scholarly journals The ability of transcription factors to differentially regulate gene expression is a crucial component of the mechanism underlying inversion, a frequently observed genetic interaction pattern

2018 ◽  
Author(s):  
Saman Amini ◽  
Annika Jacobsen ◽  
Olga Ivanova ◽  
Philip Lijnzaad ◽  
Jaap Heringa ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Molecular Mechanisms ◽  
Genetic Interaction ◽  
Genetic Diseases ◽  
Mechanistic Explanation ◽  
Genetic Interactions ◽  
Interaction Patterns ◽  
And Inversion ◽  
Complex Genetic Diseases

AbstractGenetic interactions, a phenomenon whereby combinations of mutations lead to unexpected effects, reflect how cellular processes are wired and play an important role in complex genetic diseases. Understanding the molecular basis of genetic interactions is crucial for deciphering pathway organization as well as understanding the relationship between genetic variation and disease. Several putative molecular mechanisms have been linked to different genetic interaction types. However, differences in genetic interaction patterns and their underlying mechanisms have not yet been compared systematically between different functional gene classes. Here, differences in the occurrence and types of genetic interactions are compared for two classes, gene-specific transcription factors (GSTFs) and signaling genes (kinases and phosphatases). Genome-wide gene expression data for 63 single and double deletion mutants in baker’s yeast reveals that the two most common genetic interaction patterns are buffering and inversion. Buffering is typically associated with redundancy and is well understood. In inversion, genes show opposite behavior in the double mutant compared to the corresponding single mutants. The underlying mechanism is poorly understood. Although both classes show buffering and inversion patterns, the prevalence of inversion is much stronger in GSTFs. To decipher potential mechanisms, a Petri Net modeling approach was employed, where genes are represented as nodes and relationships between genes as edges. This allowed over 9 million possible three and four node models to be exhaustively enumerated. The models show that a quantitative difference in interaction strength is a strict requirement for obtaining inversion. In addition, this difference is frequently accompanied with a second gene that shows buffering. Taken together, these results provide a mechanistic explanation for inversion. Furthermore, the ability of transcription factors to differentially regulate expression of their targets provides a likely explanation why inversion is more prevalent for GSTFs compared to kinases and phosphatases.Author SummaryThe relationship between genotype and phenotype is one of the major challenges in biology. While many previous studies have identified genes involved in complex genetic diseases, there is still a gap between genotype and phenotype. One of the difficulties in filling this gap has been attributed to genetic interactions. Large-scale studies have revealed that genetic interactions are widespread in model organisms such as baker’s yeast. Several molecular mechanisms have been proposed for different genetic interaction types. However, differences in occurrence and underlying molecular mechanism of genetic interactions have not yet been compared between gene classes of different function. Here, we compared genetic interaction patterns identified using gene expression profiling for two classes of genes: gene specific transcription factors and signaling related genes. We modelled all possible molecular networks to unravel putative molecular differences underlying different genetic interaction patterns. Our study proposes a new mechanistic explanation for a certain genetic interaction pattern that is more strongly associated with transcription factors compared to signaling related genes. Overall, our findings and the computational methodologies implemented here can be valuable for understanding the molecular mechanisms underlying genetic interactions.

scholarly journals Stress Mediating Genes in Aging, Health, and Longevity Traits: Effects of Multiple Interactions

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 286-286
Author(s):  
Anatoliy Yashin ◽  
Dequing Wu ◽  
Konstantin Arbeev ◽  
Arseniy Yashkin ◽  
Galina Gorbunova ◽  
...  
Keyword(s):  
Strong Interaction ◽  
Genetic Interaction ◽  
Interaction Effects ◽  
Genetic Interactions ◽  
Risk Scores ◽  
Data Sets ◽  
Interaction Patterns ◽  
Polygenic Risk ◽  
Drug Candidates ◽  
Aging Health

