An optimized protocol for generation and analysis of Ion Proton sequencing reads for RNA-Seq.

BACKGROUND: Previous studies compared running cost, time and other performance measures of popular sequencing platforms. However, comprehensive assessment of library construction and analysis protocols for Proton sequencing platform remains unexplored. Unlike Illumina sequencing platforms, Proton reads are heterogeneous in length and quality. When sequencing data from different platforms are combined, this can result in reads with various read length. Whether the performance of the commonly used software for handling such kind of data is satisfactory is unknown. RESULTS: By using universal human reference RNA as the initial material, RNaseIII and chemical fragmentation methods in library construction showed similar result in gene and junction discovery number and expression level estimated accuracy. In contrast, sequencing quality, read length and the choice of software affected mapping rate to a much larger extent. Unspliced aligner TMAP attained the highest mapping rate (97.27 % to genome, 86.46 % to transcriptome), though 47.83 % of mapped reads were clipped. Long reads could paradoxically reduce mapping in junctions. With reference annotation guide, the mapping rate of TopHat2 significantly increased from 75.79 to 92.09 %, especially for long (>150 bp) reads. Sailfish, a k-mer based gene expression quantifier attained highly consistent results with that of TaqMan array and highest sensitivity. CONCLUSION: We provided for the first time, the reference statistics of library preparation methods, gene detection and quantification and junction discovery for RNA-Seq by the Ion Proton platform. Chemical fragmentation performed equally well with the enzyme-based one. The optimal Ion Proton sequencing options and analysis software have been evaluated.

Identification of Ube2b as a novel target of androgen receptor in mouse sertoli cells.

Many genes are regulated by androgen and its receptor (AR), but the direct target genes of AR, especially those involved in spermatogenesis and male infertility, remain unclear. Here, we identified ubiquitin-conjugating enzyme E2B (Ube2b) as a critical target gene of AR. The expression of UBE2B was decreased in the testes of Sertoli cell AR knockout (S-AR(-/y)) mice analyzed by quantitative RT-PCR (qRT-PCR) and immunofluorescence. The upregulation of Ube2b gene by testosterone was further demonstrated by Western blot and qRT-PCR in TM4 cells, a mouse Sertoli cell line. Moreover, luciferase assay, electrophoretic mobility shift assay, and chromatin immunoprecipitation assay validated that the ligand-bound AR activated Ube2b transcription via direct binding to the androgen-responsive element of the Ube2b promoter. In vitro analyses showed that testosterone increased UBE2B expression and activated H2A ubiquitylation, while downregulation of UBE2B blocked the testosterone-induced H2A ubiquitylation. The ubiquitylation of H2A was markedly decreased in the testes of S-AR(-/y) mice by immunohistochemistry. Digital gene expression analysis showed that 113 genes were significantly downregulated and 71 were upregulated by UBE2B in TM4 cells. These results suggest that Ube2b, as a direct AR transcriptional target in Sertoli cells, mediates the function of AR in spermatogenesis by promoting H2A ubiquitylation.

Evaluation of exosomal miRNAs as potential diagnostic biomarkers for acute myocardial infarction using next-generation sequencing.

BACKGROUND: Acute myocardial infarction (AMI) is one of the most common global causes of death. Although considerable progress has been made in AMI diagnosis, there remains an urgent need for novel diagnostic biomarkers for its prevention and treatment. Functional exosomal microRNAs (miRNAs) are recognized as potential biomarkers in many diseases. This study's objective was to identify specific plasma exosomal miRNAs with biomarker potential for early AMI detection. METHODS: Exosomes from the plasma of 26 coronary artery disease (CAD) patients, 55 AMI patients, and 37 healthy controls were isolated and characterized by transmission electron microcopy (TEM), western blotting, and nanoparticle tracking analysis (NTA). The miRNAs were purified from exosomes, and unique molecular identifier (UMI) small RNA sequencing was performed. The random forest (RF) model was trained to predict potential biomarkers. RESULTS: NTA demonstrated that nanoparticle concentration did not change after AMI, while nanoparticle size distribution significantly decreased. The CAD and AMI groups' miRNA expression profiles significantly differed from the healthy group's profile. The RF classifier could be used to distinguish the healthy group from the AMI group, but could not be used to distinguish the CAD group from the other groups, which caused a high classification error rate. Eighteen miRNAs were selected as biomarkers based on their RF classifier significance. The diagnostic accuracy of 18 miRNAs was evaluated using AUC values of 0.93, 0.87, and 0.75 to detect healthy controls, AMI, and CAD, respectively. CONCLUSIONS: Nanoparticle diameter and the 18 miRNAs may serve as simple and accessible fingerprints for early AMI diagnosis.