Change point analysis of histone modifications reveals epigenetic blocks linking to physical domains

Histone modification is a vital epigenetic mechanism for transcriptional control in eukaryotes. High-throughput techniques have enabled whole-genome analysis of histone modifications in recent years. However, most studies assume one combination of histone modification invariantly translates to one transcriptional output regardless of local chromatin environment. In this study we hypothesize that, the genome is organized into local domains that manifest similar enrichment pattern of histone modification, which leads to orchestrated regulation of expression of genes with relevant biological functions. We propose a multivariate Bayesian Change Point (BCP) model to segment the Drosophila melanogaster genome into consecutive blocks on the basis of combinatorial patterns of histone marks. By modeling the sparse distribution of histone marks with a zero-inflated Gaussian mixture, our partitions capture local BLOCKs that manifest relatively homogeneous enrichment pattern of histone marks. We further characterized BLOCKs by their transcription levels, distribution of genes, degree of co-regulation and GO enrichment. Our results demonstrate that these BLOCKs, although inferred merely from histone modifications, reveal strong relevance with physical domains, which suggests their important roles in chromatin organization and coordinated gene regulation

Change point analysis of histone modifications reveals epigenetic blocks linking to physical domains

Histone modification is a vital epigenetic mechanism for transcriptional control in eukaryotes. High-throughput techniques have enabled whole-genome analysis of histone modifications in recent years. However, most studies assume one combination of histone modification invariantly translates to one transcriptional output regardless of local chromatin environment. In this study we hypothesize that, the genome is organized into local domains that manifest similar enrichment pattern of histone modification, which leads to orchestrated regulation of expression of genes with relevant biological functions. We propose a multivariate Bayesian Change Point (BCP) model to segment the Drosophila melanogaster genome into consecutive blocks on the basis of combinatorial patterns of histone marks. By modeling the sparse distribution of histone marks with a zero-inflated Gaussian mixture, our partitions capture local BLOCKs that manifest relatively homogeneous enrichment pattern of histone marks. We further characterized BLOCKs by their transcription levels, distribution of genes, degree of co-regulation and GO enrichment. Our results demonstrate that these BLOCKs, although inferred merely from histone modifications, reveal strong relevance with physical domains, which suggests their important roles in chromatin organization and coordinated gene regulation

The Bipartite Network Projection-Recommended Algorithm for Predicting Long Non-coding RNA-Protein Interactions

With the development of science and biotechnology, many evidences show that ncRNAs play an important role in the development of important biological processes, especially in chromatin modification, cell differentiation and proliferation, RNA progressing, human diseases, etc. Moreover, lncRNAs account for the majority of ncRNAs, and the functions of lncRNAs are expressed by the related RNA-binding proteins. It is well known that the experimental verification of lncRNA-protein relationships is a waste of time and expensive. So many time-saving and inexpensive computational methods are proposed to uncover potential lncRNA-protein interactions. In this work, we propose a novel computational method to predict the potential lncRNA-protein interactions with the bipartite network projection recommended algorithm (LPI-BNPRA). Our approach is a semi-supervised method based on the lncRNA similarity matrix, protein similarity matrix, and lncRNA-protein interaction matrix. Compared with three previous methods under the leave-one-out cross-validation, our model has a more high-confidence result with the AUC value of 0.8754 and the AUPR value of 0.6283. We also do case studies by the Mus musculus dataset to further reflect the reliability of our approach. This suggests that LPI-BNPRA will be a reliable computational method to uncover lncRNA-protein interactions in biomedical research. Keywords: lncRNA, protein, lncRNA-protein interaction prediction, semi-supervised method, recommended algorith

Exploring AlphaFold2′s Performance on Predicting Amino Acid Side-Chain Conformations and Its Utility in Crystal Structure Determination of B318L Protein

Recent technological breakthroughs in machine-learning-based AlphaFold2 (AF2) are pushing the prediction accuracy of protein structures to an unprecedented level that is on par with experimental structural quality. Despite its outstanding structural modeling capability, further experimental validations and performance assessments of AF2 predictions are still required, thus necessitating the development of integrative structural biology in synergy with both computational and experimental methods. Focusing on the B318L protein that plays an essential role in the African swine fever virus (ASFV) for viral replication, we experimentally demonstrate the high quality of the AF2 predicted model and its practical utility in crystal structural determination. Structural alignment implies that the AF2 model shares nearly the same atomic arrangement as the B318L crystal structure except for some flexible and disordered regions. More importantly, side-chain-based analysis at the individual residue level reveals that AF2′s performance is likely dependent on the specific amino acid type and that hydrophobic residues tend to be more accurately predicted by AF2 than hydrophilic residues. Quantitative per-residue RMSD comparisons and further molecular replacement trials suggest that AF2 has a large potential to outperform other computational modeling methods in terms of structural determination. Additionally, it is numerically confirmed that the AF2 model is accurate enough so that it may well potentially withstand experimental data quality to a large extent for structural determination. Finally, an overall structural analysis and molecular docking simulation of the B318L protein are performed. Taken together, our study not only provides new insights into AF2′s performance in predicting side-chain conformations but also sheds light upon the significance of AF2 in promoting crystal structural determination, especially when the experimental data quality of the protein crystal is poor

Research on Acoustic Emission and Electromagnetic Emission Characteristics of Rock Fragmentation at Different Loading Rates

