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Title: Evaluation of the reproducibility of amplicon sequencing with Illumina MiSeq platform

Abstract

Illumina's MiSeq has become the dominant platform for gene amplicon sequencing in microbial ecology studies; however, various technical concerns, such as reproducibility, still exist. To assess reproducibility, 16S rRNA gene amplicons from 18 soil samples of a reciprocal transplantation experiment were sequenced on an Illumina MiSeq. The V4 region of 16S rRNA gene from each sample was sequenced in triplicate with each replicate having a unique barcode. The average OTU overlap, without considering sequence abundance, at a rarefaction level of 10,323 sequences was 33.4±2.1% and 20.2±1.7% between two and among three technical replicates, respectively. When OTU sequence abundance was considered, the average sequence abundance weighted OTU overlap was 85.6±1.6% and 81.2±2.1% for two and three replicates, respectively. Removing singletons significantly increased the overlap for both (~1-3%, p<0.001). Increasing the sequencing depth to 160,000 reads by deep sequencing increased OTU overlap both when sequence abundance was considered (95%) and when not (44%). However, if singletons were not removed the overlap between two technical replicates (not considering sequence abundance) plateaus at 39% with 30,000 sequences. Diversity measures were not affected by the low overlap as α-diversities were similar among technical replicates while β-diversities (Bray-Curtis) were much smaller among technical replicates than amongmore » treatment replicates (e.g., 0.269 vs. 0.374). Higher diversity coverage, but lower OTU overlap, was observed when replicates were sequenced in separate runs. Detrended correspondence analysis indicated that while there was considerable variation among technical replicates, the reproducibility was sufficient for detecting treatment effects for the samples examined. These results suggest that although there is variation among technical replicates, amplicon sequencing on MiSeq is useful for analyzing microbial community structure if used appropriately and with caution. For example, including technical replicates, removing spurious sequences and unrepresentative OTUs, using a clustering method with a high stringency for OTU generation, estimating treatment effects at higher taxonomic levels, and adapting the unique molecular identifier (UMI) and other newly developed methods to lower PCR and sequencing error and to identify true low abundance rare species all can increase reproducibility.« less

Authors:
 [1]; ORCiD logo [2];  [2];  [2];  [2];  [3];  [2];  [2];  [4];  [3];  [5];  [6]
  1. Univ. of Oklahoma, Norman, OK (United States). Inst. for Environmental Genomics; Guangdong Ocean Univ. (China). Fisheries College
  2. Univ. of Oklahoma, Norman, OK (United States). Inst. for Environmental Genomics
  3. Chinese Academy of Sciences (CAS), Beijing (China). Inst. of Chemistry. Inst. of Soil Science
  4. Univ. of Oklahoma, Norman, OK (United States). Inst. for Environmental Genomics; Chinese Academy of Sciences (CAS), Beijing (China). Research Center for Eco-Environmental Sciences
  5. Univ. of Oklahoma, Norman, OK (United States). Inst. for Environmental Genomics; Tsinghua Univ., Beijing (China). School of Environment; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Earth Sciences Division
  6. Univ. of Illinois, Chicago, IL (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1353514
Alternate Identifier(s):
OSTI ID: 1379641
Grant/Contract Number:
AC02-05CH11231; SC0004601; SC0010715
Resource Type:
Journal Article: Published Article
Journal Name:
PLoS ONE
Additional Journal Information:
Journal Volume: 12; Journal Issue: 4; Journal ID: ISSN 1932-6203
Publisher:
Public Library of Science
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 60 APPLIED LIFE SCIENCES

