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The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions, using signals from nanopore direct RNA sequencing. CHEUI processes observed and expected signals with convolutional neural networks to achieve high single-molecule accuracy and outperform other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions.
The expanding field of epitranscriptomics might rival the epigenome in the diversity of the biological processes impacted. However, the identification of modifications in individual RNA molecules remains challenging. We present CHEUI, a new method that detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) at single-nucleotide and single-molecule resolution from Nanopore signals. CHEUI predicts methylation in Nanopore reads and transcriptomic sites in a single condition, and differential m6A and m5C methylation between any two conditions. Using extensive benchmarking with Nanopore data derived from synthetic and natural RNA, CHEUI showed higher accuracy than other existing methods in detecting m6A and m5C sites and quantifying the site stoichiometry levels, while maintaining a lower proportion of false positives. CHEUI provides a new capability to detect RNA modifications with high accuracy and resolution that can be cost-effectively expanded to other modifications to unveil the full span of the epitranscriptome in normal and disease conditions.
Abstract
Natural plant populations often harbour substantial heritable variation in DNA methylation. However, a thorough understanding of the genetic and environmental drivers of this epigenetic variation requires large-scale and high-resolution data, which currently exist only for a few model species. Here, we studied 207 lines of the annual weed Thlaspi arvense (field pennycress), collected across a large latitudinal gradient in Europe and propagated in a common environment. By screening for variation in DNA sequence and DNA methylation using whole-genome (bisulfite) sequencing, we found significant epigenetic population structure across Europe. Average levels of DNA methylation were strongly context-dependent, with highest DNA methylation in CG context, particularly in transposable elements and in intergenic regions. Residual DNA methylation variation within all contexts was associated with genetic variants, which often co-localized with annotated methylation machinery genes but also with new candidates. Variation in DNA methylation was also significantly associated with climate of origin, with methylation levels being higher in warmer regions and lower in more variable climates. Finally, we used variance decomposition to assess genetic versus environmental associations with differentially methylation regions (DMRs). We found that while genetic variation was generally the strongest predictor of DMRs, the strength of environmental associations increased from CG to CHG and CHH, with climate-of-origin as the strongest predictor in about one third of the CHH DMRs. In summary, our data show that natural epigenetic variation in Thlaspi arvense is significantly associated with both DNA sequence and environment of origin, and that the relative importance of the two factors strongly depends on the sequence context of DNA methylation. T. arvense is an emerging biofuel and winter cover crop; our results may hence be relevant for breeding efforts and agricultural practices in the context of rapidly changing environmental conditions.
Author Summary: Variation within species is an important level of biodiversity, and it is key for future adaptation. Besides variation in DNA sequence, plants also harbour heritable variation in DNA methylation, and we want to understand the evolutionary significance of this epigenetic variation, in particular how much of it is under genetic control, and how much is associated with the environment. We addressed these questions in a high-resolution molecular analysis of 207 lines of the common plant field pennycress (Thlaspi arvense), which we collected across Europe, propagated under standardized conditions, and sequenced for their genetic and epigenetic variation. We found large geographic variation in DNA methylation, associated with both DNA sequence and climate of origin. Genetic variation was generally the stronger predictor of DNA methylation variation, but the strength of environmental association varied between different sequence contexts. Climate-of-origin was the strongest predictor in about one third of the differentially methylated regions in the CHH context, which suggests that epigenetic variation may play a role in the short-term climate adaptation of pennycress. As pennycress is currently being domesticated as a new biofuel and winter cover crop, our results may be relevant also for agriculture, particularly in changing environments.
RNA-binding proteins (RBPs) control every RNA metabolic process by multiple protein-RNA and protein-protein interactions. Their roles have largely been analyzed by crude mutations, which abrogate multiple functions at once and likely impact the structural integrity of the large messenger ribonucleoprotein particle (mRNP) assemblies, these proteins often function in. Using UV-induced RNA-protein crosslinking and subsequent mass spectrometric analysis, we first identified more than 100 in vivo RNA crosslinks in 16 nuclear mRNP components in S. cerevisiae. For functional analysis, we chose Npl3, for which we determined crosslinks in its two RNA recognition motifs (RRM) and in the flexible linker region connecting the two. Using NMR and structural analyses, we show that both RRM domains and the linker uniquely contribute to RNA recognition. Interestingly, mutations in these regions cause different phenotypes, indicating distinct functions of the different RNA-binding domains of Npl3. Notably, the npl3-Linker mutation strongly impairs recruitment of several mRNP components to chromatin and incorporation of further mRNP components into nuclear mRNPs, establishing a function of Npl3 in nuclear mRNP assembly. Taken together, we determined the specific function of the RNA-binding activity of the nuclear mRNP component Npl3, an approach that can be applied to many RBPs in any RNA metabolic process.
