scholarly journals Peer Review #3 of "Estimating intraspecific genetic diversity from community DNA metabarcoding data (v0.1)"

2018 ◽  
Keyword(s):  
Genetic Diversity ◽  
Peer Review ◽  
Dna Metabarcoding ◽  
Intraspecific Genetic Diversity

scholarly journals Estimating intraspecific genetic diversity from community DNA metabarcoding data

2018 ◽  
Author(s):  
Vasco Elbrecht ◽  
Ecaterina Edith Vamos ◽  
Dirk Steinke ◽  
Florian Leese
Keyword(s):  
Genetic Diversity ◽  
Biological Diversity ◽  
Intraspecific Diversity ◽  
Great Promise ◽  
Data Sets ◽  
Mock Community ◽  
Data Set ◽  
Dna Metabarcoding ◽  
Intraspecific Genetic Diversity ◽  
Primer Sets

Background. DNA metabarcoding is used to generate species composition data for entire communities. However, sequencing errors in high throughput sequencing instruments are fairly common, usually requiring reads to be clustered into operational taxonomic units (OTU), losing information on intraspecific diversity in the process. While COI haplotype information is limited in resolution, it is nevertheless useful in a phylogeographic context, helping to formulate hypothesis on taxon dispersal. Methods. This study combines sequence denoising strategies, normally applied in microbial research, with additional abundance-based filtering to extract haplotypes from freshwater macroinvertebrate metabarcoding data sets. This novel approach was added to the R package "JAMP" and can be applied to Cytochrome c oxidase subunit I (COI) amplicon datasets. We tested our haplotyping method by sequencing i) a single-species mock community composed of 31 individuals with different haplotypes spanning three orders of magnitude in biomass and ii) 18 monitoring samples each amplified with four different primer sets and two PCR replicates. Results. We detected all 15 haplotypes of the single specimens in the mock community with relaxed filtering and denoising settings. However, up to 480 additional unexpected haplotypes remained in both replicates. Rigorous filtering removes most unexpected haplotypes, but also can discard expected haplotypes mainly from the small specimens. In the monitoring samples, the different primer sets detected 177 - 200 OTUs, each containing an average of 2.40 to 3.30 haplotypes per OTU. Population structures were consistent between replicates, and similar between primer pairs, depending on the primer length. A closer look at abundant taxa in the data set revealed various population genetic patterns, e.g. Taeniopteryx nebulosa and Hydropsyche pellucidula with a difference in north-south haplotype distribution, while Oulimnius tuberculatus and Asellus aquaticus display no clear population pattern but differ in genetic diversity. Discussion. We developed a strategy to infer intraspecific genetic diversity from bulk invertebrate monitoring samples using metabarcoding data. It needs to be stressed that at this point metabarcoding-informed haplotyping is not capable of capture the full diversity present in such samples, due to variation in specimen size, primer bias and loss of sequence variants with low abundance. Nevertheless, for a high number of species intraspecific diversity was recovered, identifying potentially isolated populations and potential taxa for further more detailed phylogeographic investigation. While we are currently lacking large-scale metabarcoding data sets to fully take advantage of our new approach, metabarcoding-informed haplotyping holds great promise for biomonitoring efforts that not only seek information about biological diversity but also underlying genetic diversity.

scholarly journals Estimating intraspecific genetic diversity from community DNA metabarcoding data

2018 ◽  
Author(s):  
Vasco Elbrecht ◽  
Ecaterina Edith Vamos ◽  
Dirk Steinke ◽  
Florian Leese
Keyword(s):  
Genetic Diversity ◽  
Biological Diversity ◽  
Intraspecific Diversity ◽  
Great Promise ◽  
Data Sets ◽  
Mock Community ◽  
Data Set ◽  
Dna Metabarcoding ◽  
Intraspecific Genetic Diversity ◽  
Primer Sets

