Elsevier

Data in Brief

Volume 30, June 2020, 105625
Data in Brief

Data Article
Metagenomic 16S rDNA amplicon data on bacterial diversity profiling and its predicted metabolic functions of varillales in Allpahuayo-Mishana National Reserve

https://doi.org/10.1016/j.dib.2020.105625Get rights and content
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Abstract

The white-sands forests or varillales of the Peruvian Amazon are characterized by their distinct physical characteristics, patchy distribution, and endemism [1, 2]. Much research has been conducted on the specialized plant and animal communities that inhabit these ecosystems, yet their soil microbiomes have yet to be studied. Here we provide metagenomic 16S rDNA amplicon data of soil microbiomes from three types of varillales in Allpahuayo-Mishana National Reserve near Iquitos, Peru. Composite soil samples were collected from very low varillal, high-dry varillal, and high-wet varillal. Purified metagenomic DNA was used to prepare and sequence 16S rDNA metagenomic libraries on the Illumina MiqSeq platform. Raw paired-endsequences were analyzed using the Metagenomics RAST server (MG-RAST) and Parallel-Meta3 software and revealed the existence of a high percentage of undiscovered sequences, potentially indicating specialized bacterial communities in these forests. Also, were predicted several metabolic functions in this dataset. The raw sequence data in fastq format is available in the public repository Discover Mendeley Data (https://data.mendeley.com/datasets/syktzxcnp6/2). Also, is available at NCBI's Sequence Read Archive (SRA) with accession numbers SRX7891206 (very low varillal), SRX7891207 (high-dry varillal), and SRX7891208 (high-wet varillal).

Keywords

Metagenomics
16S rRNA
Peruvian amazon
Soil microbiome
Tropical forest
Varillales
White-sand forests

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