scholarly journals Bayesian Linear Mixed Models for Motif Activity Analysis

2019 ◽  
Author(s):  
Simone Lederer ◽  
Tom Heskes ◽  
Simon J. van Heeringen ◽  
Cornelis A. Albers
Keyword(s):  
Gene Expression ◽  
Dna Sequences ◽  
Ridge Regression ◽  
Mixed Model ◽  
Target Genes ◽  
Linear Mixed Model ◽  
Covariance Structure ◽  
Regulatory Elements ◽  
Mathematical Explanation ◽  
Experimental Conditions

AbstractMotivationCellular identity and behavior is controlled by complex gene regulatory networks. Transcription factors (TFs) bind to specific DNA sequences to regulate the transcription of their target genes. On the basis of these TF motifs in cis-regulatory elements we can model the influence of TFs on gene expression. In such models of TF motif activity the data is usually modeled assuming a linear relationship between the motif activity and the gene expression level. A commonly used method to model motif influence is based on Ridge Regression. One important assumption of linear regression is the independence between samples. However, if samples are generated from the same cell line, tissue, or other biological source, this assumption may be invalid. This same assumption of independence is also applied to different, yet similar, experimental conditions, which may also be inappropriate. In theory, the independence assumption between samples could lead to loss in signal detection. Here we investigate whether a Bayesian model that allows for correlations results in more accurate inference of motif activities.ResultsWe extend the Ridge Regression to a Bayesian Linear Mixed Model, which allows us to model dependence between different samples. In a simulation study, we in-vestigate the differences between the two model assumptions. We show that our Bayesian Linear Mixed Model implementation outperforms Ridge Regression in a simulation scenario where the noise, the signal that can not be explained by TF motifs, is uncorrelated. However, we demonstrate that there is no such gain in performance if the noise has a similar covariance structure over samples as the signal that can be explained by motifs. We give a mathematical explanation to why this is the case. Using two representative real data sets we show that at most ∼ 40% of the signal is explained by motifs using the linear model. With these data there is no advantage to using the Bayesian Linear Mixed Model, due to the similarity of the covariance structure.Availability & ImplementationThe project implementation is available at https://github.com/Sim19/SimGEXPwMotifs.

scholarly journals t(8;21)(q22;q22) fusion proteins preferentially bind to duplicated AML1/RUNX1 DNA-binding sequences to differentially regulate gene expression

Blood ◽  
2008 ◽  
Vol 112 (4) ◽  
pp. 1392-1401 ◽  
Author(s):  
Akiko J. Okumura ◽  
Luke F. Peterson ◽  
Fumihiko Okumura ◽  
Anita Boyapati ◽  
Dong-Er Zhang
Keyword(s):  
Gene Expression ◽  
Dna Binding ◽  
Binding Site ◽  
Dna Sequences ◽  
Fusion Proteins ◽  
Target Genes ◽  
Regulatory Elements ◽  
Chromosome Abnormalities ◽  
Cancer Development ◽  
Dna Binding Site

AbstractChromosome abnormalities are frequently associated with cancer development. The 8;21(q22;q22) chromosomal translocation is one of the most common chromosome abnormalities identified in leukemia. It generates fusion proteins between AML1 and ETO. Since AML1 is a well-defined DNA-binding protein, AML1-ETO fusion proteins have been recognized as DNA-binding proteins interacting with the same consensus DNA-binding site as AML1. The alteration of AML1 target gene expression due to the presence of AML1-ETO is related to the development of leukemia. Here, using a 25-bp random double-stranded oligonucleotide library and a polymerase chain reaction (PCR)-based DNA-binding site screen, we show that compared with native AML1, AML1-ETO fusion proteins preferentially bind to DNA sequences with duplicated AML1 consensus sites. This finding is further confirmed by both in vitro and in vivo DNA-protein interaction assays. These results suggest that AML1-ETO fusion proteins have a selective preference for certain AML1 target genes that contain multimerized AML1 consensus sites in their regulatory elements. Such selected regulation provides an important molecular mechanism for the dysregulation of gene expression during cancer development.

scholarly journals Gene Expression Networks in the Drosophila Genetic Reference Panel

