Mu Wenbo, Zhang Wei
Department of Bioengineering, University of Illinois at Chicago Chicago, IL, USA.
Front Genet. 2012 Mar 5;3:31. doi: 10.3389/fgene.2012.00031. eCollection 2012.
Variation in quantitative gene expression has been observed in natural populations and associated with various complex traits/phenotypes such as risks for common diseases and drug response. MicroRNAs (miRNAs), a family of small, non-coding RNA molecules, have been demonstrated to be an important class of gene regulators that mostly downregulate gene expression at the post-transcriptional level. A comprehensive and reliable catalogue of miRNAs and miRNA gene targets is critical to understanding the gene regulatory networks. Though experimental approaches have been used to identify many miRNAs and their gene targets, due to cost and efficiency, currently miRNA and target identification still largely relies on computational algorithms. We reviewed several widely used bioinformatic resources of miRNA sequences and gene targets that take advantage of the unique characteristics of miRNA-mRNA interactions, experimental validation, as well as the integration of sequence-based evidence and microarray expression data. Furthermore, given the importance of miRNAs in regulating gene expression, elucidating expression quantitative trait loci involved with miRSNPs or miR-polymorphisms will help improve our understanding of complex traits. We reviewed the available resources of miRNA genetic variation, and the current progress (e.g., the 1000 Genomes Project) in detailing the genetic variation in miRNA-related single nucleotide polymorphisms (SNPs). We also provided our perspectives of the potential impact of next-generation sequencing on the research of miRNAs, gene targets, and miRSNPs. These bioinformatic resources may help interpret experimental and association study results, thus enhancing our knowledge of the dynamic gene regulatory networks and the physiological pathways for complex traits/phenotypes. Prospectively, these bioinformatic resources of miRNAs will need to address the challenges raised by the application of next-generation sequencing in miRNA research.
在自然种群中已观察到定量基因表达的变异，并且这种变异与各种复杂性状/表型相关，如常见疾病风险和药物反应。微小RNA（miRNA）是一类小的非编码RNA分子，已被证明是一类重要的基因调节因子，主要在转录后水平下调基因表达。全面且可靠的miRNA及其基因靶标的目录对于理解基因调控网络至关重要。尽管已采用实验方法来鉴定许多miRNA及其基因靶标，但由于成本和效率问题，目前miRNA及其靶标的鉴定在很大程度上仍依赖于计算算法。我们综述了几种广泛使用的miRNA序列和基因靶标的生物信息学资源，这些资源利用了miRNA与mRNA相互作用的独特特征、实验验证以及基于序列的证据和微阵列表达数据的整合。此外，鉴于miRNA在调节基因表达中的重要性，阐明与miRSNP或miR-多态性相关的表达数量性状位点将有助于增进我们对复杂性状的理解。我们综述了miRNA遗传变异的可用资源以及在详细描述miRNA相关单核苷酸多态性（SNP）的遗传变异方面的当前进展（例如千人基因组计划）。我们还就下一代测序对miRNA、基因靶标和miRSNP研究的潜在影响提出了我们的观点。这些生物信息学资源可能有助于解释实验和关联研究结果，从而增强我们对动态基因调控网络以及复杂性状/表型的生理途径的认识。前瞻性地看，这些miRNA的生物信息学资源将需要应对下一代测序在miRNA研究中的应用所带来的挑战。