Background. DNA metabarcoding is used to generate species composition data for entire communities. However, sequencing errors in high throughput sequencing instruments are fairly common, usually requiring reads to be clustered into operational taxonomic units (OTU), losing information on intraspecific diversity in the process. While COI haplotype information is limited in resolution, it is nevertheless useful in a phylogeographic context, helping to formulate hypothesis on taxon dispersal. Methods. This study combines sequence denoising strategies, normally applied in microbial research, with additional abundance-based filtering to extract haplotypes from freshwater macroinvertebrate metabarcoding data sets. This novel approach was added to the R package "JAMP" and can be applied to Cytochrome c oxidase subunit I (COI) amplicon datasets. We tested our haplotyping method by sequencing i) a single-species mock community composed of 31 individuals with different haplotypes spanning three orders of magnitude in biomass and ii) 18 monitoring samples each amplified with four different primer sets and two PCR replicates. Results. We detected all 15 haplotypes of the single specimens in the mock community with relaxed filtering and denoising settings. However, up to 480 additional unexpected haplotypes remained in both replicates. Rigorous filtering removes most unexpected haplotypes, but also can discard expected haplotypes mainly from the small specimens. In the monitoring samples, the different primer sets detected 177 - 200 OTUs, each containing an average of 2.40 to 3.30 haplotypes per OTU. Population structures were consistent between replicates, and similar between primer pairs, depending on the primer length. A closer look at abundant taxa in the data set revealed various population genetic patterns, e.g. Taeniopteryx nebulosa and Hydropsyche pellucidula with a difference in north-south haplotype distribution, while Oulimnius tuberculatus and Asellus aquaticus display no clear population pattern but differ in genetic diversity. Discussion. We developed a strategy to infer intraspecific genetic diversity from bulk invertebrate monitoring samples using metabarcoding data. It needs to be stressed that at this point metabarcoding-informed haplotyping is not capable of capture the full diversity present in such samples, due to variation in specimen size, primer bias and loss of sequence variants with low abundance. Nevertheless, for a high number of species intraspecific diversity was recovered, identifying potentially isolated populations and potential taxa for further more detailed phylogeographic investigation. While we are currently lacking large-scale metabarcoding data sets to fully take advantage of our new approach, metabarcoding-informed haplotyping holds great promise for biomonitoring efforts that not only seek information about biological diversity but also underlying genetic diversity.

scholarly journals Assessing intraspecific genetic diversity from community DNA metabarcoding data

2018 ◽  
Author(s):  
Vasco Elbrecht ◽  
Ecaterina Edith Vamos ◽  
Dirk Steinke ◽  
Florian Leese
Keyword(s):  
Genetic Diversity ◽  
Biological Diversity ◽  
Intraspecific Diversity ◽  
Great Promise ◽  
Data Sets ◽  
Mock Community ◽  
Data Set ◽  
Dna Metabarcoding ◽  
Intraspecific Genetic Diversity ◽  
Primer Sets

Background. DNA metabarcoding is used to generate species composition data for entire communities. However, sequencing errors in high throughput sequencing instruments are fairly common, usually requiring reads to be clustered into operational taxonomic units (OTU), loosing information on intraspecific diversity in the process. Methods. This study combines sequence denoising strategies, normally applied in microbial research, with additional abundance based filtering to extract haplotypes from freshwater macroinvertebrate metabarcoding data sets. This novel approach is implemented in the R package "JAMP" and can be applied to Cytochrome c oxidase subunit I (COI) amplicon datasets. We tested our haplotyping method by sequencing i) a single-species mock community composed of 31 individuals with different haplotypes spanning three orders of magnitude in biomass and ii) 18 monitoring samples each amplified with four different primer sets and two PCR replicates. Results. We detected all 15 haplotypes of the single specimens in the mock community with relaxed filtering and denoising settings. However, up to 480 additional unexpected haplotypes remained in both replicates. Rigorous filtering removes most unexpected haplotypes, but also can discard expected haplotypes mainly from the small specimens. In the monitoring samples, the different primer sets detected 177 - 200 OTUs, each containing an average of 2.40 to 3.30 haplotypes per OTU. Population structures were consistent between replicates, and similar between primer pairs, depending on the primer length. A closer look at abundant taxa in the data set revealed various population genetic patterns, e.g. Taeniopteryx nebulosa and Hydropsyche pellucidula with a difference in north-south haplotype distribution, while Oulimnius tuberculatus and Asellus aquaticus display no clear population pattern but differ in genetic diversity. Discussion. We developed a strategy to infer intraspecific genetic diversity from bulk invertebrate samples using metabarcoding data. It needs to be stressed that at this point metabarcoding-informed haplotyping is not capable to capture the full diversity present in bulk samples, due to variation in specimen size, primer bias and loss of sequence variants with low abundance. Nevertheless, for a high number of species intraspecific diversity is recovered, identifying potentially isolated populations and potential taxa for further more detailed phylogeographic investigation. While we are currently lacking large-scale metabarcoding data sets to fully take advantage our new approach, metabarcoding-informed haplotyping holds great promise for biomonitoring efforts that not only seek information about biological diversity but also underlying genetic diversity.

scholarly journals Estimating intraspecific genetic diversity from community DNA metabarcoding data

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4644 ◽  
Author(s):  
Vasco Elbrecht ◽  
Ecaterina Edith Vamos ◽  
Dirk Steinke ◽  
Florian Leese
Keyword(s):  
Genetic Diversity ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Intraspecific Diversity ◽  
Great Promise ◽  
Mock Community ◽  
Dna Metabarcoding ◽  
Intraspecific Genetic Diversity ◽  
Primer Sets ◽  
Haplotype Information

