Evaluation of a transposase protocol for rapid generation of shotgun high-throughput sequencing libraries from nanogram quantities of DNA

Abstract

Construction of DNA fragment libraries for next-generation sequencing can prove challenging, especially for samples with low DNA yield. Protocols devised to circumvent the problems associated with low starting quantities of DNA can result in amplification biases that skew the distribution of genomes in metagenomic data. Moreover, sample throughput can be slow, as current library construction techniques are time-consuming. This study evaluated Nextera, a new transposon-based method that is designed for quick production of DNA fragment libraries from a small quantity of DNA. The sequence read distribution across nine phage genomes in a mock viral assemblage met predictions for six of the least-abundant phages; however, the rank order of the most abundant phages differed slightly from predictions. De novo genome assemblies from Nextera libraries provided long contigs spanning over half of the phage genome; in four cases where full-length genome sequences were available for comparison, consensus sequences were found to match over 99% of the genome with near-perfect identity. Analysis of areas of low and high sequence coverage within phage genomes indicated that GC content may influence coverage of sequences from Nextera libraries. Comparisons of phage genomes prepared using both Nextera and a standard 454 FLX Titanium library preparation protocol suggested that the coverage biases according to GC content observed within the Nextera libraries were largely attributable to bias in the Nextera protocol rather than to the 454 sequencing technology. Nevertheless, given suitable sequence coverage, the Nextera protocol produced high-quality data for genomic studies. For metagenomics analyses, effects of GC amplification bias would need to be considered; however, the library preparation standardization that Nextera provides should benefit comparative metagenomic analyses.

Fig. 1.

Overview of sequencing strategies used to prepare viral genomic DNA samples for 454 sequencing.

Fig. 2.

Linear regression analysis of the percent GC content of the largest contig versus average read length for nine unknown genomes and the mock metagenome. The percent GC content for the mock metagenome represents the collective percent GC for all nine reference genomes.

Fig. 3.

Comparison of the predicted sequence coverage of each member of the mock metagenome to the experimental coverage (± SD). The predicted coverage was normalized to the experimental average read length and the number of sequence reads obtained after quality screening.

Fig. 4.

Box-and-whisker plots of the sequence coverage range as a function of phage genome GC content. Phage names are provided above each panel. (a) The Roche GS FLX Titanium general library preparation method. (b) The Nextera method with high-GC-content phage. (c) The Nextera method with low-GC-content phage. Whiskers represent the 5th and 95th percentiles; open diamonds represent mean values.

Fig. 5.

Average GC content (± SD) of regions with low or high coverage in comparisons of individual phage genomes. (a) Phage comprising the mock metagenome and unknown phage genomes prepared using the Nextera protocol. (b) Mycobacteriophage genomes prepared using the Roche GS FLX Titanium general library preparation method. Values in parentheses after the phage name indicate the average % GC content of the genome. Classification of the results into low- and high-coverage areas corresponded to the regions above or below 1.5 standard deviations from the average coverage. Genomes with at least 5 regions of low and high coverage of 50 bp or longer were included in the analysis.