GRAMMAR-Lambda Delivers Efficient Understanding of the Genetic Basis for Head Size in Catfish
文献类型: 外文期刊
第一作者: Zhao, Yunfeng
作者: Zhao, Yunfeng;Zhao, Yunfeng;Jiang, Li;Gao, Jin;Feng, Hong
作者机构:
关键词:
linear mixed model; EMMAX;
期刊名称:BIOLOGY-BASEL ( 影响因子:3.5; 五年影响因子:4.0 )
ISSN:
年卷期: 2025 年 14 卷 1 期
页码:
收录情况: SCI
摘要: The shape of the skull plays a crucial role in the evolution and adaptation of species to their environments. In the case of aquaculture fish, the size of the head is also an important economic trait, as it is linked to fillet yield and ornamental value. This study applies our GRAMMAR-Lambda method to perform a genome-wide association study analysis on loci related to head size in catfish. Compared with traditional GWAS methods, the GRAMMAR-Lambda method offers higher computational efficiency, statistical power, and stability, especially in complex population structures. This research identifies many candidate genes closely related to cranial morphology in terms of head length, width, and depth in catfish, including bmpr1bb, fgfrl1b, nipbl, foxp2, and pax5, etc. Based on the results of gene-gene interaction analysis, we speculate that there may be frequent genetic interactions between chromosome 19 and chromosome 29 in bone development. Additionally, many candidate genes, gene families, and mechanisms (such as SOCE mechanisms) affecting skeletal development and morphology have been identified. These findings contribute to our understanding of the genetic architecture of head size and will support marker-assisted breeding in aquaculture, also reflecting the potential application of the GRAMMAR-Lambda method in genetic studies of complex traits.
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