地高辛标记的黄鳝F64基因cRNA探针的制备及其应用

以黄鳝F64基因序列为模板设计引物,扩增用于c RNA探针合成的模板,构建F64/p GM-T重组质粒并线性化,利用RNA聚合酶体外转录合成正、反义c RNA探针,并对其进行地高辛标记,利用原位杂交方法检测F64基因在黄鳝性腺发育过程中的表达变化情况。结果显示,正义探针未检测到阳性信号,反义探针检测到该基因在黄鳝性腺发育早期不表达,于V期性腺开始表达。研究结果表明,体外转录法可以有效合成c RNA探针,制备的c RNA探针可以准确检测F64基因的时空表达。     

多药耐药基因分型芯片的制备及优化

目的:建立多药耐药基因(mdr1)分型芯片,以检测患者的单核苷酸多态性(SNPs)。方法:设计并合成探针和引物,制备芯片;构建野生型和突变型质粒,以其为模板经PCR仪扩增后,与芯片上的探针杂交,并用扫描仪分析结果。结果:构建了野生型和突变型质粒,与芯片杂交能很好地区分基因型;优化了制备条件,建立了分型标准。结论:该基因芯片是一种快速特异的基因分型方法。     

利用基因芯片技术筛选HIV-1F亚型基因限制性显示探针

为筛选限制性显示技术制备的HIV 1F亚型基因探针 ,应用基因芯片打印仪将其有序地打印在玻片上制备基因芯片 .在随机引物延伸的过程中进行HIV样品的荧光标记 ,然后与芯片进行杂交 .杂交后清洗玻片并干燥 ,对芯片进行扫描 ,分析各探针的杂交信号 .从中筛选了 14个基因片段作为芯片下一步研究的探针 .实验证明 ,限制性显示技术是一种制备基因芯片探针的实用方法     

纯化探针降低基因芯片杂交结果的背景

研究探针的纯化对基因芯片杂交结果的影响。将乙醇沉淀的探针和用DNA纯化试剂盒纯化的探针分别与基因芯片交,在同等条件下进行杂交后清洗和芯片扫描检测。结果表明,纯化的探针与基因芯片杂交结果的背景低,而未纯化的探针背景强,阳性信号界限比较模糊。运用基因芯片进行基因表达谱研究,要求杂交检测的结果必须低背景。探针的纯化是影响芯片杂交结果的一个重要因素。     

针对多种强致病性病毒的基因芯片检测方法的建立

为了制备灵敏的可检测多种烈性病毒性病原体的基因芯片,本研究设计了针对21种烈性病毒性病原体的基因芯片检测探针,每种5条,长50 bp.并以甲病毒属的基孔肯亚病毒和黄病毒属的黄热病毒细胞培养物为检测模型,摸索了合适的病毒基因处理与扩增方法.将提取的病毒RNA先用DNase Ⅰ处理,以去除掉其中的DNA分子,然后利用病毒属特异性引物进行反转录,以引导病毒基因组的合成,从而尽可能地减少宿主细胞基因成分的干扰.进行随机PCR扩增后将扩增产物与基因芯片进行杂交,分别出现了4条基孔肯亚病毒探针信号和5条黄热病毒的探针信号,说明所设计的检测探针具有较好的特异性,可用于这2种病毒的特异性检测.这种病毒基因样品的处理和扩增方法也为此基因芯片的临床应用奠定了基础.     

表达序列标签及基因芯片技术在植物抗性基因研究中的应用

表达序列标签和基因芯片技术是基因组学研究的重要手段。表达序列标签是cDNA的3’或5’端的一段序列,通过表达序列标签可以寻找在某种胁迫条件下特异表达的基因并推测其可能的功能。基因芯片技术是指将大量基因探针分子固定于载体上并与标记的样品分子进行杂交,通过检测每个探针分子的杂交信号强度获取样品分子数量和序列信息,通过基因芯片技术,可以研究基因在不同的条件下的表达量,进而研究植物抗性机理。     

