Metacoder: An R Package for Visualization and Manipulation of Community Taxonomic Diversity Data

Foster, Zachary; Sharpton, Thomas J.; Grünwald, Niklaus J.

doi:10.1101/071019

Cited by 93 publications

(96 citation statements)

References 21 publications

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“…Diversity was calculated using Shannon and Simpson indices, and then transformed to effective species numbers (Hill numbers 1 and 2, respectively; Jost, ). Heat trees representing community structure of each dataset, showing OTU richness and abundances across fungal lineages, were built using package M etacoder v.0.1.3 (Foster et al ., ). Assessments of richness and diversity variation across samples or in relation to ecological factors were done by means of linear regression analyses, after logarithmic or square‐root transformation of strongly skewed variables.…”

Section: Methodsmentioning

confidence: 97%

Facultative root‐colonizing fungi dominate endophytic assemblages in roots of nonmycorrhizal Microthlaspi species

et al. 2017

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There is increasing knowledge on the diversity of root-endophytic fungi, but limited information on their lifestyles and dependence on hosts hampers our understanding of their ecological functions. We compared diversity and biogeographical patterns of cultivable and noncultivable root endophytes to assess whether their occurrence is determined by distinct ecological factors. The endophytic diversity in roots of nonmycorrhizal Microthlaspi spp. growing across Europe was assessed using high-throughput sequencing (HTS) and compared with a previous dataset based on cultivation of endophytes from the same root samples. HTS revealed a large fungal richness undetected by cultivation, but which largely comprised taxa with restricted distributions and/or low representation of sequence reads. Both datasets coincided in a consistent high representation of widespread endophytes within orders Pleosporales, Hypocreales and Helotiales, as well as similar associations of community structure with spatial and environmental conditions. Likewise, distributions of particular endophytes inferred by HTS agreed with cultivation data in suggesting individual ecological preferences. Our findings support that Microthlaspi spp. roots are colonized mostly by saprotrophic and likely facultative endophytes, and that differential niche preferences and distribution ranges among fungi importantly drive the assembly of root-endophytic communities.

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Section: Methodsmentioning

confidence: 97%

Facultative root‐colonizing fungi dominate endophytic assemblages in roots of nonmycorrhizal Microthlaspi species

et al. 2017

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“…Briefly, we compared the observed dissimilarity matrix (Bray‐Curtis dissimilarity) against a matrix for climate (Euclidean distance along climatePC1) or NDVI (Euclidean distance between NDVI value at time of sampling) effects while controlling for the effect of geographical distances (distance in Km). Taxonomic‐based pairwise comparisons of microbial communities between each of the three geographical regions were tested in r ‐package Metacoder (Foster, Sharpton, & Grünwald, ) with Wilcoxon rank‐sum test followed by a Benjamini‐Hochberg correction for multiple testing (Benjamini & Hochberg, ).…”

Section: Methodsmentioning

confidence: 99%

31° South: The physiology of adaptation to arid conditions in a passerine bird

et al. 2019

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Arid environments provide ideal ground for investigating the mechanisms of adaptive evolution. High temperatures and low water availability are relentless stressors for many endotherms, including birds; yet birds persist in deserts. While physiological adaptation probably involves metabolic phenotypes, the underlying mechanisms (plasticity, genetics) are largely uncharacterized. To explore this, we took an intraspecific approach that focused on a species that is resident over a mesic to arid gradient, the Karoo scrub‐robin (Cercotrichas coryphaeus). Specifically, we integrated environmental (climatic and primary productivity), physiological (metabolic rates: a measure of energy expenditure), genotypic (genetic variation underlying the machinery of energy production) and microbiome (involved in processing food from where energy is retrieved) data, to infer the mechanism of physiological adaptation. We that found the variation in energetic physiology phenotypes and gut microbiome composition are associated with environmental features as well as with variation in genes underlying energy metabolic pathways. Specifically, we identified a small list of candidate adaptive genes, some of them with known ties to relevant physiology phenotypes. Together our results suggest that selective pressures on energetic physiology mediated by genes related to energy homeostasis and possibly microbiota composition may facilitate adaptation to local conditions and provide an explanation to the high avian intraspecific divergence observed in harsh environments.

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“…For each module, we created a list of the top 20 genes ranked by gene significance (a value calculated in wgcna that indicates the biological significance of a module gene with respect to the explanatory variable of interest). We used unique GO terms associated with the top 20 genes to construct a network of GO terms for each module, and the metacoder package (Foster, Sharpton, & Grünwald, ) to visualize networks in R . We pruned internal nodes from each network for ease of visualization.…”

Section: Methodsmentioning

confidence: 99%

Among‐family variation in survival and gene expression uncovers adaptive genetic variation in a threatened fish

et al. 2019

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Variation in among‐family transcriptional responses to different environmental conditions can help to identify adaptive genetic variation, even prior to a selective event. Coupling differential gene expression with formal survival analyses allows for the disentanglement of treatment effects, required for understanding how individuals plastically respond to environmental stressors, from the adaptive genetic variation responsible for differential survival. We combined these two approaches to investigate responses to an emerging conservation issue, thiamine (vitamin B1) deficiency, in a threatened population of Atlantic salmon (Salmo salar). Thiamine is an essential vitamin that is increasingly limited in many ecosystems. In Lake Champlain, Atlantic salmon cannot acquire thiamine in sufficient quantities to support natural reproduction; fertilized eggs must be reared in hatcheries and treated with supplemental thiamine. We evaluated transcriptional responses (via RNA sequencing) to thiamine treatment across families and found 3,616 genes differentially expressed between control (no supplemental thiamine) and treatment individuals. Fewer genes changed expression equally across families (i.e., additively) than exhibited genotype × environment interactions in response to thiamine. Differentially expressed genes were related to known physiological effects of thiamine deficiency, including oxidative stress, cardiovascular irregularities and neurological abnormalities. We also identified 1,446 putatively adaptive genes that were strongly associated with among‐family survival in the absence of thiamine treatment, many of which related to neurogenesis and visual perception. Our results highlight the utility of coupling RNA sequencing with formal survival analyses to identify candidate genes that underlie the among‐family variation in survival required for an adaptive response to natural selection.

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Metacoder: An R Package for Visualization and Manipulation of Community Taxonomic Diversity Data

Cited by 93 publications

References 21 publications

Facultative root‐colonizing fungi dominate endophytic assemblages in roots of nonmycorrhizal Microthlaspi species

Facultative root‐colonizing fungi dominate endophytic assemblages in roots of nonmycorrhizal Microthlaspi species

31° South: The physiology of adaptation to arid conditions in a passerine bird

Among‐family variation in survival and gene expression uncovers adaptive genetic variation in a threatened fish

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