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首页> 外文期刊>BMC Bioinformatics >Optimal cDNA microarray design using expressed sequence tags for organisms with limited genomic information
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Optimal cDNA microarray design using expressed sequence tags for organisms with limited genomic information

机译:使用表达的序列标签对基因组信息有限的生物进行最佳cDNA微阵列设计

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Background Expression microarrays are increasingly used to characterize environmental responses and host-parasite interactions for many different organisms. Probe selection for cDNA microarrays using expressed sequence tags (ESTs) is challenging due to high sequence redundancy and potential cross-hybridization between paralogous genes. In organisms with limited genomic information, like marine organisms, this challenge is even greater due to annotation uncertainty. No general tool is available for cDNA microarray probe selection for these organisms. Therefore, the goal of the design procedure described here is to select a subset of ESTs that will minimize sequence redundancy and characterize potential cross-hybridization while providing functionally representative probes. Results Sequence similarity between ESTs, quantified by the E-value of pair-wise alignment, was used as a surrogate for expected hybridization between corresponding sequences. Using this value as a measure of dissimilarity, sequence redundancy reduction was performed by hierarchical cluster analyses. The choice of how many microarray probes to retain was made based on an index developed for this research: a sequence diversity index (SDI) within a sequence diversity plot (SDP). This index tracked the decreasing within-cluster sequence diversity as the number of clusters increased. For a given stage in the agglomeration procedure, the EST having the highest similarity to all the other sequences within each cluster, the centroid EST, was selected as a microarray probe. A small dataset of ESTs from Atlantic white shrimp ( Litopenaeus setiferus ) was used to test this algorithm so that the detailed results could be examined. The functional representative level of the selected probes was quantified using Gene Ontology (GO) annotations. Conclusions For organisms with limited genomic information, combining hierarchical clustering methods to analyze ESTs can yield an optimal cDNA microarray design. If biomarker discovery is the goal of the microarray experiments, the average linkage method is more effective, while single linkage is more suitable if identification of physiological mechanisms is more of interest. This general design procedure is not limited to designing single-species cDNA microarrays for marine organisms, and it can equally be applied to multiple-species microarrays of any organisms with limited genomic information.
机译:背景表达微阵列越来越多地用于表征许多不同生物的环境响应和宿主-寄生虫相互作用。由于高序列冗余度和旁源基因之间潜在的交叉杂交,使用表达序列标签(EST)的cDNA微阵列探针选择具有挑战性。在基因组信息有限的生物(如海洋生物)中,由于注释的不确定性,这一挑战甚至更大。没有通用工具可用于选择这些生物的cDNA微阵列探针。因此,此处描述的设计程序的目标是选择一个EST子集,该子集将最大程度地减少序列冗余并表征潜在的交叉杂交,同时提供功能上具有代表性的探针。结果EST之间的序列相似性(通过成对比对的E值量化)被用作相应序列之间预期杂交的替代物。使用该值作为不相似性的度量,通过层次聚类分析执行了序列冗余减少。基于为这项研究开发的指标,选择保留多少微阵列探针:序列多样性图(SDP)中的序列多样性指数(SDI)。该索引跟踪随着簇数的增加而降低的簇内序列多样性。对于团聚过程中的给定阶段,选择与每个簇中所有其他序列具有最高相似性的EST(质心EST)作为微阵列探针。使用来自大西洋白虾(Litopenaeus setiferus)的少量EST数据集来测试该算法,以便可以检查详细结果。所选探针的功能代表水平使用基因本体论(GO)注释进行了量化。结论对于基因组信息有限的生物,结合层次聚类分析EST可以产生最佳的cDNA微阵列设计。如果发现生物标志物是微阵列实验的目标,则平均连锁方法会更有效,而单连锁则更适合于生理机制的识别。这种通用的设计过程不仅限于为海洋生物设计单物种cDNA微阵列,它同样可以应用于基因组信息有限的任何生物的多物种微阵列。

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