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Abstract Background Reactive oxygen species may be involved in epigenetic gene activation or silencing. We aimed to identify CpG sites, at which DNA methylation is related to urinary 8-isoprostane levels (biomarker of lipid peroxidation) and cancer or mortality outcomes. This investigation was based on a German, population-based cohort with linkage to cancer and mortality registry data (2000–2016). Results Blood DNA methylation in promoter regions of 519 genes, known to be involved in pathways from oxidative stress (OS) to cancer, was obtained at the cohort's baseline examination. Inverse associations of DNA methylation at cg25365794 (ALOXE3) and cg08862778 (MTOR) with 8-isoprostane levels were observed in a derivation set (n = 1000) and validated in two independent subsets of the cohort (n = 548 and n = 741). Multivariate regression models were used to evaluate the associations of DNA methylation at the two CpG sites with lung, colorectal, prostate, breast, and overall cancer incidence as well as CVD, cancer, and all-cause mortality. DNA methylation at cg25365794 (ALOXE3) was inversely associated with lung and prostate cancer incidence. DNA methylation at cg08862778 (MTOR) was associated with a 43% lower breast cancer incidence in the top vs. bottom tertile. Conclusion The finding for ALOXE3 may not be causal. As ALOXE3 is mainly expressed in skin tissue, the observed association might reflect the fact that both DNA methylation at the ALOXE3 gene and urinary 8-isoprostane concentrations depend on the level of OS in tissues. Contrarily, the finding for the MTOR gene and breast cancer is biologically plausible because the MTOR protein plays an important role in PI3K/Akt signaling, which is a pathway related to cancer development and cell senescence.

Phenotypic differences between diploid parents and their allotriploid offspring are common in aquaculture breeding. Some allotriploid populations exhibit rapid growth rates and increased body weight, which are significant for supporting fisheries development. Understanding the genetic mechanisms underlying these traits is crucial for implementing diverse breeding strategies to achieve high production in fish farming. Here, we collected the following fish species for our study: red crucian carp (Carassius auratus red var., 2nRR), common carp (Cyprinus carpio L., 2nCC), and two allotriploids (3nR2C and 3 nRC2). These allotriploids were obtained through backcrossing an allotetraploid of C. auratus red var. × C. carpio L. (4nR2C2, ♂) with C. auratus red var. and C. carpio L. (♀), respectively. These allotriploids demonstrated faster growth rates compared to their diploid inbred parents, contributing to the Chinese fisheries industry for several decades. We conducted a systematic comparison of mitochondrial DNA (mtDNA) copy numbers in the liver and muscle tissues of 2nRR, 2nCC, 3nR2C, and 3 nRC2 under different seasons. When entering winter (low water temperature: 13 °C), the triploid fish (3nR2C and 3 nRC2) exhibited lower mtDNA copy numbers in the muscle, indicating a reduction in individual activity and energy expenditure to facilitate weight maintenance when food availability is limited. Furthermore, we analysed the expression levels of three nuclear-regulated mitochondrial genes (tfam, tfb1m, and tfb2m) and observed an imbalance of allelic expression in tfam and tfb1m in the two triploid fish. These findings enhance our understanding of the molecular regulatory mechanisms underlying growth trait differences among fish with different ploidy levels.

Abstract Background Obesity is a global public health concern linked to chronic diseases such as cardiovascular disease and type 2 diabetes (T2D). Emerging evidence suggests that epigenetic modifications, particularly DNA methylation, may contribute to obesity. However, the molecular mechanism underlying the longitudinal change of BMI has not been well-explored, especially in East Asian populations. Methods This study performed a longitudinal epigenome-wide association analysis of DNA methylation to uncover novel loci associated with BMI change in 533 individuals across two Chinese cohorts with repeated DNA methylation and BMI measurements over four years. Results We identified three novel CpG sites (cg14671384, cg25540824, and cg10848724) significantly associated with BMI change. Two of the identified CpG sites were located in regions previously associated with body shape and basal metabolic rate. Annotation of the top 20 BMI change-associated CpGs revealed strong connections to obesity and T2D. Notably, these CpGs exhibited active regulatory roles and located in genes with high expression in the liver and digestive tract, suggesting a potential regulatory pathway from genome to phenotypes of energy metabolism and absorption via DNA methylation. Cross-sectional and longitudinal EWAS comparisons indicated different mechanisms between CpGs related to BMI and BMI change. Conclusion This study enhances our understanding of the epigenetic dynamics underlying BMI change and emphasizes the value of longitudinal analyses in deciphering the complex interplay between epigenetics and obesity.

Abstract Background Aldehyde dehydrogenases (ALDHs) are a family of enzymes that catalyze the oxidation of aldehyde molecules into the corresponding carboxylic acid, regulate the balance of aldehydes and protect plants from the poisoning caused by excessive accumulation of aldehydes; however, this gene family has rarely been studied in cotton. Results In the present study, genome-wide identification was performed, and a total of 114 ALDH family members were found in three cotton species, Gossypium hirsutum, Gossypium arboreum and Gossypium raimondii. The ALDH genes were divided into six subgroups by evolutionary analysis. ALDH genes in the same subgroup showed similar gene structures and conserved motifs, but some genes showed significant differences, which may result in functional differences. Chromosomal location analysis and selective pressure analysis revealed that the ALDH gene family had experienced many fragment duplication events. Cis-acting element analysis revealed that this gene family may be involved in the response to various biotic and abiotic stresses. The RT‒qPCR results showed that the expression levels of some members of this gene family were significantly increased under salt stress conditions. Gohir.A11G040800 and Gohir.D06G046200 were subjected to virus-induced gene silencing (VIGS) experiments, and the sensitivity of the silenced plants to salt stress was significantly greater than that of the negative control plants, suggesting that Gohir.A11G040800 and Gohir.D06G046200 may be involved in the response of cotton to salt stress. Conclusions In total, 114 ALDH genes were identified in three Gossypium species by a series of bioinformatics analysis. Gene silencing of the ALDH genes of G. hirsutum revealed that ALDH plays an important role in the response of cotton to salt stress.

