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Genome-wide gene expression analysis supports a developmental model of low temperature tolerance gene regulation in wheat (Triticum aestivum L.).

Laudencia-Chingcuanco D, Ganeshan S, You F, Fowler B, Chibbar R, Anderson O - BMC Genomics (2011)

Bottom Line: We compared the expression of genes in winter-habit (winter Norstar and winter Manitou) and spring-habit (spring Manitou and spring Norstar)) cultivars, wherein the locus for the vernalization gene Vrn-A1 was swapped between the parental winter Norstar and spring Manitou in the derived near-isogenic lines winter Manitou and spring Norstar.Functional assignments using GO annotations showed that genes involved in transport, oxidation-reduction, and stress response were highly represented.The results support the developmental model of LT tolerance gene regulation and demonstrate the complex genotype by environment interactions that determine LT adaptation in winter annual cereals.

View Article: PubMed Central - HTML - PubMed

Affiliation: Genomics and Gene Discovery Unit, USDA-ARS WRRC, Albany, CA 94710, USA. debbie.laudencia@ars.usda.gov

ABSTRACT

Background: To identify the genes involved in the development of low temperature (LT) tolerance in hexaploid wheat, we examined the global changes in expression in response to cold of the 55,052 potentially unique genes represented in the Affymetrix Wheat Genome microarray. We compared the expression of genes in winter-habit (winter Norstar and winter Manitou) and spring-habit (spring Manitou and spring Norstar)) cultivars, wherein the locus for the vernalization gene Vrn-A1 was swapped between the parental winter Norstar and spring Manitou in the derived near-isogenic lines winter Manitou and spring Norstar. Global expression of genes in the crowns of 3-leaf stage plants cold-acclimated at 6°C for 0, 2, 14, 21, 38, 42, 56 and 70 days was examined.

Results: Analysis of variance of gene expression separated the samples by genetic background and by the developmental stage before or after vernalization saturation was reached. Using gene-specific ANOVA we identified 12,901 genes (at p < 0.001) that change in expression with respect to both genotype and the duration of cold-treatment. We examined in more detail a subset of these genes (2,771) where expression was highly influenced by the interaction between these two main factors. Functional assignments using GO annotations showed that genes involved in transport, oxidation-reduction, and stress response were highly represented. Clustering based on the pattern of transcript accumulation identified genes that were up or down-regulated by cold-treatment. Our data indicate that the cold-sensitive lines can up-regulate known cold-responsive genes comparable to that of cold-hardy lines. The levels of expression of these genes were highly influenced by the initial rate and the duration of the gene's response to cold. We show that the Vrn-A1 locus controls the duration of gene expression but not its initial rate of response to cold treatment. Furthermore, we provide evidence that Ta.Vrn-A1 and Ta.Vrt1 originally hypothesized to encode for the same gene showed different patterns of expression and therefore are distinct.

Conclusion: This study provides novel insight into the underlying mechanisms that regulate the expression of cold-responsive genes in wheat. The results support the developmental model of LT tolerance gene regulation and demonstrate the complex genotype by environment interactions that determine LT adaptation in winter annual cereals.

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Principal component analyses. PC1 (Principal Component 1) separated the samples by the duration of cold-treatment; PC2 separated the samples by genotype and PC3 separated the samples by treatment (cold treated versus untreated). Symbols with the same shape and color represent biological replicates; the numbers on the axes of the graphs refers to the eigenvalues for each component.
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Figure 3: Principal component analyses. PC1 (Principal Component 1) separated the samples by the duration of cold-treatment; PC2 separated the samples by genotype and PC3 separated the samples by treatment (cold treated versus untreated). Symbols with the same shape and color represent biological replicates; the numbers on the axes of the graphs refers to the eigenvalues for each component.

Mentions: Principal component analysis (PCA) was performed to determine the structure of the dataset of almost 6 million data points generated by the experiment. PCA reduces the dimensionality of large data sets and determines the direction of the major variables or components that influence the result of the experiment. PCA analysis indicated that the first three components accounted for 89% of the variability in the data set. As shown in Figure 3, the first principal component (PC1, 49%) separated the data by the duration of cold treatment, PC2 (21%) separated the data by the genotype of the biological samples and PC3 (19%) separated the data by treatment (cold-treated versus untreated). Thus, PCA identified the three main factors that were manipulated in the experimental design. The biological replicates clustered together indicating the reproducibility of the sampling method. For further analysis, the dataset was filtered for genes expressed in at least two of the three biological samples per time-point (= 39,288 genes). After further filtering out of probesets that may cross-hybridize with other genes based on the Affymetrix probe nomenclature, 52% (= 31,768) of the probesets were used for detailed analysis.


