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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
Published on: June 23, 2012
Whole-genome resequencing of 100 healthy individuals using DNA pooling
Xiaobin Wang1, Weiguo Sui2, Weiqing Wu3
1Health Management Centre, The Affiliated Guilin Hospital, Southern Medical University, Guilin, Guangxi 541000, P.R. China; Guangxi Key Laboratory of Metabolic Diseases Research, Guilin, Guangxi 541000, P.R. China.
Abstract:
With the advent of next-generation sequencing technology, the cost of sequencing has significantly decreased. However, sequencing costs remain high for large-scale studies. In the present study, DNA pooling was applied as a cost-effective strategy for sequencing. The sequencing results for 100 healthy individuals obtained via whole-genome resequencing and using DNA pooling are presented in the present study. In order to minimise the likelihood of systematic bias in sampling, paired-end libraries with an insert size of 500 bp were prepared for all samples and then subjected to whole-genome sequencing using four lanes for each library and resulting in at least a 30-fold haploid coverage for each sample. The NCBI human genome build37 (hg19) was used as a reference genome for the present study and the short reads were aligned to the reference genome achieving 99.84% coverage. In addition, the average sequencing depth was 32.76. In total, ~3 million single-nucleotide polymorphisms were identified, of which 99.88% were in the NCBI dbSNP database. Furthermore, ~600,000 small insertion/deletions, 500,000 structure variants, 5,000 copy number variations and 13,000 single nucleotide variants were identified. According to the present study, the whole genome has been sequenced for a small sample subjects from southern China for the first time. Furthermore, new variation sites were identified by comparing with the reference sequence, and new knowledge of the human genome variation was added to the human genomic databases. Furthermore, the particular distribution regions of variation were illustrated by analyzing various sites of variation, such as single-nucleotide polymorphisms.
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