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# Resilience: from theory to practice in chicken

Nicolas Bédère

► To cite this version:

Nicolas Bédère. Resilience: from theory to practice in chicken. Doctoral. Genetics of resilience and trade-offs, Wageningen, The Netherlands, France. 2024. hal-05022066

HAL Id: hal-05022066

https://hal.science/hal-05022066v1

Submitted on 5 Apr 2025

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# Resilience: from theory to practice in chicken

<figure><img src="image_4.png" /><figcaption>Nicolas Bédère (CV)</figcaption></figure>

INRAE, UMR PEGASE, Saint-Gilles (France)

Research in genetics of environmental sensitivity in layers

<figure><img src="image_5.png" /></figure>

RÉPUBLIQUE
FRANÇAISE

Liberté
Egalité
Fraternité

INRAE
> Schedule

* Quick look at the chicken industry

* Why does resilience matter for the chicken industry?

* How can we study resilience in chicken?

> I could prepare this presentation thanks to many collaborators:

* INRAE : Marie-Hélène Pinard-van der Laan, Ingrid David

* WUR : Han Mulder*, Tom Berghof*, Marieke Poppe*, Harmen Doekes, Henk Bovenhuis, István Fodor, Pascal Duenk, Mario Calus, Malou van der Sluis, Claudia Kamphuis

* Hendrix Genetics : Katrijn Peeters, Jeroen Visscher, Bram Visser, Denis Janssen

*changed affiliations or careers

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Quick look at the chicken industry
> **Chicken meat factsheet**

World's most eaten meat

<figure><img src="image_8.png" /></figure>

source: [USDA FAS](https://usda-fas.nass.usda.gov/)

<figure><img src="image_9.png" /></figure>

European
Union

+ 3rd world producer

+ 11 MT meat

+ 6,4 B chickens

source: [ITAVI](https://www.itavi.org/) & [eurostats](https://data.eurostat.eu/)

<figure><img src="image_10.png" /></figure>

source: [ITAVI](https://www.itavi.org/)

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# Chickens' egg factsheet

## World's most eaten animal protein

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source: [ITAVI](https://www.itavi.eu)

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European
Union

+ 2ème world's producer

+ 6,4 BT eggs

+ 376 M hens

source: [ITAVI](https://www.itavi.eu) & [eurostats](https://data.eurostat.eu/)

<figure><img src="image_15.png" /></figure>

source: [ITAVI](https://www.itavi.eu)

<figure><img src="image_16.png" /></figure>

@Bergs Fairytail Garden

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Why does resilience matter for the chicken industry?
> Quick reminder of the definitions

That's all about **environmental sensitivity**

<figure><img src="image_19.png" /></figure>
> Quick reminder of the definitions

That's all about **environmental sensitivity**

<figure><img src="image_20.png" /></figure>
> Resilience relies on dynamic processes

We need series of data

<figure><img src="image_21.png" /></figure>

There is an theoretically ideal route

"the capacity of the animal to be **minimally affected** by a **disturbance** or to **rapidly return** to the physiological, behavioural, cognitive, health, affective and production states that pertained before exposure to a disturbance"

[Colditz and Hine (2016)]

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Finding the ideal route is not trivial, in this aspect you need to be both creative and pragmatic...
... and there's still room for new ideas!

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INRAO
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# Resilience relies on dynamic processes

We need series of data

<figure><img src="image_26.png" /></figure>

There is an theoretically ideal route

<figure><img src="image_27.png" /></figure>

But realty never goes as planned

> "the capacity of the animal to be **minimally affected** by a **disturbance** or to **rapidly return** to the physiological, behavioural, cognitive, health, affective and production states that pertained before exposure to a disturbance"
> 
> *Colditz and Hine (2016)*

<figure><img src="image_28.png" /></figure>

<figure><img src="image_29.png" /></figure>

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## Resilience relies on dynamic processes

We need series of data

* There is an theoretically ideal route

* But realty never goes as planned

* There is an observed route, resulting from the capacity of the individual to cope with disturbances

