Project description:This experiment was donated by The ELP Project website at elp.ucdavis.edu that was supported in part by the Arabidopsis 2010 project, NSF Division of Molecular and Cellular Biosciences, award 0115109. The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid and jasmonic acid, have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs) affecting host resistance responses. In order to identify an appropriate RIL population to map QTL controlling disease resistance responses, we performed a parental survey of 7 different Arabidopsis accessions. We treated vegetatively grown plants with either salicylic acid or a control solution, and harvested the plants at 3 different time points after chemical treatment. We present Affymetrix GeneChip microarray expression data for 3 biological replications of this parental survey. Keywords: strain_or_line; compound_treatment; time_series
Project description:Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.
Project description:Cigarette smoking is a major cause of preventable morbidity and mortality. While quitting smoking is the best option, switching from cigarettes to non-combustible alternatives (NCAs) such as e-vapor products is a viable harm reduction approach for smokers who would otherwise continue to smoke. A key challenge for the clinical assessment of NCAs is that self-reported product use can be unreliable, compromising the proper evaluation of their risk reduction potential. In this cross-sectional study with 205 healthy volunteers, we combined comprehensive exposure characterization with in-depth multi-omics profiling to compare effects across four study groups: cigarette smokers (CS), e-vapor users (EV), former smokers (FS) and never smokers (NS). Multi-omics analyses included metabolomics, transcriptomics, DNA methylomics, proteomics, and lipidomics. Comparison of the molecular effects between CS and NS recapitulated several previous observations, such as increases in inflammatory markers in CS. Generally, FS and EV demonstrated intermediate molecular effects between the NS and CS groups. Stratification of the FS and EV by combustion exposure markers suggested that this positioning on the scale between CS and NS was partially driven by non-compliance / dual use. Overall, this study highlights the importance of in-depth exposure characterization before biological effect characterization for any NCA assessment study.
Project description:This experiment was donated by The ELP Project website at elp.ucdavis.edu that was supported in part by the Arabidopsis 2010 project, NSF Division of Molecular and Cellular Biosciences, award 0115109. The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid and jasmonic acid, have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs) affecting host resistance responses. In order to identify an appropriate RIL population to map QTL controlling disease resistance responses, we performed a parental survey of 7 different Arabidopsis accessions. We treated vegetatively grown plants with either salicylic acid or a control solution, and harvested the plants at 3 different time points after chemical treatment. We present Affymetrix GeneChip microarray expression data for 3 biological replications of this parental survey. Keywords: strain_or_line; compound_treatment; time_series
Project description:This experiment was donated by The ELP Project website at elp.ucdavis.edu that was supported in part by the Arabidopsis 2010 project, NSF Division of Molecular and Cellular Biosciences, award 0115109. The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid and jasmonic acid, have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs) affecting host resistance responses. In order to identify an appropriate RIL population to map QTL controlling disease resistance responses, we performed a parental survey of 7 different Arabidopsis accessions. We treated vegetatively grown plants with either salicylic acid or a control solution, and harvested the plants at 3 different time points after chemical treatment. We present Affymetrix GeneChip microarray expression data for 3 biological replications of this parental survey. Keywords: strain_or_line; compound_treatment; time_series
Project description:This experiment was donated by The ELP Project website at elp.ucdavis.edu that was supported in part by the Arabidopsis 2010 project, NSF Division of Molecular and Cellular Biosciences, award 0115109. The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid and jasmonic acid, have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs) affecting host resistance responses. In order to identify an appropriate RIL population to map QTL controlling disease resistance responses, we performed a parental survey of 7 different Arabidopsis accessions. We treated vegetatively grown plants with either salicylic acid or a control solution, and harvested the plants at 3 different time points after chemical treatment. We present Affymetrix GeneChip microarray expression data for 3 biological replications of this parental survey. Keywords: strain_or_line; compound_treatment; time_series
Project description:This experiment was donated by The ELP Project website at elp.ucdavis.edu that was supported in part by the Arabidopsis 2010 project, NSF Division of Molecular and Cellular Biosciences, award 0115109. The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid and jasmonic acid, have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs) affecting host resistance responses. In order to identify an appropriate RIL population to map QTL controlling disease resistance responses, we performed a parental survey of 7 different Arabidopsis accessions. We treated vegetatively grown plants with either salicylic acid or a control solution, and harvested the plants at 3 different time points after chemical treatment. We present Affymetrix GeneChip microarray expression data for 3 biological replications of this parental survey. Keywords: strain_or_line; compound_treatment; time_series
Project description:This experiment was donated by The ELP Project website at elp.ucdavis.edu that was supported in part by the Arabidopsis 2010 project, NSF Division of Molecular and Cellular Biosciences, award 0115109. The study of natural genetic variation for plant disease resistance responses is a complementary approach to utilizing mutants to elucidate genetic pathways. While some key genes involved in pathways controlling disease resistance, and signaling intermediates such as salicylic acid and jasmonic acid, have been identified through mutational analyses, the use of genetic variation in natural populations permits the identification of change-of-function alleles, which likely act in a quantitative manner. Whole genome microarrays, such as Affymetrix GeneChips, allow for molecular characterization of the disease response at a genomics level and characterization of differences in gene expression due to natural variation. Differences in the level of gene expression, or expression level polymorphisms (ELPs), can be mapped in a segregating population to identify regulatory quantitative trait loci (expression QTLs) affecting host resistance responses. In order to identify an appropriate RIL population to map QTL controlling disease resistance responses, we performed a parental survey of 7 different Arabidopsis accessions. We treated vegetatively grown plants with either salicylic acid or a control solution, and harvested the plants at 3 different time points after chemical treatment. We present Affymetrix GeneChip microarray expression data for 3 biological replications of this parental survey. Keywords: strain_or_line; compound_treatment; time_series