共查询到20条相似文献，搜索用时 31 毫秒
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Binfeng Song Qian Zhang Zhaojun Zhang Yang Wan Qiong Jia Xiaomin Wang Xiaofan Zhu Anskar Yu-Hung Leung Tao Cheng Xiangdong Fang Weiping Yuan Haibo Jia 《BMC genomics》2014,15(1)
Background
Diamond–Blackfan anemia (DBA) is a class of human diseases linked to defective ribosome biogenesis that results in clinical phenotypes. Genetic mutations in ribosome protein (RP) genes lead to DBA phenotypes, including hematopoietic defects and physical deformities. However, little is known about the global regulatory network as well as key miRNAs and gene pathways in the zebrafish model of DBA.Results
In this study, we establish the DBA model in zebrafish using an RPS24 morpholino and found that RPS24 is required for both primitive hematopoiesis and definitive hematopoiesis processes that are partially mediated by the p53 pathway. Several deregulated genes and miRNAs were found to be related to hematopoiesis, vascular development and apoptosis in RPS24-deficient zebrafish via RNA-seq and miRNA-seq data analysis, and a comprehensive regulatory network was first constructed to identify the mechanisms of key miRNAs and gene pathways in the model. Interestingly, we found that the central node genes in the network were almost all targeted by significantly deregulated miRNAs. Furthermore, the enforced expression of miR-142-3p, a uniquely expressed miRNA, causes a significant decrease in primitive erythrocyte progenitor cells and HSCs.Conclusions
The present analyses demonstrate that the comprehensive regulatory network we constructed is useful for the functional prediction of new and important miRNAs in DBA and will provide insights into the pathogenesis of mutant rps24-mediated human DBA disease.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-759) contains supplementary material, which is available to authorized users. 相似文献4.
Background
MicroRNAs (miRNAs) are a class of endogenous small regulatory RNAs. Identifications of the dys-regulated or perturbed miRNAs and their key target genes are important for understanding the regulatory networks associated with the studied cellular processes. Several computational methods have been developed to infer the perturbed miRNA regulatory networks by integrating genome-wide gene expression data and sequence-based miRNA-target predictions. However, most of them only use the expression information of the miRNA direct targets, rarely considering the secondary effects of miRNA perturbation on the global gene regulatory networks.Results
We proposed a network propagation based method to infer the perturbed miRNAs and their key target genes by integrating gene expressions and global gene regulatory network information. The method used random walk with restart in gene regulatory networks to model the network effects of the miRNA perturbation. Then, it evaluated the significance of the correlation between the network effects of the miRNA perturbation and the gene differential expression levels with a forward searching strategy. Results show that our method outperformed several compared methods in rediscovering the experimentally perturbed miRNAs in cancer cell lines. Then, we applied it on a gene expression dataset of colorectal cancer clinical patient samples and inferred the perturbed miRNA regulatory networks of colorectal cancer, including several known oncogenic or tumor-suppressive miRNAs, such as miR-17, miR-26 and miR-145.Conclusions
Our network propagation based method takes advantage of the network effect of the miRNA perturbation on its target genes. It is a useful approach to infer the perturbed miRNAs and their key target genes associated with the studied biological processes using gene expression data.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2105-15-255) contains supplementary material, which is available to authorized users. 相似文献5.
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Background
Predictions of MHC binding affinity are commonly used in immunoinformatics for T cell epitope prediction. There are multiple available methods, some of which provide web access. However there is currently no convenient way to access the results from multiple methods at the same time or to execute predictions for an entire proteome at once.Results
We designed a web application that allows integration of multiple epitope prediction methods for any number of proteins in a genome. The tool is a front-end for various freely available methods. Features include visualisation of results from multiple predictors within proteins in one plot, genome-wide analysis and estimates of epitope conservation.Conclusions
We present a self contained web application, Epitopemap, for calculating and viewing epitope predictions with multiple methods. The tool is easy to use and will assist in computational screening of viral or bacterial genomes.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-015-0659-0) contains supplementary material, which is available to authorized users. 相似文献8.
