High-throughput Sequencing Methods Research Articles

Spatial transcriptomics reveals gene interactions and signaling pathway dynamics in rat embryos with anorectal malformation

Anorectal malformation (ARM) is a prevalent early pregnancy digestive tract anomaly. The intricate anatomy of the embryonic cloaca region makes it challenging for traditional high-throughput sequencing methods to capture location-specific information. Spatial transcriptomics was used to sequence libraries of frozen sections from embryonic rats at gestational days (GD) 14 to 16, covering both normal and ARM cases. Bioinformatics analyses and predictions were performed using methods such as WGCNA, GSEA, and PROGENy. Immunofluorescence staining was used to verify gene expression levels. Gene expression data was obtained with anatomical annotations of clusters, focusing on the cloaca region's location-specific traits. WGCNA revealed gene modules linked to normal and ARM cloacal anatomy development, with cooperation between modules on GD14 and GD15. Differential gene expression profiles and functional enrichment were presented. Notably, protein levels of Pcsk9, Hmgb2, and Sod1 were found to be downregulated in the GD15 ARM hindgut. The PROGENy algorithm predicted the activity and interplay of common signaling pathways in embryonic sections, highlighting their synergistic and complementary effects. A competing endogenous RNA (ceRNA) regulatory network was constructed from whole transcriptome data. Spatial transcriptomics provided location-specific cloaca region gene expression. Diverse bioinformatics analyses deepened our understanding of ARM's molecular interactions, guiding future research and providing insights into gene regulation in ARM development.

High-throughput nanopore DNA sequencing of large insert fosmid clones directly from bacterial colonies.

Fosmids and cosmids are vectors frequently used in functional metagenomic studies. With a large insert capacity (around 30 kb) they can encode dozens of cloned genes or in some cases, entire biochemical pathways. Fosmids with cloned inserts can be transferred to heterologous hosts and propagated to enable screening for new enzymes and metabolites. After screening, fosmids from clones with an activity of interest must be de novo sequenced, a critical step toward the identification of the gene(s) of interest. In this work, we present a new approach for rapid and high-throughput fosmid sequencing directly from Escherichia coli colonies without liquid culturing or fosmid purification. Our sample preparation involves fosmid amplification with phi29 polymerase and then direct nanopore sequencing using the Oxford Nanopore Technologies system. We also present a bioinformatics pipeline termed "phiXXer" that facilitates both de novo read assembly and vector trimming to generate a linear sequence of the fosmid insert. Finally, we demonstrate the accurate sequencing of 96 fosmids in a single run and validate the method using two fosmid libraries that contain cloned large insert (~30-40 kb) genomic or metagenomic DNA.IMPORTANCELarge-insert clone (fosmids or cosmids) sequencing is challenging and arguably the most limiting step of functional metagenomic screening workflows. Our study establishes a new method for high-throughput nanopore sequencing of fosmid clones directly from lysed Escherichia coli cells. It also describes a companion bioinformatic pipeline that enables de novo assembly of fosmid DNA insert sequences. The devised method widens the potential of functional metagenomic screening by providing a simple, high-throughput approach to fosmid clone sequencing that dramatically speeds the pace of discovery.

P12 Transcriptional and epigenetic changes drive increased cellular plasticity in keloid fibroblasts

Abstract Introduction and aims Keloids are fibroproliferative scars that progressively grow beyond the original wound site. They occur as a result of genetic, epigenetic and environmental abnormalities. Fibroblasts are best characterized for their role in depositing and remodelling the extracellular matrix (ECM) and are believed to have a crucial role in keloid formation. However, the detailed molecular signatures that promote this pathogenic phenotype are still unknown. Methods To investigate the epigenetic and genetic changes in keloid fibroblasts, we performed assay for transposase-accessible chromatin (ATAC)-Seq and RNA-Seq on a patient-matched set of keloid and normal fibroblasts. ATAC-Seq is a high-throughput sequencing method that defines chromatin accessible regions in which the binding of sites of transcription factors that regulate gene expression can be mapped. Identified candidates are validated in keloid fibroblasts via quantitative polymerase chain reaction and their functional role is analysed in various in vitro assays. Results ATAC-Seq analysis revealed more accessibility in coding regions of keloid fibroblasts compared with normal fibroblasts. Pathways enriched in these regions include transcriptional regulation, embryonic development, cell differentiation, calcium-binding and collagen remodelling. Intriguingly, several developmental epigenetic modulators were identified that may alter the transcription and chromatin landscape of keloid fibroblasts to a more plastic state and have the capacity to influence cell differentiation choices, potentially promoting chondrogenic and adipogenic cell features. Currently, we are investigating the ability of keloid fibroblasts to be more readily differentiated into other cell types including induced pluripotent stem cells, and the contribution of those candidates on fibrotic features to the cell are also being explored. Conclusions Our analysis reveals that the chromatin of keloid fibroblasts is more accessible, especially in genomic regions associated with embryonic development and keloid fibroblasts show an increased plasticity in vitro. These findings may support the development of fibroblast-targeted therapies for keloid scars and possibly other connective tissue disorders.

