Establishing an optimized ATAC-seq protocol for the maize.

The advent of next-generation sequencing in crop improvement offers unprecedented insights into the chromatin landscape closely linked to gene activity governing key traits in plant development and adaptation. Particularly in maize, its dynamic chromatin structure is found to collaborate with massive transcriptional variations across tissues and developmental stages, implying intricate regulatory mechanisms, which highlights the importance of integrating chromatin information into breeding strategies for precise gene controls. The depiction of maize chromatin architecture using Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq) provides great opportunities to investigate cis-regulatory elements, which is crucial for crop improvement. In this context, we developed an easy-to-implement ATAC-seq protocol for maize with fewer nuclei and simple equipment. We demonstrate a streamlined ATAC-seq protocol with four key steps for maize in which nuclei purification can be achieved without cell sorting and using only a standard bench-top centrifuge. Our protocol, coupled with the bioinformatic analysis, including validation by read length periodicity, key metrics, and correlation with transcript abundance, provides a precise and efficient assessment of the maize chromatin landscape. Beyond its application to maize, our testing design holds the potential to be applied to other crops or other tissues, especially for those with limited size and amount, establishing a robust foundation for chromatin structure studies in diverse crop species.

Estimating genome-wide DNA methylation heterogeneity with methylation patterns.

BACKGROUND: In a heterogeneous population of cells, individual cells can behave differently and respond variably to the environment. This cellular diversity can be assessed by measuring DNA methylation patterns. The loci with variable methylation patterns are informative of cellular heterogeneity and may serve as biomarkers of diseases and developmental progression. Cell-to-cell methylation heterogeneity can be evaluated through single-cell methylomes or computational techniques for pooled cells. However, the feasibility and performance of these approaches to precisely estimate methylation heterogeneity require further assessment. RESULTS: Here, we proposed model-based methods adopted from a mathematical framework originally from biodiversity, to estimate genome-wide DNA methylation heterogeneity. We evaluated the performance of our models and the existing methods with feature comparison, and tested on both synthetic datasets and real data. Overall, our methods have demonstrated advantages over others because of their better correlation with the actual heterogeneity. We also demonstrated that methylation heterogeneity offers an additional layer of biological information distinct from the conventional methylation level. In the case studies, we showed that distinct profiles of methylation heterogeneity in CG and non-CG methylation can predict the regulatory roles between genomic elements in Arabidopsis. This opens up a new direction for plant epigenomics. Finally, we demonstrated that our score might be able to identify loci in human cancer samples as putative biomarkers for early cancer detection. CONCLUSIONS: We adopted the mathematical framework from biodiversity into three model-based methods for analyzing genome-wide DNA methylation heterogeneity to monitor cellular heterogeneity. Our methods, namely MeH, have been implemented, evaluated with existing methods, and are open to the research community.

Rice transformation treatments leave specific epigenome changes beyond tissue culture.

During transgenic plant production, tissue culture often carries epigenetic, and genetic changes that underlie somaclonal variations, leading to unpredictable phenotypes. Additionally, specific treatments for rice (Oryza sativa) transformation processes may individually or jointly contribute to somaclonal variations, but their specific impacts on rice epigenomes toward transcriptional variations remain unknown. Here, the impact of individual transformation treatments on genome-wide DNA methylation and the transcriptome were examined. In addition to activating stress-responsive genes, individual transformation components targeted different gene expression modules that were enriched in specific functional categories. The transformation treatments strongly impacted DNA methylation and expression; 75% were independent of tissue culture. Furthermore, our genome-wide analysis showed that the transformation treatments consistently resulted in global hypo-CHH methylation enriched at promoters highly associated with downregulation, particularly when the promoters were colocalized with miniature inverted-repeat transposable elements. Our results clearly highlight the specificity of impacts triggered by individual transformation treatments during rice transformation with the potential association between DNA methylation and gene expression. These changes in gene expression and DNA methylation resulting from rice transformation treatments explain a significant portion of somaclonal variations, that is, way beyond the tissue culture effect.

