Back

Epigenetic modifications mediate cultivar-specific root development and metabolic adaptation to nitrogen availability in wheat

Zhang, H.; Cui, F.; Zhao, L.; Zhang, X.; Chen, J.; Zhang, J.; Li, Y.; Niu, Y.; Wang, L.; Gao, C.; Fu, X.; Tong, Y.; Ling, H.-Q.; Li, J.; Xiao, J.

2023-02-26 plant biology
10.1101/2023.02.24.529862 bioRxiv
Show abstract

The breeding of crops with improved nitrogen use efficiency (NUE) is crucial for sustainable agriculture. However, the role of epigenetic modification in the regulation of cultivar-specific responses to low nitrogen (LN) constraint is not well understood. Here, we analyzed the chromatin landscapes in roots, leaves, and seeds in two wheat cultivars (KN9204 and J411) that differ radically in NUE under normal and nitrogen-limited conditions. Transcriptional regulatory chromatin regions exhibited a clear cultivar-specificity between KN9204 and J411. Cultivar-specific regulation of nitrogen metabolism genes (NMGs) is linked to variation in histone modification levels, rather than differences in DNA sequence. Cultivar-specific histone modification regions were found to contribute to the genetic regulation of NUE-related traits, such as QTL locus of maximum root length of qMRL-7B. Furthermore, LN-induced H3K27ac and H3K27me3 dynamics enhanced root growth more in KN9204, while strengthened the nitrogen uptake system more in J411. Evidence from histone deacetylase inhibitor treatment and transgenic plants with loss-of-function of the H3K27me3 methyltransferase further showed that changes in epigenetic modifications can alter the strategy for root development and nitrogen uptake in response to LN constraint. Taken together, the results of our study highlight the importance of epigenetic regulation in mediating cultivar-specific root development and metabolic adaptation to LN in wheat.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.