First published online May 24, 2004
Journal of Experimental Biology 207, 2237-2254 (2004)
Published by The Company of Biologists 2004
doi: 10.1242/jeb.01016
Changes in gene expression associated with acclimation to constant temperatures and fluctuating daily temperatures in an annual killifish Austrofundulus limnaeus
Jason E. Podrabsky* and
George N. Somero
Hopkins Marine Station of Stanford University, 120 Oceanview
Boulevard, Pacific Grove, CA 93950-3094, USA
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Fig. 1. Natural and laboratory temperatures experienced by adult Austrofundulus
limnaeus. (A) Temperature record for 5 consecutive days in a typical
ephemeral pond inhabited by A. limnaeus
(Podrabsky et al., 1998 ). (B)
Adult male fish were exposed to four different thermal acclimations. For the
cycling temperature (20–37°C) treatment (black line) fish were
collected (open circles) every 4 h for the first three daily cycles and then
again every 4 h on day 5 and day 14. Control fish (gray line) kept at 26°C
were collected (open squares) every 4 h on day 1 and day 14. Fish exposed to
constant 20°C (blue line) were collected (open blue diamonds) at 24, 48,
72, 96, 168 and 336 h. Fish exposed to constant 37°C (pink line) were
collected (open pink squares) as the 20°C fish, except for the 336 h time
point. Time 0 for the temperature cycling is 12:30 h at a temperature of
26°C. Note the broken axis in B. While five temperature cycles were
sampled during the 2-week acclimation, the temperature was continually
cycling.
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Fig. 2. Replicate hybridizations and reciprocal dye labeling experiments. (A)
Duplicate hybridizations were performed for each time point in the first two
temperature cycles. Expression data were filtered by accepting only spots that
changed over twofold in at least 1 time point. These data are not corrected
relative to t=0, but they are median centered. Cy3 was used to label
the reference sample while Cy5 was used to label the experimental sample in
the forward (F) hybridizations. The dyes were reversed (R) in the second set
of hybridizations. Visual inspection reveals a strong relationship between the
two sets of hybridizations, especially for spots that change greater than
twofold compared to the reference. (B) There is a strong correlation between
the data for the forward and reverse hybridizations (r=0.96) for
spots on the array that change more than twofold (N=831). The
equation for the regression line on the graph is
y=1.061x+0.04056. These data indicate that there is no
significant dye bias in this data set. Further, it supports the conclusion
that changes in gene expression observed in this study are not likely to be
due to variation in hybridizations, but instead are biologically relevant.
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Fig. 3. Genes with a cyclic expression pattern in response to temperature
fluctuations. Gene expression profiles are organized by phase shift relative
to the temperature cycle in the fluctuating temperature acclimation. Each
phase shift cluster was organized with a complete linkage algorithm (Peterson,
non-centered; Eisen et al.,
1998). Each row represents a single cDNA clone and each column a
time point in the acclimation time course. About 40% of the 540 cDNA clones
that were differentially expressed have a cyclic expression pattern in
response to temperature cycling as determined by cross correlation analysis.
For the control daily cycles (26°C) and constant acclimation to 20°C
and 37°C, expression patterns are corrected relative to t=0. For
the fluctuating temperature treatment, the data are presented relative to
t=0 as well as with circadian rhythms subtracted (labeled `The effect
of temperature'). Cycling temperature profiles presented with daily rhythms
subtracted will have an expression pattern near a 1:1 ratio with controls if
there is a negligible effect of temperature on gene expression (see Materials
and methods for an expanded discussion). Letters on the right margin of the
figure correspond to the line graphs presented in
Fig. 4. For non-cyclical gene
expression patterns see supplemental Fig. 1.
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Fig. 4. Diverse patterns of cyclic gene expression. The dotted line in each graph
represents a 1:1 ratio relative to the appropriate control. Letters on the
left margin of the figure correspond to the same letters in
Fig. 3. The temperature cycle
is represented by the light gray line.
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Fig. 5. Gene expression patterns grouped according to cellular function. Data are
presented as explained in Fig.
3. (A) Heat-shock proteins and molecular chaperones; (B)
cholesterol and lipid metabolism; (C) solute carriers; (D)
glycolysis/gluconeogenesis, blood glucose homeostasis; (E) intermediary
metabolism; (F) nitrogen metabolism; (G) cytoskeletal elements; (H) protein
turnover; (I) acute phase response and complement proteins; (J) cell growth
and proliferation; (K) clones with unknown function or no homology to known
sequences. Probable gene homologies were determined using Blast searches of
the GenBank sequence database. The most significant or relevant results of
these homology searches are listed in supplemental Table 1, as are the
accession numbers for the DNA sequence of the cDNA clones presented in this
paper.
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© The Company of Biologists Ltd 2004
