Deepwheat Predicting The Effects Of Genomic Variants On Gene Expression And Regulatory Activities Across Tissues And Varieties In Wheat Using Deep Learning Zhigang Ma Jiazi Zhang Hongcui Pei Yanhong Liu Hongning Tong Lei Wang Zefu Lu by Zhigang Ma & Jiazi Zhang & Hongcui Pei & Yanhong Liu & Hongning Tong & Lei Wang & Zefu Lu instant download after payment.

Genome Biology,Abstractto this work.Spatiotemporal gene expression shapes key agronomic traits, yet tissue-specifc *Correspondence: prediction remains challenging in complex crops. We present DeepWheat, a broadly [email protected] deep learning framework comprising DeepEXP and DeepEPI, for accurate, 1 State Key Laboratory of Crop tissue-specifc gene expression prediction. DeepEXP integrates sequence and epigGene Resources and Breeding, enomic features to predict gene expression (PCC 0.82–0.88), while DeepEPI predicts Institute of Crop Sciences, epigenomic maps from DNA sequence to support model transfer across varieties. Chinese Academy of Agricultural Validations in fve wheat cultivars confrm robustness and accuracy. DeepWheat Sciences, Beijing 100081, China 2 Center for Agricultural also identifes regulatory variants with strong expression efects, enabling targeted cisResources Research, Institute regulatory elements editing and ofering a powerful tool for crop functional genomics of Genetics and Developmental and breeding.Biology, Chinese Academy of Sciences, Shijiazhuang 050022,