4.6 Article

The complex genetics of human insulin-like growth factor 2 are not reflected in public databases

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JOURNAL OF BIOLOGICAL CHEMISTRY
卷 293, 期 12, 页码 4324-4333

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AMER SOC BIOCHEMISTRY MOLECULAR BIOLOGY INC
DOI: 10.1074/jbc.RA117.001573

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  1. National Institutes of Health Research [R01 DK042748-28]

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Recent advances in genetics present unique opportunities for enhancing knowledge about human physiology and disease susceptibility. Understanding this information at the individual gene level is challenging and requires extracting, collating, and interpreting data from a variety of public gene repositories. Here, I illustrate this challenge by analyzing the gene for human insulin-like growth factor 2 (IGF2) through the lens of several databases. IGF2, a 67-amino acid secreted peptide, is essential for normal prenatal growth and is involved in other physiological and pathophysiological processes in humans. Surprisingly, none of the genetic databases accurately described or completely delineated human IGF2 gene structure or transcript expression, even though all relevant information could be found in the published literature. Although IGF2 shares multiple features with the mouse Igf2 gene, it has several unique properties, including transcription from five promoters. Both genes undergo parental imprinting, with IGF2/Igf2 being expressed primarily from the paternal chromosome and the adjacent H19 gene from the maternal chromosome. Unlike mouse Igf2, whose expression declines after birth, human IGF2 remains active throughout life. This characteristic has been attributed to a unique human gene promoter that escapes imprinting, but as shown here, it involves several different promoters with distinct tissue-specific expression patterns. Because new testable hypotheses could lead to critical insights into IGF2 actions in human physiology and disease, it is incumbent that our fundamental understanding is accurate. Similar challenges affecting knowledge of other human genes should promote attempts to critically evaluate, interpret, and correct human genetic data in publicly available databases.

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