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BMC Genomics
2008 Feb 11;9:78. doi: 10.1186/1471-2164-9-78.
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Effect of thyroid hormone concentration on the transcriptional response underlying induced metamorphosis in the Mexican axolotl (Ambystoma).
Page RB
,
Voss SR
,
Samuels AK
,
Smith JJ
,
Putta S
,
Beachy CK
.
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BACKGROUND: Thyroid hormones (TH) induce gene expression programs that orchestrate amphibian metamorphosis. In contrast to anurans, many salamanders do not undergo metamorphosis in nature. However, they can be induced to undergo metamorphosis via exposure to thyroxine (T4). We induced metamorphosis in juvenile Mexican axolotls (Ambystoma mexicanum) using 5 and 50 nM T4, collected epidermal tissue from the head at four time points (Days 0, 2, 12, 28), and used microarray analysis to quantify mRNA abundances.
RESULTS: Individuals reared in the higher T4 concentration initiated morphological and transcriptional changes earlier and completed metamorphosis by Day 28. In contrast, initiation of metamorphosis was delayed in the lower T4 concentration and none of the individuals completed metamorphosis by Day 28. We identified 402 genes that were statistically differentially expressed by > or = two-fold between T4 treatments at one or more non-Day 0 sampling times. To complement this analysis, we used linear and quadratic regression to identify 542 and 709 genes that were differentially expressed by > or = two-fold in the 5 and 50 nM T4 treatments, respectively.
CONCLUSION: We found that T4 concentration affected the timing of gene expression and the shape of temporal gene expression profiles. However, essentially all of the identified genes were similarly affected by 5 and 50 nM T4. We discuss genes and biological processes that appear to be common to salamander and anuran metamorphosis, and also highlight clear transcriptional differences. Our results show that gene expression in axolotls is diverse and precise, and that axolotls provide new insights about amphibian metamorphosis.
Figure 1. Results of the statistical analyses conducted on the microarray data. (A) Venn diagram showing the DEGs identified at specific time points by contrasting the two T4 concentrations and imposing fold change criteria. D2 = Day 2, D12 = Day 12, and D28 = Day 28. (B) Venn diagram depicting the relationship between DEGs that were identified via the 5 and 50 nM regression analyses and imposing fold change criteria. For panel B, fold change values are relative to Day 0.
Figure 2. Results of the principal component analysis. Scatter plots of the 30 GeneChips based on the rotations of their first two principal components (PC 1 and PC 2). PCA was performed on all 3688 probe-sets that were available for significance testing. PC 1 and PC 2 account for 89.2% and 6.2% of the variance respectively. Cano-Martinez stages are listed in parenthesis in the legend.
Figure 3. Generalized regression patterns. The generalized regression patterns recovered by the methodology described in Liu et al. [52]. The units and values of the axes are arbitrary. The number of probe-sets in each category is listed in parentheses by concentration. Significantly enriched biological process gene ontology terms are listed by concentration and pattern. In some cases specific terms were too abundant and were thus summarized via a broader term. Abbreviations are as follows LD = linear down, QLCD = quadratic linear concave down, QLVD = quadratic linear convex down, LU = linear up, QLCU = quadratic linear concave up, QLVU = quadratic linear convex up, QC = quadratic concave, and QV = quadratic convex. A ninth pattern (Flat) that describes null results is not shown.
Figure 4. Example regression profiles. Example regression profiles based on microarray data from a gene that does not appreciably deviate from baseline until Day 28 in 50 nM T4 (A; collagen, type VI, alpha 3; probe-set ID: SRV_05103_a_at) and a gene that is initially up regulated in 50 nM T4 before being down regulated (B; N-Myc downstream regulated gene 1; probe-set ID: SRV_12417_at). Trend lines for the 5 nM regression analyses are gray and trend lines for the 50 nM regression analyses are black. LU = linear up and QLCD = quadratic linear concave down.
Figure 5. Comparison of Q-RT-PCR and microarray data. Comparisons of the relationships between transcript abundance and days of 50 nM T4 treatment as assessed in different biological samples via Q-RT-PCR (upper panels) and Affymetrix GeneChip technology (lower panels). Trend lines in the Q-RT-PCR data were obtained by linear or quadratic regression. Models with P < 0.01 are denoted by ** and models with P < 0.0001 are denoted by ***. R2 refers to adjusted R2. The microarray data represent the mean of three samples ± standard deviation. MMP13 = matrix metallopeptidase 13 and SLC31A1 = solute carrier family 31, member 1.
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