Progress 09/01/07 to 07/31/12
Outputs
OUTPUTS: For additional information, please contact Karen Schlauch at 775-784-6236 or schlauch@unr.edu PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
For additional information, please contact Karen Schlauch at 775-784-6236 or schlauch@unr.edu
Publications
- No publications reported this period
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Progress 01/01/11 to 12/31/11
Outputs
OUTPUTS: The project is now in a one-year no-cost extension period. The focus of this period was to integrate protein expression measures with the transcriptomic expression measures. A DIGE proteomic analysis was performed on the bud data at Day 42. All spots that were abundant enough were picked with the MALDI-TOF/TOF,and annotated as best as possible. An association between the transcriptomic targets and the proteomic targets is being developed. We performed an analysis of protein expression levels of the Day 42 samples, across the cultivars (Seyval and Riparia) and the two day length treatments (short day and long day). A two-way ANOVA (Analysis of Variance) was performed to determine which proteins were differentially expressed with statistcal significance (at the 5% significance level) across cultivars, across treatments, and across the two-way effects of cultivar*treatment. These proteins are being further examined to determine which are comparable to the transcripts measured in this experiment, and whether or not their differential expression patterns are similar to their transcriptomic analogues. Differentially expressed proteins are being investigated extensively. PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: The project is in a no-cost extension period. I was not aware of this until Fall 2011, and thought the project had ended.
Impacts
We performed an analysis of protein expression levels of the Day 42 samples, across the cultivars (Seyval and Riparia) and the two day length treatments (short day and long day). A two-way ANOVA (Analysis of Variance) was performed to determine which proteins were differentially expressed with statistcal significance (at the 5% significance level) across cultivars, across treatments, and across the two-way effects of cultivar*treatment. These proteins are being further examined to determine which are comparable to the transcripts measured in this experiment, and whether or not their differential expression patterns are similar to their transcriptomic analogues. The major impact of this work is to develop a "dictionary" between differentially expressed proteins and transcripts between experimental conditions of cultivar and treatment There are three publications in preparation: Fennell, Deluc, Schlauch, and Cramer. Differential tissue responses in shoot and buds. Fennell, Schlauch, Dickerson, Cramer, Mathiason. Comparative analysis of bud morphological, transcriptomic and endodormancy development during photoperiod response. Deluc, Fennell Schlauch and Cramer. Differential protein and transcriptome expression in endodormant and paradormant grapevine buds.
Publications
- No publications reported this period
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Progress 01/01/10 to 12/31/10
Outputs
OUTPUTS: The RMA (Robust Multi-Array Average) approach was used for normalization and pre-processing of the transcriptomic data generated from Year 1 and Year 2 studies of this project. An ANOVA was performed on the RMA-processed data to examine those probesets with significant main and interaction effects. Special attention was given to probesets that exhibited a statistically significant Treatment*Time effect. This resulted in 3,186 probesets that exhibited a significant Treatment effect across the temporal states measured in our experiment. Activities: Dr. Schlauch mentored one undergraduate student in the development of a database to house and mine the transcriptomic data. The database is public, presents a simple and effective method to query the transcriptomic data, and offers a novel graph-theoretic approach to cluster the transcriptomic profiles across temporal states. Data can be mined with respect to user-defined thresholds instated on any condition measured via transcriptomic data. Thus, a query can be made to return all features on the array that have a transcriptomic measure of more than a certain threshold for any specified condition measured in the experiment. Additionally, the mining tool will return a cluster assignment of these features, and clusters can be viewed with a simple graphing application. Clusters are generated with a novel graph-theoretic approach which generates clusters based on very similar profiles across the conditions measured. The mining tool has been linked to a local version of BLAST, so that retrieved features can be queried against all sequences with respect to sequence similarity. Dissemination: This newly developed transcriptomic database and mining tool was presented in part at the Plant and Animal Genome 18 meeting in San Diego in January in a talk by Dr. Schlauch entitled "Novel graph theoretic approaches for comparative transcriptomics of Vitis". The database is currently publicly accessible, although we have kept the user base down to a small number during development. PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
We performed an analysis of 132 floral pathway related genes represented on the Affymetrix Grape Genome array, and found that 60 were significantly differentially expressed between photoperiod treatments. Genes were identified by their association with distinct grape floral meristem development and an expression pattern in Long-Day and Short-Day responses.