Background
MicroRNAs (miRNAs) represent new and potentially informative diagnostic targets for disease detection and prognosis. However, little work exists documenting the effect of TRIzol, a common viral inactivation and nucleic acid extraction reagent, on miRNA purification. Here, we developed an optimized protocol for miRNA extraction from plasma samples by evaluating five different RNA extraction kits, TRIzol phase separation, purification additives, and initial plasma sample volume. This method was then used for downstream profiling of plasma miRNAs found in archived samples from one nonhuman primate (NHP) experimentally challenged with Ebola virus by the aerosol route.Results
Comparison of real-time RT-PCR results for spiked-in and endogenous miRNA sequences determined extraction efficiencies from five different RNA purification kits. These experiments showed that 50 μL plasma processed using the QIAGEN miRNeasy Mini Kit with 5 μg of glycogen as a co-precipitant yielded the highest recovery of endogenous miRNAs. Using this optimized protocol, miRNAs from archived plasma samples of one rhesus macaque challenged with aerosolized Ebola virus was profiled using a targeted real-time PCR array. A total of 519 of the 752 unique miRNAs assayed were present in the plasma samples at day 0 and day 7 (time of death) post-exposure. Statistical analyses revealed 25 sequences significantly up- or down-regulated between day 0 and day 7 post infection, validating the utility of the extraction method for plasma miRNA profiling.Conclusions
This study contributes to the knowledgebase of circulating miRNA extraction methods and expands on the potential applications of cell-free miRNA profiling for diagnostics and pathogenesis studies. Specifically, we optimized an extraction protocol for miRNAs from TRIzol-inactivated plasma samples that can be used for highly pathogenic viruses.Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-1299-5) contains supplementary material, which is available to authorized users. 相似文献9.
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Background
DAVID is the most popular tool for interpreting large lists of gene/proteins classically produced in high-throughput experiments. However, the use of DAVID website becomes difficult when analyzing multiple gene lists, for it does not provide an adequate visualization tool to show/compare multiple enrichment results in a concise and informative manner.Result
We implemented a new R-based graphical tool, BACA (Bubble chArt to Compare Annotations), which uses the DAVID web service for cross-comparing enrichment analysis results derived from multiple large gene lists. BACA is implemented in R and is freely available at the CRAN repository (http://cran.r-project.org/web/packages/BACA/).Conclusion
The package BACA allows R users to combine multiple annotation charts into one output graph by passing DAVID website.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-015-0477-4) contains supplementary material, which is available to authorized users. 相似文献12.
Jonah D. Hocum Logan R. Battrell Ryan Maynard Jennifer E. Adair Brian C. Beard David J. Rawlings Hans-Peter Kiem Daniel G. Miller Grant D. Trobridge 《BMC bioinformatics》2015,16(1)
Background
Analyzing the integration profile of retroviral vectors is a vital step in determining their potential genotoxic effects and developing safer vectors for therapeutic use. Identifying retroviral vector integration sites is also important for retroviral mutagenesis screens.Results
We developed VISA, a vector integration site analysis server, to analyze next-generation sequencing data for retroviral vector integration sites. Sequence reads that contain a provirus are mapped to the human genome, sequence reads that cannot be localized to a unique location in the genome are filtered out, and then unique retroviral vector integration sites are determined based on the alignment scores of the remaining sequence reads.Conclusions
VISA offers a simple web interface to upload sequence files and results are returned in a concise tabular format to allow rapid analysis of retroviral vector integration sites.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-015-0653-6) contains supplementary material, which is available to authorized users. 相似文献13.
Jisheng Li Yimei Cai Lupeng Ye Shaohua Wang Jiaqian Che Zhengying You Jun Yu Boxiong Zhong 《BMC genomics》2014,15(1)
Background
The growth and development of the posterior silk gland and the biosynthesis of the silk core protein at the fifth larval instar stage of Bombyx mori are of paramount importance for silk production.Results
Here, aided by next-generation sequencing and microarry assay, we profile 1,229 microRNAs (miRNAs), including 728 novel miRNAs and 110 miRNA/miRNA* duplexes, of the posterior silk gland at the fifth larval instar. Target gene prediction yields 14,222 unique target genes from 1,195 miRNAs. Functional categorization classifies the targets into complex pathways that include both cellular and metabolic processes, especially protein synthesis and processing.Conclusion
The enrichment of target genes in the ribosome-related pathway indicates that miRNAs may directly regulate translation. Our findings pave a way for further functional elucidation of these miRNAs and their targets in silk production.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-410) contains supplementary material, which is available to authorized users. 相似文献14.
