Relative species abundance estimation in artificial mixtures of insects using mito‐metagenomics and a correction factor for the mitochondrial DNA copy number

Garrido-Sanz, Lidia; Senar, Miquel A.; Piñol, Josep

doi:10.1111/1755-0998.13464

Cited by 12 publications

(21 citation statements)

References 59 publications

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“…At the same time, we also found that the WGS sequence reads departed more strongly from the “true” 1:1 input pollen grain to output sequence proportion relationship relative to amplicon‐based methods. Comparison of WGS of chloroplast genomes with DNA metabarcoding for the identification of pollen mixtures has found improved quantification with WGS (Lang et al, 2019 ), and likewise for comparison of WGS of mitochondrial genomes with amplicon sequencing of animal mixtures (Bista et al, 2018 ), and this quantification can be further improved by correcting for mitochondrial genome copy number (Garrido‐Sanz et al, 2020 ; Garrido‐Sanz et al, 2021 ). Long‐read sequencing of nuclear DNA of pollen mixtures has been found to be semiquantitative, in that species present in high proportions were detected in high proportions and species present in low proportions were detected in low proportions (Peel et al, 2019 ).…”

Section: Discussionmentioning

confidence: 99%

Comparing whole‐genome shotgun sequencing and DNA metabarcoding approaches for species identification and quantification of pollen species mixtures

Bell

Petit

Cutler

et al. 2021

Ecology and Evolution

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Molecular identification of mixed-species pollen samples has a range of applications in various fields of research. To date, such molecular identification has primarily been carried out via amplicon sequencing, but whole-genome shotgun (WGS) sequencing of pollen DNA has potential advantages, including (1) more genetic information per sample and (2) the potential for better quantitative matching. In this study, we tested the performance of WGS sequencing methodology and publicly available reference sequences in identifying species and quantifying their relative abundance in pollen mock communities. Using mock communities previously analyzed with DNA metabarcoding, we sequenced approximately 200Mbp for each sample using Illumina HiSeq and MiSeq. Taxonomic identifications were based on the Kraken k-mer identification method with reference libraries constructed from full-genome and short read archive data from the NCBI database. We found WGS to be a reliable method for taxonomic identification of pollen with near 100% identification of species in mixtures but generating higher rates of false positives (reads not identified to the correct taxon at the required taxonomic level) relative to rbcL and ITS2 amplicon sequencing. For quantification of relative species abundance, WGS data provided a stronger correlation between pollen grain proportion and sequence read proportion, but diverged more from a 1:1 relationship, likely due to the higher rate of false positives. Currently, a limitation of WGS-based pollen identification is the lack of representation of plant diversity in publicly available genome databases. As databases improve and costs drop, we expect that eventually genomics methods will become the methods of choice for species identification and quantification of mixed-species pollen samples.

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Section: Discussionmentioning

confidence: 99%

Comparing whole‐genome shotgun sequencing and DNA metabarcoding approaches for species identification and quantification of pollen species mixtures

Bell

Petit

Cutler

et al. 2021

Ecology and Evolution

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“…Different pollen types can have different DNA extraction efficiencies, which can be improved with method optimisation. Variation occurs among species in the copy numbers of the DNA barcodes, and this has been well-studied for microbes, with the possibility to correct for these biases (Kembel, Wu, Eisen, & Green, 2012;Lamb et al, 2019;Pawluczyk et al, 2015) and a recent study on mitogenomics of insects has applied corrections for copy number (L. Garrido-Sanz et al, 2021). An additional source of bias comes from differences among species in primer binding efficiency (Pompanon et al, 2012) and biases in DNA polymerase binding efficiencies towards different nucleotide compositions (Nichols et al, 2018).…”

Section: Monitoring Impacts On Human Healthmentioning

confidence: 99%

“…Whole-genome shotgun (WGS) sequencing has been shown to have improved quantification for pollen (Bell, Petit, et al, 2021) and other mixtures of eukaryote species (Lidia Garrido-Sanz, Senar, & Pinol, 2020). Genome-skimming of organellar DNA from WGS has been shown to be quantitative for pollen (Lang et al, 2019) and other eukaryote mixtures (Bista et al, 2018), and quantification can be improved by correcting for organelle copy number (L. Garrido-Sanz et al, 2021). Reduced-representation sequencing using endonucleases (genotyping-by-sequencing) of plant roots has shown within-and across-species abundances strongly correlate with biomass-based species abundance (Wagemaker et al, 2021).…”

