scholarly journals Issues of under-representation in quantitative DNA metabarcoding weaken the inference about diet of the tundra vole Microtus oeconomus

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11936
Author(s):  
Magne Neby ◽  
Stefaniya Kamenova ◽  
Olivier Devineau ◽  
Rolf A. Ims ◽  
Eeva M. Soininen
Keyword(s):  
High Throughput ◽  
Dna Sequences ◽  
High Throughput Sequencing ◽  
Plant Biomass ◽  
Quantitative Relationship ◽  
Food Plants ◽  
Small Rodents ◽  
Microtus Oeconomus ◽  
Dna Metabarcoding ◽  
Tundra Vole

During the last decade, methods based on high-throughput sequencing such as DNA metabarcoding have opened up for a range of new questions in animal dietary studies. One of the major advantages of dietary metabarcoding resides in the potential to infer a quantitative relationship between sequence read proportions and biomass of ingested food. However, this relationship’s robustness is highly dependent on the system under study, calling for case-specific assessments. Herbivorous small rodents often play important roles in the ecosystem, and the use of DNA metabarcoding for analyses of rodent diets is increasing. However, there has been no direct validation of the quantitative reliability of DNA metabarcoding for small rodents. Therefore, we used an experimental approach to assess the relationship between input plant biomass and sequence reads proportions from DNA metabarcoding in the tundra vole Microtus oeconomus. We found a weakly positive relationship between the number of high-throughput DNA sequences and the expected biomass proportions of food plants. The weak relationship was possibly caused by a systematic under-amplification of one of the three plant taxa fed. Generally, our results add to the growing evidence that case-specific validation studies are required to reliably make use of sequence read abundance as a proxy of relative food proportions in the diet.

scholarly journals DNA-Based Herbal Teas’ Authentication: An ITS2 and psbA-trnH Multi-Marker DNA Metabarcoding Approach

Plants ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2120
Author(s):  
Jessica Frigerio ◽  
Giulia Agostinetto ◽  
Valerio Mezzasalma ◽  
Fabrizio De De Mattia ◽  
Massimo Labra ◽  
...  
Keyword(s):  
Quality Control ◽  
Quantitative Analysis ◽  
Medicinal Plants ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
The Other ◽  
Plant Component ◽  
Identification Rate ◽  
Dna Metabarcoding ◽  
Therapeutic Properties

Medicinal plants have been widely used in traditional medicine due to their therapeutic properties. Although they are mostly used as herbal infusion and tincture, employment as ingredients of food supplements is increasing. However, fraud and adulteration are widespread issues. In our study, we aimed at evaluating DNA metabarcoding as a tool to identify product composition. In order to accomplish this, we analyzed fifteen commercial products with DNA metabarcoding, using two barcode regions: psbA-trnH and ITS2. Results showed that on average, 70% (44–100) of the declared ingredients have been identified. The ITS2 marker appears to identify more species (n = 60) than psbA-trnH (n = 35), with an ingredients’ identification rate of 52% versus 45%, respectively. Some species are identified only by one marker rather than the other. Additionally, in order to evaluate the quantitative ability of high-throughput sequencing (HTS) to compare the plant component to the corresponding assigned sequences, in the laboratory, we created six mock mixtures of plants starting both from biomass and gDNA. Our analysis also supports the application of DNA metabarcoding for a relative quantitative analysis. These results move towards the application of HTS analysis for studying the composition of herbal teas for medicinal plants’ traceability and quality control.

scholarly journals PLANiTS: a curated sequence reference dataset for plant ITS DNA metabarcoding

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Elisa Banchi ◽  
Claudio G Ametrano ◽  
Samuele Greco ◽  
David Stanković ◽  
Lucia Muggia ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Its Region ◽  
Computational Effort ◽  
Its Sequences ◽  
Reference Dataset ◽  
Bioinformatic Pipeline ◽  
Taxonomic Level ◽  
Dna Metabarcoding ◽  
Reference Databases