Abstract Objective Haploinsufficiency is widely accepted as the pathogenic mechanism of hereditary spastic paraplegias type 4 (SPG4). However, there are some cases that cannot be explained by reduced function of the spastin protein encoded by SPAST. The aim of this study was to identify the causative variant of SPG4 in a large Chinese family and explore its pathological mechanism. Materials and methods A five-generation family with 49 members including nine affected (4 males and 5 females) and 40 unaffected individuals in Mongolian nationality was recruited. Whole exome sequencing was employed to investigate the genetic etiology. Western blotting and immunofluorescence were used to analyze the effects of the mutant proteins in vitro. Results A novel frameshift variant NM_014946.4: c.483_484delinsC (p.Val162Leufs*2) was identified in SPAST from a pedigree with SPG4. The variant segregated with the disease in the family and thus determined as the disease-causing variant. The c.483_484delinsC variant produced two truncated mutants (mutant M1 and M87 isoforms). They accumulated to a higher level and presented increased stability than their wild-type counterparts and may lost the microtubule severing activity. Conclusion SPAST mutations leading to premature stop codons do not always act through haploinsufficiency. The potential toxicity to the corticospinal tract caused by the intracellular accumulation of truncated spastin should be considered as the pathological mechanism of SPG4.

Abstract Arabs represent 5% of the world population and have a high prevalence of common disease, yet remain greatly underrepresented in genome-wide association studies, where only 1 in 600 individuals are Arab. We highlight the persistent and unaddressed underrepresentation of Arabs in genomic databases and discuss its impact on public health genomics and missed opportunities for biological discovery.

Abstract DNA barcodes enable Oxford Nanopore sequencing to sequence multiple barcoded DNA samples on a single flow cell. DNA sequences with the same barcode need to be grouped together through demultiplexing. As the number of samples increases, accurate demultiplexing becomes difficult. We introduce HycDemux, which incorporates a GPU-parallelized hybrid clustering algorithm that uses nanopore signals and DNA sequences for accurate data clustering, alongside a voting-based module to finalize the demultiplexing results. Comprehensive experiments demonstrate that our approach outperforms unsupervised tools in short sequence fragment clustering and performs more robustly than current state-of-the-art demultiplexing tools for complex multi-sample sequencing data.

Background. The association between acute myeloid leukemia (AML) and macrophage remains to be deeply explored. Methods. Gene expression profiles and clinical variable characteristics of AML patients were collected from TCGA, GEO, and TARGET databases. Consensus clustering was employed to construct the macrophage-related clusters. The macrophage-related index (MRI) was constructed using the LASSO and multivariate Cox analysis. The GSE71014 and TARGET datasets were utilized as external validation sets. Single-cell sequencing data for AML (GSE116256) was adopted to analyze modeled gene expression levels in cells. Results. Two macrophage-related clusters with different prognostic and immune infiltration characteristics were constructed in AML. Cluster B had a poorer prognosis, more cancer-promoting pathway enrichment, and an immunosuppressive microenvironment. Relied on the MRI, patients of different groups showed different levels of immune infiltration, different mutations, and prognoses. LGALS1 and BCL2A1 may play roles in promoting cancer in AML, while ELANE may have a significant effect on suppressing cancer. Conclusion. Macrophage-related genes (MRGs) had significant impacts on the occurrence and progression of AML. MRI may better evaluate the prognosis and immune features of AML patients.

Abstract Background Genome-wide association studies have identified numerous human host genetic risk variants that play a substantial role in the host immune response to SARS-CoV-2. Although these genetic risk variants significantly increase the severity of COVID-19, their influence on body systems is poorly understood. Therefore, we aim to interpret the biological mechanisms and pathways associated with the genetic risk factors and immune responses in severe COVID-19. We perform a deep analysis of previously identified risk variants and infer the hidden interactions between their molecular networks through disease mapping and the similarity of the molecular functions between constructed networks. Results We designed a four-stage computational workflow for systematic genetic analysis of the risk variants. We integrated the molecular profiles of the risk factors with associated diseases, then constructed protein–protein interaction networks. We identified 24 protein–protein interaction networks with 939 interactions derived from 109 filtered risk variants in 60 risk genes and 56 proteins. The majority of molecular functions, interactions and pathways are involved in immune responses; several interactions and pathways are related to the metabolic and cardiovascular systems, which could lead to multi-organ complications and dysfunction. Conclusions This study highlights the importance of analyzing molecular interactions and pathways to understand the heterogeneous susceptibility of the host immune response to SARS-CoV-2. We propose new insights into pathogenicity analysis of infections by including genetic risk information as essential factors to predict future complications during and after infection. This approach may assist more precise clinical decisions and accurate treatment plans to reduce COVID-19 complications.

