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意蜂哺育蜂与采集蜂头部mRNAs与miRNAs表达谱Solexa测序比较分析及其调控网络研究

Integrating of Solexa High-abundance Mrnas and Mirnas in Apis Mellifera:Comparison between Nurses and Foragers to Identify Regulatory Network

【作者】 刘芳

【导师】 缪云根; 苏松坤;

【作者基本信息】 浙江大学 , 特种经济动物饲养, 2012, 博士

【摘要】 蜜蜂是社会性昆虫,是公认的研究复杂社会行为进化和分子神经机制的模式生物。蜜蜂有着复杂的行为活动,成年蜜蜂一般在羽化后的2-3周从事巢内工作,其中哺育幼虫的工蜂为哺育蜂,接下来的1-3周,大多数的蜜蜂则从事巢外工作,其中采集花粉花蜜的工蜂为采集蜂,蜜蜂这种从哺育到采集的行为转变与其日龄、生理、环境、脑部结构、基因表达及调控密切相关。本研究利用新一代高通量测序技术分别检测了意大利蜜蜂(Apis mellifera ligustica)哺育蜂和采集蜂头部mRNA和miRNA的表达情况,同时比较这两者之间表达差异的基因,以寻找与蜜蜂行为转变相关的重要基因。采用生物信息学方法,分析了差异显著性表达的miRNAs和mRNAs的调控网络关系。本研究的这些结果为更好地理解蜜蜂行为转变的重要基因及其表达调控提供重要线索。主要结果如下:1.哺育蜂与采集蜂头部mRNAs的Solexa高通量测序比对为寻找哺育蜂和采集蜂头部表达差异的基因,本研究采用了数字化表达谱技术,即利用新一代高通量测序技术Solexa/Illumina平台检测哺育蜂和采集蜂头部的基因表达。结果表明,在两种蜜蜂中都得到丰富标签序列,在哺育蜂和采集蜂中分别得到3422327和4286250个序列标签;通过与GenBank内已知基因的比对,发现其中分别有173532个(哺育蜂)和426047个(采集蜂)标签序列未能匹配;在哺育蜂和采集蜂中分别检测到6875和7508个已知基因,分别占总基因数的72.47%和79.14%;比较这两组蜜蜂的基因表达情况,其中表达量最高的10个基因中都包含多种王浆主蛋白基因、葡萄糖氧化酶基因和防卫素基因;差异分析筛选发现有1434个基因的表达是差异显著的,即基因在哺育蜂和采集蜂之间的表达量之比(采集蜂/哺育蜂)大于2,且False Discovery Rate (FDR)值小于0.001,其中1337在采集蜂中上调,97个基因下调。此外,通过Gene Ontology功能显著性富集分析和Pathway显著性富集分析,发现在显著差异的基因中,有415个基因是在属于GO cellular component分类,同时还发现这些显著差异基因参与了200个Kyoto Encyclopedia of Genes and Genomes (KEGG)通路,其中包括21条信号通路,而过氧化物酶体增殖物激活受体(PPAR)信号通路是富集强度最大的。2.哺育蜂与采集蜂头部microRNAs的Solexa高通量测序比对MicroRNAs是内源性的非编码小RNA,长度大约为22个核苷酸,这些小的miRNA通常靶向一个或者多个mRNA,通过在翻译水平的抑制或者裂解靶标mRNA来调控生物体基因的表达。本实验采用第二代高通量技术Illumina测序平台检测哺育蜂和采集蜂头部sRNAs,寻找与行为转变相关的miRNAs。结果表明,哺育蜂和采集蜂头部都含有丰富的小RNAs,而且那些小RNA的长度大多集中在22个核苷酸(nt)左右。结合高通量测序和生物信息学分析,本研究发现,哺育蜂和采集蜂中有9个表达差异显著的miRNAs,即P值小于0.01,同时这些基因在哺育蜂和采集蜂间的表达量相比倍数大于或者等于2,其中部分miRNAs的目标基因与神经功能相关。本研究同时还在哺育蜂和采集蜂中发现了67个新的miRNAs。其中16个miRNAs通过茎环RT-PCR得到进一步的验证。通过荧光定量PCR验证了ame-miR-31a和ame-miR-13b的显著差异性,证明了高通量测序的可靠性及可行性。这些研究结果为了解蜜蜂中的miRNAs提供新的信息,同时为更好理解miRNAs在蜜蜂发育过程中的调控功能提供帮助。3.哺育蜂和采集蜂头部mRNA和miRNA调控网络分析通过miranda v3.3a软件预测哺育蜂和采集蜂中显著性差异表达的9个miRNAs的靶基因,发现几乎每个miRNA都对应众多的靶基因。结合差异表达mRNA与miRNA进行整合分析,通过Cytoscape2.8.2版软件构建miRNA和mRNA调控网络,结果显示miRNA的靶基因很丰富,同时有很多mRNA同时受多个miRNAs的调节。哺育蜂中4个上调的miRNAs,作用于37个下调基因和2个上调基因;下调的5个miRNAs作用的表达差异性的靶基因有55个,其中只有2个是上调基因,其余都是下调基因。利用DAVID对差异表达miRNA调控的表达上调和上调的靶基因进行GO和Pathway分析。GO分析结果显示,受miRNA的所有表达差异显著性的基因中,只有7个有GO分类,并且都属于GO分类中的cellular component,即Cytoplasm和Cytoplasmic part。Pathway分析结果显示,受miRNAs调控的表达下调的90个靶基因中,有28个属于45个pathway分类,而表达下调的靶基因,则只有2个属于两个pathway。

