The genome-wide association study of serum IgE levels demonstrated a shared genetic background in allergic diseases.

Immunoglobulin E (IgE) synthessis is highly related to a variety of atopic diseases, and several genome-wide association studies (GWASs) have demonstrated the association between genes and IgE level. In this study, we conducted the largest genome-wide association study of IgE involving a Taiwanese Han population. Eight independent variants exhibited genome-wide significance. Among them, an intronic SNP of CD28, rs1181388, and an intergenic SNP, rs1002957030, on 11q23.2 were identified as novel signals for IgE. Seven of the loci were replicated successfully in a meta-analysis using data on Japanese population. Among all the human leukocyte antigen (HLA) regions, HLA-DQA1*03:02 - HLA-DQB1*03:03 was the most significant haplotype (OR = 1.25, SE = 0.02, FDR = 1.6 × 10-14), corresponding to HLA-DQA1 Asp160 and HLA-DQB1 Leu87 amino acid residues. The genetic correlation showed significance between IgE and allergic diseases including asthma, atopic dermatitis, and pollinosis. IgE PRS was significantly correlated with total IgE levels. Furthermore, the top decile IgE polygenic risk score (PRS) group had the highest risk of asthma for the Taiwan Biobank and Biobank Japan cohorts. IgE PRS may be used to aid in predicting the occurrence of allergic reactions before symptoms occur and biomarkers are detectable. Our study provided a more comprehensive understanding of the impact of genomic variants, including complex HLA alleles, on serum IgE levels.

RNA editing-based classification of diffuse gliomas: predicting isocitrate dehydrogenase mutation and chromosome 1p/19q codeletion.

BACKGROUND: Accurate classification of diffuse gliomas, the most common tumors of the central nervous system in adults, is important for appropriate treatment. However, detection of isocitrate dehydrogenase (IDH) mutation and chromosome1p/19q codeletion, biomarkers to classify gliomas, is time- and cost-intensive and diagnostic discordance remains an issue. Adenosine to inosine (A-to-I) RNA editing has emerged as a novel cancer prognostic marker, but its value for glioma classification remains largely unexplored. We aim to (1) unravel the relationship between RNA editing and IDH mutation and 1p/19q codeletion and (2) predict IDH mutation and 1p/19q codeletion status using machine learning algorithms. RESULTS: By characterizing genome-wide A-to-I RNA editing signatures of 638 gliomas, we found that tumors without IDH mutation exhibited higher total editing level compared with those carrying it (Kolmogorov-Smirnov test, p < 0.0001). When tumor grade was considered, however, only grade IV tumors without IDH mutation exhibited higher total editing level. According to 10-fold cross-validation, support vector machines (SVM) outperformed random forest and AdaBoost (DeLong test, p < 0.05). The area under the receiver operating characteristic curve (AUC) of SVM in predicting IDH mutation and 1p/19q codeletion were 0.989 and 0.990, respectively. After performing feature selection, AUCs of SVM and AdaBoost in predicting IDH mutation were higher than that of random forest (0.985 and 0.983 vs. 0.977; DeLong test, p < 0.05), but AUCs of the three algorithms in predicting 1p/19q codeletion were similar (0.976-0.982). Furthermore, 67% of the six continuously misclassified samples by our 1p/19q codeletion prediction models were misclassifications in the original labelling after inspection of 1p/19q status and/or pathology report, highlighting the accuracy and clinical utility of our models. CONCLUSIONS: The study represents the first genome-wide analysis of glioma editome and identifies RNA editing as a novel prognostic biomarker for glioma. Our prediction models provide standardized, accurate, reproducible and objective classification of gliomas. Our models are not only useful in clinical decision-making, but also able to identify editing events that have the potential to serve as biomarkers and therapeutic targets in glioma management and treatment.

Transcriptome dynamics of developing maize leaves and genomewide prediction of cis elements and their cognate transcription factors.

