Proper experimental design requires randomization/balancing of molecular ecology experiments

Bálint, Miklós; Márton, Orsolya; Schatz, Marlene; Duering, Rolf-Alexander; Grossart, Hans‐Peter

doi:10.1101/109280

Cited by 3 publications

(3 citation statements)

References 22 publications

(16 reference statements)

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“…Sequence reads were processed using the OBITools software suite (Boyer et al, ), from pairwise alignment to clustering (Bálint, Márton, Schatz, Düring, & Grossart, ; Taberlet, Bonin, Zinger, & Coissac, ), following procedures detailed in the Supplementry Methods (see Supporting Information). Particular care was taken to remove artefacts resulting from PCR and sequencing errors, including the use of “obigrep” to eliminate sequences with a length outside the expected metabarcode size (310–316), and sequences occurring just once across the data set.…”

Section: Methodsmentioning

confidence: 99%

Have the cake and eat it: Optimizing nondestructive DNA metabarcoding of macroinvertebrate samples for freshwater biomonitoring

Martins

Galhardo

Filipe

et al. 2019

Molecular Ecology Resources

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DNA metabarcoding can contribute to improving cost‐effectiveness and accuracy of biological assessments of aquatic ecosystems, but significant optimization and standardization efforts are still required to mainstream its application into biomonitoring programmes. In assessments based on freshwater macroinvertebrates, a key challenge is that DNA is often extracted from cleaned, sorted and homogenized bulk samples, which is time‐consuming and may be incompatible with sample preservation requirements of regulatory agencies. Here, we optimize and evaluate metabarcoding procedures based on DNA recovered from 96% ethanol used to preserve field samples and thus including potential PCR inhibitors and nontarget organisms. We sampled macroinvertebrates at five sites and subsampled the preservative ethanol at 1 to 14 days thereafter. DNA was extracted using column‐based enzymatic (TISSUE) or mechanic (SOIL) protocols, or with a new magnetic‐based enzymatic protocol (BEAD), and a 313‐bp COI fragment was amplified. Metabarcoding detected at least 200 macroinvertebrate taxa, including most taxa detected through morphology and for which there was a reference barcode. Better results were obtained with BEAD than SOIL or TISSUE, and with subsamples taken 7–14 than 1–7 days after sampling, in terms of DNA concentration and integrity, taxa diversity and matching between metabarcoding and morphology. Most variation in community composition was explained by differences among sites, with small but significant contributions of subsampling day and extraction method, and negligible contributions of extraction and PCR replication. Our methods enhance reliability of preservative ethanol as a potential source of DNA for macroinvertebrate metabarcoding, with a strong potential application in freshwater biomonitoring.

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Section: Methodsmentioning

confidence: 99%

Have the cake and eat it: Optimizing nondestructive DNA metabarcoding of macroinvertebrate samples for freshwater biomonitoring

Martins

Galhardo

Filipe

et al. 2019

Molecular Ecology Resources

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“…We randomized the order of all samples prior to DNA extraction to prevent sampling biases (Bálint, Márton, Schatz, Düring, & Grossart, ). We used 300 mg of each root and soil sample for DNA extraction.…”

Section: Methodsmentioning

confidence: 99%

Spatial patterns of pathogenic and mutualistic fungi across the elevational range of a host plant

et al. 2018

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Fungi are both agents of disease and mutualistic partners of plants. Previous studies have tested the effects of abiotic or biotic factors on plant‐associated fungal communities in isolation. However, to better understand patterns of plant–fungal associations, the combined effects of abiotic and biotic drivers across environmental gradients may be important. We investigated the effects of temperature, pH, soil moisture, vegetation cover and distance to host plant on the occurrence and abundance of fungi associated with Swiss stone pine (Pinus cembra). We did this by DNA metabarcoding 288 soil samples taken across and beyond the elevation range of P. cembra (i.e. 1,850–2,250 m a.s.l.) in two valleys in the Swiss Alps. We modelled the effects of abiotic and biotic factors on DNA read abundance of pathogenic and mutualistic fungal operational taxonomic units (OTUs) associated with P. cembra. We also tested whether abiotic and biotic factors differentially affected fungi of varying host specificity (i.e. host generalists, host specialists). We found that the occurrences of both host generalist and specialist fungi exceeded the current elevational range of their host plant. Abiotic factors had only minor effects on the abundances of all fungal OTUs. However, we found positive effects of the host plant on the abundance of a host specialist pathogenic fungus, providing support for a Janzen–Connell effect of high pathogen accumulation close to conspecific host plants. We also found a positive response to the host plant in a specialist ectomycorrhizal fungus, suggesting an “inverse” Janzen–Connell effect. Synthesis. Our findings imply that negative distance dependence shapes not only the distribution of host‐specific fungal pathogens, but also host‐specific fungal mutualists. We conclude that the occurrence of both pathogenic and mutualistic fungi beyond the current elevational range of host plants may determine their potential range shifts under projected climate warming.

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“…In a second PCR, primers containing part of the Illumina sequencing primer, an 8 bp nucleotide index as well as the Illumina plate adapter were amplified to both ends of the amplicons. This was done similarly as described in Bálint et al (2017) and following the Illumina 16S metabarcoding protocol (Illumina, 2016). This way the amplicons contain a unique 8 bp index on each end, which eliminates index jumping events during the library preparation (Schnell, Bohmann, & Gilbert, 2015).…”

Section: Dna Extraction Pcr and Sequencingmentioning

confidence: 99%

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Supplemental Information 1: Supplemental Information: Figures and Tables

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Understanding the genetic variability and dispersal capabilities of plant pathogens is important to better predict pathogen spread and virulence, especially under global change conditions. The outcome of host-pathogen interactions directly depends on the dispersal capacity of the pathogens, on environmental conditions, and disease resistance of the host. Here, we analysed the distribution of finely resolved phylogenetic lineages of a poplar-specific fungal pathogen (Sphaerulina populicola) in western North America, across a 3,200 km latitudinal gradient of the host tree's (Populus balsamifera) distribution. We specifically tested whether dispersal limitations or environmental filters limit the spread and establishment of the pathogen into new areas. We assessed the genetic diversity of the pathogen with ITS1 oligotypes, recorded by metabarcoding leaf-associated fungal communities. The distribution of the recorded 16 S. populicola oligotypes showed no geographic patterns, indicating the lack of dispersal limitation of the pathogen throughout the investigated area. Climatic conditions also did not seem to restrict the occurrence and abundance of the pathogen oligotypes. Finally, we found strong variation in oligotype presence within single localities, which may suggest the importance of biotic factors in regulating the infection of this well-dispersing fungal pathogen. Our interpretation implies that the future prevalence of S. populicola-related disease will likely depend on the dynamics of host-pathogen interactions, since the pathogen does not seem dispersallimited at a continental scale.

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Proper experimental design requires randomization/balancing of molecular ecology experiments

Cited by 3 publications

References 22 publications

Have the cake and eat it: Optimizing nondestructive DNA metabarcoding of macroinvertebrate samples for freshwater biomonitoring

Have the cake and eat it: Optimizing nondestructive DNA metabarcoding of macroinvertebrate samples for freshwater biomonitoring

Spatial patterns of pathogenic and mutualistic fungi across the elevational range of a host plant

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