> "the capacity of the animal to be **minimally affected** by a **disturbance** or to **rapidly return** to the physiological, behavioural, cognitive, health, affective and production states that pertained before exposure to a disturbance"

*Colditz and Hine (2016)*

<figure><img src="image_36.png" /></figure>
<figure><img src="image_37.png" /></figure>

# Resilience relies on dynamic processes

We need series of data

<figure><img src="image_38.png" /></figure>

* **There is an theoretically ideal route**

<figure><img src="image_39.png" /></figure>

* **But realty never goes as planned**

<figure><img src="image_40.png" /></figure>

* **There is an observed route, resulting from the capacity of the individual to cope with disturbances**

<figure><img src="image_41.png" /></figure>

* **The way to study resilience is to analyze the deviations between the theoretical and the observed routes**

> "the capacity of the animal to be **minimally affected** by a **disturbance** or to **rapidly return** to the physiological, behavioural, cognitive, health, affective and production states that pertained before exposure to a disturbance"

*Colditz and Hine (2016)*

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> Resilience is about **stability**, not about level

> "the capacity of the animal to be **minimally affected** by a **disturbance** or to **rapidly return** to the physiological, behavioural, cognitive, health, affective and production states that pertained before exposure to a disturbance"
> 
> *Colditz and Hine (2016)*

<figure><img src="image_44.png" /></figure>

<figure><img src="image_45.png" /></figure>
> Resilience is about **stability**, not about level

Some examples in chicken

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> Resilience is about **stability**, not about level

Some examples in chicken

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source: Tom Berghof
> Resilience is about **stability**, not about level

Some examples in chicken

<figure><img src="image_51.png" /></figure>
> Challenges for chickens

Examples : diseases and heat waves

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2022 Avian flue

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4,5M hens in FR (~9%)

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170M€ for all poultry

source: [ITAVI](https://itavi.org)

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2004 Heat wave

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3,5M poultry in FR

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45M€ for all poultry

source: [ITAVI](https://itavi.org)

The poultry industry needs animals that are able to cope with such perturbations

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> Breeding goal : genetically improve resilience of laying hens

And if possible a general resilience

while ignoring :

- the type of perturbations

- their frequencies

- their intensity...

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> **Breeding and genetics supporting the agroecological transition of livestock systems**

All the more given the diversity of farming systems

Particular context in Europe:

↗ number of laying hens in cage-free system (2/3 in 2021), with many commercial settings

<figure><img src="image_63.png" /><figcaption>@Big Dutchman</figcaption></figure>

<figure><img src="image_64.png" /><figcaption>@Big Dutchman</figcaption></figure>

<figure><img src="image_65.png" /><figcaption>@Nicolas Goualan</figcaption></figure>

<figure><img src="image_66.png" /><figcaption>@Big Dutchman</figcaption></figure>

<figure><img src="image_67.png" /><figcaption>@Novogen</figcaption></figure>

Cage systems will be banned (probably) in 2027 in E.U.

END THE
CAGE AGE

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> Alternative breeding systems

☑ Pros

Floor farming systems = better
consideration for

* the fact that animals are sensitive beings

* the social nature of hens

* societal expectations

+ outdoor = better consideration for

* species-specific behaviors

* Enrichment

* plants and insects intake

* services : of pests control, soil amendment, heritage and landscape

☒ Cons

Floor farming systems = risks of

* Floor eggs

* Aggressive social interactions

* Piling

+ outdoor = perturbations due to

* Natural daylight (duration, intensity)

* Temperature (& hygrometry & ventilation)

* Pathogens

* Predation

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> How can we study resilience in chicken ?

<figure><img src="image_72.png" /></figure>
Remember? We need series of data → high throughput phenotyping !

→ We need tools and we're so jalous of cattle...

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source: [IDELE](#)

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> Remember? We need series of data → high throughput phenotyping !

