Differential expression of circular RNA in patients with white matter hyperintensity and cognitive impairment / 中南大学学报(医学版)

OBJECTIVES@#White matter hyperintensity (WMH) is an important factor leading to cognitive impairment, and the mechanism has not been clarified. In recent years, studies have found that circular RNA (circRNA) has differential expression in cerebrovascular diseases. This study aims to analyze the expression profile of circRNA in peripheral blood mononuclear cell (PBMC) of patients with WMH with cognitive impairment, to screen the differentially expressed circRNA, and to explore the possible role of circRNA in WMH with cognitive impairment.@*METHODS@#CircRNA microarray was used to detect the circRNA expression profile of PBMC in patients with WMH with cognitive impairment, and in patients with WMH without cognitive impairment as well as in normal controls (3 cases each, male to female ratio of 2꞉1). The differentially expressed circRNA in patients with WMH with cognitive impairment was screened. The screening criteria for differentially expressed circRNA was fold change (FC) ≥2.0 (|log@*RESULTS@#Compared with the control group, there were 5 significantly up-regulated circRNA and 3 down-regulated circRNA in the WMH with cognitive impairment group; 8 circRNA were significantly up-regulated and 2 were down-regulated in the WMH without cognitive impairment group. When compared with the WMH with cognitive impairment group, no co-differentially expressed circRNA was found in WMH without cognitive impairment group and control group. Compared with the control group, the expression of hsa_circ_0092222 was up-regulated and the expressions of hsa_circ_0000662 and hsa_circ_0083773 were down-regulated in the WMH with cognitive impairment group and the WMH without cognitive impairment group, and there was no significant difference between the 2 groups (all @*CONCLUSIONS@#The circRNA expression profile of patients with WMH is changed significantly. The differentially expressed circRNA may be the cause of WMH; Hsa_circ_0092222, hsa_circ_0000662, and hsa_circ_0083773 may regulate the expression of target genes by targeting adsorption of the target miRNA, leading to brain white matter damage through Janus kinase 2 (JAK2)/signal transducers and activators of transcription (STAT3) signal pathway and Wnt signal pathway.There is no significant difference in circRNA expression profile between WMH with or without cognitive impairment. Cognitive impairment in patients with WMH may have other reasons.

Research progress on biomarkers of rejection risk in organ transplantation / 器官移植

Rejection is the main cause of transplantation failure. Currently, the specificity and sensitivity of clinical parameters are relatively poor, which cannot accurately prompt the exact cause of rejection. It is of great clinical significance to explore novel biomarkers for monitoring the rejection. In this article, the latest research progress on the biomarkers of rejection risk in organ transplantation were summarized from the perspectives of transplantation pathology, immune cells and regulatory immune cells, non-human leukocyte antigen antibodies, exosomes, cell-free DNA and combination gene prediction, aiming to provide reference for early warning and treatment of rejection in organ transplantation.

gFACs: Gene Filtering, Analysis, and Conversion to Unify Genome Annotations Across Alignment and Gene Prediction Frameworks / 基因组蛋白质组与生物信息学报·英文版

Published genomes frequently contain erroneous gene models that represent issues associated with identification of open reading frames, start sites, splice sites, and related structural features. The source of these inconsistencies is often traced back to integration across text file formats designed to describe long read alignments and predicted gene structures. In addition, the majority of gene prediction frameworks do not provide robust downstream filtering to remove problematic gene annotations, nor do they represent these annotations in a format consistent with current file standards. These frameworks also lack consideration for functional attributes, such as the presence or absence of protein domains that can be used for gene model validation. To provide oversight to the increasing number of published genome annotations, we present a software package, the Gene Filtering, Analysis, and Conversion (gFACs), to filter, analyze, and convert predicted gene models and alignments. The software operates across a wide range of alignment, analysis, and gene prediction files with a flexible framework for defining gene models with reliable structural and functional attributes. gFACs supports common downstream applications, including genome browsers, and generates extensive details on the filtering process, including distributions that can be visualized to further assess the proposed gene space. gFACs is freely available and implemented in Perl with support from BioPerl libraries at https://gitlab.com/PlantGenomicsLab/gFACs.

Screening and analysis of long non-coding RNA differential expression in Xinjiang Han patients with esoph-ageal squamous cell carcinoma / 实用医学杂志