There's more to it: uncovering genomewide DNA methylation heterogeneity.

Tweetable abstract Monitoring changes in methylation heterogeneity can be powerful in detecting disease progression early. This editorial highlights the importance of profiling methylation heterogeneity and identifies existing measures and research gaps.

Methylome Imputation by Methylation Patterns.

DNA methylation is studied extensively for its relations with several biological processes such as transcriptional regulation. While methylation levels are usually estimated per cytosine or genomic region, additional information on methylation heterogeneity can be obtained when considering stretches of successive cytosines on the same reads; however, the majority of methylomes suffer from low coverage of genomic regions with sequencing depths enough for accurate estimation of methylation heterogeneity using existing methods. Here we describe a probabilistic-based imputation method that makes use of methylation information from neighboring sites to recover partially observed methylation patterns. Our method and software are proven to be faster and more accurate among all evaluated. Ultimately, our method allows for a more streamlined monitoring of epigenetic changes within cellular populations and their putative role in disease.

MethylC-analyzer: a comprehensive downstream pipeline for the analysis of genome-wide DNA methylation.

DNA methylation is a crucial epigenetic modification involved in multiple biological processes and diseases. Current approaches for measuring genome-wide DNA methylation via bisulfite sequencing (BS-seq) include whole-genome bisulfite sequencing (WGBS), reduced representation bisulfite sequencing (RRBS), and enzymatic methyl-seq (EM-seq). The computational analysis tools available for BS-seq data include customized aligners for mapping bisulfite-converted reads and computational pipelines for downstream data analysis. Current post-alignment methylation tools are specialized for the interpretation of CG methylation, which is known to dominate mammalian genomes, however, non-CG methylation (CHG and CHH, where H refers to A, C, or T) is commonly observed in plants and fungi and is closely associated with gene regulation, transposon silencing, and plant development. Thus, we have developed a MethylC-analyzer to analyze and visualize post-alignment WGBS, RRBS, and EM-seq data focusing on CG. The tool is able to also analyze non-CG sites to enhance deciphering genomes of plants and fungi. By processing aligned data and gene location files, MethylC-analyzer generates a genome-wide view of methylation levels and methylation in user-specified genomic regions. The meta-plot, for example, allows the investigation of DNA methylation within specific genomic elements. Moreover, our tool identifies differentially methylated regions (DMRs) and investigates the enrichment of genomic features associated with variable methylation. MethylC-analyzer functionality is not limited to specific genomes, and we demonstrated its performance on both plant and human BS-seq data. MethylC-analyzer is a Python- and R-based program designed to perform comprehensive downstream analyses of methylation data, providing an intuitive analysis platform for scientists unfamiliar with DNA methylation analysis. It is available as either a standalone version for command-line uses or a graphical user interface (GUI) and is publicly accessible at https://github.com/RitataLU/MethylC-analyzer .

BSImp: Imputing Partially Observed Methylation Patterns for Evaluating Methylation Heterogeneity.

DNA methylation is one of the most studied epigenetic modifications that has applications ranging from transcriptional regulation to aging, and can be assessed by bisulfite sequencing (BS-seq) or enzymatic methyl sequencing (EM-seq) at single base-pair resolution. The permutations of methylation statuses given by aligned reads reflect the methylation patterns of individual cells. These patterns at specific genomic locations are sought to be indicative of cellular heterogeneity within a cellular population, which are predictive of developments and diseases; therefore, methylation heterogeneity has potentials in early detection of these changes. Computational methods have been developed to assess methylation heterogeneity using methylation patterns formed by four consecutive CpGs, but the nature of shotgun sequencing often give partially observed patterns, which makes very limited data available for downstream analysis. While many programs are developed to impute genome-wide methylation levels, currently there is only one method developed for recovering partially observed methylation patterns; however, the program needs lots of data to train and cannot be used directly; therefore, we developed a probabilistic-based imputation method that uses information from neighbouring sites to recover partially observed methylation patterns speedily. It is demonstrated to allow for the evaluation of methylation heterogeneity at 15% more regions genome-wide with high accuracy for data with moderate depth. To make it more user-friendly we also provide a computational pipeline for genome-screening, which can be used in both evaluating methylation levels and profiling methylation patterns genomewide for all cytosine contexts, which is the first of its kind. Our method allows for accurate estimation of methylation levels and makes evaluating methylation heterogeneity available for much more data with reasonable coverage, which has important implications in using methylation heterogeneity for monitoring changes within the cellular populations that were impossible to detect for the assessment of development and diseases.

