Rnf103-KO Mouse
一般名
Rnf103-KO
製品ID
S-KO-18605
背景情報
C57BL/6JCya
系統ID
KOCMP-22644-Rnf103-B6J-VB
状況
このマウス系統を論文で使用する場合は、「Rnf103-KO Mouse（カタログ番号S-KO-18605）はサイアジェンから購入しました。」と引用してください。
製品タイプ
年齢
遺伝子型
性別
数量
標準的な配送方法では、少なくとも3匹のヘテロ接合体キャリアを保証しています。ホモ接合体キャリアや指定された性別の個体の繁殖サービスも利用可能です。
基本情報
系統名
Rnf103-KO
系統ID
KOCMP-22644-Rnf103-B6J-VB
遺伝子名
製品ID
S-KO-18605
遺伝子別名
kf-1, Zfp103
遺伝子別名
C57BL/6JCya
NCBI ID
修正
Conventional knockout
染色体
Chr 6
表現型
アプリケーション
--
さらに
系統詳細
EnsemblトランスクリプトID
ENSMUST00000064637
NCBIトランスクリプトID
NM_009543
ターゲット領域
Exon 2
有効領域の大きさ
~1.7 kb
遺伝子研究の概要
Rnf103, or ring finger protein 103, encodes an E3 ubiquitin-protein ligase. E3 ubiquitin-protein ligases play a crucial role in the ubiquitination process, which is involved in many cellular pathways such as protein degradation, cell cycle regulation, and immune response [1,5].
In a study on Vibrio anguillarum infection in aquaculture, Rnf103 was identified as a key target in the immune evasion mechanism of this pathogen. It promotes immune escape by inhibiting Traf6. Additionally, a circular RNA (circRNA) called circRnf103, formed by reverse splicing of the Rnf103 gene, was discovered. circRnf103 encodes Rnf103-177aa, a protein that competes with Rnf103 and binds to Traf6, preventing its degradation. In zebrafish models, circRnf103 therapy effectively treated V. anguillarum infections, reducing organ burden [1].
In the context of diabetic foot ulcers, through machine-learning-driven analysis, RNF103-CHMP3 (a possible related entity) was identified as a key gene significantly associated with the disease, linked to extracellular interactions and potentially involved in cellular communication and tissue repair mechanisms for wound healing [2].
In a pan-cancer study, RNF103-CHMP3 was found among genes that co-occurred mutations with CD8A, implicating it in the regulation of cancer-related pathways [3].
In a study on Alzheimer's disease, Rnf103 was determined as one of six characteristic genes, enabling the precise prediction of AD progression [4].
In pigs, Rnf103 was considered as a genetic marker for growth traits [6].
In a study on lipid phenotypes, Rnf103 was associated with triglycerides [7].
In conclusion, Rnf103 is involved in multiple biological processes and disease conditions. Its role in immune evasion, wound healing, cancer-related pathways, Alzheimer's disease prediction, pig growth, and lipid metabolism has been demonstrated through various research models. These findings contribute to our understanding of the underlying mechanisms of these biological processes and diseases, potentially providing new directions for treatment and management.
References：
1. Zheng, Weiwei, Lv, Xing, Tao, Yaqi, Zhu, Tongtong, Xu, Tianjun. 2023. A circRNA therapy based on Rnf103 to inhibit Vibrio anguillarum infection. In Cell reports, 42, 113314. doi:10.1016/j.celrep.2023.113314. https://pubmed.ncbi.nlm.nih.gov/37874674/
2. Yu, Xin, Wu, Zhuo, Zhang, Nan. 2024. Machine learning-driven discovery of novel therapeutic targets in diabetic foot ulcers. In Molecular medicine (Cambridge, Mass.), 30, 215. doi:10.1186/s10020-024-00955-z. https://pubmed.ncbi.nlm.nih.gov/39543487/
3. Niu, Decao, Chen, Yifeng, Mi, Hua, Mo, Zengnan, Pang, Guijian. 2022. The epiphany derived from T-cell-inflamed profiles: Pan-cancer characterization of CD8A as a biomarker spanning clinical relevance, cancer prognosis, immunosuppressive environment, and treatment responses. In Frontiers in genetics, 13, 974416. doi:10.3389/fgene.2022.974416. https://pubmed.ncbi.nlm.nih.gov/36035168/
4. Lai, Yongxing, Lin, Xueyan, Lin, Chunjin, Chen, Zhihan, Zhang, Li. 2022. Identification of endoplasmic reticulum stress-associated genes and subtypes for prediction of Alzheimer's disease based on interpretable machine learning. In Frontiers in pharmacology, 13, 975774. doi:10.3389/fphar.2022.975774. https://pubmed.ncbi.nlm.nih.gov/36059957/
5. Scheper, Johanna, Oliva, Baldo, Villà-Freixa, Jordi, Thomson, Timothy M. . Analysis of electrostatic contributions to the selectivity of interactions between RING-finger domains and ubiquitin-conjugating enzymes. In Proteins, 74, 92-103. doi:10.1002/prot.22120. https://pubmed.ncbi.nlm.nih.gov/18615712/
6. Li, Xiaoping, Kim, Sang-Wook, Do, Kyoung-Tag, Choi, Bong-Hwan, Kim, Kwan-Suk. 2010. Analyses of porcine public SNPs in coding-gene regions by re-sequencing and phenotypic association studies. In Molecular biology reports, 38, 3805-20. doi:10.1007/s11033-010-0496-1. https://pubmed.ncbi.nlm.nih.gov/21107721/
7. Li, Changwei, Bazzano, Lydia A L, Rao, Dabeeru C, Lu, Xiangfeng, Kelly, Tanika N. 2015. Genome-wide linkage and positional association analyses identify associations of novel AFF3 and NTM genes with triglycerides: the GenSalt study. In Journal of genetics and genomics = Yi chuan xue bao, 42, 107-17. doi:10.1016/j.jgg.2015.02.003. https://pubmed.ncbi.nlm.nih.gov/25819087/
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凍結前の精子濃度を測定し、精子の生存能力の判定します。
凍結後の精子では、各バッチから1本の凍結保存された精子を選び出し、体外受精に使用します。
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