Abstract Persistent stress of external or internal origin accelerates aging, increases risk of aging related health disorders, and shortens lifespan. Stressors activate stress response genes, and their products collectively influence traits. The variability of stressors and responses to them contribute to trait heterogeneity, which may cause the failure of clinical trials for drug candidates. The objectives of this paper are: to address the heterogeneity issue; to evaluate collective interaction effects of genetic factors on Alzheimer’s disease (AD) and longevity using HRS data; to identify differences and similarities in patterns of genetic interactions within two genders; and to compare AD related genetic interaction patterns in HRS and LOADFS data. To reach these objectives we: selected candidate genes from stress related pathways affecting AD/longevity; implemented logistic regression model with interaction term to evaluate effects of SNP-pairs on these traits for males and females; constructed the novel interaction polygenic risk scores for SNPs, which showed strong interaction potential, and evaluated effects of these scores on AD/longevity; and compared patterns of genetic interactions within the two genders and within two datasets. We found there were many genes involved in highly significant interactions that were the same and that were different within the two genders. The effects of interaction polygenic risk scores on AD were strong and highly statistically significant. These conclusions were confirmed in analyses of interaction effects on longevity trait using HRS data. Comparison of HRS to LOADFS data showed that many genes had strong interaction effects on AD in both data sets.

scholarly journals Shank3 Modulates Sleep and Expression of Circadian Transcription Factors

2018 ◽  
Author(s):  
Ashley M. Ingiosi ◽  
Taylor Wintler ◽  
Hannah Schoch ◽  
Kristan G. Singletary ◽  
Dario Righelli ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Molecular Mechanisms ◽  
Sleep Problems ◽  
Wheel Running ◽  
The United States ◽  
Autism Spectrum ◽  
Wheel Running Activity ◽  
Falling Asleep ◽  
Circadian Transcription

AbstractAutism Spectrum Disorder (ASD) is the most prevalent neurodevelopmental disorder in the United States and often co-presents with sleep problems. Sleep problems in ASD predict the severity of ASD core diagnostic symptoms and have a considerable impact on the quality of life of caregivers. Little is known, however, about the underlying molecular mechanisms. We investigated the role of Shank3, a high confidence ASD gene candidate, in sleep architecture and regulation. We show that mice lacking exon 21 of Shank3 have problems falling asleep even when sleepy. Using RNA-seq we show that sleep deprivation increases the differences in gene expression between mutants and wild types, downregulating circadian transcription factors Per3, Dec2, Hlf, Tef, and Reverbα. Shank3 mutants also have trouble regulating wheel-running activity in constant darkness. Overall our study shows that Shank3 is an important modulator of sleep and clock gene expression.

scholarly journals The Western Diet Regulates Hippocampal Microvascular Gene Expression: An Integrated Genomic Analyses in Female Mice

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Saivageethi Nuthikattu ◽  
Dragan Milenkovic ◽  
John Rutledge ◽  
Amparo Villablanca
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Differential Expression ◽  
Differential Gene Expression ◽  
Gene Networks ◽  
Molecular Mechanisms ◽  
Western Diet ◽  
Protein Coding ◽  
Female Mice ◽  
Differential Gene

AbstractHyperlipidemia is a risk factor for dementia, and chronic consumption of a Western Diet (WD) is associated with cognitive impairment. However, the molecular mechanisms underlying the development of microvascular disease in the memory centers of the brain are poorly understood. This pilot study investigated the nutrigenomic pathways by which the WD regulates gene expression in hippocampal brain microvessels of female mice. Five-week-old female low-density lipoprotein receptor deficient (LDL-R−/−) and C57BL/6J wild type (WT) mice were fed a chow or WD for 8 weeks. Metabolics for lipids, glucose and insulin were determined. Differential gene expression, gene networks and pathways, transcription factors, and non-protein coding RNAs were evaluated by genome-wide microarray and bioinformatics analysis of laser captured hippocampal microvessels. The WD resulted in differential expression of 2,412 genes. The majority of differential gene expression was attributable to differential regulation of cell signaling proteins and their transcription factors, approximately 7% was attributable to differential expression of miRNAs, and a lesser proportion was due to other non-protein coding RNAs, primarily long non-coding RNAs (lncRNAs) and small nucleolar RNAs (snoRNAs) not previously described to be modified by the WD in females. Our findings revealed that chronic consumption of the WD resulted in integrated multilevel molecular regulation of the hippocampal microvasculature of female mice and may provide one of the mechanisms underlying vascular dementia.

scholarly journals Effects of Cutting, Pruning, and Grafting on the Expression of Age-Related Genes in Larix kaempferi

Forests ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 218
Author(s):  
Yao Zhang ◽  
Qiao-Lu Zang ◽  
Li-Wang Qi ◽  
Su-Ying Han ◽  
Wan-Feng Li
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Regular Expression ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Reproductive Development ◽  
Larix Kaempferi ◽  
Clonal Forestry ◽  
Cdna Sequences ◽  
Age Related