HISTONE DEACETYLASE 15 and MOS4-associated complex subunits 3A/3B coregulate intron retention of ABA-responsive genes.

Histone deacetylases (HDAs) play an important role in transcriptional regulation of multiple biological processes. In this study, we investigated the function of HDA15 in abscisic acid (ABA) responses. We used immunopurification coupled with mass spectrometry-based proteomics to identify proteins interacting with HDA15 in Arabidopsis (Arabidopsis thaliana). HDA15 interacted with the core subunits of the MOS4-associated complex (MAC), MAC3A and MAC3B, with interaction between HDA15 and MAC3B enhanced by ABA. hda15 and mac3a/mac3b mutants were ABA-insensitive during seed germination and hyposensitive to salinity. RNA sequencing analysis demonstrated that HDA15 and MAC3A/MAC3B co-regulate ABA-responsive intron retention (IR). Furthermore, HDA15 reduced the histone acetylation level of genomic regions near ABA-responsive IR sites and the association of MAC3B with ABA-responsive pre-mRNA was dependent on HDA15. Our results indicate that HDA15 is involved in ABA responses by interacting with MAC3A/MAC3B to mediate splicing of introns.

EED is required for mouse primordial germ cell differentiation in the embryonic gonad.

Development of primordial germ cells (PGCs) is required for reproduction. During PGC development in mammals, major epigenetic remodeling occurs, which is hypothesized to establish an epigenetic landscape for sex-specific germ cell differentiation and gametogenesis. In order to address the role of embryonic ectoderm development (EED) and histone 3 lysine 27 trimethylation (H3K27me3) in this process, we created an EED conditional knockout mouse and show that EED is essential for regulating the timing of sex-specific PGC differentiation in both ovaries and testes, as well as X chromosome dosage decompensation in testes. Integrating chromatin and whole genome bisulfite sequencing of epiblast and PGCs, we identified a poised repressive signature of H3K27me3/DNA methylation that we propose is established in the epiblast where EED and DNMT1 interact. Thus, EED joins DNMT1 in regulating the timing of sex-specific PGC differentiation during the critical window when the gonadal niche cells specialize into an ovary or testis.

Blimp-1 molds the epigenetic architecture of IL-21-mediated autoimmune diseases through an autoregulatory circuit.

Positive regulatory domain 1 (PRDM1) encodes B lymphocyte-induced maturation protein 1 (BLIMP1), also known as a master regulator of T cell homeostasis. We observed a negative relationship between Blimp-1 and IL-21 based on our previous data that Blimp-1 overexpression in T cells suppresses autoimmune diabetes while Blimp-1-deficient T cells contribute to colitis in NOD mice. Reanalysis of published data sets also revealed an inverse correlation between PRDM1 and IL21 in Crohn's disease. Here, we illustrate that Blimp-1 repressed IL-21 by reducing chromatin accessibility and evicting an IL-21 activator, c-Maf, from the Il21 promoter. Moreover, Blimp-1 overexpression-mediated reduction in permissive chromatin structures at the Il21 promoter could override IL-21-accelerated autoimmune diabetogenesis in small ubiquitin-like modifier-defective c-Maf-transgenic mice. An autoregulatory feedback loop to harness IL-21 expression was unveiled by the evidence that IL-21 addition induced time-dependent Blimp-1 expression and subsequently enriched its binding to the Il21 promoter to suppress IL-21 overproduction. Furthermore, intervention of this feedback loop by IL-21 blockade, with IL-21R.Fc administration or IL-21 receptor deletion, attenuated Blimp-1 deficiency-mediated colitis and reinforced the circuit between Blimp-1 and IL-21 in the regulation of autoimmunity. We highlight the translation of Blimp-1-based epigenetic and transcriptomic profiles applicable to a personalized medicine approach in autoimmune diseases.

