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Pleiotropy data resource as a primer for investigating co-morbidities/multi-morbidities and their role in disease
Mammalian Genome ( IF 2.5 ) Pub Date : 2021-09-15 , DOI: 10.1007/s00335-021-09917-w
Violeta Muñoz-Fuentes 1 , Hamed Haselimashhadi 1 , Helen Parkinson 1 , Jeremy Mason 1 , Luis Santos 2 , Henrik Westerberg 2
Affiliation  

Most current biomedical and protein research focuses only on a small proportion of genes, which results in a lost opportunity to identify new gene-disease associations and explore new opportunities for therapeutic intervention. The International Mouse Phenotyping Consortium (IMPC) focuses on elucidating gene function at scale for poorly characterized and/or under-studied genes. A key component of the IMPC initiative is the implementation of a broad phenotyping pipeline, which is facilitating the discovery of pleiotropy. Characterizing pleiotropy is essential to identify gene-disease associations, and it is of particular importance when elucidating the genetic causes of syndromic disorders. Here we show how the IMPC is effectively uncovering pleiotropy and how the new mouse models and gene function hypotheses generated by the IMPC are increasing our understanding of the mammalian genome, forming the basis of new research and identifying new gene-disease associations.



中文翻译:

多效性数据资源作为调查合并症/多发病及其在疾病中的作用的入门

大多数当前的生物医学和蛋白质研究仅关注一小部分基因,这导致失去了识别新基因疾病关联和探索治疗干预新机会的机会。国际小鼠表型分析联盟 (IMPC) 专注于大规模阐明特征不佳和/或研究不足的基因的基因功能。IMPC 计划的一个关键组成部分是广泛的表型分析管道的实施,这有助于发现多效性。表征多效性对于识别基因-疾病关联至关重要,在阐明综合征的遗传原因时尤为重要。

更新日期:2021-09-16
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