Improving alignment accuracy on homopolymer regions for semiconductor-based sequencing technologies. (August 2016)

• Record Type: Journal Article
• Authors: Feng, Weixing; Zhao, Sen; Xue, Dingkai; Song, Fengfei; Li, Ziwei; Chen, Duojiao; He, Bo; Hao, Yangyang; Wang, Yadong; Liu, Yunlong
• Is Part Of: BMC genomics. Volume 17:Number 7(2016)
• Page Start: 87
• Page End: 93
• Publication Date: 2016-08
• Subjects: Homopolymer -- Ion Torrent/Proton -- Bayesian -- Alignment; Genomes -- Periodicals; Gene mapping -- Periodicals; Genomics -- Periodicals; Base Sequence -- Periodicals; Chromosome Mapping -- Periodicals; Genetic Techniques -- Periodicals; Sequence Analysis, DNA -- Periodicals; 572.8605
• DOI: 10.1186/s12864-016-2894-9
• Languages: English
• ISSNs: 1471-2164

Abstract

Abstract Background Ion Torrent and Ion Proton are semiconductor-based sequencing technologies that feature rapid sequencing speed and low upfront and operating costs, thanks to the avoidance of modified nucleotides and optical measurements. Despite of these advantages, however, Ion semiconductor sequencing technologies suffer much reduced sequencing accuracy at the genomic loci with homopolymer repeats of the same nucleotide. Such limitation significantly reduces its efficiency for the biological applications aiming at accurately identifying various genetic variants. Results In this study, we propose aBayesian inference-based method that takes the advantage of the signal distributions of the electrical voltages that are measured for all the homopolymers of a fixed length. By cross-referencing the length of homopolymers in the reference genome and the voltage signal distribution derived from the experiment, the proposed integrated model significantly improves the alignment accuracy around the homopolymer regions. Conclusions Besides improving alignment accuracy on homopolymer regions for semiconductor-based sequencing technologies with the proposed model, similar strategies can also be used on other high-throughput sequencing technologies that share similar limitations.