Aberrant overexpression of HOTAIR inhibits abdominal adipogenesis through remodelling of genome-wide DNA methylation and transcription.

OBJECTIVE: Abdominal adiposity is strongly associated with diabetic and cardiovascular comorbidities. The long noncoding RNA HOTAIR (HOX Transcript Antisense Intergenic RNA) is an important epigenetic regulator with fat depot-specific expression. Its functional roles and epigenetic regulation in abdominal adipogenesis remain uncertain. METHODS: We collected different fat depots from healthy, severely obese, and uraemic subjects to measure fat-depot specific gene expression and quantify regional adiposity via dual-energy X-ray absorptiometry (DXA). HOTAIR was overexpressed to evaluate its functional roles. Reduced representation bisulfite sequencing (RRBS), RNA-sequencing, real-time qPCR and RNA/chromatin immunoprecipitation were performed to analyse HOTAIR-mediated epigenetic regulation. RESULTS: A negative correlation between adipose tissue HOTAIR expression (arm or abdominal subcutaneous fat depots) and regional adiposity under the status of severe obesity or uraemia was observed. HOTAIR overexpression using human immortalized abdominal preadipocytes further revealed its anti-adipogenic effects. Integrative analysis of genome-wide DNA methylation by reduced representation bisulfite sequencing (RRBS) and gene expression was performed. Overall, the differentially methylated genes were functionally enriched for nervous system development, suggesting that HOTAIR may be epigenetically associated with cell lineage commitment. We specifically found that HOTAIR-mediated genes showed strong changes in both DNA methylation and gene expression during abdominal adipogenesis. We observed that two HOTAIR-repressed genes, SLITRK4 and PITPNC1, present an obesity-driven fat-depot specific expression pattern that is positively correlated with the central body fat distribution. CONCLUSIONS: Our study indicated that HOTAIR is a key regulator of abdominal adipogenesis via intricate DNA methylation and is likely to be associated with the transcriptional regulation of genes involved in nervous system development and lipid metabolism, such as SLITRK4 and PITPNC1.

Transcriptome Analysis of Dnmt3l Knock-Out Mice Derived Multipotent Mesenchymal Stem/Stromal Cells During Osteogenic Differentiation.

