradual change demonstrate increasing expression levels moving from proximal to distal segments. These patterns describe an expression map of individual transcript variation as well as multigene expression patterns along the large intestine. This is the first gene expression map of an entire human organ.

Author-supplied keywords

  • colon
  • geo
  • gse9254
  • normal

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Authors

  • Lawrence LaPointe

  • Robert Dunne

  • Glenn Brown

  • Daniel Worthley

  • Peter Molloy

  • David Wattchow

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