SynthesisBMC genomics2011
Strengthening insights into host responses to mastitis infection in ruminants by combining heterogeneous microarray data sources.
Synthesis in BMC genomics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
27 citing papers in PubMed, 3 syntheses or guidelines pooled it, 51 citations in OpenAlex.
- X-linked genes influence various complex traits in dairy cattle.BMC genomics · 2023Pooled it
- Prediction of key regulators and downstream targets of E. coli induced mastitis.Journal of applied genetics · 2019Pooled it
- Pig immune response to general stimulus and to porcine reproductive and respiratory syndrome virus infection: a meta-analysis approach.BMC genomics · 2013Pooled it
- Functional Role and Diagnostic Potential of Biomarkers in the Early Detection of Mastitis in Dairy Cows.Animals : an open access journal from MDPI · 2026Review
- Identification of genetic variants affecting reproduction traits in Vrindavani cattle.Mammalian genome : official journal of the International Mammalian Genome Society · 2024Article
- Candidate genes for mastitis resistance in dairy cattle: a data integration approach.Journal of animal science and biotechnology · 2023Article
- Investigation of hub gene associated with the infection of Staphylococcus aureus via weighted gene co-expression network analysis.BMC microbiology · 2021Article
- Gene Expression Profiling Reveals New Pathways and Genes Associated with Visna/Maedi Viral Disease.Animals : an open access journal from MDPI · 2021Article
- Regulation of Key Genes for Milk Fat Synthesis in Ruminants.Frontiers in nutrition · 2021Review
- Transcriptome Analysis of The Inflammatory Responses of Bovine Mammary Epithelial Cells: Exploring Immunomodulatory Target Genes for Bovine Mastitis.Pathogens (Basel, Switzerland) · 2020Article
- Identification of Gene Modules and Hub Genes Involved in Mastitis Development Using a Systems Biology Approach.Frontiers in genetics · 2020Article
- Integration of machine learning and meta-analysis identifies the transcriptomic bio-signature of mastitis disease in cattle.PloS one · 2018Article
- Transcriptome profiling of Staphylococci-infected cow mammary gland parenchyma.BMC veterinary research · 2017Article
- Article
- Analysis of human breast milk cells: gene expression profiles during pregnancy, lactation, involution, and mastitic infection.Functional & integrative genomics · 2016Article
- Transcriptome-Wide Analysis Reveals the Role of PPARPPAR research · 2016Article
- Gene expression profiling of porcine mammary epithelial cells after challenge with Escherichia coli and Staphylococcus aureus in vitro.Veterinary research · 2015Article
- Genes regulating lipid and protein metabolism are highly expressed in mammary gland of lactating dairy goats.Functional & integrative genomics · 2015Article
- Expression patterns of β-defensin and cathelicidin genes in parenchyma of bovine mammary gland infected with coagulase-positive or coagulase-negative Staphylococci.BMC veterinary research · 2014Article
- iTRAQ-proteomics and bioinformatics analyses of mammary tissue from cows with clinical mastitis due to natural infection with Staphylococci aureus.BMC genomics · 2014Article
Corrections and comments
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Authors and funding
26 authors at 13 institutions in 9 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGene expression profiling studies of mastitis in ruminants have provided key but fragmented knowledge for the understanding of the disease. A systematic combination of different expression profiling studies via meta-analysis techniques has the potential to test the extensibility of conclusions based on single studies. Using the program Pointillist, we performed meta-analysis of transcription-profiling data from six independent studies of infections with mammary gland pathogens, including samples from cattle challenged in vivo with S. aureus, E. coli, and S. uberis, samples from goats challenged in vivo with S. aureus, as well as cattle macrophages and ovine dendritic cells infected in vitro with S. aureus. We combined different time points from those studies, testing different responses to mastitis infection: overall (common signature), early stage, late stage, and cattle-specific.
resultsIngenuity Pathway Analysis of affected genes showed that the four meta-analysis combinations share biological functions and pathways (e.g. protein ubiquitination and polyamine regulation) which are intrinsic to the general disease response. In the overall response, pathways related to immune response and inflammation, as well as biological functions related to lipid metabolism were altered. This latter observation is consistent with the milk fat content depression commonly observed during mastitis infection. Complementarities between early and late stage responses were found, with a prominence of metabolic and stress signals in the early stage and of the immune response related to the lipid metabolism in the late stage; both mechanisms apparently modulated by few genes, including XBP1 and SREBF1.The cattle-specific response was characterized by alteration of the immune response and by modification of lipid metabolism. Comparison of E. coli and S. aureus infections in cattle in vivo revealed that affected genes showing opposite regulation had the same altered biological functions and provided evidence that E. coli caused a stronger host response.
conclusionsThis meta-analysis approach reinforces previous findings but also reveals several novel themes, including the involvement of genes, biological functions, and pathways that were not identified in individual studies. As such, it provides an interesting proof of principle for future studies combining information from diverse heterogeneous sources.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.