Multipotent mesenchymal stem/stromal cells (MSCs) exhibit great potential for cell-based therapy. Proper epigenomic signatures in MSCs are important for the maintenance and the subsequent differentiation potential. The DNA methyltransferase 3-like (DNMT3L) that was mainly expressed in the embryonic stem (ES) cells and the developing germ cells plays an important role in shaping the epigenetic landscape. Here, we report the reduced colony forming ability and impaired in vitro osteogenesis in Dnmt3l-knockout-mice-derived MSCs (Dnmt3l KO MSCs). By comparing the transcriptome between undifferentiated Dnmt3l KO MSCs and the MSCs from the wild-type littermates, some of the differentially regulated genes (DEGs) were found to be associated with bone-morphology-related phenotypes. On the third day of osteogenic induction, differentiating Dnmt3l KO MSCs were enriched for genes associated with nucleosome structure, peptide binding and extracellular matrix modulation. Differentially expressed transposable elements in many subfamilies reflected the change of corresponding regional epigenomic signatures. Interestingly, DNMT3L protein is not expressed in cultured MSCs. Therefore, the observed defects in Dnmt3l KO MSCs are unlikely a direct effect from missing DNMT3L in this cell type; instead, we hypothesized them as an outcome of the pre-deposited epigenetic signatures from the DNMT3L-expressing progenitors. We observed that 24 out of the 107 upregulated DEGs in Dnmt3l KO MSCs were hypermethylated in their gene bodies of DNMT3L knock-down ES cells. Among these 24 genes, some were associated with skeletal development or homeostasis. However, we did not observe reduced bone development, or reduced bone density through aging in vivo. The stronger phenotype in vitro suggested the involvement of potential spreading and amplification of the pre-deposited epigenetic defects over passages, and the contribution of oxidative stress during in vitro culture. We demonstrated that transient deficiency of epigenetic co-factor in ES cells or progenitor cells caused compromised property in differentiating cells much later. In order to facilitate safer practice in cell-based therapy, we suggest more in-depth examination shall be implemented for cells before transplantation, even on the epigenetic level, to avoid long-term risk afterward.

Mycena genomes resolve the evolution of fungal bioluminescence.

Mushroom-forming fungi in the order Agaricales represent an independent origin of bioluminescence in the tree of life; yet the diversity, evolutionary history, and timing of the origin of fungal luciferases remain elusive. We sequenced the genomes and transcriptomes of five bonnet mushroom species (Mycena spp.), a diverse lineage comprising the majority of bioluminescent fungi. Two species with haploid genome assemblies ∼150 Mb are among the largest in Agaricales, and we found that a variety of repeats between Mycena species were differentially mediated by DNA methylation. We show that bioluminescence evolved in the last common ancestor of mycenoid and the marasmioid clade of Agaricales and was maintained through at least 160 million years of evolution. Analyses of synteny across genomes of bioluminescent species resolved how the luciferase cluster was derived by duplication and translocation, frequently rearranged and lost in most Mycena species, but conserved in the Armillaria lineage. Luciferase cluster members were coexpressed across developmental stages, with the highest expression in fruiting body caps and stipes, suggesting fruiting-related adaptive functions. Our results contribute to understanding a de novo origin of bioluminescence and the corresponding gene cluster in a diverse group of enigmatic fungal species.

Thermal-responsive genetic and epigenetic regulation of DAM cluster controlling dormancy and chilling requirement in peach floral buds.

The Dormancy-associated MADS-box (DAM) gene cluster in peach serves as a key regulatory hub on which the seasonal temperatures act and orchestrate dormancy onset and exit, chilling response and floral bud developmental pace. Yet, how different temperature regimes interact with and regulate the six linked DAM genes remains unclear. Here, we demonstrate that chilling downregulates DAM1 and DAM3-6 in dormant floral buds with distinct patterns and identify DAM4 as the most abundantly expressed one. We reveal multiple epigenetic events, with tri-methyl histone H3 lysine 27 (H3K27me3) induced by chilling specifically in DAM1 and DAM5, a 21-nt sRNA in DAM3 and a ncRNA induced in DAM4. Such induction is inversely correlated with downregulation of their cognate DAMs. We also show that the six DAMs were hypermethylated, associating with the production of 24-nt sRNAs. Hence, the chilling-responsive dynamic of the different epigenetic elements and their interactions likely define distinct expression abundance and downregulation pattern of each DAM. We further show that the expression of the five DAMs remains steadily unchanged or continuously downregulated at the ensuing warm temperature after chilling, and this state of regulation correlates with robust increase of sRNA expression, H3K27me3 and CHH methylation, which is particularly pronounced in DAM4. Such robust increase of repressive epigenetic marks may irreversibly reinforce the chilling-imposed repression of DAMs to ensure flower-developmental programming free from any residual DAM inhibition. Taken together, we reveal novel information about genetic and epigenetic regulation of the DAM cluster in peach, which will be of fundamental significance in understanding of the regulatory mechanisms underlying chilling requirement and dormancy release, and of practical application for improvement of plasticity of flower time and bud break in fruit trees to adapt changing climates.

