Editorial [Hot Topic:Serial Analysis of Gene Expression (SAGE) (Guest Editor: Sergey V. Anisimov)]

A technique termed Serial Analysis of Gene Expression (SAGE) has emerged in 1995 and promised becoming a sort of a ‘golden bullet’ in the list of gene expression profiling methods available at the moment. Most importantly, it appeared being truly high-throughput technique, allowing gene expression profiling reaching nearly genomic scale: a success then achieved only by multi-site EST sequencing projects. More convenient than any alternative technique (including EST sequencing), SAGE was greeted with much enthusiasm and a number of tag libraries constructed and analyzed have started growing rapidly. Though challenging technically, initial SAGE protocol has been applied with success in many studies of different nature, yielding accurate large-scale gene expression profiles of numerous samples derived from various cells and tissues. Furthermore, SAGE has soon become a platform of many adaptations aiming decreasing the required amount of starting material, improving tag yield and cloning efficiency, overcoming certain sources of potential bias and finally increasing the length of the yielded tags. The latter feature has been essential to allow effective identification of tagged genes, as well as rapid cloning of gene targets. To the success of SAGE, a progress of the ongoing genome sequencing projects has contributed. Advances in sequencing technology allowed both a higher number of tags sequenced within each project's budget, and increasingly higher number of tags matching known (sequenced) genes. Additionally, a number of bioinformatics-based approaches aimed improving the reliability of SAGE data. A convenience of SAGE applications was further supplemented with the appearance of public databases serving as SAGE library depositaries (Gene Expression Omnibus (GEO; NCBI), to name the most important) and gene annotation tools (including both SAGE software and SAGEmap resource (NCBI)). It should be noted that SAGE technique has emerged in the very beginning of DNA microarray era and only by year 2002-2003 did DNA microarray technology match SAGE in terms of the throughput. Importantly, notwithstanding an astonishing progress of microarray technology, it is generally believed that SAGE still possesses certain advantages over the former - thus allowing a researcher to choose a suitable platform for each experiment. This Special Issue aims to review the evolution of SAGE and related techniques, covering such features as adapting SAGE to the requirements of mini- and micro- samples, generation of longer tags and finally bioinformatics means of SAGE data analysis. It also covers SAGE application in hematological, diabetes and cancer research, providing a fine cross-section of the abilities of this important technique. There is no doubt that in its modified form SAGE will remain in the arsenal of highthroughput gene expression profiling methods for many decades to come.