Grafting, cutting, and pruning are important horticultural techniques widely used in the establishment of clonal forestry. After the application of these techniques, some properties of the plants change, however, the underlying molecular mechanisms are still unclear. In our previous study, 27 age-related transcripts were found to be expressed differentially between the juvenile vegetative (1- and 2-year-old) and adult reproductive (25- and 50-year-old) phases of Larix kaempferi. Here, we re-analyzed the 27 age-related transcripts, cloned their full-length cDNA sequences, and measured their responses to grafting, cutting, and pruning. After sequence analysis and cloning, 20 transcription factors were obtained and annotated, most of which were associated with reproductive development, and six (LaAGL2-1, LaAGL2-2, LaAGL2-3, LaSOC1-1, LaAGL11, and LaAP2-2) showed regular expression patterns with L. kaempferi aging. Based on the expression patterns of these transcription factors in L. kaempferi trees subjected to grafting, cutting, and pruning, we concluded that (1) cutting and pruning rejuvenate the plants and change their expression, and the effects of cutting on gene expression are detectable within 14 years, although the cutting seedlings are still maturing during these years; (2) within three months after grafting, the rootstock is more sensitive to grafting than the scion and readily becomes mature with the effect of the scion, while the scion is not readily rejuvenated by the effect of the rootstock; and (3) LaAGL2-2 and LaAGL2-3 are more sensitive to grafting, while LaAP2-2 is impervious to it. These findings not only provide potential molecular markers to assess the state of plants but also aid in studies of the molecular mechanisms of rejuvenation.

scholarly journals Overlapping and Unique Roles for C-Terminal Binding Protein 1 (CtBP1) and CtBP2 during Mouse Development

2002 ◽  
Vol 22 (15) ◽  
pp. 5296-5307 ◽  
Author(s):  
Jeffrey D. Hildebrand ◽  
Philippe Soriano
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Genetic Interaction ◽  
Binding Protein ◽  
Biological Processes ◽  
Vertebrate Development ◽  
Mouse Development ◽  
Axial Patterning ◽  
Wide Range

ABSTRACT The C-terminal binding protein (CtBP) family of proteins has been linked to multiple biological processes through their association with numerous transcription factors. We generated mice harboring mutations in both Ctbp1 and Ctbp2 to address the in vivo function of CtBPs during vertebrate development. Ctbp1 mutant mice are small but viable and fertile, whereas Ctbp2-null mice show defects in axial patterning and die by E10.5 due to aberrant extraembryonic development. Mice harboring various combinations of Ctbp1 and Ctbp2 mutant alleles exhibit dosage-sensitive defects in a wide range of developmental processes. The strong genetic interaction, as well as transcription assays with CtBP-deficient cells, indicates that CtBPs have overlapping roles in regulating gene expression. We suggest that the observed phenotypes reflect the large number of transcription factors whose activities are compromised in the absence of CtBP.

scholarly journals The biological characteristics of transcription factors AP-2α and AP-2γ and their importance in various types of cancers

2019 ◽  
Vol 39 (3) ◽  
Author(s):  
Damian Kołat ◽  
Żaneta Kałuzińska ◽  
Andrzej K. Bednarek ◽  
Elżbieta Płuciennik
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Molecular Mechanisms ◽  
Regulation Of Gene Expression ◽  
Cancer Tissue ◽  
Diagnostic Biomarkers ◽  
Oncological Patients ◽  
Wide Range ◽  
Non Coding Rnas

Abstract The Activator Protein 2 (AP-2) transcription factor (TF) family is vital for the regulation of gene expression during early development as well as carcinogenesis process. The review focusses on the AP-2α and AP-2γ proteins and their dualistic regulation of gene expression in the process of carcinogenesis. Both AP-2α and AP-2γ influence a wide range of physiological or pathological processes by regulating different pathways and interacting with diverse molecules, i.e. other proteins, long non-coding RNAs (lncRNA) or miRNAs. This review summarizes the newest information about the biology of two, AP-2α and AP-2γ, TFs in the carcinogenesis process. We emphasize that these two proteins could have either oncogenic or suppressive characteristics depending on the type of cancer tissue or their interaction with specific molecules. They have also been found to contribute to resistance and sensitivity to chemotherapy in oncological patients. A better understanding of molecular network of AP-2 factors and other molecules may clarify the atypical molecular mechanisms occurring during carcinogenesis, and may assist in the recognition of new diagnostic biomarkers.

