Expression analysis of Antirrhinum majus inflorescence meristems grown under control and crowding conditions
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ABSTRACT:
ORGANISM(S): Antirrhinum majus
SUBMITTER: Marcos Egea-Cortines
PROVIDER: E-GEOD-72818 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:Investigation of gene expression level changes as a result of crowding growth conditions.
2015-09-10 | GSE72818 | GEO
Project description:Transcriptional profiling of sweet corn plant density (crowding stress) tolerance influencing yield. Tolerance to crowding stress has played a crucial role in improving agronomic productivity in field corn; however, commercial sweet corn hybrids vary greatly in crowding stress tolerance. The experiment was conducted to 1) explore transcriptional changes among sweet corn hybrids with differential yield under crowding stress, 2) identify relationships between phenotypic responses and gene expression patterns, and 3) identify groups of genes associated with yield and crowding stress tolerance. Under conditions of crowding stress, three high-yielding and three low-yielding sweet corn hybrids were grouped for transcriptional and phenotypic analyses. Transcriptional analyses identified from 372 to 859 common differentially expressed genes (DEGs) for each hybrid. Large gene expression pattern variation among hybrids and only 26 common DEGs across all hybrid comparisons were identified, suggesting each hybrid has a unique response to crowding stress. Over-represented biological functions of DEGs also differed among hybrids. Strong correlation was observed between: 1) modules with up-regulation in high-yielding hybrids and yield traits, and 2) modules with up-regulation in low-yielding hybrids and plant/ear traits. Modules linked with yield traits may be important crowding stress response mechanisms influencing crop yield. Functional analysis of the modules and common DEGs identified candidate crowding stress tolerant processes in photosynthesis, glycolysis, cell wall, carbohydrate/nitrogen metabolic process, chromatin, and transcription regulation. Moreover, these biological functions were greatly inter-connected, indicating the importance of improving the mechanisms as a network. 3 high-and 3 low-yielding hybrids with 2-3 biological replications grown under high population density (crowding stress)
2016-01-05 | E-GEOD-73435 | biostudies-arrayexpress
Project description:Expression analysis of Antirrhinum majus inflorescence meristems grown under control and crowding conditions
| PRJNA295141 | ENA
Project description:We used custom Nimblegen microarrays representing whole-larval transcriptomes for two species (Papilio zelicaon [this submission] and Erynnis propertius [submitted seperately]) to assess gene expression differences affecting tolerance to climatic regimes. Many individuals were sourced from populations from the northern periphery and center of the species' (shared) range; these were each divided into groups treated under peripheral and central climate regimes, resulting in 4 experimental groups for each species (Peripheral Source, Peripheral treatment; Peripheral Source, Central Treatment; Central Source, Peripheral Treatment; Central Source, Central Treatment). Using technical microarray replicates allowed us to use ANOVA to identify genes whose expression may underlie local adaptation to climate (i.e., those showing an interaction term between source and population). Abstract: Population differences may determine geographic range shifts and adaptive evolution under climate change. Local adaptation in peripheral populations could preclude or slow range expansions, and populations with different genetic make-up could have distinct trajectories that produce complex spatial patterns of population change. To investigate the genetic extent of local responses to climate change, we exposed poleward-periphery and central populations of two Lepidoptera to reciprocal, common-garden climatic conditions and compared whole-transcriptome expression. We found significant expression differences between populations in both species. In addition, several hundred genes including genes involved in energy metabolism and oxidative stress responded in a localized fashion in the species that exhibits greater population structure and local adaptation. Expression levels of these genes are most divergent in the same environment in which we previously detected phenotypic divergence in metabolism. By contrast, we found no localized genes in the species with higher gene flow, reflecting the lack of previously observed local adaptation. These results suggest that population differences do not generalize easily, even for related species living in the same climate, but some taxa deserve population-level consideration when predicting the effects of climate change. Previously we sequenced and assembled whole larval transcriptome ESTs sourced from pooled central-population individuals subjected to environmental stressors (see O'Neil et al., 2008). From these assemblies custom Nimblegen microarrays were designed (Nimblegen, Inc.), representing 34,609 putative gene sequences for E. propertius (submitted separately) and 25,735 putative gene sequences for P. zelicaon (this submission). Probe designs sought 5 representative 60mer probes for E.propertius and 4 representative probes for P. zelicaon. Messenger RNA was was sampled from multiple individuals of each experimental group and pooled before being converted to cDNA and hybridized to technical replicate microarrays. Three technical replicates for each experimental group were used, for a total of 12 microarrays (per species). Microarray data were log2 transformed and quintile-normalized (Bolstad et al. 2003) on a per-species basis.