禽流感病毒分型基因芯片的研制

[目的]禽流感病毒是一种全球重要的人和动物呼吸道病病原,快速确定其不同亚型对于全球流感监测具有重要的意义.本研究意在研制一种可同时鉴定禽流感病毒所有亚型的方法.[方法]根据GenBank上已发表的禽流感病毒不同亚型(16个HA亚型和9个NA亚型)的基因序列,设计合成了25对特异性引物和1对通用引物,然后以各亚型病毒的参考株RNA作为模板,建立扩增不同亚型的多重RT-PCR方法.参考各亚型病毒靶cDNAs区域的保守序列设计了52条亚型特异的探针,进而利用扩增的各亚型病毒的靶cDNAs对其特异性进行评价.在此基础上,将设计好的探针点制到处理好的玻片上,制备了禽流感病毒分型鉴定基因芯片,结合所建立的扩增不同亚型的多重RT-PCR方法,开发了禽流感病毒亚型鉴定基因芯片试剂.利用收集自49个地区的2653份标本对其特异性和敏感性进行了初步评价.[结果]用于评价的各亚型参考毒株均出现良好的特异性杂交信号,检测的敏感度可达2.47 PFU/mL或2.5 ng靶DNA片段,而且与禽类常见的IBV、NDV等6种病毒均无交叉反应.[结论]证明该病毒分型基因芯片具有良好的特异性、敏感性.     

肝素对逆转录抑制作用的研究

目的:研究肝素在逆转录过程中的作用.方法:提取人肺胚胎二倍体细胞和肝素抗凝血中总RNA,经1%琼脂糖凝胶电泳鉴定RNA的质量好后,逆转录合成相应的cDNA,分别进行看家基因β-actin的聚合酶链反应(PCR),其产物用1%琼脂糖凝胶电泳检测;用基因芯片技术检测cDNA.将肝素抗凝血中提取的总RNA分为等量的两部分,分别用肝素酶或氯化锂处理RNA进行逆转录为cDNA和RNA合成cDNA后再用肝素酶或氯化锂处理,分别进行看家基因β-actin的聚合酶链反应(PCR),其产物用1%琼脂糖凝胶电泳检测;并用基因芯片技术检测氯化锂处理RNA后cDNA.结果:二倍体细胞来源的RNA为模板,能扩增出β-actin产物,并且在基因芯片上有杂交点.肝素抗凝血来源的RNA,在肝素酶或氯化锂作用后行逆转录者,能扩增到β-actin的目的片段,且基因芯片上有杂交点;而在未处理者不能扩增到目的片段,且基因芯片上无杂交点.结论:肝素是一种逆转录的抑制剂.对RNA逆转录cDNA过程有较强的抑制作用.     

基因芯片的制备方法

合成后点样的DNA微阵列分析cDNA微阵列和寡核苷酸芯片,点样方法主要是通过物理吸附或共价结合的方式将探针固定于载体上。本文归纳了近年来国内外文献报道的基因芯片的制备方法,展望了基因芯片的应用前景。     

乙型脑炎病毒可视化分型基因芯片的制备

目的:制备乙型脑炎病毒(JEV)可视化分型基因芯片。方法:根据JEV的基因组序列,应用生物学软件设计JEV分型引物及探针,制备其可视化分型基因芯片;用生物素标记的引物PCR扩增目的片段,并与固定于玻片上的探针杂交,加入链霉亲和素标记的纳米金,银增强实现可视化;进行特异性、灵敏性及重复性试验。结果:探针特异地与相应的标记目的基因片段杂交,并在芯片上呈现较强的阳性杂交信号;2号探针能特异性检出JEV,3、4号探针可分别对Ⅰ型和Ⅲ型JEV进行分型;芯片对JEV质粒检测的灵敏度达105拷贝/mL;以蓝耳病病毒等5种病毒为对照,芯片只对JEV响应,具有特异性;制备的基因芯片具有批间、批内重复性。结论:制备的基因芯片具有高特异性、灵敏性及重复性,可以快速、准确、高通量地对JEV进行可视化分型检测。     

