Comparison of two next-generation sequencing technologies for resolving highly complex microbiota composition using tandem variable 16S rRNA gene regions - PubMed (original) (raw)
Comparative Study
Comparison of two next-generation sequencing technologies for resolving highly complex microbiota composition using tandem variable 16S rRNA gene regions
Marcus J Claesson et al. Nucleic Acids Res. 2010 Dec.
Abstract
High-throughput molecular technologies can profile microbial communities at high resolution even in complex environments like the intestinal microbiota. Recent improvements in next-generation sequencing technologies allow for even finer resolution. We compared phylogenetic profiling of both longer (454 Titanium) sequence reads with shorter, but more numerous, paired-end reads (Illumina). For both approaches, we targeted six tandem combinations of 16S rRNA gene variable regions, in microbial DNA extracted from a human faecal sample, in order to investigate their limitations and potentials. In silico evaluations predicted that the V3/V4 and V4/V5 regions would provide the highest classification accuracies for both technologies. However, experimental sequencing of the V3/V4 region revealed significant amplification bias compared to the other regions, emphasising the necessity for experimental validation of primer pairs. The latest developments of 454 and Illumina technologies offered higher resolution compared to their previous versions, and showed relative consistency with each other. However, the majority of the Illumina reads could not be classified down to genus level due to their shorter length and higher error rates beyond 60 nt. Nonetheless, with improved quality and longer reads, the far greater coverage of Illumina promises unparalleled insights into highly diverse and complex environments such as the human gut.
Figures
Figure 1.
Positions of primer sequences and tandem regions used in this work for 454 titanium and Illumina, mapped along 16S rRNA gene (co-ordinates based on the Escherichia coli 16S rRNA gene sequence). The arrows (∼100 bases) show approximately Illumina sequence read length.
Figure 2.
Error rates as function of read lengths (provided by Roche and Fasteris). Error rates beyond 100 bp for Kit v4 were obtained through extrapolation [f(x) = 0.0763e0.0408_x_].
Figure 3.
Proportion of full-length 16S rRNA and tandem regions from simulated Titanium and Illumina reads, accurately classified at five taxonomic levels. Sequencing errors were also introduced using error rates above (dashed lines: KIT-v4; dotted lines: KIT-v3).
Figure 4.
Rarefaction curves for Titanium and Illumina reads at the 97% similarity phylotype level. Dashed lines are for 8277 randomly sub-sampled Titanium reads, equal in size to the smallest Titanium amplicon dataset. Illumina rarefaction curves were calculated from random sub-samplings of 229 048 reads, equal in size to the region with fewest reads (the V3/V4 region). The inset shows rarefaction curves from randomly sub-sampled Illumina reads equal in numbers to the corresponding 454 regions. (A) Proportion of sequenced Titanium and Illumina reads that were classified at four taxonomic levels (B) Single V4 reads sequenced in our earlier study (5) were included for comparison.
Figure 5.
Resolution at genus level for Titanium and Illumina V4/V5 reads. Single V4 reads sequenced at two different depths in our earlier study (5) were included for comparison.
Figure 6.
Relative phylum and genus abundances for sequence reads from both sequencing technologies. Single V4 reads sequenced using non-Titanium pyrosequencing in our earlier study (5) were included for comparison.
Figure 7.
MEGAN comparison based on BLAST searches of all 454 Titanium reads (A) and a random subset of Illumina reads (B) against an rRNA-specific database.
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