Figure Legends
Figure 1. Map of Hokkaido, Japan, showing Noboribetsu Bear Park and the
Rusha area of the Shiretoko Peninsula.
Figure 2. Scatter plots of age
(year) versus DNA methylation level (%) in CpG sites that showed the
strongest correlation. This figure includes one of the CpGs adjacent toSLC12A5 (a), POU4F2 (b), VGF (c), and SCGN(d).
Figure 3. Within-individual
changes in DNA methylation levels with age. The same CpG sites as in
Figure 2 are shown. Dotted line represents the straight line
approximated from the samples used for model construction. This figure
includes one of the CpGs adjacent to SLC12A5 (a), POU4F2(b), VGF (c), and SCGN (d).
Figure 4. Left: scatter plots of
predicted age (year) and chronological age in the age estimation model
after LOOCV. Right: scatter plots of predicted age (year) and
chronological age for wild bears based on the methylation levels
assigned to the left model. Solid line represents predicted age = actual
age; distance between the dotted line and solid line represents the MAE
of the model after LOOCV; single regression model (a, d), the best
elastic net regression model (b, e), and the best SVR model (c, f).
Figure 5. Influences of the
interactions among age, sex and growth environment on the model. (a)
Scatter plots of Δage (year) and chronological age (year) in the female
and male datasets. (b) Scatter plots of Δage (year) and chronological
age (year) in the captive and wild datasets. The interaction between age
and growth environment was significantly explanatory for Δage. (c)
Scatter plots of |Δage| (year) and chronological age
(year) in the female and male datasets. (d) Scatter plots of
|Δage| (year) and chronological age (year) in the
captive and wild datasets.
Figure 6. Influences of sex and
growth environment on the model: (a) Δage according to sex: female and
male. (b) Δage according to growth environment. (c)
|Δage| according to sex. (d) |Δage|
according to growth environment. The growth environment was
significantly explanatory for |Δage|.