Megastigmus duclouxiana
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA934845 | ENA |
REPOSITORIES: ENA
Similar Datasets
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Project description:Primary objectives: The primary objective is to investigate circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
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Project description:Marek’s disease virus (MDV) is an oncovirus causing tumor disease known as Marek’s disease (MD) in chicken. Breeding of chickens genetically resistant to MD is considered a vital augment to better control MD. To find the mechanism underlying the genetic resistance to MD, a genomic structural variation, copy number variation (CNV), was examined in inbred MD-resistant and -susceptible chicken lines by using the comparative genomic hybridization (CGH) technique. A total of 45 copy number variation regions (CNVRs) were found spanning across 3,297,038 bp in length of the chicken genome in 4 lines of chickens. Ten CNVRs were selectively confirmed with quantitative real-time PCR. The comparison between the resistant and susceptible chicken lines revealed 28 differentially presented CNVRs, which are functionally involved in immune response, cell proliferation in midbrain, G-protein coupled receptor signaling pathway, and protein-glutamine gamma-glutamyltransferase activity. Two CNVRs that are related with MD-resistance and –susceptibility were also found transmitted to descendent recombinant congenic lines that differ in susceptibility to MD. A positive correlation was identified between the CNVRs and gene expression, indicating the importance of gene expression dosage in disease resistance. We also found the overlapping between the CNVR region and the Marek’s disease trait related quantitative trait loci (QTLs). In conclusion, our data provided additional information elucidating one of possible mechanisms underlying of genetic resistance to MD. The findings may eventually lead to better strategies for genetic improvement of resistance to MD in poultry. L63: highly resistant to MD; L72: highly susceptible to MD; RCS-L: moderate resistant to MD; RCS-M: moderate susceptible to MD
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Project description:Mental disorders (MDs) such as intellectual disability (ID), autism spectrum disabilities (ASD) and schizophrenia have a strong genetic component. Recently, many gene mutations associated with these MDs have been identified by high-throughput sequencing technology. A substantial fraction of these mutations is in genes encoding proteins involved in transcriptional regulation. It is unclear whether different MD-associated transcriptional regulators act in the same gene regulatory network. Such information is important to appreciate the underlying etiology of an MD and the molecular relatedness of different MDs. Physical interaction between transcriptional regulators is a strong predictor for their cooperation in gene regulation. Here, we purified several MD-associated transcriptional regulators from neural stem cells, identified their interaction partners by mass spectrometry and assembled a protein interaction network containing over 200 proteins. The interaction network is enriched for protein factors associated with ID, ASD or schizophrenia and enriched for protein factors encoded by evolutionary constrained genes. Our network thereby provides molecular connections between established MD factors and a discovery tool for novel MD genes. We identified interactions between many transcriptional regulators with a different MD association. We show that network factors preferentially co-localize on the genome and cooperate in the regulation of disease-relevant genes to explain overlapping phenotypes in different syndromes. Our results suggest that the observed transcriptional regulators associated with ID, schizophrenia or ASD are part of the same transcriptional network. We find that the severity of mutations in network factors increased with the severity of the associated MD, suggesting that the level of disruption of a common transcriptional network affects mental disorder outcome.
2016-12-22 | GSE70872 | GEO