Ask about this productRelated genes to: LOC51252 antibody
- Gene:
- FAM178B NIH gene
- Name:
- family with sequence similarity 178 member B
- Previous symbol:
- -
- Synonyms:
- LOC51252
- Chromosome:
- 2q11.2
- Locus Type:
- gene with protein product
- Date approved:
- 2008-07-18
- Date modifiied:
- 2016-09-30
Related products to: LOC51252 antibody
Related articles to: LOC51252 antibody
- Mammalian Y chromosomes acquire lineage-specific gene families with spermatogenic functions in male fertility, a mechanism that counters Y chromosome decay. However, in most mammals, the mechanisms by which Y chromosomes acquire new gene families and the benefits they confer to males remain poorly understood. Here, we discover that deer mice (Peromyscus) acquired a lineage-specific, massively amplified Y-linked gene family, Phf8y. Phf8y arose via the transposition of autosomal Phf8l, which previously arose via retrotransposition from an X-linked gene, PHD-finger protein 8 (Phf8). Phf8y, Phf8l, and Phf8 are expressed in haploid spermatids, where their encoded proteins each bind FAM178B in Mus musculus and Peromyscus maniculatus, while PHF8 binds ZFP711 in both species, suggesting that PHF8L/PHF8Y have similar functions. By contrast, Mus musculus PHF8L and P. maniculatus PHF8 and PHF8Y bind ZFP318, distinct from PHF8 interactors. We deleted Phf8l in M. musculus and found that neither the loss of Phf8l alone nor the loss of Phf8l and Phf8 together resulted in overt spermatogenesis defects or male infertility. However, Phf8l preferentially represses X-linked genes, and Phf8l and Phf8 cooperatively repress long interspersed element 1 (LINE1) retrotransposons and 5S rRNA. The specific regulation of X-linked genes by Phf8l suggests that while Phf8l does not influence X-bearing versus Y-bearing sperm fitness in M. musculus, acquisition of Phf8y on the Peromyscus Y chromosome may influence sperm fitness. Peromyscus Phf8y resembles the Y-linked Ssty gene family in M. musculus, which is in an evolutionary arms race, suggesting acquired Y-amplified, spermatid-specific gene families are genetic signatures of sex chromosome evolutionary arms races. - Source: PubMed
Publication date: 2026/05/13
Mier Ivan FArlt Martin FLawson Ann MarieDulka Eden AWooldridge T BrockHoekstra Hopi EMueller Jacob L - Accurate preoperative evaluation of lymph node metastasis (LNM) status in patients with papillary thyroid carcinoma (PTC) is essential for the development of individualized diagnosis and treatment strategies; however, the predictive performance of current clinical approaches remains limited. This study aims to identify key molecular biomarkers associated with LNM in PTC, construct LNM-risk prediction models using machine learning (ML) algorithms, and assess their potential value in supporting clinical decision-making. - Source: PubMed
Zhan ZhijunChen LuSun YanZeng JiaxingLi NingYin JundaTan HailongChang Shi - Genome-wide association studies (GWAS) have discovered 27 loci associated with glioma risk. Whether these loci are causally implicated in glioma risk, and how risk differs across tissues, has yet to be systematically explored. We integrated multi-tissue expression quantitative trait loci (eQTLs) and glioma GWAS data using a combined Mendelian randomisation (MR) and colocalisation approach. We investigated how genetically predicted gene expression affects risk across tissue type (brain, estimated effective n = 1194 and whole blood, n = 31,684) and glioma subtype (all glioma (7400 cases, 8257 controls) glioblastoma (GBM, 3112 cases) and non-GBM gliomas (2411 cases)). We also leveraged tissue-specific eQTLs collected from 13 brain tissues (n = 114 to 209). The MR and colocalisation results suggested that genetically predicted increased gene expression of 12 genes were associated with glioma, GBM and/or non-GBM risk, three of which are novel glioma susceptibility genes (RETREG2/FAM134A, FAM178B and MVB12B/FAM125B). The effect of gene expression appears to be relatively consistent across glioma subtype diagnoses. Examining how risk differed across 13 brain tissues highlighted five candidate tissues (cerebellum, cortex, and the putamen, nucleus accumbens and caudate basal ganglia) and four previously implicated genes (JAK1, STMN3, PICK1 and EGFR). These analyses identified robust causal evidence for 12 genes and glioma risk, three of which are novel. The correlation of MR estimates in brain and blood are consistently low which suggested that tissue specificity needs to be carefully considered for glioma. Our results have implicated genes yet to be associated with glioma susceptibility and provided insight into putatively causal pathways for glioma risk. - Source: PubMed
Publication date: 2021/01/27
Robinson Jamie WMartin Richard MTsavachidis SpiridonHowell Amy ERelton Caroline LArmstrong Georgina NBondy MelissaZheng JieKurian Kathreena M