Age Prediction Using DNA Methylation Heterogeneity Metrics.

Dynamic changes in genomic DNA methylation patterns govern the epigenetic developmental programs and accompany the organism's aging. Epigenetic clock (eAge) algorithms utilize DNA methylation to estimate the age and risk factors for diseases as well as analyze the impact of various interventions. High-throughput bisulfite sequencing methods, such as reduced-representation bisulfite sequencing (RRBS) or whole genome bisulfite sequencing (WGBS), provide an opportunity to identify the genomic regions of disordered or heterogeneous DNA methylation, which might be associated with cell-type heterogeneity, DNA methylation erosion, and allele-specific methylation. We systematically evaluated the applicability of five scores assessing the variability of methylation patterns by evaluating within-sample heterogeneity (WSH) to construct human blood epigenetic clock models using RRBS data. The best performance was demonstrated by the model based on a metric designed to assess DNA methylation erosion with an MAE of 3.686 years. We also trained a prediction model that uses the average methylation level over genomic regions. Although this region-based model was relatively more efficient than the WSH-based model, the latter required the analysis of just a few short genomic regions and, therefore, could be a useful tool to design a reduced epigenetic clock that is analyzed by targeted next-generation sequencing.

Dynamic Changes of Environment and Gut Microbial Community of Litopenaeus vannamei in Greenhouse Farming and Potential Mechanism of Gut Microbial Community Construction

The aim of this study was to investigate the dynamic changes in the microbial communities of both the environment and gut of Litopenaeus vannamei, as well as to elucidate the mechanisms underlying microbial community assembly in greenhouse farming. 16S rDNA high-throughput sequencing and bioinformatics methods were used to carry out the research on the community structure of the microorganisms under greenhouse culture conditions in water, sediment, and gut microorganisms; correlations pertaining to environmental factors; the feasibility of using Source Tracker; and the mechanisms of community construction. The results show that the dominant microorganisms in water, sediment, and gut farming in a greenhouse environment varied and were subject to dynamic change. A variety of beneficial microbiota such as Bacillus were found in the gut, whereas a variety of microorganisms such as Marivita and Pseudomonas, which function as nitrogen and phosphorus removers, were present in water. Source Tracker and environmental correlation analyses showed that changes in the gut were associated with eutrophication indicators (total nitrogen, total phosphorus, ammonia nitrogen) and changes in environmental microorganisms (in water and sediment). The results of the community-building mechanism analysis show that stochastic processes determine the community-building directions of environmental and gut microorganisms. These findings will help us to understand the microbiota characteristics of shrimp ponds under greenhouse farming conditions, and the complex interactions between the shrimp gut and the environmental microbiota and environmental variables, as well as revealing the changing rules of the gut microbiota.

The Impact of Artificial Restoration of Alpine Grasslands in the Qilian Mountains on Vegetation, Soil Bacteria, and Soil Fungal Community Diversity.