Citation Formats

Wen, Chongqing, Wu, Liyou, Qin, Yujia, Van Nostrand, Joy D., Ning, Daliang, Sun, Bo, Xue, Kai, Liu, Feifei, Deng, Ye, Liang, Yuting, Zhou, Jizhong, and Green, Stefan J. Evaluation of the reproducibility of amplicon sequencing with Illumina MiSeq platform. United States: N. p., 2017. Web. doi:10.1371/journal.pone.0176716.
Wen, Chongqing, Wu, Liyou, Qin, Yujia, Van Nostrand, Joy D., Ning, Daliang, Sun, Bo, Xue, Kai, Liu, Feifei, Deng, Ye, Liang, Yuting, Zhou, Jizhong, & Green, Stefan J. Evaluation of the reproducibility of amplicon sequencing with Illumina MiSeq platform. United States. doi:10.1371/journal.pone.0176716.
Wen, Chongqing, Wu, Liyou, Qin, Yujia, Van Nostrand, Joy D., Ning, Daliang, Sun, Bo, Xue, Kai, Liu, Feifei, Deng, Ye, Liang, Yuting, Zhou, Jizhong, and Green, Stefan J. Fri . "Evaluation of the reproducibility of amplicon sequencing with Illumina MiSeq platform". United States. doi:10.1371/journal.pone.0176716.
@article{osti_1353514,
title = {Evaluation of the reproducibility of amplicon sequencing with Illumina MiSeq platform},
author = {Wen, Chongqing and Wu, Liyou and Qin, Yujia and Van Nostrand, Joy D. and Ning, Daliang and Sun, Bo and Xue, Kai and Liu, Feifei and Deng, Ye and Liang, Yuting and Zhou, Jizhong and Green, Stefan J.},
abstractNote = {Illumina's MiSeq has become the dominant platform for gene amplicon sequencing in microbial ecology studies; however, various technical concerns, such as reproducibility, still exist. To assess reproducibility, 16S rRNA gene amplicons from 18 soil samples of a reciprocal transplantation experiment were sequenced on an Illumina MiSeq. The V4 region of 16S rRNA gene from each sample was sequenced in triplicate with each replicate having a unique barcode. The average OTU overlap, without considering sequence abundance, at a rarefaction level of 10,323 sequences was 33.4±2.1% and 20.2±1.7% between two and among three technical replicates, respectively. When OTU sequence abundance was considered, the average sequence abundance weighted OTU overlap was 85.6±1.6% and 81.2±2.1% for two and three replicates, respectively. Removing singletons significantly increased the overlap for both (~1-3%, p<0.001). Increasing the sequencing depth to 160,000 reads by deep sequencing increased OTU overlap both when sequence abundance was considered (95%) and when not (44%). However, if singletons were not removed the overlap between two technical replicates (not considering sequence abundance) plateaus at 39% with 30,000 sequences. Diversity measures were not affected by the low overlap as α-diversities were similar among technical replicates while β-diversities (Bray-Curtis) were much smaller among technical replicates than among treatment replicates (e.g., 0.269 vs. 0.374). Higher diversity coverage, but lower OTU overlap, was observed when replicates were sequenced in separate runs. Detrended correspondence analysis indicated that while there was considerable variation among technical replicates, the reproducibility was sufficient for detecting treatment effects for the samples examined. These results suggest that although there is variation among technical replicates, amplicon sequencing on MiSeq is useful for analyzing microbial community structure if used appropriately and with caution. For example, including technical replicates, removing spurious sequences and unrepresentative OTUs, using a clustering method with a high stringency for OTU generation, estimating treatment effects at higher taxonomic levels, and adapting the unique molecular identifier (UMI) and other newly developed methods to lower PCR and sequencing error and to identify true low abundance rare species all can increase reproducibility.},
doi = {10.1371/journal.pone.0176716},
journal = {PLoS ONE},
number = 4,
volume = 12,
place = {United States},
year = {Fri Apr 28 00:00:00 EDT 2017},
month = {Fri Apr 28 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1371/journal.pone.0176716

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  • Illumina's MiSeq has become the dominant platform for gene amplicon sequencing in microbial ecology studies; however, various technical concerns, such as reproducibility, still exist. To assess reproducibility, 16S rRNA gene amplicons from 18 soil samples of a reciprocal transplantation experiment were sequenced on an Illumina MiSeq. The V4 region of 16S rRNA gene from each sample was sequenced in triplicate with each replicate having a unique barcode. The average OTU overlap, without considering sequence abundance, at a rarefaction level of 10,323 sequences was 33.4±2.1% and 20.2±1.7% between two and among three technical replicates, respectively. When OTU sequence abundance was considered,more » the average sequence abundance weighted OTU overlap was 85.6±1.6% and 81.2±2.1% for two and three replicates, respectively. Removing singletons significantly increased the overlap for both (~1-3%, p<0.001). Increasing the sequencing depth to 160,000 reads by deep sequencing increased OTU overlap both when sequence abundance was considered (95%) and when not (44%). However, if singletons were not removed the overlap between two technical replicates (not considering sequence abundance) plateaus at 39% with 30,000 sequences. Diversity measures were not affected by the low overlap as α-diversities were similar among technical replicates while β-diversities (Bray-Curtis) were much smaller among technical replicates than among treatment replicates (e.g., 0.269 vs. 0.374). Higher diversity coverage, but lower OTU overlap, was observed when replicates were sequenced in separate runs. Detrended correspondence analysis indicated that while there was considerable variation among technical replicates, the reproducibility was sufficient for detecting treatment effects for the samples examined. These results suggest that although there is variation among technical replicates, amplicon sequencing on MiSeq is useful for analyzing microbial community structure if used appropriately and with caution. For example, including technical replicates, removing spurious sequences and unrepresentative OTUs, using a clustering method with a high stringency for OTU generation, estimating treatment effects at higher taxonomic levels, and adapting the unique molecular identifier (UMI) and other newly developed methods to lower PCR and sequencing error and to identify true low abundance rare species all can increase reproducibility.« less
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