【Abstract】 Honeybee (Apis mellifera), an ensocial insect, is universally acknowledged to be a good model for studying the evolution and mechanism of complex social behavior. Generally, adult honeybees take care of larvae and queen during2-3weeks after emergence, while they start to forage for honey or pollen during the following1-3weeks. In this study, the next generation sequencing technology was applied to detect the mRNAs and sRNAs of honeybee’s head. Many differentially expressed genes were obtained, which could be associated with the behaviorral transition of honeybee. The regulatory network of miRNA and mRNA were also analyzed. The main results were summarized as follows:1. High-abundance mRNAs in Apis mellifera:comparison between nurses and foragersA large volume of honey bee (Aips mellifera) tag-seq was obtained to identify the differential gene expression via Solexa/Illumina Digital Gene Expression tag profiling (DGE) based on next generation sequencing. In total,3422327(nurses) and4286250(foragers) clean tags were sequenced,173532(nurses) and426047(foragers) total clean tags could not be match to the reference database, and7508and6875mapped genes were detected in foragers and nurses, showing72.47%and79.14%of total reference gene number respectively. The top ten high expression genes includes several major royal jelly proteins, glucose oxidase and defensin.1434genes were considered having significantly different expression, that is, showing an expression ratio (foragers/nurses) of more than2and FDR of less than0.001,1337genes were up-regulated in foragers, and97genes were down-regulated in foragers. Furthermore, we performed the Gene Ontology (GO) category and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis,415genes with annotation terms were linked to the GO cellular component category.200KEGG pathways were obtained, including21signaling pathways. The PPAR signaling pathway was the most highly enriched with the lowest Q-value. 2. High-abundance miRNAs in Apis mellifera:comparison between nurses and foragersMicroRNAs (miRNAs) are endogenous small (-22nt) non-coding RNAs regulating gene expression in animals and plants by targeting mRNAs for cleavage or translational repression. To find some differentially expressed miRNAs that may be associated with age-dependent behavioral changes in honeybees, we applied the next generation sequencing technology (Solexa) to detect small RNAs in nurses and foragers. Our results showed that both of the nurses and foragers had a complicated small RNA population, and that the length of small RNAs varied,22-nt being the predominant length. Combining deep sequencing and bioinformatics analysis, we discovered9known miRNAs were significantly different between nurses and foragers with a p-value less than0.01and the absolute value of fold-change more than1. Some of their target genes were related to neural function. Moreover,67novel miRNAs were identified in nurses and foragers, of which,16ones were confirmed by step-loop RT-PCR. Ame-miR-31a and ame-miR-13b were further validated using quantitative reverse transcription polymerase chain reaction assays. This study provides new information on the miRNA abundance of honeybees, helps us to understand the miRNA function in the regulation of honeybee development.3. Regulatory network analyses of miRNA and mRNA between nurses and foragersThe targets of9differentially expressed miRNAs between nurses and foragers were predicted by using Miranda v3.3a, all of the miRNAs target a lot of mRNA. Then integrated analysis of miRNA and mRNA was done by using Cytoscape2.8.2software combining differentially expressed mRNAs, four up-regulated miRNAs in nurses target37down-regulated genes and two up-regulated genes, while five down-regulated miRNAs target55genes, only2of these genes were up-regulated, others were down-regulated genes. Their potential ontology and pathway were analyzed by using the DAVID Bioinformatics Resources. Go analyses of target mRNAs revealed that only7mRNA belonging to cellular component which include Cytoplasm and Cytoplasmic part. Pathway analyses showed that28out of90down-regulated target mRNAs belonging to45Pathway categories, while2up-regulated target mRNAs belonging to2Pathway categories.

  • 【网络出版投稿人】 浙江大学
  • 【网络出版年期】2013年 08期
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