Mollusca is the second-largest animal phylum with over 100,000 species among eight distinct taxonomic classes. Across 1000 living species in the class Polyplacophora, chitons have a relatively constrained morphology but with some notable deviations. Several genera possess “shell eyes”, true eyes with a lens and retina that are embedded within the dorsal shells, which represent the most recent evolution of animal eyes. The phylogeny of major chiton clades is mostly well established, in a set of superfamily and higher-level taxa supported by various approaches including multiple gene markers, mitogenome-phylogeny and phylotranscritomic approaches as well as morphological studies. However, one critical lineage has remained unclear: Schizochiton was controversially suggested as a potential independent origin of chiton shell eyes. Here, with the draft genome sequencing of Schizochiton incisus (superfamily Schizochitonoidea) plus assembly of transcriptome data from other polyplacophorans, we present phylogenetic reconstructions using both mitochondrial genomes and phylogenomic approaches with multiple methods. Phylogenetic trees from mitogenomic data are inconsistent, reflecting larger scale confounding factors in molluscan mitogenomes. A consistent robust topology was generated with protein coding genes using different models and methods. Our results support Schizochitonoidea is a sister group to other Chitonoidea in Chitonina, in agreement with established classification. This suggests that the earliest origin of shell eyes is in Schizochitonoidea, which were also gained secondarily in other genera in Chitonoidea. Our results have generated a holistic review of the internal relationship within Polyplacophora, and a better understanding on the evolution of Polyplacophora.
The phase diagram of the (1+1)-dimensional Gross-Neveu model is reanalyzed for (non-)zero chemical potential and (non-)zero temperature within the mean-field approximation. By investigating the momentum dependence of the bosonic two-point function, the well-known second-order phase transition from the Z2 symmetric phase to the so-called inhomogeneous phase is detected. In the latter phase the chiral condensate is periodically varying in space and translational invariance is broken. This work is a proof of concept study that confirms that it is possible to correctly localize second-order phase transition lines between phases without condensation and phases of spatially inhomogeneous condensation via a stability analysis of the homogeneous phase. To complement other works relying on this technique, the stability analysis is explained in detail and its limitations and successes are discussed in context of the Gross-Neveu model. Additionally, we present explicit results for the bosonic wave-function renormalization in the mean-field approximation, which is extracted analytically from the bosonic two-point function. We find regions -- a so-called moat regime -- where the wave function renormalization is negative accompanying the inhomogeneous phase as expected.
The phase diagram of the (1+1)-dimensional Gross-Neveu model is reanalyzed for (non-)zero chemical potential and (non-)zero temperature within the mean-field approximation. By investigating the momentum dependence of the bosonic two-point function, the well-known second-order phase transition from the Z2 symmetric phase to the so-called inhomogeneous phase is detected. In the latter phase the chiral condensate is periodically varying in space and translational invariance is broken. This work is a proof of concept study that confirms that it is possible to correctly localize second-order phase transition lines between phases without condensation and phases of spatially inhomogeneous condensation via a stability analysis of the homogeneous phase. To complement other works relying on this technique, the stability analysis is explained in detail and its limitations and successes are discussed in context of the Gross-Neveu model. Additionally, we present explicit results for the bosonic wave-function renormalization in the mean-field approximation, which is extracted analytically from the bosonic two-point function. We find regions -- a so-called moat regime -- where the wave function renormalization is negative accompanying the inhomogeneous phase as expected.
We study the μ-μ45-T phase diagram of the 2+1-dimensional Gross-Neveu model, where μ denotes the ordinary chemical potential, μ45 the chiral chemical potential and T the temperature. We use the mean-field approximation and two different lattice regularizations with naive chiral fermions. An inhomogeneous phase at finite lattice spacing is found for one of the two regularizations. Our results suggest that there is no inhomogeneous phase in the continuum limit. We show that a chiral chemical potential is equivalent to an isospin chemical potential. Thus, all results presented in this work can also be interpreted in the context of isospin imbalance.
We demonstrate ultra-sharp (≲10 nm) lateral p-n junctions in graphene using electronic transport, scanning tunneling microscopy, and first principles calculations. The p-n junction lies at the boundary between differentially-doped regions of a graphene sheet, where one side is intrinsic and the other is charge-doped by proximity to a flake of α-RuCl3 across a thin insulating barrier. We extract the p-n junction contribution to the device resistance to place bounds on the junction width. We achieve an ultra-sharp junction when the boundary between the intrinsic and doped regions is defined by a cleaved crystalline edge of α-RuCl3 located 2 nm from the graphene. Scanning tunneling spectroscopy in heterostructures of graphene, hexagonal boron nitride, and α-RuCl3 shows potential variations on a sub-10 nm length scale. First principles calculations reveal the charge-doping of graphene decays sharply over just nanometers from the edge of the α-RuCl3 flake.