Dataset Information

SMRT Sequencing for Parallel Analysis of Multiple Targets and Accurate SNP Phasing.

ABSTRACT: Single-molecule real-time (SMRT) sequencing generates much longer reads than other widely used next-generation (next-gen) sequencing methods, but its application to whole genome/exome analysis has been limited. Here, we describe the use of SMRT sequencing coupled with barcoding to simultaneously analyze one or a small number of genomic targets derived from multiple sources. In the budding yeast system, SMRT sequencing was used to analyze strand-exchange intermediates generated during mitotic recombination and to analyze genetic changes in a forward mutation assay. The general barcoding-SMRT approach was then extended to diffuse large B-cell lymphoma primary tumors and cell lines, where detected changes agreed with prior Illumina exome sequencing. A distinct advantage afforded by SMRT sequencing over other next-gen methods is that it immediately provides the linkage relationships between SNPs in the target segment sequenced. The strength of our approach for mutation/recombination studies (as well as linkage identification) derives from its inherent computational simplicity coupled with a lack of reliance on sophisticated statistical analyses.

SUBMITTER: Guo X

PROVIDER: S-EPMC4683651 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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SMRT Sequencing for Parallel Analysis of Multiple Targets and Accurate SNP Phasing.

Guo Xiaoge X Lehner Kevin K O'Connell Karen K Zhang Jenny J Dave Sandeep S SS Jinks-Robertson Sue S

G3 (Bethesda, Md.) 20151023 12

Single-molecule real-time (SMRT) sequencing generates much longer reads than other widely used next-generation (next-gen) sequencing methods, but its application to whole genome/exome analysis has been limited. Here, we describe the use of SMRT sequencing coupled with barcoding to simultaneously analyze one or a small number of genomic targets derived from multiple sources. In the budding yeast system, SMRT sequencing was used to analyze strand-exchange intermediates generated during mitotic rec ...[more]

PMID: 26497143

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Project description:BACKGROUND:Single nucleotide polymorphisms (SNPs) located within the human genome have been shown to have utility as markers of identity in the differentiation of DNA from individual contributors. Massively parallel DNA sequencing (MPS) technologies and human genome SNP databases allow for the design of suites of identity-linked target regions, amenable to sequencing in a multiplexed and massively parallel manner. Therefore, tools are needed for leveraging the genotypic information found within SNP databases for the discovery of genomic targets that can be evaluated on MPS platforms. RESULTS:The SNP island target identification algorithm (TIA) was developed as a user-tunable system to leverage SNP information within databases. Using data within the 1000 Genomes Project SNP database, human genome regions were identified that contain globally ubiquitous identity-linked SNPs and that were responsive to targeted resequencing on MPS platforms. Algorithmic filters were used to exclude target regions that did not conform to user-tunable SNP island target characteristics. To validate the accuracy of TIA for discovering these identity-linked SNP islands within the human genome, SNP island target regions were amplified from 70 contributor genomic DNA samples using the polymerase chain reaction. Multiplexed amplicons were sequenced using the Illumina MiSeq platform, and the resulting sequences were analyzed for SNP variations. 166 putative identity-linked SNPs were targeted in the identified genomic regions. Of the 309 SNPs that provided discerning power across individual SNP profiles, 74 previously undefined SNPs were identified during evaluation of targets from individual genomes. Overall, DNA samples of 70 individuals were uniquely identified using a subset of the suite of identity-linked SNP islands. CONCLUSIONS:TIA offers a tunable genome search tool for the discovery of targeted genomic regions that are scalable in the population frequency and numbers of SNPs contained within the SNP island regions. It also allows the definition of sequence length and sequence variability of the target region as well as the less variable flanking regions for tailoring to MPS platforms. As shown in this study, TIA can be used to discover identity-linked SNP islands within the human genome, useful for differentiating individuals by targeted resequencing on MPS technologies.

Project description:BACKGROUND:Although the Illumina 1 G Genome Analyzer generates billions of base pairs of sequence data, challenges arise in sequence selection due to the varying sequence quality. Therefore, in the framework of the International Porcine SNP Chip Consortium, this pilot study aimed to evaluate the impact of the quality level of the sequenced bases on mapping quality and identification of true SNPs on a large scale. RESULTS:DNA pooled from five animals from a commercial boar line was digested with DraI; 150-250-bp fragments were isolated and end-sequenced using the Illumina 1 G Genome Analyzer, yielding 70,348,064 sequences 36-bp long. Rules were developed to select sequences, which were then aligned to unique positions in a reference genome. Sequences were selected based on quality, and three thresholds of sequence quality (SQ) were compared. The highest threshold of SQ allowed identification of a larger number of SNPs (17,489), distributed widely across the pig genome. In total, 3,142 SNPs were validated with a success rate of 96%. The correlation between estimated minor allele frequency (MAF) and genotyped MAF was moderate, and SNPs were highly polymorphic in other pig breeds. Lowering the SQ threshold and maintaining the same criteria for SNP identification resulted in the discovery of fewer SNPs (16,768), of which 259 were not identified using higher SQ levels. Validation of SNPs found exclusively in the lower SQ threshold had a success rate of 94% and a low correlation between estimated MAF and genotyped MAF. Base change analysis suggested that the rate of transitions in the pig genome is likely to be similar to that observed in humans. Chromosome X showed reduced nucleotide diversity relative to autosomes, as observed for other species. CONCLUSION:Large numbers of SNPs can be identified reliably by creating strict rules for sequence selection, which simultaneously decreases sequence ambiguity. Selection of sequences using a higher SQ threshold leads to more reliable identification of SNPs. Lower SQ thresholds can be used to guarantee sufficient sequence coverage, resulting in high success rate but less reliable MAF estimation. Nucleotide diversity varies between porcine chromosomes, with the X chromosome showing less variation as observed in other species.

Dataset Information

SMRT Sequencing for Parallel Analysis of Multiple Targets and Accurate SNP Phasing.

Publications

SMRT Sequencing for Parallel Analysis of Multiple Targets and Accurate SNP Phasing.

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