%0 Journal Article
%T Deep analysis of cellular transcriptomes ¨C LongSAGE versus classic MPSS
%A Lawrence Hene
%A Vattipally B Sreenu
%A Mai T Vuong
%A S Hussain I Abidi
%A Julian K Sutton
%A Sarah L Rowland-Jones
%A Simon J Davis
%A Edward J Evans
%J BMC Genomics
%D 2007
%I BioMed Central
%R 10.1186/1471-2164-8-333
%X We used a single LongSAGE library of 503,431 tags and a "classic" MPSS library of 1,744,173 tags, both prepared from the same T cell-derived RNA sample, to compare the ability of each method to probe, at considerable depth, a human cellular transcriptome. We show that even though LongSAGE is more error-prone than MPSS, our LongSAGE library nevertheless generated 6.3-fold more genome-matching (and therefore likely error-free) tags than the MPSS library. An analysis of a set of 8,132 known genes detectable by both methods, and for which there is no ambiguity about tag matching, shows that MPSS detects only half (54%) the number of transcripts identified by SAGE (3,617 versus 1,955). Analysis of two additional MPSS libraries shows that each library samples a different subset of transcripts, and that in combination the three MPSS libraries (4,274,992 tags in total) still only detect 73% of the genes identified in our test set using SAGE. The fraction of transcripts detected by MPSS is likely to be even lower for uncharacterized transcripts, which tend to be more weakly expressed. The source of the loss of complexity in MPSS libraries compared to SAGE is unclear, but its effects become more severe with each sequencing cycle (i.e. as MPSS tag length increases).We show that MPSS libraries are significantly less complex than much smaller SAGE libraries, revealing a serious bias in the generation of MPSS data unlikely to have been circumvented by later technological improvements. Our results emphasize the need for the rigorous testing of new expression profiling technologies.In recent years, a number of techniques have emerged for large-scale gene expression analysis. Most are designed to compare the expression of many genes between cell types or under a number of different conditions. However, there has also been interest in techniques capable of identifying the complete transcriptome of a given cell or tissue. 'Closed' architecture systems, such as microarrays, are less su
%U http://www.biomedcentral.com/1471-2164/8/333