HBP21: A Novel Member of TPR Motif Family, as a Potential Chaperone of Heat Shock Protein 70 in Proliferative Vitreoretinopathy (PVR) and Breast Cancer

Liu, Qinghuai; Chen, Xi; Chen, Yuxin; Chen, Jie; Wang, Saiqun; Liu, Jin; Liu, Xiaoyi; Li, Jianmin

doi:10.1007/s12033-008-9080-5

“…Several of the top ranked tissue-specific hubs were genes with evidence of known tissue-specific function or relevance. In the tissue group including breastmammary and the two adipose tissues, the top tissue-specific TE-IR hub was TTC36, a gene highly expressed in breast cancer (Liu et al 2008). The second ranked hub gene for the tissue group including skeletal muscle and heart-left ventricle was LMOD2, which was observed to be abundantly expressed in both tissues and has been reported to regulate the thin filament length in muscles affecting cardiomyopathy in mice (Pappas et al 2015;Li et al 2016b).…”

Section: Splicing and Expression Network Across Tissuesmentioning

confidence: 99%

Co-expression networks reveal the tissue-specific regulation of transcription and splicing

Saha

¹

,

Kim

²

,

Gewirtz

³

et al. 2017

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Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues.

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“…Other proteins identified in our study include tetratricopeptide repeat protein 36 (TTC36 also named HBP21) which is capable of inducing apoptosis via the translocation of Bax from cytoplasm-to-mitochondria which leads to increase the cleaved of caspase-3, caspase-9, and poly (ADP ribose) polymerase tumor cells including hepatocellular carcinoma [60]. Moreover, HBP21 might be involved in the inhibition of progression and metastasis of breast cancer cells [61].…”

Section: Discussionmentioning

confidence: 86%

Comparative Analysis of Milk Fat Globular Membrane (MFGM) Proteome between Saudi Arabia Camelus dromedary Safra and Wadha Breeds

Sabha

¹

,

Masood

²

,

Alanazi

³

et al. 2020

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Camel milk is traditionally known to have medicinal properties and many potential health benefits. Natural milk contains many soluble proteins and nanoparticles, such as a milk fat globule membrane (MFGM), a three-layered membrane covering of milk fat globule mainly composed of proteins and lipids, which plays an important role in human health. MFGM proteins account for 1%–4% of total milk proteins, and their nutritive value and distribution depends on the different breeds. The differential composition of these membrane proteins among different camel breeds has not been explored. The current study, therefore, aimed to quantitatively analyze and compare the MFGM proteome between the milk produced by the two most common Saudi camel breeds, Camelus dromedarius: Safra and Wadha. Two-dimensional difference in gel electrophoresis (2D-DIGE) and mass spectrometry analysis revealed a total of 44 MFGM proteins that were identified with a significant difference in abundance (p ≤ 0.05; fold change ≥ 1.5) between the two breeds. Thirty-one proteins were up-regulated and 13 proteins were down-regulated in the Safra breed compared to the Wadha breed. The proteins identified with an increased abundance included α-lactalbumin, lactadherin, and annexin a8, whereas the down-regulated proteins included butyrophilin subfamily 1 member a1, lactotransferrin, and vinculin. The differentially abundant proteins were analyzed by the UNIPROT system and gene ontology (GO) to reveal their associations with known biological functions and pathways. Enzyme-linked immunosorbent assay (ELISA) confirmed the 2D-DIGE findings of butyrophilin (BTN) and α-lactalbumin (α-LA) levels obtained from Safra and Wadha breeds.

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“…Several of the top ranked tissue-specific hubs were genes with evidence of known tissue-specific function or relevance. In the tissue group including breast and two adipose tissues, the top tissue-specific TE-IR hub was TTC36 , a gene highly expressed in breast cancer (Liu et al, 2008). The top ranked gene hub for the skeletal muscle and heart – left ventricle tissues group was PLEKHG4 , which has been reported to be associated with cardiac failure in mice (Mullick et al, 2006).…”

Section: Resultsmentioning

confidence: 99%

Co-expression networks reveal the tissue-specific regulation of transcription and splicing

Kim

¹

,

Gewirtz

²

,

Jo

³

et al. 2016

Preprint

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Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of regulatory genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single or small sets of tissues. Here, we have reconstructed networks that capture a much more complete set of regulatory relationships, specifically including regulation of relative isoform abundance and splicing, and tissue-specific connections unique to each of a diverse set of tissues. Using the Genotype-Tissue Expression (GTEx) project v6 RNA-sequencing data across 44 tissues in 449 individuals, we evaluated shared and tissue-specific network relationships. First, we developed a framework called Transcriptome Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the complex interplay between the regulation of splicing and transcription. We built TWNs for sixteen tissues, and found that hubs with isoform node neighbors in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome, and providing a set of candidate shared and tissue-specific regulatory hub genes. Next, we used a Bayesian biclustering model that identifies network edges between genes with co-expression in a single tissue to reconstruct tissue-specific networks (TSNs) for 27 distinct GTEx tissues and for four 1 . CC-BY-NC-ND4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/078741 doi: bioRxiv preprint first posted online Oct. 2, 2016;subsets of related tissues. Using both TWNs and TSNs, we characterized gene co-expression patterns shared across tissues. Finally, we found genetic variants associated with multiple neighboring nodes in our networks, supporting the estimated network structures and identifying 33 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships between genes in the human transcriptome, including tissue-specificity of gene co-expression, regulation of splicing, and the coordinated impact of genetic variation on transcription.

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HBP21: A Novel Member of TPR Motif Family, as a Potential Chaperone of Heat Shock Protein 70 in Proliferative Vitreoretinopathy (PVR) and Breast Cancer

Cited by 12 publications

References 39 publications

Co-expression networks reveal the tissue-specific regulation of transcription and splicing

Co-expression networks reveal the tissue-specific regulation of transcription and splicing

Comparative Analysis of Milk Fat Globular Membrane (MFGM) Proteome between Saudi Arabia Camelus dromedary Safra and Wadha Breeds

Co-expression networks reveal the tissue-specific regulation of transcription and splicing

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