BackgroundDNA metabarcoding is used to generate species composition data for entire communities. However, sequencing errors in high-throughput sequencing instruments are fairly common, usually requiring reads to be clustered into operational taxonomic units (OTUs), losing information on intraspecific diversity in the process. While Cytochrome c oxidase subunit I (COI) haplotype information is limited in resolving intraspecific diversity it is nevertheless often useful e.g. in a phylogeographic context, helping to formulate hypotheses on taxon distribution and dispersal.MethodsThis study combines sequence denoising strategies, normally applied in microbial research, with additional abundance-based filtering to extract haplotype information from freshwater macroinvertebrate metabarcoding datasets. This novel approach was added to the R package “JAMP” and can be applied to COI amplicon datasets. We tested our haplotyping method by sequencing (i) a single-species mock community composed of 31 individuals with 15 different haplotypes spanning three orders of magnitude in biomass and (ii) 18 monitoring samples each amplified with four different primer sets and two PCR replicates.ResultsWe detected all 15 haplotypes of the single specimens in the mock community with relaxed filtering and denoising settings. However, up to 480 additional unexpected haplotypes remained in both replicates. Rigorous filtering removes most unexpected haplotypes, but also can discard expected haplotypes mainly from the small specimens. In the monitoring samples, the different primer sets detected 177–200 OTUs, each containing an average of 2.40–3.30 haplotypes per OTU. The derived intraspecific diversity data showed population structures that were consistent between replicates and similar between primer pairs but resolution depended on the primer length. A closer look at abundant taxa in the dataset revealed various population genetic patterns, e.g. the stoneflyTaeniopteryx nebulosaand the caddisflyHydropsyche pellucidulashowed a distinct north–south cline with respect to haplotype distribution, while the beetleOulimnius tuberculatusand the isopodAsellus aquaticusdisplayed no clear population pattern but differed in genetic diversity.DiscussionWe developed a strategy to infer intraspecific genetic diversity from bulk invertebrate metabarcoding data. It needs to be stressed that at this point this metabarcoding-informed haplotyping is not capable of capturing the full diversity present in such samples, due to variation in specimen size, primer bias and loss of sequence variants with low abundance. Nevertheless, for a high number of species intraspecific diversity was recovered, identifying potentially isolated populations and taxa for further more detailed phylogeographic investigation. While we are currently lacking large-scale metabarcoding datasets to fully take advantage of our new approach, metabarcoding-informed haplotyping holds great promise for biomonitoring efforts that not only seek information about species diversity but also underlying genetic diversity.

scholarly journals Assessing intraspecific genetic diversity from community DNA metabarcoding data

2017 ◽  
Author(s):  
Vasco Elbrecht ◽  
Ecaterina Edith Vamos ◽  
Dirk Steinke ◽  
Florian Leese
Keyword(s):  
Genetic Diversity ◽  
Data Analysis ◽  
Species Composition ◽  
Ecological Monitoring ◽  
Intraspecific Diversity ◽  
Data Sets ◽  
Composition Data ◽  
Dna Metabarcoding ◽  
Intraspecific Genetic Diversity

DNA metabarcoding provides species composition data for entire communities, yet information on intraspecific diversity is usually lost during data analysis. The capacity to infer intraspecific genetic diversity within whole communities would, however, represent a leap forward for ecological monitoring and conservation. We developed an amplicon-based sequence denoising approach that allows the identification of haplotypes from metabarcoding data sets and demonstrate its power with two freshwater macroinvertebrate data sets.

scholarly journals Estimating intraspecific genetic diversity from community DNA metabarcoding data

2018 ◽  
Author(s):  
Vasco Elbrecht ◽  
Ecaterina Edith Vamos ◽  
Dirk Steinke ◽  
Florian Leese
Keyword(s):  
Genetic Diversity ◽  
Biological Diversity ◽  
Intraspecific Diversity ◽  
Great Promise ◽  
Data Sets ◽  
Mock Community ◽  
Data Set ◽  
Dna Metabarcoding ◽  
Intraspecific Genetic Diversity ◽  
Primer Sets

