H3K4me3 at the four <i>Hox</i> loci is menin-dependent in PILECs

<p>UCSC genome browser images of H3K4me3 profiles (top four tracks) at the four <i>Hox</i> loci in wild-type (WT) and menin-null (KO) mESCs and PILECs. The bottom four tracks show profiles for control Input DNA. Rectangular box highlights the regions showing differential H3K4me3 in WT and KO PILECs. Genes within the four <i>Hox</i> loci and their orientation are marked using arrows at the bottom.</p

<i>In vitro</i> differentiation of mESCs into pancreatic islet-like endocrine cells (PILECs).

<p>(A) Phase contrast images of wild-type (WT) mESCs and menin-null (KO) mESCs differentiated into PILECs. (B) RT-PCR analysis measuring mRNA levels of genes expressed in islet cells using RNA from mESCs and mESC-derived PILECs. WT: wild-type cells; KO: <i>Men1</i>-ko cells (menin-null). RNA from the mouse insulinoma cell line MIN6 was used as a positive control. Gapdh served as an internal control for RT-PCR using a 1∶10 dilution of the oligo-dT primed first strand cDNA template. (C) Western blot analysis of whole cell protein extracts from wt or menin-null mESCs before and after differentiation into PILECs with antibodies against menin, an ESC pluripotency marker Oct3/4, and an islet differentiation marker NeuroD1. Tubulin served as protein loading control. (D) <i>In vitro</i> differentiation of pancreatic precursor cells (step-3) derived from mESCs into PILECS was performed in gelatinized chamber slides and processed for immunofluorescence (red) staining with a pro-insulin C-peptide mouse monoclonal antibody to detect insulin. MIN6 cells cultured in chamber slides were used as a positive control.</p

Proposed model for menin-dependent H3K4me3-mediated regulation of gene expression.

<p>(A) Left and right panels show gene expression status of genes regulated by menin-dependent H3K4me3 as the wild-type and menin-null embryonic stem cells (ESCs), respectively, differentiate into pancreatic islet-like endocrine cells. H3K4me3 marks along the chromatin is shown using filled green circles. Transcription start sites of <i>Meg3</i> and <i>Hox</i> genes are marked using a green (expressed) or a red (silent) arrow. Menin positively regulates Meg3 expression in ESCs, but not in islet cells. The loss of menin results in the loss of Meg3 expression in ESCs, but not in islet cells. In contrast, menin positively regulates the expression of Hox genes in islet cells, but not in ESCs. <i>Hox</i> genes are silenced in menin-null islet. (B) The gene expression status of <i>MEG3</i> and <i>HOX</i> genes in MEN1-like tumors types (left), parathyroid tumors (middle), and pituitary tumors (right) as previously reported <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037952#pone.0037952-Cheunsuchon1" target="_blank">[16]</a>, .</p

Decrease in gene expression accompanies decrease in H3K4me3 in menin-null PILECs but not in menin-null mESCs.

<p>Correlation between changes in gene expression and changes in H3K4me3 in menin-null (KO) mESCs vs. wild-type (WT) mESCs (A), and menin-null PILECs vs. wild-type (WT) PILECs (B). Normalized average tag density surrounding the transcription start site (TSS) is shown for genes that were at least 2-fold downregulated/upregulated in menin-null cells compared to WT cells.</p

Menin-dependent regulation of <i>Hox</i> genes in PILECs.

<p>(A) Expression fold changes of genes that showed at least 4-fold change (p-value <0.005) in menin-null (KO) PILECs vs wild-type (WT) PILECs in microarray analysis. (B) RT-PCR analysis measuring mRNA levels of 39 <i>Hox</i> genes from the 4 <i>Hox</i> clusters (<i>HoxA</i>, <i>HoxB</i>, <i>HoxC</i> and <i>HoxD</i>) using RNA from wild-type (WT) or menin-null (KO) mESC-derived PILECs. Gapdh served as an internal control for RT-PCR using a 1∶10 dilution of the oligo-dT primed first strand cDNA template. Blank boxes represent <i>Hox</i> genes whose expression was undetectable in the WT or KO cells.</p

H3K4me3 at the <i>Meg3</i> promoter is menin-dependent in mESCs, but not in PILECs.

