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Short communication
Characterization of the leaf microbiome from whole-genome sequencing data of the 3000 rice genomes project.
Ricardo Oliva
Corresponding Author
ORCiD: https://orcid.org/0000-0001-9517-5249
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at Rice.
Background: The crop microbial communities are shaped by interactions between the host, microbes and the environment, however, their relative contribution is beginning to be understood. Here, we explore these interactions in the leaf bacterial community across 3,024 rice accessions.
Findings: By using unmapped DNA sequencing reads as microbial reads, we characterized the structure of the rice bacterial microbiome. We identified central bacteria taxa that emerge as microbial “hubs” and may have an influence on the network of host-microbe interactions. We found regions in the rice genome that might control the assembly of these microbial hubs. To our knowledge this is one of the first studies that uses raw data from plant genome sequencing projects to characterize the leaf bacterial communities.
Conclusion: We showed, that the structure of the rice leaf microbiome is modulated by multiple interactions among host, microbes, and environment. Our data provide insight into the factors influencing microbial assemblage in the rice leaf and also opens the door for future initiatives to modulate rice consortia for crop improvement efforts.
Keywords
Oryza sativa, leaf microbiome, abundance network, GWAS, functional profile
Figure 1
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This is a list of supplementary files associated with this preprint. Click to download.
- Additionalfile1.pdf
Additional file 1: Figure S1: Generation of 3000 rice genomes dataset and pipeline for collecting the leaf microbiome. Figure S2: Growing location shapes the rice leaf microbiome diversity and composition. A-B Richness and Shannon index comparisons between accessions grown in China and Philippines; *P-value < 0.001. Kruskal-Wallis test. C Leaf microbiome composition of rice accessions grown in China and Philippines. The inner position of the sunburst chart represents taxonomic hierarchy phylum and the outer position represents Genus. The chart shows abundance higher than 1% determined as the relative abundance across all samples. The black line highlights the unique genera for each environment. The figure showed the average relative abundance across all accessions from each location using only the classified reads. Figure S3: Leaf microbiome network and functional profile is conserved across growing locations. A Microbial ecological network from China and the Philippines with abundant genera present in at least 50% of all samples. The colors represent the seven modules of each network. Each node represents a genus and the circle size indicates betweenness centrality increment. The key microbial hubs are Clostridium (Clo), Mycoplasma (My) and Helicobacter (H). Other hubs in China are Spiroplasma (Sa), Azospirillum (Am), Prochlorococcus (Pr), Sphingobium (Sm). For the Philippines, important hubs are Bacillus (Ba), Pseudomonas (P), and Azotobacter (A). The properties of the network are number of edges, number of nodes or genera, average degree and modularity. Only for the network analysis the genus counts were center-log-transformed. B KEGG level 2 pathways with more than 1% relative abundance in accessions grown in China and the Philippines. NS no significant, Wilcoxon rank-sum test = 6869, P-value = 0.421. Figure S4. Relationships between significant SNPs and hubs abundances represented as box plots. A significant difference using the average of the 12 hubs abundances. B Significant differences using the hubs Mycoplasma, Clostridium and Bacillus abundances. All box plots have an FDR adjusted p-value < 0.05 using a pairwise Wilcoxon test. SNPs nomenclature are chromosome and position. Figure S5. Gene ontology enrichment analysis with the genes from the haploblocks. Bars indicate the frequency of the three GO categories was calculated over the 120 genes. The colors in the bars indicate the -log(p-value) for each GO term.
- additionalfile2.pdf
Additional file 2: Methods
- supplementaltablesV4.xls
Additional file 3: Table S1. List of 3K-RGP rice accessions with number of reads that did not map to the rice genomes (unmapped reads). Table S2. Phyla and genera composition of the 3K RGP microbiome. Table S3. Significant genera that contribute to the differences between accessions grown in China and accessions grown in Philippines. Table S4. Quantitative PCR validation of metagenomic analysis using 17 rice accessions from the 3K-RGP project. The table indicate the genera used for the experiments, followed by the primer sequences, the reference for the primers, the qPCR results (delta Ct and standard deviation). Then the list of the 17 accessions and their groups are indicated. Table S5. Co-abundance network values for the most abundant genera in the 3KRGP microbiome. Table S6. Co-abundance network modules with the most connected microbes. Table S7. Metabolic pathways predicted by Vikodak based on KEGG levels 1 and 3. Table S8: Significant signals from the genome wide association analysis (GWAS). Table S9: Description of haplotype blocks for each significant SNP, number of associated candidate genes and the QTLs that match to the same region.
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CURRENT STATUS: Published
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Posted 25 Sep, 2020
Published
On 09 Oct, 2020
No community comments so far
Editorial decision: Accept
On 30 Sep, 2020
Editor assigned
On 24 Sep, 2020
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On 23 Sep, 2020
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On 02 Aug, 2020
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On 30 Jul, 2020
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On 29 Jul, 2020
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Received 16 Jul, 2020
Editorial decision: Major revision
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Received 08 Jul, 2020
Reviewer #2 agreed
On 28 Jun, 2020
Reviewer #1 agreed
On 18 Jun, 2020
Reviewers invited
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Subject Areas
Plant Molecular Biology and Genetics
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This preprint is under consideration at Rice. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Short communication
Characterization of the leaf microbiome from whole-genome sequencing data of the 3000 rice genomes project.
Ricardo Oliva
Corresponding Author
ORCiD: https://orcid.org/0000-0001-9517-5249
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
Version 3
Posted 25 Sep, 2020
Published
On 09 Oct, 2020
No community comments so far
Editorial decision: Accept
On 30 Sep, 2020
Editor assigned
On 24 Sep, 2020
Submission checks complete
On 23 Sep, 2020
Editor invited
On 23 Sep, 2020
No comments provided
Reviewer #1 agreed
On 02 Aug, 2020
Editor assigned
On 30 Jul, 2020
Reviewers invited
Invitations sent on 30 Jul, 2020
Submission checks complete
On 29 Jul, 2020
Editor invited
On 29 Jul, 2020
No comments provided
Review #2 received
Received 16 Jul, 2020
Editorial decision: Major revision
On 16 Jul, 2020
Review #1 received
Received 08 Jul, 2020
Reviewer #2 agreed
On 28 Jun, 2020
Reviewer #1 agreed
On 18 Jun, 2020
Reviewers invited
Invitations sent on 17 Jun, 2020
Editor assigned
On 16 Jun, 2020
First submitted
On 15 Jun, 2020
Submission checks complete
On 15 Jun, 2020
Editor invited
On 15 Jun, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Plant Molecular Biology and Genetics
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at Rice.
Background: The crop microbial communities are shaped by interactions between the host, microbes and the environment, however, their relative contribution is beginning to be understood. Here, we explore these interactions in the leaf bacterial community across 3,024 rice accessions.
Findings: By using unmapped DNA sequencing reads as microbial reads, we characterized the structure of the rice bacterial microbiome. We identified central bacteria taxa that emerge as microbial “hubs” and may have an influence on the network of host-microbe interactions. We found regions in the rice genome that might control the assembly of these microbial hubs. To our knowledge this is one of the first studies that uses raw data from plant genome sequencing projects to characterize the leaf bacterial communities.
Conclusion: We showed, that the structure of the rice leaf microbiome is modulated by multiple interactions among host, microbes, and environment. Our data provide insight into the factors influencing microbial assemblage in the rice leaf and also opens the door for future initiatives to modulate rice consortia for crop improvement efforts.
Figure 1
Figure 2
Figure 3