Dynamic patterns of the translatome in a hybrid triplet show translational fractionation of the maize subgenomes

Heterosis,the phenomenon in which hybrids outperform their parents,has been utilized in maize(Zea mays L.)for over 100 years.To provide a more complete understanding of heterosis,we collected a comprehensive transcriptome and translatome dataset on seedling leaves for B73,Mo17,and their F1 hybrid,which provided a dynamic landscape of transcriptomic and translatomic variation in maize.Although additivity accounted for a large proportion of variation at two omics-levels,an elevated nonadditive effect was observed in the translatome,especially in the translated subgenome maize1 genes,and the genes that switched from additivity in the transcriptome to nonadditivity in the translatome were significantly enriched in the subgenome maize1.Many genes with allele-specific expression and translation show dramatic regulatory switches between the transcriptome and translatome,and partial genes with allele-specific translation underlying regulatory mechanism also exhibited subgenome bias.Interestingly,we found the translated isoforms show different expression patterns compared with transcriptome and more genes changed their dominant isoforms during the genetic flow from parents to the hybrid at the translatome level.The translated genes with switched dominant isoforms significantly biased to the subgenome maize2 while genes with conserved dominant isoforms significantly enriched in subgenome maize1.Together,the dynamic changed patterns in translatome across hybrid and parental lines show translational fractionation of the maize subgenomes,which may be associated with heterosis in maize and provides a potential theoretical basis for breeding.

A cost-effective ts CUT&Tag method for profiling transcription factor binding landscape

Knowledge of the transcription factor binding landscape(TFBL)is necessary to analyze gene regulatory networks for important agronomic traits.However,a low-cost and high-throughput in vivo chromatin profiling method is still lacking in plants.Here,we developed a transient and simplified cleavage under targets and tagmentation(tsCUT&Tag)that combines transient expression of transcription factor proteins in protoplasts with a simplified CUT&Tag without nucleus extraction.Our tsCUT&Tag method provided higher data quality and signal resolution with lower sequencing depth compared with traditional ChIP-seq.Furthermore,we developed a strategy combining tsCUT&Tag with machine learning,which has great potential for profiling the TFBL across plant development.