But a new area is coming for chickens ! Mostly thanks to RFID technologies

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source: Lohmann

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source: Hendrix Genetics

INRAO

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Guettier et al. (2020)

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Rufener et al. (2018)

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Ellen et al. (2019) p. 23
> Remember? We need series of data → high throughput phenotyping !

Is it worth investing in individual tracking of hens?

<figure><img src="image_81.png" /></figure>

Hutu et al. (2020)
## Let's go through a few examples

### Resilience indicators derived from body weight data

* Berghof, T.V.L., Henk Bovenhuis, Mulder, H.A., 2019. **Body Weight Deviations as Indicator for Resilience in Layer Chickens.** Front. Genet. 10, 1216. https://doi.org/10.3389/fgene.2019.01216

### Resilience indicators derived from egg production data

* Bédère, N., Berghof, T., Peeters, K., Pinard-van Der Laan, M.-H., Visscher, J., David, I., Mulder, H., 2022. **Using egg production longitudinal recording to study the genetic background of resilience in purebred and crossbred laying hens.** Genetics Selection Evolution 54, 12 p. https://doi.org/10.1186/s12711-022-00716-8

* Berghof, T., Bédère, N., Peeters, K., Poppe, M., Visscher, J., Mulder, H., 2024. **The genetics of resilience and its relationships with egg production traits and antibody traits in chickens.** Genetics Selection Evolution 56, 20. https://doi.org/10.1186/s12711-024-00888-5

* Doekes, H.P., Bovenhuis, H., Berghof, T.V.L., Peeters, K., Visscher, J., Mulder, H.A., 2023. **Research Note: Genome-wide association study for natural antibodies and resilience in a purebred layer chicken line.** Poultry Science 102, 102312. https://doi.org/10.1016/j.psj.2022.102312

* Fodor, I., Duenk, P., Visser, B., Janssen, D., Calus, M. P. L., van der Sluis, M., Kamphuis, C., 2024. **Novel resilience indicators based on egg production in laying hens**, in: Proceedings 75th Annual Meeting of the EAAP. 01 sept 2024, Florence, Italy.

<figure><img src="image_82.png" /></figure>
## Resilience indicators based on body weight data in laying hens

> "The objective of this research was to investigate genetic parameters of resilience indicators based on standardized body weight (BW) deviations and to investigate its relation with immunity (i.e. NAb) and disease resistance."

### Selection experiment for *natural antibodies*: High vs. Low

* Observations: 4-weekly

* # observations: 5 (cut-off) to 8

* Standardization ($\mu=0, \sigma=1$): line*generation*age (BW High > BW Low)

* n=1,500 individuals

**Selection experiment**
natural antibodies

<figure><img src="image_83.png" /></figure>

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## Resilience indicators based on body weight data in laying hens

"The objective of this research was to investigate genetic parameters of resilience indicators based on standardized body weight (BW) deviations and to investigate its relation with immunity (i.e. NAb) and disease resistance."

Resilience indicator traits:

- Theoretical standardized body weight : batch average for each line / generation / time

- Observed standardized body weight

- Deviations = observed – theoretical

For each hen, we can then calculate:

- ln(variance(deviations)) : indication of the general impact of the disturbances ($\Leftrightarrow \text{lnvar} = \text{\textbf{\textup{resilience}}}$)

- Skewness : indication of the direction of the impact of the disturbances ($\text{skewness} \sim 0$ = same deviations as random)

- Autocorrelation : indication of the recovery from a disturbances (if impacted) ($\text{auto-r} \le 0$ = $\text{\textbf{\textup{resilience}}}$)
## Resilience indicators based on body weight data in laying hens

“The objective of this research was to investigate genetic parameters of resilience indicators based on standardized body weight (BW) deviations and to investigate its relation with immunity (i.e. NAb) and disease resistance.”

