Project description:Metagenome data from soil samples were collected at 0 to 10cm deep from 2 avocado orchards in Channybearup, Western Australia, in 2024. Amplicon sequence variant (ASV) tables were constructed based on the DADA2 pipeline with default parameters.
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.
Project description:Reforestation is effective in restoring ecosystem functions and enhancing ecosystem services of degraded land. The three most commonly employed reforestation methods of natural reforestation, artificial reforestation with native Masson pine (Pinus massoniana Lamb.), and introduced slash pine (Pinus elliottii Engelm.) plantations were equally successful in biomass yield in southern China. However, it is not known if soil ecosystem functions, such as nitrogen (N) cycling, are also successfully restored. Here, we employed a functional microarray to illustrate soil N cycling. The composition and interactions of N-cycling genes in soils varied significantly with reforestation method. Natural reforestation had more superior organization of N-cycling genes, and higher functional potential (abundance of ammonification, denitrification, assimilatory, and dissimilatory nitrate reduction to ammonium genes) in soils, providing molecular insight into the effects of reforestation.
Project description:The goals of this study are to use Next-generation sequencing (NGS) to detect bacterial mRNA profiles of wild-type Acinetobacter baylyi ADP1 and Pwh1266 plasmid, and their mRNA response under the exposure of four artificial sweeteners, including saccharin, sucralose, aspartame, and acesulfame potassium. 3 mg/L of each sweetener was used to treat the mixture of bacteria cell and plasmid. The group without dosing any artificial sweeteners was the control group. Each sample was conducted in triplicate. By comparing the mRNA profiles of experimental groups and control group, the effects of these four artificial sweeteners on the transcriptional levels can be revealed. Illumina HiSeq 2500 was applied. The NGS QC toolkit (version 2.3.3) was used to treat the raw sequence reads to trim the 3’-end residual adaptors and primers, and the ambiguous characters in the reads were removed. Then, the sequence reads consisting of at least 85% bases were progressively trimmed at the 3’-ends until a quality value ≥ 20 were kept. Downstream analyses were performed using the generated clean reads of no shorter than 75 bp. The clean reads of each sample were aligned to the Acinetobacter baylyi ADP1 reference genome (NC_005966) using SeqAlto (version 0.5). Cufflinks (version 2.2.1) was used to calculate the strand-specific coverage for each gene, and to analyze the differential expression in triplicate bacterial cell culture. The statistical analyses and visualization were conducted using CummeRbund package in R (http://compbio.mit.edu/cummeRbund/). Gene expression was calculated as fragments per kilobase of a gene per million mapped reads (FPKM, a normalized value generated from the frequency of detection and the length of a given gene.