Dataset Information

Dataset of computed N-value and factual N-value traced for Soil Subsurface Profiling.

ABSTRACT: Soil requires load bearing impact assessment for stability. Therefore, this study aims to utilize the multi-channel analysis surface wave (MASW) for soil subsurface investigation and profiling around Peninsular Malaysia. The standard penetration test (SPT) was conducted for comparison between factual N-value and computed N-value from shear wave velocity (Vs ) obtained from MASW using the Imai and Tonouchi equation. The correlation coefficient (R) and coefficient of determination, (R2 ), showed strong relationship between factual N-value and computed N-value. The model of Vs and factual N-value data distribution is non-normal but the analyzed relationship shows a significant level of p-value < 0.05. The R2 for each location of Vs -N-value relationship are ranging from 0.5 to 0.9.

SUBMITTER: Jusoh H

PROVIDER: S-EPMC7327803 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Dataset of computed N-value and factual N-value traced for Soil Subsurface Profiling.

Jusoh Hisyam H Sabariah Binti Abd Manan Teh T Beddu Salmia S Osman Syed Baharom Syed SBS Jusoh Muhammad Noor Hazwan MNH Mohtar Wan Hanna Melini Wan WHMW Khan Taimur T Kamal Nur Liyana Mohd NLM Ghanim Abdulnoor A AA Ismail Marzuki M Abdullah Mohd Tajuddin MT

Data in brief 20200616

Soil requires load bearing impact assessment for stability. Therefore, this study aims to utilize the multi-channel analysis surface wave (MASW) for soil subsurface investigation and profiling around Peninsular Malaysia. The standard penetration test (SPT) was conducted for comparison between factual N-value and computed N-value from shear wave velocity (Vs ) obtained from MASW using the Imai and Tonouchi equation. The correlation coefficient (R) and coeffi ...[more]

PMID: 32637485

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Project description:While most bacterial and archaeal taxa living in surface soils remain undescribed, this problem is exacerbated in deeper soils, owing to the unique oligotrophic conditions found in the subsurface. Additionally, previous studies of soil microbiomes have focused almost exclusively on surface soils, even though the microbes living in deeper soils also play critical roles in a wide range of biogeochemical processes. We examined soils collected from 20 distinct profiles across the United States to characterize the bacterial and archaeal communities that live in subsurface soils and to determine whether there are consistent changes in soil microbial communities with depth across a wide range of soil and environmental conditions. We found that bacterial and archaeal diversity generally decreased with depth, as did the degree of similarity of microbial communities to those found in surface horizons. We observed five phyla that consistently increased in relative abundance with depth across our soil profiles: Chloroflexi, Nitrospirae, Euryarchaeota, and candidate phyla GAL15 and Dormibacteraeota (formerly AD3). Leveraging the unusually high abundance of Dormibacteraeota at depth, we assembled genomes representative of this candidate phylum and identified traits that are likely to be beneficial in low-nutrient environments, including the synthesis and storage of carbohydrates, the potential to use carbon monoxide (CO) as a supplemental energy source, and the ability to form spores. Together these attributes likely allow members of the candidate phylum Dormibacteraeota to flourish in deeper soils and provide insight into the survival and growth strategies employed by the microbes that thrive in oligotrophic soil environments.IMPORTANCE Soil profiles are rarely homogeneous. Resource availability and microbial abundances typically decrease with soil depth, but microbes found in deeper horizons are still important components of terrestrial ecosystems. By studying 20 soil profiles across the United States, we documented consistent changes in soil bacterial and archaeal communities with depth. Deeper soils harbored communities distinct from those of the more commonly studied surface horizons. Most notably, we found that the candidate phylum Dormibacteraeota (formerly AD3) was often dominant in subsurface soils, and we used genomes from uncultivated members of this group to identify why these taxa are able to thrive in such resource-limited environments. Simply digging deeper into soil can reveal a surprising number of novel microbes with unique adaptations to oligotrophic subsurface conditions.

Project description:Sago palm (Metroxylon sagu Rottb.) is an important agricultural starch-producing palm that contributes to Malaysia's economics, especially in the State of Sarawak, Malaysian Borneo. In this palm tree, the central part of the plant storage-starch. Under normal condition, sago palm develop its trunk after 4-5 years being planted. However, sago palms planted on deep-peat soil failed to develop their trunk even after 17 years of being planted. This phenomenon is known as 'non-trunking', which eliminates the economic value of the palms. Numerous research has been done to address the phenomenon, but the molecular mechanisms of sago palm responding toward the responsible stresses are still lacking. Therefore, in this study, leaf samples were collected from trunking (normal) and non-trunking sago palms planted on peat soil for total RNA extraction, followed by next-generation sequencing using the BGISEQ-500 platform. The raw reads were cleaned, and de novo assembled using TRINITY software package. A total of 40.11 Gb bases were sequenced from the sago palm leaf samples. The assembled sequence produced 102,447 unigenes, with N50 score 1809 bp and GC ratio of 44.34%. The alignment of unigenes with seven functional databases (NR, NT, GO, KOG, KEGG, SwissProt and InterPro) resulted in the annotation of 65,523 (63.96%) unigenes. Functional annotation results in the detection of 46,335 coding DNA sequences by Transdecoder. A total of 30,039 simple-sequence repeats distributed on 21,676 unigenes were detected using Primer3 software, and 2355 transcription factor coding unigenes were predicted using getorf and hmmseach software. This work is registered under NCBI BioProject PRJNA781491. The raw RNA sequencing data are available in Sequence Read Archive (SRA) database with accession numbers SRX13165895, SRX13165896, SRX13165897, SRX13165898, SRX13165899, and SRX13165900. Gene expression and annotation information are accessible in public functional genomics data repository Gene Expression Omnibus (GEO) with accession number GSE189085.

Dataset Information

Dataset of computed N-value and factual N-value traced for Soil Subsurface Profiling.

Publications

Dataset of computed N-value and factual N-value traced for Soil Subsurface Profiling.

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