scholarly journals A full-length transcriptome and gene expression analysis reveal genes and molecular elements expressed during seed development in Gnetum luofuense

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Nan Deng ◽  
Chen Hou ◽  
Boxiang He ◽  
Fengfeng Ma ◽  
Qingan Song ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Seed Development ◽  
Molecular Mechanisms ◽  
Immature Stage ◽  
Full Length ◽  
Differentially Expressed ◽  
Mature Stage ◽  
Medicinal Uses ◽  
A Site

Abstract Background Gnetum is an economically important tropical and subtropical gymnosperm genus with various dietary, industrial and medicinal uses. Many carbohydrates, proteins and fibers accumulate during the ripening of Gnetum seeds. However, the molecular mechanisms related to this process remain unknown. Results We therefore assembled a full-length transcriptome from immature and mature G. luofuense seeds using PacBio sequencing reads. We identified a total of 5726 novel genes, 9061 alternative splicing events, 3551 lncRNAs, 2160 transcription factors, and we found that 8512 genes possessed at least one poly(A) site. In addition, gene expression comparisons of six transcriptomes generated by Illumina sequencing showed that 14,323 genes were differentially expressed from an immature stage to a mature stage with 7891 genes upregulated and 6432 genes downregulated. The expression of 14 differentially expressed transcription factors from the MADS-box, Aux/IAA and bHLH families was validated by qRT-PCR, suggesting that they may have important roles in seed ripening of G. luofuense. Conclusions These findings provide a valuable molecular resource for understanding seed development of gymnosperms.

Protein Interaction Networks

2006 ◽  
Author(s):  
Soumya Raychaudhuri
Keyword(s):  
Gene Expression ◽  
Protein Interactions ◽  
Large Scale ◽  
Scientific Literature ◽  
Genetic Interaction ◽  
Genetic Interactions ◽  
Protein Protein Interactions ◽  
Expression Array ◽  
Biological Responses ◽  
Altered Gene

Genes and proteins interact with each other in many complicated ways. For example, proteins can interact directly with each other to form complexes or to modify each other so that their function is altered. Gene expression can be repressed or induced by transcription factor proteins. In addition there are countless other types of interactions. They constitute the key physiological steps in regulating or initiating biological responses. For example the binding of transcription factors to DNA triggers the assembly of the RNA assembly machinery that transcribes the mRNA that then is used as the template for protein production. Interactions such as these have been carefully elucidated and have been described in great detail in the scientific literature. Modern assays such as yeast-2-hybrid screens offer rapid means to ascertain many of the potential protein–protein interactions in an organism in a large-scale approach. In addition, other experimental modalities such as gene-expression array assays offer indirect clues about possible genetic interactions. One area that has been greatly explored in the bioinformatics literature is the possibility of learning genetic or protein networks, both from the scientific literature and from large-scale experimental data. Indeed, as we get to know more and more genes, it will become increasingly important to appreciate their interactions with each other. An understanding of the interactions between genes and proteins in a network allows for a meaningful global view of the organism and its physiology and is necessary to better understand biology. In this chapter we will explore methods to either (1) mine the scientific literature to identify documented genetic interactions and build networks of genes or (2) to confirm protein interactions that have been proposed experimentally. Our focus here is on direct physical protein–protein interactions, though the techniques described could be extended to any type of biological interaction between genes or proteins. There are multiple steps that must be addressed in identifying genetic interaction information contained within the text. After compiling the necessary documents and text, the first step is to identify gene and protein names in the text.

Role of Long Coding RNAs in Epigenetic Modulation of Hematopoiesis

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. SCI-28-SCI-28
Author(s):  
Mitchell J. Weiss
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Molecular Mechanisms ◽  
Conflicts Of Interest ◽  
Fetal Liver ◽  
Protein Localization ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Similar Degree ◽  
Erythroid Progenitors

