Research progress and applications of genome‐wide association study in farm animals

Tan, Xiaodong; He, Zhengxiao; Fahey, Alan G.; Zhao, Guiping; Liu, Ranran; Wen, Jie

doi:10.1002/aro2.14

Cited by 8 publications

(3 citation statements)

References 328 publications

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“…The cattle dataset’s sample size is larger than the pig data. Still, we believe a larger sample size will improve statistical power and enhance the ability to detect genuine associations [ 54 ]. Second, the cattle dataset may exhibit an unaccounted population structure due to the samples’ different geographic origins.…”

Section: Discussionmentioning

confidence: 99%

Exploring the Interplay between the Hologenome and Complex Traits in Bovine and Porcine Animals Using Genome-Wide Association Analysis

Qadri,

Lai,

Zhao

et al. 2024

IJMS

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Genome-wide association studies (GWAS) significantly enhance our ability to identify trait-associated genomic variants by considering the host genome. Moreover, the hologenome refers to the host organism’s collective genetic material and its associated microbiome. In this study, we utilized the hologenome framework, called Hologenome-wide association studies (HWAS), to dissect the architecture of complex traits, including milk yield, methane emissions, rumen physiology in cattle, and gut microbial composition in pigs. We employed four statistical models: (1) GWAS, (2) Microbial GWAS (M-GWAS), (3) HWAS-CG (hologenome interaction estimated using COvariance between Random Effects Genome-based restricted maximum likelihood (CORE-GREML)), and (4) HWAS-H (hologenome interaction estimated using the Hadamard product method). We applied Bonferroni correction to interpret the significant associations in the complex traits. The GWAS and M-GWAS detected one and sixteen significant SNPs for milk yield traits, respectively, whereas the HWAS-CG and HWAS-H each identified eight SNPs. Moreover, HWAS-CG revealed four, and the remaining models identified three SNPs each for methane emissions traits. The GWAS and HWAS-CG detected one and three SNPs for rumen physiology traits, respectively. For the pigs’ gut microbial composition traits, the GWAS, M-GWAS, HWAS-CG, and HWAS-H identified 14, 16, 13, and 12 SNPs, respectively. We further explored these associations through SNP annotation and by analyzing biological processes and functional pathways. Additionally, we integrated our GWA results with expression quantitative trait locus (eQTL) data using transcriptome-wide association studies (TWAS) and summary-based Mendelian randomization (SMR) methods for a more comprehensive understanding of SNP-trait associations. Our study revealed hologenomic variability in agriculturally important traits, enhancing our understanding of host-microbiome interactions.

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Section: Discussionmentioning

confidence: 99%

Exploring the Interplay between the Hologenome and Complex Traits in Bovine and Porcine Animals Using Genome-Wide Association Analysis

Qadri,

Lai,

Zhao

et al. 2024

IJMS

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“…Their feed conversion ratio is ten times that of cattle, and the carbon emissions of broilers are only 1/10 of those of cattle 6 . Therefore, it is necessary to investigate genomic markers and genetic mechanisms related to economic traits via whole-genome sequencing to bridge the gap in production performance and accelerate breeding progress 7 .…”

Section: Background and Summarymentioning

confidence: 99%

Whole-genome variants dataset of 209 local chickens from China

Tan,

Zhang,

Dong

et al. 2024

Sci Data

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Compared to commercial chickens, local breeds exhibit better in meat quality and flavour, but the productivity (e.g., growth rate, body weight) of local chicken breeds is rather low. Genetic analysis based on whole-genome sequencing contributes to elucidating the genetic markers or putative candidate genes related to some economic traits, facilitating the improvement of production performance, the acceleration of breeding progress, and the conservation of genetic resources. Here, a total of 209 local chickens from 13 breeds were investigated, and the observation of approximately 91.4% high-quality sequences (Q30 > 90%) and a mapping rate over 99% for each individual indicated good results of this study, as confirmed by a genome coverage of 97.6%. Over 19 million single nucleotide polymorphisms (SNPs) and 1.98 million insertion-deletions (InDels) were identified using the reference genome (GRCg7b), further contributing to the public database. This dataset provides valuable resources for studying genetic diversity and adaptation and for the cultivation of new chicken breeds/lines.

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“…Growth traits are key in poultry breeding, and the properties of growth traits need to be considered in breeding for feed efficiency. In recent years, GWAS has been applied in poultry to explore the association between host genetics and economic traits [ 20 ]. Earlier studies identified candidate genes including NSUN3 , EPHA6 , and AGK for broilers RFI, while LAP3 was identified as a candidate gene for broiler body weight [ 21 – 26 ].…”

Section: Introductionmentioning

confidence: 99%

Genome-wide association analysis identify candidate genes for feed efficiency and growth traits in Wenchang chickens

Cai,

Liu,

Wei

et al. 2024

BMC Genomics

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Background Wenchang chickens are one of the most popular local chicken breeds in the Chinese chicken industry. However, the low feed efficiency is the main shortcoming of this breed. Therefore, there is a need to find a more precise breeding method to improve the feed efficiency of Wenchang chickens. In this study, we explored important candidate genes and variants for feed efficiency and growth traits through genome-wide association study (GWAS) analysis. Results Estimates of genomic heritability for growth and feed efficiency traits, including residual feed intake (RFI) of 0.05, average daily food intake (ADFI) of 0.21, average daily weight gain (ADG) of 0.24, body weight (BW) at 87, 95, 104, 113 days of age (BW87, BW95, BW104 and BW113) ranged from 0.30 to 0.44. Important candidate genes related to feed efficiency and growth traits were identified, such as PLCE1, LAP3, MED28, QDPR, LDB2 and SEL1L3 genes. Conclusion The results identified important candidate genes for feed efficiency and growth traits in Wenchang chickens and provide a theoretical basis for the development of new molecular breeding technology.

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Research progress and applications of genome‐wide association study in farm animals

Cited by 8 publications

References 328 publications

Exploring the Interplay between the Hologenome and Complex Traits in Bovine and Porcine Animals Using Genome-Wide Association Analysis

Exploring the Interplay between the Hologenome and Complex Traits in Bovine and Porcine Animals Using Genome-Wide Association Analysis

Whole-genome variants dataset of 209 local chickens from China

Genome-wide association analysis identify candidate genes for feed efficiency and growth traits in Wenchang chickens

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