Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Metabarcoding on both environmental DNA and RNA highlights differences between fungal communities sampled in different habitats

View through CrossRef
In recent years, metabarcoding has become a key tool to describe microbial communities from natural and artificial environments. Thanks to its high throughput nature, metabarcoding efficiently explores microbial biodiversity under different conditions. It can be performed on environmental (e)DNA to describe so-called total microbial community, or from environmental (e)RNA to describe active microbial community. As opposed to total microbial communities, active ones exclude dead or dormant organisms. For what concerns Fungi, which are mostly filamentous microorganisms, the relationship between DNA-based (total) and RNA-based (active) communities is unclear. In the present study, we evaluated the consequences of performing metabarcoding on both soil and wood-extracted eDNA and eRNA to delineate molecular operational taxonomic units (MOTUs) and differentiate fungal communities according to the environment they originate from. DNA and RNA-based communities differed not only in their taxonomic composition, but also in the relative abundances of several functional guilds. From a taxonomic perspective, we showed that several higher taxa are globally more represented in either “active” or “total” microbial communities. We also observed that delineation of MOTUs based on their co-occurrence among DNA and RNA sequences highlighted differences between the studied habitats that were overlooked when all MOTUs were considered, including those identified exclusively by eDNA sequences. We conclude that metabarcoding on eRNA provides original functional information on the specific roles of several taxonomic or functional groups that would not have been revealed using eDNA alone.
Title: Metabarcoding on both environmental DNA and RNA highlights differences between fungal communities sampled in different habitats
Description:
In recent years, metabarcoding has become a key tool to describe microbial communities from natural and artificial environments.
Thanks to its high throughput nature, metabarcoding efficiently explores microbial biodiversity under different conditions.
It can be performed on environmental (e)DNA to describe so-called total microbial community, or from environmental (e)RNA to describe active microbial community.
As opposed to total microbial communities, active ones exclude dead or dormant organisms.
For what concerns Fungi, which are mostly filamentous microorganisms, the relationship between DNA-based (total) and RNA-based (active) communities is unclear.
In the present study, we evaluated the consequences of performing metabarcoding on both soil and wood-extracted eDNA and eRNA to delineate molecular operational taxonomic units (MOTUs) and differentiate fungal communities according to the environment they originate from.
DNA and RNA-based communities differed not only in their taxonomic composition, but also in the relative abundances of several functional guilds.
From a taxonomic perspective, we showed that several higher taxa are globally more represented in either “active” or “total” microbial communities.
We also observed that delineation of MOTUs based on their co-occurrence among DNA and RNA sequences highlighted differences between the studied habitats that were overlooked when all MOTUs were considered, including those identified exclusively by eDNA sequences.
We conclude that metabarcoding on eRNA provides original functional information on the specific roles of several taxonomic or functional groups that would not have been revealed using eDNA alone.

Related Results

Echinococcus granulosus in Environmental Samples: A Cross-Sectional Molecular Study
Echinococcus granulosus in Environmental Samples: A Cross-Sectional Molecular Study
Abstract Introduction Echinococcosis, caused by tapeworms of the Echinococcus genus, remains a significant zoonotic disease globally. The disease is particularly prevalent in areas...
Genome wide hypomethylation and youth-associated DNA gap reduction promoting DNA damage and senescence-associated pathogenesis
Genome wide hypomethylation and youth-associated DNA gap reduction promoting DNA damage and senescence-associated pathogenesis
Abstract Background: Age-associated epigenetic alteration is the underlying cause of DNA damage in aging cells. Two types of youth-associated DNA-protection epigenetic mark...
Detection of Multiple Types of Cancer Driver Mutations Using Targeted RNA Sequencing in NSCLC
Detection of Multiple Types of Cancer Driver Mutations Using Targeted RNA Sequencing in NSCLC
ABSTRACTCurrently, DNA and RNA are used separately to capture different types of gene mutations. DNA is commonly used for the detection of SNVs, indels and CNVs; RNA is used for an...
Abstract P1-05-23: Utilities and challenges of RNA-Seq based expression and variant calling in a clinical setting
Abstract P1-05-23: Utilities and challenges of RNA-Seq based expression and variant calling in a clinical setting
Abstract Introduction Variant calling based on DNA samples has been the gold standard of clinical testing since the advent of Sanger sequencing. The u...
B-247 BLADE-R: streamlined RNA extraction for clinical diagnostics and high-throughput applications
B-247 BLADE-R: streamlined RNA extraction for clinical diagnostics and high-throughput applications
Abstract Background Efficient nucleic acid extraction and purification are crucial for cellular and molecular biology research, ...
GEOSPATIAL ASPECTS OF FINANCIAL CAPACITY OF TERRITORIAL COMMUNITIES OF TERNOPIL REGION
GEOSPATIAL ASPECTS OF FINANCIAL CAPACITY OF TERRITORIAL COMMUNITIES OF TERNOPIL REGION
In the article geospatial aspects of the financial capacity of territorial communities of Ternopil region are described. The need to conduct such a study has been updated, since no...
Inferring fungal growth rates from optical density data
Inferring fungal growth rates from optical density data
AbstractQuantifying fungal growth underpins our ability to effectively treat severe fungal infections. Current methods quantify fungal growth rates from time-course morphology-spec...

Back to Top