Abstract DNA metabarcoding combines DNA barcoding with high-throughput sequencing to identify different taxa within environmental communities. The ITS has already been proposed and widely used as universal barcode marker for plants, but a comprehensive, updated and accurate reference dataset of plant ITS sequences has not been available so far. Here, we constructed reference datasets of Viridiplantae ITS1, ITS2 and entire ITS sequences including both Chlorophyta and Streptophyta. The sequences were retrieved from NCBI, and the ITS region was extracted. The sequences underwent identity check to remove misidentified records and were clustered at 99% identity to reduce redundancy and computational effort. For this step, we developed a script called ‘better clustering for QIIME’ (bc4q) to ensure that the representative sequences are chosen according to the composition of the cluster at a different taxonomic level. The three datasets obtained with the bc4q script are PLANiTS1 (100 224 sequences), PLANiTS2 (96 771 sequences) and PLANiTS (97 550 sequences), and all are pre-formatted for QIIME, being this the most used bioinformatic pipeline for metabarcoding analysis. Being curated and updated reference databases, PLANiTS1, PLANiTS2 and PLANiTS are proposed as a reliable, pivotal first step for a general standardization of plant DNA metabarcoding studies. The bc4q script is presented as a new tool useful in each research dealing with sequences clustering. Database URL: https://github.com/apallavicini/bc4q; https://github.com/apallavicini/PLANiTS.

scholarly journals Predicting plant biomass accumulation from image-derived parameters

2016 ◽  
Author(s):  
Dijun Chen ◽  
Rongli Shi ◽  
Jean-Michel Pape ◽  
Christian Klukas
Keyword(s):  
High Throughput ◽  
Plant Biomass ◽  
Quantitative Relationship ◽  
Biomass Accumulation ◽  
Plant Phenotyping ◽  
Suitable Model ◽  
The European Union ◽  
Relative Contribution ◽  
Crop Plant Research ◽  
High Throughput Phenotyping

AbstractImage-based high-throughput phenotyping technologies have been rapidly developed in plant science recently and they provide a great potential to gain more valuable information than traditionally destructive methods. Predicting plant biomass is regarded as a key purpose for plant breeders and ecologist. However, it is a great challenge to find a suitable model to predict plant biomass in the context of high-throughput phenotyping. In the present study, we constructed several models to examine the quantitative relationship between image-based features and plant biomass accumulation. Our methodology has been applied to three consecutive barley experiments with control and stress treatments. The results proved that plant biomass can be accurately predicted from image-based parameters using a random forest model. The high prediction accuracy based on this model, in particular the cross-experiment performance, is promising to relieve the phenotyping bottleneck in biomass measurement in breeding applications. The relative contribution of individual features for predicting biomass was further quantified, revealing new insights into the phenotypic determinants of plant biomass outcome. What’s more, the methods could also be used to determine the most important image-based features related to plant biomass accumulation, which would be promising for subsequent genetic mapping to uncover the genetic basis of biomass.One-sentence SummaryWe demonstrated that plant biomass can be accurately predicted from image-based parameters in the context of high-throughput phenotyping.FootnotesThis work was supported by the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), the Robert Bosch Stiftung (32.5.8003.0116.0) and the Federal Agency for Agriculture and Food (BEL, 15/12-13, 530-06.01-BiKo CHN) and the Federal Ministry of Education and Research (BMBF, 0315958A and 031A053B). This research was furthermore enabled with support of the European Plant Phenotyping Network (EPPN, grant agreement no. 284443) funded by the FP7 Research Infrastructures Programme of the European Union.

scholarly journals Sorting things out - assessing effects of unequal specimen biomass on DNA metabarcoding

2016 ◽  
Author(s):  
Vasco Elbrecht ◽  
Bianca Peinert ◽  
Florian Leese
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Sequencing Depth ◽  
West Germany ◽  
Coi Gene ◽  
Mountain Stream ◽  
Detection Rates ◽  
Size Classes ◽  
Dna Metabarcoding ◽  
Size Sorting

1) Environmental bulk samples often contain many taxa with biomass differences of several orders of magnitude. This can be problematic in DNA metabarcoding and metagenomic high throughput sequencing approaches, as large specimens contribute over proportionally much DNA template. Thus a few specimens of high biomass will dominate the dataset, potentially leading to smaller specimens remaining undetected. Sorting of samples and balancing the amounts of tissue used per size fraction should improve detection rates, but has not been systematically tested. 2) Here we tested the effects of size sorting on taxa detection using freshwater macroinvertebrates. Kick sampling was performed at two locations of a low-mountain stream in West Germany, specimens were morphologically identified and sorted into small, medium and large size classes (< 2.5x5, 5x10 and up to 10x20 mm). Tissue from the 3 size categories was extracted individually, and pooled to simulate bulk samples that were not sorted and samples which were sorted and then pooled proportionately by specimen size. DNA from all 5 extractions of both samples was amplified using 4 different freshwater primer sets for the COI gene and sequenced on a HiSeq Illumina sequencer. 3) Sorting taxa by size and pooling them proportionately according to their abundance lead to a more equal amplification compared to the processing of complete samples without sorting. The sorted samples recovered 30% more taxa than the unsorted samples, at the same sequencing depth. Our results imply that sequencing depth can be decreased ~ 5 fold when sorting the samples into three size classes. 4) Our results demonstrate that even a coarse size sorting can substantially improve detection rates. While high throughput sequencing will become more accessible and cheaper within the next years, sorting bulk samples by specimen biomass is a simple yet efficient method to reduce current sequencing costs.

