基因组预测已成为畜禽、作物遗传评估和人类疾病风险预测的主要技术，但经典的基因组预测方法在性状遗传调控机制等生物学先验信息的整合方面有一定的不足。本研究提出一种将mRNA转录本信息整合应用于复杂性状表型预测的方法。基于国际上广泛应用于数量遗传学研究的果蝇群体，对本研究提出的新方法进行准确性评估。结果显示，整合mRNA转录本，可有效提高部分性状基因组预测准确性，但对部分性状的表型预测准确性没有改善。与GBLUP相比，雄性果蝇D-香芹酮嗅觉反应(dCarvone)准确性由0.256提高到0.274，提高幅度7%。雄性果蝇咖啡因耐受反应(cafe)准确性由0.355提高到0.401，提高幅度13%。雄性果蝇百草枯耐受反应(survival_paraquat)准确性由0.101提高到0.138，提高幅度36%。雌性果蝇1-已醇嗅觉反应(1hexanol)准确性由0.147提高到0.210，提高幅度43%。综上所述，对于部分性状，通过整合mRNA转录本可有效提高基因组预测准确性(提高幅度为7%~43%)。对于部分性状，整合mRNA转录本并考虑互作效应可进一步提高预测准确性。

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.