Muscular dystrophy in PTFR/cavin-1 null mice

Ding, Shi-Ying; Liu, Libin; Pilch, Paul F.

doi:10.1172/jci.insight.91023

Cited by 19 publications

(19 citation statements)

References 66 publications

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“…Caveolae are 50-80-nm invaginations of the plasma membrane and are composed of specialized lipids and caveolin (CAV)1-3, cavin 1-4, EHD, and pacsin proteins [2,5,96]. Caveolae-deficient patients and animal models have lipid and muscular dystrophies [97][98][99][100][101][102]. A principal function of caveolae is mechanosensing and -protection [96,99,[103][104][105][106][107].…”

Section: The Hippo Pathway Yap/taz and Caveolaementioning

confidence: 99%

The Hippo Pathway, YAP/TAZ, and the Plasma Membrane

Rausch

Hansen

2020

Trends in Cell Biology

180

154

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The plasma membrane allows the cell to sense and adapt to changes in the extracellular environment by relaying external inputs via intracellular signaling networks. One central cellular signaling pathway is the Hippo pathway, which regulates homeostasis and plays chief roles in carcinogenesis and regenerative processes. Recent studies have found that mechanical stimuli and diffusible chemical components can regulate the Hippo pathway primarily through receptors embedded in the plasma membrane. Morphologically defined structures within the plasma membrane, such as cellular junctions, focal adhesions, primary cilia, caveolae, clathrin-coated pits, and plaques play additional key roles. Here, we discuss recent evidence highlighting the importance of these specialized plasma membrane domains in cellular feedback via the Hippo pathway. Cellular Regulation by the Hippo PathwayThe plasma membrane is essential for cell integrity and serves as an interface to sense and respond to changes in the extracellular environment [1]. A large variety of plasma membrane domains, such as, adherens and tight junctions (see Glossary), focal adhesions (FAs), clathrin-coated pits (CCPs) or plaques, caveolae, and primary cilia [2-8], allow the cell to dynamically relay chemical and mechanical stimuli, which are translated into direct cellular responses. The plasma membrane as a whole, but FAs in particular, strongly interacts with the extracellular matrix (ECM) [9]. The ECM is a dynamic noncellular matrix surrounding cells and tissues that acts as a scaffold for cell anchorage and mechanotransduction [9]. The signals perceived by plasma membrane elements are integrated and transmitted by a variety of signaling pathways. One central pathway, which enables the cell to respond to various signals, is the Hippo pathway (Box 1) [10][11][12][13]. By highly context specific responses the Hippo pathway regulates cellular homeostasis and plays central roles in carcinogenesis and regenerative processes [10,12,13]. The Hippo pathway is extracellularly regulated by mechanical stimuli and diffusible chemicals. These signals are sensed in great part by receptors, such as G-protein coupled receptors (GPCRs) and adherence complexes embedded in the plasma membrane [1,[10][11][12][13][14][15][16]. To ensure a highly specific response, junctional complexes and receptors accumulate in distinct membrane structures and their plasma membrane abundance is furthermore dynamically regulated by exo-and endocytosis [3,4,7,17]. Junctional complexes provide robust cellular sensitivity of Hippo signaling to cell polarity and cell-cell contacts [10,15,16]. Catenins [18,19], protein tyrosine phosphatase nonreceptor (PTPN)14 [20,21], and the angiomotin family [22][23][24][25][26] play central roles in this regulation as direct YAP-binding proteins. Both PTPN14 and AMOT interact via PPxY motifs with WW domains of YAP and TAZ, and consequently, this interaction does not directly require YAP and TAZ Hippopathway-mediated phosphorylation [20][21][22][23]. Several of the Hippo ...

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Section: The Hippo Pathway Yap/taz and Caveolaementioning

confidence: 99%

The Hippo Pathway, YAP/TAZ, and the Plasma Membrane

Rausch

Hansen

2020

Trends in Cell Biology

180

154

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“…Notably, five 3'UTR mutations were identified in a gene coding for polymerase I and transcript release factor (PTRF/cavin-1) ( Table 5). Lack of cavin-1 in mice and humans caused muscular dystrophy [102]. Cavin-1 supports cell proliferation and migration in humans and shows downregulated expression during myogenic differentiation [103].…”

