Basic Information
Symbol
circPPP1R12A
RNA Class
circRNA
Alias
Protein Phosphatase 1 Regulatory Subunit 12A
MBS
Myosin Phosphatase-Targeting Subunit 1
MYPT1
M130
Protein Phosphatase 1, Regulatory (Inhibitor) Subunit 12A
Protein Phosphatase Myosin-Binding Subunit
Myosin Binding Subunit
Protein Phosphatase 1, Regulatory Subunit 12A
Myosin Phosphatase, Target Subunit 1
Myosin Phosphatase Target Subunit 1
GUBS
Location (GRCh37)
12:80109331-80328903
UCSC Genome Browser
Location (GRCh38)
12:79715551-79935123
Host gene
PPP1R12A
Host category
mRNA
Forensic tag(s)
Other applications
External database
Transcripts
| ID | Type | Location (GRCh37) | Location (GRCh38) | Length | GC content |
|---|---|---|---|---|---|
| hsa_PPP1R12A_0008700 | Intron-Exon | chr12:80199150-80199388 | chr12:79805370-79805608 | 239 nt | 0.3515 |
| hsa_PPP1R12A_0009000 | Exon-Exon | chr12:80199372-80200098 | chr12:79805592-79806318 | 330 nt | 0.4788 |
| hsa_PPP1R12A_0009500 | Exon-Exon | chr12:80199372-80203790 | chr12:79805592-79810010 | 216 nt | 0.4213 |
| hsa_PPP1R12A_0009100 | Exon-Exon | chr12:80199372-80211298 | chr12:79805592-79817518 | 886 nt | 0.4289 |
| hsa_PPP1R12A_0009200 | Exon-Exon | chr12:80199372-80222244 | chr12:79805592-79828464 | 1353 nt | 0.4139 |
| hsa_PPP1R12A_0009600 | Exon-Exon | chr12:80199372-80226271 | chr12:79805592-79832491 | 177 nt | 0.4972 |
| hsa_PPP1R12A_0009300 | Exon-Exon | chr12:80199372-80239200 | chr12:79805592-79845420 | 1632 nt | 0.4191 |
| hsa_PPP1R12A_0009400 | Exon-Exon | chr12:80199372-80266718 | chr12:79805592-79872938 | 1763 nt | 0.4169 |
| hsa_PPP1R12A_0009700 | Intron-Exon-Intron | chr12:80199729-80200132 | chr12:79805949-79806352 | 404 nt | 0.3886 |
| hsa_PPP1R12A_0009800 | Exon-Exon | chr12:80199946-80200113 | chr12:79806166-79806333 | 168 nt | 0.4583 |
Showing 101 to 110 of 218 entries
Forensic Context
A study in humans developed the CoraL framework to predict cancer-associated ncRNA-encoded small peptides (ncPEPs) from 15 cancer types, demonstrating high-confidence predictions with few samples and outperforming existing models [Li et al. DOI:10.1093/bib/bbad352].