ISOLATION AND CHARACTERIZATION OF HUMAN GENES AFFECTING CHROMOSOME METABOLISM

工作概述：人类基因组计划正处于起步阶段

Summary of Work: The Human Genome Project is progressing from the early stages of high throughput large scale sequencing to one of functional genomics, i.e. elucidation of both biochemical structure and function of proteins encoded by identified human transcripts. To date, functional genomics has primarily depended on low throughput approaches such as reverse genetics, complementation analysis and gene isolation via PCR utilizing degenerate oligos. In addition to these approaches, large- scale sequencing of many diverse genomes has led to the emergence of comparative genomics whereby gene function is deduced in silico. As an alternative to these approaches, we developed a new approach, termed phenotype disruption, which allows us to quickly functionally identify human genes that may have a role in DNA and chromosome metabolism and genome stability. The phenotype disruption approach relies upon assessing the phenotypic impact that over-expressed human cDNAs have in genetically sensitized microbial mutants as they relate to specific genetic endpoints. We proposed that an established genetic interaction between an over-expressed human cDNA and a specific microbial mutant can lend insight to the human protein function in their normal human cell milieu. Specifically, we have screened for and isolated both well- characterized and unknown human genes that specifically prevent the growth of a yeast polymerase d as well as genes that induce the E.coli SOS response. While both of the phenotype disruption assays facilitate the rapid isolation of factors involved in genome stability, these systems also provide the opportunity for additional molecular characterization of the isolated genes. In related work we have shown that human RAD51 elicits increased radiation sensitivity and a growth defect in a checkpoint mutant the DNA polymerase mutant. This will form the basis for investigation of interactions with other human factors including hBRCA1 and hp53. Altogether, our approach has provided a valuable tool for functional genomic analysis.