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Soil and coal

ABSTRACT: soil and coal Raw sequence reads

PROVIDER: PRJNA548311 | ENA |

REPOSITORIES: ENA

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Dataset's files

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			Action	DRS
	SRR9312780.fastq.gz	Fastqsanger.gz
	SRR9312790.fastq.gz	Fastqsanger.gz
	SRR9312781.fastq.gz	Fastqsanger.gz
	SRR9312791.fastq.gz	Fastqsanger.gz
	SRR9312782.fastq.gz	Fastqsanger.gz

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Buccal epithelial gene expression in smoky and smokeless coal users

Project description:Exposure to indoor air pollution generated from the combustion of solid fuels is a major risk factor for a spectrum of cardiovascular and respiratory diseases, including lung cancer. In Chinaâs rural counties of Xuanwei and Fuyuan, lung cancer rates are among the highest in the country. While the elevated disease risk in this population has been linked to the widespread usage of bituminous (smoky) coal as compared to anthracite (smokeless) coal, the underlying physiologic mechanism that smoky coal induces in comparison to other fuel types is unclear. As we have previously used airway gene-expression profiling to gain molecular insights into the physiologic effects of cigarette smoke, here we profiled the buccal epithelium of residents exposed to the burning of smoky and smokeless coal in order to understand the physiologic effects of solid fuels. Buccal mucosa scrapings were collected from healthy, non-smoking female residents of Xuanwei and Fuyuan counties who burn coal indoors. RNA was isolated and hybridized onto Affymetrix Human gene 1.0 ST GeneChips, capturing the gene-expression response of (n=26) smoky coal users and (n=9) smokeless coal users. 24-hour indoor personal exposure levels (PM2.5, Polycyclic Aromatic Hydrocarbons) were also captured during this sampling period.

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Soil Bacterial Community in Coal Mining Subsidence Analysis

Project description:Soil Bacterial Community in Coal Mining Subsidence Analysis Raw sequence reads

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RNA-Seq Analysis to confirm Different Transcriptomic Profiles of Soil-Derived Functional Module Consortia.

Project description:Purpose: Deconstructing the soil microbiome into reduced-complexity functional modules represents a novel method of microbiome analysis. The goals of this study are to confirm differences in transcriptomic patterns among five functional module consortia. Methods: mRNA profiles of 3 replicates each of functional module enrichments of soil inoculum in M9 media with either 1) xylose, 2) n-acetylglucosamine, 3) glucose and gentamycin, 4) xylan, or 5) pectin were generated by sequencing using an Illumina platform (GENEWIZ performed sequencing). Sequence reads that passed quality filters were aligned to a soil metagenome using Burrows Wheeler Aligner. Resulting SAM files were converted to raw reads using HTSeq, and annotated using Uniref90 or EGGNOG databases. Results: To reduce the size of the RNA-Seq counts table and increase its computational tractability, transcripts containing a minimum of 75 total counts, but no more than 3 zero counts, across the 15 samples were removed. The subsequent dataset was normalized using DESeq2, resulting in a dataset consisting of 6947 unique transcripts across the 15 samples, and 185,920,068 reads. We identified gene categories that were enriched in a sample type relative to the overall dataset using Fisher’s exact test. Conclusions: our dataset confirms that the functional module consortia generated from targeted enrichments of a starting soil inoculum had distinct functional trends by enrichment type.

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