A comparison of massively parallel nucleotide sequencing with oligonucleotide microarrays for global transcription profiling.
A comparison of massively parallel nucleotide sequencing with oligonucleotide microarrays for global transcription profiling.
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DOI：
10.1186/1471-2164-11-282
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发表时间：
2010-05-05
期刊：
影响因子：
4.4
通讯作者：
Miller CJ
中科院分区：
文献类型：
--
作者：
Bradford JR;Hey Y;Yates T;Li Y;Pepper SD;Miller CJ
RNA-Seq 利用大规模并行核苷酸测序快速生成千兆碱基的序列数据，从而可以对整个转录组进行绘图和数字量化。虽然之前的 RNA-Seq 和微阵列之间的比较是在基因表达水平上进行的，但在本研究中，我们采用了更细粒度的方法。使用来自正常人乳腺上皮细胞系 (MCF-10a) 和乳腺癌细胞系 (MCF-7) 的 RNA 样本，我们对 Applied Biosystems SOLiD 平台生成的 RNA-Seq 数据与来自 Affymetrix Exon 1.0ST 阵列的数据进行了全面比较。外显子阵列的使用使得评估 RNA-Seq 在两个关键领域的性能成为可能：检测单个外显子粒度的表达，以及发现注释基因座之外的转录。我们发现两个平台在外显子水平折叠变化和检测方面具有高度的对应性。例如，超过 80% 在 RNA-Seq 中检测到表达的外显子也在外显子阵列上检测到，并且在至少一个平台上标记为从不存在变为存在的外显子中有 91% 具有相同方向的倍数变化。当标记 SOLiD 数据中不存在的外显子的读数计数阈值设置为 t<1 时，可以看到最大的检测对应性，这表明 RNA-Seq 中的背景错误率极低。我们还发现 RNA-Seq 对检测差异表达的外显子比 Exon 阵列更敏感，反映出 SOLiD 平台可实现更宽的动态范围。此外，我们在已知外显子之外发现了新蛋白质编码区的重要证据，其中 93% 映射到外显子阵列探针组，并且能够通过检测先前未报道的外显子-外显子连接来推断数千个新转录本的存在。通过关注外显子水平的表达，我们提出了迄今为止 RNA-Seq 和微阵列之间最精细的比较。总体而言，我们的研究表明，SOLiD RNA-Seq 实验的数据足以产生与 Affymetrix Exon 阵列产生的结果相当的结果，即使仅使用每个平台的单个重复，并且当呈现大型基因组时。
RNA-Seq exploits the rapid generation of gigabases of sequence data by Massively Parallel Nucleotide Sequencing, allowing for the mapping and digital quantification of whole transcriptomes. Whilst previous comparisons between RNA-Seq and microarrays have been performed at the level of gene expression, in this study we adopt a more fine-grained approach. Using RNA samples from a normal human breast epithelial cell line (MCF-10a) and a breast cancer cell line (MCF-7), we present a comprehensive comparison between RNA-Seq data generated on the Applied Biosystems SOLiD platform and data from Affymetrix Exon 1.0ST arrays. The use of Exon arrays makes it possible to assess the performance of RNA-Seq in two key areas: detection of expression at the granularity of individual exons, and discovery of transcription outside annotated loci. We found a high degree of correspondence between the two platforms in terms of exon-level fold changes and detection. For example, over 80% of exons detected as expressed in RNA-Seq were also detected on the Exon array, and 91% of exons flagged as changing from Absent to Present on at least one platform had fold-changes in the same direction. The greatest detection correspondence was seen when the read count threshold at which to flag exons Absent in the SOLiD data was set to t<1 suggesting that the background error rate is extremely low in RNA-Seq. We also found RNA-Seq more sensitive to detecting differentially expressed exons than the Exon array, reflecting the wider dynamic range achievable on the SOLiD platform. In addition, we find significant evidence of novel protein coding regions outside known exons, 93% of which map to Exon array probesets, and are able to infer the presence of thousands of novel transcripts through the detection of previously unreported exon-exon junctions. By focusing on exon-level expression, we present the most fine-grained comparison between RNA-Seq and microarrays to date. Overall, our study demonstrates that data from a SOLiD RNA-Seq experiment are sufficient to generate results comparable to those produced from Affymetrix Exon arrays, even using only a single replicate from each platform, and when presented with a large genome.
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影响因子：
12.3
作者：
Gentleman RC;Carey VJ;Bates DM;Bolstad B;Dettling M;Dudoit S;Ellis B;Gautier L;Ge Y;Gentry J;Hornik K;Hothorn T;Huber W;Iacus S;Irizarry R;Leisch F;Li C;Maechler M;Rossini AJ;Sawitzki G;Smith C;Smyth G;Tierney L;Yang JY;Zhang J
通讯作者：
Zhang J
影响因子：
12.3
作者：
Denoeud F;Aury JM;Da Silva C;Noel B;Rogier O;Delledonne M;Morgante M;Valle G;Wincker P;Scarpelli C;Jaillon O;Artiguenave F
通讯作者：
Artiguenave F
影响因子：
48
作者：
Cloonan, Nicole;Forrest, Alistair R. R.;Grimmond, Sean M.
通讯作者：
Grimmond, Sean M.
影响因子：
46.9
作者：
Trapnell, Cole;Salzberg, Steven L.
通讯作者：
Salzberg, Steven L.
DOI：
10.1016/0005-2795(75)90109-9
发表时间：
1975-01-01
期刊：
BIOCHIMICA ET BIOPHYSICA ACTA
影响因子：
--
作者：
MATTHEWS, BW
通讯作者：
MATTHEWS, BW