Precise annotation of Drosophila mitochondrial genomes leads to insights into AT-rich regions.

In the present study, we performed precise annotation of Drosophila melanogaster, D. simulans, D. grimshawi, Bactrocera oleae mitochondrial (mt) genomes using pan RNA-seq analysis.

How the Replication and Transcription Complex Functions in Jumping Transcription of SARS-CoV-2.

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although unprecedented efforts are underway to develop therapeutic strategies against this disease, scientists have acquired only a little knowledge regarding the structures and functions of the CoV replication and transcription complex (RTC). Ascertaining all the RTC components and the arrangement of them is an indispensably step for the eventual determination of its global structure, leading to completely understanding all of its functions at the molecular level.

Full-Length Genome of an Strain CBS4732 Δ Reveals Large Duplicated Segments in Subtelomeric Regions.

Background: Currently, methylotrophic yeasts (e.g., , , and ) are subjects of intense genomics studies in basic research and industrial applications.

A Negative Feedback Model to Explain Regulation of SARS-CoV-2 Replication and Transcription.

Background: Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although a preliminary understanding of the replication and transcription of SARS-CoV-2 has recently emerged, their regulation remains unknown.

Results: By comprehensive analysis of genome sequence and protein structure data, we propose a negative feedback model to explain the regulation of CoV replication and transcription, providing a molecular basis of the "leader-to-body fusion" model.

Detecting distant-homology protein structures by aligning deep neural-network based contact maps.

Accurate prediction of atomic-level protein structure is important for annotating the biological functions of protein molecules and for designing new compounds to regulate the functions. Template-based modeling (TBM), which aims to construct structural models by copying and refining the structural frameworks of other known proteins, remains the most accurate method for protein structure prediction. Due to the difficulty in recognizing distant-homology templates, however, the accuracy of TBM decreases rapidly when the evolutionary relationship between the query and template vanishes.

Predicting essential proteins from protein-protein interactions using order statistics.

Many computational methods have been proposed to predict essential proteins from protein-protein interaction (PPI) networks. However, it is still challenging to improve the prediction accuracy. In this study, we propose a new method, esPOS (essential proteins Predictor using Order Statistics) to predict essential proteins from PPI networks.

NormExpression: An R Package to Normalize Gene Expression Data Using Evaluated Methods.

Data normalization is a crucial step in the gene expression analysis as it ensures the validity of its downstream analyses. Although many metrics have been designed to evaluate the existing normalization methods, different metrics or different datasets by the same metric yield inconsistent results, particularly for the single-cell RNA sequencing (scRNA-seq) data. The worst situations could be that one method evaluated as the best by one metric is evaluated as the poorest by another metric, or one method evaluated as the best using one dataset is evaluated as the poorest using another dataset.

Using Pan RNA-Seq Analysis to Reveal the Ubiquitous Existence of 5' and 3' End Small RNAs.

In this study, we used pan RNA-seq analysis to reveal the ubiquitous existence of both 5' and 3' end small RNAs (5' and 3' sRNAs). 5' and 3' sRNAs alone can be used to annotate nuclear non-coding and mitochondrial genes at 1-bp resolution and identify new steady RNAs, which are usually transcribed from functional genes. Then, we provided a simple and cost effective way for the annotation of nuclear non-coding and mitochondrial genes and the identification of new steady RNAs, particularly long non-coding RNAs (lncRNAs).

Complemented Palindromic Small RNAs First Discovered from SARS Coronavirus.

In this study, we report for the first time the existence of complemented palindromic small RNAs (cpsRNAs) and propose that cpsRNAs and palindromic small RNAs (psRNAs) constitute a novel class of small RNAs. The first discovered 19-nt cpsRNA UUAACAAGCUUGUUAAAGA, named SARS-CoV-cpsR-19, was detected from a 22-bp DNA complemented palindrome TCTTTAACAAGCTTGTTAAAGA in the severe acute respiratory syndrome coronavirus (SARS-CoV) genome. The phylogenetic analysis supported that this DNA complemented palindrome originated from bat betacoronavirus.

Disease Gene Prediction by Integrating PPI Networks, Clinical RNA-Seq Data and OMIM Data.

Disease gene prediction is a challenging task that has a variety of applications such as early diagnosis and drug development. The existing machine learning methods suffer from the imbalanced sample issue because the number of known disease genes (positive samples) is much less than that of unknown genes which are typically considered to be negative samples. In addition, most methods have not utilized clinical data from patients with a specific disease to predict disease genes.

A Novel Method for Drug Screen to Regulate G Protein-Coupled Receptors in the Metabolic Network of Alzheimer's Disease.

Alzheimer's disease (AD) is a chronic and progressive neurodegenerative disorder and the pathogenesis of AD is poorly understood. G protein-coupled receptors (GPCRs) are involved in numerous key AD pathways and play a key role in the pathology of AD. To fully understand the pathogenesis of AD and design novel drug therapeutics, analyzing the connection between AD and GPCRs is of great importance.

Gene expression profiling reveals U1 snRNA regulates cancer gene expression.

U1 small nuclear RNA (U1 snRNA), as one of the most abundant ncRNAs in human cells, plays an important role in splicing of pre-mRNAs. Compared to previous studies which have focused on the primary function of U1 snRNA and the neurodegenerative diseases caused by abnormalities of U1 snRNA, this study is to investigate how U1 snRNA over-expression affects the expression of mammal genes on a genome-wide scale. By comparing the gene expression profiles of U1 snRNA over-expressed cells with those of their controls using microarray experiments, 916 genes or loci were identified significantly Differentially Expressed (DE).

