scholarly journals Conserved immunomodulatory transcriptional networks underlie antipsychotic-induced weight gain

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rizaldy C. Zapata ◽  
Besma S. Chaudry ◽  
Mariela Lopez Valencia ◽  
Dinghong Zhang ◽  
Scott A. Ochsner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Weight Gain ◽  
Regulatory Networks ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Whole Body ◽  
Transcriptional Networks ◽  
Gene Set ◽  
P Gene ◽  
Whole Body Metabolism

AbstractAlthough antipsychotics, such as olanzapine, are effective in the management of psychiatric conditions, some patients experience excessive antipsychotic-induced weight gain (AIWG). To illuminate pathways underlying AIWG, we compared baseline blood gene expression profiles in two cohorts of mice that were either prone (AIWG-P) or resistant (AIWG-R) to weight gain in response to olanzapine treatment for two weeks. We found that transcripts elevated in AIWG-P mice relative to AIWG-R are enriched for high-confidence transcriptional targets of numerous inflammatory and immunomodulatory signaling nodes. Moreover, these nodes are themselves enriched for genes whose disruption in mice is associated with reduced body fat mass and slow postnatal weight gain. In addition, we identified gene expression profiles in common between our mouse AIWG-P gene set and an existing human AIWG-P gene set whose regulation by immunomodulatory transcription factors is highly conserved between species. Finally, we identified striking convergence between mouse AIWG-P transcriptional regulatory networks and those associated with body weight and body mass index in humans. We propose that immunomodulatory transcriptional networks drive AIWG, and that these networks have broader conserved roles in whole body-metabolism.

scholarly journals Comparative transcriptomics identifies differences in the regulation of the floral transition between Arabidopsis and Brassica rapa cultivars

2020 ◽  
Author(s):  
Alexander Calderwood ◽  
Jo Hepworth ◽  
Shannon Woodhouse ◽  
Lorelei Bilham ◽  
D. Marc Jones ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brassica Rapa ◽  
Regulatory Networks ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Detailed Comparison ◽  
Developmental Time ◽  
Floral Transition ◽  
Gene Regulatory

AbstractThe timing of the floral transition affects reproduction and yield, however its regulation in crops remains poorly understood. Here, we use RNA-Seq to determine and compare gene expression dynamics through the floral transition in the model species Arabidopsis thaliana and the closely related crop Brassica rapa. A direct comparison of gene expression over time between species shows little similarity, which could lead to the inference that different gene regulatory networks are at play. However, these differences can be largely resolved by synchronisation, through curve registration, of gene expression profiles. We find that different registration functions are required for different genes, indicating that there is no common ‘developmental time’ to which Arabidopsis and B. rapa can be mapped through gene expression. Instead, the expression patterns of different genes progress at different rates. We find that co-regulated genes show similar changes in synchronisation between species, suggesting that similar gene regulatory sub-network structures may be active with different wiring between them. A detailed comparison of the regulation of the floral transition between Arabidopsis and B. rapa, and between two B. rapa accessions reveals different modes of regulation of the key floral integrator SOC1, and that the floral transition in the B. rapa accessions is triggered by different pathways, even when grown under the same environmental conditions. Our study adds to the mechanistic understanding of the regulatory network of flowering time in rapid cycling B. rapa under long days and highlights the importance of registration methods for the comparison of developmental gene expression data.

scholarly journals Convergent evolution of venom gland transcriptomes across Metazoa

2021 ◽  
Author(s):  
Giulia Zancolli ◽  
Maarten Reijnders ◽  
Robert Waterhouse ◽  
Marc Robinson-Rechavi
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Venom Gland ◽  
Bioactive Molecules ◽  
Specific Gene ◽  
Animal Kingdom ◽  
Venom Glands