SARS病毒再测序DNA微阵列的探针设计

探针设计是SARS病毒再测序DNA微阵列制作的关键步骤,为了保证探针的杂交条件尽可能一致,采用了作者提出的两种等长变覆盖的探针设计方法,即基于Tm距离的算法和遗传算法。针对SAILS病毒基因组中的两段特异序列设计了一组探针,并与等长移位法和变长变覆盖法的设计结果进行了比较。等长变覆盖法得到的探针集在探针长度一致的情况下,探针的Tm值有较小的标准差和变化范围。结果表明,等长变覆盖法得到的探针具有更好的杂交条件一致性。     

一种高密度基因芯片的优化方法

基因芯片 (ｇｅｎｅｃｈｉｐ) ,又称ＤＮＡ微阵列(ｍｉｃｒｏａｒｒａｙ) ,是分子生物学和微电子、微机械学科交叉的产物。基因芯片技术将生命科学研究中所涉及的许多不连续的分析过程 ,如探针制备、杂交反应和检测分析等 ,通过采用微电子、微机械等工艺集成到芯片中 ,使之连续化、集成化和微型化。这一技术的成熟和应用将在新世纪里给遗传研究、疾病诊断和治疗、新药发现和环境保护等生命科学相关领域带来一场革命。本文探讨高密度基因芯片的优化技术。1　高密度基因芯片高密度基因芯片是由大量ＤＮＡ或寡核苷酸探针密集排列所形成的探针阵…     

GenXHC: a probabilistic generative model for cross-hybridization compensation in high-density genome-wide microarray data

MOTIVATION: Microarray designs containing millions to hundreds of millions of probes that tile entire genomes are currently being released. Within the next 2 months, our group will release a microarray data set containing over 12,000,000 microarray measurements taken from 37 mouse tissues. A problem that will become increasingly significant in the upcoming era of genome-wide exon-tiling microarray experiments is the removal of cross-hybridization noise. We present a probabilistic generative model for cross-hybridization in microarray data and a corresponding variational learning method for cross-hybridization compensation, GenXHC, that reduces cross-hybridization noise by taking into account multiple sources for each mRNA expression level measurement, as well as prior knowledge of hybridization similarities between the nucleotide sequences of microarray probes and their target cDNAs. RESULTS: The algorithm is applied to a subset of an exon-resolution genome-wide Agilent microarray data set for chromosome 16 of Mus musculus and is found to produce statistically significant reductions in cross-hybridization noise. The denoised data is found to produce enrichment in multiple gene ontology-biological process (GO-BP) functional groups. The algorithm is found to outperform robust multi-array analysis, another method for cross-hybridization compensation.     

Fast large scale oligonucleotide selection using the longest common factor approach

We present a fast method that selects oligonucleotide probes (such as DNA 25-mers) for microarray experiments on a truly large scale. For example, reliable oligos for human genes can be found within four days, a speedup of one to two orders of magnitude compared to previous approaches. This speed is attained by using the longest common substring as a specificity measure for candidate oligos. We present a space- and time-efficient algorithm, based on a suffix array with additional information, to compute matching statistics (lengths of longest matches) between all candidate oligos and all remaining sequences. With the matching statistics available, we show how to incorporate constraints such as oligo length, melting temperature, and self-complementarity into the selection process at a postprocessing stage. As a result, we can now design custom oligos for any sequenced genome, just as the technology for on-site chip synthesis is becoming increasingly mature.     

细小病毒B19 Oligo探针设计

利用BLAST软件对细小病毒B19的序列进行序列比对,获得特异序列;利用生物学软件Oligo6.40设计特异性高、Tm值接近、长度均一的Oligo探针。结果获得了13条70bp的Oligo探针,用于芯片打印及细小病毒B19的检测。表明利用BLAST系统和生物学软件Oligo6.40设计细小病毒B19诊断芯片的探针是一种简便而有效的方法。     

Comprehensive aligned sequence construction for automated design of effective probes (CASCADE-P) using 16S rDNA

