National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
BMC Genomics. 2014 Mar 14;15:198. doi: 10.1186/1471-2164-15-198.
Massively-parallel cDNA sequencing (RNA-Seq) is a new technique that holds great promise for cardiovascular genomics. Here, we used RNA-Seq to study the transcriptomes of matched coronary artery disease cases and controls in the ClinSeq® study, using cell lines as tissue surrogates.
Lymphoblastoid cell lines (LCLs) from 16 cases and controls representing phenotypic extremes for coronary calcification were cultured and analyzed using RNA-Seq. All cell lines were then independently re-cultured and along with another set of 16 independent cases and controls, were profiled with Affymetrix microarrays to perform a technical validation of the RNA-Seq results. Statistically significant changes (p < 0.05) were detected in 186 transcripts, many of which are expressed at extremely low levels (5-10 copies/cell), which we confirmed through a separate spike-in control RNA-Seq experiment. Next, by fitting a linear model to exon-level RNA-Seq read counts, we detected signals of alternative splicing in 18 transcripts. Finally, we used the RNA-Seq data to identify differential expression (p < 0.0001) in eight previously unannotated regions that may represent novel transcripts. Overall, differentially expressed genes showed strong enrichment (p = 0.0002) for prior association with cardiovascular disease. At the network level, we found evidence for perturbation in pathways involving both cardiovascular system development and function as well as lipid metabolism.
We present a pilot study for transcriptome involvement in coronary artery calcification and demonstrate how RNA-Seq analyses using LCLs as a tissue surrogate may yield fruitful results in a clinical sequencing project. In addition to canonical gene expression, we present candidate variants from alternative splicing and novel transcript detection, which have been unexplored in the context of this disease.
大规模平行 cDNA 测序（RNA-Seq）是一项具有广阔前景的心血管基因组学新技术。在这里，我们使用 RNA-Seq 研究了 ClinSeq®研究中匹配的冠心病病例和对照的转录组，使用细胞系作为组织替代物。
培养了来自 16 例病例和对照的淋巴母细胞系（LCL），这些病例和对照代表了冠状动脉钙化的表型极端，并用 RNA-Seq 进行了分析。然后，所有细胞系都被独立重新培养，并与另一组 16 例独立的病例和对照一起，用 Affymetrix 微阵列进行分析，以对 RNA-Seq 结果进行技术验证。在 186 个转录本中检测到了统计学上显著的变化（p < 0.05），其中许多转录本的表达水平极低（5-10 个拷贝/细胞），我们通过单独的 Spike-in 对照 RNA-Seq 实验证实了这一点。接下来，通过对外显子水平的 RNA-Seq 读计数进行线性模型拟合，我们在 18 个转录本中检测到了可变剪接的信号。最后，我们使用 RNA-Seq 数据来识别八个以前未注释的区域的差异表达（p < 0.0001），这些区域可能代表新的转录本。总的来说，差异表达的基因显示出与心血管疾病的强烈相关性（p = 0.0002）。在网络水平上，我们发现了涉及心血管系统发育和功能以及脂质代谢的途径受到干扰的证据。
我们提出了一个关于冠状动脉钙化中转录组参与的初步研究，并展示了如何使用 LCL 作为组织替代物进行 RNA-Seq 分析，这可能会在临床测序项目中产生有价值的结果。除了规范的基因表达外，我们还提出了来自可变剪接和新转录本检测的候选变体，这些在该疾病的背景下尚未得到探索。
