ArticleNucleic acids research2005
Cell-type-specific transcriptomics in chimeric models using transcriptome-based masks.
Article in Nucleic acids research, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 25 citations in OpenAlex.
- A mouse tissue transcription factor atlas.Nature communications · 2017Article
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- In vivo topoisomerase I inhibition attenuates the expression of hypoxia-inducible factor 1α target genes and decreases tumor angiogenesis.Molecular medicine (Cambridge, Mass.) · 2012Article
- Detection of interacting transcription factors in human tissues using predicted DNA binding affinity.BMC genomics · 2012Article
- Genome-wide mapping of RNA Pol-II promoter usage in mouse tissues by ChIP-seq.Nucleic acids research · 2011Article
- Validation of a mouse xenograft model system for gene expression analysis of human acute lymphoblastic leukaemia.BMC genomics · 2010Article
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- Identification of differentially expressed sense and antisense transcript pairs in breast epithelial tissues.BMC genomics · 2009Article
- Nuclear reprogramming in heterokaryons is rapid, extensive, and bidirectional.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2009Article
- Impact of normalization on miRNA microarray expression profiling.RNA (New York, N.Y.) · 2009Article
- Contaminating cells alter gene signatures in whole organ versus laser capture microdissected tumors: a comparison of experimental breast cancers and their lymph node metastases.Clinical & experimental metastasis · 2008Article
- High-density rhesus macaque oligonucleotide microarray design using early-stage rhesus genome sequence information and human genome annotations.BMC genomics · 2007Article
- Application of functional genomics to the chimeric mouse model of HCV infection: optimization of microarray protocols and genomics analysis.Virology journal · 2006Article
- Establishment of the epithelial-specific transcriptome of normal and malignant human breast cells based on MPSS and array expression data.Breast cancer research : BCR · 2006Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Regulatory networks involving different cell types control inflammation, morphogenesis and tissue homeostasis. Cell-type-specific transcriptional profiling offers a powerful tool for analyzing such cross-talk but is often hampered by mingling of cells within a tissue. Here, we present a novel method that performs cell-type-specific expression measurements without prior cell separation. This involves inter-species transplantation or chimeric co-culture models among which the human mouse system is frequently used. Here, we exploit the sufficiently divergent transcriptomes of human and mouse in conjunction with high-density oligonucleotide arrays. This required a masking procedure based on transcriptome databases and exhaustive fuzzy mapping of oligonucleotide probes onto these data. The approach was tested in a human-mouse experiment, demonstrating that we can efficiently measure species-specific transcriptional profiles in chimeric RNA samples without physically separating cells. Our results stress the importance of transcriptome databases with accurate 3' mRNA termination for computational prediction of accurate probe masks. We find that most human and mouse 3'-untranslated region contain unique stretches to allow for an effective control of cross-hybridization between the two species. This approach can be applied to xenograft models studying tumor-host interactions, morphogenesis or immune responses.
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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.