Western medication plus Traditional Chinese Medicine preparations in patients with chronic heart failure: a prospective, single-blind, randomized, controlled, and multicenter clinical trial.

Objective: To assess the efficacy and safety in patients with chronic heart failure (CHF) of Western medication plus Traditional Chinese Medicine (TCM) preparations.

Methods: This prospective, single-blind, randomized, controlled, and multicenter clinical trial began on September 17, 2008, and was completed on June 25, 2011. A total of 340 inpatients, aged 40-79 years, with exacerbating CHF from 10 hospitals were enrolled and randomly allocated within 24 h of admission.

Two novel lncRNAs discovered in human mitochondrial DNA using PacBio full-length transcriptome data.

In this study, we established a general framework to use PacBio full-length transcriptome sequencing for the investigation of mitochondrial RNAs. As a result, we produced the first full-length human mitochondrial transcriptome using public PacBio data and characterized the human mitochondrial genome with more comprehensive and accurate information. Other results included determination of the H-strand primary transcript, identification of the ND5/ND6AS/tRNAAS transcript, discovery of palindrome small RNAs (psRNAs) and construction of the "mitochondrial cleavage" model, etc.

Using Small RNA-seq Data to Detect siRNA Duplexes Induced by Plant Viruses.

Small interfering RNA (siRNA) duplexes are short (usually 21 to 24 bp) double-stranded RNAs (dsRNAs) with several overhanging nucleotides at both 5'- and 3'-ends. It has been found that siRNA duplexes bind the RNA-induced silencing complex (RISC) and cleave the sense strands with endonucleases. In this study, for the first time, we detected siRNA duplexes induced by plant viruses on a large scale using next-generation sequencing (NGS) data.

Two featured series of rRNA-derived RNA fragments (rRFs) constitute a novel class of small RNAs.

In this study, we reported two featured series of rRNA-derived RNA fragments (rRFs) from the small RNA sequencing (sRNA-seq) data of Amblyomma testudinarium using the Illunima platform. Two series of rRFs (rRF5 and rRF3) were precisely aligned to the 5' and 3' ends of the 5.8S and 28S rRNA gene.

PrAS: Prediction of amidation sites using multiple feature extraction.

Amidation plays an important role in a variety of pathological processes and serious diseases like neural dysfunction and hypertension. However, identification of protein amidation sites through traditional experimental methods is time consuming and expensive. In this paper, we proposed a novel predictor for Prediction of Amidation Sites (PrAS), which is the first software package for academic users.

PacBio full-length transcriptome profiling of insect mitochondrial gene expression.

In this study, we sequenced the first full-length insect transcriptome using the Erthesina fullo Thunberg based on the PacBio platform. We constructed the first quantitative transcription map of animal mitochondrial genomes and built a straightforward and concise methodology to investigate mitochondrial gene transcription, RNA processing, mRNA maturation and several other related topics. Most of the results were consistent with the previous studies, while to the best of our knowledge some findings were reported for the first time in this study.

Improved Species-Specific Lysine Acetylation Site Prediction Based on a Large Variety of Features Set.

Lysine acetylation is a major post-translational modification. It plays a vital role in numerous essential biological processes, such as gene expression and metabolism, and is related to some human diseases. To fully understand the regulatory mechanism of acetylation, identification of acetylation sites is first and most important.

Using Small RNA Deep Sequencing Data to Detect Human Viruses.

Small RNA sequencing (sRNA-seq) can be used to detect viruses in infected hosts without the necessity to have any prior knowledge or specialized sample preparation. The sRNA-seq method was initially used for viral detection and identification in plants and then in invertebrates and fungi. However, it is still controversial to use sRNA-seq in the detection of mammalian or human viruses.

PSIONplus: Accurate Sequence-Based Predictor of Ion Channels and Their Types.

Ion channels are a class of membrane proteins that attracts a significant amount of basic research, also being potential drug targets. High-throughput identification of these channels is hampered by the low levels of availability of their structures and an observation that use of sequence similarity offers limited predictive quality. Consequently, several machine learning predictors of ion channels from protein sequences that do not rely on high sequence similarity were developed.

Uncovering the Molecular Mechanism of Actions between Pharmaceuticals and Proteins on the AD Network.

This study begins with constructing the mini metabolic networks (MMNs) of beta amyloid (Aβ) and acetylcholine (ACh) which stimulate the Alzheimer's Disease (AD). Then we generate the AD network by incorporating MMNs of Aβ and ACh, and other MMNs of stimuli of AD. The panel of proteins contains 49 enzymes/receptors on the AD network which have the 3D-structure in PDB.

Analysis of Conformational B-Cell Epitopes in the Antibody-Antigen Complex Using the Depth Function and the Convex Hull.

The prediction of conformational b-cell epitopes plays an important role in immunoinformatics. Several computational methods are proposed on the basis of discrimination determined by the solvent-accessible surface between epitopes and non-epitopes, but the performance of existing methods is far from satisfying. In this paper, depth functions and the k-th surface convex hull are used to analyze epitopes and exposed non-epitopes.