scholarly journals Developmental system drift in motor ganglion patterning between distantly related tunicates

2018 ◽  
Author(s):  
Elijah K. Lowe ◽  
Alberto Stolfi
Keyword(s):  
Gene Expression ◽  
Spatial Organization ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Lone Pair ◽  
Embryonic Cell ◽  
Specific Gene ◽  
Developmental System Drift ◽  
Larval Nervous System ◽  
Contralateral Projection

AbstractThe larval nervous system of the solitary tunicate Ciona is a simple model for the study of chordate neurodevelopment. The development and connectivity of the Ciona Motor Ganglion (MG) has been studied in fine detail, but how this important structure develops in other tunicates is not well known. By comparing gene expression patterns in the developing MG of the distantly related tunicate Molgula occidentalis, we found that its patterning is highly conserved compared to the Ciona MG. MG neuronal subtypes in Molgula were specified in the exact same positions as in Ciona, though the timing of subtype-specific gene expression onset was slightly shifted to begin earlier, relative to mitotic exit and differentiation. In transgenic Molgula embryos electroporated with Dmbx reporter plasmids, we were also able to characterize the morphology of the lone pair of descending decussating neurons (ddNs) in Molgula, revealing the same unique contralateral projection seen in Ciona ddNs and their putative vertebrate homologs the Mauthner cells. Although Dmbx expression labels the ddNs in both species, cross-species transgenic assays revealed significant changes to the cis-regulatory logic underlying Dmbx transcription. We found that Dmbx cis-regulatory DNAs from Ciona can drive highly specific reporter gene expression in Molgula ddNs, but Molgula sequences are not active in Ciona ddNs. This acute divergence in the molecular mechanisms that underlie otherwise functionally conserved cis-regulatory DNAs supports the recently proposed idea that the extreme genetic plasticity observed in tunicates may be attributed to the extreme rigidity of the spatial organization of their embryonic cell lineages.

scholarly journals Comparative analyses of saprotrophy in Salisapilia sapeloensis and diverse plant pathogenic oomycetes reveal lifestyle-specific gene expression

2020 ◽  
Vol 96 (11) ◽  
Author(s):  
Sophie de Vries ◽  
Jan de Vries ◽  
John M Archibald ◽  
Claudio H Slamovits
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Plant Pathogens ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Reference Points ◽  
Global Perspective ◽  
Specific Gene ◽  
Gene Regulatory ◽  
Specific Array

ABSTRACT Oomycetes include many devastating plant pathogens. Across oomycete diversity, plant-infecting lineages are interspersed by non-pathogenic ones. Unfortunately, our understanding of the evolution of lifestyle switches is hampered by a scarcity of data on the molecular biology of saprotrophic oomycetes, ecologically important primary colonizers of dead tissue that can serve as informative reference points for understanding the evolution of pathogens. Here, we established Salisapilia sapeloensis as a tractable system for the study of saprotrophic oomycetes. We generated multiple transcriptomes from S. sapeloensis and compared them with (i) 22 oomycete genomes and (ii) the transcriptomes of eight pathogenic oomycetes grown under 13 conditions. We obtained a global perspective on gene expression signatures of oomycete lifestyles. Our data reveal that oomycete saprotrophs and pathogens use similar molecular mechanisms for colonization but exhibit distinct expression patterns. We identify a S. sapeloensis-specific array and expression of carbohydrate-active enzymes and putative regulatory differences, highlighted by distinct expression levels of transcription factors. Salisapilia sapeloensis expresses only a small repertoire of candidates for virulence-associated genes. Our analyses suggest lifestyle-specific gene regulatory signatures and that, in addition to variation in gene content, shifts in gene regulatory networks underpin the evolution of oomycete lifestyles.

scholarly journals Network Analysis Identifies Sex-Specific Gene Expression Changes in Blood of Amyotrophic Lateral Sclerosis Patients

2021 ◽  
Vol 22 (13) ◽  
pp. 7150
Author(s):  
Jose A. Santiago ◽  
James P. Quinn ◽  
Judith A. Potashkin
Keyword(s):  
Gene Expression ◽  
Amyotrophic Lateral Sclerosis ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Specific Gene ◽  
Ampk Signaling ◽  
Specific Gene Expression ◽  
Als Patients ◽  
Functional Analyses ◽  
Lateral Sclerosis

