Comparing high throughput sequencing and real time qPCR for characterizing entomopathogenic nematode biogeography

Entomopathogenic nematodes (EPNs) are widely distributed in soils across all continents except Antarctica. Assessing the EPN community structure in an ecoregion can help reveal their biological control potential against important crop pests. Common methods for detecting EPNs in soil samples include...

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Published in:Soil Biology and Biochemistry
Main Authors: Dritsoulas, Alexandros, Campos-Herrera, R., Blanco-Pérez, Rubén, Duncan, L. W.
Other Authors: United States Agency for International Development, National Academy of Sciences (US), Science and Technology Development Fund (Egypt)
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2020
Subjects:
Online Access:http://hdl.handle.net/10261/223466
https://doi.org/10.1016/j.soilbio.2020.107793
https://doi.org/10.13039/100000209
https://doi.org/10.13039/501100003009
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spelling ftcsic:oai:digital.csic.es:10261/223466 2024-02-11T09:56:16+01:00 Comparing high throughput sequencing and real time qPCR for characterizing entomopathogenic nematode biogeography Dritsoulas, Alexandros Campos-Herrera, R. Blanco-Pérez, Rubén Duncan, L. W. United States Agency for International Development National Academy of Sciences (US) Science and Technology Development Fund (Egypt) Campos-Herrera, R. 2020-06 http://hdl.handle.net/10261/223466 https://doi.org/10.1016/j.soilbio.2020.107793 https://doi.org/10.13039/100000209 https://doi.org/10.13039/501100003009 en eng Elsevier Postprint http://dx.doi.org/10.1016/j.soilbio.2020.107793 Sí Soil Biology and Biochemistry 145: 107793 (2020) 0038-0717 http://hdl.handle.net/10261/223466 doi:10.1016/j.soilbio.2020.107793 http://dx.doi.org/10.13039/100000209 http://dx.doi.org/10.13039/501100003009 open Entomopathogenic nematodes Soil food webs qPCR Metabarcoding Species detection ITS1 artículo http://purl.org/coar/resource_type/c_6501 2020 ftcsic https://doi.org/10.1016/j.soilbio.2020.10779310.13039/10000020910.13039/501100003009 2024-01-16T10:59:42Z Entomopathogenic nematodes (EPNs) are widely distributed in soils across all continents except Antarctica. Assessing the EPN community structure in an ecoregion can help reveal their biological control potential against important crop pests. Common methods for detecting EPNs in soil samples include baiting with sentinel insects, direct observation of extracted nematodes, or use of species-specific primer-probe combinations using qPCR. Less well studied is the use of high throughput sequencing (HTS), which has tremendous potential to characterize soil communities of EPNs and natural enemies of EPNs. Here, for the first time, we compared qPCR and HTS to characterize EPN food webs. The frequency and abundance of 10 EPN species and 13 organisms associated with EPNs from 50 orchard and natural area sites in two ecoregions of Portugal were evaluated using qPCR tools, and results were published in 2019. We applied an HTS approach to analyze frozen DNA samples from 36 sites in that study. Universal primers targeting ITS1 were used for nematode detection. All EPN species detected by qPCR were also detected by HTS. The EPN species and nearly all free-living nematodes detected by both processes were highly correlated (P < 0.01). Steinernema feltiae, the dominant EPN species, was detected by HTS in 55% more sites than by qPCR. HTS also detected more EPN species than did qPCR. Sample accuracy, measured by the fit of Taylor's Power Law to data from each method, was significantly better using HTS (r = 0.95, P < 0.01) than qPCR (r = 0.76, P < 0.01). The effect of biotic and abiotic variables on individual EPN species did not differ according to ANOVA and multiple regression analyses of both data sets while the drivers of EPN community structure did not differ when analyzing either data set with CCA. Our results combined with decreasing costs of metabarcoding, suggest that HTS may provide the most cost-effective and accurate means of assessing soil food webs of methods currently available. This study was supported in ... Article in Journal/Newspaper Antarc* Antarctica Digital.CSIC (Spanish National Research Council) Soil Biology and Biochemistry 145 107793
institution Open Polar
collection Digital.CSIC (Spanish National Research Council)
op_collection_id ftcsic
