Autosomal recessive polycystic kidney disease (ARPKD) is, among congenital renal disorders, a significant cause of pediatric morbidity and mortality. Affected children typically suffer from hypertension progressive renal insufficiency and portal tract fibrosis. The clinical spectrum of ARPKD is widely variable with most cases presenting in infancy. The genetic defect in this disease is unknown and the molecular mechanisms involved in renal cyst formation, liver disease and the development of hypertension remain to be elucidated. The gene responsible for the milder form of this disorder has recently been mapped to chromosome 6p21-12. We have subsequently confirmed linkage between this locus and the severe perinatal form of the disease and have refined the ARPKD genetic interval using recombination mapping to an interval of equal to or less than 4 centiMorgan. The proposed project is part of an interactive, international consortium effort to identify the ARPKD gene. In preparation for this study, we have assembled the largest available database of ARPKD families and tissue from affected individuals. We have constructed a contig of overlapping genomic fragments cloned in yeast artificial chromosomes (YACs) that spans the interval between the closest flanking genetic markers and have verified its authenticity using sequence tagged sites (STSs) generated in our laboratories. The collection of pedigrees, ARPKD kidney and liver tissues, the physical map and the cloned genomic segments represent critical resources for the isolation of the human ARPKD gene. In this application, we propose to construct a high density genetic map of the ARPKD candidate region. We will study currently identified recombinants and recruit the participation of additional families to further refine the recombination map. We will isolate and characterize new microsatellite markers mapping within the interval defined by the current closest flanking genetic markers and a high density STS map (<50 kb resolution) of the refined interval will be produced. The YAC-based physical map will be converted into a set of overlapping P1 and/or cosmid clones. The latter reagents will be used to identify expressed sequences using a combination of methods (e.g., cDNA library screening, exon trapping and cDNA selection protocols). This data will be integrated with existing EST content maps of the YACs to produce a transcription map of the ARPKD interval. We will evaluate the potential candidacy of each gene by determining its sequence and expression pattern in normal and affected tissue. We will.scan leading candidates for pathogenic sequence differenceS using a combination of methods including SSCA, heteroduplex analysis, direct genomic sequencing and/or RNase protection. The ultimate selection of a method will depend on the size of the gene and the rate of progress in the development of newer, more efficient technologies.
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