Background. DNA metabarcoding is used to generate species composition data for entire communities. However, sequencing errors in high throughput sequencing instruments are fairly common, usually requiring reads to be clustered into operational taxonomic units (OTU), losing information on intraspecific diversity in the process. While COI haplotype information is limited in resolution, it is nevertheless useful in a phylogeographic context, helping to formulate hypothesis on taxon dispersal. Methods. This study combines sequence denoising strategies, normally applied in microbial research, with additional abundance-based filtering to extract haplotypes from freshwater macroinvertebrate metabarcoding data sets. This novel approach was added to the R package "JAMP" and can be applied to Cytochrome c oxidase subunit I (COI) amplicon datasets. We tested our haplotyping method by sequencing i) a single-species mock community composed of 31 individuals with different haplotypes spanning three orders of magnitude in biomass and ii) 18 monitoring samples each amplified with four different primer sets and two PCR replicates. Results. We detected all 15 haplotypes of the single specimens in the mock community with relaxed filtering and denoising settings. However, up to 480 additional unexpected haplotypes remained in both replicates. Rigorous filtering removes most unexpected haplotypes, but also can discard expected haplotypes mainly from the small specimens. In the monitoring samples, the different primer sets detected 177 - 200 OTUs, each containing an average of 2.40 to 3.30 haplotypes per OTU. Population structures were consistent between replicates, and similar between primer pairs, depending on the primer length. A closer look at abundant taxa in the data set revealed various population genetic patterns, e.g. Taeniopteryx nebulosa and Hydropsyche pellucidula with a difference in north-south haplotype distribution, while Oulimnius tuberculatus and Asellus aquaticus display no clear population pattern but differ in genetic diversity. Discussion. We developed a strategy to infer intraspecific genetic diversity from bulk invertebrate monitoring samples using metabarcoding data. It needs to be stressed that at this point metabarcoding-informed haplotyping is not capable of capture the full diversity present in such samples, due to variation in specimen size, primer bias and loss of sequence variants with low abundance. Nevertheless, for a high number of species intraspecific diversity was recovered, identifying potentially isolated populations and potential taxa for further more detailed phylogeographic investigation. While we are currently lacking large-scale metabarcoding data sets to fully take advantage of our new approach, metabarcoding-informed haplotyping holds great promise for biomonitoring efforts that not only seek information about biological diversity but also underlying genetic diversity.

scholarly journals Can metabarcoding resolve intraspecific genetic diversity changes to environmental stressors? A test case using river macrozoobenthos

2020 ◽  
Vol 4 ◽  
Author(s):  
Vera Marie Alida Zizka ◽  
Martina Weiss ◽  
Florian Leese
Keyword(s):  
Genetic Diversity ◽  
Species Diversity ◽  
Haplotype Diversity ◽  
Environmental Stressors ◽  
Intraspecific Diversity ◽  
River Systems ◽  
Opposite Pattern ◽  
Dna Metabarcoding ◽  
Intraspecific Genetic Diversity ◽  
Promising Source

Genetic diversity is the most basal level of biodiversity and determines the evolutionary capacity of species to adapt to changing environments, yet it is typically neglected in routine biomonitoring and stressor impact assessment. For a comprehensive analysis of stressor impacts on genetic diversity, it is necessary to assess genetic variants simultaneously in many individuals and species. Such an assessment is not as straightforward and usually limited to one or few focal species. However, nowadays species diversity can be assessed by analysing thousands of individuals of a community simultaneously with DNA metabarcoding. Recent bioinformatic advances also allow for the extraction of exact sequence variants (ESVs or haplotypes) in addition to Operational Taxonomic Units (OTUs). By using this new capability, we here evaluated if the analysis of intraspecific mitochondrial diversity in addition to species diversity can provide insights into responses of stream macrozoobenthic communities to environmental stressors. For this purpose, we analysed macroinvertebrate bulk samples of three German river systems with different stressor levels using DNA metabarcoding. While OTU and haplotype number were negatively correlated with stressor impact, this association was not as clear when studying haplotype diversity across all taxa. However, stressor responses were found for sensitive EPT (Ephemeroptera, Plecoptera, Trichoptera) taxa and those exceedingly resistant to organic stress. An increase in haplotype number per OTU and haplotype diversity of sensitive taxa was observed with an increase in ecosystem quality and stability, while the opposite pattern was detected for pollution resistant taxa. However, this pattern was less prominent than expected based on the strong differences in stressor intensity between sites. To compare genetic diversity among communities in river systems, we focussed on OTUs, which were present in all systems. As OTU composition differed strongly between rivers, this led to the exclusion of a high number of OTUs, especially in diverse river systems of good quality, which potentially diminished the increase in intraspecific diversity. To better understand responses of intraspecific genetic diversity to environmental stressors, for example in river ecosystems, it would be important to increase OTU overlap between compared sites, e.g. by sampling a narrower stressor gradient, and to perform calibrated studies controlling for the number of individuals and their haplotypes. However, this pioneer study shows that the extraction of haplotypes from DNA metabarcoding datasets is a promising source of information to simultaneously assess intraspecific diversity changes in response to environmental impacts for a metacommunity.

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