Back

Transcription factor-target relationships complicated by knockout analysis

Dai, Z.

2020-08-31 genetics
10.1101/2020.08.30.274548 bioRxiv
Show abstract

Knockout analysis is a common tool to reveal transcription factor (TF) functions. However, such a reverse genetic analysis based on observed phenotype changes in mutant cell may lead to a misunderstanding of TF wild-type functions. Here, a model was proposed, in which the knockout-observed TF-target regulatory relationships might only occur in mutant cell, and they do not reflect TF normal functions in wild-type cell. Actually, the knockout of one TF might release another TF which is the protein-protein interaction partner of the deleted TF. The free TF could bind its new target genes and cause their significant expression changes. These seemingly TF knockout affected genes are thus not directly regulated by the deleted TF, but are gain-of-regulated genes of the latter TF in mutant cell. Based on this model, multiple sources of genome-wide data were used to identify 20 such TF pairs, and one pair was validated using other independent data. TF wild-type regulatory genes are not associated with their gain-of-regulated genes. My findings revealed TF-target relationships complicated by TF knockout analysis.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Genomics, Proteomics & Bioinformatics
171 papers in training set
Top 0.4%
12.4%
2
PLOS Computational Biology
1633 papers in training set
Top 3%
10.0%
3
Genes to Cells
23 papers in training set
Top 0.1%
10.0%
4
eLife
5422 papers in training set
Top 11%
6.8%
5
Journal of Genetics and Genomics
36 papers in training set
Top 0.1%
6.8%
6
Frontiers in Genetics
197 papers in training set
Top 0.9%
6.3%
50% of probability mass above
7
PLOS ONE
4510 papers in training set
Top 40%
3.6%
8
Cell Discovery
54 papers in training set
Top 1%
3.6%
9
Science China Life Sciences
26 papers in training set
Top 0.6%
2.3%
10
Journal of Molecular Cell Biology
21 papers in training set
Top 0.1%
2.3%
11
PLOS Genetics
756 papers in training set
Top 7%
2.1%
12
National Science Review
22 papers in training set
Top 0.8%
1.9%
13
Human Molecular Genetics
130 papers in training set
Top 2%
1.7%
14
Scientific Reports
3102 papers in training set
Top 60%
1.6%
15
Molecular Genetics and Genomics
11 papers in training set
Top 0.2%
1.5%
16
Synthetic and Systems Biotechnology
10 papers in training set
Top 0.3%
1.5%
17
Genes
126 papers in training set
Top 2%
1.2%
18
Briefings in Bioinformatics
326 papers in training set
Top 5%
1.2%
19
International Journal of Molecular Sciences
453 papers in training set
Top 13%
0.9%
20
Biosystems
18 papers in training set
Top 0.4%
0.8%
21
Cell Structure and Function
11 papers in training set
Top 0.1%
0.7%
22
Cell Reports Physical Science
18 papers in training set
Top 0.8%
0.7%
23
Frontiers in Cell and Developmental Biology
218 papers in training set
Top 9%
0.7%
24
Biology
43 papers in training set
Top 3%
0.7%
25
Journal of Biomedical Science
14 papers in training set
Top 0.3%
0.6%
26
Cell Proliferation
12 papers in training set
Top 0.5%
0.6%
27
BioMed Research International
25 papers in training set
Top 4%
0.6%