Robust-LongSAGE (RL-SAGE): A Substantially Improved LongSAGE Method for Gene Discovery and Transcriptome Analysis
Open Access
- 1 March 2004
- journal article
- research article
- Published by Oxford University Press (OUP) in Plant Physiology
- Vol. 134 (3), 890-897
- https://doi.org/10.1104/pp.103.034496
Abstract
Serial analysis of gene expression (SAGE) is a widely used technique for large-scale transcriptome analysis in mammalian systems. Recently, a modified version called LongSAGE (S. Saha, A.B. Sparks, C. Rago, V. Akmaev, C.J. Wang, B. Vogelstein, K.W. Kinzler [2002] Nat Biotechnol 20: 508-512) was reported by increasing tag length up to 21 bp. Although the procedures for these two methods are similar, a detailed protocol for LongSAGE library construction has not been reported yet, and several technical difficulties associated with concatemer cloning and purification have not been solved. In this study, we report a substantially improved LongSAGE method called Robust-LongSAGE, which has four major improvements when compared with the previously reported protocols. First, a small amount of mRNA (50 ng) was enough for a library construction. Second, enhancement of cDNA adapter and ditag formation was achieved through an extended ligation period (overnight). Third, only 20 ditag polymerase chain reactions were needed to obtain a complete library (up to 90% reduction compared with the original protocols). Fourth, concatemers were partially digested with NlaIII before cloning into vector (pZEro-1), greatly improving cloning efficiency. The significant contribution of Robust-LongSAGE is that it solved the major technical difficulties, such as low cloning efficiency and small insert sizes associated with existing SAGE and LongSAGE protocols. Using this protocol, one can generate two to three libraries, each containing over 4.5 million tags, within a month. We recently have constructed five libraries from rice (Oryza sativa), one from maize (Zea mays), and one from the rice blast fungus (Magnaporthe grisea).Keywords
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