Genetic assessment of fighting ability in Valdostana cattle breeds
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1 Genetic assessment of fighting ability in Valdostana cattle breeds Cristina Sartori and Roberto Mantovani Department of Animal Science, University of Padua
2 Introduction Fighting Ability Capability to win a contest (Parker, 1974) In cows: rigid dominance relations quickly established at grazing when unfamiliar individuals meet (Beilharz & Zeeb, 1982)
3 Introduction Aosta Chestnut & Aosta Black Pied cattle (Valdostana breed) Autochthonous of West Alps Dual Purpose Population (21): Chestnut n=22,857; Black Pied n=1394 Strong attitude to fight: Batailles de Reines
4 Batailles de Reines Introduction
5 Bataillesde Reines Introduction Each year: 2 Eliminatories + Final battle 3 Tournaments per day, defined by weight Knock-out battles among couples Heréns breed Valais, CH / Haute Savoie, FR, Aosta Black Pied & Aosta Chestnut, Aosta, IT
6 Steps of the study Introduction To sum up the studies carried on fighting ability in Aosta Chestnut and Aosta Black Pied cattle, in terms of: 1. Behavioural evaluation of agonistic performances 2. Genetic assessment of fighting ability 3. Incidence of inbreeding on the trait General aim => to build up genetic indexes suitable for breeding
7 To sum up the studies carried on fighting ability in Aosta Chestnut and Aosta Black Pied cattle, in terms of: 1. Behavioural evaluation of agonistic performances 2. Genetic assessment of fighting ability 3. Incidence of inbreeding on the trait General aim => to build up genetic indexes suitable for breeding
8 1. Behavioural evaluation of fights Materials & Methods (Sartori, Manser and Mantovani, in prep.) Video recording of 4 tournaments performed in 29 (n = 188 fights) Quantification of the main behaviours expressed during cow fights (JWatcher TM software) Ethogram for cattle escalated conflict
9 1. Behavioural evaluation of fights Materials & Methods Statistical analyses Evaluation of dynamics of conflicts, in terms of: - duration - agonistic intensity - ratio of different behaviours* on total battle *non agonistic behaviours; exhibitions; physical fights Mixed linear model for repeated measurements (SAS, 24) (Sartori, Manser and Mantovani, in prep.)
10 1. Behavioural evaluation of fights Results NA NA Friendly Passive Defence of resource Visual display E E E E Vocalization Looking in eyes Pushing Vigorous clash PF PF 1, 2, 6 = score of intensity NA = Non agonistic behaviour; E = exhibition; PF = Physical fight
11 1 Friendly NA 1. Behavioural evaluation of fights Results 2 Passive 3 NA E Transition diagram of behaviours obtained from ethograms (JWatcher TM, Blumstein & Daniel, 27) Defence of resource 3 E 3 Visual display Least squares means and standard errors of diff. number of fights disputed in the tournament (MIXED Procedure, SAS 24, Bonferroni adjustment method) E 4 Vocalization Variable 1 st Match disputed 3 rd 5 th E 5 Looking in eyes PF Duration of match (sec.) Intensity of match (score) 21.1 (28.6) 3.34 (.11) A (27.9) 3.79 (.11) B (4.5) 4.4 (.15) B Non agonistic behavior/total (%).11 (.3) a.12 (.2) a.4 (.1) b Pushing Exhibition/total (%).74 (.4) a.57 (.4) b.59 (.5) b 6 Physical fight/total (%).15 (.3) A.31 (.4) B.37 (.6) B A & B = diff. at P.1 within row; a & b = diff. at P.5 within row PF Vigorous clash
12 To sum up the studies carried on fighting ability in Aosta Chestnut and Aosta Black Pied cattle, in terms of: 1. Behavioural evaluation of agonistic performances 2. Genetic assessment of fighting ability 3. Incidence of inbreeding on the trait General aim => to build up genetic indexes suitable for breeding
13 2. Genetic assessment of the trait Difficulties on genetic analysis of behaviour: Results Low h 2 Great influence of environment (Plomin, 199) Low heritability (Mosseau and Roff 1987) Mark Ridley, 24. Modified from Hoffman 2 Genetic investigation of fighting ability: Data of tournaments Records: 16,59 Participants: 5,891 cows Pedigree: 13,456 animals IDs and pedigree of cows winner & looser of each match individual weight, age & herd weight categories level of the battle board a. Quantitative model for genetic evaluation of fighting ability b. Assessment of the opponents incidence on the trait
14 2. Genetic assessment of the trait Materials & Methods a. Genetic evaluation I. Phenotype for fighting ability (Sartori & Mantovani, 29; 21) Placement Score (PS) PS ijkl =2+ty i +d j +2w k PS = score of cow in a given tournament ty = type of tournament (ty= for heats & ty=7 for final) d = difficulty coefficient (j=-2: >128, -1: , : 33-64, 1: 17-32, 2: <17 participants) w = number of wins achieved (k=,, 8)
15 Materials & 2. Genetic assessment of the trait Methods II. Genetic model (Sartori & Mantovani, 29; 21) y = Xβ + W D p D + Z D a D + e Vectors: y = observations β = systematic fixed factors, p D = permanent environmental effects a D = direct additive genetic effects e = residuals a D V pd e AVa = D AVp IVe Fixed factors (b): Day of tournament (year-battle* weight cat.) Herd-Year Age (in classes) Weight by weight cat. P<.1 for all factors after preliminary ANOVA D EM-REML method, single-trait animal model (Misztal, 28) Models comparison: Akaike Information Criterion (AIC; Akaike, 1974)
16 Materials & 2. Genetic assessment of the trait b. Inclusion of the competitors Methods (Sartori & Mantovani, 29; 21) I. Competitors within the phenotype Competitive PS (CPS) CPS ijkl =5+ty i +2d j -b k -(k-cps ijka ) CPS = score of cow in a given tournament (l=individual; a=competitor) ty = type of tournament (as in PS) d = difficulty coefficient (as in PS) b = highest level achieved (as for w in PS)