<table><thead><tr><th></th><th>In(var)</th><th>skew</th><th>r<sub>auto</sub></th></tr></thead><tbody><tr><th>GCV</th><td>0.30</td><td>1.56</td><td>0.52</td></tr><tr><th>h<sup>2</sup></th><td>0.10</td><td>0.09</td><td>0.11</td></tr></tbody></table>

Substantial GCV = genetic improvement is possible

Low h² = low response to selection

<table><thead><tr><th>r<sub>g</sub></th><th>In(var)</th><th>skew</th></tr></thead><tbody><tr><th>skew</th><td>-0.20</td><td>-</td></tr><tr><th>r<sub>auto</sub></th><td>0.40</td><td>0.07</td></tr></tbody></table>

Rather favorable r_g (except for Invar and skew)
<figure><img src="image_85.png" /></figure>

# Resilience indicators based on body weight data in laying hens

"The objective of this research was to investigate genetic parameters of resilience indicators based on standardized body weight (BW) deviations and to investigate its relation with immunity (i.e. NAb) and disease resistance."

<table><thead><tr><th rowspan="2"></th><th colspan="3">Genetic correlations</th></tr><tr><th>IgTotal</th><th>IgM</th><th>IgG</th></tr></thead><tbody><tr><th>ln(variance)</th><td>-0.09 (0.12)</td><td>-0.09 (0.12)</td><td>-0.06 (0.13)</td></tr><tr><th>skewness</th><td>0.01 (0.12)</td><td>-0.01 (0.13)</td><td>0.01 (0.13)</td></tr><tr><th>autocorrelation</th><td>0.02 (0.12)</td><td>0.08 (0.12)</td><td>0.01 (0.13)</td></tr></tbody></table>

Low r<sub>g</sub> = low common genetic background
= little (no) correlated response

Lnvar, skewness and autocorrelation = indicator traits of resilience

IgT, IgM, and IgG are NAbs (natural antibodies) = indicator traits of general immunity

<figure><img src="image_86.png" /></figure>
<figure><img src="image_87.png" /></figure>

# Resilience indicators based on body weight data in laying hens

"The objective of this research was to investigate genetic parameters of resilience indicators based on standardized body weight (BW) deviations and to investigate its relation with immunity (i.e. NAb) and disease resistance."

<table><caption>TABLE 5 | Predictors for avian pathogenic *Escherichia coli* mortality.</caption><thead><tr><th>Predictor</th><th># Predictors</th><th>HR</th><th>p</th></tr></thead><tbody><tr><td>EBV<sub>NAb</sub></td><td>1</td><td>0.59</td><td>0.01</td></tr><tr><td>EBV<sub>In(variance)</sub></td><td>1</td><td>1.98</td><td>0.63</td></tr><tr><td>EBV<sub>skewness</sub></td><td>1</td><td>2.60</td><td>0.59</td></tr><tr><td>EBV<sub>autocorrelation</sub></td><td>1</td><td>33.70</td><td>0.26</td></tr><tr><td>EBV<sub>NAb</sub> + EBV<sub>In(variance)</sub></td><td>2</td><td>0.54<br>0.26</td><td>0.01<br>0.39</td></tr><tr><td>EBV<sub>NAb</sub> + EBV<sub>skewness</sub></td><td>2</td><td>0.59<br>1.89</td><td>0.01<br>0.70</td></tr><tr><td>EBV<sub>NAb</sub> + EBV<sub>autocorrelation</sub></td><td>2</td><td>0.58<br>39.90</td><td>0.01<br>0.22</td></tr></tbody></table>

<table><caption>TABLE 6 | Predictors for avian pathogenic *Escherichia coli* total lesion scores.</caption><thead><tr><th>Predictor</th><th># Predictors</th><th>β</th><th>p</th></tr></thead><tbody><tr><td>EBV<sub>NAb</sub></td><td>1</td><td>-0.50</td><td>0.09</td></tr><tr><td>EBV<sub>In(variance)</sub></td><td>1</td><td>6.20</td><td>0.03</td></tr><tr><td>EBV<sub>skewness</sub></td><td>1</td><td>5.85</td><td>0.20</td></tr><tr><td>EBV<sub>autocorrelation</sub></td><td>1</td><td>-5.70</td><td>0.76</td></tr><tr><td>EBV<sub>NAb</sub> + EBV<sub>In(variance)</sub></td><td>2</td><td>-0.37<br>5.36</td><td>0.23<br>0.07</td></tr><tr><td>EBV<sub>NAb</sub> + EBV<sub>skewness</sub></td><td>2</td><td>-0.38<br>4.89</td><td>0.07<br>0.14</td></tr><tr><td>EBV<sub>NAb</sub> + EBV<sub>autocorrelation</sub></td><td>2</td><td>-0.54<br>-6.49</td><td>0.09<br>0.60</td></tr></tbody></table>

