Multiplex target enrichment using DNA indexing for ultra-high throughput SNP detection

Area of Science:

• Genomics and Molecular Biology
• Next-Generation Sequencing Technologies

Background:

• Next-generation sequencing (NGS) is crucial for screening DNA samples for sequence variation.
• Existing methods lack efficiency in parallel target enrichment for large-scale studies.
• A need exists for streamlined, cost-effective methods for analyzing multiple DNA samples simultaneously.

Purpose of the Study:

• To develop and validate an advanced method for parallel DNA sample enrichment using indexing.
• To assess the accuracy and efficiency of this indexed approach for SNP identification.
• To demonstrate the utility of the method for analyzing sequence and structural variations in multiple samples.

Main Methods:

• Individual DNA samples were labeled with unique 6-bp indexes (barcodes).
• Indexed libraries were pooled in equal quantities, followed by a single in-solution target enrichment.
• Pooled samples were sequenced in a single reaction, with reads parsed by their index for individual analysis.

Main Results:

• Indexed sample preparation did not compromise the efficiency of the target enrichment process.
• High accuracy was achieved for SNP identification in HapMap DNA samples, with 99% concordance at 8x coverage.
• The method allows sequencing of hundreds of genes in tens of samples using minimal input DNA (1 μg/sample).

Conclusions:

• Indexed DNA sample pooling prior to target enrichment is an efficient strategy for large-scale sequencing studies.
• This method significantly enhances throughput and accuracy for SNP discovery and variation analysis.
• It offers a cost-effective solution for comprehensive genomic analysis across numerous samples.