Objective To investigate the expression alteration and significance of long non-coding RNA (lncRNA)by GWAS(Genome-wide association study)between Esophageal squamous cell carcinoma(ESCC)and its adjacent normal esophageal tissues. Methods lncRNA and mRNA differential expression in 6 pairs of ESCC and matched non-cancerous tissues were screened by microarray assay. The target genes were predicted. Finally , GO(Gene Ontology)and Pathway analysis was used for the further research of lncRNA. Results A total of 680 lncRNA and 1472mRNA were differentially expressed at more than two-fold change(P ≤ 0.05,with 161lncRNA and 653mRNA up-regulated,519lncRNA and 819mRNA down-regulated between ESCC and its adjacent normal esophageal tissues. Gene ontology and pathway analysis results suggested that the differentially expressed genes were involved in 11 pathways.Theyare potentially associated with esophageal squamous cell carcinoma ,including post-translational protein modification ,mucin type O-Glycan biosynthesis and sphingolipid metabolism pathways , which mainly related to the changes of molecular function ,cellular components and biological processes. Through cis and trans analysis,a total of 15 differentially expressed lncRNA had cis-and/or trans-regulated target genes in the database,with 13 lncRNA had cis-regulated target genes,3 lncRNA had trans-regulated target genes,and 1 lncRNA had both cis- and trans-regulated target genes. Conclusion Compared with adjacent normal tissues ,a large number of lncRNA were expressed differentially in ESCC in Xinjiang Han people.Aberrantly expressed lncRNA may play important roles in ESCC development and progression through some signaling pathways ,which are of great significance for further search of new targets for the diagnosis and treatment of ESCC.

Comparative sequence analyses of genome and transcriptome reveal novel transcripts and variants in the Asian elephant Elephas maximus.

The Asian elephant Elephas maximus and the African elephant Loxodonta africana that diverged 5–7 million years ago exhibit differences in their physiology, behaviour and morphology. A comparative genomics approach would be useful and necessary for evolutionary and functional genetic studies of elephants. We performed sequencing of E. maximus and map to L. africana at ~15X coverage. Through comparative sequence analyses, we have identified Asian elephant specific homozygous, non-synonymous single nucleotide variants (SNVs) that map to 1514 protein coding genes, many of which are involved in olfaction. We also present the first report of a high-coverage transcriptome sequence in E. maximus from peripheral blood lymphocytes. We have identified 103 novel protein coding transcripts and 66-long non-coding (lnc)RNAs. We also report the presence of 181 protein domains unique to elephants when compared to other Afrotheria species. Each of these findings can be further investigated to gain a better understanding of functional differences unique to elephant species, as well as those unique to elephantids in comparison with other mammals. This work therefore provides a valuable resource to explore the immense research potential of comparative analyses of transcriptome and genome sequences in the Asian elephant.

Mining Alzheimer's Disease Susceptible Genes Based on Data Integration Strategy / 中国康复理论与实践

@# Objective To clarify the role of the known genes and new discovered genes, which were important to the pathogenesis of Alzheimer's disease (AD), in order to provide targets for clinical prevention, diagnosis and treatment. Methods In order to predict AD susceptible genes, the website databases (OMIM, AlzGene) and a variety of pathogenic gene prediction tools such as Endeavour, Gene Prospector, GLAD4U and ProphNet were used to make biological analysis. Results Disease-causing genes were directly obtained from the OMIM and Alzgene databases, and related genes were collected by 4 kinds of tools (select gene whose frequency was 3 or more). The data were shared and a list of 25 genes was gotten. These genes were CALHM1、 ABCA7、 A2M、 CLU、 SORL1、 HFE、 CD2AP、 APP、 ACE、 PICALM、 APOE、 NOS3、 MS4A6A、 PLD3、 CR1、 ADAM10、 MS4A4E、 BLMH、 PSEN1、 CD33、 PSEN2、 MPO、 APBB2、 BIN1 and PLAU. Conclusion CALHM1, ABCA7, A2M and CLU, etc., have a certain correlation with AD, which provide theoretical basis for further research of AD genics and clinical treatment.

Expression of hsa-miR-10 b in three cervical cancer cell lines and its target genes / 基础医学与临床

Objective To analyze the expression of hsa-miR-10b in three cervical cancer cell lines , and to find the target genes of hsa-miR-10b.Methods PCR was applied to measure expression levels of hsa-miR-10b in C-33A, HeLa and CaSki .The relative studies on hsa-miR-10b were retrieved from PubMed .The sequence and genome char-acteristics of hsa-miR-10b were analyzed on line by miRbase and NCBI .The target genes of hsa-miR-10b were searched by TargetScan , PicTar and miRanda , and then demonstrated by Gene Ontology and Pathway Enrichment analysis.Results Compared with C-33A, the expression of hsa-miR-10b significantly reduced in HeLa and Caski (P<0.01).Current studies showed that hsa-miR-10b was related with multiple tumorigenesis .hsa-miR-10b was lo-cated in human chromosome 2q31.1 and highly conserved among different species .The target genes were enriched in the biological processes of transcription , gene expression regulation , cell proliferation and etc .(P<0.05).Pathway analysis showed that these target genes were responsible for biochemical erents mediated by to the signaling pathways of cancer, cell cycle, ARF and etc.(P<0.05).Conclusions hsa-miR-10b may have extensive functions , and closely related with the occurrence and development in cervical cancer .Prediction of target genes provides a theoreti-cal basis for the further study .