Understanding the molecular mechanisms underlying the pathogenesis of amyotrophic lateral sclerosis (ALS), a devastating neurodegenerative disease, is a major challenge. We used co-expression networks implemented by the SWitch Miner software to identify switch genes associated with drastic transcriptomic changes in the blood of ALS patients. Functional analyses revealed that switch genes were enriched in pathways related to the cell cycle, hepatitis C, and small cell lung cancer. Analysis of switch genes by sex revealed that switch genes from males were associated with metabolic pathways, including PI3K-AKT, sphingolipid, carbon metabolism, FOXO, and AMPK signaling. In contrast, female switch genes related to infectious diseases, inflammation, apoptosis, and atherosclerosis. Furthermore, eight switch genes showed sex-specific gene expression patterns. Collectively, we identified essential genes and pathways that may explain sex differences observed in ALS. Future studies investigating the potential role of these genes in driving disease disparities between males and females with ALS are warranted.

scholarly journals JSTA: joint cell segmentation and cell type annotation for spatial transcriptomics

2020 ◽  
Author(s):  
Russell Littman ◽  
Zachary Hemminger ◽  
Robert Foreman ◽  
Douglas Arneson ◽  
Guanglin Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Gene Expression ◽  
Spatial Organization ◽  
Expression Patterns ◽  
Granular Cell ◽  
Detection Sensitivity ◽  
Cell Segmentation ◽  
Specific Gene ◽  
Cell Type ◽  
Differential Gene

AbstractRNA hybridization based spatial transcriptomics provides unparalleled detection sensitivity. However, inaccuracies in segmentation of image volumes into cells cause misassignment of mRNAs which is a major source of errors. Here we develop JSTA, a computational framework for Joint cell Segmentation and cell Type Annotation that utilizes prior knowledge of cell-type specific gene expression. Simulation results show that leveraging existing cell type taxonomy increases RNA assignment accuracy by more than 45%. Using JSTA we were able to classify cells in the mouse hippocampus into 133 (sub)types revealing the spatial organization of CA1, CA3, and Sst neuron subtypes. Analysis of within cell subtype spatial differential gene expression of 80 candidate genes identified 43 with statistically significant spatial differential gene expression across 61 (sub)types. Overall, our work demonstrates that known cell type expression patterns can be leveraged to improve the accuracy of RNA hybridization based spatial transcriptomics while providing highly granular cell (sub)type information. The large number of newly discovered spatial gene expression patterns substantiates the need for accurate spatial transcriptomics measurements that can provide information beyond cell (sub)type labels.

scholarly journals Comparative analyses of saprotrophy in Salisapilia sapeloensis and diverse plant pathogenic oomycetes reveal lifestyle-specific gene expression

2019 ◽  
Author(s):  
Sophie de Vries ◽  
Jan de Vries ◽  
John M Archibald ◽  
Claudio H Slamovits
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Plant Pathogens ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Reference Points ◽  
Global Perspective ◽  
Specific Gene ◽  
Gene Regulatory ◽  
Specific Array

Oomycetes include many well-studied, devastating plant pathogens. Across oomycete diversity, plant-infecting lineages are interspersed by non-pathogenic ones. Unfortunately, our understanding of the evolution of lifestyle switches is hampered by a scarcity of data on the molecular biology of saprotrophic oomycetes, ecologically important primary colonizers of dead tissue that can serve as informative reference points for understanding the evolution of pathogens. Here, we established Salisapilia sapeloensis growing on axenic litter as a tractable system for the study of saprotrophic oomycetes. We generated multiple transcriptomes from S. sapeloensis and compared them to (a) 22 oomycete genomes and (b) the transcriptomes of eight pathogenic oomycetes grown under 13 conditions (three pathogenic lifestyles, six hosts/substrates, and four tissues). From these analyses we obtained a global perspective on the gene expression signatures of oomycete lifestyles. Our data reveal that oomycete saprotrophs and pathogens use generally similar molecular mechanisms for colonization, but exhibit distinct expression patterns. We identify S. sapeloensis' specific array and expression of carbohydrate-active enzymes and regulatory differences in pathogenicity-associated factors, including the virulence factor EpiC2B. Further, S. sapeloensis was found to express only a small repertoire of effector genes. In conclusion, our analyses reveal lifestyle-specific gene regulatory signatures and suggest that, in addition to variation in gene content, shifts in gene regulatory networks might underpin the evolution of oomycete lifestyles.

scholarly journals Molecular Profiling of Glatiramer Acetate Early Treatment Effects in Multiple Sclerosis

2009 ◽  
Vol 27 (2) ◽  
pp. 63-73 ◽  
Author(s):  
Anat Achiron ◽  
Anna Feldman ◽  
Michael Gurevich
Keyword(s):  
Gene Expression ◽  
Multiple Sclerosis ◽  
Glatiramer Acetate ◽  
Molecular Mechanisms ◽  
Mononuclear Cells ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Molecular Signature ◽  
Specific Gene ◽  
Altered Expression

