Dataset Information

Histone code dynamics during nitrogen response in tomato

ABSTRACT: In plants, environmental stimuli trigger rapid transcriptional reprogramming of relevant gene suites. Regulation occurs down to the local chromatin landscape of the genes, and while epigenetic modifications proceed in a manner dependent on specific organ and tissue contexts, detailed investigations at this level remain limited. To better understand the organ specificity of dynamic chromatin modifications in response to external signals, we treated nitrogen-limited tomato seedlings with a supply of nitrate and measured the genome-wide changes of four histone marks, the permissive histone marks H3K27ac, H3K4me3, and H3K36me3 and repressive mark H3K27me3, in shoots and roots separately. We observed dynamic histone acetylation and methylation events which are largely organ-specific in scope at functionally relevant gene loci. Integration of transcriptomic and epigenomic datasets generated from the same tissue samples revealed largely syngenetic relations between changes in transcript levels and histone modifications, with the exception of H3K27me3 where an increased level at genes up-regulated in response to nitrate supply is observed in only the shoots. This non-canonical pattern of H3K27me3 deposition could possibly function to prevent over-expression of certain activated genes. To study the determinant roles of histone code in predicting gene regulation at the genome-wide level we applied a machine learning approach. While gene regulation could be best predicted using all four histone marks together, we observed different rules regarding the importance of individual histone marks between shoots, where H3K36me3 is the most successful mark in predicting gene activation and repression events, and the roots, where H3K4me3 is the strongest individual predictor. In summary, our integrated study substantiates a view that during plant environmental responses, the histone code dynamics that govern relationships between chromatin modification and gene regulation are highly dependent on tissue specific contexts.

ORGANISM(S): Solanum lycopersicum

PROVIDER: GSE196887 | GEO | 2023/11/08

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:In comparison with provision of either ammonium or nitrate alone, simultaneously supplying both forms of N results in superior growth and yield for the majority of plants including rice. Using a rice 22K oligo-array, we performed transcriptome analysis to identify genes of rice (Oryza sativa L. ssp. japonica) responsive to change of N-supply forms and N-starvation. Using the supply of ammonium nitrate (one to one molar ratio) as control, the total number of root genes that were equal or more than two fold up- or down- regulated was 445, 324, and 781 by upon supply of either ammonium or nitrate or continuous N starvation, respectively for 96 h. In the shoot the equivalent numbers were much smaller only 32, 58, and 165, respectively. Clustering of the rice genes associated with different environmental stresses revealed substantial organ specificity of the root and shoot to N starvation, and also to the N supply form. Genes encoding transporters for ammonium and nitrate, nitrate reductase, glutamate dehydrogenase, and aspartate amino transferase, showed great response to change of the N supply form, especially to N starvation. Some of the genes involved in chlorophyll metabolism, carbon fixation and assimilation, were enhanced by ammonium supply only, but significantly suppressed by N-starvation. In the shoot there was increased expression of more general stress genes under nitrate when compared to ammonium nutrition. In the root the reverse situation was true with more apparent stress under ammonium nutrition. The microarray approach has revealed new levels of complexity in the response of rice to the form of N supply. Experiment Overall Design: Rice seedlings were grown in a hydroponic system in a growth chamber with control of both temperature and light. After normal growth for two weeks and for one week with completely avoiding any N source, the plants at four and a half leaf stage were re-supplied with ammonium nitrate (equal amount of either form of N), or only ammonium (ammonium sulphate and ammonium chloride), or only nitrate (calcium nitrate and magnesium nitrate), and continuing at zero N (N starvation). All the other essential nutrients were the same for all four treatments, except for sulfate and chloride which ranged between 1.1 â 2.6 mM and 0.5 â 2.5 mM, respectively. In Arabidopsis, addition of 3 mM Cl to âcontrolsâ did not produce any changes in the expression of genes in an experiment investigating the re-supply of 3 mM nitrate (Scheible et al., 2004). In other microarray experiments, extra addition of 5 mM Cl for Arabidopsis (Wang et al., 2000; Wang et al., 2004) and 1.4 mM sulphate for tomato (Wang et al., 2001) were used to replace nitrate for identifying the N deprivation responsive genes. Therefore, we assume that the relative smaller difference in sulfate and chloride concentrations among the four treatments in the normal supply range for plants would not significantly affect the expression profile of genes responsible for changes in N supply form and starvation in our experiments. Experiment Overall Design: For identifying the genes responding to the various N conditions by micro-array analysis, we extracted total RNA respectively from the roots and shoots at the 96 h after initiation of the four respective treatments. We used amplified and labeled cRNA from ammonium nitrate treatment as control, we performed array-hybridization for the cRNA from the treatment of single ammonium form, single nitrate form, or continuous N depletion, respectively. Agilent 60-mer oligonucleotide arrays containing 21,938 unique transcription units (Agilent Technologies, Tokyo, Japan) were used. Two biological replicates of each treatment were performed for microarray analyses.

Dataset Information

Histone code dynamics during nitrogen response in tomato

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure