Abstract
Next-generation sequencing (NGS) technologies, by sequencing hundreds of thousands to millions of DNA templates in parallel, resulted in higher throughput (Gb scale) and lowered sequencing cost (Mardis 2008; Shendure and Ji 2008). This has permitted the definition of entire genome as well as the differences that exist between them. The ultimate goal is to routinely perform whole-genome sequencing to allow us to gain a deeper understanding of genetic variation and to define its role in phenotypic variation and the pathogenesis of complex traits (Mamanova et al. 2010). Due to the cost and time limitations, it is not yet feasible to sequence large numbers of complex genomes. Therefore, a significant effort has focused on the development of “target enrichment” methods, in which genomic regions are selectively captured from a DNA sample before sequencing (Fig. 3.1). This approach is more time- and cost-effective, and the resulting data are considerably less cumbersome to analyze, except in the case of exome capture (Chap. 8). Several approaches to target enrichment have been developed, and the performance parameters vary from one to another: (1) sensitivity, or the percentage of the target bases that are represented by one or more sequence reads; (2) specificity, or the percentage of sequences that map to the intended targets; (3) uniformity, or the variability in sequence coverage across target regions; (4) reproducibility, or how closely results obtained from replicate experiments correlate; (5) cost; (6) ease of use; and (7) amount of DNA required per experiment, or per megabase of target (Mamanova et al. 2010).
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Valencia, C.A., Pervaiz, M.A., Husami, A., Qian, Y., Zhang, K. (2013). A Review of DNA Enrichment Technologies. In: Next Generation Sequencing Technologies in Medical Genetics. SpringerBriefs in Genetics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-9032-6_3
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