Maize is a major crop and a model plant for studying C4 photosynthesis and leaf development. However, a genomewide regulatory network of leaf development is not yet available. This knowledge is useful for developing C3 crops to perform C4 photosynthesis for enhanced yields. Here, using 22 transcriptomes of developing maize leaves from dry seeds to 192 h post imbibition, we studied gene up- and down-regulation and functional transition during leaf development and inferred sets of strongly coexpressed genes. More significantly, we developed a method to predict transcription factor binding sites (TFBSs) and their cognate transcription factors (TFs) using genomic sequence and transcriptomic data. The method requires not only evolutionary conservation of candidate TFBSs and sets of strongly coexpressed genes but also that the genes in a gene set share the same Gene Ontology term so that they are involved in the same biological function. In addition, we developed another method to predict maize TF-TFBS pairs using known TF-TFBS pairs in Arabidopsis or rice. From these efforts, we predicted 1,340 novel TFBSs and 253 new TF-TFBS pairs in the maize genome, far exceeding the 30 TF-TFBS pairs currently known in maize. In most cases studied by both methods, the two methods gave similar predictions. In vitro tests of 12 predicted TF-TFBS interactions showed that our methods perform well. Our study has significantly expanded our knowledge on the regulatory network involved in maize leaf development.

Identification of genes and pathways related to lymphovascular invasion in breast cancer patients: A bioinformatics analysis of gene expression profiles.

Surgery is the most effective treatment for breast cancer patients. However, some patients developed recurrence and distant metastasis after surgery. Adjuvant therapy is considered for high-risk patients depending on several prognostic markers, and lymphovascular invasion has become one of such prognostic markers that help physicians to identify the risk for distant metastasis and recurrence. However, the mechanism of lymphovascular invasion in breast cancer remains unknown. This study aims to unveil the genes and pathways that may involve in lymphovascular invasion in breast cancer. In total, 108 breast cancer samples were collected during surgery and microarray analysis was performed. Significance analysis of the microarrays and limma package for R were used to examine differentially expressed genes between lymphovascular invasion-positive and lymphovascular invasion-negative cases. Network and pathway analyses were mapped using the Ingenuity Pathway Analysis and the Database for Annotation, Visualization and Integrated Discovery. In total, 86 differentially expressed genes, including 37 downregulated genes and 49 upregulated genes were identified in lymphovascular invasion-positive patients. Among these genes, TNFSF11, IL6ST, and EPAS1 play important roles in cytokine-receptor interaction, which is the most enriched pathway related to lymphovascular invasion. Moreover, the results also suggested that an imbalance between extracellular matrix components and tumor micro-environment could induce lymphovascular invasion. Our study evaluated the underlying mechanisms of lymphovascular invasion, which may further help to assess the risk of breast cancer progression and identify potential targets of adjuvant treatment.

Anatomical and transcriptional dynamics of maize embryonic leaves during seed germination.

Our anatomical analysis revealed that a dry maize seed contains four to five embryonic leaves at different developmental stages. Rudimentary kranz structure (KS) is apparent in the first leaf with a substantial density, but its density decreases toward younger leaves. Upon imbibition, leaf expansion occurs rapidly with new KSs initiated from the palisade-like ground meristem cells in the middle of the leaf. In parallel to the anatomical analysis, we obtained the time course transcriptomes for the embryonic leaves in dry and imbibed seeds every 6 h up to hour 72. Over this time course, the embryonic leaves exhibit transcripts of 30,255 genes at a level that can be regarded as "expressed." In dry seeds, ∼25,500 genes are expressed, showing functional enrichment in transcription, RNA processing, protein synthesis, primary metabolic pathways, and calcium transport. During the 72-h time course, ∼13,900 genes, including 590 transcription factor genes, are differentially expressed. Indeed, by 30 h postimbibition, ∼2,200 genes expressed in dry seeds are already down-regulated, and ∼2,000 are up-regulated. Moreover, the top 1% expressed genes at 54 h or later are very different from those before 30 h, reflecting important developmental and physiological transitions. Interestingly, clusters of genes involved in hormone metabolism, signaling, and responses are differentially expressed at various time points and TF gene expression is also modular and stage specific. Our dataset provides an opportunity for hypothesizing the timing of regulatory actions, particularly in the context of KS development.

Maize and millet transcription factors annotated using comparative genomic and transcriptomic data.