MethGET: web-based bioinformatics software for correlating genome-wide DNA methylation and gene expression.

BACKGROUND: DNA methylation is a major epigenetic modification involved in regulating gene expression. The effects of DNA methylation on gene expression differ by genomic location and vary across kingdoms, species and environmental conditions. To identify the functional regulatory roles of DNA methylation, the correlation between DNA methylation changes and alterations in gene expression is crucial. With the advance of next-generation sequencing, genome-wide methylation and gene expression profiling have become feasible. Current bioinformatics tools for investigating such correlation are designed to the assessment of DNA methylation at CG sites. The correlation of non-CG methylation and gene expression is very limited. Some bioinformatics databases allow correlation analysis, but they are limited to specific genomes such as that of humans and do not allow user-provided data. RESULTS: Here, we developed a bioinformatics web tool, MethGET (Methylation and Gene Expression Teller), that is specialized to analyse the association between genome-wide DNA methylation and gene expression. MethGET is the first web tool to which users can supply their own data from any genome. It is also the tool that correlates gene expression with CG, CHG, and CHH methylation based on whole-genome bisulfite sequencing data. MethGET not only reveals the correlation within an individual sample (single-methylome) but also performs comparisons between two groups of samples (multiple-methylomes). For single-methylome analyses, MethGET provides Pearson correlations and ordinal associations to investigate the relationship between DNA methylation and gene expression. It also groups genes with different gene expression levels to view the methylation distribution at specific genomic regions. Multiple-methylome analyses include comparative analyses and heatmap representations between two groups. These functions enable the detailed investigation of the role of DNA methylation in gene regulation. Additionally, we applied MethGET to rice regeneration data and discovered that CHH methylation in the gene body region may play a role in the tissue culture process, which demonstrates the capability of MethGET for use in epigenomic research. CONCLUSIONS: MethGET is a Python software that correlates DNA methylation and gene expression. Its web interface is publicly available at https://paoyang.ipmb.sinica.edu.tw/Software.html. The stand-alone version and source codes are available on GitHub at https://github.com/Jason-Teng/MethGET.

Epigenomic regulation of OTU5 in Arabidopsis thaliana.

Epigenetic regulation by DNA methylation and histone marks is crucial to plant development. In Arabidopsis, the otu5 mutant exhibited altered root phenotypes resembling those of phosphate-deficient plants. In low phosphate (Pi) conditions, altered H3K4 and H3K27 trimethylation were associated with the expression of Pi homeostasis-related genes. However, the genetic effect of OTU5 on the epigenomes was left unexplored. We assessed genome-wide DNA methylation, gene expression and histone modifications of roots from both Col-0 and otu5 mutants. We found that OTU5 altered DNA methylation profile with a context-specific effect through targeting local genomic regions. Our analysis showed that in otu5 the abundance of H3K4me3 was clearly associated with the changes of DNA methylation, leading to the transcriptional difference from wildtype. We concluded that OTU5 induced cross-talks among epigenomes that altogether impacted the regulation of approximately 7060 genes. Of which 186 genes associated with root development were likely to be epigenetically regulated.

EpiMOLAS: an intuitive web-based framework for genome-wide DNA methylation analysis.

