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Understanding the phyllosphere microbiome assemblage in grape species (Vitaceae) with amplicon sequence data
Prashant Singh1, Sylvain Santoni2, Audrey Weber2
1AGAP, University of Montpellier, INRA-SupAgro, CIRAD, Montpellier, France. patrice.this@inra.fr.
Scientific Reports
|October 6, 2019
Summary
Grape species significantly impacts leaf microbes, with the growing year having an even greater effect on phyllosphere microbial communities. This study highlights the need for better normalization methods in microbiome research.
Area of Science:
- Microbiology
- Plant Science
- Genomics
Background:
- The phyllosphere microbiome influences plant health and performance.
- Previous studies focused on Vitis vinifera genotypes, neglecting the impact of different grape species.
- Understanding grape species' effect on phyllosphere microbes is crucial for viticulture.
Purpose of the Study:
- To investigate the impact of grape species on phyllosphere microbial community structure.
- To analyze the influence of the growing year on these microbial assemblages.
- To evaluate different normalization methods for microbiome data.
Main Methods:
- 16S and ITS profiling for bacterial and fungal characterization.
- Genus-level analysis of phyllosphere microflora from five grape species.
- Alpha and beta diversity analyses over two consecutive years.
- Comparison of normalization methods for high-throughput microbiome data.
Main Results:
- Significant effects of both grape species and growing year on microbial diversity were observed.
- The growing year had a more pronounced impact than grape species.
- One normalization method showed superiority, indicating a need for improved techniques.
- Differential taxa abundance analyses were influenced by normalization choices.
Conclusions:
- Grape species and environmental factors like the growing year shape the phyllosphere microbiome.
- Robust normalization is critical for accurate differential abundance analysis in microbiome studies.
- This research provides insights into grape-associated microbial ecology and data processing.
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