Xiao-jun Li Lik Wee Lee Clive Hayward Mi-Youn Brusniak Pui-Yee Fong Matthew McLean JoAnne Mulligan Douglas Spicer Kenneth C Fang Stephen W Hunsucker Paul Kearney 《Clinical proteomics》2015,12(1)
Background
Current quantification methods for mass spectrometry (MS)-based proteomics either do not provide sufficient control of variability or are difficult to implement for routine clinical testing.Results
We present here an integrated quantification (InteQuan) method that better controls pre-analytical and analytical variability than the popular quantification method using stable isotope-labeled standard peptides (SISQuan). We quantified 16 lung cancer biomarker candidates in human plasma samples in three assessment studies, using immunoaffinity depletion coupled with multiple reaction monitoring (MRM) MS. InteQuan outperformed SISQuan in precision in all three studies and tolerated a two-fold difference in sample loading. The three studies lasted over six months and encountered major changes in experimental settings. Nevertheless, plasma proteins in low ng/ml to low μg/ml concentrations were measured with a median technical coefficient of variation (CV) of 11.9% using InteQuan. The corresponding median CV using SISQuan was 15.3% after linear fitting. Furthermore, InteQuan surpassed SISQuan in measuring biological difference among clinical samples and in distinguishing benign versus cancer plasma samples.Conclusions
We demonstrated that InteQuan is a simple yet robust quantification method for MS-based quantitative proteomics, especially for applications in biomarker research and in routine clinical testing.Electronic supplementary material
The online version of this article (doi:10.1186/1559-0275-12-3) contains supplementary material, which is available to authorized users. 相似文献15.
Background
Meta-analysis has become a popular approach for high-throughput genomic data analysis because it often can significantly increase power to detect biological signals or patterns in datasets. However, when using public-available databases for meta-analysis, duplication of samples is an often encountered problem, especially for gene expression data. Not removing duplicates could lead false positive finding, misleading clustering pattern or model over-fitting issue, etc in the subsequent data analysis.Results
We developed a Bioconductor package Dupchecker that efficiently identifies duplicated samples by generating MD5 fingerprints for raw data. A real data example was demonstrated to show the usage and output of the package.Conclusions
Researchers may not pay enough attention to checking and removing duplicated samples, and then data contamination could make the results or conclusions from meta-analysis questionable. We suggest applying DupChecker to examine all gene expression data sets before any data analysis step.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2105-15-323) contains supplementary material, which is available to authorized users. 相似文献16.
Botao Zhao Dehua Yang Jing Jiang Jinsong Li Chunsun Fan Menggui Huang Yi Fan Yan Jin Youxin Jin 《BMC genomics》2014,15(1)
Background
Reprogrammed cells, including induced pluripotent stem cells (iPSCs) and nuclear transfer embryonic stem cells (NT-ESCs), are similar in many respects to natural embryonic stem cells (ESCs). However, previous studies have demonstrated that iPSCs retain a gene expression signature that is unique from that of ESCs, including differences in microRNA (miRNA) expression, while NT-ESCs are more faithfully reprogrammed cells and have better developmental potential compared with iPSCs.Results
We focused on miRNA expression and explored the difference between ESCs and reprogrammed cells, especially ESCs and NT-ESCs. We also compared the distinct expression patterns among iPSCs, NT-ESCs and NT-iPSCs. The results demonstrated that reprogrammed cells (iPSCs and NT-ESCs) have unique miRNA expression patterns compared with ESCs. The comparison of differently reprogrammed cells (NT-ESCs, NT-iPSCs and iPSCs) suggests that several miRNAs have key roles in the distinct developmental potential of reprogrammed cells.Conclusions
Our data suggest that miRNAs play a part in the difference between ESCs and reprogrammed cells, as well as between MEFs and pluripotent cells. The variation of miRNA expression in reprogrammed cells derived using different reprogramming strategies suggests different characteristics induced by nuclear transfer and iPSC generation, as well as different developmental potential among NT-ESCs, iPSCs and NT-iPSCs.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-488) contains supplementary material, which is available to authorized users. 相似文献17.
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Background
Identification of tumor heterogeneity and genomic similarities across different cancer types is essential to the design of effective stratified treatments and for the discovery of treatments that can be extended to different types of tumors. However, systematic investigations on comprehensive molecular profiles have not been fully explored to achieve this goal.Results
Here, we performed a network-based integrative pan-cancer genomic analysis on >3000 samples from 12 cancer types to uncover novel stratifications among tumors. Our study not only revealed recurrently reported cross-cancer similarities, but also identified novel ones. The macro-scale stratification demonstrates strong clinical relevance and reveals consistent risk tendency among cancer types. The micro-scale stratification shows essential pan-cancer heterogeneity with subgroup-specific gene network characteristics and biological functions.Conclusions
In summary, our comprehensive network-based pan-cancer stratification provides valuable information about inter- and intra- cancer stratification for patient clinical assessments and therapeutic strategies.Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-1687-x) contains supplementary material, which is available to authorized users. 相似文献19.
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Mary F Lopez Bryan Krastins David A Sarracino Gregory Byram Maryann S Vogelsang Amol Prakash Scott Peterman Shadab Ahmad Gouri Vadali Wenjun Deng Ignacio Inglessis Tom Wickham Kathleen Feeney G William Dec Igor Palacios Ferdinando S Buonanno Eng H Lo MingMing Ning 《Clinical proteomics》2015,12(1)