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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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 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 |
op_rights |
open |
op_doi |
https://doi.org/10.1016/j.soilbio.2020.10779310.13039/10000020910.13039/501100003009 |
container_title |
Soil Biology and Biochemistry |
container_volume |
145 |
container_start_page |
107793 |
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1790601859881238528 |