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MMP1 bimodal expression and differential response to inflammatory mediators is linked to promoter polymorphisms.

Affara M, Dunmore BJ, Sanders DA, Johnson N, Print CG, Charnock-Jones DS - BMC Genomics (2011)

Bottom Line: Identifying the functional importance of the millions of single nucleotide polymorphisms (SNPs) in the human genome is a difficult challenge.In this study, we used a novel but straightforward method based on agglomerative hierarchical clustering to identify bimodally expressed transcripts in human umbilical vein endothelial cell (HUVEC) microarray data from 15 individuals.We describe a simple method to identify putative bimodally expressed RNAs from transcriptome data that is effective yet easy for non-statisticians to understand and use.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Pathology, University of Cambridge, Tennis Court Road, Cambridge, CB2 1QP, UK.

ABSTRACT

Background: Identifying the functional importance of the millions of single nucleotide polymorphisms (SNPs) in the human genome is a difficult challenge. Therefore, a reverse strategy, which identifies functionally important SNPs by virtue of the bimodal abundance across the human population of the SNP-related mRNAs will be useful. Those mRNA transcripts that are expressed at two distinct abundances in proportion to SNP allele frequency may warrant further study. Matrix metalloproteinase 1 (MMP1) is important in both normal development and in numerous pathologies. Although much research has been conducted to investigate the expression of MMP1 in many different cell types and conditions, the regulation of its expression is still not fully understood.

Results: In this study, we used a novel but straightforward method based on agglomerative hierarchical clustering to identify bimodally expressed transcripts in human umbilical vein endothelial cell (HUVEC) microarray data from 15 individuals. We found that MMP1 mRNA abundance was bimodally distributed in un-treated HUVECs and showed a bimodal response to inflammatory mediator treatment. RT-PCR and MMP1 activity assays confirmed the bimodal regulation and DNA sequencing of 69 individuals identified an MMP1 gene promoter polymorphism that segregated precisely with the MMP1 bimodal expression. Chromatin immunoprecipitation (ChIP) experiments indicated that the transcription factors (TFs) ETS1, ETS2 and GATA3, bind to the MMP1 promoter in the region of this polymorphism and may contribute to the bimodal expression.

Conclusions: We describe a simple method to identify putative bimodally expressed RNAs from transcriptome data that is effective yet easy for non-statisticians to understand and use. This method identified bimodal endothelial cell expression of MMP1, which appears to be biologically significant with implications for inflammatory disease. (271 Words).

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Dendrograms and histograms for MMP1 in untreated and IM treated HUVECS. Dendrograms of MMP1 RNA expressions are shown for the un-treated (A) and IM-treated (C) HUVECs. Histograms showing the frequency (y-axis) of maximum branch height (x-axis) across 10,000 simulated MMP1 transcript datasets, each with parameters similar to the estimated parameters of the population from which the actual MMP1 data set was drawn, are shown (B and D). Green arrows indicate the maximum branch height from cluster analysis of the actual data sets. In both un-treated and IM-treated HUVECs, the maximum clustering branch height for MMP1 exceeded the maximum clustering branch height identified in 90% of the simulated data sets.
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Figure 4: Dendrograms and histograms for MMP1 in untreated and IM treated HUVECS. Dendrograms of MMP1 RNA expressions are shown for the un-treated (A) and IM-treated (C) HUVECs. Histograms showing the frequency (y-axis) of maximum branch height (x-axis) across 10,000 simulated MMP1 transcript datasets, each with parameters similar to the estimated parameters of the population from which the actual MMP1 data set was drawn, are shown (B and D). Green arrows indicate the maximum branch height from cluster analysis of the actual data sets. In both un-treated and IM-treated HUVECs, the maximum clustering branch height for MMP1 exceeded the maximum clustering branch height identified in 90% of the simulated data sets.

Mentions: MMP1 was of particular interest since it encodes a biologically and clinically important enzyme, and since analysis of the rSNPs database identified several common SNPs in the MMP1 gene promoter within 2,000 bp upstream of the start of transcription (data not shown). Dendrograms for MMP1 in un-treated and IM-treated HUVECs, along with histograms of the maximum cluster branch height in each of 10,000 parametric bootstrap data sets (to estimate the probability of transcripts appearing to be bimodally expressed due to chance alone) are shown in Figure 4. Quantitative RT-PCR from 29 additional individuals confirmed in this new group of individuals a bimodal expression pattern for MMP1. We identified two distinct populations; (i) HUVECs isolated from 7 of the 29 individuals had low MMP1 mRNA abundance (Figure 5a), however in 6 of these 7 individuals, MMP1 mRNA abundance was significantly increased by culture in IM conditions (Figure 5b). (ii) The remaining 22 individuals had relatively higher MMP1 mRNA abundance regardless of UT or IM culture conditions (Figure 5a). In the high MMP1 expressing HUVECs isolated from these 22 individuals, the abundance of MMP1 mRNA was either not significantly affected or was decreased by IM culture conditions (Figure 5b). This differential response to inflammatory mediator treatment was striking and we sought to understand the underlying mechanisms.


