Veselenak Ronald L, Miller Aaron L, Milligan Gregg N, Bourne Nigel, Pyles Richard B
Department of Microbiology and Immunology, University of Texas Medical Branch, 301 University Blvd, Galveston, TX, 77555-0436, USA.
Mol Biotechnol. 2015 Feb;57(2):172-83. doi: 10.1007/s12033-014-9813-6.
Transcriptome analysis is a powerful tool for evaluating molecular pathways central to maturation of specific biological processes and disease states. Recently, PCR-based arrays have supplemented microarray and RNA-seq methodologies for studying changes in gene expression levels. PCR arrays are a more cost efficient alternative, however commercially available assemblies are generally limited to only a few more widely researched species (e.g., rat, human, and mouse). Consequently, the investigation of emerging or under-studied species is hindered until such assays are created. To address this need, we present data documenting the success of a developed workflow with enhanced potential to create and validate novel RT-PCR arrays for underrepresented species with whole or partial genome annotation. Utilizing this enhanced workflow, we have achieved a success rate of 80 % for first-round designs for over 400 primer pairs. Of these, ~160 distinct targets were sequence confirmed. Proof of concept studies using two unique arrays, one targeting the pathogenic bacterium Mycoplasma genitalium and the other specific for the guinea pig (Cavia porcellus), allowed us to identify significant (P < 0.05) changes in mRNA expression validated by subsequent qPCR. This flexible and adaptable platform provides a valuable and cost-effective alternative for gene expression analysis.
转录组分析是评估特定生物学过程和疾病状态成熟核心分子途径的有力工具。最近，基于PCR的芯片补充了用于研究基因表达水平变化的微阵列和RNA测序方法。PCR芯片是一种更具成本效益的替代方法，然而，市售的组件通常仅限于少数研究更广泛的物种（如大鼠、人类和小鼠）。因此，在创建此类检测方法之前，对新兴或研究不足的物种的研究受到阻碍。为满足这一需求，我们展示了数据，记录了一种开发的工作流程的成功，该流程具有增强的潜力，可为具有全基因组或部分基因组注释的代表性不足的物种创建和验证新型RT-PCR芯片。利用这种增强的工作流程，我们对400多个引物对的首轮设计成功率达到了80%。其中，约160个不同的靶标得到了序列确认。使用两个独特的芯片进行的概念验证研究，一个针对致病性细菌生殖支原体，另一个针对豚鼠（豚鼠），使我们能够识别出经后续qPCR验证的mRNA表达的显著（P < 0.05）变化。这个灵活且适应性强的平台为基因表达分析提供了一种有价值且具有成本效益的替代方法。
