Gene Analysis

基因分析共享资源（GASR）为梅奥诊所癌症中心的研究人员提供了高效，

The Gene Analysis Shared Resource (GASR) provides Mayo Clinic Cancer Center researchers efficient, high-quality, cost-effective access to state-of-the-art genomics technologies for studying gene structure and function. Since 2003, the GASR components have been working in a coordinated fashion to provide technical expertise, instrumentation, and coordinated support for DMA sequencing, gene expression profiling, and genotyping. Support for gene expression regulation through RNAi analysis was added in 2007. The services provided by the facility include large-scale, full-service re-sequencing analysis using ABI 3730x1 sequencers, plus comprehensive genotyping and gene transcript analysis using Affymetrix Genechip¿ technology and Illumina BeadChips. Recent additions to our capabilities include Agilent array CGH and miRNA analysis as well as NextGen sequencing on an Illumina 1G Genome Analyzer Since the last competitive grant renewal, more than 130 Cancer Center members have used the services offered by the GASR and Cancer Center projects account for about two-thirds of all the activity in the GASR. The primary goals of the GASR are to bring cutting edge genomic technologies to Mayo researchers and to do so at an affordable price. This includes, but is not limited to: i. maintaining solid expertise in the use of well-defined commercial platforms for genomic analysis and translating this knowledge into high quality data for Cancer Center members, ii. continued exploration, validation, and implementation of new technologies which will advance the capabilities of the GASR to provide cutting edge genomic assays, iii. enhancement of the utility of archived and fresh clinical samples by developing methodologies which allow for the use of very small amounts of ribonucleic acid from formalin fixed, paraffin embedded (FFPE) and laser-captured microdissected tissues, iv. exploration of new technologies, such as "next generation sequencing," and miRNA profiling based on input from users of the GASR for continuous improvement. In addition, we will continue to work closely with bioinformatics and biostatistics to insure seamless interpretation of the data generated through GASR services.