Computational evaluation of TIS annotation for prokaryotic genomes

doi:10.1186/1471-2105-9-160

CORC > 北京大学 > 工学院

	Computational evaluation of TIS annotation for prokaryotic genomes
	Hu, Gang-Qing ; Zheng, Xiaobin ; Ju, Li-Ning ; Zhu, Huaiqiu ; She, Zhen-Su
刊名	bmc bioinformatics
	2008
关键词	MICROBIAL GENOMES TRANSLATION INITIATION SEQUENCE DATABASE ESCHERICHIA-COLI BACTERIAL GENES PREDICTION ARCHAEA EVOLUTION SIGNALS STARTS
DOI	10.1186/1471-2105-9-160
英文摘要	Background: Accurate annotation of translation initiation sites (TISs) is essential for understanding the translation initiation mechanism. However, the reliability of TIS annotation in widely used databases such as RefSeq is uncertain due to the lack of experimental benchmarks. Results: Based on a homogeneity assumption that gene translation-related signals are uniformly distributed across a genome, we have established a computational method for a large-scale quantitative assessment of the reliability of TIS annotations for any prokaryotic genome. The method consists of modeling a positional weight matrix (PWM) of aligned sequences around predicted TISs in terms of a linear combination of three elementary PWMs, one for true TIS and the two others for false TISs. The three elementary PWMs are obtained using a reference set with highly reliable TIS predictions. A generalized least square estimator determines the weighting of the true TIS in the observed PWM, from which the accuracy of the prediction is derived. The validity of the method and the extent of the limitation of the assumptions are explicitly addressed by testing on experimentally verified TISs with variable accuracy of the reference sets. The method is applied to estimate the accuracy of TIS annotations that are provided on public databases such as RefSeq and ProTISA and by programs such as EasyGene, GeneMarkS, Glimmer 3 and TiCo. It is shown that RefSeq's TIS prediction is significantly less accurate than two recent predictors, Tico and ProTISA. With convincing proofs, we show two general preferential biases in the RefSeq annotation, i.e. over-annotating the longest open reading frame ( LORF) and under-annotating ATG start codon. Finally, we have established a new TIS database, SupTISA, based on the best prediction of all the predictors; SupTISA has achieved an average accuracy of 92% over all 532 complete genomes. Conclusion: Large-scale computational evaluation of TIS annotation has been achieved. A new TIS database much better than RefSeq has been constructed, and it provides a valuable resource for further TIS studies.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000256034400001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Biochemical Research Methods; Biotechnology & Applied Microbiology; Mathematical & Computational Biology; SCI(E); PubMed; 11; ARTICLE; 160; 9
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/154060]
专题	工学院
推荐引用方式 GB/T 7714	Hu, Gang-Qing,Zheng, Xiaobin,Ju, Li-Ning,et al. Computational evaluation of TIS annotation for prokaryotic genomes[J]. bmc bioinformatics,2008.
APA	Hu, Gang-Qing,Zheng, Xiaobin,Ju, Li-Ning,Zhu, Huaiqiu,&She, Zhen-Su.(2008).Computational evaluation of TIS annotation for prokaryotic genomes.bmc bioinformatics.
MLA	Hu, Gang-Qing,et al."Computational evaluation of TIS annotation for prokaryotic genomes".bmc bioinformatics (2008).