Section: Single Marker Association Analysismentioning

confidence: 99%

Genome-wide identification of loci associated with growth in rainbow trout

et al. 2020

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Background: Growth is a major economic production trait in aquaculture. Improvements in growth performance will reduce time and cost for fish to reach market size. However, genes underlying growth have not been fully explored in rainbow trout. Results: A previously developed 50 K gene-transcribed SNP chip, containing~21 K SNPs showing allelic imbalances potentially associated with important aquaculture production traits including body weight, muscle yield, was used for genotyping a total of 789 fish with available phenotypic data for bodyweight gain. Genotyped fish were obtained from two consecutive generations produced in the NCCCWA growth-selection breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform a genome-wide association (GWA) analysis to identify quantitative trait loci (QTL) associated with bodyweight gain. Using genomic sliding windows of 50 adjacent SNPs, 247 SNPs associated with bodyweight gain were identified. SNP-harboring genes were involved in cell growth, cell proliferation, cell cycle, lipid metabolism, proteolytic activities, chromatin modification, and developmental processes. Chromosome 14 harbored the highest number of SNPs (n = 50). An SNP window explaining the highest additive genetic variance for bodyweight gain (~6.4%) included a nonsynonymous SNP in a gene encoding inositol polyphosphate 5-phosphatase OCRL-1. Additionally, based on a single-marker GWA analysis, 33 SNPs were identified in association with bodyweight gain. The highest SNP explaining variation in bodyweight gain was identified in a gene coding for thrombospondin-1 (THBS1) (R 2 = 0.09). Conclusion: The majority of SNP-harboring genes, including OCRL-1 and THBS1, were involved in developmental processes. Our results suggest that development-related genes are important determinants for growth and could be prioritized and used for genomic selection in breeding programs.

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“…Notably, five 3'UTR mutations were identified in a gene coding for polymerase I and transcript release factor (PTRF/cavin-1) ( Table 5). Lack of cavin-1 in mice and humans caused muscular dystrophy [101]. Cavin-1 supports cell proliferation and migration in humans and shows downregulated expression during myogenic differentiation [102].…”

Section: Single Marker Association Analysismentioning

confidence: 99%

Genome-wide identification of loci associated with growth in rainbow trout

Ali

Al-Tobasei

Lourenço

et al. 2019

Preprint

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Background Growth is a major economic production trait in aquaculture. Improvements in growth performance will reduce time and cost for fish to reach market size. However, genes underlying growth have not been fully explored in rainbow trout.Results A previously developed 50K gene-transcribed SNP chip, containing ~21K SNPs showing allelic imbalances potentially associated with important aquaculture production traits including body weight, muscle yield, was used for genotyping a total of 789 fish with available phenotypic data for bodyweight gain. Genotyped fish were obtained from two consecutive generations produced in the NCCCWA growth-selection breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform a genome-wide association (GWA) analysis to identify quantitative trait loci (QTL) associated with bodyweight gain. Using genomic sliding windows of 50 adjacent SNPs, 247 SNPs associated with bodyweight gain were identified. SNP-harboring genes were involved in cell growth, cell proliferation, cell cycle, lipid metabolism, proteolytic activities, chromatin modification, and developmental processes. Chromosome 14 harbored the highest number of SNPs (n = 50). An SNP window explaining the highest additive genetic variance for bodyweight gain (~6.4%) included a nonsynonymous SNP in a gene encoding inositol polyphosphate 5-phosphatase OCRL-1. Additionally, based on a singlemarker GWA analysis, 46 SNPs were identified in association with bodyweight gain. The highest SNP associated with this trait was identified in a gene coding for thrombospondin-1 (THBS1) (R 2 = 0.09). ConclusionThe majority of SNP-harboring genes, including OCRL-1 and THBS1, were involved in developmental processes. Our results suggest that development-related genes are important determinants for growth and could be prioritized and used for genomic selection in breeding programs.Biol Chem 2008, 283(9):5760-5768. Rep 2014, 9(5):1723-1728. -11 and Ceap-16, two novel splicing-variantproteins, associated with centrosome, microtubule aggregation and cell proliferation. J Mol Biol 2004, 343(1):71-82. 31. Tobias ES, Hurlstone AF, MacKenzie E, McFarlane R, Black DM: The TES gene at 7q31.1 is methylated in tumours and encodes a novel growth-suppressing LIM domain protein. Oncogene 2001, 20(22):2844-2853. 32. Ramirez-Valle F, Braunstein S, Zavadil J, Formenti SC, Schneider RJ: eIF4GI links nutrient sensing by mTOR to cell proliferation and inhibition of autophagy. J Cell Biol 2008, 181(2):293-307. 33. Uhl GR: Involvement of the neutral amino acid transporter SLC6A15 and leucine in obesity-related phenotypes. PLoS One 2013, 8(9):e68245. 34. Fernandez AI, Perez-Montarelo D, Barragan C, Ramayo-Caldas Y, Ibanez-Escriche N, Castello A, Noguera JL, Silio L, Folch JM, Rodriguez MC: Genome-wide linkage analysis of QTL for growth and body composition employing the PorcineSNP60 BeadChip. BMC Genet 2012, 13:41. 35. Yang K, Hitomi M, Stacey DW: Variations in cyclin D1 levels through the cell cycle determine the proliferative fate of a cell. Cell Div 2006,...

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Muscular dystrophy in PTFR/cavin-1 null mice

Cited by 19 publications

References 66 publications

The Hippo Pathway, YAP/TAZ, and the Plasma Membrane

The Hippo Pathway, YAP/TAZ, and the Plasma Membrane

Genome-wide identification of loci associated with growth in rainbow trout

Genome-wide identification of loci associated with growth in rainbow trout

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