scholarly journals Ciliary dyslexia candidate genes DYX1C1 and DCDC2 are regulated by Regulatory Factor X (RFX) transcription factors through X‐box promoter motifs

2016 ◽  
Vol 30 (10) ◽  
pp. 3578-3587 ◽  
Author(s):  
Kristiina Tammimies ◽  
Andrea Bieder ◽  
Gilbert Lauter ◽  
Debora Sugiaman‐Trapman ◽  
Rachel Torchet ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Candidate Genes ◽  
Factor X ◽  
Regulatory Factor

scholarly journals Regulatory Factor X Transcription Factors Control Musashi1 Transcription in Mouse Neural Stem/Progenitor Cells

2014 ◽  
Vol 23 (18) ◽  
pp. 2250-2261 ◽  
Author(s):  
Satoshi Kawase ◽  
Kenichiro Kuwako ◽  
Takao Imai ◽  
Francois Renault-Mihara ◽  
Kunio Yaguchi ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Progenitor Cells ◽  
Factor X ◽  
Regulatory Factor ◽  
Neural Stem Progenitor Cells

The C. elegans Regulatory Factor X (RFX) DAF-19M Module: A Shift From General Ciliogenesis to Ciliary and Behavioral Specialization

2021 ◽  
Author(s):  
Soungyub Ahn ◽  
Heeseung Yang ◽  
Sangwon Son ◽  
Dongjun Park ◽  
Hyunsoo Yim ◽  
...  
Keyword(s):  
Factor X ◽  
Regulatory Factor ◽  
C Elegans ◽  
Behavioral Specialization

scholarly journals Mutations in P63 and IRF-6 Present with Overlapping Craniofacial Defects: A study from Lebanon

2019 ◽  
pp. 1-3
Author(s):  
Mazen Kurban ◽  
Edgar Jabbour ◽  
Lamiaa Hamie ◽  
Mazen Kurban ◽  
Pamela Kassabian
Keyword(s):  
Transcription Factors ◽  
Cleft Lip ◽  
Interferon Regulatory Factor ◽  
Craniofacial Development ◽  
Regulatory Factor ◽  
Van Der Woude Syndrome ◽  
Interferon Regulatory Factor 6 ◽  
Cleft Lip Palate ◽  
Exon 9 ◽  
Craniofacial Defects

Interferon Regulatory Factor 6 (IRF-6) and p63 are two vital transcription factors implicated in normal craniofacial development. In this report, we present a family with Van Der Woude Syndrome (VWS) with a mutation in exon 9 of IRF-6 gene and a phenotypically overlapping case of Rapp-Hodgkin Syndrome (RHS) resulting from a mutation in the p63 gene. Members from both families presented with congenital lip pits and cleft lip/palate. The RHS case had additional ectodermal features that underscore the upstream nature of p63 in the complex p63-IRF-6 interactive pathway.

scholarly journals Learning the human chromatin network from all ENCODE ChIP-seq data

2015 ◽  
Author(s):  
Scott M. Lundberg ◽  
William B. Tu ◽  
Brian Raught ◽  
Linda Z. Penn ◽  
Michael M. Hoffman ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Protein Interactions ◽  
Graphical Model ◽  
Cell Types ◽  
Statistical Technique ◽  
Regulatory Factor ◽  
Genomic Context ◽  
Regulatory Factors ◽  
Conditional Dependence ◽  
Factor Interactions

Introduction: A cell's epigenome arises from interactions among regulatory factors --- transcription factors, histone modifications, and other DNA-associated proteins --- co-localized at particular genomic regions. Identifying the network of interactions among regulatory factors, the chromatin network, is of paramount importance in understanding epigenome regulation. Methods: We developed a novel computational approach, ChromNet, to infer the chromatin network from a set of ChIP-seq datasets. ChromNet has four key features that enable its use on large collections of ChIP-seq data. First, rather than using pairwise co-localization of factors along the genome, ChromNet identifies conditional dependence relationships that better discriminate direct and indirect interactions. Second, our novel statistical technique, the group graphical model, improves inference of conditional dependence on highly correlated datasets. Such datasets are common because some transcription factors form a complex and the same transcription factor is often assayed in different laboratories or cell types. Third, ChromNet's computationally efficient method and the group graphical model enable the learning of a joint network across all cell types, which greatly increases the scope of possible interactions. We have shown that this results in a significantly higher fold enrichment for validated protein interactions. Fourth, ChromNet provides an efficient way to identify the genomic context that drives a particular network edge, which provides a more comprehensive understanding of regulatory factor interactions. Results: We applied ChromNet to all available ChIP-seq data from the ENCODE Project, consisting of 1451 ChIP-seq datasets, which revealed previously known physical interactions better than alternative approaches. ChromNet also identified previously unreported regulatory factor interactions. We experimentally validated one of these interactions, between the MYC and HCFC1 transcription factors. Discussion: ChromNet provides a useful tool for understanding the interactions among regulatory factors and identifying novel interactions. We have provided an interactive web-based visualization of the full ENCODE chromatin network and the ability to incorporate custom datasets at http://chromnet.cs.washington.edu.

