Extracting abundance information from DNA-based data

Luo, Mingjie; Ji, Yinqiu; Yu, Douglas W.

doi:10.1101/2022.01.06.475221

Cited by 6 publications

(10 citation statements)

References 98 publications

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“…In total, 286 arthropods were collected in Kunming, China (25°8′23″ N, 102°44′17″ E) (Luo et al, 2022 ). DNA was extracted from each individual using the DNeasy Blood & Tissue Kit (Qiagen).…”

Section: Methodsmentioning

confidence: 99%

Extracting abundance information from DNA‐based data

Luo

Warton

et al. 2022

Molecular Ecology Resources

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The accurate extraction of species‐abundance information from DNA‐based data (metabarcoding, metagenomics) could contribute usefully to diet analysis and food‐web reconstruction, 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, multiple sources of bias and noise in sampling and processing combine to inject error into DNA‐based data sets. To understand how to extract abundance information, it is useful to distinguish two concepts. (i) Within‐sample across‐species quantification describes relative species abundances in one sample. (ii) Across‐sample within‐species quantification describes how the abundance of each individual species varies from sample to sample, such as over a time series, an environmental gradient or different experimental treatments. First, we review the literature on methods to recover across‐species abundance information (by removing what we call “species pipeline biases”) and within‐species abundance information (by removing what we call “pipeline noise”). We argue that many ecological questions can be answered with just within‐species quantification, and we therefore demonstrate how to use a “DNA spike‐in” to correct for pipeline noise and recover within‐species abundance information. We also introduce a model‐based estimator that can be used on data sets without a physical spike‐in to approximate and correct for pipeline noise.

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Section: Methodsmentioning

confidence: 99%

Extracting abundance information from DNA‐based data

Luo

Warton

et al. 2022

Molecular Ecology Resources

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“…We referred to the number of OTUs as our measure of microbial richness and used the number of reads for each OTU as proportional abundance of each OTU in a community. Potentially systematic biases inherent in sample processing, amplification and sequencing, however, may affect the classification of OTUs and reads, reducing the utility of quantitative metrics (Amend et al, 2010; Luo et al, 2022). We assumed that such biases would be universal among samples, and that our estimates of microbial richness and composition should thus be semi‐quantitative and can only be compared among samples (Amend et al, 2010).…”

Section: Methodsmentioning

confidence: 99%

“…Recently, although an increasing number of studies have explored the relationships between biodiversity and ecosystem functioning in unmanipulated naturally assembled communities (Duffy et al, 2017;Jochum et al, 2020;van der Plas, 2019), such critical relationships have been strongly understudied in alpine and boreal moorland/peatland ecosystems, despite their potential as global carbon sinks (Chapin et al, 2000;Gorham, 1991). Due to potentially systematic biases on the classification of OTUs and read abundance, our estimates of microbial richness and composition should be semi-quantitative and results need to be interpreted with caution (Amend et al, 2010;Luo et al, 2022). Accordingly, we used such semi-quantitative measures across plots, which would result in universal bias.…”

Section: Teamentioning

confidence: 99%

Plant and microbial community composition jointly determine moorland multifunctionality

et al. 2022

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Understanding how ecosystem multifunctionality is maintained in naturally assembled communities is crucial, because human activities benefit from multiple functions and services of various ecosystems. However, the effects of above‐ and below‐ground biodiversity on ecosystem multifunctionality in alpine and boreal moorland ecosystems remain unclear despite their potential as global carbon sinks. Here we evaluated how ecosystem multifunctionality related to primary production and carbon sequestration, which are crucial for global climate regulation, is maintained in natural systems. We disentangled the relationships between diversity and composition of plants and soil microbes (fungi and bacteria) and ecosystem multifunctionality in subalpine moorlands in northern Japan. We found that microbial composition primarily regulated carbon sequestration, whereas plant taxonomic and functional composition were related to all functions considered. Plant and microbial α diversity (diversity within local communities) were not generally related to any single function, highlighting the important roles of specific plant and microbial taxa in determining ecosystem functioning. When single functions were aggregated to ecosystem multifunctionality within local communities, plant and microbial community composition rather than diversity regulated ecosystem multifunctionality. We further found that plant and bacterial taxonomic β diversity (taxonomic turnover between local communities) primarily regulated the dissimilarity of ecosystem multifunctionality between local communities. Synthesis. We provide observational evidence that plant and microbial community composition rather than diversity are essential for sustaining subalpine moorland multifunctionality. Furthermore, plant and bacterial β diversity enhance the dissimilarity of moorland multifunctionality. Our study provides novel insights into biodiversity–ecosystem multifunctionality relationships occurring in nature, and helps to sustain desirable ecosystem functioning to human society.

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“…Finally, the extrapolation of abundance data from metabarcode sequence output is complicated, but several promising approaches for deriving abundance data from standardised samples have been developed (e.g. Ji et al, 2020;Krehenwinkel et al, 2017;Luo, Ji, & Yu, 2022).…”

Section: Multiplex Barcoding and Whole Organism Community Metabarcodingmentioning

confidence: 99%

Collective and harmonised high throughput barcoding of insular arthropod biodiversity: toward a Genomic Observatories Network for islands

Emerson

Borges²,

Cardoso³

et al. 2022

Preprint

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Our current understanding of ecological and evolutionary processes underlying island biodiversity is heavily shaped by empirical data from plants and birds, although arthropods comprise the overwhelming majority of known animal species. This is due to inherent problems with obtaining high-quality arthropod data. Novel high throughput sequencing approaches are now emerging as powerful tools to overcome such limitations, and thus comprehensively address existing shortfalls in arthropod biodiversity data. Here we explore how, as a community, we might most effectively exploit these tools for comprehensive and comparable inventory and monitoring of insular arthropod biodiversity. We first review the strengths, limitations and potential synergies among existing approaches of high throughput barcode sequencing. We consider how this can be complemented with deep learning approaches applied to image analysis to study arthropod biodiversity. We then explore how these approaches can be implemented within the framework of an island Genomic Observatories Network (iGON) for the advancement of fundamental and applied understanding of island biodiversity. To this end, we identify seven island biology themes at the interface of ecology, evolution and conservation biology, within which collective and harmonised efforts in HTS arthropod inventory could yield significant advances in island biodiversity research.

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Extracting abundance information from DNA-based data

Cited by 6 publications

References 98 publications

Extracting abundance information from DNA‐based data

Extracting abundance information from DNA‐based data

Plant and microbial community composition jointly determine moorland multifunctionality

Collective and harmonised high throughput barcoding of insular arthropod biodiversity: toward a Genomic Observatories Network for islands

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