RNA-Seq技术概述
RNA测序（RNA-Seq）技术能够快速分析并深入研究任何物种的转录组。与基因表达研究中常用的传统技术——芯片分析相比，该方法拥有许多优势。
RNA-Seq对比芯片技术的优势
无偏好的新型转录本检测:与芯片不同，RNA-Seq技术不需要物种或转录本特异性探针。该技术可检测新型转录本、基因融合、单核苷酸变异、插入缺失（小片段插入和缺失）以及之前采用芯片无法检测的其他未知变化。1,2
动态范围更宽:使用芯片杂交技术时，基因表达测定受到背景噪音（下限）和信号饱和（上限）的限制。RNA-Seq技术通过离散的定量以及数字化的read读数提供了更宽的动态范围。 (>105 for RNA-Seq vs. 103 for arrays).1,2,3
特异性和灵敏度更高:与芯片相比，RNA-Seq技术的特异性和灵敏度更高，从而全面提升对基因、转录本以及其他差异表达的检测。4-6
轻松检测稀有和低丰度转录本:轻松提高测序覆盖深度以检测稀有转录本、每个细胞的单一转录本或弱表达基因。
从芯片技术过渡到RNA-Seq
从测序服务提供商的角度了解芯片与RNA-Seq技术的详细比较结果。
“mRNA-Seq offers improved specificity, so it’s better at detecting transcripts, and specifically isoforms, than microarrays. It’s also more sensitive in detecting differential expression and offers increased dynamic range.”
Steve McPhail
President and Chief Executive Officer, Expression Analysis
用户友好的数据分析工具
在过去，对新一代测序（NGS）数据进行分析需要操作人员具备广泛的生物信息学专业知识，这是生物学家采用RNA测序技术的最大障碍。最新的用户友好型工具极大地简化了分析过程，可为所有研究人员提供便于使用的解决方案。
台式RNA-Seq技术
NextSeq 2000系统为RNA-Seq提供了可扩展的方法，灵敏度和准确性均优于传统芯片。
RNA-Seq Grants Outpace Array Grants
The portion of NIH grant funding allocated to new RNA sequencing vs. gene expression microarray-inclusive grants has been trending towards RNA-Seq technology for the last several years, and now constitutes the majority. Download our transcriptomics eBook to see the evidence.
Empowering Transcriptomics
This eBook discusses how NGS is advancing gene expression research, and includes a section on the advantages of RNA-Seq over arrays.
From Microarrays to RNA-Seq for Gene Expression Studies
Annika Sonntag, PhD and her team originally used microarrays to measure RNA expression, but needed to see exon-specific RNA expression as well. After comparing many technologies, they chose Illumina NGS for their gene expression studies.
Interested in receiving newsletters, case studies, and information from Illumina based on your area of interest? Sign up now.
References
- Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009;10:57–63.
- Wilhelm BT, Landry JR. RNA-Seq—quantitative measurement of expression through massively parallel RNA sequencing. Methods. 2009;48:249–57.
- Zhao S, Fung-Leung WP, Bittner A, and Ngo K, Liu X. Comparison of RNA-Seq and microarray in transcriptome profiling of activated T cells. PLoS One. 2014;16;9(1):e78644.
- Wang C, Gong B, Bushel PR, et al. The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance. Nat Biotechnol. 2014;32:926–932.
- Li J, Hou R, Niu X, et al. Comparison of microarray and RNA-Seq analysis of mRNA expression in dermal mesenchymal stem cells. Biotechnol Lett. 2016;38:33–41.
- Liu Y, Morley M, Brandimarto J, et al. RNA-Seq identifies novel myocardial gene expression signatures of heart failure. Genomics. 2015;105:83–89.