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_0015200 | Intron-Exon-Intron | chr12:80215896-80242711 | chr12:79822116-79848931 | 181 nt | 0.4088 |
| hsa_PPP1R12A_0015300 | Intron-Intron | chr12:80217462-80217623 | chr12:79823682-79823843 | 162 nt | 0.5432 |
| hsa_PPP1R12A_0015400 | Intron-Intron | chr12:80218133-80218291 | chr12:79824353-79824511 | 159 nt | 0.3270 |
| hsa_PPP1R12A_0015500 | Intron-Exon-Intron | chr12:80221324-80222244 | chr12:79827544-79828464 | 921 nt | 0.3442 |
| hsa_PPP1R12A_0015600 | Intron-Exon-Intron | chr12:80221324-80251535 | chr12:79827544-79857755 | 62 nt | 0.4355 |
| hsa_PPP1R12A_0015700 | Intron-Exon-Intron | chr12:80221324-80266718 | chr12:79827544-79872938 | 312 nt | 0.4199 |
| hsa_PPP1R12A_0016000 | Exon-Exon | chr12:80222100-80239200 | chr12:79828320-79845420 | 424 nt | 0.4292 |
| hsa_PPP1R12A_0016100 | Intron-Exon-Intron | chr12:80222100-80299815 | chr12:79828320-79906035 | 305 nt | 0.4230 |
| hsa_PPP1R12A_0016200 | Exon-Exon | chr12:80222165-80239121 | chr12:79828385-79845341 | 200 nt | 0.4350 |
| hsa_PPP1R12A_0016300 | Intron-Intron | chr12:80223078-80223278 | chr12:79829298-79829498 | 201 nt | 0.3831 |
Showing 161 to 170 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].