2019 ◽  
Author(s):  
Logan J. Everett ◽  
Wen Huang ◽  
Shanshan Zhou ◽  
Mary Anna Carbone ◽  
Richard F. Lyman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transposable Elements ◽  
Dna Sequences ◽  
Quantitative Trait ◽  
Regulatory Networks ◽  
Target Genes ◽  
Reference Panel ◽  
Modern Biology ◽  
Specific Expression ◽  
Drosophila Genetic Reference Panel

SummaryA major challenge in modern biology is to understand how naturally occurring variation in DNA sequences affects complex organismal traits through networks of intermediate molecular phenotypes. Here, we performed deep RNA sequencing of 200 Drosophila Genetic Reference Panel inbred lines with complete genome sequences, and mapped expression quantitative trait loci for annotated genes, novel transcribed regions (most of which are long noncoding RNAs), transposable elements and microbial species. We identified host variants that affect expression of transposable elements, independent of their copy number, as well as microbiome composition. We constructed sex-specific expression quantitative trait locus regulatory networks. These networks are enriched for novel transcribed regions and target genes in heterochromatin and euchromatic regions of reduced recombination, and genes regulating transposable element expression. This study provides new insights regarding the role of natural genetic variation in regulating gene expression and generates testable hypotheses for future functional analyses.

scholarly journals HCR-FlowFISH: A flexible CRISPR screening method to identify cis-regulatory elements and their target genes

2020 ◽  
Author(s):  
SK Reilly ◽  
SJ Gosai ◽  
A Gutierrez ◽  
JC Ulirsch ◽  
M Kanai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Screening Method ◽  
Cell Types ◽  
Regulatory Elements ◽  
Hybridization Chain Reaction ◽  
Genome Wide ◽  
Wide Range ◽  
Causal Variants ◽  
Endogenous Loci

AbstractCRISPR screens for cis-regulatory elements (CREs) have shown unprecedented power to endogenously characterize the non-coding genome. To characterize CREs we developed HCR-FlowFISH (Hybridization Chain Reaction Fluorescent In-Situ Hybridization coupled with Flow Cytometry), which directly quantifies native transcripts within their endogenous loci following CRISPR perturbations of regulatory elements, eliminating the need for restrictive phenotypic assays such as growth or transcript-tagging. HCR-FlowFISH accurately quantifies gene expression across a wide range of transcript levels and cell types. We also developed CASA (CRISPR Activity Screen Analysis), a hierarchical Bayesian model to identify and quantify CRE activity. Using >270,000 perturbations, we identified CREs for GATA1, HDAC6, ERP29, LMO2, MEF2C, CD164, NMU, FEN1 and the FADS gene cluster. Our methods detect subtle gene expression changes and identify CREs regulating multiple genes, sometimes at different magnitudes and directions. We demonstrate the power of HCR-FlowFISH to parse genome-wide association signals by nominating causal variants and target genes.

scholarly journals Evolutionary Analysis of Transcriptional Regulation Mediated by Cdx2 in Rodents

2021 ◽  
Author(s):  
Weizheng Liang ◽  
Guipeng Li ◽  
Huanhuan Cui ◽  
Yukai Wang ◽  
Wencheng Wei ◽  
...  
Keyword(s):  
Gene Expression ◽  
Amino Acid ◽  
Dna Binding ◽  
Target Genes ◽  
Embryonic Stem ◽  
Regulatory Elements ◽  
Evolutionary Analysis ◽  
Protein Sequence Analysis ◽  
Functional Differences ◽  
Transcriptional Effect

