Contrastive modelling of transcription and transcript abundance in legumes using PlanTT

Predicting the impacts of sequence variation on gene expression remains a challenging task. Further, in plants, we have a limited understanding of the relative contributions of different gene expression regulatory mechanisms. To address these limitations we generated a comparative multiomic dataset comprising matched 3’-RNA-seq and PRO-seq data from matched tissues of reference genotypes of four legumes of the invert repeat lacking clade ( Pisum sativum, Vicia faba, Lathyrus sativa and Medicago truncatula ). Focused on the challenging task of predicting expression differences between ortholog pairs from unseen orthogroups, we used this dataset and a novel prediction framework to build contrastive models that predict quantitative differences (effect size differences) in transcription and transcript abundance.