Back

Homeodomain transcription factors in adipocyte thermogenesis: insights into the species-specific and conserved regulatory elements of human UCP1

B. Toth, B.; Hegedus, G.; Virag, E. A.; Gergely, P. T.; Laczko, L.; Fesus, L.

2024-09-04 genomics
10.1101/2024.05.16.594487 bioRxiv
Show abstract

Adipocyte thermogenesis is a promising target for treating metabolic disorders, but its regulatory mechanisms remain unclear. This study investigates transcription factors (TFs) and regulatory elements that may control the human UCP1 gene, which is essential for thermogenesis and the formation of the adipocyte phenotype. Using the Eukaryota Promoter Database, we performed computational analyses of the UCP1, UCP2 and UCP3 promoter sequences in humans, mice and rats to identify conserved and species-specific elements. We also used transcriptome data from human neck-derived adipocytes and databases (Contra v3, ChiPBase, TFlink, AdipoNet, ISMARA, etc.) to narrow potential regulatory TFs. Our results show that mouse and rat UCP1 enhancers lack large segments, primarily due to the insertion of repetitive elements that are already lost in some clades. We identified key TFs such as PPARA, PPARG, THR, RARE, RXR, JUN, TFAP2 and SREBF1 as general regulators of UCPs. Additionally, human-specific UCP1 regulatory hotspots (e.g. 5-TCTAATTAGA-3) recognised by homeodomain TFs (e.g. EN1, PAX4, HOXA5 and PRRX2) and NFIL3 were detected. Phylogenetically conserved regulatory elements suggest common TFs in human UCP1 paralogues (MAX, MYCN, MNT, HES1) and cross-species (POU6F1). These results improve our understanding of thermogenic adipocyte development and provide new therapeutic targets for metabolic diseases. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=198 SRC="FIGDIR/small/594487v2_ufig1.gif" ALT="Figure 1"> View larger version (82K): org.highwire.dtl.DTLVardef@1fe65a3org.highwire.dtl.DTLVardef@c2c6e5org.highwire.dtl.DTLVardef@1900abborg.highwire.dtl.DTLVardef@1b09883_HPS_FORMAT_FIGEXP M_FIG C_FIG

Matching journals

The top 11 journals account for 50% of the predicted probability mass.

1
Molecular Genetics and Genomics
11 papers in training set
Top 0.1%
10.2%
2
Frontiers in Genetics
197 papers in training set
Top 0.8%
6.4%
3
Frontiers in Endocrinology
53 papers in training set
Top 0.3%
6.4%
4
Computational and Structural Biotechnology Journal
216 papers in training set
Top 0.8%
4.9%
5
Gene
41 papers in training set
Top 0.2%
4.0%
6
The Journal of Nutritional Biochemistry
13 papers in training set
Top 0.1%
3.6%
7
Scientific Reports
3102 papers in training set
Top 36%
3.6%
8
International Journal of Molecular Sciences
453 papers in training set
Top 3%
3.6%
9
eLife
5422 papers in training set
Top 31%
2.8%
10
Genes
126 papers in training set
Top 0.5%
2.6%
11
Genomics, Proteomics & Bioinformatics
171 papers in training set
Top 2%
2.4%
50% of probability mass above
12
Genomics
60 papers in training set
Top 0.8%
1.9%
13
PLOS ONE
4510 papers in training set
Top 52%
1.8%
14
Biochimie
23 papers in training set
Top 0.1%
1.7%
15
Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease
25 papers in training set
Top 0.3%
1.7%
16
Cells
232 papers in training set
Top 2%
1.7%
17
Frontiers in Cell and Developmental Biology
218 papers in training set
Top 4%
1.7%
18
International Journal of Obesity
25 papers in training set
Top 0.4%
1.5%
19
PLOS Computational Biology
1633 papers in training set
Top 18%
1.5%
20
Physiological Genomics
15 papers in training set
Top 0.1%
1.5%
21
iScience
1063 papers in training set
Top 19%
1.3%
22
Journal of Personalized Medicine
28 papers in training set
Top 0.6%
1.2%
23
PeerJ
261 papers in training set
Top 10%
1.2%
24
Advanced Biology
29 papers in training set
Top 0.8%
1.0%
25
Metabolites
50 papers in training set
Top 0.9%
0.9%
26
Biochimica et Biophysica Acta (BBA) - General Subjects
16 papers in training set
Top 0.2%
0.9%
27
Computational Biology and Chemistry
23 papers in training set
Top 0.3%
0.9%
28
Epigenetics
43 papers in training set
Top 0.7%
0.9%
29
BMC Cancer
52 papers in training set
Top 2%
0.8%
30
Journal of Translational Medicine
46 papers in training set
Top 3%
0.8%