Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, USA.
Nat Biotechnol. 2013 Jan;31(1):46-53. doi: 10.1038/nbt.2450. Epub 2012 Dec 9.
Differential analysis of gene and transcript expression using high-throughput RNA sequencing (RNA-seq) is complicated by several sources of measurement variability and poses numerous statistical challenges. We present Cuffdiff 2, an algorithm that estimates expression at transcript-level resolution and controls for variability evident across replicate libraries. Cuffdiff 2 robustly identifies differentially expressed transcripts and genes and reveals differential splicing and promoter-preference changes. We demonstrate the accuracy of our approach through differential analysis of lung fibroblasts in response to loss of the developmental transcription factor HOXA1, which we show is required for lung fibroblast and HeLa cell cycle progression. Loss of HOXA1 results in significant expression level changes in thousands of individual transcripts, along with isoform switching events in key regulators of the cell cycle. Cuffdiff 2 performs robust differential analysis in RNA-seq experiments at transcript resolution, revealing a layer of regulation not readily observable with other high-throughput technologies.
使用高通量 RNA 测序(RNA-seq)进行基因和转录本表达的差异分析受到多种测量变异源的影响,并带来了许多统计挑战。我们提出了 Cuffdiff 2,这是一种算法,可以在转录本分辨率上估计表达水平,并控制在重复文库中明显存在的变异性。Cuffdiff 2 可以稳健地识别差异表达的转录本和基因,并揭示差异剪接和启动子偏好变化。我们通过对发育转录因子 HOXA1 缺失的肺成纤维细胞的差异分析证明了我们方法的准确性,我们表明 HOXA1 缺失是肺成纤维细胞和 HeLa 细胞周期进展所必需的。HOXA1 的缺失导致数千个单独转录本的表达水平发生显著变化,同时细胞周期关键调节因子的同工型转换事件也发生了。Cuffdiff 2 在 RNA-seq 实验中以转录本分辨率进行稳健的差异分析,揭示了一层不易用其他高通量技术观察到的调控。