17 Materials & 2. Genetic assessment of the trait b. Inclusion of the competitors y = Xβ + W D p D + Z D a D + Z C a C + e Methods (Sartori & Mantovani, 29; 21) II. Competitors within the genetic model Vectors: y = observations β = systematic fixed factors p D = permanent environmental effects a D = direct genetic effects a C = indirect genetic effects (IGEs) e = residuals ad AVa ac = V p D e D AVa C AVp D IVe Fixed factors (b): Day of tournament (year-battle* weight cat.) Herd-Year Age (in classes) Weight by weight cat. P<.1 for all factors after preliminary ANOVA EM-REML method, Competitive animal model, partitioning variance approach (Arango et al., 25; Bijma et al., 27)
18 2. Genetic assessment of the trait Results (Sartori & Mantovani, 29; 21) a. Genetic evaluation Item Classical model, AIC PS no competitors Classical model, competitor in phenotype Competitive model Trait Variance components Va D Va C Vp Ve PS including opponent* h 2 SE h 2 CPS r V a = direct additive genetics, V ass = associative genetics; V p = permanent environmental & V e = random residual; AIC = Akaike Information Criterion; h 2 = heritability; SE h 2 = standard error of h 2 ; r = repeatability
19 2. Genetic assessment of the trait Results (Sartori & Mantovani, 29; 21) b. Inclusion of the competitor Item Classical model, PS no competitors Classical model, competitor in phenotype Competitive model AIC Trait Variance components PS including opponent* *indirect genetic effect Va D Va C Vp Ve More suitable models for genetic analyses h 2 SE h 2 CPS r V a = direct additive genetics, V ass = associative genetics; V p = permanent environmental & V e = random residual; AIC = Akaike Information Criterion; h 2 = heritability; SE h 2 = standard error of h 2 ; r = repeatability
20 To sum up the studies carried on fighting ability in Aosta Chestnut and Aosta Black Pied cattle, in terms of: 1. Behavioural evaluation of agonistic performances 2. Genetic assessment of fighting ability 3. Incidence of inbreeding on the trait General aim => to build up genetic indexes suitable for breeding
21 3. Incidence of inbreeding Materials & Methods (Sartori & Mantovani, in peer review) Data of tournaments Records: 23,998 Participants: 8,259 cows Pedigree: 17,724 animals F coefficient (Inbreeding) INBREEDING Recursive algorithm (Aguilar & Misztal, 28) Herd Book Reference population: individuals born in Item ABP AC Individuals retained for analysis 27,638 16,61 Purebred individuals 27,184 14,854 males 7,764 42,737 females 19,42 62,117 Individuals in Herd Book (21) 11,958 22,857 ABP= Aosta Black Pied cattle, AC=Aosta Chestnut cattle
22 3. Incidence of inbreeding Materials & Methods (Sartori & Mantovani, in peer review) a. Comparison among genetic models including inbreeding or not 4 Models: Inbreeding (F): fixed effect, in classes (based on Sewalem et al., 26; P<.1 for F after ANOVA) Classical model, No F Competitive model, No F Classical model, + F Competitive model + F EM-REML method, single-trait animal model - Competitive model, partitioning variance approach - Models comparison: AIC b. Linear regression of EBVs on F across and within lineages of founders Founders individuals without genetic relationships in pedigree other than their heirs (Gulisija et al., 26) lacking in inbreeding attained using a recursive procedure Dataset 33 lineages 6,87 participants (184±235 heir fighting cows/line) at least 1 fighting cows as offspring EBVs of fighting ability
23 3. Incidence of inbreeding Results (Sartori & Mantovani, in peer review) Genetic trend for inbreeding coefficient (F) Inbreeding coefficient (F) B b ABP = +.6%/year b AC = +.3%/year Birth year Aosta Black Pied Aosta Chestnut (>1 iterations) (16 iterations)
24 3. Incidence of inbreeding Results (Sartori & Mantovani, in peer review) Model fitting, variance components & parameters estimates. Average no.competitors per fighting cows = Fitting Variance Components Genetic parameters Model AIC Vp D Vp C Va D Va C h 2 SE h 2 rep. Classical model, no F Classical model, with F Competitive model*, no F Competitive model*, with NF 111, , , r = 99.2% R 2 = 98.6% 87, *including 4 indirect genetic effects Single-trait ENREML (Misztal et al., 28), mixed linear model, linear form Rank correlation among EBVs of fighting cows' sires; n=818
25 3. Incidence of inbreeding Results (Sartori & Mantovani, in peer review) Within lineage (n=33 with a mean of 184 fighters/lineage) regression coefficients between fighting ability & inbreeding coefficient (F) 1 5 bebv/f Founder
26 Conclusions Conclusions Traditional cow competitions of Aosta Black Pied (ABP) and Aosta Chestnut (AC) cattle vary in intensity during a battle and in the course of a competition Fighting ability can be investigated via quantitative genetics as Placement score Tournament, herd, age & weight affect the trait, which h 2 is about 8% Fighting ability expresses in a social contest, and conspecifics may be included in the genetic model as indirect genetic effects ABP and AC cattle show low levels of inbreeding (2.7% ABP;.8% AC), which influence on fighting ability is slight...further step Genetic correlation among fighting ability and milk & meat yields
27 Thank you for your attention! AnaBoRaVa
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