To understand how the soil microbial community structure responds to vegetation restoration in alpine mining areas, this study specifically examines the grassland ecosystem in the Qianmalong mining area of the Qilian Mountains after five years of artificial restoration. High-throughput sequencing methods were employed to analyze soil bacteria and fungi microbial characteristics in diverse grassland communities. Combined with modifications in vegetation diversity as well as soil physicochemical properties, the impact of vegetation restoration on soil microbiome diversity in this alpine mining area was investigated. The findings indicated that the dominant plants were Cyperus rotundus, Carex spp., and Elymus nutans. As the extent of the grassland's restoration increased, the number of plant species, importance values, and plant community diversity showed an increasing trend. The plant functional groups were mainly dominated by Cyperaceae, followed by Poaceae. Plant height, density, plant cover, frequency, and aboveground biomass showed an increasing trend, and soil water content (SWC) increased. While soil pH and soil electrical conductivity (EC) exhibited a declining trend, available phosphorus (AP), total phosphorus (TP), total nitrogen (TN), nitrate nitrogen (NO3-N), soil organic carbon (SOC), and soil water content (SWC) showed an increasing trend. The dominant bacterial communities were Actinobacteriota, Proteobacteria, Acidobacteriota, Chloroflexi, Firmicutes, and Gemmatimonadota, while the dominant fungal communities were Ascomycota, Mortierellomycota, Basidiomycota, unclassified_k_Fungi, and Glomeromycota. Significant differences were detected within soil microbial community composition among different degrees of restoration grasslands, with bacteria generally dominating over fungi. SWC, TP, and TN were found to be the main soil physicochemical factors affecting the distribution of soil bacterial communities' structure; however, SOC, TN, and NO3-N were the primary factors influencing the soil distribution of fungal communities. The results of this study indicate that different degrees of vegetation restoration in alpine mining areas can significantly affect soil bacterial and fungal communities, and the degree of restoration has varying effects on the soil bacteria and fungi community structure in alpine mining areas.

Temporal Dynamics of Fungal Communities in Alkali-Treated Round Bamboo Deterioration under Natural Weathering.

Microbes naturally inhabit bamboo-based materials in outdoor environments, sequentially contributing to their deterioration. Fungi play a significant role in deterioration, especially in environments with abundant water and favorable temperatures. Alkali treatment is often employed in the pretreatment of round bamboo to change its natural elastic and aesthetic behaviors. However, little research has investigated the structure and dynamics of fungal communities on alkali-treated round bamboo during natural deterioration. In this work, high-throughput sequencing and multiple characterization methods were used to disclose the fungal community succession and characteristic alterations of alkali-treated round bamboo in both roofed and unroofed habitats throughout a 13-week deterioration period. In total, 192 fungal amplicon sequence variants (ASVs) from six phyla were identified. The fungal community richness of roofed bamboo samples declined, whereas that of unroofed bamboo samples increased during deterioration. The phyla Ascomycota and Basidiomycota exhibited dominance during the entire deterioration process in two distinct environments, and the relative abundance of them combined was more than 99%. A distinct shift in fungal communities from Basidiomycota dominant in the early stage to Ascomycota dominant in the late stage was observed, which may be attributed to the increase of moisture and temperature during succession and the effect of alkali treatment. Among all environmental factors, temperature contributed most to the variation in the fungal community. The surface of round bamboo underwent continuous destruction from fungi and environmental factors. The total amount of cell wall components in bamboo epidermis in both roofed and unroofed conditions presented a descending trend. The content of hemicellulose declined sharply by 8.3% and 11.1% under roofed and unroofed environments after 9 weeks of deterioration. In addition, the contact angle was reduced throughout the deterioration process in both roofed and unroofed samples, which might be attributed to wax layer removal and lignin degradation. This study provides theoretical support for the protection of round bamboo under natural weathering.

Comparative Analysis of Gut Bacterial Community Composition in Two Tropical Economic Sea Cucumbers under Different Seasons of Artificial Environment.

With the continuous rise of the sea cucumber aquaculture industry in China, the tropical sea cucumber aquaculture industry is also improving. However, research on the gut microorganisms of tropical sea cucumbers in captivity is scarce. In this study, high-throughput sequencing methods were used to analyze the gut microbial composition of Stichopus monotuberculatus and Holothuria scabra in the dry season and wet season of artificial environments. The results showed that 66 phyla were obtained in all samples, of which 59 phyla were obtained in the dry season, and 45 phyla were obtained in the wet season. The Tax4Fun analysis showed that certain gut bacterial communities affect the daily metabolism of two sea cucumber species and are involved in maintaining gut microecological balance in the gut of two sea cucumber species. In addition, compared with differences between species, PCoA and UPGMA clustering analysis showed the gut prokaryotes of the same sea cucumber species varied more in different seasons, indicating that the influence of environment was higher than the feeding choices of sea cucumbers under relatively closed conditions. These results revealed the gut bacterial community composition of S. monotuberculatus and H. scabra and the differences in gut bacterial structure between two sea cucumber species in different seasons were compared, which would provide the foundation for tropical sea cucumber aquaculture in the future.

