Back

The RNA-Binding Protein SAM68 regulates cardiomyocyte differentiation by enhancing Gata4 translation

Dasti, A.; Antonelli, M. C.; Segura, M. A.; Armaos, A.; Bonnin, S.; Graf, T.; Paronetto, M. P.; Tian, T. V.; Bechara, E.; Tartaglia, G. G.

2022-01-11 molecular biology
10.1101/2022.01.11.475875 bioRxiv
Show abstract

The signal transduction and activation of RNA (STAR) family is composed of RNA-binding proteins (RBPs) that play a central role in mammalian development. Nonetheless, the functions and modes of action that STAR proteins have in lineage specification are still poorly understood. Here, we characterized the role of STAR proteins SAM68 and QUAKING (QKI) in pluripotency and differentiation by performing their depletion through CRISPR-Cas9 in mouse embryonic stem cells (mESCs). Combining RNA-sequencing, ribosome profiling and advanced computational predictions, we found that both SAM68 and QKI regulate the mESCs self-renewal and are indispensable for cardiomyocyte differentiation. At the molecular level, we discovered that SAM68 and QKI antagonistically control the expression of cardiogenic factors. Our calculations indicated that SAM68, unlike QKI, binds the cardiogenic-specific transcription factor Gata4 in a region spanning nucleotides 500 to 1000 of the mRNA corresponding to part of the 5 untranslated region and the first exon. We validated the predictions by electrophoretic mobility shift assay and RNA immunoprecipitation showing that SAM68 controls the translation of Gata4 during mESCs differentiation towards the cardiomyocyte lineage.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Nature Communications
○ 5641 papers in training set
Top 15%
12.2%
Similar papers in this journal
2
Nucleic Acids Research
◐ 1281 papers in training set
Top 2%
10.8%
Similar papers in this journal
3
Scientific Reports
○ 3612 papers in training set
Top 11%
6.6%
Similar papers in this journal
4
eLife
● 5828 papers in training set
Top 20%
6.1%
Similar papers in this journal
5
Stem Cells
◐ 31 papers in training set
Top 0.1%
6.1%
Similar papers in this journal
6
iScience
○ 1154 papers in training set
Top 2%
5.4%
7
Communications Biology
○ 993 papers in training set
Top 2%
5.0%
50% of probability mass above
8
Stem Cell Reports
○ 130 papers in training set
Top 0.5%
4.7%
9
Cell Reports
○ 1498 papers in training set
Top 9%
4.2%
10
Cells
○ 249 papers in training set
Top 1%
3.1%
11
EMBO Reports
○ 263 papers in training set
Top 2%
2.7%
12
RNA Biology
○ 78 papers in training set
Top 0.6%
2.1%
13
Development
● 497 papers in training set
Top 3%
1.9%
14
Life Science Alliance
● 285 papers in training set
Top 4%
1.7%
15
BMC Biology
○ 265 papers in training set
Top 2%
1.6%
16
International Journal of Molecular Sciences
○ 494 papers in training set
Top 8%
1.6%
17
PLOS Genetics
● 862 papers in training set
Top 8%
1.5%
18
Cell Death & Disease
147 papers in training set
Top 2%
1.3%
19
PLOS Biology
● 486 papers in training set
Top 7%
1.3%
20
Molecular Therapy - Nucleic Acids
○ 25 papers in training set
Top 0.5%
1.1%
21
Cell Death & Differentiation
○ 48 papers in training set
Top 1%
1.0%
22
The EMBO Journal
○ 309 papers in training set
Top 6%
1.0%
23
Cellular and Molecular Life Sciences
○ 96 papers in training set
Top 2%
0.8%
24
Cell Proliferation
○ 12 papers in training set
Top 0.3%
0.8%
25
Frontiers in Cell and Developmental Biology
○ 233 papers in training set
Top 6%
0.6%
26
EMBO Molecular Medicine
○ 95 papers in training set
Top 4%
0.6%
27
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 46%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.