Background: Glatiramer acetate (GA, Copaxone®) has beneficial effects on the clinical course of relapsing-remitting multiple sclerosis (RRMS). However, the exact molecular mechanisms of GA effects are only partially understood.Objective: To characterized GA molecular effects in RRMS patients within 3 months of treatment by microarray profiling of peripheral blood mononuclear cells (PBMC).Methods: Gene-expression profiles were determined in RRMS patients before and at 3 months after initiation of GA treatment using Affimetrix (U133A-2) microarrays containing 14,500 well-characterized human genes. Most informative genes (MIGs) of GA-induced biological convergent pathways operating in RRMS were constructed using gene functional annotation, enrichment analysis and pathway reconstruction bioinformatic softwares. Verification at the mRNA and protein level was performed by qRT-PCR and FACS.Results: GA induced a specific gene expression molecular signature that included altered expression of 480 genes within 3 months of treatment; 262 genes were up-regulated, and 218 genes were down-regulated. The main convergent mechanisms of GA effects were related to antigen-activated apoptosis, inflammation, adhesion, and MHC class-I antigen presentation.Conclusions: Our findings demonstrate that GA treatment induces alternations of immunomodulatory gene expression patterns that are important for suppression of disease activity already at three months of treatment and can be used as molecular markers of GA activity.

A Global Vista of the Epigenomic State of the Mouse Submandibular Gland

2021 ◽  
pp. 002203452110120
Author(s):  
C. Gluck ◽  
S. Min ◽  
A. Oyelakin ◽  
M. Che ◽  
E. Horeth ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcriptional Control ◽  
Expression Patterns ◽  
Global Gene Expression ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Submandibular Salivary Gland ◽  
Data Sets ◽  
Control Mechanisms ◽  
Chromatin Immunoprecipitation Sequencing

The parotid, submandibular, and sublingual glands represent a trio of oral secretory glands whose primary function is to produce saliva, facilitate digestion of food, provide protection against microbes, and maintain oral health. While recent studies have begun to shed light on the global gene expression patterns and profiles of salivary glands, particularly those of mice, relatively little is known about the location and identity of transcriptional control elements. Here we have established the epigenomic landscape of the mouse submandibular salivary gland (SMG) by performing chromatin immunoprecipitation sequencing experiments for 4 key histone marks. Our analysis of the comprehensive SMG data sets and comparisons with those from other adult organs have identified critical enhancers and super-enhancers of the mouse SMG. By further integrating these findings with complementary RNA-sequencing based gene expression data, we have unearthed a number of molecular regulators such as members of the Fox family of transcription factors that are enriched and likely to be functionally relevant for SMG biology. Overall, our studies provide a powerful atlas of cis-regulatory elements that can be leveraged for better understanding the transcriptional control mechanisms of the mouse SMG, discovery of novel genetic switches, and modulating tissue-specific gene expression in a targeted fashion.

Serial analysis of gene expression (SAGE) during porcine embryo development

2004 ◽  
Vol 16 (2) ◽  
pp. 87 ◽  
Author(s):  
Le Ann Blomberg ◽  
Kurt A. Zuelke
Keyword(s):  
Gene Expression ◽  
Functional Genomics ◽  
Embryo Development ◽  
Molecular Mechanisms ◽  
Physiological Role ◽  
Transgenic Animals ◽  
Specific Gene ◽  
Research Strategies

Functional genomics provides a powerful means for delving into the molecular mechanisms involved in pre-implantation development of porcine embryos. High rates of embryonic mortality (30%), following either natural mating or artificial insemination, emphasise the need to improve the efficiency of reproduction in the pig. The poor success rate of live offspring from in vitro-manipulated pig embryos also hampers efforts to generate transgenic animals for biotechnology applications. Previous analysis of differential gene expression has demonstrated stage-specific gene expression for in vivo-derived embryos and altered gene expression for in vitro-derived embryos. However, the methods used to date examine relatively few genes simultaneously and, thus, provide an incomplete glimpse of the physiological role of these genes during embryogenesis. The present review will focus on two aspects of applying functional genomics research strategies for analysing the expression of genes during elongation of pig embryos between gestational day (D) 11 and D12. First, we compare and contrast current methodologies that are being used for gene discovery and expression analysis during pig embryo development. Second, we establish a paradigm for applying serial analysis of gene expression as a functional genomics tool to obtain preliminary information essential for discovering the physiological mechanisms by which distinct embryonic phenotypes are derived.

