Understanding Human Tissue Identity Through Gene Expression
Author Information
Author(s): Greco Dario, Somervuo Panu, Di Lieto Antonio, Raitila Tuomas, Nitsch Lucio, Castrén Eero, Auvinen Petri
Primary Institution: Institute of Biotechnology, University of Helsinki
Hypothesis
Can gene expression profiles help identify the functional relatedness of human tissues?
Conclusion
The study found that gene expression data can effectively categorize human tissues and their related functions.
Supporting Evidence
- The study identified 1601 genes selectively expressed in one or more tissues.
- These tissue-selective genes were linked to 361 human diseases.
- The research proposed a network of tissues based on shared gene expression.
Takeaway
Scientists looked at how genes work in different parts of the body to understand what makes each tissue special.
Methodology
The study analyzed gene expression data from 195 Affymetrix GeneChips across 78 human tissues.
Potential Biases
Potential mis-annotation of probes could introduce bias in gene expression analysis.
Limitations
The complexity of tissue architecture may affect the accuracy of gene expression assignments.
Participant Demographics
Normal adult and fetal human tissues were used.
Statistical Information
P-Value
p<1.0E-18
Statistical Significance
p<1.0E-4
Digital Object Identifier (DOI)
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