<p>(A) UCSC genome browser images of H3K4me3 profiles (top four tracks) at <i>Meg3</i> (left) and <i>Mest</i> (right) loci in wild-type (WT) and menin-null (KO) mESCs and PILECs. The bottom four tracks show profiles for control Input DNA. Rectangular box highlights the promoter regions of <i>Meg3</i> and <i>Mest</i>. Genes within the two loci and their orientation are marked using arrows at the bottom. (B) Schematic (left) showing the <i>Meg3</i> promoter region and the location of the ChIP-PCR primers and product length. Transcriptional start site is marked with the forward arrow. Results from ChIP-PCR analysis (right) from control input DNA, and DNA from ChIPs with antibodies against H3K4me3, menin, and normal rabbit IgG.</p

Relationship between pathaway similarity score, measured as the Jaccard coefficient between the proteins' KEGG pathway memberships, and profile similarity score (using reference set BAE3a), measured as the mutual information score of proteins' profiles

<p><b>Copyright information:</b></p><p>Taken from "Discovering functional linkages and uncharacterized cellular pathways using phylogenetic profile comparisons: a comprehensive assessment"</p><p>http://www.biomedcentral.com/1471-2105/8/173</p><p>BMC Bioinformatics 2007;8():173-173.</p><p>Published online 23 May 2007</p><p>PMCID:PMC1904249.</p><p></p> Each data point in the plot represents a pair of proteins. (a) 708, 645 pairs of proteins, out of which 664,677 had zero pathway similarity score. A weak positive correlation (R = 0.14) is found to exist between the pathway similarity score and the mutual information score. Rather than computing the correlation of all data points, Data and Marcotte computed the correlation of "representative" data points, each of which represents the average values for 1000 data points. This results in an artificial increase in the correlation (R = 0.89, inset). (b) 635 628 pairs of yeast proteins, out of which 599,954 had zero pathway similarity score. A weak positive correlation is observed (R = 0.16) between the pathway and profile similarity measures. An artificial increase in the correlation is observed (R = 0.65, inset) when Date and Marcotte's correlation computation strategy is employed

Sensitivity versus specificity plots for protein pairs in various yeast pathways based on the 2nd level of KEGG orthology

<p><b>Copyright information:</b></p><p>Taken from "Discovering functional linkages and uncharacterized cellular pathways using phylogenetic profile comparisons: a comprehensive assessment"</p><p>http://www.biomedcentral.com/1471-2105/8/173</p><p>BMC Bioinformatics 2007;8():173-173.</p><p>Published online 23 May 2007</p><p>PMCID:PMC1904249.</p><p></p> Performances were measured at different mutual information thresholds. (a) Carbohydrate metabolism. (b) Energy metabolism (c) Lipid metabolism (d) Nucleotide metabolism (e) Amino acid metabolism (f) Metabolism of cofactors and vitamins (g) Translation (h) Folding, sorting, and degradation

Sensitivity versus specificity plots for protein pairs in various pathways based on the 2nd level of KEGG orthology

<p><b>Copyright information:</b></p><p>Taken from "Discovering functional linkages and uncharacterized cellular pathways using phylogenetic profile comparisons: a comprehensive assessment"</p><p>http://www.biomedcentral.com/1471-2105/8/173</p><p>BMC Bioinformatics 2007;8():173-173.</p><p>Published online 23 May 2007</p><p>PMCID:PMC1904249.</p><p></p> Performances were measured at different mutual information thresholds. (a) Carbohydrate metabolism. (b) Energy metabolism (c) Lipid metabolism (d) Nucleotide metabolism (e) Amino acid metabolism (f) Metabolism of cofactors and vitamins (g) Translation (d) Membrane transport

Results from the -tests measuring the statistical significance of the difference in the means of the distributions of mutual information scores of random protein pairs and protein pairs with pathway similarity ≥ 50%

<p><b>Copyright information:</b></p><p>Taken from "Discovering functional linkages and uncharacterized cellular pathways using phylogenetic profile comparisons: a comprehensive assessment"</p><p>http://www.biomedcentral.com/1471-2105/8/173</p><p>BMC Bioinformatics 2007;8():173-173.</p><p>Published online 23 May 2007</p><p>PMCID:PMC1904249.</p><p></p> The t-scores for all 16 reference sets of genomes are statistically significant for both the and the yeast proteins