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A property-based analysis of human transcription factors.

Bahrami S, Ehsani R, Drabløs F - BMC Res Notes (2015)

Bottom Line: Reliable information about key properties associated with transcription factors will therefore be useful for data analysis, in particular of data from high-throughput experiments.The study shows that well-annotated feature list for transcription factors is a useful resource for extensive data analysis; both of transcription factor properties in general and of properties associated with specific processes.However, the study also shows that such analyses are easily biased by incomplete coverage in experimental data, and by how gene sets are defined.

View Article: PubMed Central - PubMed

Affiliation: Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, P.O. Box 8905, , NO-7491, Trondheim, Norway. shahram.bahrami@ntnu.no.

ABSTRACT

Background: Transcription factors are essential proteins for regulating gene expression. This regulation depends upon specific features of the transcription factors, including how they interact with DNA, how they interact with each other, and how they are post-translationally modified. Reliable information about key properties associated with transcription factors will therefore be useful for data analysis, in particular of data from high-throughput experiments.

Results: We have used an existing list of 1978 human proteins described as transcription factors to make a well-annotated data set, which includes information on Pfam domains, DNA-binding domains, post-translational modifications and protein-protein interactions. We have then used this data set for enrichment analysis. We have investigated correlations within this set of features, and between the features and more general protein properties. We have also used the data set to analyze previously published gene lists associated with cell differentiation, cancer, and tissue distribution.

Conclusions: The study shows that well-annotated feature list for transcription factors is a useful resource for extensive data analysis; both of transcription factor properties in general and of properties associated with specific processes. However, the study also shows that such analyses are easily biased by incomplete coverage in experimental data, and by how gene sets are defined.

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Related in: MedlinePlus

A Venn diagram for distribution of PTMs across TFs. The diagram shows that PTMs tend to co-occur, possibly due to experimental bias.
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Fig4: A Venn diagram for distribution of PTMs across TFs. The diagram shows that PTMs tend to co-occur, possibly due to experimental bias.

Mentions: Ravasi et al. tested 1222 TFs experimentally for protein–protein interactions and found 762 actual interactions for 482 TFs [17]. These interactions were included in the data set. For the mapping of PTMs, we retrieved information for each TF from the PTM-specific files from Phosphosite [26]. The distribution of PTMs is shown in Figure 4.Figure 4


A property-based analysis of human transcription factors.

Bahrami S, Ehsani R, Drabløs F - BMC Res Notes (2015)

A Venn diagram for distribution of PTMs across TFs. The diagram shows that PTMs tend to co-occur, possibly due to experimental bias.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4373352&req=5

Fig4: A Venn diagram for distribution of PTMs across TFs. The diagram shows that PTMs tend to co-occur, possibly due to experimental bias.
Mentions: Ravasi et al. tested 1222 TFs experimentally for protein–protein interactions and found 762 actual interactions for 482 TFs [17]. These interactions were included in the data set. For the mapping of PTMs, we retrieved information for each TF from the PTM-specific files from Phosphosite [26]. The distribution of PTMs is shown in Figure 4.Figure 4

Bottom Line: Reliable information about key properties associated with transcription factors will therefore be useful for data analysis, in particular of data from high-throughput experiments.The study shows that well-annotated feature list for transcription factors is a useful resource for extensive data analysis; both of transcription factor properties in general and of properties associated with specific processes.However, the study also shows that such analyses are easily biased by incomplete coverage in experimental data, and by how gene sets are defined.

View Article: PubMed Central - PubMed

Affiliation: Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, P.O. Box 8905, , NO-7491, Trondheim, Norway. shahram.bahrami@ntnu.no.

ABSTRACT

Background: Transcription factors are essential proteins for regulating gene expression. This regulation depends upon specific features of the transcription factors, including how they interact with DNA, how they interact with each other, and how they are post-translationally modified. Reliable information about key properties associated with transcription factors will therefore be useful for data analysis, in particular of data from high-throughput experiments.

Results: We have used an existing list of 1978 human proteins described as transcription factors to make a well-annotated data set, which includes information on Pfam domains, DNA-binding domains, post-translational modifications and protein-protein interactions. We have then used this data set for enrichment analysis. We have investigated correlations within this set of features, and between the features and more general protein properties. We have also used the data set to analyze previously published gene lists associated with cell differentiation, cancer, and tissue distribution.

Conclusions: The study shows that well-annotated feature list for transcription factors is a useful resource for extensive data analysis; both of transcription factor properties in general and of properties associated with specific processes. However, the study also shows that such analyses are easily biased by incomplete coverage in experimental data, and by how gene sets are defined.

Show MeSH
Related in: MedlinePlus