Metagenomics: read length matters.
Obtaining an unbiased view of the phylogenetic composition and functional diversity within a microbial community is one central objective of metagenomic analysis. New technologies, such as 454 pyrosequencing, have dramatically reduced sequencing costs, to a level where metagenomic analysis may become a viable alternative to more-focused assessments of the phylogenetic (e.g., 16S rRNA genes) and functional diversity of microbial communities. To determine whether the short (approximately 100 to 200 bp) sequence reads obtained from pyrosequencing are appropriate for the phylogenetic and functional characterization of microbial communities, the results of BLAST and COG analyses were compared for long (approximately 750 bp) and randomly derived short reads from each of two microbial and one virioplankton metagenome libraries. Overall, BLASTX searches against the GenBank nr database found far fewer homologs within the short-sequence libraries. This was especially pronounced for a Chesapeake Bay virioplankton metagenome library. Increasing the short-read sampling depth or the length of derived short reads (up to 400 bp) did not completely resolve the discrepancy in BLASTX homolog detection. Only in cases where the long-read sequence had a close homolog (low BLAST E-score) did the derived short-read sequence also find a significant homolog. Thus, more-distant homologs of microbial and viral genes are not detected by short-read sequences. Among COG hits, derived short reads sampled at a depth of two short reads per long read missed up to 72% of the COG hits found using long reads. Noting the current limitation in computational approaches for the analysis of short sequences, the use of short-read-length libraries does not appear to be an appropriate tool for the metagenomic characterization of microbial communities.
Wommack
K Eric
KE
Delaware Biotechnology Institute, University of Delaware, 15 Innovation Way, Newark, Delaware 19711,USA.
Bhavsar
Jaysheel
J
Ravel
Jacques
J
D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D017753:Ecosystem; D015723:Gene Library; D005814:Genes, Viral / Q000235:genetics; D014644:Genetic Variation; D023281:Genomics / Q000379:methods / Q000639:trends*; D017422:Sequence Analysis, DNA / Q000379:methods*; D017385:Sequence Homology