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Expression-based discovery of candidate ovule development regulators through transcriptional profiling of ovule mutants.

Skinner DJ, Gasser CS - BMC Plant Biol. (2009)

Bottom Line: Redundancy, pleiotropic effects and subtle phenotypes may preclude identification of mutants affecting some processes in screens for phenotypic changes.Approximately two hundred genes were found to have a high probability of preferential expression in these structures, and the predictive nature of the expression classes was confirmed with reverse transcriptase polymerase chain reaction and in situ hybridization.The results showed that it was possible to use a mutant, ant, with broad effects on plant phenotype to identify genes expressed specifically in ovules, when coupled with predictions from known gene expression patterns, or in combination with a more specific mutant, ino.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Molecular and Cellular Biology, University of California, Davis, CA 95616, USA. dskinnr@illinois.edu

ABSTRACT

Background: Arabidopsis ovules comprise four morphologically distinct parts: the nucellus, which contains the embryo sac, two integuments that become the seed coat, and the funiculus that anchors the ovule within the carpel. Analysis of developmental mutants has shown that ovule morphogenesis relies on tightly regulated genetic interactions that can serve as a model for developmental regulation. Redundancy, pleiotropic effects and subtle phenotypes may preclude identification of mutants affecting some processes in screens for phenotypic changes. Expression-based gene discovery can be used access such obscured genes.

Results: Affymetrix microarrays were used for expression-based gene discovery to identify sets of genes expressed in either or both integuments. The genes were identified by comparison of pistil mRNA from wild type with mRNA from two mutants; inner no outer (ino, which lacks the outer integument), and aintegumenta (ant, which lacks both integuments). Pools of pistils representing early and late stages of ovule development were evaluated and data from the three genotypes were used to designate genes that were predominantly expressed in the integuments using pair-wise and cluster analyses. Approximately two hundred genes were found to have a high probability of preferential expression in these structures, and the predictive nature of the expression classes was confirmed with reverse transcriptase polymerase chain reaction and in situ hybridization.

Conclusion: The results showed that it was possible to use a mutant, ant, with broad effects on plant phenotype to identify genes expressed specifically in ovules, when coupled with predictions from known gene expression patterns, or in combination with a more specific mutant, ino. Robust microarray averaging (RMA) analysis of array data provided the most reliable comparisons, especially for weakly expressed genes. The studies yielded an over-abundance of transcriptional regulators in the identified genes, and these form a set of candidate genes for evaluation of roles in ovule development using reverse genetics.

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Comparison of values obtained for differential expression using qRT-PCR and microarrays. Relative expression levels obtained through qRT-PCR were compared with microarray expression levels (RMA derived) for selected genes. Error bars for qRT-PCR values are the standard deviations (n ≥ 3). (A) Comparisons between WT E and ant E, and between WT E and ino E. For the gene At4g36740 no amplification product was obtained from the mutants, indicating that mRNA for this gene was below the limit of detection using qRT-PCR. (B) Differential expression between WT F and ino F.
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Figure 5: Comparison of values obtained for differential expression using qRT-PCR and microarrays. Relative expression levels obtained through qRT-PCR were compared with microarray expression levels (RMA derived) for selected genes. Error bars for qRT-PCR values are the standard deviations (n ≥ 3). (A) Comparisons between WT E and ant E, and between WT E and ino E. For the gene At4g36740 no amplification product was obtained from the mutants, indicating that mRNA for this gene was below the limit of detection using qRT-PCR. (B) Differential expression between WT F and ino F.

Mentions: qRT-PCR was used to obtain an independent assessment of a sample of the microarray results [101], to test for spurious results due to cross hybridization, alternative splicing, or technical problems leading to inaccurate measurement of expression. Twelve genes that represented a range of fold changes and absolute expression levels were tested. The relative expression levels determined by qRT-PCR are compared with fold changes from the arrays in Figure 5, and for all the genes tested the direction of the fold change was confirmed, although there was variability in the magnitude of fold changes. When fold changes were small (< 2) the microarray and qRT-PCR results were more similar than when fold changes were larger. The rankings of genes by fold change did not vary widely between the two methods, so that relative differences in expression levels were also confirmed by the qRT-PCR method.