Abstract Background: Differences in gene expression, which arises from divergence in cis-regulatory elements or alterations in transcription factors (TFs) binding specificity, are one of the most important causes of phenotypic diversity during evolution. On one hand, changes in the cis-elements located in the vicinity of target genes affect TF binding and/or local chromatin environment, thereby modulating gene expression in one-to-one manner. On the other hand, alterations in trans-factors influence the expression of their target genes in a more pleiotropic fashion. Although evolution of amino acid sequences is much slower than that of non-coding regulatory elements, particularly for the TF DNA binding domains (DBD)， it is still possible that changes in TF-DBD might have the potential to drive large phenotypic changes if the resulting effects have a net positive effect on the organism’s fitness. If so, species-specific changes in TF-DBD might be positively selected. So far, however, this possibility has been largely unexplored.Results: By protein sequence analysis, we observed high sequence conservation in the DNA binding domain (DBD) of the transcription factor Cdx2 across many vertebrates, whereas three amino acid changes were exclusively found in mouse Cdx2 (mCdx2), suggesting potential positive selection in the mouse lineage. Multi-omics analyses were then carried out to investigate the effects of these changes. Surprisingly, there were no significant functional differences between mCdx2 and its rat homologue (rCdx2), and none of the three amino acid changes had any impact on its function. Finally, we used rat-mouse allodiploid embryonic stem cells (RMES) to study the cis effects of Cdx2-mediated gene regulation between the two rodents. Interestingly, whereas Cdx2 binding is largely divergent between mouse and rat, the transcriptional effect induced by Cdx2 is conserved to a much larger extent.Conclusions: There were no significant functional differences between mCdx2 and its rat homologue (rCdx2), and none of the three amino acid changes had any impact on its function. Moreover, Cdx2 binding is largely divergent between mouse and rat, the transcriptional effect induced by Cdx2 is conserved to a much larger extent.

New insights into promoter–enhancer communication mechanisms revealed by dynamic single-molecule imaging

2021 ◽  
Author(s):  
Jieru Li ◽  
Alexandros Pertsinidis
Keyword(s):  
Gene Expression ◽  
Single Molecule ◽  
Target Genes ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Single Molecule Imaging ◽  
Cell Type ◽  
Regulatory Information ◽  
Cell Type Specific ◽  
Target Promoters

Establishing cell-type-specific gene expression programs relies on the action of distal enhancers, cis-regulatory elements that can activate target genes over large genomic distances — up to Mega-bases away. How distal enhancers physically relay regulatory information to target promoters has remained a mystery. Here, we review the latest developments and insights into promoter–enhancer communication mechanisms revealed by live-cell, real-time single-molecule imaging approaches.

263 USE OF PORCINE PARTHENOTES AND GENE EXPRESSION PROFILING USING MICROARRAYS FOR IDENTIFICATION OF IMPRINTED GENES

2006 ◽  
Vol 18 (2) ◽  
pp. 239
Author(s):  
J. Piedrahita ◽  
S. Bischoff ◽  
J. Estrada ◽  
B. Freking ◽  
D. Nonneman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Candidate Genes ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Expression Profiles ◽  
Mammalian Species ◽  
Polar Body ◽  
Gene Expression Profiles ◽  
Tissue Type ◽  
Imprinted Genes

Genomic imprinting arises from differential epigenetic markings including DNA methylation and histone modifications and results in one allele being expressed in a parent-of-origin specific manner. For further insight into the porcine epigenome, gene expression profiles of parthenogenetic (PRT; two maternally derived chromosome sets) and biparental embryos (BP; one maternal and one paternal set of chromosomes) were compared using microarrays. Comparison of the expression profiles of the two tissue types permits identification of both maternally and paternally imprinted genes and thus the degree of conservation of imprinted genes between swine and other mammalian species. Diploid porcine parthenogenetic fetuses were generated using follicular oocytes (BOMED, Madison, WI, USA). Oocytes with a visible polar body were activated using a single square pulse of direct current of 50 V/mm for 100 �s and diploidized by culture in 10 �g/mL cycloheximide for 6 h to limit extrusion of the second polar body. Following culture, BP embryos obtained by natural matings, and PRT embryos, were surgically transferred to oviducts on the first day of estrus. Fetuses recovered at 28-30 days of gestation were dissected to separate viscera including brain, liver, and placenta; the visceral tissues were then flash-frozen in liquid nitrogen. Porcine fibroblast tissue was obtained from the remaining carcass by mincing, trypsinization, and plating cells in �-MEM. Total RNA was extracted from frozen tissue or cell culture using RNA Aqueous kit (Ambion, Austin, TX, USA) according to the manufacturer's protocol. Gene expression differences between BP and PRT tissues were determined using the GeneChip� Porcine Genome Array (Affymetrix, Santa Clara, CA) containing 23 256 transcripts from Sus scrofa and representing 42 genes known to be imprinted in human and/or mice. Triplicate arrays were utilized for each tissue type, and for PRT versus BP combination. Significant differential gene expression was identified by a linear mixed model analysis using SAS 5.0 (SAS Institute, Cary, NC, USA). Storey's q-value method was used to correct for multiple testing at q d 0.05. The following genes were classified as imprinted on the basis of their expression profiles: In fibroblasts, ARHI, HTR2A, MEST, NDN, NNAT, PEG3, PLAGL1, PEG10, SGCE, SNRPN, and UBE3A; in liver, IGF2, PEG3, PLAGL1, PEG10, and SNRPN; in placenta, HTR2A, IGF2, MEST, NDN, NNAT, PEG3, PLAGL1, PEG10, and SNRPN; and in brain, none. Additionally, several genes not known to be imprinted in humans/mice were highly differentially expressed between the two tissue types. Overall, utilizing the PRT models and gene expression profiles, we have identified thirteen genes where imprinting is conserved between swine and humans/mice, and several candidate genes that represent potentially imprinted genes. Presently, our efforts are focused in the identification of single nucleotide polymorphisms (SNPs) to more carefully evaluate the behavior of these genes in normal and abnormal gestations and to test whether the candidate genes are indeed imprinted. This research was supported by USDA-CSREES grant 524383 to J. P. and B. F.