language English
topic Entomopathogenic nematodes
Soil food webs
qPCR
Metabarcoding
Species detection
ITS1
spellingShingle Entomopathogenic nematodes
Soil food webs
qPCR
Metabarcoding
Species detection
ITS1
Dritsoulas, Alexandros
Campos-Herrera, R.
Blanco-Pérez, Rubén
Duncan, L. W.
Comparing high throughput sequencing and real time qPCR for characterizing entomopathogenic nematode biogeography
topic_facet Entomopathogenic nematodes
Soil food webs
qPCR
Metabarcoding
Species detection
ITS1
description Entomopathogenic nematodes (EPNs) are widely distributed in soils across all continents except Antarctica. Assessing the EPN community structure in an ecoregion can help reveal their biological control potential against important crop pests. Common methods for detecting EPNs in soil samples include baiting with sentinel insects, direct observation of extracted nematodes, or use of species-specific primer-probe combinations using qPCR. Less well studied is the use of high throughput sequencing (HTS), which has tremendous potential to characterize soil communities of EPNs and natural enemies of EPNs. Here, for the first time, we compared qPCR and HTS to characterize EPN food webs. The frequency and abundance of 10 EPN species and 13 organisms associated with EPNs from 50 orchard and natural area sites in two ecoregions of Portugal were evaluated using qPCR tools, and results were published in 2019. We applied an HTS approach to analyze frozen DNA samples from 36 sites in that study. Universal primers targeting ITS1 were used for nematode detection. All EPN species detected by qPCR were also detected by HTS. The EPN species and nearly all free-living nematodes detected by both processes were highly correlated (P < 0.01). Steinernema feltiae, the dominant EPN species, was detected by HTS in 55% more sites than by qPCR. HTS also detected more EPN species than did qPCR. Sample accuracy, measured by the fit of Taylor's Power Law to data from each method, was significantly better using HTS (r = 0.95, P < 0.01) than qPCR (r = 0.76, P < 0.01). The effect of biotic and abiotic variables on individual EPN species did not differ according to ANOVA and multiple regression analyses of both data sets while the drivers of EPN community structure did not differ when analyzing either data set with CCA. Our results combined with decreasing costs of metabarcoding, suggest that HTS may provide the most cost-effective and accurate means of assessing soil food webs of methods currently available. This study was supported in ...
author2 United States Agency for International Development
National Academy of Sciences (US)
Science and Technology Development Fund (Egypt)
Campos-Herrera, R.
format Article in Journal/Newspaper
author Dritsoulas, Alexandros
Campos-Herrera, R.
Blanco-Pérez, Rubén
Duncan, L. W.
author_facet Dritsoulas, Alexandros
Campos-Herrera, R.
Blanco-Pérez, Rubén
Duncan, L. W.
author_sort Dritsoulas, Alexandros
title Comparing high throughput sequencing and real time qPCR for characterizing entomopathogenic nematode biogeography
title_short Comparing high throughput sequencing and real time qPCR for characterizing entomopathogenic nematode biogeography
title_full Comparing high throughput sequencing and real time qPCR for characterizing entomopathogenic nematode biogeography
title_fullStr Comparing high throughput sequencing and real time qPCR for characterizing entomopathogenic nematode biogeography
title_full_unstemmed Comparing high throughput sequencing and real time qPCR for characterizing entomopathogenic nematode biogeography
title_sort comparing high throughput sequencing and real time qpcr for characterizing entomopathogenic nematode biogeography
publisher Elsevier
publishDate 2020
url http://hdl.handle.net/10261/223466
https://doi.org/10.1016/j.soilbio.2020.107793
https://doi.org/10.13039/100000209
https://doi.org/10.13039/501100003009
genre Antarc*
Antarctica
genre_facet Antarc*
Antarctica
op_relation Postprint
http://dx.doi.org/10.1016/j.soilbio.2020.107793

Soil Biology and Biochemistry 145: 107793 (2020)
0038-0717
http://hdl.handle.net/10261/223466
doi:10.1016/j.soilbio.2020.107793
http://dx.doi.org/10.13039/100000209
http://dx.doi.org/10.13039/501100003009
op_rights open
op_doi https://doi.org/10.1016/j.soilbio.2020.10779310.13039/10000020910.13039/501100003009
container_title Soil Biology and Biochemistry
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