Gut microbiome is associated with personality traits of free-ranging Tibetan macaques (Macaca thibetana).

Recent studies have emphasized that there is a strong link between the gut microbiome and the brain that affects social behavior and personality in animals. However, the interface between personality and the gut microbiome in wild primates remains poorly understood. Here, we used high-throughput sequencing and ethological methods in primate behavioral ecology to investigate the relationship between gut microbiome and personality in Tibetan macaques (Macaca thibetana). The behavioral assessment results indicated three personality dimensions including socialization, shyness, and anxiety. There was significant variation in alpha diversity only for shyness, with a significantly lower alpha diversity indices (including Shannon, Chao1, and PD) for bold individuals than for shy individuals. Using regression models to control for possible confounding factors, we found that the relative abundance of three genera, Akkermansia, Dialister, and Asteroleplasma, was significantly and positively correlated with the sociability scores in the macaques. In addition, Oscillospiraceae exhibited a positive correlation with scores for Shy Dimension. Furthermore, we found that the predicted functional genes for propionate and pyruvate, porphyrin and chlorophyll metabolic pathways related to animal behavior, were significant enriched in shyness group. We propose that the gut microbiome may play an important role in the formation of personality of Tibetan macaques.

Therapeutic potential of targeting Nrf2 by panobinostat in pituitary neuroendocrine tumors

We aimed to identify the druggable cell-intrinsic vulnerabilities and target-based drug therapies for PitNETs using the high-throughput drug screening (HTS) and genomic sequencing methods. We examined 9 patient-derived PitNET primary cells in HTS. Based on the screening results, the potential target genes were analyzed with genomic sequencing from a total of 180 PitNETs. We identified and verified one of the most potentially effective drugs, which targeted the Histone deacetylases (HDACs) both in in vitro and in vivo PitNET models. Further RNA sequencing revealed underlying molecular mechanisms following treatment with the representative HDACs inhibitor, Panobinostat. The HTS generated a total of 20,736 single-agent dose responses which were enriched among multiple inhibitors for various oncogenic targets, including HDACs, PI3K, mTOR, and proteasome. Among these drugs, HDAC inhibitors (HDACIs) were, on average, the most potent drug class. Further studies using in vitro, in vivo, and isolated PitNET primary cell models validated HDACIs, especially Panobinostat, as a promising therapeutic agent. Transcriptional surveys revealed substantial alterations to the Nrf2 signaling following Panobinostat treatment. Moreover, Nrf2 is highly expressed in PitNETs. The combination of Panobinostat and Nrf2 inhibitor ML385 had a synergistic effect on PitNET suppression. The current study revealed a class of effective anti-PitNET drugs, HDACIs, based on the HTS and genomic sequencing. One of the representative compounds, Panobinostat, may be a potential drug for PitNET treatment via Nrf2-mediated redox modulation. Combination of Panobinostat and ML385 further enhance the effectiveness for PitNET treatment.

Soil microeukaryotic communities and phosphorus-cycling microorganisms respond to chloropicrin fumigation and azoxystrobin application

