IlPhlMeti
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB42108 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Phlogophora meticulosa (angle shades) genome assembly, ilPhlMeti2
| PRJEB41949 | ENA
Project description:Phlogophora meticulosa (angle shades) genome assembly, ilPhlMeti2, alternate haplotype
| PRJEB41950 | ENA
Project description:Euplexia lucipara (small angle shades), genomic and transcriptomic data
| PRJEB46838 | ENA
Project description:Euplexia lucipara (small angle shades) genome assembly, ilEupLuci1
| PRJEB49080 | ENA
Project description:Euplexia lucipara (small angle shades) genome assembly, ilEupLuci1, alternate haplotype
| PRJEB49081 | ENA
Project description:The goal of this study was to perform RNA-seq expression analysis on Solanum lycopersicum cv. M82 X S. pennellii introgression lines, deriving expression Quantitative Trait Loci which were analyzed together with pre-existing genomic and phenotypic data to define genes and regulatory pathways controlling tomato root development and observed natural variation. We completed the RNAseq expression profiling analysis and developed a tool to display this information graphically in collaboration with Nicholas Provart at the University of Toronto: http://bar.utoronto.ca/efp_tomato/cgi-bin/efpWeb.cgi?dataSource=ILs_Root_Tip_Brady_Lab To identify candidate genes and pathways we focussed on one root growth trait, root growth angle, and identified two statistically significant genomic regions within tomato root growth angle QTL containing two candidate genes that likely control the gravitropic setpoint angle (CDC73 and PAP27), both of which are conserved between Arabidopsis and tomato, and which we tested using transgenic lines of the Arabidopsis orthologs. A possible regulatory role for suberin in root growth angle control was also identified.
2018-01-01 | GSE87162 | GEO
Project description:Increasing utilization and human population density in the coastal zone is widely believed to place increasing stresses on the resident biota, but confirmation of this belief is somewhat lacking. While we have solid evidence that highly disturbed estuarine systems have dramatic changes in the resident biota (black and white if you will), we lack tools that distinguish the shades of grey. In part this lack of ability to distinguish shades of grey stems from the analytical tools that have been applied to studies of estuarine systems and perhaps more important is the insensitivity of the biological end points that we have used to assess these impacts. In this paper we will present data on the phenotypic adjustments as measured by transcriptomic signatures of a resilient organism (oysters) to land use practices in the surrounding watershed using advanced machine learning algorithms. We will demonstrate that such an approach can reveal subtle and meaningful shifts in oyster gene expression in response to land use. Further, the data shows that gill tissues are far more responsive and provide superior discrimination of land use classes than hepatopancreas and that transcript encoding proteins involved in energy productions, protein synthesis and basic metabolism are more robust indicators of land use than classic biomarkers such as metallothioneins, GST and cytochrome P450. Keywords: Comparative genomics, ecogenomics. Tissue differences, impacts of land use and contaminants on gene expression. Oysters were collected from 11 tidal creeks in Georgia, South Carolina and North Carolina at sites variously impacted by human development. A total of 267 individuals were examined for gene expression profiles in gill and hepatopancreas tissues for a total of 534 arrays. The data were filtered though standard tools and ultimately analyzed using advance machine learning techniques.
2009-07-01 | E-GEOD-14793 | biostudies-arrayexpress