Large-scale statistical analysis of secondary xylem ESTs in pine

Large-scale statistical analysis of secondary xylem ESTs in pine A computational analysis of pine transcripts was conducted to contribute to the functional annotation of conifer sequences. A statistical analysis of expressed sequential tags(ESTs) belonging the 7732 contigs in the TIGR Pinus Gene Index (PGI1.0) identified 260 differentially represented gene sequences across six cDNA libraries from loblolly pine secondary xylem. Cluster analysis of this subset of contigs resulted in five groups representing genes preferentially represented in one of the xylem samples (compression wood, plannings, root xylem, latewood) and one group containing mostly genes simultaneously present in compression and side wood libraries. To complement the sequence annotation, 27 cDNA clones representing selected transcripts were completely sequenced. Several genes were identified that could represent putative markers for xylem from different organs, at different stages of development. Several sequences encoding regulatory proteins were over-represented in root xylem as opposed to the other xylem samples. Some of them belonged to known families of plant transcription factors, but two genes were previously uncharacterized in plants. One transcript was homologous to the gene encoding the Smad4 interacting factor, a key co-activator in TGFβ (transforming growth factor) signalling in animals. Thus, the digital analysis of pine ESTs highlighted a putative gene function of potentially broad interest but that has yet to be investigated in plants. More generally, this study showed that the application of numerical approaches to EST databases should be helpful in establishing priorities among genes to consider for targeted functional studies. Thus, we illustrated the potential of extracting information from conifer sequences already accessible through well-structured public databases. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Plant Molecular Biology Springer Journals

Large-scale statistical analysis of secondary xylem ESTs in pine

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Publisher
Springer Journals
Copyright
Copyright © 2005 by Springer
Subject
Life Sciences; Biochemistry, general; Plant Sciences; Plant Pathology
ISSN
0167-4412
eISSN
1573-5028
D.O.I.
10.1007/s11103-004-6969-7
Publisher site
See Article on Publisher Site

Abstract

A computational analysis of pine transcripts was conducted to contribute to the functional annotation of conifer sequences. A statistical analysis of expressed sequential tags(ESTs) belonging the 7732 contigs in the TIGR Pinus Gene Index (PGI1.0) identified 260 differentially represented gene sequences across six cDNA libraries from loblolly pine secondary xylem. Cluster analysis of this subset of contigs resulted in five groups representing genes preferentially represented in one of the xylem samples (compression wood, plannings, root xylem, latewood) and one group containing mostly genes simultaneously present in compression and side wood libraries. To complement the sequence annotation, 27 cDNA clones representing selected transcripts were completely sequenced. Several genes were identified that could represent putative markers for xylem from different organs, at different stages of development. Several sequences encoding regulatory proteins were over-represented in root xylem as opposed to the other xylem samples. Some of them belonged to known families of plant transcription factors, but two genes were previously uncharacterized in plants. One transcript was homologous to the gene encoding the Smad4 interacting factor, a key co-activator in TGFβ (transforming growth factor) signalling in animals. Thus, the digital analysis of pine ESTs highlighted a putative gene function of potentially broad interest but that has yet to be investigated in plants. More generally, this study showed that the application of numerical approaches to EST databases should be helpful in establishing priorities among genes to consider for targeted functional studies. Thus, we illustrated the potential of extracting information from conifer sequences already accessible through well-structured public databases.

Journal

Plant Molecular BiologySpringer Journals

Published: Nov 30, 2004

References

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