Functional genomics in nephrology: construction and application of bioinformatics

Abstract

An expression profile is a list of expressed genes determined by a direct sequencing of thousands of clones randomly selected from nonbiased and unamplified cDNA libraries. The data depict their relative abundance in analyzed tissues or cells. We constructed the expression profiles of mouse proximal tubules and inner medullary collecting ducts. First, approximately 18 cm and 20 cm of mouse proximal tubules and inner medullary collecting duct, respectively, were collected by microdissection methods, and cDNA libraries were prepared. Second, 1000 to 2000 clones were randomly selected and sequenced, confirming that 646 and 1613 types of transcripts existed in each nephron segment respectively. The profiles revealed that the most abundant gene was kidney androgen-regulated gene (Accession number M22810) for proximal tubule and α-B crystallin (Accession number M63170) for inner medullary collecting duct. The computer-based subtraction was performed using the expression profiles of nephron segments with those of other tissues. It illuminated several putative nephron-specific genes. Northern analyses and in situ hybridization demonstrated that abundant genes appearing more than three times in the profile were predominantly expressed in kidney nephron segments. Recently, the possible roles of proximal tubules in the progression of kidney diseases, especially the adverse effects of proteinuria, have been proposed. To evaluate the hypothesis, proximal tubules were collected from a protein-overloaded proteinuria model and analyzed. The disease profile of model mouse proximal tubule constructed by sequencing approximately 3000 clones was compared with those of normal tubules. The results revealed that proteinuria for one week caused dramatic changes of gene expression in proximal tubules. The results were confirmed by laser-based microdissection along with a reverse transcription-polymerase chain reaction method that allowed us to isolate proxi-mal tubules from histological specimens and to quantify mRNA expression. The expression profiles provided useful bioinformatics concerning kidney diseases, hopefully leading to future applications including development of new therapies, better prognosis, and additional information for diagnosis.