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Transcriptional profiling of Medicago truncatula meristematic root cells.

Holmes P, Goffard N, Weiller GF, Rolfe BG, Imin N - BMC Plant Biol. (2008)

Bottom Line: With bioinformatics tools developed to functionally annotate the Medicago genome array we could identify significant changes in metabolism, signalling and the differentially expression of 55 transcription factors in meristematic and non-meristematic roots.This is the first comprehensive analysis of M. truncatula root meristem cells using this genome array.This data will facilitate the mapping of regulatory and metabolic networks involved in the open root meristem of M. truncatula and provides candidates for functional analysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: ARC Centre of Excellence for Integrative Legume Research, Genomic Interactions Group, Research School of Biological Sciences, Australian National University, Canberra ACT 2601, Australia. peta.holmes@anu.edu.au

ABSTRACT

Background: The root apical meristem of crop and model legume Medicago truncatula is a significantly different stem cell system to that of the widely studied model plant species Arabidopsis thaliana. In this study we used the Affymetrix Medicago GeneChip(R) to compare the transcriptomes of meristem and non-meristematic root to identify root meristem specific candidate genes.

Results: Using mRNA from root meristem and non-meristem we were able to identify 324 and 363 transcripts differentially expressed from the two regions. With bioinformatics tools developed to functionally annotate the Medicago genome array we could identify significant changes in metabolism, signalling and the differentially expression of 55 transcription factors in meristematic and non-meristematic roots.

Conclusion: This is the first comprehensive analysis of M. truncatula root meristem cells using this genome array. This data will facilitate the mapping of regulatory and metabolic networks involved in the open root meristem of M. truncatula and provides candidates for functional analysis.

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Classification of expression changes with GeneBins. GeneBins classification of probe sets with changes in expression that are significant at 2.0 fold.
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Figure 2: Classification of expression changes with GeneBins. GeneBins classification of probe sets with changes in expression that are significant at 2.0 fold.

Mentions: To interpret gene expression results, we used GeneBins to assign a relationship the genes differentially expressed transcripts on the Medicago genome array to a hierarchical functional classification modelled on KEGG ontology [26,27]. This analysis showed that the metabolism of the root meristem and non-meristem varies significantly between the two sections, see Figure 2. About 28% percent of differentially expressed probe sets could be assigned a functional classification with GeneBins; of note 7% and 3.3% of transcripts differentially expressed are involved in carbohydrate metabolism and the biosynthesis of secondary metabolites respectively. 25.5% of differentially expressed transcripts have no homolog, however by far the largest class of probe sets that had significantly altered expression in our analysis were unclassified with a homolog. This result led us to use other bioinformatics strategies to annotate the probe sets on the genome array.


Transcriptional profiling of Medicago truncatula meristematic root cells.

Holmes P, Goffard N, Weiller GF, Rolfe BG, Imin N - BMC Plant Biol. (2008)

Classification of expression changes with GeneBins. GeneBins classification of probe sets with changes in expression that are significant at 2.0 fold.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2277415&req=5

Figure 2: Classification of expression changes with GeneBins. GeneBins classification of probe sets with changes in expression that are significant at 2.0 fold.
Mentions: To interpret gene expression results, we used GeneBins to assign a relationship the genes differentially expressed transcripts on the Medicago genome array to a hierarchical functional classification modelled on KEGG ontology [26,27]. This analysis showed that the metabolism of the root meristem and non-meristem varies significantly between the two sections, see Figure 2. About 28% percent of differentially expressed probe sets could be assigned a functional classification with GeneBins; of note 7% and 3.3% of transcripts differentially expressed are involved in carbohydrate metabolism and the biosynthesis of secondary metabolites respectively. 25.5% of differentially expressed transcripts have no homolog, however by far the largest class of probe sets that had significantly altered expression in our analysis were unclassified with a homolog. This result led us to use other bioinformatics strategies to annotate the probe sets on the genome array.

Bottom Line: With bioinformatics tools developed to functionally annotate the Medicago genome array we could identify significant changes in metabolism, signalling and the differentially expression of 55 transcription factors in meristematic and non-meristematic roots.This is the first comprehensive analysis of M. truncatula root meristem cells using this genome array.This data will facilitate the mapping of regulatory and metabolic networks involved in the open root meristem of M. truncatula and provides candidates for functional analysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: ARC Centre of Excellence for Integrative Legume Research, Genomic Interactions Group, Research School of Biological Sciences, Australian National University, Canberra ACT 2601, Australia. peta.holmes@anu.edu.au

ABSTRACT

Background: The root apical meristem of crop and model legume Medicago truncatula is a significantly different stem cell system to that of the widely studied model plant species Arabidopsis thaliana. In this study we used the Affymetrix Medicago GeneChip(R) to compare the transcriptomes of meristem and non-meristematic root to identify root meristem specific candidate genes.

Results: Using mRNA from root meristem and non-meristem we were able to identify 324 and 363 transcripts differentially expressed from the two regions. With bioinformatics tools developed to functionally annotate the Medicago genome array we could identify significant changes in metabolism, signalling and the differentially expression of 55 transcription factors in meristematic and non-meristematic roots.

Conclusion: This is the first comprehensive analysis of M. truncatula root meristem cells using this genome array. This data will facilitate the mapping of regulatory and metabolic networks involved in the open root meristem of M. truncatula and provides candidates for functional analysis.

Show MeSH