2014-05-05 | E-GEOD-56403 | biostudies-arrayexpress
Project description:We used custom Nimblegen microarrays representing whole-larval transcriptomes for two species (Erynnis propertius [this submission] and Papilio zelicaon [submitted seperately]) to assess gene expression differences affecting tolerance to climatic regimes. Many individuals were sourced from populations from the northern periphery and center of the species' (shared) range; these were each divided into groups treated under peripheral and central climate regimes, resulting in 4 experimental groups for each species (Peripheral Source, Peripheral treatment; Peripheral Source, Central Treatment; Central Source, Peripheral Treatment; Central Source, Central Treatment). Using technical microarray replicates allowed us to use ANOVA to identify genes whose expression may underlie local adaptation to climate (i.e., those showing an interaction term between source and population). Abstract: Population differences may determine geographic range shifts and adaptive evolution under climate change. Local adaptation in peripheral populations could preclude or slow range expansions, and populations with different genetic make-up could have distinct trajectories that produce complex spatial patterns of population change. To investigate the genetic extent of local responses to climate change, we exposed poleward-periphery and central populations of two Lepidoptera to reciprocal, common-garden climatic conditions and compared whole-transcriptome expression. We found significant expression differences between populations in both species. In addition, several hundred genes including genes involved in energy metabolism and oxidative stress responded in a localized fashion in the species that exhibits greater population structure and local adaptation. Expression levels of these genes are most divergent in the same environment in which we previously detected phenotypic divergence in metabolism. By contrast, we found no localized genes in the species with higher gene flow, reflecting the lack of previously observed local adaptation. These results suggest that population differences do not generalize easily, even for related species living in the same climate, but some taxa deserve population-level consideration when predicting the effects of climate change. Previously we sequenced and assembled whole larval transcriptome ESTs sourced from pooled central-population individuals subjected to environmental stressors (see O'Neil et al., 2008). From these assemblies custom Nimblegen microarrays were designed (Nimblegen, Inc.), representing 34,609 putative gene sequences for E. propertius (this submission) and 25,735 putative gene sequences for P. zelicaon (submitted seperately). Probe designs sought 5 representative 60mer probes for E.propertius and 4 representative probes for P. zelicaon. Messenger RNA was was sampled from multiple individuals of each experimental group and pooled before being converted to cDNA and hybridized to technical replicate microarrays. Three technical replicates for each experimental group were used, for a total of 12 microarrays (per species). Microarray data were log2 transformed and quintile-normalized (Bolstad et al. 2003) on a per-species basis.
2014-05-05 | E-GEOD-56404 | biostudies-arrayexpress
Project description:Transcriptional profiling of sweet corn response to plant density (crowding stress). Determine the extent to which hybrid and environment influences crowding stress response and identify crowding stress transcriptional response in sweet corn
2021-06-01 | GSE72434 | GEO
Project description:To better undersand the effects of drought stress on wheat developing seeds, the transcription profile of early developing wheat seeds under control and drought stress conditions were comparatively analyzed by using the Affymetrix wheat geneChip. Drought stress is a major yield-limiting factor for wheat. Wheat yields are particularly sensitive to drought stress during reproductive development. Early seed development stage is an important determinant of seed size, one of the yield components. We specifically examined the impact of drought stress imposed during postzygotic early seed development in wheat. We imposed a short-term drought stress on plants with day-old seeds and observed that even a short-duration drought stress significantly reduced the size of developing seeds as well as mature seeds. Drought stress delayed the developmental transition from syncytial to cellularized stage of endosperm. Coincident with reduced seed size and delayed endosperm development, a subset of genes associated with cytoskeleton organization was misregulated in developing seeds under drought-stressed. Several genes linked to hormone pathways were also differentially regulated in response to drought stress in early seeds. Notably, drought stress strongly repressed the expression of wheat storage protein genes such as gliadins, glutenins and avenins as early as 3 days after pollination. Our results provide new insights on how some of the early seed developmental events are impacted by water stress, and the underlying molecular pathways that can possibly impact both grain size and quality in wheat. Winter wheat cultivar Redland, PI 502907 (Triticum aestivum L.) was used for this study. Seedlings were vernalized at 4°C for 6 weeks and then transplanted to a one gallon pot of soil-sand mixture (3:1, v/v) and grown in a growth chamber under the following conditions: relative humidity, 50–70%; 16-h light/8-h dark photoperiod; 21°C daytime temperature and 18°C nights. Plants were watered regularly twice daily at the rate of 100ml/ per pot. Because, wheat has an asynchronous fertilization pattern for ovlues in the inflorescence, each floret needs to be specifically marked for timing the fertilization and stress induction. After spikes developed, unfertilized ovules were monitored and observed for the fertilization process. Closed wheat spikes with anthers outside were marked as fertilized. Drought stress was imposed 24h after the fertilization (HAF). Drought stress treatment was initiated by discontinuing watering on the drought treatment plants while control plants were regularly watered twice daily. Stress treatment was applied at 48 HAF and relieved at 96 HAF. The microarray study focuses on 24 HAF to 72 HAF in control and drought stress conditions. We started to impose drought stress 24HAF.
2015-09-15 | E-GEOD-70443 | biostudies-arrayexpress
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