结合基因表达数据和ChIP-chip数据的酵母转录调控模块的识别

活细胞依赖其众多的转录调控模块来实现复杂的生物功能,识别转录调控模块对深入理解细胞的功能及其转录机制有着重要的意义。本文结合酵母基因表达数据和ChIP-chip数据,提出了一种转录调控模块识别算法。该算法通过采用不同的P值阈值分别得到了核心集和粗糙集,然后对核心集和粗糙集进行判别,最后对基因进行扩展之后得到基因转录调控模块。将该算法运用到两个酵母基因表达数据中,得到了一些具有显著生物学意义的基因转录调控模块。与其它算法相比,该算法不仅可以识别含有较多基因的转录调控模块,而且可以识别一些其它算法不能识别的基因转录调控模块。识别得到的基因转录调控模块有着不同的生物学功能,并且有助于进一步理解酵母的转录调控机制。     

Prediction of Associations between microRNAs and Gene Expression in Glioma Biology

Despite progress in the determination of miR interactions, their regulatory role in cancer is only beginning to be unraveled. Utilizing gene expression data from 27 glioblastoma samples we found that the mere knowledge of physical interactions between specific mRNAs and miRs can be used to determine associated regulatory interactions, allowing us to identify 626 associated interactions, involving 128 miRs that putatively modulate the expression of 246 mRNAs. Experimentally determining the expression of miRs, we found an over-representation of over(under)-expressed miRs with various predicted mRNA target sequences. Such significantly associated miRs that putatively bind over-expressed genes strongly tend to have binding sites nearby the 3'UTR of the corresponding mRNAs, suggesting that the presence of the miRs near the translation stop site may be a factor in their regulatory ability. Our analysis predicted a significant association between miR-128 and the protein kinase WEE1, which we subsequently validated experimentally by showing that the over-expression of the naturally under-expressed miR-128 in glioma cells resulted in the inhibition of WEE1 in glioblastoma cells.     

Identification of Prognostic Biomarkers by Combined mRNA and miRNA Expression Microarray Analysis in Pancreatic Cancer

Pancreatic cancer is the fourth leading cause for cancer-related death, and early diagnosis is one key to improve the survival rate of this disease. Molecular biomarkers are an important method for diagnostic use in pancreatic cancer. We used data from three mRNA microarray datasets and a microRNA dataset (GSE16515, GSE15471, GSE28735, and GSE41372) to identify potential key genes. Differentially expressed genes (DEGs) and microRNAs (DEMs) were identified. Functional, pathway enrichment, and protein-protein interaction analyses were performed on common DEGs across all datasets. The target genes of the DEMs were identified. DEMs targets that were also DEGs were further scrutinized using overall survival analysis. A total of 236 DEGs and 21 DEMs were identified. There were a total of four DEGs (ECT2, NR5A2, NRP2, and TGFBI), which were also predicted target genes of DEMs. Overall survival analysis showed that high expression levels of three of these genes (ECT2, NRP2, and TGFBI) were associated with poor overall survival for pancreatic cancer patients. The basic expression of DEGs in pancreas stood lower level in various organ tissues. The expression of ECT2 and NRP2 was higher in different pancreatic cancer cell lines than normal pancreas cell line. Knockout of ECT2 by Crispr Cas9 gene editing system decreased proliferation and migration ability in pancreatic cancer cell line MiaPaCa2. In conclusion, we think that data mining method can do well in biomarker screening, and ECT2 and NRP2 can play as potential biomarker or therapy target by Crispr Cas9 in pancreatic cancer.     

基因表达与mRNA结构的关系

基因的转录调控和转录后水平的调控在基因表达过程中起着重要作用。mRNA的结构与基因表达调控的关系非常密切。目前对于mRNA结构对表达的影响因素,主要集中于起始密码子和S-D序列的结构和间隔长度、基因和基因间的间隔区序列和长度,5’末端与3’末端非翻译区、多聚（A）尾、内含子序列对翻译起始效率、发夹结构对mRNA的稳定性的影响和mRNA翻译起始区等对基因表达影响。     

融合基因关系网和功能预测恶性胶质瘤基因方法研究

目的:建立挖掘恶性胶质瘤候选基因的方法并进行系统分析。方法:结合恶性胶质瘤已知通路内基因和发生点突变和拷贝数改变的基因构建扩展基因关系网络,计算并分别寻找在网络中度和中心性得分高,脆弱性为正数的节点(基因),将满足一种或多种测度并与已知恶性胶质瘤基因共功能的基因作为恶性胶质瘤候选基因。最后,通过文献验证方法评价多种测度预测恶性胶质瘤基因的效能。结果:融合基因功能后,利用基因在网络中的度和脆弱性可识别大部分恶性胶质瘤基因,但利用中心性预测的结果较差;当将三个测度融合后,效能并没比单独使用脆弱性高。结论:融合基因功能关系和网络脆弱性是预测恶性胶质瘤基因的最佳测度。     

