Genetic integration of behavioural and endocrine components of the stress response

  1. Thomas M Houslay  Is a corresponding author
  2. Ryan L Earley
  3. Stephen J White
  4. Wiebke Lammers
  5. Andrew J Grimmer
  6. Laura M Travers
  7. Elizabeth L Johnson
  8. Andrew J Young
  9. Alastair Wilson
  1. Centre for Ecology and Conservation, University of Exeter (Penryn Campus), United Kingdom
  2. Department of Biological Sciences, University of Alabama, United States
6 figures, 2 tables and 7 additional files


The lack of a strong positive relationship between observed track length and area covered (panel A), is initially puzzling given expected autocorrelation and that both are used as positive indicators of exploratory (or ‘bold’) behaviour.

Inset examples of OFT tracks from four individuals (panel B) shed light on this. Fish 1 and 2 appear to be exploring the tank, while 3 and 4 are engaging in stereotypical ‘flight’ behaviour characterised by strong thigmotaxis (remaining close to tank walls) and/or rapid movement along tank walls. As a consequence, individuals 2 and 3 have similar area covered during the OFT, but very different track lengths. We simulated random movements to define an expected null relationship between area covered and track length (panel C; dashed red line shows the fourth order polynomial model fit; see Materials and methods). The polynomial regression was then used to predict the expected area covered under random movement for each trial’s observed track length, and the ‘relative area covered’ was calculated as the observation minus this prediction. Panel D shows the resultant relative area covered plotted against track length for all trials (dashed red line at relative area covered = 0, shows where individuals of any track length are expected to lie if they move randomly with respect to direction). From this it is apparent that fish 1 and 2 have high relative area covered, while 3 and 4 do not.

Guppies habituate to the waterborne sampling procedure, as shown by a decline in average ln-transformed cortisol level (ng/hr) following stressor exposure between first and third exposures.

Black circles and associated bars denote predicted population means (± standard error) from mixed model analysis. Gray lines depict the predicted genetic reaction norms across repeated stressor exposure for each individual. Weak, but statistically significant GxE is manifest as variance in the genetic reaction norm slopes (i.e. lack of parallelism) and results in a slight reduction of genetic variance for cortisol at the third exposure relative to the first.

The additive genetic relationship between ln-transformed cortisol (x-axis) and five behaviours (a, relative area covered; b, time in the middle; c, track length; d, √freezings; e, -ln emergence time).

Points show (predicted) bivariate genetic deviations from the population means, plotted for those individuals in the pedigree with cortisol data. In each case the black ellipse depicts the ‘shape’ of the relationship as given by the point estimate of G. Specifically it encompasses the area expected to contain 95% of the bivariate genetic distribution for the population. Grey ellipses denote the corresponding areas defined from 5000 bootstrapped replicates of G, and so highlight the uncertainty around these bivariate distributions.

Figure 4 with 2 supplements
Trait loadings from gmax, the first eigen vector (principal component) of G.

This axis explains 59.5% of the genetic (co)variation found in the focal behavioural and physiological components of the stress response in our guppy population. Points show trait loadings from the first eigen vector of our estimate of G, with bars representing 95% confidence intervals on each loading (calculated from 5000 bootstrapped replicates of the model).

Figure 4—figure supplement 1
Scree plot showing the proportion of total variance explained by each eigen vector, with vertical bars indicating 95% confidence intervals as estimated from 5000 bootstrapped replicates.

The horizontal dotted line indicates where equal variance across all eigen vectors would lie.

Figure 4—figure supplement 2
Histogram of PC scores for gmax calculated for each individual that was assayed for both behaviour and endocrine responses.

The distribution is skewed but clearly not bimodal, as is predicted by some verbal models of ‘stress coping style’.

Appendix 1—figure 1
Percentage of time inactive is strongly correlated with track length at the phenotypic level.
Appendix 1—figure 2
Time in the middle is strongly correlated with average distance from the tank wall at the phenotypic level.


Table 1
Estimated variance components, along with adjusted heritability, for each trait as estimated in a univariate model (± standard error).

