scholarly journals An Integrated Statistical Approach to Compare Transcriptomics Data across Experiments: A Case Study on the Identification of Candidate Target Genes of the Transcription Factor PPARα

2012 ◽  
Vol 6 ◽  
pp. BBI.S9529
Author(s):  
Mohammad Ohid Ullah ◽  
Michael Müller ◽  
Guido J.E.J. Hooiveld

An effective strategy to elucidate the signal transduction cascades activated by a transcription factor is to compare the transcriptional profiles of wild type and transcription factor knockout models. Many statistical tests have been proposed for analyzing gene expression data, but most tests are based on pair-wise comparisons. Since the analysis of microarrays involves the testing of multiple hypotheses within one study, it is generally accepted that one should control for false positives by the false discovery rate (FDR). However, it has been reported that this may be an inappropriate metric for comparing data across different experiments. Here we propose an approach that addresses the above mentioned problem by the simultaneous testing and integration of the three hypotheses (contrasts) using the cell means ANOVA model. These three contrasts test for the effect of a treatment in wild type, gene knockout, and globally over all experimental groups. We illustrate our approach on microarray experiments that focused on the identification of candidate target genes and biological processes governed by the fatty acid sensing transcription factor PPARα in liver. Compared to the often applied FDR based across experiment comparison, our approach identified a conservative but less noisy set of candidate genes with same sensitivity and specificity. However, our method had the advantage of properly adjusting for multiple testing while integrating data from two experiments, and was driven by biological inference. Taken together, in this study we present a simple, yet efficient strategy to compare differential expression of genes across experiments while controlling for multiple hypothesis testing.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 776-776
Author(s):  
Zhongfa Yang ◽  
Alan G. Rosmarin

Abstract GABP is an ets transcription factor that regulates transcription of key myeloid genes, including CD18 (beta2 leukocyte integrin), neutrophil elastase, lysozyme, and other key mediators of the inflammatory response; it is also known to regulate important cell cycle control genes. GABP consists of two distinct and unrelated proteins that, together, form a functional transcription factor complex. GABPalpha (GABPa) is an ets protein that binds to DNA; it forms a tetrameric complex by recruiting its partner, GABPbeta (GABPb), which contains the transactivation domain. GABPa is a single copy gene in both the human and murine genomes and it is the only protein that can recruit GABPb to DNA. We cloned GABPa from a murine genomic BAC library and prepared a targeting vector in which exon 9 (which encodes the GABPa ets domain) was flanked by loxP (floxed) recombination sites. The targeting construct was electroporated into embryonic stem cells, homologous recombinants were implanted into pseudopregnant mice, heterozygous floxed GABPa mice were identified, and intercrossing yielded expected Mendelian ratios of wild type, heterozygous, and homozygous floxed GABPa mice. Breeding of heterozygous floxed GABPa mice to CMV-Cre mice (which express Cre recombinase in all tissues) yielded expected numbers of hemizygous mice (only one intact GABPa allele), but no nullizygous (GABPa−/−) mice among 64 pups; we conclude that homozygous deletion of GABPa causes an embryonic lethal defect. To determine the effect of GABPa deletion on myeloid cell development, we bred heterozygous and homozygous floxed mice to LysMCre mice, which express Cre only in myeloid cells. These mice had a normal complement of myeloid cells but, unexpectedly, PCR indicated that their Gr1+ myeloid cells retained an intact (undeleted) floxed GABPa allele. We detected similar numbers of in vitro myeloid colonies from bone marrow of wild type, heterozygous floxed, and homozygous floxed progeny of LysMCre matings. However, PCR of twenty individual in vitro colonies from homozygous floxed mice indicated that they all retained an intact floxed allele. Breeding of floxed GABPa/LysMCre mice with hemizygous mice indicated that retention of a floxed allele was not due to incomplete deletion by LysMCre; rather, it appears that only myeloid cells that retain an intact GABPa allele can survive to mature in vitro or in vivo. We prepared murine embryonic fibroblasts from homozygous floxed mice and efficiently deleted GABPa in vitro. We found striking abnormalities in proliferation and G1/S phase arrest. We used quantitative RT-PCR to identify mechanisms that account for the altered growth of GABPa null cells. We found dramatically reduced expression of known GABP target genes that regulate DNA synthesis and cell cycle that appear to account for the proliferative defect. We conclude that GABPa is required for growth and maturation of myeloid cells and we identified downstream targets that may account for their failure to proliferate and mature in vitro and in vivo.


1995 ◽  
Vol 15 (3) ◽  
pp. 1522-1535 ◽  
Author(s):  
W J Fredericks ◽  
N Galili ◽  
S Mukhopadhyay ◽  
G Rovera ◽  
J Bennicelli ◽  
...  