Introduction: Clear cell renal cell carcinoma (ccRCC) is associated with unfavorable clinical outcomes. To identify viable therapeutic targets, a comprehensive understanding of intratumoral heterogeneity is crucial. In this study, we conducted bioinformatic analysis to scrutinize single-cell RNA sequencing data of ccRCC tumor and para-tumor samples, aiming to elucidate the intratumoral heterogeneity in the ccRCC tumor microenvironment (TME).Methods: A total of 51,780 single cells from seven ccRCC tumors and five para-tumor samples were identified and grouped into 11 cell lineages using bioinformatic analysis. These lineages included tumor cells, myeloid cells, T-cells, fibroblasts, and endothelial cells, indicating a high degree of heterogeneity in the TME. Copy number variation (CNV) analysis was performed to compare CNV frequencies between tumor and normal cells. The myeloid cell population was further re-clustered into three major subgroups: monocytes, macrophages, and dendritic cells. Differential expression analysis, gene ontology, and gene set enrichment analysis were employed to assess inter-cluster and intra-cluster functional heterogeneity within the ccRCC TME.Results: Our findings revealed that immune cells in the TME predominantly adopted an inflammatory suppression state, promoting tumor cell growth and immune evasion. Additionally, tumor cells exhibited higher CNV frequencies compared to normal cells. The myeloid cell subgroups demonstrated distinct functional properties, with monocytes, macrophages, and dendritic cells displaying diverse roles in the TME. Certain immune cells exhibited pro-tumor and immunosuppressive effects, while others demonstrated antitumor and immunostimulatory properties.Conclusion: This study contributes to the understanding of intratumoral heterogeneity in the ccRCC TME and provides potential therapeutic targets for ccRCC treatment. The findings emphasize the importance of considering the diverse functional roles of immune cells in the TME for effective therapeutic interventions.

MicroRNAs (miRNAs) play a crucial role in various biological processes and human diseases, and are considered as therapeutic targets for small molecules (SMs). Due to the time-consuming and expensive biological experiments required to validate SM-miRNA associations, there is an urgent need to develop new computational models to predict novel SM-miRNA associations. The rapid development of end-to-end deep learning models and the introduction of ensemble learning ideas provide us with new solutions. Based on the idea of ensemble learning, we integrate graph neural networks (GNNs) and convolutional neural networks (CNNs) to propose a miRNA and small molecule association prediction model (GCNNMMA). Firstly, we use GNNs to effectively learn the molecular structure graph data of small molecule drugs, while using CNNs to learn the sequence data of miRNAs. Secondly, since the black-box effect of deep learning models makes them difficult to analyze and interpret, we introduce attention mechanisms to address this issue. Finally, the neural attention mechanism allows the CNNs model to learn the sequence data of miRNAs to determine the weight of sub-sequences in miRNAs, and then predict the association between miRNAs and small molecule drugs. To evaluate the effectiveness of GCNNMMA, we implement two different cross-validation (CV) methods based on two different datasets. Experimental results show that the cross-validation results of GCNNMMA on both datasets are better than those of other comparison models. In a case study, Fluorouracil was found to be associated with five different miRNAs in the top 10 predicted associations, and published experimental literature confirmed that Fluorouracil is a metabolic inhibitor used to treat liver cancer, breast cancer, and other tumors. Therefore, GCNNMMA is an effective tool for mining the relationship between small molecule drugs and miRNAs relevant to diseases.

Late-stage drug development failures are usually a consequence of ineffective targets. Thus, proper target identification is needed, which may be possible using computational approaches. The reason being, effective targets have disease-relevant biological functions, and omics data unveil the proteins involved in these functions. Also, properties that favor the existence of binding between drug and target are deducible from the protein’s amino acid sequence. In this work, we developed OncoRTT, a deep learning (DL)-based method for predicting novel therapeutic targets. OncoRTT is designed to reduce suboptimal target selection by identifying novel targets based on features of known effective targets using DL approaches. First, we created the “OncologyTT” datasets, which include genes/proteins associated with ten prevalent cancer types. Then, we generated three sets of features for all genes: omics features, the proteins’ amino-acid sequence BERT embeddings, and the integrated features to train and test the DL classifiers separately. The models achieved high prediction performances in terms of area under the curve (AUC), i.e., AUC greater than 0.88 for all cancer types, with a maximum of 0.95 for leukemia. Also, OncoRTT outperformed the state-of-the-art method using their data in five out of seven cancer types commonly assessed by both methods. Furthermore, OncoRTT predicts novel therapeutic targets using new test data related to the seven cancer types. We further corroborated these results with other validation evidence using the Open Targets Platform and a case study focused on the top-10 predicted therapeutic targets for lung cancer.

Abstract Background Heterosis of growth traits in allotriploid fish has benefited the production of aquaculture for many years, yet its genetic and molecular basis has remained obscure. Now, an allotriploid complex, including two triploids and their diploid inbred parents, has provided an excellent model for investigating the potential regulatory mechanisms of heterosis. Results Here, we performed a series of analyses on DNA methylation modification and miRNA expression in combination with gene expression in the allotriploid complex. We first established a model of cis- and trans-regulation related to DNA methylation and miRNA in allotriploids. Then, comparative analyses showed that DNA methylation contributed to the emergence of a dosage compensation effect, which reduced gene expression levels in the triploid to the diploid state. We detected 31 genes regulated by DNA methylation in the subgenomes of the allotriploids. Finally, the patterns of coevolution between small RNAs and their homoeologous targets were classified and used to predict the regulation of miRNA expression in the allotriploids. Conclusions Our results uncovered the regulatory network between DNA methylation and miRNAs in allotriploids, which not only helps us understand the regulatory mechanisms of heterosis of growth traits but also benefits the study and application of epigenetics in aquaculture.

