Author:
Gilles André,Meglécz Emese,Pech Nicolas,Ferreira Stéphanie,Malausa Thibaut,Martin Jean-François
Abstract
Abstract
Background
The rapid evolution of 454 GS-FLX sequencing technology has not been accompanied by a reassessment of the quality and accuracy of the sequences obtained. Current strategies for decision-making and error-correction are based on an initial analysis by Huse et al. in 2007, for the older GS20 system based on experimental sequences. We analyze here the quality of 454 sequencing data and identify factors playing a role in sequencing error, through the use of an extensive dataset for Roche control DNA fragments.
Results
We obtained a mean error rate for 454 sequences of 1.07%. More importantly, the error rate is not randomly distributed; it occasionally rose to more than 50% in certain positions, and its distribution was linked to several experimental variables. The main factors related to error are the presence of homopolymers, position in the sequence, size of the sequence and spatial localization in PT plates for insertion and deletion errors. These factors can be described by considering seven variables. No single variable can account for the error rate distribution, but most of the variation is explained by the combination of all seven variables.
Conclusions
The pattern identified here calls for the use of internal controls and error-correcting base callers, to correct for errors, when available (e.g. when sequencing amplicons). For shotgun libraries, the use of both sequencing primers and deep coverage, combined with the use of random sequencing primer sites should partly compensate for even high error rates, although it may prove more difficult than previous thought to distinguish between low-frequency alleles and errors.
Publisher
Springer Science and Business Media LLC
Reference30 articles.
1. Zhou XG, Ren LF, Li YT, Zhang M, Yu YD, Yu J: The next-generation sequencing technology: A technology review and future perspective. Science China-Life Sciences. 53 (1): 44-57.
2. Reis-Filho JS: Next-generation sequencing. Breast Cancer Research. 2009, 11:
3. Lundin S, Stranneheim H, Pettersson E, Klevebring D, Lundeberg J: Increased Throughput by Parallelization of Library Preparation for Massive Sequencing. Plos One. 5 (3):
4. Metzker ML: Applications of next-generation sequencing. Sequencing technologies - the next generation. Nature Reviews Genetics. 11 (1): 31-46.
5. Hahn DA, Ragland GJ, Shoemaker DD, Denlinger DL: Gene discovery using massively parallel pyrosequencing to develop ESTs for the flesh fly Sarcophaga crassipalpis. Bmc Genomics. 2009, 10:
Cited by
317 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