Alveolar rhabdomyosarcomas are pediatric solid tumors with a hallmark cytogenetic abnormality: translocation of chromosomes 2 and 13 [t(2;13) (q35;q14)]. The genes on each chromosome involved in this translocation have been identified as the transcription factor-encoding genes PAX3 and FKHR. The NH2-terminal paired box and homeodomain DNA-binding domains of PAX3 are fused in frame to COOH-terminal regions of the chromosome 13-derived FKHR gene, a novel member of the forkhead DNA-binding domain family. To determine the role of the fusion protein in transcriptional regulation and oncogenesis, we identified the PAX3-FKHR fusion protein and characterized its function(s) as a transcription factor relative to wild-type PAX3. Antisera specific to PAX3 and FKHR were developed and used to examine PAX3 and PAX3-FKHR expression in tumor cell lines. Sequential immunoprecipitations with anti-PAX3 and anti-FKHR sera demonstrated expression of a 97-kDa PAX3-FKHR fusion protein in the t(2;13)-positive rhabdomyosarcoma Rh30 cell line and verified that a single polypeptide contains epitopes derived from each protein. The PAX3-FKHR protein was localized to the nucleus in Rh30 cells, as was wild-type PAX3, in t(2;13)-negative A673 cells. In gel shift assays using a canonical PAX binding site (e5 sequence), we found that DNA binding of PAX3-FKHR was significantly impaired relative to that of PAX3 despite the two proteins having identical PAX DNA-binding domains. However, the PAX3-FKHR fusion protein was a much more potent transcriptional activator than PAX3 as determined by transient cotransfection assays using e5-CAT reporter plasmids. The PAX3-FKHR protein may function as an oncogenic transcription factor by enhanced activation of normal PAX3 target genes.


2013 ◽  
Vol 58 (5) ◽  
pp. 403-408 ◽  
Author(s):  
Seo Young Bang ◽  
Jeong Hoon Kim ◽  
Phil Young Lee ◽  
Seung-Wook Chi ◽  
Sayeon Cho ◽  
...  

2021 ◽  
Author(s):  
Huabo Wang ◽  
Jie Lu ◽  
Frances Alencastro ◽  
Alexander Roberts ◽  
Julia Fiedor ◽  
...  

The Myc bHLH-ZIP transcription factor is deregulated by most cancers. As a heterodimer with the bHLH-ZIP protein Max, Myc regulates target genes that contribute to metabolism and proliferation. This "Myc Network" cross-talks with the "Mlx Network" comprised of the Myc-like bHLH-ZIP proteins MondoA and ChREBP and the Max-like bHLH-ZIP protein Mlx. This "Extended Myc Network" regulates genes with both common and distinct functions. We have generated hepatocytes lacking Mlx (mlxKO) or Mlx+Myc (double KO or DKO) and quantified their abilities to replace dying hepatocytes in a murine model of Type I tyosinemia. We find that this function deteriorates as the Extended Myc Network is progressively dismantled. Genes dysregulated in mlxKO and DKO hepatocytes include those involved in translation and mitochondrial function. The Myc and Mlx Networks thus cross-talk with the latter playing a disproportionate role. mycKO and mlxKO mice also develop non-alcoholic fatty liver disease and mlxKO and DKO mice develop extensive hepatic adenomatosis not observed in wild-type, mycKO, chrebpKO or mycKOxchrebpKO mice. In addition to demonstrating cooperation between the Myc and Mlx Networks, this study reveals the latter to be more important in maintaining metabolic and translational homeostasis, while concurrently serving as a suppressor of benign tumorigenesis.


2019 ◽  
Vol 116 (48) ◽  
pp. 24133-24142 ◽  
Author(s):  
Siu Chiu Chan ◽  
Ying Zhang ◽  
Marco Pontoglio ◽  
Peter Igarashi

Hepatocyte nuclear factor-1β (HNF-1β) is a tissue-specific transcription factor that is essential for normal kidney development and renal tubular function. Mutations of HNF-1β produce cystic kidney disease, a phenotype associated with deregulation of canonical (β-catenin–dependent) Wnt signaling. Here, we show that ablation of HNF-1β in mIMCD3 renal epithelial cells produces hyperresponsiveness to Wnt ligands and increases expression of Wnt target genes, including Axin2, Ccdc80, and Rnf43. Levels of β-catenin and expression of Wnt target genes are also increased in HNF-1β mutant mouse kidneys. Genome-wide chromatin immunoprecipitation sequencing (ChIP-seq) in wild-type and mutant cells showed that ablation of HNF-1β increases by 6-fold the number of sites on chromatin that are occupied by β-catenin. Remarkably, 50% of the sites that are occupied by β-catenin in HNF-1β mutant cells colocalize with HNF-1β–occupied sites in wild-type cells, indicating widespread reciprocal binding. We found that the Wnt target genes Ccdc80 and Rnf43 contain a composite DNA element comprising a β-catenin/lymphoid enhancer binding factor (LEF) site overlapping with an HNF-1β half-site. HNF-1β and β-catenin/LEF compete for binding to this element, and thereby HNF-1β inhibits β-catenin–dependent transcription. Collectively, these studies reveal a mechanism whereby a transcription factor constrains canonical Wnt signaling through direct inhibition of β-catenin/LEF chromatin binding.