Interploid cross is regularly observed in plants and often results in phenotypic changes, including reduced fertility and heterosis. Yet few triploids have been observed in animals due to the rare coexistence of diploid and allotetraploid populations in species. However, heterosis in growth traits and innate immunity have been detected in the allotriploids obtained from interploid crossing of the male allotetraploids of red crucian carp and common carp (4nAT) with the females of their inbred parents. Here, we obtained two new types of allotriploids (3nR2C and 3nRC2) by the interploid crossing of female 4nAT with the inbred parents (red crucian carp and common carp, respectively). The embryos of the two allotriploids developed normally through the zygote, cleavage, blastula, gastrula, segmentation and hatching stages, and high fertilization rates (3nR2C: 91.31%, 3nRC2: 84.09%) and hatching rates (3nR2C: 72.96%, 3nRC2: 71.15%) were observed. The measured DNA content and chromosome numbers suggested that both 3nR2C and 3nRC2 were allotriploids with 150 chromosomes. Intermediate characteristics of some morphological traits, such as the body length to body height ratio (BL/BH), were observed in 3nR2C and 3nRC2. In contrast to the stage II oocytes in the ovaries of the inbred parents, cystic structures formed by small, underdeveloped oogonia were observed in the two allotriploids. In contrast to the observation of mature spermatids in the testes of the inbred parents, spermatids with irregular shapes that began to degrade and disintegrate were observed in the two allotriploids. These results revealed abnormal gonad development in the allotriploids. Taken together, our results indicate that the two new allotriploids will be significant in aquaculture.

Abstract Abscisic acid (ABA) is a phytohormone that plays important roles in the regulation of plant growth, seed germination, and stress responses. The pyrabactin resistance 1-like (PYR/PYL) protein, an ABA receptor, was involved in the initial step in ABA signal transduction. However, the evolutionary history and characteristics of PYL genes expression remain unclear in Chinese white pear (Pyrus bretschneideri) or other Rosaceae species. In this study, 67 PYL genes were identified in eight Rosaceae species, and have been classified into three subgroups based on specific motifs and phylogenetic analysis. Intriguingly, we observed that whole-genome duplication (WGD) and dispersed duplication (DSD) have a major contribution to PYL family expansion. Purifying selection was the major force in PYL genes evolution. Expression analysis finds that PYL genes may function in multiple pear tissues. qRT-PCR validation of 11 PbrPYL genes indicates their roles in seed germination and abiotic stress responses. Our study provides a basis for further elucidation of the function of PYL genes and analysis of their expansion, evolution and expression patterns, which helps to understand the molecular mechanism of pear response to seed germination and seedling abiotic stress.

Background: Salinity stress is a major adverse environmental factor that can limit crop yield and restrict normal land use. The selection of salt-tolerant strains and elucidation of the underlying mechanisms by plant breeding scientists are urgently needed to increase agricultural production in arid and semi-arid regions.Results: In this study, we selected the salt-tolerant wheat (Triticum aestivum) strain ST9644 as a model to study differences in expression patterns between salt-tolerant and salt-sensitive strains. High-throughput RNA sequencing resulted in more than 359.10 Gb of clean data from 54 samples, with an average of 6.65 Gb per sample. Compared to the IWGSC reference annotation, we identified 50,096 new genes, 32,923 of which have functional annotations. Comparisons of abundances between salt-tolerant and salt-sensitive strains revealed 3,755, 5,504, and 4,344 genes that were differentially expressed at 0, 6, and 24 h, respectively, in root tissue under salt stress. KEGG pathway analysis of these genes showed that they were enriched for phenylpropanoid biosynthesis (ko00940), cysteine and methionine metabolism (ko00270), and glutathione metabolism (ko00480). We also applied weighted gene co-expression network analysis (WGCNA) analysis to determine the time course of root tissue response to salt stress and found that the acute response lasts >6 h and ends before 12 h. We also identified key alternative splicing factors showing different splicing patterns in salt-sensitive and salt-tolerant strains; however, only few of them were differentially expressed in the two groups.Conclusion: Our results offer a better understanding of wheat salt tolerance and improve wheat breeding.

Background. The problem of prognostic stratification in acute myeloid leukemia (AML) patients still has limitations. Methods. The expression profile data and clinical features of AML patients were obtained from multiple publicly available sources, including GSE71014, TCGA-LAML, and TARGET-AML. Single-cell analysis was performed using the TISCH project. All the analysis was conducted in the R software. Results. In our study, three public AML cohorts, GSE71014, TARGET-AML, and TCGA-AML, were selected. Then, we identified the prognosis-related molecules through bioinformatic analysis. Finally, the DUSP7 was noticed as a risk factor for AML patients, which has not been reported previously. Biological enrichment analysis and immune-related analysis were performed to illustrate the role of DUSP7 in AML. Single-cell analysis indicated that the DUSP7 was widely distributed in various cells, especially in monocyte/macrophages and malignant. Following this, a prognosis model based on DUSP7-derived genes was constructed, which showed a good prognosis prediction ability in all cohorts. Conclusions. Our results preliminarily reveal the role and potential mechanism of DUSP7 in AML, providing direction for future research.

Genetic interactions between nuclear and mitochondrial genomes always play an important role in growth and development. However, it is not feasible to directly perform these studies in some animals. The reciprocal hybrid fishes obtained from intergeneric hybridization are an effective research model for the same nuclear genome and different mitochondrial genomes. The transcriptomes of embryonic development (Blastula Period, Gastrula Period, Segmentation Period and Hatching Period) were obtained from the two reciprocal hybrids of Carassius auratus red var. (RCC) ​× ​Cyprinus carpio L. (CC) and their parents. Most of the reads (average ​> ​99.90%) in the transcriptome of F1-RC (C. auratus red var. (♀) ​× ​C. carpio L. (♂)) and F1-CR (C. carpio L. (♀) ​× ​C. auratus red var. (♂)) were optimally mapped to the maternal mitochondrial genome (MMG), respectively. Then, the other reads with optimally mapped to paternal mitochondrial genome exhibited that the partial coverages and low-level (

