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      Evaluation of next generation sequencing platforms for population targeted sequencing studies

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          Abstract

          Human sequence generated from three next-generation sequencing platforms reveals systematic variability in sequence coverage due to local sequence characteristics.

          Abstract

          Background

          Next generation sequencing (NGS) platforms are currently being utilized for targeted sequencing of candidate genes or genomic intervals to perform sequence-based association studies. To evaluate these platforms for this application, we analyzed human sequence generated by the Roche 454, Illumina GA, and the ABI SOLiD technologies for the same 260 kb in four individuals.

          Results

          Local sequence characteristics contribute to systematic variability in sequence coverage (>100-fold difference in per-base coverage), resulting in patterns for each NGS technology that are highly correlated between samples. A comparison of the base calls to 88 kb of overlapping ABI 3730xL Sanger sequence generated for the same samples showed that the NGS platforms all have high sensitivity, identifying >95% of variant sites. At high coverage, depth base calling errors are systematic, resulting from local sequence contexts; as the coverage is lowered additional 'random sampling' errors in base calling occur.

          Conclusions

          Our study provides important insights into systematic biases and data variability that need to be considered when utilizing NGS platforms for population targeted sequencing studies.

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          Most cited references18

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          The complete genome of an individual by massively parallel DNA sequencing.

          The association of genetic variation with disease and drug response, and improvements in nucleic acid technologies, have given great optimism for the impact of 'genomic medicine'. However, the formidable size of the diploid human genome, approximately 6 gigabases, has prevented the routine application of sequencing methods to deciphering complete individual human genomes. To realize the full potential of genomics for human health, this limitation must be overcome. Here we report the DNA sequence of a diploid genome of a single individual, James D. Watson, sequenced to 7.4-fold redundancy in two months using massively parallel sequencing in picolitre-size reaction vessels. This sequence was completed in two months at approximately one-hundredth of the cost of traditional capillary electrophoresis methods. Comparison of the sequence to the reference genome led to the identification of 3.3 million single nucleotide polymorphisms, of which 10,654 cause amino-acid substitution within the coding sequence. In addition, we accurately identified small-scale (2-40,000 base pair (bp)) insertion and deletion polymorphism as well as copy number variation resulting in the large-scale gain and loss of chromosomal segments ranging from 26,000 to 1.5 million base pairs. Overall, these results agree well with recent results of sequencing of a single individual by traditional methods. However, in addition to being faster and significantly less expensive, this sequencing technology avoids the arbitrary loss of genomic sequences inherent in random shotgun sequencing by bacterial cloning because it amplifies DNA in a cell-free system. As a result, we further demonstrate the acquisition of novel human sequence, including novel genes not previously identified by traditional genomic sequencing. This is the first genome sequenced by next-generation technologies. Therefore it is a pilot for the future challenges of 'personalized genome sequencing'.
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            Repbase update: a database and an electronic journal of repetitive elements.

            J Jurka (2000)
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              Genome-wide in situ exon capture for selective resequencing.

              Increasingly powerful sequencing technologies are ushering in an era of personal genome sequences and raising the possibility of using such information to guide medical decisions. Genome resequencing also promises to accelerate the identification of disease-associated mutations. Roughly 98% of the human genome is composed of repeats and intergenic or non-protein-coding sequences. Thus, it is crucial to focus resequencing on high-value genomic regions. Protein-coding exons represent one such type of high-value target. We have developed a method of using flexible, high-density microarrays to capture any desired fraction of the human genome, in this case corresponding to more than 200,000 protein-coding exons. Depending on the precise protocol, up to 55-85% of the captured fragments are associated with targeted regions and up to 98% of intended exons can be recovered. This methodology provides an adaptable route toward rapid and efficient resequencing of any sizeable, non-repeat portion of the human genome.
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                Author and article information

                Journal
                Genome Biol
                Genome Biology
                BioMed Central
                1465-6906
                1465-6914
                2009
                27 March 2009
                : 10
                : 3
                : R32
                Affiliations
                [1 ]Scripps Genomic Medicine - Scripps Translational Science Institute - The Scripps Research Institute, N. Torrey Pines Court, La Jolla, CA 92037, USA
                [2 ]The J Craig Venter Institute, Medical Center Drive, Rockville, MD 20850, USA
                Article
                gb-2009-10-3-r32
                10.1186/gb-2009-10-3-r32
                2691003
                19327155
                44a117b1-adb7-4e34-adcc-384681b061c8
                Copyright © 2009 Harismendy et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 14 December 2008
                : 23 February 2009
                : 27 March 2009
                Categories
                Research

                Genetics
                Genetics

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