Genes ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 995
Author(s):  
Xuhua Xia

Trees and their seeds regulate their germination, growth, and reproduction in response to environmental stimuli. These stimuli, through signal transduction, trigger transcription factors that alter the expression of various genes leading to the unfolding of the genetic program. A regulon is conceptually defined as a set of target genes regulated by a transcription factor by physically binding to regulatory motifs to accomplish a specific biological function, such as the CO-FT regulon for flowering timing and fall growth cessation in trees. Only with a clear characterization of regulatory motifs, can candidate target genes be experimentally validated, but motif characterization represents the weakest feature of regulon research, especially in tree genetics. I review here relevant experimental and bioinformatics approaches in characterizing transcription factors and their binding sites, outline problems in tree regulon research, and demonstrate how transcription factor databases can be effectively used to aid the characterization of tree regulons.


PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0245824
Author(s):  
Otília Menyhart ◽  
Boglárka Weltz ◽  
Balázs Győrffy

Scientists from nearly all disciplines face the problem of simultaneously evaluating many hypotheses. Conducting multiple comparisons increases the likelihood that a non-negligible proportion of associations will be false positives, clouding real discoveries. Drawing valid conclusions require taking into account the number of performed statistical tests and adjusting the statistical confidence measures. Several strategies exist to overcome the problem of multiple hypothesis testing. We aim to summarize critical statistical concepts and widely used correction approaches while also draw attention to frequently misinterpreted notions of statistical inference. We provide a step-by-step description of each multiple-testing correction method with clear examples and present an easy-to-follow guide for selecting the most suitable correction technique. To facilitate multiple-testing corrections, we developed a fully automated solution not requiring programming skills or the use of a command line. Our registration free online tool is available at www.multipletesting.com and compiles the five most frequently used adjustment tools, including the Bonferroni, the Holm (step-down), the Hochberg (step-up) corrections, allows to calculate False Discovery Rates (FDR) and q-values. The current summary provides a much needed practical synthesis of basic statistical concepts regarding multiple hypothesis testing in a comprehensible language with well-illustrated examples. The web tool will fill the gap for life science researchers by providing a user-friendly substitute for command-line alternatives.


Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 36-36
Author(s):  
Jessica M Salmon ◽  
Casie Leigh Reed ◽  
Maddyson Bender ◽  
Helen Lorraine Mitchell ◽  
Vanessa Fox ◽  
...  

