LEADER 02348nam 2200409z- 450 001 9910220053503321 005 20210211 035 $a(CKB)3800000000216243 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/54590 035 $a(oapen)doab54590 035 $a(EXLCZ)993800000000216243 100 $a20202102d2016 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aNew Insights into Microbial Ecology through Subtle Nucleotide Variation 210 $cFrontiers Media SA$d2016 215 $a1 online resource (133 p.) 225 1 $aFrontiers Research Topics 311 08$a2-88919-988-6 330 $aThe 16S ribosomal RNA gene commonly serves as a molecular marker for investigating microbial community composition and structure. Vast amounts of 16S rRNA amplicon data generated from environmental samples thanks to the recent advances in sequencing technologies allowed microbial ecologists to explore microbial community dynamics over temporal and spatial scales deeper than ever before. However, widely used methods for the analysis of bacterial communities generally ignore subtle nucleotide variations among high-throughput sequencing reads and often fail to resolve ecologically meaningful differences between closely related organisms in complex microbial datasets. Lack of proper partitioning of the sequencing data into relevant units often masks important ecological patterns. Our research topic contains articles that use oligotyping to demonstrate the importantance of high-resolution analyses of marker gene data, and providides further evidence why microbial ecologists should open the "black box" of OTUs identified through arbitrary sequence similarity thresholds. 606 $aMicrobiology (non-medical)$2bicssc 610 $a16S rRNA gene 610 $ahigh-resolution 610 $amicrobiome 610 $aMinimum Entropy Decomposition 610 $aoligotyping 615 7$aMicrobiology (non-medical) 700 $aA. Murat Eren$4auth$01286185 702 $aMitchell Sogin$4auth 702 $aLois Maignien$4auth 906 $aBOOK 912 $a9910220053503321 996 $aNew Insights into Microbial Ecology through Subtle Nucleotide Variation$93019751 997 $aUNINA