Suppr超能文献

GWAS 图谱:一个整合了更多在动植物中经过精心整理的关联信息的更新知识库。

GWAS Atlas: an updated knowledgebase integrating more curated associations in plants and animals.

机构信息

National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China.

CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China.

出版信息

Nucleic Acids Res. 2023 Jan 6;51(D1):D969-D976. doi: 10.1093/nar/gkac924.

Abstract

GWAS Atlas (https://ngdc.cncb.ac.cn/gwas/) is a manually curated resource of genome-wide genotype-to-phenotype associations for a wide range of species. Here, we present an updated implementation of GWAS Atlas by curating and incorporating more high-quality associations, with significant improvements and advances over the previous version. Specifically, the current release of GWAS Atlas incorporates a total of 278,109 curated genotype-to-phenotype associations for 1,444 different traits across 15 species (10 plants and 5 animals) from 830 publications and 3,432 studies. A collection of 6,084 lead SNPs of 439 traits and 486 experiment-validated causal variants of 157 traits are newly added. Moreover, 1,056 trait ontology terms are newly defined, resulting in 1,172 and 431 terms for Plant Phenotype and Trait Ontology and Animal Phenotype and Trait Ontology, respectively. Additionally, it is equipped with four online analysis tools and a submission platform, allowing users to perform data analysis and data submission. Collectively, as a core resource in the National Genomics Data Center, GWAS Atlas provides valuable genotype-to-phenotype associations for a diversity of species and thus plays an important role in agronomic trait study and molecular breeding.

摘要

GWAS 图谱 (https://ngdc.cncb.ac.cn/gwas/) 是一个手动整理的基因组范围基因型-表型关联资源,涵盖了广泛的物种。在这里,我们通过整理和纳入更多高质量的关联信息,对 GWAS 图谱进行了更新实现,相较于之前的版本有了显著的改进和进步。具体来说,GWAS 图谱的当前版本共整理和纳入了 15 个物种(10 种植物和 5 种动物)的 830 篇文献和 3432 项研究中的 278109 个与 1444 个不同性状相关的经证实的基因型-表型关联。新增加了 6084 个 439 个性状的主要 SNP 和 157 个性状的 486 个实验验证的因果变异。此外,还新定义了 1056 个性状本体术语,分别产生了 1172 个和 431 个植物表型和性状本体术语和动物表型和性状本体术语。此外,它还配备了四个在线分析工具和一个提交平台,允许用户进行数据分析和数据提交。总之,作为国家基因组学数据中心的核心资源,GWAS 图谱为多种物种提供了有价值的基因型-表型关联,因此在农业性状研究和分子育种中发挥着重要作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b3b/9825481/aafb180228dc/gkac924fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验