| ID | Sequence | Length | GC content |
|---|---|---|---|
| GAACUGCGGCGGCGGCGAGCGCCGGCCGCAUCUGAGCAGAGCUGCAGCG… | 3483 nt | 0.5940 | |
| GCGUUGCCAAGGUGACCCGGGCGCGGGAAGGCGGCUCCGGCUCGCGCGG… | 3338 nt | 0.5989 | |
| GAACUGCGGCGGCGGCGAGCGCCGGCCGCAUCUGAGCAGAGCUGCAGCG… | 3684 nt | 0.6002 | |
| GAACUGCGGCGGCGGCGAGCGCCGGCCGCAUCUGAGCAGAGCUGCAGCG… | 3743 nt | 0.6001 | |
| GAACUGCGGCGGCGGCGAGCGCCGGCCGCAUCUGAGCAGAGCUGCAGCG… | 3590 nt | 0.5955 | |
| GAACUGCGGCGGCGGCGAGCGCCGGCCGCAUCUGAGCAGAGCUGCAGCG… | 3816 nt | 0.5933 | |
| GAACUGCGGCGGCGGCGAGCGCCGGCCGCAUCUGAGCAGAGCUGCAGCG… | 3512 nt | 0.5968 | |
| GAACUGCGGCGGCGGCGAGCGCCGGCCGCAUCUGAGCAGAGCUGCAGCG… | 3488 nt | 0.5960 | |
| GAACUGCGGCGGCGGCGAGCGCCGGCCGCAUCUGAGCAGAGCUGCAGCG… | 3534 nt | 0.6013 | |
| GAACUGCGGCGGCGGCGAGCGCCGGCCGCAUCUGAGCAGAGCUGCAGCG… | 3510 nt | 0.6006 |
This gene encodes a type of GTPase-activating-protein (GAP) that down-regulates the activity of the ras-related RAP1 protein. RAP1 acts as a molecular switch by cycling between an inactive GDP-bound form and an active GTP-bound form. The product of this gene, RAP1GAP, promotes the hydrolysis of bound GTP and hence returns RAP1 to the inactive state whereas other proteins, guanine nucleotide exchange factors (GEFs), act as RAP1 activators by facilitating the conversion of RAP1 from the GDP- to the GTP-bound form. In general, ras subfamily proteins, such as RAP1, play key roles in receptor-linked signaling pathways that control cell growth and differentiation. RAP1 plays a role in diverse processes such as cell proliferation, adhesion, differentiation, and embryogenesis. Alternative splicing results in multiple transcript variants encoding distinct proteins. [provided by RefSeq, Aug 2011]
A study in humans analyzed peripheral blood mRNA expression profiles from 127 Chinese individuals and identified the RAP1GAP as a differentially expressed gene exhibiting a consistent trend in expression from young adulthood to later life [Liao et al. DOI:10.1016/J.Fsigen.2025.103373]. This mRNA was selected as one of 34 candidate age-related genes and incorporated into a machine learning-based age prediction model, with the optimal elastic net model achieving a mean absolute error of 6.72 years on the test set.