Publications
- Sreekantan L, Mathiason K, Grimplet, J, Schlauch K, Dickerson JA, Fennell AY. 2010. Differential floral development and gene expression in grapevines during long and short photoperiods suggests a role for floral genes in dormancy transitioning. Plant Molecular Biology. May;73(1-2):191-205
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Progress 01/01/09 to 12/31/09
Outputs
OUTPUTS: INTRODUCTION: The long-term goal of our research is to develop a comprehensive understanding of the regulation of endodormancy in grapevines and other woody plants. Grapevine and temperate woody plant bud endodormancy is promoted by short photoperiod, low temperature or water stress. Endodormancy release is driven by low temperature and promoted by gibberellins and chemicals such as hydrogen cyanamide. Endodormancy development, like stress tolerance, is a complex process wherein the perception of external signals induces a cascade of changes in different metabolic pathways. We will use our established Vitis genetic system with differences in endodormancy induction and release, the grape transcriptomic, proteomic and metabolomic infrastructure at UNR, the Affymetrix Vitis GeneChip microarray, and several bioinformatics databases and tools to examine and reveal functional interrelationships and to identify genes and pathways involved in regulation of endodormancy processes. OBJECTIVES: We propose to identify mechanisms regulating grape bud endodormancy induction and maintenance using an integrated genetic and functional genomic approach. The specific research objectives are: 1. Analyze the transcript profiles following controlled endodormancy induction to identify gene clusters involved in endodormancy regulation based on similarities in the expression profiles. 2. Validate functional response in endodormancy at the organ level using proteomic and metabolomic analyses. 3. Verify endodormancy specificity using a genetic model system with differences in endodormancy induction and maintenance characteristics. 4. Improve existing and develop new robust bioinformatics tools for integrated functional genomics analyses using a systems approach to reveal functional interrelationships between transcriptomic, proteomic, and metabolomic expression profiles. ACTIVITIES: My role as co-PI for this year was to complete the quality control, processing, normalization, and analysis of the combined Year 1 and Year 2 transcriptomic data. During 2009, I analyzed the combined data from Year 1 and Year 2 (168 arrays) using a very strict quality control protocol to ensure the reproducibility and quality of the data. The RMA (Robust Multi-Array Average) approach was used for normalization and pre-processing. An ANOVA was performed on the RMA-processed data to examine those probesets with significant main and interaction effects. Special attention was given to probesets that exhibited a statistically significant Treatment*Time effect. This resulted in 3,186 probesets that exhibited a significant Treatment effect across the temporal states measured in our experiment. PRODUCTS: I have developed a database and data mining tool for the transcriptional data generated in Years 1 and 2 of this study. The database is public, presents a simple and effective method to query the transcriptomic data, and offers a novel graph-theoretic approach to cluster the transcriptomic profiles across temporal states. DISSEMINATION: The newly developed transcriptomic database will be presented at PAG 2010 in January 2010. Local dissemination within the project team has already taken place. PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
IMPACT: 2009/01 TO 2009/12 My role in this project is to supply the PI with a set of statistically sound results regarding genes that are significantly differentially expressed between the two experimental treatments (long day photoperiod and short day photoperiod) and one of the seven developmental stages of the experiment. These results have been presented to the PI, who is currently examining them for putative functional associations. The database described above to cluster and group the transcriptional profiles is being implemented and used by both myself and the PI to generate these hypotheses, which we believe are biologically meaningful and useful.
Publications
- No publications reported this period
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Progress 01/01/08 to 12/31/08
Outputs
OUTPUTS: For this project, the PI proposes to identify mechanisms regulating grape bud endodormancy induction and maintenance using an integrated genetic and functional genomic approach. The specific research objectives are: 1. Analyze the transcript profiles following controlled endodormancy induction to identify gene clusters involved in endodormancy regulation based on similarities in the expression profiles. 2. Validate functional response in endodormancy at the organ level using proteomic and metabolomic analyses. 3. Verify endodormancy specificity using a genetic model system with differences in endodormancy induction and maintenance characteristics. 4. Improve existing and develop new robust bioinformatics tools for integrated functional genomics analyses using a systems approach to reveal functional interrelationships between transcriptomic, proteomic, and metabolomic expression profiles. My role as co-PI in this project for this year is to complete Task 1 for the transcriptomic data generated in Year 1 (2007-2008) using robust statistical methods. For this year, I have analyzed the data from Year 1 using a very strict quality control protocol to ensure the reproducibility and quality of the data. The RMA (Robust Multi-Array Average) approach was used for normalization and pre-processing. A simple three-way ANOVA was performed on the RMA-processed data to examine those probesets with significant main and interaction effects. Special attention was given to those probesets that exhibited a statistically significant Treatment*Time effect. 3,892 probesets exhibited a significant Treatment effect across one or more of the seven temporal states measured in our experiment. These probesets are now being examined by the PI and her students for functional similarities. PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
Again, my role in this project is to supply the PI with a set of statistically sound results regarding genes that are significantly differentially expressed between the two experimental treatments (long day photoperiod and short day photoperiod) and one of the seven developmental stages of the experiment. As my results only indicate the first year results, and exactly one-half of the entire experiment, these results will be used to only generate biological hypotheses that will be tested using the entire experimental data set this year.
Publications
- No publications reported this period
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