scholarly journals Modeling gene regulation from paired expression and chromatin accessibility data

2017 ◽  
Vol 114 (25) ◽  
pp. E4914-E4923 ◽  
Author(s):  
Zhana Duren ◽  
Xi Chen ◽  
Rui Jiang ◽  
Yong Wang ◽  
Wing Hung Wong
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
Joint Modeling ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Exciting Opportunity ◽  
Transcriptional Regulatory ◽  
Dna Elements ◽  
Context Specific

The rapid increase of genome-wide datasets on gene expression, chromatin states, and transcription factor (TF) binding locations offers an exciting opportunity to interpret the information encoded in genomes and epigenomes. This task can be challenging as it requires joint modeling of context-specific activation of cis-regulatory elements (REs) and the effects on transcription of associated regulatory factors. To meet this challenge, we propose a statistical approach based on paired expression and chromatin accessibility (PECA) data across diverse cellular contexts. In our approach, we model (i) the localization to REs of chromatin regulators (CRs) based on their interaction with sequence-specific TFs, (ii) the activation of REs due to CRs that are localized to them, and (iii) the effect of TFs bound to activated REs on the transcription of target genes (TGs). The transcriptional regulatory network inferred by PECA provides a detailed view of how trans- and cis-regulatory elements work together to affect gene expression in a context-specific manner. We illustrate the feasibility of this approach by analyzing paired expression and accessibility data from the mouse Encyclopedia of DNA Elements (ENCODE) and explore various applications of the resulting model.

scholarly journals Beyond the ENCODE project: using genomics and epigenomics strategies to study enhancer evolution

2013 ◽  
Vol 368 (1632) ◽  
pp. 20130022 ◽  
Author(s):  
Noboru Jo Sakabe ◽  
Marcelo A. Nobrega
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Expression Patterns ◽  
Dna Interaction ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Genome Wide ◽  
Identify Transcription Factor ◽  
Specific Proteins ◽  
Species Specific

The complex expression patterns observed for many genes are often regulated by distal transcription enhancers. Changes in the nucleotide sequences of enhancers may therefore lead to changes in gene expression, representing a central mechanism by which organisms evolve. With the development of the experimental technique of chromatin immunoprecipitation (ChIP), in which discrete regions of the genome bound by specific proteins can be identified, it is now possible to identify transcription factor binding events (putative cis -regulatory elements) in entire genomes. Comparing protein–DNA binding maps allows us, for the first time, to attempt to identify regulatory differences and infer global patterns of change in gene expression across species. Here, we review studies that used genome-wide ChIP to study the evolution of enhancers. The trend is one of high divergence of cis -regulatory elements between species, possibly compensated by extensive creation and loss of regulatory elements and rewiring of their target genes. We speculate on the meaning of the differences observed and discuss that although ChIP experiments identify the biochemical event of protein–DNA interaction, it cannot determine whether the event results in a biological function, and therefore more studies are required to establish the effect of divergence of binding events on species-specific gene expression.

Hand Hygiene With Alcohol-Based Hand Rub: How Long Is Long Enough?

