SNAPC3 antibody - N-terminal region (ARP34174_T100)
- Known as:
- SNAPC3 (anti-) - N-terminal region (ARP34174_T100)
- Catalog number:
- arp34174_t100
- Product Quantity:
- USD
- Category:
- -
- Supplier:
- Aviva Systems Biology
- Gene target:
- SNAPC3 antibody - N-terminal region (ARP34174_T100)
Related genes to: SNAPC3 antibody - N-terminal region (ARP34174_T100)
- Gene:
- SNAPC3 NIH gene
- Name:
- small nuclear RNA activating complex polypeptide 3
- Previous symbol:
- -
- Synonyms:
- SNAP50, PTFbeta, MGC33124, MGC132011
- Chromosome:
- 9p22.3
- Locus Type:
- gene with protein product
- Date approved:
- 1996-04-12
- Date modifiied:
- 2015-11-09
Related products to: SNAPC3 antibody - N-terminal region (ARP34174_T100)
Related articles to: SNAPC3 antibody - N-terminal region (ARP34174_T100)
- Genome-wide association studies (GWAS) have identified numerous body mass index (BMI) loci. However, most underlying mechanisms from risk locus to BMI remain unknown. Leveraging omics data through integrative analyses could provide more comprehensive views of biological pathways on BMI. - Source: PubMed
Publication date: 2025/09/26
Xu HanfeiGupta ShreyashDinsmore IanKollu AbbeyCawley Anne MarieAnwar Mohammad YChen Hung-HsinPetty Lauren ESeshadri SudhaGraff MisaBelow Jennifer EBrody Jennifer AChittoor GeethaFisher-Hoch Susan PHeard-Costa Nancy LLevy DanielLin HonghuangLoos Ruth J FMccormick Joseph BRotter Jerome IMirshahi ToorajStill Christopher DDestefano AnitaCupples L AdrienneMohlke Karen LNorth Kari EJustice Anne ELiu Ching-Ti - The noncoding small nuclear RNAs (snRNAs) associate with a large set of proteins to form small nuclear ribonucleoprotein particles (snRNPs). While the function of snRNAs is well characterized, the regulation of their transcription remains poorly understood. Recently, we demonstrated that SUMO conjugation regulates snRNA3' end processing. To further study the connection between SUMOylation and snRNA biogenesis, we generated a CRISPR/dCas9 tool comprising a catalytically inactive Cas9 (dCas9) fused to the catalytic domain of the SUMO protease SENP1 (dCas9-SENP1). Here, we show that snRNA transcription decreases when dCas9-SENP1 is delivered to their promoter-proximal sequence elements (PSE), indicating that SUMO conjugation to proteins associated with snRNA promoters is necessary for proper transcriptional activity. Focusing on SNAPC1, a subunit of the snRNA-specific transcription complex SNAPc, we identified lysine residues 245 and 333 as SUMO acceptor sites and generated a SUMOylation-deficient mutant of this protein (SNAPC1 2KR). To explore the relevance of SNAPC1 SUMOylation on snRNA transcription, we generated a cell line carrying an inducible degron system for depletion of the endogenous SNAPC1 protein. This system led us to demonstrate that SNAPC1 2KR is unable to sustain basal levels of snRNA transcription. By tagging endogenous SNAPC3 and SNAPC4, two other subunits of SNAPc, we show that while SNAPC1 SUMOylation-deficient mutant is able to interact with SNAPC3, its interaction with SNAPC4 is affected, despite the fact it is still recruited to the PSE. Altogether, these results indicate that SNAPC1 SUMOylation is required for proper snRNA transcription and SNAPc complex assembly. - Source: PubMed
Publication date: 2025/09/16
Bragado LaureanoPozzi BertaBeckerman InésMagalnik MelinaSrebrow Anabella - KMT2A fusions are a critical oncogenic driver in 5% to 10% of patients with acute myeloid leukemia (AML) and are associated with poor prognosis. Currently, there are no published somatic guidelines for fusions in AML, and developing methods to accurately classify fusions, especially those involving KMT2A, is essential for patient care. Therefore, the Laboratory for Personalized Molecular Medicine (LabPMM) KMT2A Fusions Workflow was developed utilizing the framework of the somatic guidelines by Horak et al, where classification of oncogenicity is based on points awarded for varying types of evidence. Fusions previously detected by LabPMM's CAP/CLIA-certified MyAML and MyMRD gene panels were used to test this workflow. A total of 100 KMT2A fusions were reassessed, and 97 of these had a breakpoint in the major breakpoint cluster region. There were 20 distinct partner genes for KMT2A, and the most common partners were MLLT3, ELL, AFDN, MLLT10, and AFF1. Five KMT2A fusions had a novel partner (MYB, RC3H1, SNAPC3, STPG1, and HPSE2). Breakpoints in the partner genes were assessed to better understand their potential role in driving leukemogenesis. Of the 100 fusions reassessed, 9 had a classification change. This LabPMM KMT2A Fusions Workflow provides a points-based system for curation that allows for standardization and clarity both within and among genetic diagnostic laboratories reporting on KMT2A fusions in AML. - Source: PubMed
Publication date: 2025/07/22
Petersen Lauren MSainger RachanaSanchez PaulinaBurke JillianWemmer Joshua DPatay BradleyMiller Jeffrey E - Genome-wide association studies (GWAS) have identified numerous body mass index (BMI) loci. However, most underlying mechanisms from risk locus to BMI remain unknown. Leveraging omics data through integrative analyses could provide more comprehensive views of biological pathways on BMI. We analyzed genotype and blood gene expression data in up to 5,619 samples from the Framingham Heart Study (FHS). Using 3,992 single nucleotide polymorphisms (SNPs) at 97 BMI loci and 20,692 transcripts within 1 Mb, we performed separate association analyses of transcript with BMI and SNP with transcript (P and P, respectively) and then a correlated meta-analysis between the full summary data sets (P). We identified transcripts that met Bonferroni-corrected significance for each omic, were more significant in the correlated meta-analysis than each omic, and were at least nominally associated with BMI in FHS data. Among 308 significant SNP-transcript-BMI associations, we identified seven genes (, , , , , , and ) in five association regions. Using an independent sample of blood gene expression data, we validated results for and . We tested for generalization of these associations in hypothalamus, nucleus accumbens, and liver and observed significant (P<0.05 & PPublication date: 2024/06/12
Xu HanfeiGupta ShreyashDinsmore IanKollu AbbeyCawley Anne MarieAnwar Mohammad YChen Hung-HsinPetty Lauren ESeshadri SudhaGraff MisaBelow PiperBrody Jennifer AChittoor GeethaFisher-Hoch Susan PHeard-Costa Nancy LLevy DanielLin HonghuangLoos Ruth JfMccormick Joseph BRotter Jerome IMirshahi ToorajStill Christopher DDestefano AnitaCupples L AdrienneMohlke Karen LNorth Kari EJustice Anne ELiu Ching-Ti - The role of breastfeeding in modulating epigenetic factors has been suggested as a possible mechanism conferring its benefits on child development but it lacks evidence. Using extensive DNA methylation data from the ALSPAC child cohort, we characterized the genome-wide landscape of DNA methylation variations associated with the duration of exclusive breastfeeding and assessed whether these variations mediate the association between exclusive breastfeeding and BMI over different epochs of child growth. - Source: PubMed
Publication date: 2021/12/22
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