Whole Genome Resequencing

Next-generation Sequencing

Service Overview

Whole genome resequencing, as the name indicates, is a scanning and sequencing of the whole genome, which enable revealing of both common and rare mutations on whole genome. It discovers various types of mutations including Single Nucleotide Polymorphisms (SNP), Insertion Deletion (InDel), Structure variation (SV) and Copy Number Variation(CNV).

Experimental Workflow

Experimental processes including sample quality control, library construction, library quality control and sequencing are processed following standard protocol provided by Illumina.
Figure 1. Experimental Workflow

Results Demo

Whole genome resequencing bioinformatics analysis
Genomewide Distribution of read coverage
Distribution of SNP mutation type
Genomewide distribution of mutations


1What's the applications of whole genome resequencing?
Whole genome resequencing has been widely employed in clinical studies, such as pathogenesis of genetic diseases, cancer molecular profiling, risk assessment of disease, etc.
2What's the advantages of whole genome resequencing compared to whole exon sequencing?
Whole genome resequencing is processed on the whole genome, including exons, introns, non-coding regions, intergenic regions, etc. It enables examinations not only on SNP, InDel but also structural mutations such as CNV and SV. Whole Exon sequencing (WES) targets on exons by pre-designed probes. Therefore, more than 50% of raw data is originated from exons, which lacking information of other regions. WES is mainly applied in the analysis of SNP and InDels.
3What's the difference between NGS resequencing and Third-generation sequencing (TGS)?
Whole genome resequencing is a sequencing strategy applied to individuals with known genome sequence. It is an effective method to analyse differences of an individual or a community. NGS based whole genome sequencing is a reliable method to discover SNP and InDels, however, not as reliable for SV discovery. Nanopore-based whole genome sequencing could generate reads with length of Mb, which achieves much higher resolution in SV identification and more accurate localization on reference genome. The number of identified SV could be ten times larger than that in NGS.