Functional genomics in nephrology

Masaru Takenaka and Enyu Imai

Division of Nephrology, Department of Internal Medicine and Therapeutics, Osaka University Graduate School of Medicine, Osaka, Japan

Correspondence and offprint requests to: Enyu Imai MD, Department of Internal Medicine and Therapeutics, Osaka University Graduate School of Medicine (A8), 2–2 Yamadaoka, Suita, Osaka, 565-0871 Japan.

Introduction

We are facing a new era in molecular biology. The complete DNA sequences of the genomes of many organisms have been analysed. The Human Genome Project is scheduled to finish prior to 2003. Now it is announced that approximately 90% of the data will be made accessible to the public in the coming year. This means that cloning of genes or characterization of the genomic structures will no longer be main issues in the near future. Expanding DNA databases such as GenBank are accumulating more than 3 million sequence records. Most of the data has come from EST (expressed sequence tag) projects collecting sequences directly from whole cDNA libraries that started in 1990s [1,2]. More than 1.2 million entries for human ESTs and over four hundred thousand mouse ESTs are recorded in dbEST (release 021999), and 80% of human coding sequences are in databases. The data can provide new powerful tools; for example, application to RNA expression analysis, hunting for candidate disease genes or characterization of tissue-specific genes. Combination with computer analyses and gene technology manipulating large-scale sequences will potentially allow the exploration of all genes and the deduced proteins in a systematic fashion based on the information of whole genome sequences [3,4].

`Functional genomics' to understand how differential genes work

The results of genome projects, including Homo sapiens, will impact on basic research as well as clinical practice much more than hitherto. The genome is the fundamental blueprint of the cell function. The comprehensive knowledge of the whole genome sequence will make feasible the analyses of the expression of all genes in response to various physiological or pathological conditions. A concept of `functional genomics' has come true. As Hieter and Boguski [3] have said, `... it refers to the development and application of global (genome-wide or system-wide) experimental approaches to assess gene function by making use of the information and reagents provided by structural genomics'. In mammals, the genome is thought to encode about a hundred thousand genes. Analyses of the whole gene expression cannot be achieved by the methods that we had in the past. Recent DNA technology, such as microarrays, DNA chips, or direct large-scale sequencing of cDNA [58] allows the handling of 10–100 thousand genes simultaneously. Microarray, one of the promising methods, could enable the imaging of large-scale (over thousands) northern blot or dot-blot analyses. Thousands of cDNAs or synthetic oligonucleotides are fixed on small membranes, silica wafers, or glass slides in high density, for hybridization to either fluorescent or radiolabelled probes. The changes of gene activity can be detected by the intensity of hybridization signals.

A shortcoming of the microarray is the relatively large amount of RNA required, especially for preparing fluorescent probes [9]. Because special and expensive hardware such as the robotic printing of a large number of templates, scanning devices, and image processing tools [10,11] is required to prepare microarrays, it has been difficult for many researchers to apply this technique in their own laboratories. It is becoming easier to access these techniques because several kinds of array are now available commercially [12]. When using microarray to compare the expression of genes between several conditions, a considerable numbers of genes would show up as potential targets for analyses [13,14]. The dynamic alteration of the clustering genes in concert would provide clues to understanding the dynamics of cellular function that cannot be obtained by investigation of a single gene. It should be borne in mind that many of the sequences in microarray came from EST clusters of which most of the functions were unknown, leading researchers to perform the additional intensive experiments to characterize several target genes.

Functional genomics in nephrology

A human kidney consists of approximately one million nephrons, which are functionally and morphologically divided into several segments [15]. The genes expressed in each nephron segment of the normal kidney have not yet been fully identified, although the number of entries collecting data from whole kidney in dbEST has been increasing (http://www.ncbi.nlm.nih.gov/). In this context, we isolated about 18 cm of mouse renal proximal tubules or 20 cm of inner medullary collecting ducts by a microdissection method, respectively, and constructed the gene expression profiles by direct-sequencing procedure [8,16]. Over 2200 kinds of independent transcripts termed gene signatures (GS) in the kidney were identified [17,18]. By comparing the data with those of other tissues and cells, several genes, expressed preferentially in distinct nephron segments of the kidney, were characterized [17,18]. Among them, a new member of proximal tubule specific aspartic proteinase and GS4059 were localized in proximal tubules by in situ hybridization method [18]. GS4059 shows significant similarity to rat HP33 that has been recently cloned and reported to be localized at the centrosome in a microtubule-dependent manner [19]. In addition, the profiles showed that the most abundant genes in mouse proximal tubules and inner medullary collecting ducts were `kidney androgen-regulated protein' [20,21] and `{alpha}B-crystallin' [22] respectively. Our databases will provide the basis of gene expression in the normal kidney and could be applied to prepare kidney specific or nephron segment specific microarrays in the future.

The information concerning large-scale gene expression could be used not only to understand genes that may play important roles for renal functions, but also to identify genes related to the initial insult or the progression of renal diseases. New methods described above will be useful to monitor differential patterns of expression of thousands of genes under normal conditions in various renal diseases, or in various developmental stages. When those techniques are used to analyse experimental models of pure-bred animals such as a mouse strain, genes would be organized to their possible functions and expression patterns without considering genetic diversity found in the human. Accumulation of the gene expression profiling data in various pathological conditions may illuminate the key transcripts for the diseases. Because most mouse genes are considered to have their human counterparts, it may be easy to apply the results obtained from experimental models to human diseases. The central issues in nephrology are the mechanisms of progression of kidney diseases that remain to be resolved. If there were unique transcripts or even clusters of gene expression related to the kidney disease, the information might be utilized to understand the mechanisms of human kidney diseases, to design new drugs, to assess the possibility of genetic disorders, and to predict the prognosis for each case. It may help to provide the most suitable treatments for the patients. The therapeutic strategies could be worked out in a custom-made manner at a molecular level. To achieve these goals, more comprehensive information should be collected systematically, e.g. the construction of array-database [23] relating to renal diseases.

Conclusions

The progress of genome projects and the rapid expansion of databases for mRNA expression will open a new field of research along with the introduction of new technologies that allow the analysis of large-scale gene expressions. We may see a new comprehension of cells by analysis of dynamic changes of clusters of genes, which may not necessarily be recognized by the observation of change of a single gene expression. In this context, a paradigm shift from `structural analysis' to `functional genomics' might occur in the field of nephrology. In consequence, it could provide new insights into renal physiology and pathology.

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