Abstract Background Molecular autopsy refers to DNA-based identification of the cause of death. Despite recent attempts to broaden its scope, the term remains typically reserved to sudden unexplained death in young adults. In this study, we aim to showcase the utility of molecular autopsy in defining lethal variants in humans. Methods We describe our experience with a cohort of 481 cases in whom the cause of premature death was investigated using DNA from the index or relatives (molecular autopsy by proxy). Molecular autopsy tool was typically exome sequencing although some were investigated using targeted approaches in the earlier stages of the study; these include positional mapping, targeted gene sequencing, chromosomal microarray, and gene panels. Results The study includes 449 cases from consanguineous families and 141 lacked family history (simplex). The age range was embryos to 18 years. A likely causal variant (pathogenic/likely pathogenic) was identified in 63.8% (307/481), a much higher yield compared to the general diagnostic yield (43%) from the same population. The predominance of recessive lethal alleles allowed us to implement molecular autopsy by proxy in 55 couples, and the yield was similarly high (63.6%). We also note the occurrence of biallelic lethal forms of typically non-lethal dominant disorders, sometimes representing a novel bona fide biallelic recessive disease trait. Forty-six disease genes with no OMIM phenotype were identified in the course of this study. The presented data support the candidacy of two other previously reported novel disease genes (FAAH2 and MSN). The focus on lethal phenotypes revealed many examples of interesting phenotypic expansion as well as remarkable variability in clinical presentation. Furthermore, important insights into population genetics and variant interpretation are highlighted based on the results. Conclusions Molecular autopsy, broadly defined, proved to be a helpful clinical approach that provides unique insights into lethal variants and the clinical annotation of the human genome.

Fisheries is a social production sector that captures and farms fish and other aquatic animals and plants for aquatic products. In a broad sense, fisheries also include upstream departments (e.g., manufacturing, maintenance and supply of fishing gear, fishing boats, fishery machinery, fishery instruments and other means of production), downstream departments (e.g., storage, processing, comprehensive utilization, transportation and sales of aquatic products), and auxiliary departments (e.g., the construction of fishing ports). As an important constituent part of the national economy in China, fisheries not only provide a large amount of food sources for humans but also provide many industrial raw materials for national construction. In this paper, the development of fisheries in China is reviewed, including the development history of fisheries, the current situations of the aquatic seed industry, aquaculture industry, capture industry, aquatic product processing industry, aquatic animal nutrition and feed industry, and leisure fishery; additionally, the contribution of Chinese fisheries in the global fisheries is assessed, as are the current fisheries development problems and development strategies in China. This paper has important guiding significance for the development of fisheries in China.

Background: Bladder cancer (BLCA) is a malignant tumor with a complex molecular mechanism and high recurrence rate in the urinary system. Studies have shown that pyroptosis regulates tumor cell proliferation and metastasis and affects the prognosis of cancer patients. However, the role of pyroptosis-related (PR) genes or long non-coding RNAs (lncRNAs) in BLCA development is not fully understood.Methods: We comprehensively analyzed the molecular biological characteristics of PR genes in BLCA, including copy number variation, mutations, expression and prognostic value based on TCGA database. We then identified PR lncRNAs with prognostic value based on the expression of PR genes and performed a consistent clustering analysis of 407 BLCA patients according to the expression of prognosis-related PR lncRNAs and identified two clusters. The least absolute shrinkage and selection operator (LASSO) regression was used to establish a PR lncRNA signature and calculate the risk score associated with the prognosis of patients with BLCA. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) were used to evaluate the possible functions of PR lncRNA signature. We also evaluated the relationship between the risk score and tumor immune microenvironment (TIME).Results: A total of 33 PR genes were obtained in our study and 194 prognosis-related PR lncRNAs were identified. We also constructed a signature consisting of eight-PR-lncRNAs and divided patients into high- and low-risk groups. The overall survival rate of patients with a high risk was significantly lower than patients with a low risk. The risk score was significantly correlated with the degree of infiltration of multiple immune cell subtypes and positively correlated with multiple immune checkpoint genes expression in BLCA. Enrichment analyses showed that these lncRNAs are involved in human immune regulatory functions and immune-related pathways.Conclusion: Our study comprehensively studied the molecular biological characteristics of PR genes BLCA, and the eight-PR-lncRNA signature we identified might play a crucial role in tumor immunity and may be able to predict the prognosis of BLCA patients, providing a theoretical basis for an in-depth study of the relationship between the prognosis and TIME.

Abstract Quantifying the genetic heterogeneity of a cell population is essential to understanding of biological systems. We develop a universal method to label individual DNA molecules for single-base-resolution haplotype-resolved quantitative characterization of diverse types of rare variants, with frequency as low as 4 × 10−5, using both short- or long-read sequencing platforms. It provides the first quantitative evidence of persistent nonrandom large structural variants and an increase in single-nucleotide variants at the on-target locus following repair of double-strand breaks induced by CRISPR-Cas9 in human embryonic stem cells.