EBV for Invar was predictive of lesions scores from *E. coli* challenge
However, none of the EBV for resilience indicator traits was associated to mortality to *E. coli*
## Resilience indicators based on body weight data in laying hens

> "The objective of this research was to investigate genetic parameters of resilience indicators based on standardized body weight (BW) deviations and to investigate its relation with immunity (i.e. NAb) and disease resistance."

Resilience indicator traits:

* Have substantial GCV = selection is possible

* Have low h² = response to selection is low

* Are not correlated with general immunity (NAbs)

* Are possibly correlated with disease resistance (morbidity, not mortality)

<figure><img src="image_88.png" /></figure>
## Resilience indicators based on body weight data in laying hens

> "The objective of this research was to investigate genetic parameters of resilience indicators based on standardized body weight (BW) deviations and to investigate its relation with immunity (i.e. NAb) and disease resistance."

Some may say that 5 to 8 records is not frequent enough to capture fluctuations

<figure><img src="image_89.png" /></figure>

Ghaderi Zefreh et al. (2024)

Resilience indicator traits are robust to low recording frequencies

However, BW fluctuations are maybe too slow physiological processes
## Let's go through a few examples

### Resilience indicators derived from body weight data

* Berghof, T.V.L., Henk Bovenhuis, Mulder, H.A., 2019. **Body Weight Deviations as Indicator for Resilience in Layer Chickens.** Front. Genet. 10, 1216. https://doi.org/10.3389/fgene.2019.01216

### Resilience indicators derived from egg production data

* Bédère, N., Berghof, T., Peeters, K., Pinard-van Der Laan, M.-H., Visscher, J., David, I., Mulder, H., 2022. **Using egg production longitudinal recording to study the genetic background of resilience in purebred and crossbred laying hens.** Genetics Selection Evolution 54, 12 p. https://doi.org/10.1186/s12711-022-00716-8

* Berghof, T., Bédère, N., Peeters, K., Poppe, M., Visscher, J., Mulder, H., 2024. **The genetics of resilience and its relationships with egg production traits and antibody traits in chickens.** Genetics Selection Evolution 56, 20. https://doi.org/10.1186/s12711-024-00888-5

* Doekes, H.P., Bovenhuis, H., Berghof, T.V.L., Peeters, K., Visscher, J., Mulder, H.A., 2023. **Research Note: Genome-wide association study for natural antibodies and resilience in a purebred layer chicken line.** Poultry Science 102, 102312. https://doi.org/10.1016/j.psj.2022.102312

* Fodor, I., Duenk, P., Visser, B., Janssen, D., Calus, M. P. L., van der Sluis, M., Kamphuis, C., 2024. **Novel resilience indicators based on egg production in laying hens**, in: Proceedings 75th Annual Meeting of the EAAP. 01 sept 2024, Florence, Italy.
> Resilience indicators based on egg production data in laying hens

"Our objectives were: (i) to study the genetic parameters of resilience indicator traits that are derived from longitudinal egg production data, (ii) to assess whether these traits are genetically correlated in purebreds and crossbreds (purebred–crossbred correlation), and (iii) to assess the genetic correlations of these traits with egg production", "the predictive potential of the resilience indicators for immunity traits", "heat tolerance", and GWAS

Laying hens lines from Hendrix Genetics :

<figure><img src="image_90.png" /></figure>

White Leghorn (WA)

* Purebreds n = 33,825 ind.

