Abstract
Contemporary genetic studies frequently involve sequencing of a targeted gene panel, for instance consisting of a set of genes associated with a specific disease. The NimbleGen SeqCap EZ Choice kit is commonly used for the targeted enrichment of sequencing libraries comprising a target size up to 7 Mb. A major drawback of this commercially available method is the exclusive use of single-indexing, meaning that at most 24 samples can be multiplexed in a single reaction. In case of relatively small target sizes, this will lead to excessive amounts of data per sample. We present an extended version of the NimbleGen SeqCap EZ protocol which allows to robustly multiplex up to 96 samples. We achieved this by incorporating Illumina dual-indexing based custom adapters into the original protocol. To further extend the optimization of cost-efficient sequencing of custom target panels, we studied the effect of higher pre-enrichment pooling factors and show that pre-enrichment pooling of up to 12 samples does not affect the quality of the data. To facilitate evaluation of capture efficiency in custom design panels, we also provide a detailed reporting tool.
Highlights
IntroductionOver the last years next-generation sequencing has been applied in many (human) genetics studies
Over the last years next-generation sequencing has been applied in many genetics studies
Many studies illustrated the importance of next-generation sequencing and especially wholeexome sequencing to identify causative mutations in genetic diseases [3, 24, 25]
Summary
Over the last years next-generation sequencing has been applied in many (human) genetics studies. Whole-exome sequencing is an effective technique to screen the great majority of the genes in the genome for the presence of sequence alterations in an unbiased fashion. It is predominantly used to identify causal genes for genetic disorders, including neurodevelopmental disorders such as intellectual disability and autism spectrum disorders [1,2,3]. For these purposes the advantages of an unbiased candidate gene discovery outweigh the disadvantages of incomplete coverage of the target region. When the objective is to screen a relatively limited set of known genes with absolute coverage for sequence abnormalities, such as required in routine diagnostics, targeted sequencing of a set of selected genes is more robust
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