10.5061/DRYAD.B4D75M52
Yu, Douglas W.
Kunming Institute of Zoology
Ji, Yinqiu
Kunming Institute of Zoology
Emerson, Brent C.
Norwich Research Park
Wang, Xiaoyang
Kunming Institute of Zoology
Ye, Chengxi
Kunming Institute of Zoology
Yang, Chunyan
Kunming Institute of Zoology
Ding, Zhaoli
Institute of Zoology
Data from: Biodiversity soup: metabarcoding of arthropods for rapid
biodiversity assessment and biomonitoring
Dryad
dataset
2012
metagenetics
Metagenomics
OTU picking
Holocene
454 Genome Sequencer FLX System
2012-05-09T16:38:43Z
2012-05-09T16:38:43Z
en
https://doi.org/10.1111/j.2041-210X.2012.00198.x
43064975 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
1) Traditional biodiversity assessment is costly in time, money, and
taxonomic expertise. Moreover, data are frequently collected in ways (e.g.
visual bird lists) that are unsuitable for auditing by neutral parties,
which is necessary for dispute resolution. 2) We present protocols for the
extraction of ecological, taxonomic and phylogenetic information from bulk
samples of arthropods. The protocols combine mass trapping of arthropods,
mass-PCR amplification of the COI barcode gene, pyrosequencing, and
bioinformatic analysis, which together we call ‘metabarcoding.’ 3) We
construct seven communities of arthropods (mostly insects) and show that
it is possible to recover a substantial proportion of the original
taxonomic information. We further demonstrate, for the first time, that
metabarcoding allows for the precise estimation of pairwise community
dissimilarity (beta diversity) and within-community phylogenetic diversity
(alpha diversity), despite the inevitable loss of taxonomic information
inherent to metabarcoding. 4) Alpha and beta diversity metrics are the raw
materials of ecology and the environmental sciences, facilitating
assessment of the state of the environment with a broad and efficient
measure of biodiversity.
Sequences after initial processing in QIIME (seqs.fna, library 1)Raw
sequence data from the Roche 454 GS FLX sequencer, region 1
(split_library_output_1). These data are the output of the command:
split_libraries.py -m 454_Map.txt -f 1.TCA.454Reads.fna -q
1.TCA.454Reads.qual -o split_library_output_1/ -l 100 -L 700 -H 9 -M 2 -b
10seqs.fnaSequences after initial processing in QIIME (seqs.fna, library
2)Raw sequence data from the Roche 454 GS FLX sequencer, region 2
(split_library_output_2). These data are the output of the command:
split_libraries.py -m 454_Map.txt -f 2.TCA.454Reads.fna -q
2.TCA.454Reads.qual -o split_library_output_2/ -l 100 -L 700 -H 9 -M 2 -b
10 -n 55100seqs.fna
China
Yunnan province