Systematic comparison of three genomic enrichment methods for massively parallel DNA sequencing

Abstract

Massively parallel DNA sequencing technologies have greatly increased our ability to generate large amounts of sequencing data at a rapid pace. Several methods have been developed to enrich for genomic regions of interest for targeted sequencing. We have compared three of these methods: Molecular Inversion Probes (MIP), Solution Hybrid Selection (SHS), and Microarray-based Genomic Selection (MGS). Using HapMap DNA samples, we compared each of these methods with respect to their ability to capture an identical set of exons and evolutionarily conserved regions associated with 528 genes (2.61 Mb). For sequence analysis, we developed and used a novel Bayesian genotype-assigning algorithm, Most Probable Genotype (MPG). All three capture methods were effective, but sensitivities (percentage of targeted bases associated with high-quality genotypes) varied for an equivalent amount of pass-filtered sequence: for example, 70% (MIP), 84% (SHS), and 91% (MGS) for 400 Mb. In contrast, all methods yielded similar accuracies of >99.84% when compared to Infinium 1M SNP BeadChip-derived genotypes and >99.998% when compared to 30-fold coverage whole-genome shotgun sequencing data. We also observed a low false-positive rate with all three methods; of the heterozygous positions identified by each of the capture methods, >99.57% agreed with 1M SNP BeadChip, and >98.840% agreed with the whole-genome shotgun data. In addition, we successfully piloted the genomic enrichment of a set of 12 pooled samples via the MGS method using molecular bar codes. We find that these three genomic enrichment methods are highly accurate and practical, with sensitivities comparable to that of 30-fold coverage whole-genome shotgun data.

Figure 1.

Three genomic enrichment methods. (A) (MIP) Molecular Inversion Probe: 70 base probes are prepared and hybridized to genomic DNA. Capture occurs by filling in sequence between the probe-targeting arms with polymerase and then sealing the circle with ligase. Total genomic DNA is removed with nucleases. The remaining closed circles undergo shotgun library and sequencing library preparation, followed by sequencing. (B) (SHS) Solution Hybrid Selection: A sequencing library is prepared from genomic DNA. This library is hybridized to biotinylated RNA probes in solution and recovered with streptavidin beads. Eluted products are amplified prior to cluster generation and sequencing. (C) (MGS) Microarray-based Genomic Selection: A sequencing library is prepared from genomic DNA and hybridized to a capture array. Eluted products are amplified prior to cluster generation and sequencing.

Figure 2.

Depth of coverage distribution. Distributions of depth of coverage at each ROI position. Scales have been standardized for comparison purposes, and maximum coverage depth values are indicated above the arrow. (A) (MIP) Molecular Inversion Probe. (B) (SHS) Solution Hybrid Selection. (C) (MGS) Microarray-based Genomic Selection.

Figure 3.

Genotype sensitivity across multiple samples. Boxplots showing distribution of genotype call sensitivities across multiple samples (extended sample set) for each capture method. (N) Number of samples.

Figure 4.

ROI regions with genotype assignments. The Venn diagram of overlapping genotype coverage is area proportional. Colored rectangles identify the proportion of genotype assignments in the ROI for each method: (red) MIP; (green) SHS; (blue) MGS. Note that the greatest overlap is among all three methods, and the second greatest is between SHS and MGS. The numbers sum to 95.35% because 4.65% of the ROI was not assigned a genotype in any method.

Figure 5.

Genotype sensitivity with increasing sequence data. Percentage of genotypes assigned in the ROI (same for all methods) with increasing filtered sequence data for NA18507 and NA12878. Sequence counts are based on 36 bases per read for MIP and SHS. To account for the 6-base index bar code, 42 bases were used in the sequence count calculations for MGS. The dashed arrow indicates genotype sensitivity level (67.3%) of 30-fold coverage whole-genome shotgun (WG) data for the ROI analyzed in this study.