BACKGROUND: Transcription factors (TFs) contain DNA-binding domains (DBDs) and regulate gene expression by binding to specific DNA sequences. In addition, there are proteins, called transcription coregulators (TCs), which lack DBDs but can alter gene expression through interaction with TFs or RNA Polymerase II. Therefore, it is interesting to identify and classify the TFs and TCs in a genome. In this study, maize (Zea mays) and foxtail millet (Setaria italica), two important species for the study of C4 photosynthesis and kranz anatomy, were selected. RESULT: We conducted a comprehensive genome-wide annotation of TFs and TCs in maize B73 and in two strains of foxtail millet, Zhang gu and Yugu1, and classified them into families. To gain additional support for our predictions, we searched for their homologous genes in Arabidopsis or rice and studied their gene expression level using RNA-seq and microarray data. We identified many new TF and TC families in these two species, and described some evolutionary and functional aspects of the 9 new maize TF families. Moreover, we detected many pseudogenes and transposable elements in current databases. In addition, we examined tissue expression preferences of TF and TC families and identified tissue/condition-specific TFs and TCs in maize and millet. Finally, we identified potential C4-related TF and TC genes in maize and millet. CONCLUSIONS: Our results significantly expand current TF and TC annotations in maize and millet. We provided supporting evidence for our annotation from genomic and gene expression data and identified TF and TC genes with tissue preference in expression. Our study may facilitate the study of regulation of gene expression, tissue morphogenesis, and C4 photosynthesis in maize and millet. The data we generated in this study are available at http://sites.google.com/site/jjlmmtf.

The relationships among microRNA regulation, intrinsically disordered regions, and other indicators of protein evolutionary rate.

Many indicators of protein evolutionary rate have been proposed, but some of them are interrelated. The purpose of this study is to disentangle their correlations. We assess the strength of each indicator by controlling for the other indicators under study. We find that the number of microRNA (miRNA) types that regulate a gene is the strongest rate indicator (a negative correlation), followed by disorder content (the percentage of disordered regions in a protein, a positive correlation); the strength of disorder content as a rate indicator is substantially increased after controlling for the number of miRNA types. By dividing proteins into lowly and highly intrinsically disordered proteins (L-IDPs and H-IDPs), we find that proteins interacting with more H-IDPs tend to evolve more slowly, which largely explains the previous observation of a negative correlation between the number of protein-protein interactions and evolutionary rate. Moreover, all of the indicators examined here, except for the number of miRNA types, have different strengths in L-IDPs and in H-IDPs. Finally, the number of phosphorylation sites is weakly correlated with the number of miRNA types, and its strength as a rate indicator is substantially reduced when other indicators are considered. Our study reveals the relative strength of each rate indicator and increases our understanding of protein evolution.

RNA Editing in Glioma as a Sexually Dimorphic Prognostic Factor That Affects mRNA Abundance in Fatty Acid Metabolism and Inflammation Pathways.

RNA editing alters the nucleotide sequence and has been associated with cancer progression. However, little is known about its prognostic and regulatory roles in glioma, one of the most common types of primary brain tumors. We characterized and analyzed RNA editomes of glioblastoma and isocitrate dehydrogenase mutated (IDH-MUT) gliomas from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas (CGGA). We showed that editing change during glioma progression was another layer of molecular alterations and that editing profiles predicted the prognosis of glioblastoma and IDH-MUT gliomas in a sex-dependent manner. Hyper-editing was associated with poor survival in females but better survival in males. Moreover, noncoding editing events impacted mRNA abundance of the host genes. Genes associated with inflammatory response (e.g., EIF2AK2, a key mediator of innate immunity) and fatty acid oxidation (e.g., acyl-CoA oxidase 1, the rate-limiting enzyme in fatty acid ß-oxidation) were editing-regulated and associated with glioma progression. The above findings were further validated in CGGA samples. Establishment of the prognostic and regulatory roles of RNA editing in glioma holds promise for developing editing-based therapeutic strategies against glioma progression. Furthermore, sexual dimorphism at the epitranscriptional level highlights the importance of developing sex-specific treatments for glioma.

Phosphorylated and nonphosphorylated serine and threonine residues evolve at different rates in mammals.

Protein phosphorylation plays an important role in the regulation of protein function. Phosphorylated residues are generally assumed to be subject to functional constraint, but it has recently been suggested from a comparison of distantly related vertebrate species that most phosphorylated residues evolve at the rates consistent with the surrounding regions. To resolve the controversy, we infer the ancestral phosphoproteome of human and mouse to compare the evolutionary rates of phosphorylated and nonphosphorylated serine (S), threonine (T), and tyrosine (Y) residues. This approach enables accurate estimation of evolutionary rates as it does not assume deep conservation of phosphorylated residues. We show that phosphorylated S/T residues tend to evolve more slowly than nonphosphorylated S/T residues not only in disordered but also in ordered protein regions, indicating evolutionary conservation of phosphorylated S/T residues in mammals. Thus, phosphorylated S/T residues tend to be subject to stronger functional constraint than nonphosphorylated residues regardless of the protein regions in which they reside. In contrast, phosphorylated Y residues evolve at similar rates as nonphosphorylated ones. We also find that the human lineage has gained more phosphorylated T residues and lost fewer phosphorylated Y residues than the mouse lineage. The cause of the gain/loss imbalance remains a mystery but should be worth exploring.