Animals have repeatedly evolved specialized organs and anatomical structures to produce and deliver a cocktail of potent bioactive molecules to subdue prey or predators: venom. This makes it one of the most widespread convergent functions in the animal kingdom. Whether animals have adopted the same genetic toolkit to evolved venom systems is a fascinating question that still eludes us. Here, we performed the first comparative analysis of venom gland transcriptomes from 20 venomous species spanning the main Metazoan lineages, to test whether different animals have independently adopted similar molecular mechanisms to perform the same function. We found a strong convergence in gene expression profiles, with venom glands being more similar to each other than to any other tissue from the same species, and their differences closely mirroring the species phylogeny. Although venom glands secrete some of the fastest evolving molecules (toxins), their gene expression does not evolve faster than evolutionarily older tissues. We found 15 venom gland specific gene modules enriched in endoplasmic reticulum stress and unfolded protein response pathways, indicating that animals have independently adopted stress response mechanisms to cope with mass production of toxins. This, in turns, activates regulatory networks for epithelial development, cell turnover and maintenance which seem composed of both convergent and lineage-specific factors, possibly reflecting the different developmental origins of venom glands. This study represents the first step towards an understanding of the molecular mechanisms underlying the repeated evolution of one of the most successful adaptive traits in the animal kingdom.

scholarly journals Technique of Gene Expression Profiles Extraction Based on the Complex Use of Clustering and Classification Methods

Diagnostics ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 584
Author(s):  
Sergii Babichev ◽  
Jiří Škvor
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Fuzzy Inference ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Quality Criterion ◽  
Gene Expressions ◽  
Inference System ◽  
Stepwise Procedure ◽  
Binary Classifiers

In this paper, we present the results of the research concerning extraction of informative gene expression profiles from high-dimensional array of gene expressions considering the state of patients’ health using clustering method, ML-based binary classifiers and fuzzy inference system. Applying of the proposed stepwise procedure can allow us to extract the most informative genes taking into account both the subtypes of disease or state of the patient’s health for further reconstruction of gene regulatory networks based on the allocated genes and following simulation of the reconstructed models. We used the publicly available gene expressions data as the experimental ones which were obtained using DNA microarray experiments and contained two types of patients’ gene expression profiles—the patients with lung cancer tumor and healthy patients. The stepwise procedure of the data processing assumes the following steps—in the beginning, we reduce the number of genes by removing non-informative genes in terms of statistical criteria and Shannon entropy; then, we perform the stepwise hierarchical clustering of gene expression profiles at hierarchical levels from 1 to 10 using the SOTA (Self-Organizing Tree Algorithm) clustering algorithm with correlation distance metric. The quality of the obtained clustering was evaluated using the complex clustering quality criterion which is considered both the gene expression profiles distribution relative to center of the clusters where these gene expression profiles are allocated and the centers of the clusters distribution. The result of this stage execution was a selection of the optimal cluster at each of the hierarchical levels which corresponded to the minimum value of the quality criterion. At the next step, we have implemented a classification procedure of the examined objects using four well known binary classifiers—logistic regression, support-vector machine, decision trees and random forest classifier. The effectiveness of the appropriate technique was evaluated based on the use of ROC (Receiver Operating Characteristic) analysis using criteria, included as the components, the errors of both the first and the second kinds. The final decision concerning the extraction of the most informative subset of gene expression profiles was taken based on the use of the fuzzy inference system, the inputs of which are the results of the appropriate single classifiers operation and the output is the final solution concerning state of the patient’s health. To our mind, the implementation of the proposed stepwise procedure of the informative gene expression profiles extraction create the conditions for the increasing effectiveness of the further procedure of gene regulatory networks reconstruction and the following simulation of the reconstructed models considering the subtypes of the disease and/or state of the patient’s health.

scholarly journals RNA-seq Analysis Reveals Gene Expression Profiling of Female Fertile and Sterile Ovules of Pinus Tabulaeformis Carr. during Free Nuclear Mitosis of the Female Gametophyte

2018 ◽  
Vol 19 (8) ◽  
pp. 2246 ◽  
Author(s):  
Yang Yao ◽  
Rui Han ◽  
Zaixin Gong ◽  
Caixia Zheng ◽  
Yuanyuan Zhao
Keyword(s):  
Gene Expression ◽  
Female Gametophyte ◽  
Expression Profiles ◽  
Signal Transduction Pathway ◽  
Gene Expression Profiles ◽  
Pinus Tabulaeformis ◽  
Cdna Libraries ◽  
Pcr Analysis ◽  
Transcriptional Networks ◽  
Ovule Development