Fumigants and fungicides are effective at controlling soil-borne pathogens but might also adversely affect soil beneficial microbes, such as soil phosphorus (P) solubilizing microbes, further altering nutrient cycling processes. Therefore, this study investigated the effects of the fumigant chloropicrin (CP) and the fungicide azoxystrobin (AZO) on soil microeukaryotes and P-cycling related soil bacteria through a greenhouse experiment. Soil microeukaryotic communities and bacterial communities containing two phosphomonoesterase encoding genes (phoC and phoD) were analysed using high-throughput sequencing methods. Results showed that, when applied at the field recommended application dosage, the fungicide AZO had no significant influence on the community structure of soil microeukaryotes and phoD-containing bacteria. However, in CP-fumigated soils, the soil microeukaryotic community composition changed from fungi-dominated to protist-dominated. CP fumigation significantly decreased the total phoC/phoD gene copy number but increased the relative abundance of some phoC/phoD-containing bacteria (such as Sinorhizobium and Streptomyces), which are significantly positively correlated to available P compositions in soil. The structural equation model (SEM) confirmed that CP fumigation could affect soil available P content directly by altering phoC-/phoD-containing bacteria, or indirectly by affecting phoC/phoD gene abundance and acid/alkaline phosphatases activity in soil. The inconsistent changes in phoC/phoD-containing bacteria, phoC/phoD gene number, and the phosphomonoesterase activities indicated that enzyme secretion may not be the only way for P solubilizing soil microorganisms to regulate P availability after soil fumigation. The outcome of this study can provide theoretical support for the design of soil beneficial microorganism recovery strategies and the regulation of phosphate fertilizer after soil fumigation.

Chemical manipulation of m1A mediates its detection in human tRNA.

N 1-methyl adenosine (m1A) is a widespread RNA modification present in tRNA, rRNA, and mRNA. m1A modification sites in tRNAs are evolutionarily conserved and its formation on tRNA is catalyzed by methyltransferase TRMT61A and TRMT6 complex. m1A promotes translation initiation and elongation. Due to its positive charge under physiological conditions, m1A can notably modulate RNA structure. It also blocks Watson-Crick-Franklin base-pairing and causes mutation and truncation during reverse transcription. Several misincorporation-based high-throughput sequencing methods have been developed to sequence m1A. In this study, we introduce a reduction-based m1A sequencing (red-m1A-seq). We report that NaBH4 reduction of m1A can improve the mutation and readthrough rates using commercially available RT enzymes to give a better positive signature, while alkaline-catalyzed Dimroth rearrangement can efficiently convert m1A to m6A to provide good controls, allowing the detection of m1A with higher sensitivity and accuracy. We applied red-m1A-seq to sequence human small RNA, and we not only detected all the previously reported tRNA m1A sites, but also new m1A sites in mt-tRNAAsn-GTT and 5.8S rRNA.

Responses of Attached Bacterial Communities to Blooms of the Swimming Shelled Pteropod Creseis acicula in Daya Bay, Southern China.

The shelled pteropod Creseis acicula is a marine pelagic shellfish widely distributed from temperate to tropical seas around the world. From June to July 2020, a C. acicula bloom first happened in the Daya Bay, southern China, and its density reached the highest value (5600 ind. m-3) ever recorded around the world. However, few studies have investigated the responses of bacterial communities to the C. acicula bloom. In the present study, we examined the community profiles of three communities of bacteria including the free-living and particle-attached bacteria in the blooming and reference waters, and bacteria attached to the whole body and shell of C. acicula using a high-throughput sequencing method. The results indicated that the C. acicula bloom had a greater impact on particle-attached bacteria than free-living bacteria. Among the bloom-sensitive particle-attached bacteria, the predominant bacterial phyla were Pseudomonadota, Bacteroidota, and Verrucomicrobiota in the blooming areas, whereas, they were Actinomycetota and Planctomycetota in the reference areas. Specifically, fecal bacteria Haloferula and Halioglobus sp. were significantly enriched in the blooming waters and accumulated on C. acicula shells. Conversely, the significantly lower relative abundance of Nocardioides sp. in the blooming area and accumulated on the whole body of C. acicula indicated their attachment to particles consumed by C. acicula. Overall, our results suggested that the C. acicula bloom influenced marine bacteria, particularly particle-attached bacteria by increasing (e.g. providing shells and feces) or decreasing (e.g. filter-feeding the suspended particles) the abundance of available substances.

Correlated Allele Frequency Changes Reveal Clonal Structure and Selection in Temporal Genetic Data.

