Serial Analysis of Gene Expression pdf epub mobi txt 电子书 下载 2025

This book facilitates the introduction of SAGE into the laboratory and provides a framework for interpreting and comparing data derived from SAGE experiments. SAGE studies encompass 50,000 tags and can provide detailed knowledge of the 2000 most highly expressed genes in the tissue sample. The SAGE protocols presented are detailed, fully annotated, and tested, and are all written by experienced SAGE researchers from around the world.

Serial Analysis of Gene Expression (SAGE): Digital Gene Expression Profiling facilitates the introduction of SAGE into the laboratory, and provides a framework for interpreting and comparing data derived from SAGE experiments. Of the several methods of genetic profiling available, only SAGE measures the expression of both known and unknown genes. SAGE studies encompass 50,000 tags and can provide detailed knowledge of the 2000 most highly expressed genes in the tissue sample. The SAGE protocols presented are detailed, fully annotated, and tested, and are all written by experienced SAGE researchers from around the world. Part 1 is dedicated to experimental procedures of SAGE and related methods including aRNA LongSAGE, SuperSAGE, DeepSAGE, and GMAT. Part 2 provides methods for extraction and filtration of tags, analysis of ditag populations, and completing statistically correct comparisons of gene expression profiles.

Comparative transcriptomics enables scientists to understand the underlying genetics of biological changes such as development, disease, crop yield, and resistance. SAGE analysis is also used to obtain unknown tags, which can be used as gene-specific primers in Rapid Amplification of cDNA Ends (RACE) reactions to generate full-length transcripts for cloning and sequencing. This book will be an indispensable tool for any lab engaged in genetic profiling and comparative transcriptomics, and will help many laboratories to successfully implement tag-based sequencing methods and procedures and obtain comprehensive, useful, and interpretative data.