Project description:These data provide a basis for exploration of gene expression differences between physiologically diverse accessions of Arabidopsis thaliana. Recent studies have documented remarkable genetic variation among Arabidopsis thaliana accessions collected from diverse habitats and across its geographical range. Of particular interest are accessions with putatively locally adapted phenotypes – i.e., accessions with attributes that are likely adaptive under the climatic or habitat conditions of their sites of origin. These genotypes are especially valuable as they may provide insight into the genetic basis of adaptive evolution as well as allow the discovery of genes of ecological importance. Therefore we studied the physiology, genome content and gene expression of 18 physiologically diverse accessions. The gene expression studies were conducted under two levels of soil moisture and accompanied by physiological measurements to characterize early responses to soil moisture deficit.
Project description:4-week old Arabidopsis plants grown in soil were flooded to the soil surface (root flooding) or completely submerged under 6 cm of water (submergence). Samples are collected at the time specified.
Project description:These data provide a basis for exploration of gene expression differences between physiologically diverse Spring annual accessions of Arabidopsis thaliana. Recent studies have documented remarkable genetic variation among Arabidopsis thaliana accessions collected from diverse habitats and across its geographical range. Of particular interest are accessions with putatively locally adapted phenotypes – i.e., accessions with attributes that are likely adaptive under the climatic or habitat conditions of their sites of origin. These genotypes are especially valuable as they may provide insight into the genetic basis of adaptive evolution as well as allow the discovery of genes of ecological importance. Therefore we studied the physiology, genome content and gene expression of 18 physiologically diverse accessions. The gene expression studies were conducted under two levels of soil moisture and accompanied by physiological measurements to characterize early responses to soil moisture deficit.
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:This is comparative transcriptomics by using the wild type and dph1 mutants to see the change of dph1 mutants at transcript levels compared with wild type. Rosette tissues of four-week-old plants grown in soil were harvested for total RNA isolation by RNeasy Plant Mini Kit (Qiagen). Libraries were prepared and sequenced using the Illumina platform by Novogene (Hongkong, CN). For RNA-seq data analysis, raw reads were first filtered by CutAdapt 2.1 to remove adaptors and low quality reads. The filtered reads were mapped to Arabidopsis thaliana Col-0 reference genome (Tair 10). Read counts were determined by Qualimap2. Differentially expressed genes were identified using the R package DESeq2.