MOTIVATION: Prokaryotic organisms have been identified utilizing the sequence variation of the 16S rRNA gene. Variations steer the design of DNA probes for the detection of taxonomic groups or specific organisms. The long-term goal of our project is to create probe arrays capable of identifying 16S rDNA sequences in unknown samples. This necessitated the authentication, categorization and alignment of the >75 000 publicly available '16S' sequences. Preferably, the entire process should be computationally administrated so the aligned collection could periodically absorb 16S rDNA sequences from the public records. A complete multiple sequence alignment would provide a foundation for computational probe selection and facilitates microbial taxonomy and phylogeny. RESULTS: Here we report the alignment and similarity clustering of 62 662 16S rDNA sequences and an approach for designing effective probes for each cluster. A novel alignment compression algorithm, NAST (Nearest Alignment Space Termination), was designed to produce the uniform multiple sequence alignment referred to as the prokMSA. From the prokMSA, 9020 Operational Taxonomic Units (OTUs) were found based on transitive sequence similarities. An automated approach to probe design was straightforward using the prokMSA clustered into OTUs. As a test case, multiple probes were computationally picked for each of the 27 OTUs that were identified within the Staphylococcus Group. The probes were incorporated into a customized microarray and were able to correctly categorize Staphylococcus aureus and Bacillus anthracis into their correct OTUs. Although a successful probe picking strategy is outlined, the main focus of creating the prokMSA was to provide a comprehensive, categorized, updateable 16S rDNA collection useful as a foundation for any probe selection algorithm.     

The Effects of Face Masks on the Doctor-Patient Relationship in Orthopaedics

BackgroundSince the onset of the COVID-19 pandemic, the widespread use of face masks has grown exponentially. There is limited data highlighting the patient perception of face mask use during this pandemic, specifically in orthopaedic clinics. The purpose of this study was to determine the patient’s perception of the implementation of face masks in the orthopaedic clinic during a period of mask mandates and if this change impacted the success of their interactions with physicians. The secondary aim includes measures of patient satisfaction such as the ability to understand conversation and communicate effectively with the physician.MethodsParticipants were recruited on the day of their appointment at our institution’s orthopaedic clinic and provided with instructions via email. The online, anonymous survey included the CARE questionnaire - a tool to examine patient satisfaction by assessing perception of empathy and was conducted using Qualtrics.ResultsDoes patient preference to have their physician wear a face mask impact the success of their interactions with physicians? Overall, the use of face masks by physicians did not negatively impact patient encounters. CARE scores for patients who preferred masks (37.2) were similar to those who preferred their physician did not wear a mask (37.5). Is patient satisfaction affected by the use of face masks in the orthopaedic clinic? Patients who preferred that their doctor wear a face mask stated that it had no negative impact on the effect of communication or conversation with the physician. Other factors such as how well the patients knew the physician and patient gender had a greater impact on the CARE score than masks did.ConclusionOur study determined that the preference of face masks by patients does not impact the success of their interactions with physicians using the CARE score. The findings of this study are valuable in informing orthopaedic physicians about patient attitudes towards mask use and could influence decision making for not only the COVID-19 pandemic, but also future infectious outbreaks that may arise. Level of Evidence: III     

基于组合探针识别的大规模细菌分类16 S rRNA基因芯片设计

随着16 S rRNA序列资源的不断丰富,以及寡核苷酸微阵列基因芯片技术的不断进步,检测复杂微生物菌落中的微生物种群构成成为可能．现有的序列特异性探针设计算法缺乏足够的覆盖度、灵活性以及效率,不能满足大规模细菌检测基因芯片的设计要求．很多组特异性探针设计算法的思路多局限于针对某个目标序列组设计唯一的组特异性探针．在很多应用场合,设计单个探针检测组内所有目标序列的目标是很难达到的．因此,设计多个探针通过组合方式进行检测是很有必要的．每个探针能特异性地检测组内一部分目标序列,通过组合就能提高覆盖率．然而,在所有可能的探针组合中找到一个优化的探针组合是很耗时的．提出了一个可行的基于相对熵和遗传算法的组合探针设计算法．