scholarly journals Scaling up DNA metabarcoding for freshwater macrozoobenthos monitoring

2018 ◽  
Author(s):  
Vasco Elbrecht ◽  
Dirk Steinke
Keyword(s):  
High Throughput ◽  
Illumina Sequencing ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Scaling Up ◽  
The Past ◽  
Dna Metabarcoding ◽  
Primer Sets ◽  
Fusion Primer ◽  
Positive Controls

The viability of DNA metabarcoding for assessment of freshwater macrozoobenthos has been demonstrated over the past years. It matured to a stage where it can be applied to monitoring at a large scale, keeping pace with increased high throughput sequencing (HTS) capacity. However, workflows and sample tagging need to be optimized to accommodate for hundreds of samples within a single sequencing run. We here conceptualize a streamlined metabarcoding workflow, in which samples are processed in 96-well plates. Each sample is replicated starting with tissue extraction. Negative and positive controls are included to ensure data reliability. With our newly developed fusion primer sets for the BF2+BR2 primer pair up to three 96-well plates (288 wells) can be uniquely tagged for a single Illumina sequencing run. By including Illumina indices tagging can be extended to thousands of samples. We hope that our metabarcoding workflow will be used as a practical guide for future large-scale biodiversity assessments involving freshwater invertebrates. However, we also want to point out that this is just one approach, and that we hope this article will stimulate discussion and publication of alternatives and extensions.

scholarly journals Scaling up DNA metabarcoding for freshwater macrozoobenthos monitoring

2018 ◽  
Author(s):  
Vasco Elbrecht ◽  
Dirk Steinke
Keyword(s):  
High Throughput ◽  
Illumina Sequencing ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Scaling Up ◽  
The Past ◽  
Dna Metabarcoding ◽  
Primer Sets ◽  
Fusion Primer ◽  
Positive Controls

The viability of DNA metabarcoding for assessment of freshwater macrozoobenthos has been demonstrated over the past years. It matured to a stage where it can be applied to monitoring at a large scale, keeping pace with increased high throughput sequencing (HTS) capacity. However, workflows and sample tagging need to be optimized to accommodate for hundreds of samples within a single sequencing run. We here conceptualize a streamlined metabarcoding workflow, in which samples are processed in 96-well plates. Each sample is replicated starting with tissue extraction. Negative and positive controls are included to ensure data reliability. With our newly developed fusion primer sets for the BF2+BR2 primer pair up to three 96-well plates (288 wells) can be uniquely tagged for a single Illumina sequencing run. By including Illumina indices tagging can be extended to thousands of samples. We hope that our metabarcoding workflow will be used as a practical guide for future large-scale biodiversity assessments involving freshwater invertebrates. However, we also want to point out that this is just one approach, and that we hope this article will stimulate discussion and publication of alternatives and extensions.

scholarly journals Scaling up DNA metabarcoding for freshwater macrozoobenthos monitoring

2018 ◽  
Author(s):  
Vasco Elbrecht ◽  
Dirk Steinke
Keyword(s):  
High Throughput ◽  
Illumina Sequencing ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Scaling Up ◽  
The Past ◽  
Dna Metabarcoding ◽  
Primer Sets ◽  
Fusion Primer ◽  
Positive Controls

The viability of DNA metabarcoding for assessment of freshwater macrozoobenthos has been demonstrated over the past years. It matured to a stage where it can be applied to monitoring at a large scale, keeping pace with increased high throughput sequencing (HTS) capacity. However, workflows and sample tagging need to be optimized to accommodate for hundreds of samples within a single sequencing run. We here conceptualize a streamlined metabarcoding workflow, in which samples are processed in 96-well plates. Each sample is replicated starting with tissue extraction. Negative and positive controls are included to ensure data reliability. With our newly developed fusion primer sets for the BF2+BR2 primer pair up to three 96-well plates (288 wells) can be uniquely tagged for a single Illumina sequencing run. By including Illumina indices, tagging can be extended to thousands of samples. We hope that our metabarcoding workflow will be used as a practical guide for future large-scale biodiversity assessments involving freshwater invertebrates. However, we also want to point out that this is just one possible metabarcoding approach, and that we hope this article will stimulate discussion and publication of alternatives and extensions.