In evolving populations where the rate of beneficial mutations is large, subpopulations of individuals with competing beneficial mutations can be maintained over long times. Evolution with this kind of clonal structure is commonly observed in a wide range of microbial and viral populations. However, it can be difficult to completely resolve clonal dynamics in data. This is due to limited read lengths in high-throughput sequencing methods, which are often insufficient to directly measure linkage disequilibrium or determine clonal structure. Here, we develop a method to infer clonal structure using correlated allele frequency changes in time-series sequence data. Simulations show that our method recovers true, underlying clonal structures when they are known and accurately estimate linkage disequilibrium. This information can then be combined with other inference methods to improve estimates of the fitness effects of individual mutations. Applications to data suggest novel clonal structures in an E. coli long-term evolution experiment, and yield improved predictions of the effects of mutations on bacterial fitness and antibiotic resistance. Moreover, our method is computationally efficient, requiring orders of magnitude less run time for large data sets than existing methods. Overall, our method provides a powerful tool to infer clonal structures from data sets where only allele frequencies are available, which can also improve downstream analyses.

Effects of the epiphytic patterns on endophytes and metabolites of Dendrobium nobile Lindl.

Dendrobium is an epiphytic herb plant with neuroprotective, gastroprotective, anti-inflammatory, and immunomodulatory effects. It is often found attached to tree trunks or rocks. With the development of the dendrobium industry, numerous epiphytic patterns exist, such as crushed stone, stump, and sawdust. The study of metabolites and endophytes of D. nobile under different epiphytic patterns, which revealed the effects of epiphytic patterns on D. nobile from the perspectives of metabolomics and microbiology, is of great significance for the healthy development of D. nobile. In the study, the D. nobile under five epiphytic patterns grown in the same environment were selected. The metabolites were investigated by widely targeted metabolomics, and the endophytes were sequenced using high-throughput sequencing methods. Then, a correlation analysis between the different metabolites and endophytes was performed. A total of 1,032 metabolites were annotated in D. nobile. There are more flavonoids and phenolic acids accumulated on the epiphytic pattern of Danxia stone, whereas the accumulation of lipids on the other epiphytic patterns and 16 differential metabolites was screened out. The endophyte composition of D. nobile was dominated by Proteobacteria, Actinomycetes, unidentified bacteria, Firmicutes, and Cyanobacteria. For endophytic fungi, Basidiomycota and Ascomycota were the dominant phyla of D. nobile. The relative abundance of Spirosoma, Nocardioides, and Arrhenia in the Danxia stone was significantly higher than that of other epiphytic patterns. According to correlation analysis, we found a significant correlation between differential metabolites and Spirosoma, Nocardioides, and Arrheni. This study confirmed that Dendrobium quality was affected by its epiphytic patterns and revealed its possible causes from a microbiological point of view.

Mechanism of improving anaerobic fermentation performance of kitchen waste pretreated by ionizing irradiation-part 1: rice.

Ionizing irradiation, as a new pretreatment method for the anaerobic fermentation of organic pollutants, is featured with fast reaction speed, good treatment effect, no need to add any chemical reagents, and no secondary pollution. This study explores the mechanism of improving anaerobic fermentation performance of rice samples pretreated by cobalt-60 gamma irradiation through the influence on fermentation substrate, acidogenic phase and methanogenic phase. The results reveal that the soluble chemical oxygen demand of the irradiated rice sample at an absorbed dose of 9.6 kGy increases by 12.4 times due to the dissolution of small molecules of fat-soluble organic matter. The yield of biogas in the acidogenic phase increases by 22.2% with a slight increase in hydrogen gas content. The yield of biogas and methane gas content in the methanogenic phase increases by 27.3% and 15%, respectively. Microbial genome analysis, performed with MiSeq high-throughput sequencing and metagenomic methods, suggests the microbial abundance and metabolic functions in the anaerobic fermentation process change significantly as a result of the pretreatment by gamma irradiation.

Juveniles, young adults, and infants with hepatitis B virus infection: A genomic study.

Integration of hepatitis B virus (HBV) DNA into the human genome is recognized as an oncogenic factor and a barrier to hepatitis B cure. In the study, biopsy liver tissues were collected from adolescents and young adults with acute HBV infection younger than or equal to 35 years of age and from HBV-infected infant patients younger than or equal to 6 months of age. A high-throughput sequencing method was used to detect HBV DNA integration. Totally, 12 adolescents, young adults, and 6 infants were included. Among the 12 patients with acute HBV infection, immunohistochemical staining of intrahepatic hepatitis B surface antigen for all displayed negative results, and no HBV DNA integrants in the hepatocyte DNA were confirmed. All infant patients had elevated levels of alanine aminotransferase and high levels of serum HBV DNA. Numerous gene sites of hepatocyte DNA were integrated by HBV DNA for each infant patient, ranging from 120 to 430 integration sites. The fragile histidine triad gene was the high-frequency integrated site in the intragenic region for infant patients. In conclusion, hepatocyte DNA is integrated by HBV DNA in babies with active hepatitis B but seems seldom affected among adolescents and young adults with acute HBV infection. Infantile hepatitis B should be taken seriously considering abundant HBV DNA integration events.