* Crossbreds

* 6,154 cages of 6 hens

* 6,698 cages of 7 hens

<figure><img src="image_91.png" /></figure>

Rhode Island (BD)

* Purebredss n = 34,397 ind.

* Crossbreds

* 2,428 cages of 7 hens

* 1,470 cages of 8 hens

Pedigree > 4 generations

Pop structure: 50 purebred offsprg./sire | 35 crossbred offsprg/sire

<figure><img src="image_92.png" /></figure>
> Resilience indicators based on egg production data in laying hens

"Our objectives were: (i) to study the genetic parameters of resilience indicator traits that are derived from longitudinal egg production data, (ii) to assess whether these traits are genetically correlated in purebreds and crossbreds (purebred–crossbred correlation), and (iii) to assess the genetic correlations of these traits with egg production", "the predictive potential of the resilience indicators for immunity traits", "heat tolerance", and GWAS

<figure><img src="image_93.png" /><figcaption>Data collection set-up:</figcaption></figure>
> Resilience indicators based on egg production data in laying hens

"Our objectives were: (i) to study the genetic parameters of resilience indicator traits that are derived from longitudinal egg production data, (ii) to assess whether these traits are genetically correlated in purebreds and crossbreds (purebred–crossbred correlation), and (iii) to assess the genetic correlations of these traits with egg production", "the predictive potential of the resilience indicators for immunity traits", "heat tolerance", and GWAS

<figure><img src="image_94.png" /><figcaption>Not resilient hen</figcaption></figure>

<figure><img src="image_95.png" /></figure>

<figure><img src="image_96.png" /></figure>
> Resilience indicators based on egg production data in laying hens

"Our objectives were: (i) to study the genetic parameters of resilience indicator traits that are derived from longitudinal egg production data, (ii) to assess whether these traits are genetically correlated in purebreds and crossbreds (purebred-crossbred correlation), and (iii) to assess the genetic correlations of these traits with egg production", "the predictive potential of the resilience indicators for immunity traits", "heat tolerance", and GWAS

<figure><img src="image_97.png" /></figure>

<figure><img src="image_98.png" /></figure>

BD : similar results
## Resilience indicators based on egg production data in laying hens

“Our objectives were: (i) to study the genetic parameters of resilience indicator traits that are derived from longitudinal egg production data, (ii) to assess whether these traits are genetically correlated in purebreds and crossbreds (purebred-crossbred correlation), and (iii) to assess the genetic correlations of these traits with egg production”, “the predictive potential of the resilience indicators for immunity traits”, “heat tolerance”, and GWAS

<table><caption>**Table 11** Estimates of genetic correlations between resilience indicators and antibody traits</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Period</th><th colspan="2">White</th><th colspan="2">Brown</th></tr><tr><th>IgM</th><th>IgG</th><th>IgM</th><th>IgG</th></tr></thead><tbody><tr><td rowspan="2">In(variance)</td><td>25-83</td><td>-0.09<br>(0.11)</td><td>0.06 (0.17)</td><td>-0.03<br>(0.30)</td><td>-0.27 (0.32)</td></tr><tr><td>83-end</td><td>-0.12<br>(0.12)</td><td>-0.02<br>(0.18)</td><td>-0.21<br>(0.34)</td><td>-0.24 (0.39)</td></tr><tr><td rowspan="2">Skewness</td><td>25-83</td><td>0.08 (0.13)</td><td>-0.18<br>(0.19)</td><td>-0.16<br>(0.42)</td><td>0.16 (0.48)</td></tr><tr><td>83-end</td><td><sup>a</sup></td><td><sup>a</sup></td><td>0.28 (0.34)</td><td>-0.09 (0.39)</td></tr><tr><td rowspan="2">Autocorrelation</td><td>25-83</td><td>0.16 (0.12)</td><td>0.21 (0.18)</td><td>-0.09<br>(0.31)</td><td>-0.15 (0.33)</td></tr><tr><td>83-end</td><td>0.15 (0.15)</td><td>0.13 (0.21)</td><td>0.03 (0.42)</td><td>0.56 (0.42)</td></tr></tbody></table>

