Caldarone et al.: Biological indices of growth rate and nutritional state of Salmo salar 
297 
Table 3 
Coefficients and Akaike’s second-order information criterion for small sample sizes (AICc) for the top candidate regression 
models for growth rate of postsmolt Atlantic salmon (Salmo salar) reared at 12°C under 3 feeding regimens in order to gener- 
ate a range of nutritional condition and growth rates. RNA/DNA (pg/pg); IGFl=:circulating plasma insulin-like growth factor 
1 (ng/mL); RNA/pro=RNA/protein (pg/mg); DNA/pro=DNA/protein (pg/mg); AAICc=difference in AICc values with respect to 
the best candidate model. For all models P<0.0001. r^=coefficient of determination. 
Dependent variable 
n 
Model 
AICc 
AAICc 
All variables tested 
Growth rate (per d) 
53 
-0.0181-^0.0040(RNA/DNA)-l-0.0001(IGFl) 
0.733 
-547.81 
0 
Growth rate (per d) 
53 
-0.0173+0.0048(RNA/DNA) 
0.686 
-542.39 
5.42 
RNA/DNA not included 
Growth rate (per d) 
53 
-0.0045-i-0.0011(RNA/pro)-0.0036(DNA/pro)+0.0001(IGFl) 
0.738 
-546.53 
1.28 
Growth rate (per d) 
53 
0.0001-!-0.0013(RNA/pro)-0.0045(DNA/pro) 
0.712 
-543.82 
3.99 
1.5 
CD 
Q. 
^ 1.0 
This study 
Maclean et at, 2008 
0.5 
cP A 
* B 
"i * ' 
» ^ cP □ 
^ □ 
O 
o 
□ □ a 5 P 
°a Dj 
□ „_na dp ^ 
0.0 
-0.5 
2 3 4 5 6 7 8 
RNA/DNA 
Figure 7 
Specific growth rate (% wet weight per d) versus RNA/ 
DNA for postsmolt Atlantic salmon (Salmo salar) reared 
in the laboratory. ♦ denotes data from fed and fasted fish 
held at 12° C and sampled throughout a 27-day period 
(present study). □ denotes data from the study of MacLean 
et al. ( 2008 ) in which postsmolts were sampled at the end 
of 30 days at a final water temperature of 12.8°C. In both 
experiments nucleic acid values were determined by the 
same method. 
of RNA/DNA and RNA/pro to fed and refed growth 
rates are evidence that the relations between RNA 
indices and growth rate were not altered by repeated 
sampling of individual fish. 
How best to standardize RNA values (RNA/DNA vs. 
RNA/pro) is not clear and may depend upon the devel- 
opmental stage of the fish. Fish muscle is unique in 
that it increases in size throughout the life of a fish 
owing to both hyperplasia (increase in cell number) 
and hypertrophy (increase in cell size) (Weatherly et 
al., 1988; Higgins and Thorpe, 1990; Koumans et al., 
1993; Mommsen, 2001). Hyperplastic muscle growth 
is accomplished by fusion of myosatellite cells, re- 
sulting in a brief initial increase in DNA per cell 
followed by a nearly constant amount of DNA per 
cell. In contrast, muscle growth through hypertrophy 
produces multiple nuclei per cell and often multiple 
copies of DNA per nucleus (polyploidy) resulting in a 
variable amount of DNA per cell (Jimenez and Kin- 
sey, 2012). Higgins and Thorpe (1990) investigated 
muscle growth in Atlantic salmon and concluded that 
juvenile Atlantic salmon (<15 cm) increased muscle 
mass by hyperplasia, whereas hypertrophy was more 
important in autumn and winter when growth of the 
salmon was slow. Weatherly et al. (1988) concluded 
that in fish smaller than approximately 44% of their 
maximum size, most fish muscle growth was due to 
hyperplasia. Our fish were recent postsmolts, approx- 
imately 23% of their maximum size, and most likely 
increasing their muscle size predominantly through 
hyperplasia. In our study, RNA/DNA performed bet- 
ter than RNA/pro for indicating short-term growth. 
In general, RNA/DNA may be the better indicator of 
growth rate during larval and juvenile stages when 
a fish is growing rapidly by increasing cell numbers. 
Until the relation of RNA to DNA in polyploidy cells 
is better known, RNA/pro may be the preferred in- 
dicator of growth rate in older fish where growth 
by hypertrophy predominates. In adults, however, 
RNA-based indices may not be an appropriate index 
of condition or growth rate. In the adult stage, pro- 
tein synthesis is directed more toward protein turnover 
rather than protein accretion. Additionally, fat reten- 
tion or gonad development may be the driving force 
behind weight-specific growth. This increase in nonpro- 
tein mass would cause an uncoupling of the relation of 
RNA-mass to growth rate. Because the turnover rate 
of RNAs (mRNA, tRNA, rRNA) ranges from minutes to 
a few days (see Fraser and Rogers, 2007), RNA-based 
indices would be most useful for estimating recent 
growth rates and current nutritional state and would 
