PubMed · 11802438
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T Nakayama, S Yokoyama. 2001. [Structural genomics].. https://pubmed.ncbi.nlm.nih.gov/11802438/
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The ability to obtain experimental measurements for thousands of genes has revolutionized our view of biological systems. While traditional studies of gene function evaluated many different properties for a single gene, genomic approaches can measure a single property for thousands of genes. Over the last years, genomic approaches have been developed to measure many different properties, including gene expression, deletion phenotype, and protein characteristics. The promise of integrating these datasets has made it attractive to test whether genomic approaches can determine gene function with accuracy comparable to single gene approaches.
Making accurate functional predictions for genes is a key step in this era of high throughput gene and genome sequencing. While most functional prediction methods are comparative in nature, many do not take advantage of the power that an evolutionary perspective provides to any comparative biology analysis. Here we review how evolutionary analysis can greatly benefit both homology-based and non-homology-based functional prediction methods. Examples that are discussed include phylogenetic determination of orthology, the use of character state reconstruction analysis of gene function, and evolutionary analysis of rates and patterns of gene evolution.
Parkinson's disease was thought, until recently, to have little or no genetic component. This notion has changed with the identification of three genes, and the mapping of five others, that are linked to rare familial forms of the disease (FPD). The products of the identified genes, alpha-synuclein (PARK 1), parkin (PARK 2), and ubiquitin-C-hydrolase-L1 (PARK 5) are the subject of intense cell-biological and biochemical studies designed to elucidate the underlying mechanism of FPD pathogenesis. In addition, the complex genetics of idiopathic PD is beginning to be unraveled. Genetic information may prove to be useful in identifying new therapeutic targets and identifying the preclinical phase of PD, allowing treatment to begin sooner.