Abstract Background Maternal effects contribute to adaptive significance for shaping various phenotypes of many traits. Potential implications of maternal effects are the cause of expression diversity, but these effects on mRNA expression and alternative splicing (AS) have not been fully elucidated in hybrid animals. Results Two reciprocal cross hybrids following hybridization of Megalobrama amblycephala (blunt snout bream, BSB) and Culter alburnus (topmouth culter, TC) were used as a model to investigate maternal effects. By comparing the expression of BSB- and TC- homoeologous genes between the two reciprocal cross hybrids, we identified 49–348 differentially expressed BSB-homoeologous genes and 54–354 differentially expressed TC-homoeologous genes. 2402, 2959, and 3418 AS events between the two reciprocal cross hybrids were detected in Illumina data of muscle, liver, and gonad, respectively. Moreover, 21,577 (TC-homoeologs) and 30,007 (BSB-homoeologs) AS events were found in the 20,131 homoeologous gene pairs of TBF3 based on PacBio data, while 30,561 (TC-homoeologs) and 30,305 (BSB-homoeologs) AS events were found in BTF3. These results further improve AS prediction at the homoeolog level. The various AS patterns in bmpr2a belonging to the bone morphogenetic protein family were selected as AS models to investigate the expression diversity and its potential effects to body shape traits. Conclusions The distribution of differentially expressed genes and AS in BSB- and TC-subgenomes exhibited various changes between the two reciprocal cross hybrids, suggesting that maternal effects were the cause of expression diversity. These findings provide a novel insight into mRNA expression changes and AS under maternal effects in lower vertebrates.

Abstract Background At least 50% of patients with suspected Mendelian disorders remain undiagnosed after whole-exome sequencing (WES), and the extent to which non-coding variants that are not captured by WES contribute to this fraction is unclear. Whole transcriptome sequencing is a promising supplement to WES, although empirical data on the contribution of RNA analysis to the diagnosis of Mendelian diseases on a large scale are scarce. Results Here, we describe our experience with transcript-deleterious variants (TDVs) based on a cohort of 5647 families with suspected Mendelian diseases. We first interrogate all families for which the respective Mendelian phenotype could be mapped to a single locus to obtain an unbiased estimate of the contribution of TDVs at 18.9%. We examine the entire cohort and find that TDVs account for 15% of all “solved” cases. We compare the results of RT-PCR to in silico prediction. Definitive results from RT-PCR are obtained from blood-derived RNA for the overwhelming majority of variants (84.1%), and only a small minority (2.6%) fail analysis on all available RNA sources (blood-, skin fibroblast-, and urine renal epithelial cells-derived), which has important implications for the clinical application of RNA-seq. We also show that RNA analysis can establish the diagnosis in 13.5% of 155 patients who had received “negative” clinical WES reports. Finally, our data suggest a role for TDVs in modulating penetrance even in otherwise highly penetrant Mendelian disorders. Conclusions Our results provide much needed empirical data for the impending implementation of diagnostic RNA-seq in conjunction with genome sequencing.

Effective treatment of glioblastoma (GBM) remains an open challenge. Given the critical role of the immune microenvironment in the progression of cancers, we aimed to develop an immune-related gene (IRG) signature for predicting prognosis and improving the current treatment paradigm of GBM. Multi-omics data were collected, and various bioinformatics methods, as well as machine learning algorithms, were employed to construct and validate the IRG-based signature and to explore the characteristics of the immune microenvironment of GBM. A five-gene signature (ARPC1B, FCGR2B, NCF2, PLAUR, and S100A11) was identified based on the expression of IRGs, and an effective prognostic risk model was developed. The IRG-based risk model had superior time-dependent prognostic performance compared to well-studied molecular pathology markers. Besides, we found prominent inflamed features in the microenvironment of the high-risk group, including neutrophil infiltration, immune checkpoint expression, and activation of the adaptive immune response, which may be associated with increased hypoxia, epidermal growth factor receptor (EGFR) wild type, and necrosis. Notably, the IRG-based risk model had the potential to predict the effectiveness of radiotherapy. Together, our study offers insights into the immune microenvironment of GBM and provides useful information for clinical management of this desperate disease.

The present research offers novel understandings of the reproductive biology of Pseudecheneis sulcatus (McClelland, 1842) found in the Yarlung Zangbo Grand Canyon, a biodiversity hotspot. Reproductive characteristics of Pseudecheneis sulcatus, including their maturation age, fertility, spawning season, and maximum body size, constitute important aspects of its life-history traits. We collected a total of 310 specimens from the Yarlung Zangbo River’s Motuo reach between March and November 2016 and found the male-to-female ratio to be 0.73:1, markedly different from the anticipated 1:1. The total length of individuals ranged from 72 to 207 mm, while overall weight ranged from 2.5 to 65.0 g. Their length at first maturity was estimated as 131 mm in males and 132 mm in females. Based on the adult proportion and fluctuation in the monthly gonadosomatic index (GSI) and size distribution of oocytes, spawning was determined to occur from March to June. The absolute fecundity ranged between 247 and 2886 eggs, while the fluctuation in average relative fertility ranged between 16.8 and 77.1 eggs/g of fish. The fecundity of P. sulcatus was linearly correlated to the overall weight and length of the fish along with the ovarian weight. In conclusion, P. sulcatus spawned synchronously in spring and early summer, exhibiting low fecundity and large oocytes. Our results provided basic information in understanding how this species adapted well to the unique canyon environment, which may be useful for developing a sustainable conservation plan for P. sulcatus at the lower reach of the Yarlung Zangbo River.

