Extracting abundance information from <scp>DNA</scp>‐based data

Luo, Mingjie; Ji, Yinqiu; Warton, David I.; Yu, Douglas W.

doi:10.1111/1755-0998.13703

Cited by 33 publications

(35 citation statements)

References 142 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…How well species abundance may be estimated through metabarcoding is currently a hotly debated topic. Early studies suggested that metabarcoding was unsuitable for quantification, but more recent efforts using correction factors or spike‐ins of known concentration to calibrate metabarcoding‐based estimates have reported encouraging results (Ershova et al, 2021; Luo et al, 2023). Nevertheless, our study offers some of the first quantitative analyses of the accuracy that might be achieved using such approaches.…”

Section: Discussionmentioning

confidence: 99%

“…One of the solutions proposed to address these challenges is the introduction of known amounts of either tissue or DNA (so-called spike-ins; Ji et al, 2020;Luo et al, 2023;Thomas et al, 2016) to facilitate normalizing sequencing results between and within samples.…”

Section: Introductionmentioning

confidence: 99%

“…Added to this, primer biases towards certain taxonomic groups can obscure estimates of species diversity and abundance, as demonstrated through metabarcoding of samples with known composition (Braukmann et al, 2019; Elbrecht et al, 2019; Elbrecht & Leese, 2015; Martoni et al, 2022). One of the solutions proposed to address these challenges is the introduction of known amounts of either tissue or DNA (so‐called spike‐ins ; Ji et al, 2020; Luo et al, 2023; Thomas et al, 2016) to facilitate normalizing sequencing results between and within samples.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimizing insect metabarcoding using replicated mock communities

Iwaszkiewicz‐Eggebrecht

Granqvist

Buczek

et al. 2023

Methods Ecol Evol

View full text Add to dashboard Cite

Metabarcoding (high‐throughput sequencing of marker gene amplicons) has emerged as a promising and cost‐effective method for characterizing insect community samples. Yet, the methodology varies greatly among studies and its performance has not been systematically evaluated to date. In particular, it is unclear how accurately metabarcoding can resolve species communities in terms of presence‐absence, abundance and biomass. Here we use mock community experiments and a simple probabilistic model to evaluate the effect of different DNA extraction protocols on metabarcoding performance. Specifically, we ask four questions: (Q1) How consistent are the recovered community profiles across replicate mock communities?; (Q2) How does the choice of lysis buffer affect the recovery of the original community?; (Q3) How are community estimates affected by differing lysis times and homogenization? and (Q4) Is it possible to obtain adequate species abundance estimates through the use of biological spike‐ins? We show that estimates are quite variable across community replicates. In general, a mild lysis protocol is better at reconstructing species lists and approximate counts, while homogenization is better at retrieving biomass composition. Small insects are more likely to be detected in lysates, while some tough species require homogenization to be detected. Results are less consistent across biological replicates for lysates than for homogenates. Some species are associated with strong PCR amplification bias, which complicates the reconstruction of species counts. Yet, with adequate spike‐in data, species abundance can be determined with roughly 40% standard error for homogenates, and with roughly 50% standard error for lysates, under ideal conditions. In the latter case, however, this often requires species‐specific reference data, while spike‐in data generalize better across species for homogenates. We conclude that a non‐destructive, mild lysis approach shows the highest promise for the presence/absence description of the community, while also allowing future morphological or molecular work on the material. However, homogenization protocols perform better for characterizing community composition, in particular in terms of biomass.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimizing insect metabarcoding using replicated mock communities

Iwaszkiewicz‐Eggebrecht

Granqvist

Buczek

et al. 2023

Methods Ecol Evol

View full text Add to dashboard Cite

show abstract

“…Alternative sample preparations have been suggested to facilitate a posteriori morphological control, such as the removal of legs (Braukmann et al 2019) which is timeconsuming, or photographing bulk specimens which is a more scalable process but may be insufficient for accurate morphological identification. As for abundance information, optional molecular steps such as DNA spike-in of known mock communities and DNA concentration can also be implemented to infer taxa relative abundance from sequence read-based number correction (Luo et al 2022). Non-destructive DNA extraction buffer (e.g.…”

Section: Introductionmentioning

confidence: 99%

Non-destructive DNA metabarcoding of arthropods using collection medium from passive traps