scholarly journals Combined Analysis of the Metabolome and Transcriptome Identified Candidate Genes Involved in Phenolic Acid Biosynthesis in the Leaves of Cyclocarya paliurus

2020 ◽  
Vol 21 (4) ◽  
pp. 1337 ◽  
Author(s):  
Weida Lin ◽  
Yueling Li ◽  
Qiuwei Lu ◽  
Hongfei Lu ◽  
Junmin Li
Keyword(s):  
Transcription Factors ◽  
Candidate Genes ◽  
Phenolic Acid ◽  
Developmental Stages ◽  
Ultra Performance Liquid Chromatography ◽  
Differentially Expressed ◽  
Regulation Mechanism ◽  
Acid Biosynthesis ◽  
Cyclocarya Paliurus ◽  
Helix Loop Helix

To assess changes of metabolite content and regulation mechanism of the phenolic acid biosynthesis pathway at different developmental stages of leaves, this study performed a combined metabolome and transcriptome analysis of Cyclocarya paliurus leaves at different developmental stages. Metabolite and transcript profiling were conducted by ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometer and high-throughput RNA sequencing, respectively. Transcriptome identification showed that 58 genes were involved in the biosynthesis of phenolic acid. Among them, 10 differentially expressed genes were detected between every two developmental stages. Identification and quantification of metabolites indicated that 14 metabolites were located in the phenolic acid biosynthetic pathway. Among them, eight differentially accumulated metabolites were detected between every two developmental stages. Association analysis between metabolome and transcriptome showed that six differentially expressed structural genes were significantly positively correlated with metabolite accumulation and showed similar expression trends. A total of 128 transcription factors were identified that may be involved in the regulation of phenolic acid biosynthesis; these include 12 MYBs and 10 basic helix–loop–helix (bHLH) transcription factors. A regulatory network of the phenolic acid biosynthesis was established to visualize differentially expressed candidate genes that are involved in the accumulation of metabolites with significant differences. The results of this study contribute to the further understanding of phenolic acid biosynthesis during the development of leaves of C. paliurus.

ISDN2014_0347: Candidate genes for schizophrenia: Focus on transcription factors

2015 ◽  
Vol 47 (Part_A) ◽  
pp. 105-105
Author(s):  
Anna Boyajyan ◽  
Roksana Zakharyan ◽  
Sofi Atshemyan ◽  
Kristina Pirumyan ◽  
Gohar Mkrtchyan ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Candidate Genes

scholarly journals Regulatory factor-X binding to mutant HLA-DRA promoter sequences

1991 ◽  
Vol 19 (6) ◽  
pp. 1243-1249 ◽  
Author(s):  
Susan L. Hasegawa ◽  
John H. Sloan ◽  
Walter Reith ◽  
Bernard Mach ◽  
Jeremy M Boss
Keyword(s):  
Factor X ◽  
Regulatory Factor ◽  
Promoter Sequences

scholarly journals Functional Analysis of the Asian Soybean Rust Resistance Pathway Mediated by Rpp2

2011 ◽  
Vol 24 (2) ◽  
pp. 194-206 ◽  
Author(s):  
Ajay K. Pandey ◽  
Chunling Yang ◽  
Chunquan Zhang ◽  
Michelle A. Graham ◽  
Heidi D. Horstman ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Candidate Genes ◽  
Leaf Tissue ◽  
Soybean Rust ◽  
Virus Induced Gene Silencing ◽  
Resistance Response ◽  
P450 Monooxygenase ◽  
Methyl Transferase ◽  
Asian Soybean Rust ◽  
Resistance Pathway

Asian soybean rust is an aggressive foliar disease caused by the obligate biotrophic fungus Phakopsora pachyrhizi. On susceptible plants, the pathogen penetrates and colonizes leaf tissue, resulting in the formation of necrotic lesions and the development of numerous uredinia. The soybean Rpp2 gene confers resistance to specific isolates of P. pachyrhizi. Rpp2-mediated resistance limits the growth of the pathogen and is characterized by the formation of reddish-brown lesions and few uredinia. Using virus-induced gene silencing, we screened 140 candidate genes to identify those that play a role in Rpp2 resistance toward P. pachyrhizi. Candidate genes included putative orthologs to known defense-signaling genes, transcription factors, and genes previously found to be upregulated during the Rpp2 resistance response. We identified 11 genes that compromised Rpp2-mediated resistance when silenced, including GmEDS1, GmNPR1, GmPAD4, GmPAL1, five predicted transcription factors, an O-methyl transferase, and a cytochrome P450 monooxygenase. Together, our results provide new insight into the signaling and biochemical pathways required for resistance against P. pachyrhizi.

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