Linked Life Data

20880993

Source:http://linkedlifedata.com/resource/pubmed/id/20880993

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
22
pubmed:dateCreated
2010-12-14
pubmed:abstractText
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.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1362-4962
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
38
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
e200
pubmed:dateRevised
2011-8-24
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Comparison of two next-generation sequencing technologies for resolving highly complex microbiota composition using tandem variable 16S rRNA gene regions.
pubmed:affiliation
Department of Microbiology, University College Cork, Cork, Ireland. mclaesson@bioinfo.ucc.ie
pubmed:publicationType
Journal Article, Comparative Study, Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't, Evaluation Studies