Prediction of novel miRNAs and associated target genes in Glycine max.
Prediction of novel miRNAs and associated target genes in Glycine max.
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DOI：
10.1186/1471-2105-11-s1-s14
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发表时间：
2010-01-18
影响因子：
3
通讯作者：
Stacey G
中科院分区：
文献类型：
--
作者：
Joshi T;Yan Z;Libault M;Jeong DH;Park S;Green PJ;Sherrier DJ;Farmer A;May G;Meyers BC;Xu D;Stacey G
小的非编码rna（21 - 24个核苷酸）通过多种机制沉默基因来调节植物和动物的许多发育过程。其中，最保守的一类是microRNAs （miRNAs）和小干扰rna (sirna)，它们都是由被称为Dicers的类RNase iii酶产生的。许多植物mirna在营养平衡、发育过程、非生物胁迫和病原体反应中起着关键作用。目前，在大豆中仅鉴定出70种miRNA。我们利用Illumina的SBS测序技术从四种大豆（Glycine max）组织（包括根、种子、花和根瘤）中生成高质量的小RNA （sRNA）数据，以扩大目前已知的大豆mirna的收集。我们开发了一个生物信息学管道，使用内部脚本和公开可用的结构预测工具来区分真实的成熟miRNA序列与公共测序数据中代表的其他srna和短RNA片段。结合测序和生物信息学分析，根据预测前体的发夹二级结构特征鉴定出129个mirna。其中，42个mirna与大豆或其他物种中已知的mirna相匹配，同时鉴定出87个新的mirna。我们还使用计算方法预测了所有已鉴定的mirna的假定靶基因，并使用5' RACE方法验证了这些靶标子集的体内预测切割位点。最后，我们还通过对比Solexa cDNA测序数据，研究了miRNA丰度与各自靶基因丰度之间的关系。我们的研究显著增加了已知在大豆中表达的mirna的数量。生物信息学分析提供了mirna及其预测靶基因表达之间的调控模式的见解。我们还将数据存储在基于UCSC基因组浏览器架构的大豆基因组浏览器中。使用浏览器，我们用来自四个组织的miRNA序列和cDNA测序数据对大豆数据进行了注释。将这两个数据集叠加在浏览器中，研究人员可以分析相对于相关靶基因的miRNA表达水平。可以通过http://digbio.missouri.edu/soybean_mirna/访问该浏览器。
Small non-coding RNAs (21 to 24 nucleotides) regulate a number of developmental processes in plants and animals by silencing genes using multiple mechanisms. Among these, the most conserved classes are microRNAs (miRNAs) and small interfering RNAs (siRNAs), both of which are produced by RNase III-like enzymes called Dicers. Many plant miRNAs play critical roles in nutrient homeostasis, developmental processes, abiotic stress and pathogen responses. Currently, only 70 miRNA have been identified in soybean. We utilized Illumina's SBS sequencing technology to generate high-quality small RNA (sRNA) data from four soybean (Glycine max) tissues, including root, seed, flower, and nodules, to expand the collection of currently known soybean miRNAs. We developed a bioinformatics pipeline using in-house scripts and publicly available structure prediction tools to differentiate the authentic mature miRNA sequences from other sRNAs and short RNA fragments represented in the public sequencing data. The combined sequencing and bioinformatics analyses identified 129 miRNAs based on hairpin secondary structure features in the predicted precursors. Out of these, 42 miRNAs matched known miRNAs in soybean or other species, while 87 novel miRNAs were identified. We also predicted the putative target genes of all identified miRNAs with computational methods and verified the predicted cleavage sites in vivo for a subset of these targets using the 5' RACE method. Finally, we also studied the relationship between the abundance of miRNA and that of the respective target genes by comparison to Solexa cDNA sequencing data. Our study significantly increased the number of miRNAs known to be expressed in soybean. The bioinformatics analysis provided insight on regulation patterns between the miRNAs and their predicted target genes expression. We also deposited the data in a soybean genome browser based on the UCSC Genome Browser architecture. Using the browser, we annotated the soybean data with miRNA sequences from four tissues and cDNA sequencing data. Overlaying these two datasets in the browser allows researchers to analyze the miRNA expression levels relative to that of the associated target genes. The browser can be accessed at http://digbio.missouri.edu/soybean_mirna/.