Project description:DNA N6-methyldeoxyadenosine (6mA) is a well known prokaryotic DNA modification and has been shown to exist and play epigenetic roles in eukaryotic DNA. Here we report that 6mA accumulates up to 0.1% of total deoxyadenosine during early embryogenesis of vertebates, but diminishes with progression of the embryo development. During this process most 6mA locates in repetitive regions of the genome.
Project description:The R-loop is a common chromatin feature presented from prokaryotic to eukaryotic genomes and has been revealed to be involved in multiple cellular processes and associated with many human diseases. Here, we take the advantage of our recently developed ssDRIP method to profile genome-wide R-loop levels and provided a first-hand R-loop atlas during Arabidopsis development and in response to various environmental factors.
2020-02-19 | GSE116232 | GEO
Project description:Environmental DNA detection of plant biodiversity
Project description:RNAs are well-suited to act as cellular sensors that detect and respond to metabolite changes in the environment due to their ability to fold into complex structures. Here, we introduce a genome-wide strategy called PARCEL that experimentally identifies RNA aptamers in vitro, in a high-throughput manner. By applying PARCEL to a collection of prokaryotic and eukaryotic organisms, we have revealed 58 new RNA aptamers to three key metabolites, greatly expanding the list of natural RNA aptamers. The newly identified RNA aptamers exhibit significant sequence conservation, are highly structured and show an unexpected prevalence in coding regions. We identified a prokaryotic precursor tmRNA that acts as a vitamin B2 (FMN) binder to facilitate its maturation, as well as new coding-region eukaryotic riboswitches that bind and respond to FMN, highlighting FMN as a second class of eukaryotic riboswitches. PARCEL results show that RNA-based sensing and gene regulation is more widespread than previously appreciated in different organisms.
Project description:DNA methylation is an important regulator of genome function in the eukaryotes, but it is currently unclear if the same is true in prokaryotes. While regulatory functions have been demonstrated for a small number of bacteria, there have been no large-scale studies of prokaryotic methylomes and the full repertoire of targets and biological functions of DNA methylation remains unclear. Here we applied single-molecule, real-time sequencing to directly study the methylomes of 232 phylogenetically diverse prokaryotes. Collectively, we identified 834 methylated motifs, enabling the specific annotation of 415 DNA methyltransferases (MTases), and adding substantially to existing databases of MTase specificities. While the majority of MTases function as components of restriction-modification systems, 139 MTases have no cognate restriction enzyme in the genome, suggesting some other functional role. Several of these âorphanâ MTases are conserved across species and exhibit patterns of DNA methylation consistent with known regulatory MTases. Based on these patterns of methylation, we identify candidate novel regulators of gene expression in several phyla of bacteria, and candidate regulators of DNA replication in Haloarchaea. Together these data substantially advance our knowledge of DNA restriction-modification systems, and hint at a wider role for methylation in prokaryotic genome regulation. Single-molecule, real-time sequencing of DNA modifications across 232 diverse prokaryotic genomes.
Project description:The poly(A)+ and poly(A)− fractions of interacting and non-interacting cells were used for distinct library preparation of interacting and non-interacting prokaryotic pathogen and eukaryotic host cells by deepSuperSAGE. Sequencing was performed with the Illumina HiSeq 2000 platform, and one point of time post infection (early interaction) was additionally prepared by Massive Analysis of cDNA Ends (MACE) as alternative tag-based library preparation method.
Project description:We extended the mathematical models of measuring biodiversity to estimate DNA methylation heterogeneity in a cell population. We propose a model-based approach (abundance-based, phylogeny-based and pairwise similarity-based heterogeneity) and consider similarity in DNA methylation patterns from individual cells to evaluate heterogeneity that overcomes biases due to missing data. We also applied commonly used non-model based method (methylation entropy) and other reported methods of estimating methylation heterogeneity such as single-cell based approach to evaluate methylation heterogeineity.
Project description:The poly(A)+ and poly(A)− fractions of interacting and non-interacting cells were used for distinct library preparation of interacting and non-interacting prokaryotic pathogen and eukaryotic host cells by deepSuperSAGE. Sequencing was performed with the Illumina HiSeq 2000 platform, and one point of time post infection (early interaction) was additionally prepared by Massive Analysis of cDNA Ends (MACE) as alternative tag-based library preparation method. 10 deepSuperSAGE and 2 MACE libraries. Please consult the publication mentioned in the following for more details.