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.

Development and Bias Assessment of a Method for Targeted Metagenomic Sequencing of Marine Cyanobacteria

“…We find comparable levels of GC bias by both methods. The latter is in accordance with recent findings where a transposon-based protocol can introduce some coverage and GC biases (23). The minimum amount of cells needed for metagenomic libraries can likely be reduced by a more rigorous DNA contamination removal of all reagents (16), but this was not necessary for our purpose as we can easily sort Ͼ10…”

“…In most cases, genome assembly (18)(19)(20) or assignment of metabolic function (21) is the primary goal. However, there are commonly several biases associated with genome amplification, including the evenness of genome coverage, fraction of the genome captured, and sequencing errors (22,23). In an effort to successfully sequence lower DNA input samples while avoiding the biases inherent to amplification, we conducted this study using a transposonbased genome amplification and library preparation protocol (i.e., Nextera) that does not require large quantities of input DNA.…”

Evaluation of Two Approaches for Assessing the Genetic Similarity of Virioplankton Populations as Defined by Genome Size

“…While signature gene analyses have been critical to investigations of virioplankton population ecology, other molecular genetic tools, such as pulsed-field gel electrophoresis (65), randomly amplified polymorphic DNA PCR (RAPD-PCR) fingerprinting (61), and most recently shotgun metagenomics (34), have also provided important advances in our understanding of the virioplankton. The critical distinction between these fingerprinting or random sequencing approaches and signature gene analyses is that they do not require a priori sequence information necessary for the design of a targeted PCR assay.…”

A novel approach for the assembly of complex genomic DNA cloned into bacterial artificial chromosome vectors: assembly and analysis of Triticum aestivum chromosome arm 7DS

“…In addition, although enzymatic protocols offer further advantages of being able to use low quantities of DNA as the starting material, such low quantities have been shown to skew the distribution of genomes represented in metagenomic samples (Marine et al, 2011). The Nextera and Nextera XT protocols resulted in uneven coverage across pooled BACs when compared to TruSeq.…”

“…Although the use of enzymes for DNA fragmentation is quicker, their use has been shown to result in GC biases resulting in uneven (non random) coverage of targeted genomic regions (Marine et al, 2011). In addition, although enzymatic protocols offer further advantages of being able to use low quantities of DNA as the starting material, such low quantities have been shown to skew the distribution of genomes represented in metagenomic samples (Marine et al, 2011).…”