The relationships among the generation of acoustic emission, electromagnetic emission, and the fracture stress of rock grain are investigated, which are based on the mechanism of acoustic emission and electromagnetic emission produced in the process of indenting rock. Based on the relationships, the influence of loading rate on the characteristics of acoustic emission and electromagnetic emission of rock fragmentation is further discussed. Experiment on rock braking was carried out with three loading rates of 0.001 mm/s, 0.01 mm/s, and 0.1 mm/s. The results show that the phenomenon of acoustic emission and electromagnetic emission is produced during the process of loading and breaking rock. The wave forms of the two signals and the curve of the cutter indenting load show jumping characteristics. Both curves have good agreement with each other. With the increase of loading rate, the acoustic emission and electromagnetic emission signals are enhanced. Through analysis, it is found that the peak count rate, the energy rate of acoustic emission, the peak intensity, the number of pulses of the electromagnetic emission, and the loading rate have a positive correlation with each other. The experimental results agree with the theoretical analysis. The proposed studies can lead to an in-depth understanding of the rock fragmentation mechanism and help to prevent rock dynamic disasters

Simulation Study on the Structure Design of p-GaN/AlGaN/GaN HEMT-Based Ultraviolet Phototransistors

This work investigates the impacts of structural parameters on the performances of p-GaN/AlGaN/GaN HEMT-based ultraviolet (UV) phototransistors (PTs) using Silvaco Atlas. The simulation results show that a larger Al content or greater thickness for the AlGaN barrier layer can induce a higher two-dimensional electron gas (2DEG) density and produce a larger photocurrent. However, they may also lead to a larger dark current due to the incomplete depletion of the GaN channel layer. The depletion conditions with various Al contents and thicknesses of the AlGaN layer are investigated in detail, and a borderline between full depletion and incomplete depletion was drawn. An optimized structure with an Al content of 0.23 and a thickness of 14 nm is achieved for UV-PT, which exhibits a high photocurrent density of 92.11 mA/mm, a low dark current density of 7.68 × 10−10 mA/mm, and a large photo-to-dark-current ratio of over 1011 at a drain voltage of 5 V. In addition, the effects of other structural parameters, such as the thickness and hole concentration of the p-GaN layer as well as the thickness of the GaN channel layer, on the performances of the UV-PTs are also studied in this work

Transcriptome Profiling Reveals Molecular Responses to Salt Stress in Common Vetch (<i>Vicia sativa</i> L.)

Common vetch (Vicia sativa L.) is an important annual diploid leguminous forage. In the present study, transcriptomic profiling in common vetch in response to salt stress was conducted using a salt-tolerant line (460) and a salt-sensitive line (429). The common responses in common vetch and the specific responses associated with salt tolerance in 460 were analyzed. Several KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, including plant hormone and MAPK (mitogen-activated protein kinase) signaling, galactose metabolism, and phenylpropanoid phenylpropane biosynthesis, were enriched in both lines, though some differentially expressed genes (DEGs) showed distinct expression patterns. The roots in 460 showed higher levels of lignin than in 429. α-linolenic acid metabolism, carotenoid biosynthesis, the photosynthesis-antenna pathway, and starch and sucrose metabolism pathways were specifically enriched in salt-tolerant line 460, with higher levels of accumulated soluble sugars in the leaves. In addition, higher transcript levels of genes involved in ion homeostasis and reactive oxygen species (ROS) scavenging were observed in 460 than in 429 in response to salt stress. The transcriptomic analysis in common vetch in response to salt stress provides useful clues for further investigations on salt tolerance mechanism in the future

Association of triglyceride-glucose index with cardiovascular disease among a general population: a prospective cohort study

Abstract Background The impact of triglyceride-glucose (TyG) index, a surrogate marker for insulin resistance, on the risk of cardiovascular disease (CVD) in general populations remains controversial. We aimed to comprehensively study the relationship between TyG index with the risk of incident CVD events in the general population in Shanghai. Methods A total of 42,651 participants without previous history of CVD events from Shanghai Suburban Adult Cohort and Biobank (SSACB) were included. SSACB was a community-based natural population cohort study using multistage cluster sampling method. TyG index was calculated as Ln [fasting serum triglyceride (mg/dL) * fasting blood glucose (mg/dL)/2]. Kaplan-Meier curves, log-rank test and cox proportional hazards model were used to calculate the association between TyG index and incident CVD, including stroke and coronary heart disease (CHD). Restricted cubic spline analyses were used to determine whether there was a non-linear relationship between TyG index and CVD events. Results During a median follow-up of 4.7 years, 1,422 (3.3%) individuals developed CVD, including 674 (1.6%) cases of stroke and 732 (1.7%) cases of CHD. A one unit increment higher TyG index was associated with [HR(95%CI)] 1.16(1.04–1.29) in CVD and with 1.39(1.19–1.61) in stroke. Only linear relationships between TyG and CVD/stroke were observed, while no relationship was observed with CHD after adjustments for confounders. In subgroup analyses, younger (< 50y) and diabetic participants had higher risk of CVD than their counterpart groups, while hypertensive and dyslipidemic participants depicted lower risks than their counterparts. Conclusion Elevated TyG index was associated with a higher risk of incident CVD and stroke. TyG index may help in the early stage of identifying people at high risk of CVD