Chi-square test statistics and p-values are provided for the pedigree term, testing for the presence of significant additive genetic variance (Va).

Relative area covered42.87 ± 12.8956.16 ± 10.9219.17 ± 4.92203.17 ± 6.260.13 ± 0.0431.2< 0.001
Time in the middle554.78 ± 144.18473.24 ± 114.77196.94 ± 53.542002.06 ± 62.380.17 ± 0.0447.2< 0.001
Track length23584.54 ± 5534.9026587.74 ± 4556.873173.34 ± 1396.8476140.49 ± 2376.320.18 ± 0.0488.7< 0.001
√Freezings0.34 ± 0.080.18 ± 0.060.08 ± 0.021.13 ± 0.040.20 ± 0.0548.2< 0.001
ln Emergence time0.12 ± 0.050.06 ± 0.060.05 ± 0.021.07 ± 0.050.09 ± 0.0222.5< 0.001
Shoaling tendency0 ± 02457.36 ± 570.96708.87 ± 316.309900.95 ± 622.100 ± 000.5
ln Cortisol0.08 ± 0.020.02 ± 0.020.01 ± 0.010.15 ± 0.010.31 ± 0.0924.4< 0.001
Table 2
Additive genetic covariance-correlation matrix (G) from the full multivariate animal model.

Genetic variances provided on the shaded diagonal, with genetic covariances below and genetic correlations above. 95% confidence intervals in parentheses are estimated from 5000 bootstrapped replicates. Where the confidence intervals for any estimate do not cross zero the estimate is considered statistically significant (at the 0.05 alpha level) and are shown in bold.

Relative area coveredTime in the middleTrack length√Freezings-ln Emergence timeLn Cortisol
Relative area covered0.115 (0.050,0.182)0.795 (0.601,0.952)0.549 (-0.789,–0.239)0.139 (-0.260,0.511)–0.438 (-1.305,0.239)–0.376 (-0.959,0.272)
Time in the middle0.103 (0.044,0.165)0.145 (0.070,0.215)0.658 (-0.86,–0.414)0.363 (0.024,0.659)–0.153 (-0.815,0.538)0.617 (-1.139,–0.155)
Track length0.071 (-0.127,–0.017)0.096 (-0.154,–0.035)0.147 (0.080,0.219)0.801 (-0.931,–0.647)0.61 (0.064,1.328)0.425 (-0.027,0.968)
√Freezings0.020 (-0.034,0.076)0.059 (-0.001,0.120)0.132 (-0.200,–0.060)0.185 (0.091,0.269)–0.483 (-1.103,0.146)0.556 (-1.069,–0.067)
-ln Emergence time–0.041 (-0.103,0.012)–0.016 (-0.073,0.041)0.065 (0.008,0.121)–0.057 (-0.126,0.009)0.076 (0.009,0.148)–0.020 (-0.807,0.790)
ln Cortisol–0.044 (-0.105,0.023)0.082 (-0.145,–0.018)0.057 (-0.002,0.119)0.083 (-0.155,–0.01)–0.002 (-0.058,0.053)0.121 (0.036,0.206)

Additional files

Supplementary file 1

Fixed effects estimates from the full multivariate animal model.
Supplementary file 2

Permanent environment (co)variance matrix from the full multivariate animal model.
Supplementary file 3

Group (co)variance matrix from the full multivariate animal model.
Supplementary file 4

Residual variance-correlation matrix from the full multivariate animal model.
Supplementary file 5

Among-individual (co)variance matrix from the multivariate model that excluded genetic effects.
Supplementary file 6

Eigen decomposition of the G matrix.
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  1. Thomas M Houslay
  2. Ryan L Earley
  3. Stephen J White
  4. Wiebke Lammers
  5. Andrew J Grimmer
  6. Laura M Travers
  7. Elizabeth L Johnson
  8. Andrew J Young
  9. Alastair Wilson
Genetic integration of behavioural and endocrine components of the stress response
eLife 11:e67126.