2017 ◽  
Vol 38 (5) ◽  
pp. 547-552 ◽  
Author(s):  
Daniela Pires ◽  
Hervé Soule ◽  
Fernando Bellissimo-Rodrigues ◽  
Angèle Gayet-Ageron ◽  
Didier Pittet
Keyword(s):  
Hand Hygiene ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Random Effect ◽  
Healthcare Personnel ◽  
Infection Prevention And Control ◽  
Bacterial Reduction ◽  
Experimental Conditions ◽  
Bacterial Counts ◽  
Hand Rubbing

BACKGROUNDHand hygiene is the core element of infection prevention and control. The optimal hand-hygiene gesture, however, remains poorly defined.OBJECTIVEWe aimed to evaluate the influence of hand-rubbing duration on the reduction of bacterial counts on the hands of healthcare personnel (HCP).METHODSWe performed an experimental study based on the European Norm 1500. Hand rubbing was performed for 10, 15, 20, 30, 45, or 60 seconds, according to the WHO technique using 3 mL alcohol-based hand rub. Hand contamination with E. coli ATCC 10536 was followed by hand rubbing and sampling. A generalized linear mixed model with a random effect on the subject adjusted for hand size and gender was used to analyze the reduction in bacterial counts after each hand-rubbing action. In addition, hand-rubbing durations of 15 and 30 seconds were compared to assert non-inferiority (0.6 log10).RESULTSIn total, 32 HCP performed 123 trials. All durations of hand rubbing led to significant reductions in bacterial counts (P<.001). Reductions achieved after 10, 15, or 20 seconds of hand rubbing were not significantly different from those obtained after 30 seconds. The mean bacterial reduction after 15 seconds of hand rubbing was 0.11 log10 lower (95% CI, −0.46 to 0.24) than after 30 seconds, demonstrating non-inferiority.CONCLUSIONSHand rubbing for 15 seconds was not inferior to 30 seconds in reducing bacterial counts on hands under the described experimental conditions. There was no gain in reducing bacterial counts from hand rubbing longer than 30 seconds. Further studies are needed to assess the clinical significance of our findings.Infect Control Hosp Epidemiol 2017;38:547–552

scholarly journals Deep Sclerectomy with Goniosynechiolysis Ab Interno for Chronic Glaucoma Associated with Peripheral Anterior Synechiae

2015 ◽  
Vol 2015 ◽  
pp. 1-5 ◽  
Author(s):  
Alireza Mirshahi ◽  
Peter Raak ◽  
Katharina Ponto ◽  
Bernhard Stoffelns ◽  
Katrin Lorenz ◽  
...  
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Covariance Structure ◽  
Glaucoma Surgery ◽  
Deep Sclerectomy ◽  
Chronic Glaucoma ◽  
Target Pressure ◽  
The Mean ◽  
One Year ◽  
Ab Interno

Purpose. To report one-year results of phacoemulsification combined with deep sclerectomy and goniosynechiolysis ab interno for chronic glaucoma associated with peripheral anterior synechiae (PAS).Methods. We retrospectively analyzed medical charts of 16 patients (20 eyes) treated by one-site combined phacoemulsification and deep sclerectomy with goniosynechiolysis ab interno. PAS were transected by a spatula introduced into the anterior chamber through a paracentesis. To account for the correlation of right and left eyes a linear mixed model with unstructured covariance structure was calculated.Results. The mean preoperative intraocular pressure (IOP) was20.3±5.2 mmHg with2.4±1.0medications. One year postoperatively, the mean IOP was15.3±3.3 mmHg (P=0.004, pairedt-test) with0.6±1.0medications. A postoperative IOP of ≤21 mmHg without medication was achieved in 17 of 19 eyes (89.5%) and in 12/19 eyes (63.2%) at 3 and 12 months after surgery, respectively. In the remaining eyes (10.5% at 3 months and 36.8% at 12 months), additional medication led to an IOP ≤21 mmHg or the target pressure. No case required further glaucoma surgery. In one eye, conversion of the surgery to trabeculectomy was necessary due to Descemet’s window rupture.Conclusions. With goniosynechiolysis ab interno, effective and safe nonpenetrating glaucoma surgery is possible in presence of PAS.

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