No significant genetic correlation between resilience indicator traits and immunity traits
> Resilience indicators based on egg production data in laying hens

"Our objectives were: (i) to study the genetic parameters of resilience indicator traits that are derived from longitudinal egg production data, (ii) to assess whether these traits are genetically correlated in purebreds and crossbreds (purebred-crossbred correlation), and (iii) to assess the genetic correlations of these traits with egg production", "the predictive potential of the resilience indicators for immunity traits", "heat tolerance", and GWAS

<figure><img src="image_99.png" /></figure>

Higher mean InVar ~ lower production at thermoneutral circumstances
~ lower sensitivity to heat stress (at least during the pic and persistency)

On-going work of Fodor et al.
> Resilience indicators based on egg production data in laying hens

"Our objectives were: (i) to study the genetic parameters of resilience indicator traits that are derived from longitudinal egg production data, (ii) to assess whether these traits are genetically correlated in purebreds and crossbreds (purebred–crossbred correlation), and (iii) to assess the genetic correlations of these traits with egg production", "the predictive potential of the resilience indicators for immunity traits", and GWAS

Both resilience indicator traits and
immunity traits displayed a highly
polygenic background

<figure><img src="image_100.png" /></figure>

<figure><img src="image_101.png" /></figure>
> Resilience indicators based on egg production data in laying hens

"Our objectives were: (i) to study the genetic parameters of resilience indicator traits that are derived from longitudinal egg production data, (ii) to assess whether these traits are genetically correlated in purebreds and crossbreds (purebred–crossbred correlation), and (iii) to assess the genetic correlations of these traits with egg production", "the predictive potential of the resilience indicators for immunity traits", and GWAS

Resilience indicator traits, derived from EP, displayed similar results than those from BW on different populations:

* Have substantial GCV = selection is possible

* Have low h² = response to selection is low

* Are not correlated with general immunity (NAbs)

+ new:

* Favorably correlated with egg number

* Favorably correlated with heat tolerance

* No QTL with major effect, highly polygenic traits

+ cherry on top of the cake:

* Purebred-crossbred genetic correlations lower than hoped → crossbred data is valuable

* High genetic correlations between periods → consistency

* High genetic correlation between methods of theoretical EP → consistency

<figure><img src="image_102.png" /></figure>
> Resilience indicators based on egg production data in laying hens

"Our objectives were: (i) to study the genetic parameters of resilience indicator traits that are derived from longitudinal egg production data, (ii) to assess whether these traits are genetically correlated in purebreds and crossbreds (purebred-crossbred correlation), and (iii) to assess the genetic correlations of these traits with egg production", "the predictive potential of the resilience indicators for immunity traits", and GWAS

<figure><img src="image_103.png" /></figure>

Moderate genetic correlations between purebreds and crossbreds

<table><thead><tr><th>WA</th><th>h<sup>2</sup><sub>p</sub></th><th>h<sup>2</sup><sub>c</sub>*</th><th>r<sub>pc</sub></th><th>r<sub>g (pures)</sub></th></tr></thead><tbody><tr><td>NOT</td><td>0,11</td><td>0,05 - 0,07</td><td>0,31</td><td>#</td></tr><tr><td>LNVAR</td><td>0,10</td><td>0,13</td><td>0,16</td><td>-0.72</td></tr><tr><td>ASYM</td><td>0,04</td><td>0,005 - 0,006</td><td>0,20</td><td>-0.05</td></tr><tr><td>AUTO-R</td><td>0,06</td><td>0,01 - 0,02</td><td>0,64</td><td>0.25</td></tr></tbody></table>

→ Response in crossbred to selection in purebred will be tune down if information from crossbred is ignored

<figure><img src="image_104.png" /></figure>

BD : similar results
> Resilience indicators based on egg production data in laying hens