Glioma IL13Rα2 Is Associated with Mesenchymal Signature Gene Expression and Poor Patient Prognosis

A major challenge for successful immunotherapy against glioma is the identification and characterization of validated targets. We have taken a bioinformatics approach towards understanding the biological context of IL-13 receptor α2 (IL13Rα2) expression in brain tumors, and its functional significance for patient survival. Querying multiple gene expression databases, we show that IL13Rα2 expression increases with glioma malignancy grade, and expression for high-grade tumors is bimodal, with approximately 58% of WHO grade IV gliomas over-expressing this receptor. By several measures, IL13Rα2 expression in patient samples and low-passage primary glioma lines most consistently correlates with the expression of signature genes defining mesenchymal subclass tumors and negatively correlates with proneural signature genes as defined by two studies. Positive associations were also noted with proliferative signature genes, whereas no consistent associations were found with either classical or neural signature genes. Probing the potential functional consequences of this mesenchymal association through IPA analysis suggests that IL13Rα2 expression is associated with activation of proinflammatory and immune pathways characteristic of mesenchymal subclass tumors. In addition, survival analyses indicate that IL13Rα2 over-expression is associated with poor patient prognosis, a single gene correlation ranking IL13Rα2 in the top ~1% of total gene expression probes with regard to survival association with WHO IV gliomas. This study better defines the functional consequences of IL13Rα2 expression by demonstrating association with mesenchymal signature gene expression and poor patient prognosis. It thus highlights the utility of IL13Rα2 as a therapeutic target, and helps define patient populations most likely to respond to immunotherapy in present and future clinical trials.     

综合ChIP-chip数据、基因敲除数据和表达谱数据重构基因调控网络

揭示生物体内在的调控机制是生物信息学的一项重要研究内容．各种高通量生物数据的涌现,为从基因组的尺度上重构基因调控网络提供了可能．由于单数据源仅能提供关于调控关系的片面信息且存在噪声,因此整合多种生物学数据的方法有望得到可靠性较高的调控网络．提出了一种综合ChIP-chip数据、knock out (敲除)数据和各种条件下的表达谱数据来推断调控关系的新方法．ChIP-chip数据和knock out 数据能分别提供转录因子和目标基因对关系的直接物理结合和功能关系的证据,这两类数据的整合有望获得较高的识别准确率．但这两类数据的重合性通常较低,基于共调控的基因通常具有较高的表达相似性这一假设,在一定程度上降低了这两类数据重合性较低所带来的影响．算法所识别的大部分调控关系都被YEASTRACT,高质量ChIP-chip数据和文献所验证,从而证明了该方法在调控关系的预测上具有较高的准确性．与其他方法的比较,也表明了该方法具有较高的预测性能．     

High-Throughput miRNA and mRNA Sequencing of Paired Colorectal Normal,Tumor and Metastasis Tissues and Bioinformatic Modeling of miRNA-1 Therapeutic Applications

MiRNAs are discussed as diagnostic and therapeutic molecules. However, effective miRNA drug treatments with miRNAs are, so far, hampered by the complexity of the miRNA networks. To identify potential miRNA drugs in colorectal cancer, we profiled miRNA and mRNA expression in matching normal, tumor and metastasis tissues of eight patients by Illumina sequencing. We validated six miRNAs in a large tissue screen containing 16 additional tumor entities and identified miRNA-1, miRNA-129, miRNA-497 and miRNA-215 as constantly de-regulated within the majority of cancers. Of these, we investigated miRNA-1 as representative in a systems-biology simulation of cellular cancer models implemented in PyBioS and assessed the effects of depletion as well as overexpression in terms of miRNA-1 as a potential treatment option. In this system, miRNA-1 treatment reverted the disease phenotype with different effectiveness among the patients. Scoring the gene expression changes obtained through mRNA-Seq from the same patients we show that the combination of deep sequencing and systems biological modeling can help to identify patient-specific responses to miRNA treatments. We present this data as guideline for future pre-clinical assessments of new and personalized therapeutic options.     

逆境胁迫诱导基因的结构、功能与表达调控

对有关逆境响应基因的最新进展作了一简要的综述.在逆境条件下,脱落酸(ABA)浓度增加,诱导许多新的基因表达及蛋白质合成.已克隆到几百种逆境响应基因,其中大多数可受外源ABA的诱导.对这些基因及蛋白质的功能已有所了解,认为它们可能与植物的抗逆能力有关.目前认为有多条信号传递途径参与胁迫信号的转导.     