Expression-based discovery of candidate ovule development regulators through transcriptional profiling of ovule mutants.

Skinner DJ, Gasser CS - BMC Plant Biol. (2009)

Comparison of values obtained for differential expression using qRT-PCR and microarrays. Relative expression levels obtained through qRT-PCR were compared with microarray expression levels (RMA derived) for selected genes. Error bars for qRT-PCR values are the standard deviations (n ≥ 3). (A) Comparisons between WT E and ant E, and between WT E and ino E. For the gene At4g36740 no amplification product was obtained from the mutants, indicating that mRNA for this gene was below the limit of detection using qRT-PCR. (B) Differential expression between WT F and ino F.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2664812&req=5

Figure 5: Comparison of values obtained for differential expression using qRT-PCR and microarrays. Relative expression levels obtained through qRT-PCR were compared with microarray expression levels (RMA derived) for selected genes. Error bars for qRT-PCR values are the standard deviations (n ≥ 3). (A) Comparisons between WT E and ant E, and between WT E and ino E. For the gene At4g36740 no amplification product was obtained from the mutants, indicating that mRNA for this gene was below the limit of detection using qRT-PCR. (B) Differential expression between WT F and ino F.
Mentions: qRT-PCR was used to obtain an independent assessment of a sample of the microarray results [101], to test for spurious results due to cross hybridization, alternative splicing, or technical problems leading to inaccurate measurement of expression. Twelve genes that represented a range of fold changes and absolute expression levels were tested. The relative expression levels determined by qRT-PCR are compared with fold changes from the arrays in Figure 5, and for all the genes tested the direction of the fold change was confirmed, although there was variability in the magnitude of fold changes. When fold changes were small (< 2) the microarray and qRT-PCR results were more similar than when fold changes were larger. The rankings of genes by fold change did not vary widely between the two methods, so that relative differences in expression levels were also confirmed by the qRT-PCR method.

Bottom Line: Redundancy, pleiotropic effects and subtle phenotypes may preclude identification of mutants affecting some processes in screens for phenotypic changes.Approximately two hundred genes were found to have a high probability of preferential expression in these structures, and the predictive nature of the expression classes was confirmed with reverse transcriptase polymerase chain reaction and in situ hybridization.The results showed that it was possible to use a mutant, ant, with broad effects on plant phenotype to identify genes expressed specifically in ovules, when coupled with predictions from known gene expression patterns, or in combination with a more specific mutant, ino.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Molecular and Cellular Biology, University of California, Davis, CA 95616, USA. dskinnr@illinois.edu

ABSTRACT

Background: Arabidopsis ovules comprise four morphologically distinct parts: the nucellus, which contains the embryo sac, two integuments that become the seed coat, and the funiculus that anchors the ovule within the carpel. Analysis of developmental mutants has shown that ovule morphogenesis relies on tightly regulated genetic interactions that can serve as a model for developmental regulation. Redundancy, pleiotropic effects and subtle phenotypes may preclude identification of mutants affecting some processes in screens for phenotypic changes. Expression-based gene discovery can be used access such obscured genes.

Results: Affymetrix microarrays were used for expression-based gene discovery to identify sets of genes expressed in either or both integuments. The genes were identified by comparison of pistil mRNA from wild type with mRNA from two mutants; inner no outer (ino, which lacks the outer integument), and aintegumenta (ant, which lacks both integuments). Pools of pistils representing early and late stages of ovule development were evaluated and data from the three genotypes were used to designate genes that were predominantly expressed in the integuments using pair-wise and cluster analyses. Approximately two hundred genes were found to have a high probability of preferential expression in these structures, and the predictive nature of the expression classes was confirmed with reverse transcriptase polymerase chain reaction and in situ hybridization.

Conclusion: The results showed that it was possible to use a mutant, ant, with broad effects on plant phenotype to identify genes expressed specifically in ovules, when coupled with predictions from known gene expression patterns, or in combination with a more specific mutant, ino. Robust microarray averaging (RMA) analysis of array data provided the most reliable comparisons, especially for weakly expressed genes. The studies yielded an over-abundance of transcriptional regulators in the identified genes, and these form a set of candidate genes for evaluation of roles in ovule development using reverse genetics.

Show MeSH