scholarly journals In silico assessment of primers for eDNA studies using PrimerTree and application to characterize the biodiversity surrounding the Cuyahoga River

2015 ◽  
Author(s):  
M.V. Cannon ◽  
J. Hester ◽  
A. Shalkhauser ◽  
E.R. Chan ◽  
K. Logue ◽  
...  
Keyword(s):  
High Throughput ◽  
Dna Sequences ◽  
Water Samples ◽  
High Throughput Sequencing ◽  
Biological Diversity ◽  
Pcr Amplification ◽  
Environmental Dna ◽  
Asian Carp ◽  
Broad Perspective ◽  
Wide Range

Analysis of environmental DNA (eDNA) enables the detection of species of interest from water and soil samples, typically using species-specific PCR. Here, we describe a method to characterize the biodiversity of a given environment by amplifying eDNA using primer pairs targeting a wide range of taxa and high-throughput sequencing for species identification. We tested this approach on 91 water samples of 40 mL collected along the Cuyahoga River (Ohio, USA). We amplified eDNA using 12 primer pairs targeting mammals, fish, amphibians, birds, bryophytes, arthropods, copepods, plants and several microorganism taxa and sequenced all PCR products simultaneously by high-throughput sequencing. Overall, we identified DNA sequences from 15 species of fish, 17 species of mammals, 8 species of birds, 15 species of arthropods, one turtle and one salamander. Interestingly, in addition to aquatic and semiaquatic animals, we identified DNA from terrestrial species that live near the Cuyahoga River. We also identified DNA from one Asian carp species invasive to the Great Lakes but that had not been previously reported in the Cuyahoga River. Our study shows that analysis of eDNA extracted from small water samples using wide-range PCR amplification combined with high-throughput sequencing can provide a broad perspective on biological diversity.

scholarly journals Scaling up DNA metabarcoding for freshwater macrozoobenthos monitoring

2018 ◽  
Author(s):  
Vasco Elbrecht ◽  
Dirk Steinke
Keyword(s):  
High Throughput ◽  
Illumina Sequencing ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Scaling Up ◽  
The Past ◽  
Dna Metabarcoding ◽  
Primer Sets ◽  
Fusion Primer ◽  
Positive Controls

The viability of DNA metabarcoding for assessment of freshwater macrozoobenthos has been demonstrated over the past years. It matured to a stage where it can be applied to monitoring at a large scale, keeping pace with increased high throughput sequencing (HTS) capacity. However, workflows and sample tagging need to be optimized to accommodate for hundreds of samples within a single sequencing run. We here conceptualize a streamlined metabarcoding workflow, in which samples are processed in 96-well plates. Each sample is replicated starting with tissue extraction. Negative and positive controls are included to ensure data reliability. With our newly developed fusion primer sets for the BF2+BR2 primer pair up to three 96-well plates (288 wells) can be uniquely tagged for a single Illumina sequencing run. By including Illumina indices, tagging can be extended to thousands of samples. We hope that our metabarcoding workflow will be used as a practical guide for future large-scale biodiversity assessments involving freshwater invertebrates. However, we also want to point out that this is just one possible metabarcoding approach, and that we hope this article will stimulate discussion and publication of alternatives and extensions.

scholarly journals Scaling up DNA metabarcoding for freshwater macrozoobenthos monitoring

2018 ◽  
Author(s):  
Vasco Elbrecht ◽  
Dirk Steinke
Keyword(s):  
High Throughput ◽  
Illumina Sequencing ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Scaling Up ◽  
The Past ◽  
Dna Metabarcoding ◽  
Primer Sets ◽  
Fusion Primer ◽  
Positive Controls

The viability of DNA metabarcoding for assessment of freshwater macrozoobenthos has been demonstrated over the past years. It matured to a stage where it can be applied to monitoring at a large scale, keeping pace with increased high throughput sequencing (HTS) capacity. However, workflows and sample tagging need to be optimized to accommodate for hundreds of samples within a single sequencing run. We here conceptualize a streamlined metabarcoding workflow, in which samples are processed in 96-well plates. Each sample is replicated starting with tissue extraction. Negative and positive controls are included to ensure data reliability. With our newly developed fusion primer sets for the BF2+BR2 primer pair up to three 96-well plates (288 wells) can be uniquely tagged for a single Illumina sequencing run. By including Illumina indices, tagging can be extended to thousands of samples. We hope that our metabarcoding workflow will be used as a practical guide for future large-scale biodiversity assessments involving freshwater invertebrates. However, we also want to point out that this is just one possible metabarcoding approach, and that we hope this article will stimulate discussion and publication of alternatives and extensions.

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