Bone is the most common site of distant metastasis from malignant tumors, with the highest prevalence observed in breast and prostate cancers. Such bone metastases (BM) cause many painful skeletal-related events, such as severe bone pain, pathological fractures, spinal cord compression, and hypercalcemia, with adverse effects on life quality. Many bone-targeting agents developed based on the current understanding of BM onset’s molecular mechanisms dull these adverse effects. However, only a few studies investigated potential predictors of high risk for developing BM, despite such knowledge being critical for early interventions to prevent or delay BM. This work proposes a computational network-based pipeline that incorporates a ML/DL component to predict BM development. Based on the proposed pipeline we constructed several machine learning models. The deep neural network (DNN) model exhibited the highest prediction accuracy (AUC of 92.11%) using the top 34 featured genes ranked by betweenness centrality scores. We further used an entirely separate, “external” TCGA dataset to evaluate the robustness of this DNN model and achieved sensitivity of 85%, specificity of 80%, positive predictive value of 78.10%, negative predictive value of 80%, and AUC of 85.78%. The result shows the models’ way of learning allowed it to zoom in on the featured genes that provide the added benefit of the model displaying generic capabilities, that is, to predict BM for samples from different primary sites. Furthermore, existing experimental evidence provides confidence that about 50% of the 34 hub genes have BM-related functionality, which suggests that these common genetic markers provide vital insight about BM drivers. These findings may prompt the transformation of such a method into an artificial intelligence (AI) diagnostic tool and direct us towards mechanisms that underlie metastasis to bone events.

Genetic factors play an important role in the susceptibility to pancreatic cancer (PC). However, established loci explain a small proportion of genetic heritability for PC; therefore, more progress is needed to find the missing ones. We aimed at identifying single nucleotide polymorphisms (SNPs) affecting PC risk through effects on micro-RNA (miRNA) function. We searched in silico the genome for SNPs in miRNA seed sequences or 3 prime untranslated regions (3'UTRs) of miRNA target genes. Genome-wide association data of PC cases and controls from the Pancreatic Cancer Cohort (PanScan) Consortium and the Pancreatic Cancer Case–Control (PanC4) Consortium were re-analyzed for discovery, and genotyping data from two additional consortia (PanGenEU and PANDoRA) were used for replication, for a total of 14,062 cases and 11,261 controls. None of the SNPs reached genome-wide significance in the meta-analysis, but for three of them the associations were in the same direction in all the study populations and showed lower value of p in the meta-analyses than in the discovery phase. Specifically, rs7985480 was consistently associated with PC risk (OR = 1.12, 95% CI 1.07–1.17, p = 3.03 × 10−6 in the meta-analysis). This SNP is in linkage disequilibrium (LD) with rs2274048, which modulates binding of various miRNAs to the 3'UTR of UCHL3, a gene involved in PC progression. In conclusion, our results expand the knowledge of the genetic PC risk through miRNA-related SNPs and show the usefulness of functional prioritization to identify genetic polymorphisms associated with PC risk.

Abstract Background Grass carp (Ctenopharyngodon idellus, GC), as the highest-output fish in China, is economically important. The production of gynogenetic grass carp (GGC) will provide important germplasm resource for producing improved GC. At present, knowledge regarding the heterologous sperm DNA in gynogenetic offspring is little. Thus, revealing paternal DNA in GGC at the molecular level would be highly significant for fish genetic breeding. Result In this study, ultraviolet-treated sperm of koi carp (Cyprinus carpio haematopterus, KOC, 2n = 100), was used to activate the eggs of GC (2n = 48). Afterwards, cold shock (0–4 °C) was administered for 12 min to double the chromosomes, resulting in GGC. No significant difference (p > 0.05) was found between GGC and GC in appearance, erythrocytes size and chromosome numbers. However, at the molecular level, a specific microsatellite DNA fragment (MFW1-gynogenetic grass carp, MFW1-G) derived from the paternal parent KOC was found to be transmitted into GGC. Conclusions For the first time, this study provided an evidence at the molecular level that the DNA fragment derived from the paternal parent occurred in GGC. This finding is of great significance for fish genetic breeding.

Spinal schwannoma is the most common primary spinal tumor but its genomic landscape and underlying mechanism driving its initiation remain elusive. The aim of the present study was to gain further insights into the molecular mechanisms of this kind of tumor through whole genome sequencing of nine spinal schwannomas and paired blood samples. The results showed that ATM, CHD4, FAT1, KMT2D, MED12, NF2, and SUFU were the most frequently mutated cancer-related genes. In addition, the somatic copy number alterations (CNA) was potentially associated with spinal schwannoma, among which NF2 was found to be frequently deleted in schwannoma samples. Only a few genes were located within the amplified regions. In contrast, the deleted regions in 15q15.1 and 7q36.1 contained most of these genes. With respect to tumorigenesis, NF2 had the highest variant allele frequency (VAF) than other genes, and homozygous deletion was observed in NF1, NF2, and CDKN2C. Pathway-level analysis suggested that Hippo signaling pathway may be a critical pathway controlling the initiation of spinal schwannoma. Collectively, this systematic analysis of DNA sequencing data revealed that some key genes including NF1, NF2, and CDKN2C and Hippo signaling pathway were associated with spinal schwannoma, which may help improve our understanding about the genomic landscape of spinal schwannoma.

Abstract Background The increasing spectrum of multidrug-resistant bacteria is a major global public health concern, necessitating discovery of novel antimicrobial agents. Here, members of the genus Bacillus are investigated as a potentially attractive source of novel antibiotics due to their broad spectrum of antimicrobial activities. We specifically focus on a computational analysis of the distinctive biosynthetic potential of Bacillus paralicheniformis strains isolated from the Red Sea, an ecosystem exposed to adverse, highly saline and hot conditions. Results We report the complete circular and annotated genomes of two Red Sea strains, B. paralicheniformis Bac48 isolated from mangrove mud and B. paralicheniformis Bac84 isolated from microbial mat collected from Rabigh Harbor Lagoon in Saudi Arabia. Comparing the genomes of B. paralicheniformis Bac48 and B. paralicheniformis Bac84 with nine publicly available complete genomes of B. licheniformis and three genomes of B. paralicheniformis, revealed that all of the B. paralicheniformis strains in this study are more enriched in nonribosomal peptides (NRPs). We further report the first computationally identified trans-acyltransferase (trans-AT) nonribosomal peptide synthetase/polyketide synthase (PKS/ NRPS) cluster in strains of this species. Conclusions B. paralicheniformis species have more genes associated with biosynthesis of antimicrobial bioactive compounds than other previously characterized species of B. licheniformis, which suggests that these species are better potential sources for novel antibiotics. Moreover, the genome of the Red Sea strain B. paralicheniformis Bac48 is more enriched in modular PKS genes compared to B. licheniformis strains and other B. paralicheniformis strains. This may be linked to adaptations that strains surviving in the Red Sea underwent to survive in the relatively hot and saline ecosystems.

