In order to characterize defense responses not only cytologically, but also on the transcript level, genome-wide sequencing of mRNA isolated from non-infected control leaves and from leaves inoculated either with the WT or with GLS1 overexpressing strains was performed, using Illumina Next Generation Sequencing Technology. In order to identify transcripts specifically induced in leaves infected by ß-1,3-glucan-exposing strains, transcript patterns of leaves inoculated with GLS1 overexpressing PtrpC:GLS1 strains were compared with those of the WT. In PtrpC:GLS1-inoculated leaves, a total of 2179 genes were more than 2.5-fold increased, with many genes known as genes typically up-regulated in PAMP-triggered defense responses. These genes include genes encoding PR proteins enzymes involved in cell wall re-inforcemen, and terpene synthases possibly involved in phytoalexin synthesis. Furthermore, increased transcript abundance of genes encoding serine-threonine receptor-like kinases calmodulin, as well as zinc-finger and WRKY transcription factors have been identified. Other up-regulated genes encode proteins involved in protein degradation, i.e. proteases, ubiquitin ligases, as well as enzymes involved in synthesis of auxin or cytokinin phytohormones. In comparison, 2164 genes were more than 2.5-fold down-regulated in maize leaves infected by PtrpC:GLS1 strains, as compared to WT-infected leaves. Several of the encoded proteins are known susceptibility factors. Forty-six down-regulated genes code for proteins containing iron or manganese, or are involved in uptake of these ions, suggesting major re-arrangement of the redox-status in maize leaves after ß-glucan perception. Overall design: Examination of plant defense responses in maize plants inoculated with 2 different Colletotrichum graminicola strains.
Infection structure-specific expression of β-1,3-glucan synthase is essential for pathogenicity of Colletotrichum graminicola and evasion of β-glucan-triggered immunity in maize.
Age, Subject, Time
View SamplesA major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes, and identification of involved pathways and networks.
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.
No sample metadata fields
View SamplesA major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes, and identification of involved pathways and networks.
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.
No sample metadata fields
View SamplesA major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes, and identification of involved pathways and networks.
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.
No sample metadata fields
View SamplesA major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes, and identification of involved pathways and networks.
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.
No sample metadata fields
View SamplesA major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes, and identification of involved pathways and networks.
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.
No sample metadata fields
View SamplesBackground: In multiple sclerosis (MS), immune up-regulation is coupled to subnormal immune response to interferon-β (IFN-β) and low serum IFN-β levels. The relationship between the defect in IFN signalling and acute and long-term effects of IFN-β on gene expression in MS is inadequately understood. Methods: We profiled IFN-β-induced transcriptome shifts, using high-resolution microarrays on 227 mononuclear cell samples from IFN-β-treated MS Complete Responders (CR) stable for five years, and stable and active Partial Responders (PR), stable and active untreated MS, and healthy controls. Findings: IFN-β injection induced short-term changes in 1,200 genes compared to baseline expression after 4-day IFN washout. Pre-injection after washout, and in response to IFN-β injections, PR more frequently had abnormal gene expression than CR. Surprisingly, short-term IFN-β induced little shift in Th1/Th17/Th2 gene expression, but up-regulated immune-inhibitory genes (ILT, IDO1, PD-L1). Expression of 8,800 genes was dysregulated n therapy-naïve compared to IFN-β-treated patients. These long-term changes in protein-coding and long non-coding RNAs affect immunity, synaptic transmission, and CNS cell survival, and correct the disordered therapy-naïve transcriptome to near-normal. In keeping with its impact on clinical course and brain repair in MS, long-term IFN-β treatment reversed the overexpression of proinflammatory and MMP genes, while enhancing genes involved in the oligodendroglia-protective integrated stress response, neuroprotection, and immunoregulation. In the rectified long-term signature, 277 transcripts differed between stable PR and CR patients.
Interferon-β corrects massive gene dysregulation in multiple sclerosis: Short-term and long-term effects on immune regulation and neuroprotection.
Age, Specimen part
View SamplesWe have develped a novel method of making siRNAs (named pro-siRNA for prokaryotic siRNA). To evaluate off-targeting of pro-siRNA, we compared the mRNA expression profiles of HeLa-d1EGFP cells transfected with 4 nM EGFP siRNAs and pro-siRNAs by microarray. Overall design: We used microarray to study the off-target effect of siRNAs in the HeLa-d1EGFP cell line. After transfection of siRNAs for 24 hrs, RNA were extracted using Trizol. Deep sequencing libraries were generated using the NEBNext Ultra RNA Library Prep Kit for Illumina (NEB #E7530). HeLa-d1EGFP cells are HeLa cells stably expressing d1EGFP gene. EGFP siRNA is a siRNA made by chemical synthesis. EGFP100 and EGFPFL are pro-siRNAs made from either a 100 bp hairpin or a full length hairpin targeting EGFP coding sequence.
Efficient and specific gene knockdown by small interfering RNAs produced in bacteria.
Specimen part, Cell line, Subject
View SamplesWe have develped a novel method of making siRNAs (named pro-siRNA for prokaryotic siRNA). To evaluate off-targeting of pro-siRNA, we compared mRNA expression profile of HeLa-d1EGFP cells transfected with 4 nM LMNA siRNAs and pro-siRNAs by microarray.
Efficient and specific gene knockdown by small interfering RNAs produced in bacteria.
Cell line
View SamplesMYC is induced early in human adipose stem cells in response to a standard MDIR adipogenic cocktail. The objective of this experiment was to identify key gene networks impacted by MYC loss-of-function in a mixed donor pool of human derived adipose stem cells.
MYC is an early response regulator of human adipogenesis in adipose stem cells.
Sex, Race
View Samples