scholarly journals Dietary vitamin B12 regulates chemosensory receptor gene expression via the MEF2 transcription factor in Caenorhabditis elegans

2021 ◽  
Author(s):  
Aja McDonagh ◽  
Jeannette Crew ◽  
Alexander M. van der Linden
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Vitamin B12 ◽  
Sensory Neuron ◽  
Receptor Gene ◽  
Dietary Vitamin ◽  
Neuron Type ◽  
Expression Levels ◽  
Biologically Relevant ◽  
Gene Expression Levels

Dynamic changes in chemoreceptor gene expression levels in sensory neurons is one strategy that an animal can use to modify their responses to dietary changes. However, the mechanisms underlying diet-dependent modulation of chemosensory gene expression are unclear. Here, we show that the expression of the srh-234 chemoreceptor gene localized in a single ADL sensory neuron type of C. elegans is downregulated when animals are fed a Comamonas bacterial diet, but not on an E. coli diet. Remarkably, this diet-modulated effect on srh-234 gene expression levels is dependent on the micronutrient vitamin B12 endogenously produced by Comamonas bacteria. Excess propionate and genetic perturbations in the canonical and shunt propionate breakdown pathways are able to override the repressing effects of vitamin B12 on srh-234 expression. The vitamin B12-mediated regulation of srh-234 expression levels in ADL requires the MEF-2 transcription factor, providing a potential mechanism by which dietary vitamin B12 may transcriptionally tune individual chemoreceptor genes in a single sensory neuron type, which in turn may change animal responses to biologically relevant chemicals in their diet.

scholarly journals Methylation QTLs Are Associated with Coordinated Changes in Transcription Factor Binding, Histone Modifications, and Gene Expression Levels

PLoS Genetics ◽  
2014 ◽  
Vol 10 (9) ◽  
pp. e1004663 ◽  
Author(s):  
Nicholas E. Banovich ◽  
Xun Lan ◽  
Graham McVicker ◽  
Bryce van de Geijn ◽  
Jacob F. Degner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Histone Modifications ◽  
Transcription Factor Binding ◽  
Expression Levels ◽  
Factor Binding ◽  
Gene Expression Levels

scholarly journals Pathway based factor analysis of gene expression data produces highly heritable phenotypes that associate with age

2015 ◽  
Author(s):  
Andrew Anand Brown ◽  
Zhihao Ding ◽  
Ana Viñuela ◽  
Dan Glass ◽  
Leopold Parts ◽  
...  
Keyword(s):  
Gene Expression ◽  
Factor Analysis ◽  
Gene Expression Data ◽  
Biological Knowledge ◽  
Expression Data ◽  
Expression Levels ◽  
Biologically Relevant ◽  
Kegg Pathways ◽  
Analysis Methods ◽  
Gene Expression Levels

Statistical factor analysis methods have previously been used to remove noise components from high dimensional data prior to genetic association mapping, and in a guided fashion to summarise biologically relevant sources of variation. Here we show how the derived factors summarising pathway expression can be used to analyse the relationships between expression, heritability and ageing. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarise patterns of gene expression, both to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 "pathway phenotypes" which summarised patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold (P<5.38E-5). These phenotypes are more heritable (h^2=0.32) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolising sugars and fatty acids, others with insulin signalling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors.

scholarly journals Differential Expression of MicroRNAs in Silent and Functioning Corticotroph Tumors

2020 ◽  
Vol 9 (6) ◽  
pp. 1838
Author(s):  
Araceli García-Martínez ◽  
Antonio C. Fuentes-Fayos ◽  
Carmen Fajardo ◽  
Cristina Lamas ◽  
Rosa Cámara ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Potential Role ◽  
Therapeutic Option ◽  
Pharmacological Treatments ◽  
Expression Levels ◽  
Qrt Pcr ◽  
Gene Expression Levels

The potential role of miRNAs in the silencing mechanisms of pituitary neuroendocrine tumors (PitNETs) has not been addressed. The aim of the present study was to evaluate the expression levels and the potential associated role of some miRNAs, pathways, and transcription factors in the silencing mechanisms of corticotroph tumors (CTs). Accordingly, the expression of miR-375, miR-383, miR-488, miR-200a and miR-103; of PKA, MAP3K8, MEK, MAPK3, NGFIB, NURR1, PITX1, and STAT3 were analyzed via qRT-PCR in 23 silent and 24 functioning CTs. miR-200a and miR-103 showed significantly higher expression in silent than in functioning CTs, even after eliminating the bias of tumor size, therefore enabling the differentiation between the two variants. Additionally, miR-383 correlated negatively with TBX19 in silent CTs, a transcription factor related with the processing of POMC that can participate in the silencing mechanisms of CTs. Finally, the gene expression levels of miR-488, miR-200a, and miR-103 were significantly higher in macroadenomas (functioning and silent) than in microadenomas. The evidence from this study indicates that miRNAs could be involved in the pathophysiology of CTs. The translational implications of these findings suggest that pharmacological treatments specifically targeting these miRNAs could become a promising therapeutic option for these patients.