Section: Monitoring Impacts On Human Healthmentioning

confidence: 99%

“…Ongoing method development in pollen DNA metabarcoding is likely to improve taxonomic resolution and quantification accuracy, and could eventually include intraspecific identifications (i.e., distinct subspecies or populations within a species). These developments could include using more of the genome (Bell, Petit, et al, 2021;Lang, Tang, Hu, & Zhou, 2019), using longer reads (Peel et al, 2019), and correcting for copy number of barcode gene regions (L. Garrido-Sanz, Senar, & Pinol, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Pollen DNA metabarcoding and related methods in global change ecology: prospects, challenges, and progress

Bell

Turo

Lowe

et al. 2022

Preprint

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Anthropogenic activities are leading to changes in the environment at global scales, and understanding these changes requires rapid, high-throughput methods of assessment. Pollen DNA metabarcoding and related methods provide advantages in throughput and efficiency over traditional methods, such as microscopic identification of pollen and visual observation of plant-pollinator interactions. Pollen DNA metabarcoding is currently being applied to assessments of plant-pollinator interactions and their responses to land-use change such as increased agricultural intensity and urbanisation, surveillance of ecosystem change, and monitoring of spatiotemporal distribution of allergenic pollen. In combination with historical specimens, pollen DNA metabarcoding can compare contemporary and past ecosystems. Current technical challenges with pollen DNA metabarcoding include the need to understand the relationship between sequence read and species abundance, develop methods for determining confidence limits for detection and taxonomic classification, increase method standardisation, and improve of gaps in reference databases. Future research expanding the method to intraspecific identification, analysis of DNA in ancient pollen samples, and increased use of museum and herbarium specimens could open further avenues for research. Ongoing developments in sequencing technologies can accelerate progress towards these goals. Global ecological change is happening rapidly, and we anticipate that high-throughput methods such as pollen DNA metabarcoding are critical for assessing these changes and providing timely management recommendations to preserve biodiversity and the evolutionary and ecological processes that support it.

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“…Species pipeline biases. -Species differ in body size (biomass bias), genome size, mitochondrial copy number, DNA extraction efficiency, and PCR amplification efficiency (primer bias) (Amend et al 2010;Yu et al 2012;Elbrecht and Leese 2015;Piñol et al 2015Piñol et al , 2019Tang et al 2015;Bell et al 2017;Krehenwinkel et al 2017;McLaren et al 2019;Pauvert et al 2019;Garrido-Sanz et al 2021;Yang et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Extracting abundance information from DNA-based data

Luo

2022

Preprint

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The accurate extraction of species-abundance information from DNA-based data (metabarcoding, metagenomics) could contribute usefully to diet reconstruction and quantitative food webs, the inference of species interactions, the modelling of population dynamics and species distributions, the biomonitoring of environmental state and change, and the inference of false positives and negatives. However, capture bias, capture noise, species pipeline biases, and pipeline noise all combine to inject error into DNA-based datasets. We focus on methods for correcting the latter two error sources, as the first two are addressed extensively in the ecological literature. To extract abundance information, it is useful to distinguish two concepts. (1) Across-species quantification describes relative species abundances within one sample. (2) In contrast, within-species quantification describes how the abundance of each individual species varies from sample to sample, as in a time series, an environmental gradient, or different experimental treatments. Firstly, we review methods to remove species pipeline biases and pipeline noise. Secondly, we demonstrate experimentally (with a detailed protocol) how to use a 'DNA spike-in' to remove pipeline noise and recover within-species abundance information. We also introduce a statistical estimator that can partially remove pipeline noise from datasets that lack a physical DNA spike-in.

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Relative species abundance estimation in artificial mixtures of insects using mito‐metagenomics and a correction factor for the mitochondrial DNA copy number

Abstract: Mitochondrial metagenomics or mito-metagenomics (hereafter, MMG) is becoming an alternative to the classical amplicon metabarcoding for the large-scale assessment of biodiversity of Metazoa

Cited by 12 publications

References 59 publications

Comparing whole‐genome shotgun sequencing and DNA metabarcoding approaches for species identification and quantification of pollen species mixtures

Comparing whole‐genome shotgun sequencing and DNA metabarcoding approaches for species identification and quantification of pollen species mixtures

Pollen DNA metabarcoding and related methods in global change ecology: prospects, challenges, and progress

Extracting abundance information from DNA-based data

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