Integrating mRNA transcripts and genomic information into genomic prediction
Received date: 2024-04-08
Revised date: 2024-05-24
Online published: 2024-06-03
Supported by
National Natural Science Foundation of China(32002148);Scientific Research Fund of Hunan Provincial Education Department(22B0219);Natural Science Foundation of Hunan Province(2022JJ30286);Hunan Association for Science and Technology Talent Support Project(2022TJ-Q15);Hunan Province Enterprise Technology Innovation and Entrepreneurship Team Project]
Genomic prediction has emerged as a pivotal technology for the genetic evaluation of livestock, crops, and for predicting human disease risks. However, classical genomic prediction methods face challenges in incorporating biological prior information such as the genetic regulation mechanisms of traits. This study introduces a novel approach that integrates mRNA transcript information to predict complex trait phenotypes. To evaluate the accuracy of the new method, we utilized a Drosophila population that is widely employed in quantitative genetics researches globally. Results indicate that integrating mRNA transcript data can significantly enhance the genomic prediction accuracy for certain traits, though it does not improve phenotype prediction accuracy for all traits. Compared with GBLUP, the prediction accuracy for olfactory response to dCarvone in male Drosophila increased from 0.256 to 0.274. Similarly, the accuracy for cafe in male Drosophila rose from 0.355 to 0.401. The prediction accuracy for survival_paraquat in male Drosophila is improved from 0.101 to 0.138. In female Drosophila, the accuracy of olfactory response to 1hexanol increased from 0.147 to 0.210. In conclusion, integrating mRNA transcripts can substantially improve genomic prediction accuracy of certain traits by up to 43%, with range of 7% to 43%. Furthermore, for some traits, considering interaction effects along with mRNA transcript integration can lead to even higher prediction accuracy.
Key words： genomic selection; genomic prediction; mRNA transcripts; integrative omics
Yulong Hu, Fang Yang, Yantong Chen, Shuokai Shen, Yubo Yan, Yuebo Zhang, Xiaolin Wu, Jiaming Wang, Jun He, Ning Gao . Integrating mRNA transcripts and genomic information into genomic prediction[J]. Hereditas(Beijing), 2024 , 46(7) : 560 -569 . DOI: 10.16288/j.yczz.24-096
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