Chromatin Signature and Transcription Factor Binding Provide a Predictive Basis for Understanding Plant Gene Expression

2019 ◽  
Vol 60 (7) ◽  
pp. 1471-1486 ◽  
Author(s):  
Zefeng Wu ◽  
Jing Tang ◽  
Junjie Zhuo ◽  
Yuhan Tian ◽  
Feiyang Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Histone Modifications ◽  
Gene Expression Level ◽  
Expression Level ◽  
Good Prediction ◽  
Chromatin Modifications ◽  
Chromatin Signature ◽  
Expression Levels ◽  
Gene Expression Levels

Abstract Chromatin accessibility and post-transcriptional histone modifications play important roles in gene expression regulation. However, little is known about the joint effect of multiple chromatin modifications on the gene expression level in plants, despite that the regulatory roles of individual histone marks such as H3K4me3 in gene expression have been well-documented. By using machine-learning methods, we systematically performed gene expression level prediction based on multiple chromatin modifications data in Arabidopsis and rice. We found that as few as four histone modifications were sufficient to yield good prediction performance, and H3K4me3 and H3K36me3 being the top two predictors with known functions related to transcriptional initiation and elongation, respectively. We demonstrated that the predictive powers differed between protein-coding and non-coding genes as well as between CpG-enriched and CpG-depleted genes. We also showed that the predictive model trained in one tissue or species could be applied to another tissue or species, suggesting shared underlying mechanisms. More interestingly, the gene expression levels of conserved orthologs are easier to predict than the species-specific genes. In addition, chromatin state of distal enhancers was moderately correlated to gene expression but was dispensable if given the chromatin features of the proximal regions of genes. We further extended the analysis to transcription factor (TF) binding data. Strikingly, the combinatorial effects of only a few TFs were roughly fit to gene expression levels in Arabidopsis. Overall, by using quantitative modeling, we provide a comprehensive and unbiased perspective on the epigenetic and TF-mediated regulation of gene expression in plants.

scholarly journals Evaluation of microphthalmia associated transcription factor (MITF) expression in peripheral blood of a population with malign melanoma and control population and cell lines

1969 ◽  
Vol 40 (1) ◽  
pp. 16-33
Author(s):  
Nelson Rangel ◽  
Milena Rondón ◽  
Sandra Ramírez
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Cell Lines ◽  
Peripheral Blood ◽  
Housekeeping Genes ◽  
Expression Levels ◽  
Free People ◽  
And Control ◽  
Mitf Expression ◽  
Gene Expression Levels

Background: The incidence of malign melanoma tumours has increased more rapidly than any other type of cancer; this has intensified the searching for tools that facilitate early detection of melanoma. Microphthalmia associated transcription factor (MITF) is currently known as being a master melanocyte regulator. The article analyses MITF gene expression in peripheral blood of individuals suffering from melanoma, compared to people without any type of cancer and some cell lines. Materials and methods: Thirty one samples of peripheral blood were used: 19 from patients having melanoma and 12 from healthy people. Then RNA was extracted from these samples. MITF and housekeeping genes (b2M and GAPDH) expression levels were then quantified by real-time PCR. Five cell lines were also used to determine the MITF expression. Results: MITF gene expression could be observed in all individuals, though no statistical significant differences were found among expression levels in the groups studied (p=0.09). Even so, MITF expression in the group of patients suffering from melanoma was much more variable than that observed in the group of cancer-free people. Expression was detected in the cell line AGS (gastric adenocarcinoma), not yet described. Conclusions: MITF gene expression levels were detected in the peripheral blood from both people suffering from melanoma and people without any type of cancer. However, variability in the number of molecules in MITF gene expression was observed in people with melanoma, this suggests the presence of tumour cells in circulation.

scholarly journals Gene expression models based on transcription factor binding events confer insight into functional cis-regulatory variants

2018 ◽  
Vol 35 (15) ◽  
pp. 2610-2617 ◽  
Author(s):  
Wenqiang Shi ◽  
Oriol Fornes ◽  
Wyeth W Wasserman
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
External Validation ◽  
Model Performance ◽  
Supplementary Information ◽  
Expression Levels ◽  
Functional Roles ◽  
Regulatory Variants ◽  
The Impact ◽  
Gene Expression Levels

Abstract Motivation Deciphering the functional roles of cis-regulatory variants is a critical challenge in genome analysis and interpretation. It has been hypothesized that altered transcription factor (TF) binding events are a central mechanism by which cis-regulatory variants impact gene expression levels. However, we lack a computational framework to understand and quantify such mechanistic contributions. Results We present TF2Exp, a gene-based framework to predict the impact of altered TF-binding events on gene expression levels. Using data from lymphoblastoid cell lines, TF2Exp models were applied successfully to predict the expression levels of 3196 genes. Alterations within DNase I hypersensitive, CTCF-bound and tissue-specific TF-bound regions were the greatest contributing features to the models. TF2Exp models performed as well as models based on common variants, both in cross-validation and external validation. Combining TF alteration and common variant features can further improve model performance. Unlike variant-based models, TF2Exp models have the unique advantage to evaluate the functional impact of variants in linkage disequilibrium and uncommon variants. We find that adding TF-binding events altered only by uncommon variants could increase the number of predictable genes (R2 > 0.05). Taken together, TF2Exp represents a key step towards interpreting the functional roles of cis-regulatory variants in the human genome. Availability and implementation The code and model training results are publicly available at https://github.com/wqshi/TF2Exp. Supplementary information Supplementary data are available at Bioinformatics online.

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