Plant MPSS

NAR Molecular Biology Database Collection entry number 843
Nakano M.1, Nobuta K.1, Vemaraju K.2, Singh Tej S.2, Skogen J.W.2, and Meyers B.C.1,2
1Department of Plant and Soil Sciences and 2Delaware Biotechnology Institute, University of Delaware, Newark, Delaware 19714, USA

Database Description

MPSS (Massively Parallel Signature Sequencing) is a sequencing-based technology that uses a unique method to quantify gene expression level, generating millions of short sequence tags per library. The Plant MPSS databases are the largest publicly available set of tag-based gene expression data. These databases provide MPSS data with a user-friendly interface for four organisms (Arabidopsis, rice, grape, and Magnaporthe grisea, the rice blast fungus). These data include mRNA data and we’re currently expanding a set of small RNA data. The databases are built on a common set of web interfaces and are equipped with various graphical and analytical tools that allow the user to retrieve and analyze the data. The sequencing depth provides a quantitative assessment of transcript abundance (i.e. the expression level of the corresponding gene), while greatly increasing the likelihood of discovering novel transcripts. The website, equipped with various graphical and analytical tools, is available at


We are grateful to David Lee and Huizhuan Wu for their contributions to earlier versions of several of our MPSS databases. Our collaborators who contributed plant materials, RNA or MPSS libraries include Drs. Venu Reddyvari-Channa and Guo-liang Wang of the Ohio State University (rice and Magnaporthe materials), Drs. Cheng Lu and Pam Green of the University of Delaware (small RNA materials), and Dr. Alberto Iandolino of the University of California-Davis (grape materials). This work was supported primarily by awards from the NSF Plant Genome Program (#0321437) and USDA (2005-35604-15326).


1. Meyers, B.C., Lee, D.K., Vu, T.H., Tej, S.S., Edberg, S.B., Matvienko, M. and Tindell, L.D. (2004) Arabidopsis MPSS. An online resource for quantitative expression analysis. Plant Physiol., 135, 801-813.

Category: Plant databases

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