Abstract Background The advantages of Pacific Biosciences (PacBio) single-molecule real-time (SMRT) technology include long reads, low systematic bias, and high consensus read accuracy. Here we use these attributes to improve on the genome annotation of the parasitic hookworm Ancylostoma ceylanicum using PacBio RNA-Seq. Results We sequenced 192,888 circular consensus sequences (CCS) derived from cDNAs generated using the CloneTech SMARTer system. These SMARTer-SMRT libraries were normalized and size-selected providing a robust population of expressed structural genes for subsequent genome annotation. We demonstrate PacBio mRNA sequences based genome annotation improvement, compared to genome annotation using conventional sequencing-by-synthesis alone, by identifying 1609 (9.2%) new genes, extended the length of 3965 (26.7%) genes and increased the total genomic exon length by 1.9 Mb (12.4%). Non-coding sequence representation (primarily from UTRs based on dT reverse transcription priming) was particularly improved, increasing in total length by fifteen-fold, by increasing both the length and number of UTR exons. In addition, the UTR data provided by these CCS allowed for the identification of a novel SL2 splice leader sequence for A. ceylanicum and an increase in the number and proportion of functionally annotated genes. RNA-seq data also confirmed some of the newly annotated genes and gene features. Conclusion Overall, PacBio data has supported a significant improvement in gene annotation in this genome, and is an appealing alternative or complementary technique for genome annotation to the other transcript sequencing technologies.

The connection between lipoprotein (a) [Lp(a)] levels and the risks of cardiovascular disease and diabetes remains poorly understood. Lp(a) is encoded by the LPA gene, and evidence suggests that the kringle IV type 2 (KIV-2) variant is particularly important to Lp(a) isoform size. A large isoform size, represented as a high number of KIV-2 repeats in LPA, is associated with low serum Lp(a) concentrations and an increased risk of type 2 diabetes. We investigated the associations among Lp(a) concentrations, LPA KIV-2 repeats, and type 2 diabetes in a Chinese population of 1,863 consecutive patients with very high cardiovascular risk, as identified by coronary angiography. Individuals with Lp(a) levels in the top tertile [67.86 (35.34–318.50) mg/dl] had a lower risk of diabetes compared with those in the bottom tertile [7.38 (0.60–12.91) mg/dl]. There was an inverse association between the number of KIV-2 repeats and serum Lp(a) concentrations. This study demonstrated that a high number of LPA KIV-2 repeats are associated with increased risk of type 2 diabetes in a Chinese population with very high cardiovascular risk, which suggests that large Lp(a) isoform size, associated with low Lp(a) concentration, has a causal effect on type 2 diabetes.

Early biomarkers of therapeutic responses can help optimize the treatment of metastatic colorectal cancers (mCRC). In this prospective exploratory study, we examined serial changes of plasma-circulating tumor DNA (ctDNA) in 41 mCRC patients receiving first-line chemotherapies and tested its association with treatment outcomes according to radiological assessments. Using next-generation sequencing technologies, we profiled somatic mutations in 50 cancer-related genes in ctDNA before each of the first four treatment cycles. We observed mutations in 95.7% of pre-treatment ctDNA samples. Using mutations of the maximal frequency in each pre-treatment plasma ctDNA sample as the candidate targets, we computed log2 fold changes of ctDNA levels between adjacent treatment cycles. We found that ctDNA reductions as early as prior to cycle 2 predicted responses after cycle 4. Log2 fold changes of ctDNA after cycle 1 (ctDNA log2 (C1/C0)) > −0.126 predicted progressive disease, with an accuracy of 94.6%. These patients also showed significantly worse progression-free survival than those with ctDNA log2 (C1/C0) ≤ −0.126 (median 2.0 vs. 9.0 months; P = 0.007). Together, the present exploratory study suggests that early changes in ctDNA levels detected via targeted sequencing are potential biomarkers of future treatment responses in mCRCs.

As a great challenge in bioinformatics, enzyme function prediction is a significant step toward designing novel enzymes and diagnosing enzyme-related diseases. Existing studies mainly focus on the mono-functional enzyme function prediction. However, the number of multi-functional enzymes is growing rapidly, which requires novel computational methods to be developed. In this paper, following our previous work, DEEPre, which uses deep learning to annotate mono-functional enzyme's function, we propose a novel method, mlDEEPre, which is designed specifically for predicting the functionalities of multi-functional enzymes. By adopting a novel loss function, associated with the relationship between different labels, and a self-adapted label assigning threshold, mlDEEPre can accurately and efficiently perform multi-functional enzyme prediction. Extensive experiments also show that mlDEEPre can outperform the other methods in predicting whether an enzyme is a mono-functional or a multi-functional enzyme (mono-functional vs. multi-functional), as well as the main class prediction across different criteria. Furthermore, due to the flexibility of mlDEEPre and DEEPre, mlDEEPre can be incorporated into DEEPre seamlessly, which enables the updated DEEPre to handle both mono-functional and multi-functional predictions without human intervention.

An amendment to this paper has been published and can be accessed via the original article.