Interpretable Multi-Scale Deep Learning for RNA Methylation Analysis across Multiple Species.

RNA modification plays a crucial role in cellular regulation. However, traditional high-throughput sequencing methods for elucidating their functional mechanisms are time-consuming and labor-intensive, despite extensive research. Moreover, existing methods often limit their focus to specific species, neglecting the simultaneous exploration of RNA modifications across diverse species. Therefore, a versatile computational approach is necessary for interpretable analysis of RNA modifications across species. A multi-scale biological language-based deep learning model is proposed for interpretable, sequential-level prediction of diverse RNA modifications. Benchmark comparisons across species demonstrate the model's superiority in predicting various RNA methylation types over current state-of-the-art methods. The cross-species validation and attention weight visualization also highlight the model's capability to capture sequential and functional semantics from genomic backgrounds. Our analysis of RNA modifications helps us find the potential existence of "biological grammars" in each modification type, which could be effective for mapping methylation-related sequential patterns and understanding the underlying biological mechanisms of RNA modifications.

AStruct: detection of allele-specific RNA secondary structure in structuromic probing data

BackgroundUncovering functional genetic variants from an allele-specific perspective is of paramount importance in advancing our understanding of gene regulation and genetic diseases. Recently, various allele-specific events, such as allele-specific gene expression, allele-specific methylation, and allele-specific binding, have been explored on a genome-wide scale due to the development of high-throughput sequencing methods. RNA secondary structure, which plays a crucial role in multiple RNA-associated processes like RNA modification, translation and splicing, has emerged as an essential focus of relevant research. However, tools to identify genetic variants associated with allele-specific RNA secondary structures are still lacking.ResultsHere, we develop a computational tool called ‘AStruct’ that enables us to detect allele-specific RNA secondary structure (ASRS) from RT-stop based structuromic probing data. AStruct shows robust performance in both simulated datasets and public icSHAPE datasets. We reveal that single nucleotide polymorphisms (SNPs) with higher AStruct scores are enriched in coding regions and tend to be functional. These SNPs are highly conservative, have the potential to disrupt sites involved in m6A modification or protein binding, and are frequently associated with disease.ConclusionsAStruct is a tool dedicated to invoke allele-specific RNA secondary structure events at heterozygous SNPs in RT-stop based structuromic probing data. It utilizes allelic variants, base pairing and RT-stop information under different cell conditions to detect dynamic and functional ASRS. Compared to sequence-based tools, AStruct considers dynamic cell conditions and outperforms in detecting functional variants. AStruct is implemented in JAVA and is freely accessible at: https://github.com/canceromics/AStruct.

Allergy-associated biomarkers in early life identified by Omics techniques.

The prevalence and severity of allergic diseases have increased over the last 30 years. Understanding the mechanisms responsible for these diseases is a major challenge in current allergology, as it is crucial for the transition towards precision medicine, which encompasses predictive, preventive, and personalized strategies. The urge to identify predictive biomarkers of allergy at early stages of life is crucial, especially in the context of major allergic diseases such as food allergy and atopic dermatitis. Identifying these biomarkers could enhance our understanding of the immature immune responses, improve allergy handling at early ages and pave the way for preventive and therapeutic approaches. This minireview aims to explore the relevance of three biomarker categories (proteome, microbiome, and metabolome) in early life. First, levels of some proteins emerge as potential indicators of mucosal health and metabolic status in certain allergic diseases. Second, bacterial taxonomy provides insight into the composition of the microbiota through high-throughput sequencing methods. Finally, metabolites, representing the end products of bacterial and host metabolic activity, serve as early indicators of changes in microbiota and host metabolism. This information could help to develop an extensive identification of biomarkers in AD and FA and their potential in translational personalized medicine in early life.