MMP1 bimodal expression and differential response to inflammatory mediators is linked to promoter polymorphisms.

Affara M, Dunmore BJ, Sanders DA, Johnson N, Print CG, Charnock-Jones DS - BMC Genomics (2011)

Dendrograms and histograms for MMP1 in untreated and IM treated HUVECS. Dendrograms of MMP1 RNA expressions are shown for the un-treated (A) and IM-treated (C) HUVECs. Histograms showing the frequency (y-axis) of maximum branch height (x-axis) across 10,000 simulated MMP1 transcript datasets, each with parameters similar to the estimated parameters of the population from which the actual MMP1 data set was drawn, are shown (B and D). Green arrows indicate the maximum branch height from cluster analysis of the actual data sets. In both un-treated and IM-treated HUVECs, the maximum clustering branch height for MMP1 exceeded the maximum clustering branch height identified in 90% of the simulated data sets.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3040839&req=5

Figure 4: Dendrograms and histograms for MMP1 in untreated and IM treated HUVECS. Dendrograms of MMP1 RNA expressions are shown for the un-treated (A) and IM-treated (C) HUVECs. Histograms showing the frequency (y-axis) of maximum branch height (x-axis) across 10,000 simulated MMP1 transcript datasets, each with parameters similar to the estimated parameters of the population from which the actual MMP1 data set was drawn, are shown (B and D). Green arrows indicate the maximum branch height from cluster analysis of the actual data sets. In both un-treated and IM-treated HUVECs, the maximum clustering branch height for MMP1 exceeded the maximum clustering branch height identified in 90% of the simulated data sets.
Mentions: MMP1 was of particular interest since it encodes a biologically and clinically important enzyme, and since analysis of the rSNPs database identified several common SNPs in the MMP1 gene promoter within 2,000 bp upstream of the start of transcription (data not shown). Dendrograms for MMP1 in un-treated and IM-treated HUVECs, along with histograms of the maximum cluster branch height in each of 10,000 parametric bootstrap data sets (to estimate the probability of transcripts appearing to be bimodally expressed due to chance alone) are shown in Figure 4. Quantitative RT-PCR from 29 additional individuals confirmed in this new group of individuals a bimodal expression pattern for MMP1. We identified two distinct populations; (i) HUVECs isolated from 7 of the 29 individuals had low MMP1 mRNA abundance (Figure 5a), however in 6 of these 7 individuals, MMP1 mRNA abundance was significantly increased by culture in IM conditions (Figure 5b). (ii) The remaining 22 individuals had relatively higher MMP1 mRNA abundance regardless of UT or IM culture conditions (Figure 5a). In the high MMP1 expressing HUVECs isolated from these 22 individuals, the abundance of MMP1 mRNA was either not significantly affected or was decreased by IM culture conditions (Figure 5b). This differential response to inflammatory mediator treatment was striking and we sought to understand the underlying mechanisms.

Bottom Line: Identifying the functional importance of the millions of single nucleotide polymorphisms (SNPs) in the human genome is a difficult challenge.In this study, we used a novel but straightforward method based on agglomerative hierarchical clustering to identify bimodally expressed transcripts in human umbilical vein endothelial cell (HUVEC) microarray data from 15 individuals.We describe a simple method to identify putative bimodally expressed RNAs from transcriptome data that is effective yet easy for non-statisticians to understand and use.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Pathology, University of Cambridge, Tennis Court Road, Cambridge, CB2 1QP, UK.

ABSTRACT

Background: Identifying the functional importance of the millions of single nucleotide polymorphisms (SNPs) in the human genome is a difficult challenge. Therefore, a reverse strategy, which identifies functionally important SNPs by virtue of the bimodal abundance across the human population of the SNP-related mRNAs will be useful. Those mRNA transcripts that are expressed at two distinct abundances in proportion to SNP allele frequency may warrant further study. Matrix metalloproteinase 1 (MMP1) is important in both normal development and in numerous pathologies. Although much research has been conducted to investigate the expression of MMP1 in many different cell types and conditions, the regulation of its expression is still not fully understood.

Results: In this study, we used a novel but straightforward method based on agglomerative hierarchical clustering to identify bimodally expressed transcripts in human umbilical vein endothelial cell (HUVEC) microarray data from 15 individuals. We found that MMP1 mRNA abundance was bimodally distributed in un-treated HUVECs and showed a bimodal response to inflammatory mediator treatment. RT-PCR and MMP1 activity assays confirmed the bimodal regulation and DNA sequencing of 69 individuals identified an MMP1 gene promoter polymorphism that segregated precisely with the MMP1 bimodal expression. Chromatin immunoprecipitation (ChIP) experiments indicated that the transcription factors (TFs) ETS1, ETS2 and GATA3, bind to the MMP1 promoter in the region of this polymorphism and may contribute to the bimodal expression.

Conclusions: We describe a simple method to identify putative bimodally expressed RNAs from transcriptome data that is effective yet easy for non-statisticians to understand and use. This method identified bimodal endothelial cell expression of MMP1, which appears to be biologically significant with implications for inflammatory disease. (271 Words).

Show MeSH
Related in: MedlinePlus