FC 011KIDNEYNETWORK: USING KIDNEY DERIVED GENE EXPRESSION DATA TO PREDICT AND PRIORITIZE NOVEL GENES INVOLVED IN KIDNEY DISEASE

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Floranne Boulogne ◽  
Laura Claus ◽  
Henry Wiersma ◽  
Roy Oelen ◽  
Floor Schukking ◽  
...  
Keyword(s):  
Gene Expression ◽  
Kidney Disease ◽  
Candidate Gene ◽  
Exome Sequencing ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Genetic Diagnosis ◽  
Specific Gene ◽  
Sequencing Data ◽  
Exome Sequencing Data

Abstract Background and Aims Genetic testing in patients with suspected hereditary kidney disease does not always reveal the genetic cause for the patient's disorder. Potentially pathogenic variants can reside in genes that are not known to be involved in kidney disease, which makes it difficult to prioritize and interpret the relevance of these variants. As such, there is a clear need for methods that predict the phenotypic consequences of gene expression in a way that is as unbiased as possible. To help identify candidate genes we have developed KidneyNetwork, in which tissue-specific expression is utilized to predict kidney-specific gene functions. Method We combined gene co-expression in 878 publicly available kidney RNA-sequencing samples with the co-expression of a multi-tissue RNA-sequencing dataset of 31,499 samples to build KidneyNetwork. The expression patterns were used to predict which genes have a kidney-related function, and which (disease) phenotypes might be caused when these genes are mutated. By integrating the information from the HPO database, in which known phenotypic consequences of disease genes are annotated, with the gene co-expression network we obtained prediction scores for each gene per HPO term. As proof of principle, we applied KidneyNetwork to prioritize variants in exome-sequencing data from 13 kidney disease patients without a genetic diagnosis. Results We assessed the prediction performance of KidneyNetwork by comparing it to GeneNetwork, a multi-tissue co-expression network we previously developed. In KidneyNetwork, we observe a significantly improved prediction accuracy of kidney-related HPO-terms, as well as an increase in the total number of significantly predicted kidney-related HPO-terms (figure 1). To examine its clinical utility, we applied KidneyNetwork to 13 patients with a suspected hereditary kidney disease without a genetic diagnosis. Based on the HPO terms “Renal cyst” and “Hepatic cysts”, combined with a list of potentially damaging variants in one of the undiagnosed patients with mild ADPKD/PCLD, we identified ALG6 as a new candidate gene. ALG6 bears a high resemblance to other genes implicated in this phenotype in recent years. Through the 100,000 Genomes Project and collaborators we identified three additional patients with kidney and/or liver cysts carrying a suspected deleterious variant in ALG6. Conclusion We present KidneyNetwork, a kidney specific co-expression network that accurately predicts what genes have kidney-specific functions and may result in kidney disease. Gene-phenotype associations of genes unknown for kidney-related phenotypes can be predicted by KidneyNetwork. We show the added value of KidneyNetwork by applying it to exome sequencing data of kidney disease patients without a molecular diagnosis and consequently we propose ALG6 as a promising candidate gene. KidneyNetwork can be applied to clinically unsolved kidney disease cases, but it can also be used by researchers to gain insight into individual genes to better understand kidney physiology and pathophysiology. Acknowledgments This research was made possible through access to the data and findings generated by the 100,000 Genomes Project; http://www.genomicsengland.co.uk.

scholarly journals Identification of biological pathways and genes associated with neurogenic heterotopic ossification by text mining

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8276 ◽  
Author(s):  
Yichong Zhang ◽  
Yuanbo Zhan ◽  
Yuhui Kou ◽  
Xiaofeng Yin ◽  
Yanhua Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Text Mining ◽  
Heterotopic Ossification ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Egf Receptor ◽  
Enrichment Analysis ◽  
Biological Pathways ◽  
Specific Gene ◽  
Cord Injury

Background Neurogenic heterotopic ossification is a disorder of aberrant bone formation affecting one in five patients sustaining a spinal cord injury or traumatic brain injury (SCI-TBI-HO). However, the underlying mechanisms of SCI-TBI-HO have proven difficult to elucidate. The aim of the present study is to identify the most promising candidate genes and biological pathways for SCI-TBI-HO. Methods In this study, we used text mining to generate potential explanations for SCI-TBI-HO. Moreover, we employed several additional datasets, including gene expression profile data, drug data and tissue-specific gene expression data, to explore promising genes that associated with SCI-TBI-HO. Results We identified four SCI-TBI-HO-associated genes, including GDF15, LDLR, CCL2, and CLU. Finally, using enrichment analysis, we identified several pathways, including integrin signaling, insulin pathway, internalization of ErbB1, urokinase-type plasminogen activator and uPAR-mediated signaling, PDGFR-beta signaling pathway, EGF receptor (ErbB1) signaling pathway, and class I PI3K signaling events, which may be associated with SCI-TBI-HO. Conclusions These results enhance our understanding of the molecular mechanisms of SCI-TBI-HO and offer new leads for researchers and innovative therapeutic strategies.

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.

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