A major obstacle in positional cloning is identifying the specific mutated gene from within a large physical contig. Here we describe the application of DNA microarray technology to a defined genomic region (physical map) to identify: (i) exons without a priori sequence data and (ii) the disease gene based on differential gene expression in a recessive disorder. The feasibility was tested using resources from the positional cloning of the Neimann-Pick Type C (NP-C) disease gene, NPC1. To identify NPC1 exons and optimize the technology, an array was generated from genomic fragments of the 110-kb bacterial artificial chromosome, 108N2, which encodes NPC1. First, as a test case for blindly identifying exons, fluorescently labeled NPC1 cDNA identified 108N2 fragments that contained NPC1 exons, many of which also contained intronic sequences and could be used to determine part of the NPC1 genomic structure. Second, to demonstrate that the NPC1 disease gene could be identified based upon differential gene expression, subarrays of 108N2 fragments were hybridized with fluorescently labeled cDNA probes generated from total RNA from hamster cell lines differentially expressing NPC1. A probe derived from the NP-C cell line CT60 did not detect NPC1 exons or other genomic fragments from 108N2. In contrast, several NPC1 exons were detected by a probe generated from the non-NP-C cell line 911D5A13, which was derived from CT60, and expressed NPC1 as a consequence of stable transduction with a YAC that contains NPC1 and encompasses 108N2. Thus, the array technology identified NPC1 as a candidate gene based on a physical contig and differential NPC1 expression between NP-C and non-NP-C cells. This technique should facilitate gene identification when a physical contig exists for a region of interest and mutations result in changes in the mRNA level of the disease gene or portions thereof. (C) 2000 Academic Press.
ASJC Scopus subject areas
- Endocrinology, Diabetes and Metabolism
- Molecular Biology