The development of the female gametophyte (FG) is one of the key processes of life cycle alteration between the haploid gametophyte and the diploid sporophytes in plants and it is required for successful seed development after fertilization. It is well demonstrated that free nuclear mitosis (FNM) of FG is crucial for the development of the ovule. However, studies of the molecular mechanism of ovule and FG development focused mainly on angiosperms, such as Arabidopsis thaliana and further investigation of gymnosperms remains to be completed. Here, Illumina sequencing of six transcriptomic libraries obtained from developing and abortive ovules at different stages during free nuclear mitosis of magagametophyte (FNMM) was used to acquire transcriptome data and gene expression profiles of Pinus tabulaeformis. Six cDNA libraries generated a total of 71.0 million high-quality clean reads that aligned with 63,449 unigenes and the comparison between developing and abortive ovules identified 7174 differentially expressed genes (DEGs). From the functional annotation results, DEGs involved in the cell cycle and phytohormone regulation were highlighted to reveal their biological importance in ovule development. Furthermore, validation of DEGs from the phytohormone signal transduction pathway was performed using quantitative real-time PCR analysis, revealing the dynamics of transcriptional networks and potential key components in the regulation of FG development in P. tabulaeformis were identified. These findings provide new insights into the regulatory mechanisms of ovule development in woody gymnosperms.

scholarly journals Gene Expression Profiles Suggest a Better Cold Acclimation of Polyploids in the Alpine Species Ranunculus kuepferi (Ranunculaceae)

Genes ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1818
Author(s):  
Eleni Syngelaki ◽  
Claudia Paetzold ◽  
Elvira Hörandl
Keyword(s):  
Gene Expression ◽  
Cold Stress ◽  
Cold Acclimation ◽  
Temperature Stress ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Distribution Patterns ◽  
Gene Set ◽  
Cation Homeostasis ◽  
Response To Temperature

Alpine habitats are shaped by harsh abiotic conditions and cold climates. Temperature stress can affect phenotypic plasticity, reproduction, and epigenetic profiles, which may affect acclimation and adaptation. Distribution patterns suggest that polyploidy seems to be advantageous under cold conditions. Nevertheless, whether temperature stress can induce gene expression changes in different cytotypes, and how the response is initialized through gene set pathways and epigenetic control remain vague for non-model plants. The perennial alpine plant Ranunculus kuepferi was used to investigate the effect of cold stress on gene expression profiles. Diploid and autotetraploid individuals were exposed to cold and warm conditions in climate growth chambers and analyzed via transcriptome sequencing and qRT-PCR. Overall, cold stress changed gene expression profiles of both cytotypes and induced cold acclimation. Diploids changed more gene set pathways than tetraploids, and suppressed pathways involved in ion/cation homeostasis. Tetraploids mostly activated gene set pathways related to cell wall and plasma membrane. An epigenetic background for gene regulation in response to temperature conditions is indicated. Results suggest that perennial alpine plants can respond to temperature extremes via altered gene expression. Tetraploids are better acclimated to cold conditions, enabling them to colonize colder climatic areas in the Alps.

scholarly journals VariED: the first integrated database of gene annotation and expression profiles for variants related to human diseases

Database ◽  
2019 ◽  
Vol 2019 ◽  
Author(s):  
Chien-Yueh Lee ◽  
Amrita Chattopadhyay ◽  
Li-Mei Chiang ◽  
Jyh-Ming Jimmy Juang ◽  
Liang-Chuan Lai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Gene Annotation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Integrated Analysis ◽  
Free Text ◽  
Functional Prediction ◽  
Annotation Database ◽  
Dna Variants

Abstract Integrated analysis of DNA variants and gene expression profiles may facilitate precise identification of gene regulatory networks involved in disease mechanisms. Despite the widespread availability of public resources, we lack databases that are capable of simultaneously providing gene expression profiles, variant annotations, functional prediction scores and pathogenic analyses. VariED is the first web-based querying system that integrates an annotation database and expression profiles for genetic variants. The database offers a user-friendly platform and locates gene/variant names in the literature by connecting to established online querying tools, biological annotation tools and records from free-text literature. VariED acts as a central hub for organized genome information consisting of gene annotation, variant allele frequency, functional prediction, clinical interpretation and gene expression profiles in three species: human, mouse and zebrafish. VariED also provides a novel scoring scheme to predict the functional impact of a DNA variant. With one single entry, all results regarding queried DNA variants can be downloaded. VariED can potentially serve as an efficient way to obtain comprehensive variant knowledge for clinicians and scientists around the world working on important drug discoveries and precision treatments.

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