Mining Alzheimer's Disease Susceptible Genes Based on Data Integration Strategy / 中国康复理论与实践

Objective To clarify the role of the known genes and new discovered genes, which were important to the pathogenesis of Al-zheimer's disease (AD), in order to provide targets for clinical prevention, diagnosis and treatment. Methods In order to predict AD suscepti-ble genes, the website databases (OMIM, AlzGene) and a variety of pathogenic gene prediction tools such as Endeavour, Gene Prospector, GLAD4U and ProphNet were used to make biological analysis. Results Disease-causing genes were directly obtained from the OMIM and Alzgene databases, and related genes were collected by 4 kinds of tools (select gene whose frequency was 3 or more). The data were shared and a list of 25 genes was gotten. These genes were CALHM1、ABCA7、A2M、CLU、SORL1、HFE、CD2AP、APP、ACE、PICALM、APOE、NOS3、MS4A6A、PLD3、CR1、ADAM10、MS4A4E、BLMH、PSEN1、CD33、PSEN2、MPO、APBB2、BIN1 and PLAU. Conclusion CALHM1, ABCA7, A2M and CLU, etc., have a certain correlation with AD, which provide theoretical basis for further research of AD genics and clinical treatment.

Data mining and influential analysis of gene expression data for plant resistance gene identification in tomato (Solanum lycopersicum)

Background Molecular mechanisms of plant-pathogen interactions have been studied thoroughly but much about them is still unknown. A better understanding of these mechanisms and the detection of new resistance genes can improve crop production and food supply. Extracting this knowledge from available genomic data is a challenging task. Results Here, we evaluate the usefulness of clustering, data-mining and regression to identify potential new resistance genes. Three types of analyses were conducted separately over two conditions, tomatoes inoculated with Phytophthora infestans and not inoculated tomatoes. Predictions for 10 new resistance genes obtained by all applied methods were selected as being the most reliable and are therefore reported as potential resistance genes. Conclusion Application of different statistical analyses to detect potential resistance genes reliably has shown to conduct interesting results that improve knowledge on molecular mechanisms of plant resistance to pathogens.

Automatic prediction of non-coding RNA genes in prokaryotes based on compositional statistics.

Although non-coding RNA (ncRNA) genes do not encode proteins, they play vital roles in cells by producing functionally important RNAs. In this paper, we present a novel method for predicting ncRNA genes based on compositional features extracted directly from gene sequences. Our method consists of two Support Vector Machine (SVM) models — Codon model which uses codon usage features derived from ncRNA genes and protein-coding genes and Kmer model which utilizes features of nucleotide and dinucleotide frequency extracted respectively from ncRNA genes and randomly chosen genome sequences. The 10-fold cross-validation accuracy for the two models is found to be 92% and 91%, respectively. Thus, we could make an automatic prediction of ncRNA genes in one genome without manual filtration of protein-coding genes. After applying our method in Sulfolobus solfataricus genome, 25 prediction results have been generated according to 25 cut-off pairs. We have also applied the approach in E. coli and found our results comparable to those of previous studies. In general, our method enables automatic identification of ncRNA genes in newly sequenced prokaryotic genomes. Datasets and program code used in this work are available at http://cobi.uestc.edu.cn/resource/SS_ncRNA/

ORF Miner: a Web-based ORF Search Tool

The primary clue for locating protein-coding regions is the open reading frame and the determination of ORFs (Open Reading Frames) is the first step toward the gene prediction, especially for prokaryotes. In this respect, we have developed a web-based ORF search tool called ORF Miner. The ORF Miner is a graphical analysis utility which determines all possible open reading frames of a selectable minimum size in an input sequence. This tool identifies all open reading frames using alternative genetic codes as well as the standard one and reports a list of ORFs with corresponding deduced amino acid sequences. The ORF Miner can be employed for sequence annotation and give a crucial clue to determination of actual protein-coding regions.

New Solutions of Translation Initiation Site Prediction for Prokaryotic Genomes / 生物化学与生物物理进展

Accurate prediction of the translation initiation site (TIS) is an important issue for prokaryotic genome annotation. However, it is still a challenge for the existing methods to predict the TIS in the genomes over a wide variety of GC content. Besides, the existing methods have not yet undergone a comprehensive evaluation, leaving prediction reliability as a largely open problem. A new algorithm MED-StartPlus, a tool that predicts TIS in prokaryotic genomes with a wide variety of GC content was presented. It makes several efforts to model the nucleotide composition bias, the regulatory motifs upstream of the TIS, the sequence patterns around the TIS, and the operon structure. Tests on hundreds of reliable data sets, with TISs confirmed by experiments or having annotated functions, show that the new method achieves a totally high accuracy of TIS prediction. Compared with existing TIS predictors, the method reports a totally higher performance, especially for genomes that are GC-rich or have complex initiation mechanisms. The potential application of the method to improve the TIS annotation deposited in the public database was also proposed.