BACKGROUND: DNA methylation is a crucial epigenomic mechanism in various biological processes. Using whole-genome bisulfite sequencing (WGBS) technology, methylated cytosine sites can be revealed at the single nucleotide level. However, the WGBS data analysis process is usually complicated and challenging. RESULTS: To alleviate the associated difficulties, we integrated the WGBS data processing steps and downstream analysis into a two-phase approach. First, we set up the required tools in Galaxy and developed workflows to calculate the methylation level from raw WGBS data and generate a methylation status summary, the mtable. This computation environment is wrapped into the Docker container image DocMethyl, which allows users to rapidly deploy an executable environment without tedious software installation and library dependency problems. Next, the mtable files were uploaded to the web server EpiMOLAS_web to link with the gene annotation databases that enable rapid data retrieval and analyses. CONCLUSION: To our knowledge, the EpiMOLAS framework, consisting of DocMethyl and EpiMOLAS_web, is the first approach to include containerization technology and a web-based system for WGBS data analysis from raw data processing to downstream analysis. EpiMOLAS will help users cope with their WGBS data and also conduct reproducible analyses of publicly available data, thereby gaining insights into the mechanisms underlying complex biological phenomenon. The Galaxy Docker image DocMethyl is available at https://hub.docker.com/r/lsbnb/docmethyl/. EpiMOLAS_web is publicly accessible at http://symbiosis.iis.sinica.edu.tw/epimolas/.

Construction and characterization of a knock-down RNA interference line of OsNRPD1 in rice (Oryza sativa ssp japonica cv Nipponbare).

In plants, RNA-directed DNA methylation (RdDM) is a silencing mechanism relying on the production of 24-nt small interfering RNAs (siRNAs) by RNA POLYMERASE IV (Pol IV) to trigger methylation and inactivation of transposable elements (TEs). We present the construction and characterization of osnrpd1, a knock-down RNA interference line of OsNRPD1 gene that encodes the largest subunit of Pol IV in rice (Oryza sativa ssp japonica cv Nipponbare). We show that osnrpd1 displays a lower accumulation of OsNRPD1 transcripts, associated with an overall reduction of 24-nt siRNAs and DNA methylation level in all three contexts, CG, CHG and CHH. We uncovered new insertions of known active TEs, the LTR retrotransposons Tos17 and Lullaby and the long interspersed nuclear element-type retrotransposon Karma. However, we did not observe any clear developmental phenotype, contrary to what was expected for a mutant severely affected in RdDM. In addition, despite the presence of many putatively functional TEs in the rice genome, we found no evidence of in planta global reactivation of transposition. This knock-down of OsNRPD1 likely led to a weakly affected line, with no effect on development and a limited effect on transposition. We discuss the possibility that a knock-out mutation of OsNRPD1 would cause sterility in rice. This article is part of a discussion meeting issue 'Crossroads between transposons and gene regulation'.

The expression of long non-coding RNAs is associated with H3Ac and H3K4me2 changes regulated by the HDA6-LDL1/2 histone modification complex in Arabidopsis.

In recent years, eukaryotic long non-coding RNAs (lncRNAs) have been identified as important factors involved in a wide variety of biological processes, including histone modification, alternative splicing and transcription enhancement. The expression of lncRNAs is highly tissue-specific and is regulated by environmental stresses. Recently, a large number of plant lncRNAs have been identified, but very few of them have been studied in detail. Furthermore, the mechanism of lncRNA expression regulation remains largely unknown. Arabidopsis HISTONE DEACETYLASE 6 (HDA6) and LSD1-LIKE 1/2 (LDL1/2) can repress gene expression synergistically by regulating H3Ac/H3K4me. In this research, we performed RNA-seq and ChIP-seq analyses to further clarify the function of HDA6-LDL1/2. Our results indicated that the global expression of lncRNAs is increased in hda6/ldl1/2 and that this increased lncRNA expression is particularly associated with H3Ac/H3K4me2 changes. In addition, we found that HDA6-LDL1/2 is important for repressing lncRNAs that are non-expressed or show low-expression, which may be strongly associated with plant development. GO-enrichment analysis also revealed that the neighboring genes of the lncRNAs that are upregulated in hda6/ldl1/2 are associated with various developmental processes. Collectively, our results revealed that the expression of lncRNAs is associated with H3Ac/H3K4me2 changes regulated by the HDA6-LDL1/2 histone modification complex.