Mining of Candidate Maize Genes for Nitrogen Use Efficiency by Integrating Gene Expression and QTL Data

Breeding maize varieties for high nitrogen (N) use efficiency (NUE) by marker-assisted selection using NUE quantitative trait locus (QTL) or by genetic transfer of NUE-associated genes is a viable approach for increasing grain yield in N-limited production areas. In this investigation, we evaluated a set of introgression line populations under N supply and N deficiency conditions. From 42 QTLs for grain yield and yield components, 23 were identified under N supply conditions and 33 from N limited conditions. Meta-analysis of published maize NUE QTLs revealed 37 “consensus” QTLs, of which, 18 was detected under low N conditions. In addition, 258 unique ESTs associated with low N stress response, N uptake, transport, and assimilation were aligned on the maize genome by in silico mapping. Integrating the EST map with the QTL map has resulted in the identification of candidate NUE-associated genes of the following functional categories: N uptake, transport, and assimilation; carbon (C) metabolism and assimilation; and cascades of stress response and signal transduction genes. Nine candidates that have been introgressed into Ye478 significantly altered grain yield/yield components. It is suggested that the dynamics of interactions between C and N metabolism are important for maize yield. A high NUE variety should have a highly efficient C assimilation per unit N and actively express CO₂ assimilation-related genes under N-limited conditions.     

麻疯树脂酶全长基因克隆、表达及其蛋白质结构预测

脂酶(Lipase, EC3.1.1.3)是普遍应用于皮革、饲料及生物柴油工业的工业酶制剂, 具有广泛的应用价值。目前对植物来源的脂酶研究较少。本研究用在生物柴油中具有应用前景的油料植物——麻疯树(Jatropha curcas)作为研究对象, 克隆了该物种的脂酶基因(JcLIP)。通过多序列比对并结合物种的亲缘关系设计了具有较高特异性的简并引物, 通过使用RT-PCR和RACE技术, 最终获得了麻疯树脂酶基因的全长序列并成功地在大肠杆菌中表达, 酶活测定结果表明, 麻疯树脂酶在大肠杆菌中表达在包涵体中, 但是能产生具有活力的蛋白质, 酶活约为0.8 U.mL-1。结构预测和比较表明, JcLIP蛋白质具有脂酶的结构核心和催化活性中心, 而在非核心区具有较毛霉脂酶更多的插入和随机卷曲, 这可能是决定二者之间酶活差异的重要原因。     

麻疯树脂酶全长基因克隆、表达及其蛋白质结构预测

脂酶(Lipase,EC3.1.1.3)是普遍应用于皮革、饲料及生物柴油工业的工业酶制剂,具有广泛的应用价值。目前对植物来源的脂酶研究较少。本研究用在生物柴油中具有应用前景的油料植物——麻疯树(Jatrophacurcas)作为研究对象,克隆了该物种的脂酶基因(JcLIP)。通过多序列比对并结合物种的亲缘关系设计了具有较高特异性的简并引物,通过使用RT-PCR和RACE技术,最终获得了麻疯树脂酶基因的全长序列并成功地在大肠杆菌中表达,酶活测定结果表明,麻疯树脂酶在大肠杆菌中表达在包涵体中,但是能产生具有活力的蛋白质,酶活约为0.8U.mL-1。结构预测和比较表明,JcLIP蛋白质具有脂酶的结构核心和催化活性中心,而在非核心区具有较毛霉脂酶更多的插入和随机卷曲,这可能是决定二者之间酶活差异的重要原因。     

Identification of Nisin-Producing Strains by Nisin-Controlled Gene Expression System

A specific method to identify nisin-producing strains was developed based on Nisin-Controlled gene Expression (NICE) vector pSec:Nuc. The plasmid pSec:Nuc was transformed into non-nisin-producing strain Lactococcus lactis NZ9000, a host commonly used for the NICE system. The generating strain L. lactis NZ9000/pSec:Nuc could sense extracellular inducer nisin and efficiently secrete a reporter protein Nuc, the staphylococcal nuclease (Nuc) into the medium. Instead of using purified nisin, the culture supernatants of nisin-producing strains were also used as inducers. Therefore, the NICE system could be used to identify nisin-producing strains. With this principle, 4 among 56 lactococci strains isolated from raw milk were identified as nisin producers. The results were further confirmed by polymerase chain reaction amplification with their genomic DNA as templates, and nucleotide sequencing revealed that three of them produced nisin A, and the others produced nisin Z. Those results made it possible to isolate and identify nisin-producing strains specifically and rapidly using NICE system.