Sire

Yáñez

Bézier

et al. 2023

Preprint

View full text Add to dashboard Cite

Background: Broad-scale monitoring of arthropods is often carried out with passive traps (e.g. Malaise traps) that can collect thousands of specimens per sample. The identification of individual specimens requires time and taxonomic expertise, limiting the geographical and temporal scale of research and monitoring studies. DNA metabarcoding of bulk-sample homogenates is faster and has been found to be efficient and reliable, but is destructive and prevents a posteriori validation of species occurrences and/or relative abundances. Non-destructive DNA metabarcoding from the collection medium has been applied in a limited number of studies, but further tests of efficiency are required in a broader range of circumstances to assess the consistency of the method. Methods: We quantified the detection rate of arthropod species when applying non-destructive DNA metabarcoding with a short (127-bp) fragment of mitochondrial COI on two types of passive traps and collection media: 1) water with monopropylene glycol (H2O-MPG) used in window-flight traps (WFT, 53 in total); 2) ethanol with monopropylene glycol (EtOH-MPG) used in Malaise traps (MT, 27 in total). We then compared our results with those obtained for the same samples using morphological identification (for WFTs) or destructive metabarcoding of bulk homogenate (for MTs). This comparison was applied as part of a larger study of arthropod species richness in silver fir (Abies alba) stands across a range of climate-induced tree dieback levels and forest management strategies. Results: Of the 53 H2O-MPG samples from WFTs, 16 produced no metabarcoding results, while the remaining 37 samples yielded 77 arthropod MOTUs in total. None of those MOTUs were shared species with the 389 morphological taxa (343 of which were Coleoptera) obtained from the same traps. Metabarcoding of 26 EtOH-MPG samples from MTs detected more arthropod MOTUs (233) and insect orders (11) than destructive metabarcoding of homogenate (146 MOTUs, 8 orders). Arachnida and Collembola were more diverse in EtOH-MPG samples, but Hymenoptera, Coleoptera and Lepidoptera were less represented than in homogenate. Overall, MOTU richness per trap similar for EtOH-MPG (21.81 MOTUs) than for homogenate (32.4 MOTUs). Arthropod communities from EtOH-MPG and homogenate metabarcoding were relatively distinct, with 162 MOTUs (53%) unique to the collection medium and only 71 MOTUs (23%) present in both treatments. Finally, collection medium did not reveal any significant changes in arthropod richness along a disturbance gradient in silver fir forests. We conclude that DNA metabarcoding of collection medium can be used to complement homogenate metabarcoding in inventories to favour the detection of soft-bodied arthropods like spiders.

show abstract

“…Given such uncertainty, the conservative interpretation has been to treat metabarcoding data as presence/absence until evidence for reliable correction factors can be obtained (Pawlowski et al, 2018). However, correction factors only allow changes in the relative abundance within a taxon to be estimated (Luo et al, 2022), and the prospect of calibrating for bias (McLaren et al, 2019) remains a distant prospect for those diverse communities where we gain most from DNA‐based identification.…”

Section: Introductionmentioning

confidence: 99%

Replicate DNA metabarcoding can discriminate seasonal and spatial abundance shifts in river macroinvertebrate assemblages

Буш

Compson

Rideout

et al. 2023

Molecular Ecology Resources

View full text Add to dashboard Cite

The delivery of consistent and accurate fine‐resolution data on biodiversity using metabarcoding promises to improve environmental assessment and research. Whilst this approach is a substantial improvement upon traditional techniques, critics note that metabarcoding data are suitable for establishing taxon occurrence, but not abundance. We propose a novel hierarchical approach to recovering abundance information from metabarcoding, and demonstrate this technique using benthic macroinvertebrates. To sample a range of abundance structures without introducing additional changes in composition, we combined seasonal surveys with fish‐exclusion experiments at Catamaran Brook in northern New Brunswick, Canada. Five monthly surveys collected 31 benthic samples for DNA metabarcoding divided between caged and control treatments. A further six samples per survey were processed using traditional morphological identification for comparison. By estimating the probability of detecting a single individual, multispecies abundance models infer changes in abundance based on changes in detection frequency. Using replicate detections of 184 genera (and 318 species) from metabarcoding samples, our analysis identified changes in abundance arising from both seasonal dynamics and the exclusion of fish predators. Counts obtained from morphological samples were highly variable, a feature that limited the opportunity for more robust comparison, and emphasizing the difficulty standard methods also face to detect changes in abundance. Our approach is the first to demonstrate how quantitative estimates of abundance can be made using metabarcoding, both among species within sites as well as within species among sites. Many samples are required to capture true abundance patterns, particularly in streams where counts are highly variable, but few studies can afford to process entire samples. Our approach allows study of responses across whole communities, and at fine taxonomic resolution. We discuss how ecological studies can use additional sampling to capture changes in abundance at fine resolution, and how this can complement broad‐scale biomonitoring using DNA metabarcoding.

show abstract

Extracting abundance information from DNA‐based data

Cited by 33 publications

References 142 publications

Optimizing insect metabarcoding using replicated mock communities

Optimizing insect metabarcoding using replicated mock communities

Non-destructive DNA metabarcoding of arthropods using collection medium from passive traps

Replicate DNA metabarcoding can discriminate seasonal and spatial abundance shifts in river macroinvertebrate assemblages

Contact Info

Product

Resources

About