Identifying candidate genetic variants for egg number by analyzing over 1,000 fully sequenced layers
We identified candidate genetic variants for egg production traits by analyzing 1,004 fully sequenced layers. Detection benefited from incorporating dominance into the GWAS model. Traits with higher heterosis tended to be more affected by genes with a dominant mode of action. Moreover, multiomics data allowed for the contribution to deciphering genetic mechanisms underlying egg production by establishing connections between genetic variants, gene expression, and egg number.
Authors
- Yunlei Li (ORCID: https://orcid.org/0000-0001-8117-6232)
- M.P.L. Calus (ORCID: https://orcid.org/0000-0002-3213-704X)
- Aixin Ni (ORCID: https://orcid.org/0009-0002-7938-1231)
- Henk Bovenhuis (ORCID: https://orcid.org/0000-0002-9074-5334)
- Yanyan Sun (ORCID: https://orcid.org/0000-0001-6425-7786)
- Jilan Chen (ORCID: https://orcid.org/0000-0002-9400-009X)
- Jingwei Yuan
Institutions
- Chinese Academy of Agricultural Sciences (CN)
- Ministry of Agriculture and Rural Affairs (CN)
- Wageningen University & Research (NL)
Publication Details
- Journal
- GigaScience
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1093/gigascience/giaf064
- Citations
- 2
- Primary Topic
- Genetic Mapping and Diversity in Plants and Animals
- Type
- article
- Field-Weighted Citation Impact
- 3.63
Funders
- National Natural Science Foundation of China
- Chinese Academy of Agricultural Sciences
- Agricultural Science and Technology Innovation Program