Joint effect of changes in physical activity and weight on incident non-alcoholic fatty liver disease.

BACKGROUND: Increases in physical activity (PA) and weight have opposite effects on the risk of non-alcoholic fatty liver disease (NAFLD), but their joint effect remains unknown. We examined the dose-effect of PA increase for NAFLD prevention and the amount of PA increase required to offset the deleterious effect of weight gain. METHODS: We analysed 47 058 participants who were extracted from the Taiwan MJ cohort, aged 20-50 years, without NAFLD at baseline, and followed at 1-5 years between 1997 and 2016. The outcome was incident NAFLD, diagnosed by ultrasonography. PA was measured by metabolic equivalents (METs) and duration (hour/week). We used flexible parametric survival models to estimate the HRs of annual change in PA and body mass index (BMI), controlling for their interaction and baseline covariates. RESULTS: During 138 646 person-years of follow-up, 12 836 participants (40.6% men and 20.1% women) developed incident NAFLD. The HR (95% CI) of annual PA increase of 1 MET-hour/week was 0.88 (0.85-0.92) after controlling for weight change. Moreover, 28 min/week of moderate-intensity PA could neutralise NAFLD risk elevated by annual BMI increase of 0.1 kg/m2 at the end of year 3. We also observed an extra 35% risk reduction when PA increase (1 MET-hour/week) and weight loss (0.1 kg/m2) occurred simultaneously. CONCLUSIONS: Annual PA increase of 1 MET-hour/week was associated with a 12% lower NAFLD risk. PA increase can counteract the harmful effect of weight gain and there is a synergistic effect from PA increase and weight loss.

The Cancer Editome Atlas: A Resource for Exploratory Analysis of the Adenosine-to-Inosine RNA Editome in Cancer.

Increasing evidence has suggested a role for adenosine-to-inosine RNA editing in carcinogenesis. However, the clinical utility of RNA editing remains limited because functions of the vast majority of editing events remain largely unexplored. To help the cancer research community investigate functional consequences of individual editing events, we have developed a user-friendly bioinformatic resource, The Cancer Editome Atlas (TCEA; http://tcea.tmu.edu.tw). TCEA characterizes >192 million editing events at >4.6 million editing sites from approximately 11,000 samples across 33 cancer types in The Cancer Genome Atlas. Clinical information, miRNA expression, and alteration in miRNA targeting modulated through RNA editing are also integrated into TCEA. TCEA supports several modules to search, analyze, and visualize the cancer editome, providing a solid basis for investigating the oncogenic mechanisms of RNA editing and expediting the identification of therapeutic targets in cancer. SIGNIFICANCE: This user-friendly bioinformatic resource reduces the barrier to analyzing the huge and complex cancer RNA editome that cancer researchers face and facilitates the identification of novel therapeutic targets in cancer.

Liver Fat, Hepatic Enzymes, Alkaline Phosphatase and the Risk of Incident Type 2 Diabetes: A Prospective Study of 132,377 Adults.

Previous studies have reported inconsistent results of the associations of alanine transaminase (ALT), aspartate transaminase (AST), gamma-glutamyltransferase (GGT) and alkaline phosphatase (ALP) with incident type 2 diabetes (diabetes hereafter). We aimed to resolve the controversy by taking nonalcoholic fatty liver disease (NAFLD) into account. The study population comprised 132,377 non-diabetic individuals (64,875 men and 67,502 women) aged 35-79 who had two or more health examinations during 1996-2014. A total of 6,555 incident diabetes (3,734 men and 2,821 women) were identified, on average, over 5.8 years of follow-up. Cox regression was used to calculate the hazard ratio (HR) for incident diabetes, adjusting for classical confounders. The risk of incident diabetes was significantly associated with NAFLD [HR = 2.08 (men) and 2.65 (women)]. Elevated ALT, AST, GGT and ALP were also significantly associated with the increased risk of diabetes, with HRs of 1.27, 1.23, 1.58 and 1.37, respectively, in men, and 1.56, 1.18, 1.48 and 1.44, respectively in women. Our results suggest that NAFLD, ALT, AST, GGT and ALP are independent predictors for incident diabetes in both men and women.