Krüppel-like factors (KLFs) are a family of transcription factors that play essential roles in the development and differentiation of the hematopoietic system. These transcription factors possess highly conserved C-terminal zinc-finger motifs, which enable their binding to GC-rich, or CACC-box, motifs in promoter and enhancer regions of target genes. The N-terminal domains of these proteins are more varied and mediate the recruitment of various co-factors, which can form a complex with either activator or repressor function. Acting primarily as a gene repressor through its recruitment of CtBPs and histone deacetylases (HDACs) [1], we have recently shown that KLF3 competes with KLF1 bound sites in the genome to repress gene expression during erythropoiesis [2]. However, the function of Klf3 in other lineages has been less well studied. This widely expressed transcription factor has reported roles in the differentiation of marginal zone B cells, eosinophil function and inflammation [3]. We utilised the Klf3-null mouse model [4] to more closely examine the role of Klf3 in innate inflammatory cells. These mice exhibit elevated white cell counts, including monocytes (Figure 1A), and inflammation of the skin. Conditional knockout of Klf4 in myeloid cells leads to a deficiency of inflammatory macrophages [5]. To test our hypothesis KLF3 normally represses inflammation, perhaps by antagonising the action of KLF4, bone-marrow derived macrophages (BMDM) were generated from wild-type or Klf3-null mice and stimulated with the bacterial toxin lipopolysaccharide (LPS). In wild type BMDM, LPS induces Klf3 gene expression and activation then delayed repression of target genes such as Lgals3 (galectin-3) over a 21 hour time course (Figure 1B). Quantitative real-time PCR and mRNA-seq of WT v Klf3-null macrophages identified ~100 differentially expressed genes involved in proliferation, macrophage activation and inflammation. We transduced the monocyte cell line, RAW264.7 (that expresses Klf4, Klf3 and Klf2), with a retroviral vector expressing a tamoxifen-inducible KLF3-ER fusion construct. KLF3 induced cell cycle arrest and macrophage differentiation. We will report on KLF3-induced gene expression changes (repression and activation), and ChIP-seq for KLF3, in RAW cells. The results shed light on the mechanism by which KLF3 normally represses monocyte/macrophage responses to infection. This study highlights the importance of key transcriptional regulators that tightly control gene expression during inflammation. Loss of Klf3 leads to alterations in this process, resulting in hyper-activation of inflammatory macrophages, increased white cell counts and inflammation of the skin. A greater knowledge of the inflammatory process and how it is regulated is important for our understanding of acute infection and inflammatory disease. Further studies are planned to investigate the role of the KLF3 transcription factor in response to inflammation in vivo. References: 1. Pearson, R., et al., Kruppel-like transcription factors: A functional family. Int J Biochem Cell Biol, 2007. W2. Ilsley, M.D., et al., Kruppel-like factors compete for promoters and enhancers to fine-tune transcription. Nucleic Acids Res, 2017. 45(11): p. 6572-6588. W3. Knights, A.J., et al., Kruppel-like factor 3 (KLF3) suppresses NF-kappaB-driven inflammation in mice. J Biol Chem, 2020. 295(18): p. 6080-6091. W4. Sue, N., et al., Targeted disruption of the basic Kruppel-like factor gene (Klf3) reveals a role in adipogenesis. Mol Cell Biol, 2008. 28(12): p. 3967-78. W5. Alder, J.K., et al., Kruppel-like factor 4 is essential for inflammatory monocyte differentiation in vivo. J Immunol, 2008. 180(8): p. 5645-52. Figure 1: Elevated WCC (A) and inflammatory markers (B) in BMDM after LPS stimulation. 1. Total WCC in adult mice (3-6 months old) of the indicated genotypes. There is a statistically significant increase in the WCC in Klf3-/- v wild type mice (P<0.001 by student's t test). B. Time course (hours) after LPS stimulation of confluent BMDM. Klf3 is induced 3-fold by LPS and KLF3-target genes such as Lgals3 are not fully repressed by 21 hours in knockout mice. Figure 1 Disclosures Perkins: Novartis Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees.


2021 ◽  
Author(s):  
Otília Menyhárt ◽  
Boglárka Weltz ◽  
Balázs Győrffy

ABSTRACTScientists from nearly all disciplines face the problem of simultaneously evaluating many hypotheses. Conducting multiple comparisons increases the likelihood that a non-negligible proportion of associations will be false positives, clouding real discoveries.Drawing valid conclusions require taking into account the number of performed statistical tests and adjusting the statistical confidence measures. Several strategies exist to overcome the problem of multiple hypothesis testing. We aim to summarize critical statistical concepts and widely used correction approaches while also draw attention to frequently misinterpreted notions of statistical inference.We provide a step-by-step description of each multiple-testing correction method with clear examples and present an easy-to-follow guide for selecting the most suitable correction technique.To facilitate multiple-testing corrections, we developed a fully automated solution not requiring programming skills or the use of a command line. Our registration free online tool is available at www.multipletesting.com and compiles the five most frequently used adjustment tools, including the Bonferroni, the Holm (step-down), the Hochberg (step-up) corrections, allows to calculate False Discovery Rates (FDR) and q-values.The current summary provides a much needed practical synthesis of basic statistical concepts regarding multiple hypothesis testing in a comprehensible language with well-illustrated examples. The web tool will fill the gap for life science researchers by providing a user-friendly substitute for command-line alternatives.


2020 ◽  
Author(s):  
Zhiming Dai

AbstractKnockout analysis is a common tool to reveal transcription factor (TF) functions. However, such a reverse genetic analysis based on observed phenotype changes in mutant cell may lead to a misunderstanding of TF wild-type functions. Here, a model was proposed, in which the knockout-observed TF-target regulatory relationships might only occur in mutant cell, and they do not reflect TF normal functions in wild-type cell. Actually, the knockout of one TF might release another TF which is the protein-protein interaction partner of the deleted TF. The free TF could bind its new target genes and cause their significant expression changes. These seemingly TF knockout affected genes are thus not directly regulated by the deleted TF, but are gain-of-regulated genes of the latter TF in mutant cell. Based on this model, multiple sources of genome-wide data were used to identify 20 such TF pairs, and one pair was validated using other independent data. TF wild-type regulatory genes are not associated with their gain-of-regulated genes. My findings revealed TF-target relationships complicated by TF knockout analysis.


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