"Our objectives were: (i) to study the genetic parameters of resilience indicator traits that are derived from longitudinal egg production data, (ii) to assess whether these traits are genetically correlated in purebreds and crossbreds (purebred-crossbred correlation), and (iii) to assess the genetic correlations of these traits with egg production", "the predictive potential of the resilience indicators for immunity traits", and GWAS

Genetic correlations between different life periods (EP25-83 vs. EP83-end)

<table><thead><tr><th></th><th>In(var)</th><th>skew</th><th>r<sub>auto</sub></th></tr></thead><tbody><tr><td>White</td><td>0.80 (0.04)</td><td>NS</td><td>0.73 (0.07)</td></tr><tr><td>Brown</td><td>0.76 (0.07)</td><td>-0.46 (0.13)</td><td>0.80 (0.08)</td></tr></tbody></table>
> Resilience indicators based on egg production data in laying hens

"Our objectives were: (i) to study the genetic parameters of resilience indicator traits that are derived from longitudinal egg production data, (ii) to assess whether these traits are genetically correlated in purebreds and crossbreds (purebred-crossbred correlation), and (iii) to assess the genetic correlations of these traits with egg production", "the predictive potential of the resilience indicators for immunity traits", and GWAS

<figure><img src="image_105.png" /></figure>

<figure><img src="image_106.png" /></figure>

INRAE
## Resilience indicators based on egg production data in laying hens

“Our objectives were: (i) to study the genetic parameters of resilience indicator traits that are derived from longitudinal egg production data, (ii) to assess whether these traits are genetically correlated in purebreds and crossbreds (purebred-crossbred correlation), and (iii) to assess the genetic correlations of these traits with egg production”, “the predictive potential of the resilience indicators for immunity traits”, and GWAS

<table><thead><tr><th>trait</th><th>period</th><th>White</th><th>Brown</th></tr></thead><tbody><tr><td rowspan="2">ln(var)</td><td>25-83</td><td>0.95 (0.01)</td><td>0.98 (0.01)</td></tr><tr><td>83-end</td><td>0.996 (0.002)</td><td>0.99 (0.01)</td></tr><tr><td rowspan="2">skew</td><td>25-83</td><td>0.27 (0.08)</td><td>0.001 (0.14)</td></tr><tr><td>83-end</td><td>NS</td><td>0.99 (0.01)</td></tr><tr><td rowspan="2">r<sub>auto</sub></td><td>25-83</td><td>0.62 (0.06)</td><td>0.73 (0.06)</td></tr><tr><td>83-end</td><td>0.92 (0.02)</td><td>0.97 (0.02)</td></tr></tbody></table>

Heritabilities of individual EP curve were slightly higher
## › Resilience indicators based on egg production data in laying hens

“Our objectives were: (i) to study the genetic parameters of resilience indicator traits that are derived from longitudinal egg production data, (ii) to assess whether these traits are genetically correlated in purebreds and crossbreds (purebred–crossbred correlation), and (iii) to assess the genetic correlations of these traits with egg production”, “the predictive potential of the resilience indicators for immunity traits”, and GWAS

Egg number is a special trait, with a binary nature and a large selection history.

Other traits closely related to environmental sensitivity are needed: behavior, feed and water intake, egg weight... so we can't wait for the tools to be ready and the data to be recorded!

<figure><img src="image_107.png" /></figure>

source: Lohmann

<figure><img src="image_108.png" /></figure>

source: Hendrix Genetics

<figure><img src="image_109.png" /></figure>

Guettier et al. (2020)

<figure><img src="image_110.png" /></figure>

Rufener et al. (2018)

<figure><img src="image_111.png" /></figure>

Ellen et al. (2019)
Resilience: from theory to practice in chicken

<figure><img src="image_112.png" /></figure>

Thank you for listening!

<caption>Nicolas Bédère (CV)</caption>

INRAE, UMR PEGASE, Saint-Gilles (France)

Research in genetics of environmental sensitivity in layers