Abstract Long noncoding (Lnc) RNAs are RNA transcripts greater than 200 nucleotides (nt) that regulate gene expression independent of protein coding potential (1-3). It is estimated that thousands of lncRNAs play vital roles in diverse cellular processes. LncRNAs modulate many stages of gene expression by regulating transcription, epigenetics, splicing, translation, and protein localization. We hypothesize that multiple lncRNAs are expressed specifically during erythrocyte and megakaryocyte differentiation, and are likely to have important roles. To identify lncRNAs in erythro-megakaryopoiesis, we performed strand-specific, paired-end deep sequencing (RNA-Seq) to a depth of 200 million reads per sample on two replicates each of murine Ter119+erythroblasts, CD41+ megakaryocytes and bipotential megakaryocyte-erythroid progenitors (MEPs) [lin- Kit+ Sca1- CD16/32- CD34-], and used bioinformatic filtering tools to identify approximately 1,100 candidate lncRNAs. Over 60 percent of these lncRNAs are novel unannotated transcripts with exquisite lineage-specific expression. Using erythroid and megakaryocytic primary cell ChIP-Seq for key transcription factors (TFs) GATA1, TAL1, GATA2,and FLI1, we found that the loci of lncRNAs show similar degree of TF binding as coding genes. We used the erythroid line G1E-ER4 (which expresses estrogen-activated GATA1) to confirm that lncRNAs bound by GATA1 are also directly regulated by it. Furthermore, we used histone methylation ChIP-Seq to show that most lncRNAs arise from classical “promoters” with high H3K4me3 levels and low H3K4me1 levels. Thus, we find that lncRNAs show epigenetic features similar to the promoters of coding genes and are directly regulated by similar TF networks. Comparison of the transcriptomes of mouse fetal liver and human cord blood erythroblasts demonstrated that lncRNAs are expressed in a highly species-specific fashion, i.e., most lncRNAs identifiable in one species are not transcribed in the other, even though the corresponding genomic region is present in both species. Numerous non-conserved but functional lncRNAs are reported in the literature, and the significance of conservation in lncRNA biology is greatly debated. In order to identify functional lncRNAs, we are currently performing RNAi knockdown on numerous candidates to assess how loss of function affects erythroid maturation. We are also performing HITS-CLIP of key chromatin modifying complexes and erythroid transcription factors to identify lncRNAs bound to them. Our studies are beginning to define new layers of gene regulation in normal erythro-megakaryopoiesis, which may be relevant to the pathophysiology of related disorders including various anemias, myeloproliferative and myelodysplastic syndromes and leukemias. 1. Wang K.C., Chang H.Y. Molecular mechanisms of long noncoding RNAs. Molecular Cell. 2011;43(6):904-914. Prepublished on 2011/09/20 as DOI 10.1016/j.molcel.2011.08.018. 2. Hu W., Alvarez-Dominguez J.R., Lodish H.F. Regulation of mammalian cell differentiation by long non-coding RNAs. EMBO reports. 2012;13(11):971-983. Prepublished on 2012/10/17 as DOI 10.1038/embor.2012.145. 3. Paralkar V.R., Weiss M.J. Long noncoding RNAs in biology and hematopoiesis. Blood. 2013;121(24):4842-4846. Prepublished on 2013/05/07 as DOI 10.1182/blood-2013-03-456111. Disclosures: No relevant conflicts of interest to declare.

Hox transcription factors: an overview of multi-step regulators of gene expression

2018 ◽  
Vol 62 (11-12) ◽  
pp. 723-732 ◽  
Author(s):  
Julie Carnesecchi ◽  
Pedro B. Pinto ◽  
Ingrid Lohmann
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Cell Fates ◽  
Hox Proteins ◽  
Regulatory Modules ◽  
Genome Wide ◽  
Transcription Complexes ◽  
Regulatory Functions

Hox transcription factors (TFs) function as key determinants in the specification of cell fates during development. They do so by triggering entire morphogenetic cascades through the activation of specific target genes. In contrast to their fundamental role in development, the molecular mechanisms employed by Hox TFs are still poorly understood. In recent years, a new picture has emerged regarding the function of Hox proteins in gene regulation. Initial studies have primarily focused on understanding how Hox TFs recognize and bind specific enhancers to activate defined Hox targets. However, genome-wide studies on the interactions and dynamics of Hox proteins have revealed a more elaborate function of the Hox factors. It is now known that Hox proteins are involved in several steps of gene expression with potential regulatory functions in the modification of the chromatin landscape and its accessibility, recognition and activation of specific cis-regulatory modules, assembly and activation of promoter transcription complexes and mRNA processing. In the coming years, the characterization of the molecular activity of Hox TFs in these mechanisms will greatly contribute to our general understanding of Hox activity.

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