4.1 Article Data Paper

Soil microbial diversity and functional profiling of a tropical rainforest of a highly dissected low hill from the upper Itaya river basin revealed by analysis of shotgun metagenomics sequencing data

Journal

DATA IN BRIEF
Volume 42, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.dib.2022.108205

Keywords

Peruvian amazon; Shotgun metagenomics; Soil microbiome; Tropical rainforest

Funding

  1. National Fund for Science, Technology and Innovation Research (FONDECYT)/National Council on Science, Technology, And Technological Innovation (CONCYTEC)
  2. World Bank [018-2018-FONDECYT/BM]

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This report presents shotgun metagenomics sequencing data from soils of a highly dissected low hill in the western Amazonia region, focusing on the sample collection, DNA purification, library preparation, and sequencing methods. The soils in this region are composed of moderately fertile sediments, but scientific information about soil microbial and functional diversity is still lacking.
The tropical rainforest of a highly dissected low hill from the upper Itaya river basin belongs to the western Amazonia region. Some investigations on the biodiversity of these rainforests were more focused on animals and plants diversity. The soils of this region are composed of moderately fertile sediments deposited recently from the initiation of the Andean orogenesis in the Miocene until now. However, scientific information about the soil microbial and functional diversity is still missing. This report presents shotgun metagenomics sequencing data from soils of this rainforest type. A composite loamy soil sample was collected from a primary forest, and metagenomic DNA was purified with standardized methods. Furthermore, libraries were prepared and paired-end sequenced on the Illumina NextSeq 550 platform. Raw Illumina paired-end reads have been uploaded and analysed in the Metagenomics RAST server (MG-RAST). The raw sequence data in fastq format is available at NCBI's Sequence Read Archive (SRA) with accession number SRX12846710. (C) 2022 Published by Elsevier Inc.

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