Raw sequence data and OTU tables of soil microorganisms obtained across a summit in the Lesotho highlands
De Maayer, Pieter (2023), Raw sequence data and OTU tables of soil microorganisms obtained across a summit in the Lesotho highlands , Dryad, Dataset, https://doi.org/10.5061/dryad.v6wwpzh0j
Mountain regions represent unique environments characterized by strong topographical diversity which drive climatic and environmental variability within these environments. These regions thus provide an opportunity to explore the relationships between various environmental factors and soil microorganisms. In this study, we investigated the impact of micro-topographical (i.e., north/south-facing slope aspects and flat plateau between them) variations on microbial diversity and community structures across a Lesotho mountain summit.
Raw sequenced data were generated using the Illumina MiSeq platform on DNA extracted from soil samples collected across the plateau, north- and south-facing slopes. This data was then used for taxonomic classification of the bacterial and fungal OTUs for the determination of the alpha- and beta-diversity across the slopes. These analyses revealed that a relatively greater bacterial and fungal diversity could be observed for the north-facing slope compared to the south-facing slope and plateau. While there was no difference in group variance of bacterial and fungal community structures across the plateau, north- and south-facing slopes.
Multiple comparison analyses were conducted to determine the impact of various abiotic and geographical factors on bacterial and fungal diversity and community structures. These analyses indicated that the slope aspect significantly affects bacterial and fungal community structures at this location. These results provide an original insight into soil microbial diversity in the Lesotho highlands and offer an opportunity to investigate the response of soil microorganisms to changes in environmental and climatic factors in highly variable mountain environments such as the Lesotho highlands.
The datasets include the raw sequences of joined paired-end reads reorientated in a uniform direction of bacteria and fungi obtained from the soil samples across a summit in the Lesotho highlands. DNA was initially extracted from the soil samples from which the partial bacterial 16S rRNA and fungal ITS2 gene amplicon were generated after which sequencing was performed using the Illumina Miseq platform by MR DNA (www.mrdnalab.co, Shallowater, Texas, USA). The raw sequence datasets still contain barcodes, errors, chimeras, and short read sequences and the paired-ends have just been joined.
The raw sequence datasets thus can be processed using the MR DNA analysis pipeline for any further analysis. Through this process barcodes need to be removed, sequences less than 150 base pairs need to be removed, quality filter trimmed sequences, and denoise sequences with errors to rectify them. Lastly, chimeric sequences need to be removed using the method USEARCH. These sequences are then classified into OTUs using BLASTn against a curated database. Raw sequenced datasets classified into OTUs are used for subsequent analysis for the determination of the taxonomic composition per sites and slopes across the sampled summit and for the determination of the alpha- and beta-diversity.
OTU tables were generated using the processed raw sequence datasets for bacteria and fungi. The sequences were classified on a basis of 97% sequence identity using BLASTn against a curated database derived from Ribosomal Database Project (www.rdp.cme.msu.edu) and NCBI (www.ncbi.nlm.gov). Sequences were classified into the taxonomic ranks of kingdom, phylum, class, order, family, genus, and species. Respective counts of each OTU per sample location were then calculated and provided for each OTU. OTU tables were then used for the determination of the alpha- and beta-diversity across the short scale of the summit in the Lesotho highlands using R v 3.6.1 (R Foundation for Statistical Computing; http://www.R-project.org) and RStudio (RStudio Team, 2014).
Raw sequence data can be handled with a fasta editor.
OTU tables can be opened using Microsoft Excel.
National Research Foundation, Award: NRF Masters Scholarship SFH180517331412