Genome-wide gene expression analysis supports a developmental model of low temperature tolerance gene regulation in wheat (Triticum aestivum L.).

Laudencia-Chingcuanco D, Ganeshan S, You F, Fowler B, Chibbar R, Anderson O - BMC Genomics (2011)

Principal component analyses. PC1 (Principal Component 1) separated the samples by the duration of cold-treatment; PC2 separated the samples by genotype and PC3 separated the samples by treatment (cold treated versus untreated). Symbols with the same shape and color represent biological replicates; the numbers on the axes of the graphs refers to the eigenvalues for each component.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3141665&req=5

Figure 3: Principal component analyses. PC1 (Principal Component 1) separated the samples by the duration of cold-treatment; PC2 separated the samples by genotype and PC3 separated the samples by treatment (cold treated versus untreated). Symbols with the same shape and color represent biological replicates; the numbers on the axes of the graphs refers to the eigenvalues for each component.
Mentions: Principal component analysis (PCA) was performed to determine the structure of the dataset of almost 6 million data points generated by the experiment. PCA reduces the dimensionality of large data sets and determines the direction of the major variables or components that influence the result of the experiment. PCA analysis indicated that the first three components accounted for 89% of the variability in the data set. As shown in Figure 3, the first principal component (PC1, 49%) separated the data by the duration of cold treatment, PC2 (21%) separated the data by the genotype of the biological samples and PC3 (19%) separated the data by treatment (cold-treated versus untreated). Thus, PCA identified the three main factors that were manipulated in the experimental design. The biological replicates clustered together indicating the reproducibility of the sampling method. For further analysis, the dataset was filtered for genes expressed in at least two of the three biological samples per time-point (= 39,288 genes). After further filtering out of probesets that may cross-hybridize with other genes based on the Affymetrix probe nomenclature, 52% (= 31,768) of the probesets were used for detailed analysis.

Bottom Line: We compared the expression of genes in winter-habit (winter Norstar and winter Manitou) and spring-habit (spring Manitou and spring Norstar)) cultivars, wherein the locus for the vernalization gene Vrn-A1 was swapped between the parental winter Norstar and spring Manitou in the derived near-isogenic lines winter Manitou and spring Norstar.Functional assignments using GO annotations showed that genes involved in transport, oxidation-reduction, and stress response were highly represented.The results support the developmental model of LT tolerance gene regulation and demonstrate the complex genotype by environment interactions that determine LT adaptation in winter annual cereals.

View Article: PubMed Central - HTML - PubMed

Affiliation: Genomics and Gene Discovery Unit, USDA-ARS WRRC, Albany, CA 94710, USA. debbie.laudencia@ars.usda.gov

ABSTRACT

Background: To identify the genes involved in the development of low temperature (LT) tolerance in hexaploid wheat, we examined the global changes in expression in response to cold of the 55,052 potentially unique genes represented in the Affymetrix Wheat Genome microarray. We compared the expression of genes in winter-habit (winter Norstar and winter Manitou) and spring-habit (spring Manitou and spring Norstar)) cultivars, wherein the locus for the vernalization gene Vrn-A1 was swapped between the parental winter Norstar and spring Manitou in the derived near-isogenic lines winter Manitou and spring Norstar. Global expression of genes in the crowns of 3-leaf stage plants cold-acclimated at 6°C for 0, 2, 14, 21, 38, 42, 56 and 70 days was examined.

Results: Analysis of variance of gene expression separated the samples by genetic background and by the developmental stage before or after vernalization saturation was reached. Using gene-specific ANOVA we identified 12,901 genes (at p < 0.001) that change in expression with respect to both genotype and the duration of cold-treatment. We examined in more detail a subset of these genes (2,771) where expression was highly influenced by the interaction between these two main factors. Functional assignments using GO annotations showed that genes involved in transport, oxidation-reduction, and stress response were highly represented. Clustering based on the pattern of transcript accumulation identified genes that were up or down-regulated by cold-treatment. Our data indicate that the cold-sensitive lines can up-regulate known cold-responsive genes comparable to that of cold-hardy lines. The levels of expression of these genes were highly influenced by the initial rate and the duration of the gene's response to cold. We show that the Vrn-A1 locus controls the duration of gene expression but not its initial rate of response to cold treatment. Furthermore, we provide evidence that Ta.Vrn-A1 and Ta.Vrt1 originally hypothesized to encode for the same gene showed different patterns of expression and therefore are distinct.

Conclusion: This study provides novel insight into the underlying mechanisms that regulate the expression of cold-responsive genes in wheat. The results support the developmental model of LT tolerance gene regulation and demonstrate the complex genotype by environment interactions that determine LT adaptation in winter annual cereals.

Show MeSH