Arabidopsis thaliana
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA100323 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Natural variation in Arabidopsis thaliana transcriptomes
| PRJNA167306 | ENA
Project description:Natural variation in Arabidopsis thaliana transcriptomes
| PRJNA132277 | ENA
Project description:Like protein coding genes, loci that produce microRNAs (miRNAs) are generally considered to be under purifying selection, consistent with miRNA polymorphisms being able to cause disease. Nevertheless, it has been hypothesized that variation in miRNA genes may contribute to phenotypic diversity. Here we demonstrate that a naturally occurring polymorphism in the MIR164A gene interacts epistatically with an unlinked locus to affect leaf shape and shoot architecture in Arabidopsis thaliana. A single-base pair substitution in the miRNA complementary sequence alters the stability of the miRNA:miRNA* duplex. It thereby interferes with processing of the precursor and greatly reduces miRNA accumulation. We demonstrate that this is not a rare exception, but that natural strains of Arabidopsis thaliana harbor dozens of similar polymorphisms that affect processing of a wide range of miRNA precursors. Our results suggest that natural variation in miRNA processability due to cis mutations is a common contributor to phenotypic variation in plants.
2012-10-31 | GSE32927 | GEO
Project description:Natural variation in processability of individual Arabidopsis thaliana microRNAs
| PRJNA146493 | ENA
Project description:Natural epigenetic variation provides a source for the generation of phenotypic diversity, but to understand its contribution to phenotypic diversity, its interaction with genetic variation requires further investigation. MethylC-seq from naturally-occurring Arabidopsis accessions
2013-03-05 | E-GEOD-43857 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the following subset Series: GSE24571: Transposable elements and small RNAs contribute to gene expression divergence between Arabidopsis thaliana and Arabidopsis lyrata [RNA-Seq] GSE38109: Natural variation in Arabidopsis thaliana transcriptomes Refer to individual Series
2012-05-21 | E-GEOD-38113 | biostudies-arrayexpress
Project description:Waters Raw data can be downloaded for shoot- and root parts of Arabidopsis thaliana accessions.
2018-11-14 | ST001096 | MetabolomicsWorkbench
Project description:A major effort is underway to study the natural variation within the model plant species, Arabidopsis thaliana. Much of this effort is focused on genome resequencing, however the translation of genotype to phenotype will be largely effected through variations within the transcriptomes at the sequence and expression levels. To examine the cross-talk between natural variation in genomes and transcriptomes, we have examined the transcriptomes of three divergent A. thaliana accessions using tiling arrays. Combined with genome resequencing efforts, we were able to adjust the tiling array datasets to account for polymorphisms between the accessions and therefore gain a more accurate comparison of the transcriptomes. The corrected results for the transcriptomes allowed us to correlate higher gene polymorphism with greater variation in transcript level among the accessions. Our results demonstrate the utility of combining genomic data with tiling arrays to assay non-reference accession transcriptomes.
2012-03-12 | GSE24669 | GEO
Project description:A major effort is underway to study the natural variation within the model plant species, Arabidopsis thaliana. Much of this effort is focused on genome resequencing, however the translation of genotype to phenotype will be largely effected through variations within the transcriptomes at the sequence and expression levels. To examine the cross-talk between natural variation in genomes and transcriptomes, we have examined the transcriptomes of three divergent A. thaliana accessions using tiling arrays. Combined with genome resequencing efforts, we were able to adjust the tiling array datasets to account for polymorphisms between the accessions and therefore gain a more accurate comparison of the transcriptomes. The corrected results for the transcriptomes allowed us to correlate higher gene polymorphism with greater variation in transcript level among the accessions. Our results demonstrate the utility of combining genomic data with tiling arrays to assay non-reference accession transcriptomes.
2012-05-22 | GSE38109 | GEO