Shotgun metagenomics dataset of the core rhizo-microbiome of monoculture and soybean-precedent carrot
Abstract Objectives Carrot is a significant vegetable crop contributing to agricultural diversity and food security, but less is known about the core microbiome associated with its rhizosphere. More so, the effect of preceding crop and cropping history on the composition and diversity of carrot rhiz...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-04-01
|
| Series: | BMC Genomic Data |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12863-025-01320-7 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Abstract Objectives Carrot is a significant vegetable crop contributing to agricultural diversity and food security, but less is known about the core microbiome associated with its rhizosphere. More so, the effect of preceding crop and cropping history on the composition and diversity of carrot rhizo-microbiome remains largely unknown. With shotgun metagenomics, the study unveils how cropping systems direct rhizo-microbiome structure and functions, previously limited by other methods. Data description Metagenomic-DNA molecule was extracted from four replicates each (12 samples) of a distant bulk soil and the rhizosphere soils from monoculture and soybean-precedent carrots, with the Power soil® DNA Isolation kit. The DNA samples were subjected to Next Generation Sequencing using the Illumina Novaseq X Plus (PE 150) platform. Raw sequencing reads were assembled and annotated with MEGAHIT and LCA algorithms in MEGAN software respectively, before a quality control check was done with FASTP. CD-Hit was used to de-replicate the sequences and the removal of host genomic-DNA and contaminant sequences was done with Bowtie2. The clean sequence data, in FastQ files, were analyzed for taxonomic classification and functional diversity of the rhizosphere microbiome using the Micro_NR and KEGG database respectively. The findings provide insights into microbiome dynamics, with potential implications for sustainable agricultural practices. |
|---|---|
| ISSN: | 2730-6844 |