Comparison and calibration of transcriptome data from RNA-Seq and tiling arrays
-
Published:2010-06-17
Issue:1
Volume:11
Page:
-
ISSN:1471-2164
-
Container-title:BMC Genomics
-
language:en
-
Short-container-title:BMC Genomics
Author:
Agarwal Ashish,Koppstein David,Rozowsky Joel,Sboner Andrea,Habegger Lukas,Hillier LaDeana W,Sasidharan Rajkumar,Reinke Valerie,Waterston Robert H,Gerstein Mark
Abstract
Abstract
Background
Tiling arrays have been the tool of choice for probing an organism's transcriptome without prior assumptions about the transcribed regions, but RNA-Seq is becoming a viable alternative as the costs of sequencing continue to decrease. Understanding the relative merits of these technologies will help researchers select the appropriate technology for their needs.
Results
Here, we compare these two platforms using a matched sample of poly(A)-enriched RNA isolated from the second larval stage of C. elegans. We find that the raw signals from these two technologies are reasonably well correlated but that RNA-Seq outperforms tiling arrays in several respects, notably in exon boundary detection and dynamic range of expression. By exploring the accuracy of sequencing as a function of depth of coverage, we found that about 4 million reads are required to match the sensitivity of two tiling array replicates. The effects of cross-hybridization were analyzed using a "nearest neighbor" classifier applied to array probes; we describe a method for determining potential "black list" regions whose signals are unreliable. Finally, we propose a strategy for using RNA-Seq data as a gold standard set to calibrate tiling array data. All tiling array and RNA-Seq data sets have been submitted to the modENCODE Data Coordinating Center.
Conclusions
Tiling arrays effectively detect transcript expression levels at a low cost for many species while RNA-Seq provides greater accuracy in several regards. Researchers will need to carefully select the technology appropriate to the biological investigations they are undertaking. It will also be important to reconsider a comparison such as ours as sequencing technologies continue to evolve.
Publisher
Springer Science and Business Media LLC
Subject
Genetics,Biotechnology
Reference50 articles.
1. Kapranov P, Cawley SE, Drenkow J, Bekiranov S, Strausberg RL, Fodor SPA, Gingeras TR: Large-scale transcriptional activity in chromosomes 21 and 22. Science (New York, N.Y.). 2002, 296 (5569): 916-919. 2. Rinn JL, Euskirchen G, Bertone P, Martone R, Luscombe NM, Hartman S, Harrison PM, Nelson FK, Miller P, Gerstein M, Weissman S, Snyder M: The transcriptional activity of human Chromosome 22. Genes & Development. 2003, 17 (4): 529-540. 10.1101/gad.1055203. 3. Bertone P, Stolc V, Royce TE, Rozowsky JS, Urban AE, Zhu X, Rinn JL, Tongprasit W, Samanta M, Weissman S, Gerstein M, Snyder M: Global identification of human transcribed sequences with genome tiling arrays. Science. 2004, 306 (5705): 2242-6. 10.1126/science.1103388. 4. Manak JR, Dike S, Sementchenko V, Kapranov P, Biemar F, Long J, Cheng J, Bell I, Ghosh S, Piccolboni A, Gingeras TR: Biological function of unannotated transcription during the early development of Drosophila melanogaster. Nature Genetics. 2006, 38 (10): 1151-8. 10.1038/ng1875. 5. David L, Huber W, Granovskaia M, Toedling J, Palm CJ, Bofkin L, Jones T, Davis RW, Steinmetz LM: A high-resolution map of transcription in the yeast genome. Proceedings of the National Academy of Sciences PNAS. 2006, 103 (14): 5320-5325. 10.1073/pnas.0601091103.
Cited by
93 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|