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Items: 5

1.
Fig 3

Fig 3. From: A global analysis of the complex landscape of isoforms and regulatory networks of p63 in human cells and tissues.

Transcription Factors predicted to coordinate with ΔNp63 and TAp63 based on expression profiles (a) Heatmap depicts hierarchical clustering of fold change in expression (over median) of 867 TFs across 40 cell-types (54 experiments). Trimmed dendrogram (correlation > = 0.6) highlights the transcriptional regulators with similar expression pattern to (b) ΔNp63 and (c) TAp63, across a subset of cell-lines (depicted by yellow dotted rectangle). The specific p63 isoforms are shown in red

Isha Sethi, et al. BMC Genomics. 2015;16:584.
2.
Fig 2

Fig 2. From: A global analysis of the complex landscape of isoforms and regulatory networks of p63 in human cells and tissues.

Protein expression profiles of p63 isoforms. Western blot analysis of whole cell extracts demonstrates p63 expression using (a) a pan-p63 antibody (b) and an alpha specific antibody (H-129). TAp63 and ∆Np63 isoform specific expression is shown in panels (c) and (d) respectively. Blue and red arrows mark the TAp63 and ∆Np63 protein bands, respectively. Beta-tubulin serves as a loading control. se: short exposure and le:long exposure

Isha Sethi, et al. BMC Genomics. 2015;16:584.
3.
Fig 5

Fig 5. From: A global analysis of the complex landscape of isoforms and regulatory networks of p63 in human cells and tissues.

Predicted transcriptional co-regulators of ΔNp63 in human tissues and organs (a) Heatmap depicting transcript abundances of p63 across major human tissues and organs using CAGE-Seq and RNA-Seq (as obtained from the FANTOM database and the Human Protein Atlas). TPM: transcripts per million; FPKM: fragments per kilobase of transcript per million. (b) Hierarchical clustering of fold change in RNA-Seq expression (over median) of 867 TFs (rows) across 27 major tissues and organs, (c) Close-up shows a trimmed dendrogram (correlation > = 0.65) depicting the TFs with most similar expression pattern to p63 (shown in red)

Isha Sethi, et al. BMC Genomics. 2015;16:584.
4.
Fig 4

Fig 4. From: A global analysis of the complex landscape of isoforms and regulatory networks of p63 in human cells and tissues.

ΔNp63 and TAp63 TF networks. (a) Interaction Network for ΔNp63. Green molecules denote predicted co-regulators. Red arrows represent TFs that are likely direct targets of p63 as determined by overlay with ChIP-Seq information. Molecules with blue boundaries are those involved in Hair and Skin development and function. (b) Interaction Network of TAp63. Molecules denoted in blue are the predicted co-regulators. Molecules with green boundaries are involved in lymphoid tissue structure and development. The interaction networks (black lines connecting molecules) were generated by QIAGEN’s Ingenuity Pathway Analysis. The specific type of evidence in literature is denoted by–PP: Protein-Protein interaction, A: Activation, I: Inhibition, T: Transcription, E: Expression, PD: Protein-DNA interaction

Isha Sethi, et al. BMC Genomics. 2015;16:584.
5.
Fig 1

Fig 1. From: A global analysis of the complex landscape of isoforms and regulatory networks of p63 in human cells and tissues.

RNA-Seq reveals distinct expression patterns for TAp63 and ∆Np63. a Cartoon depicting ∆NP63 (α, β, γ) and TAp63α gene structure. TA β and γ (not shown) undergo similar alternative splicing to ∆NP63 (β, γ). TA, transactivation; Oligo, oligomerization; SAM, sterile alpha motif; TID, transactivation-inhibitory domain; UTR, untranslated region. b Snapshot from UCSC genome browser showing distribution of the aligned RNA-Seq reads at the TP63 locus in representative epithelial cell-lines (Head and neck squamous cell carcinoma (SCC) cell-lines: SCC4 and SCC15) and Non-Hodgkin lymphomas (Burkitt lymphoma cell-lines: Raji and BL2). c Heatmap depicting the expression of p63 isoforms (average across replicates) in FPKM (fragments per kilobase of transcript per million) across representative p63 expressing cell-lines

Isha Sethi, et al. BMC Genomics. 2015;16:584.

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