Dataset Information

Mouse ameloblasts Bcl9 interactors

ABSTRACT: Bcl9 and Bcl9l (Bcl9l) are commonly thought as beta-catenin-dependent Wnt signaling transcriptional activators. We find however that, in the enamel-producin ameloblasts cells, Bcl9/9l are localiyed in the cytoplasm toward to apical secretory membrane. We performed pull down followed by mass spectrometry analysis to discover the molecular partners of Bcl9 that could explain this cytoplasmic localyzation.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Primary Cell, Epithelial Cell

DISEASE(S): Disease Free

SUBMITTER: Claudio Cantù

LAB HEAD: Claudio Cantù - lab of Konrad Basler

PROVIDER: PXD005449 | Pride | 2017-02-13

REPOSITORIES: Pride

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Publications

A cytoplasmic role of Wnt/β-catenin transcriptional cofactors Bcl9, Bcl9l, and Pygopus in tooth enamel formation.

Cantù Claudio C Pagella Pierfrancesco P Shajiei Tania D TD Zimmerli Dario D Valenta Tomas T Hausmann George G Basler Konrad K Mitsiadis Thimios A TA

Science signaling 20170207 465

Wnt-stimulated β-catenin transcriptional regulation is necessary for the development of most organs, including teeth. Bcl9 and Bcl9l are tissue-specific transcriptional cofactors that cooperate with β-catenin. In the nucleus, Bcl9 and Bcl9l simultaneously bind β-catenin and the transcriptional activator Pygo2 to promote the transcription of a subset of Wnt target genes. We showed that Bcl9 and Bcl9l function in the cytoplasm during tooth enamel formation in a manner that is independent of Wnt-st ...[more]

PMID: 28174279

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Project description:Background Array-based comparative genome hybridization (aCGH) is commonly used to determine the genomic content of bacterial strains. In aCGH data, systematic errors are comparable to those occurring in transcriptome data. However, especially for microbes, an additional source of variation exists: differences in hybridization due to gene sequence divergence between the strains hybridized. Current normalization methods do not take this source of variation into consideration. Results We present Supervised Lowess, or S-Lowess, an application of the subset Lowess normalization method that does take difference in genomic content into account. The performance of S-Lowess was assessed on aCGH experiments in which differentially labeled genomic DNA fragments of Lactococcus lactis IL1403 and L. lactis MG1363 strains were hybridized to IL1403 microarrays. Since both genome sequences are known (they have only on average 85 % sequence identity), the success rate in detecting deletions in the MG1363 genome of different aCGH normalization methods can be compared. S-Lowess detects 97% of the deletions, whereas other aCGH normalization methods detect up to only 60% of the deletions. Conclusions S-Lowess removes systematic errors from dual-dye aCGH data in two steps: (i) determination of likely homologous genes (LHG); and (ii) estimation of correction factors for systematic errors from spots of LHG and subset Lowess normalization of the remaining spots using these correction factors. It is implemented in a user-friendly web-tool accessible from http://bioinformatics.biol.rug.nl/websoftware/s-lowess. We demonstrate that it outperforms existing normalization methods and maximizes the number of detectable genomic deletions or duplications from microbial aCGH data. Keywords: comparative genome hybridisation In this study, 4 aCGH comparisons (slides) between L. lactis MG1363 and L. lactis IL1403 were performed (including dye swap with biological replicates; see also supplementary materials). The resulting aCGH slide signals were normalized using the different 'likely homologous gene' (LHG) sets (see above) yielding ratios of signals of labelled DNA of MG1363 over those of IL1403. A maximum of 8 ratios per amplicon (gene) were obtained for the 4 hybridized slides (each with 2 replicate spots per amplicon). Only genes with at least 5 measurements were used in this study. The normalization methods evaluated in this study are: a) no normalization, b) total signal normalization, c) grid-based Lowess (implemented in PreP; f = 0.7) [GarcM-CM--a de la Nava, J et al. 2003. Bioinformatics 19:2328-2329], and d) S-Lowess using different subsets of conserved lactococcal genes (for details see above). Results with the MANOR R package (spatial normalization; standard parameters) [Neuvial P, et al. 2006. BMC Bioinformatics 7:264; Liva S, et al. 2006. Nucleic Acids Res 34:W477-W481] are shown in our supplementary materials.

			Action	DRS
	Bcl9_RAW_2.raw	Raw
	Bcl9_SEARCH_1.dat	Other
	Bcl9_SEARCH_2.dat	Other
	IgG_RAW_1.raw	Raw
	IgG_RAW_2.raw	Raw