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The role of genetic constraints and social environment in explaining female extra-pair mating

Why females of socially monogamous species copulate with males other than their partner has been a long-standing, unresolved puzzle. We previously reported that female promiscuity appears to be a genetic corollary of male promiscuity (intersexual pleiotropy hypothesis). Here we put this earlier finding to a critical test using the same population of zebra finches Taeniopygia guttata. After three generations of artificial selection on male courtship rate, a correlate of extra-pair mating, we assess whether female promiscuity changed by indirect selection and we re-examine the crucial genetic correlations. Our new analyses with substantially increased statistical power clearly reject the hypothesis that male and female promiscuity are genetically homologous traits. Our study highlights that individual females show low repeatability in extra-pair mating behavior across different social environments. This emphasizes the potential importance of pair bond strength and the availability of favored extra-pair males as factors explaining variation in patterns of female promiscuity.


Introduction
Why females in socially monogamous species actively engage in matings outside the pair bond 16 is a long-standing, intriguing question [1][2][3][4][5]. Mating outside the pair bond is obviously adaptive 17 for males (i.e. benefits from this behavior will typically outweigh costs), because it leads to 18 additional offspring that are raised by another pair, and hence directly increases male fitness [6, 19 7]. However, why females engage in extra-pair copulations is more puzzling: promiscuous 20 behavior does not increase the number of offspring females can produce and is associated with 21 costs such as increased predation risk, increased risk of contracting sexually transmitted 22 diseases, reduced paternal care and punishment by the social mate [1,4]. In birds, more than 90% 23 of species breed in socially monogamous pairs, but extra-pair paternity is common [2,8]. Birds 24 have served as paragons for studying the evolution of female promiscuity, because males 25 typically cannot force copulations and females often actively seek extra-pair copulations [9][10][11]. 26 The majority of studies tried to explain the occurrence of female extra-pair mating behavior by 27 highlighting the potential benefits [1, 2, 12]. These included indirect genetic [13][14][15] as well as 28 direct ecological benefits [8,16,17]. Yet, despite much empirical work, the general support for 29 these adaptive scenarios remains limited [4,[18][19][20][21]. Therefore, alternative, non-adaptive 30 explanations deserve attention [12]. 31 Several hypotheses of 'genetic constraint' have been proposed to solve the evolutionary puzzle 32 of apparent non-adaptive female extra-pair behavior [22,23]. These hypotheses assume that 33 promiscuous behavior is heritable and state that the alleles underlying female promiscuity are 34 maintained in the population, because they have additional pleiotropic effects that are 35 beneficial to at least one sex. Depending on whether the pleiotropic effect is expressed in males 36 or females, two types of hypotheses can be distinguished. 37 (1) The hypothesis of 'intersexual pleiotropy' proposes that female and male promiscuity are 38 homologous traits that are affected by the same sets of genes [22]. Alleles that increase 39 promiscuity will be maintained in the population due to positive selection in males. When 40 inherited to a daughter, these alleles will cause female promiscuity even if this behavior is not 41 adaptive for females. This hypothesis requires a positive genetic correlation between measures 42 of female and male promiscuity (i.e. positive cross-sex genetic covariance). 43 (2) The hypothesis of 'intrasexual pleiotropy' posits that female promiscuity is maintained 44 because its causal alleles have pleiotropic effects on other female traits that are under positive 45 selection [11,23]. For example, female responsiveness to male courtship might be genetically 46 linked to female fecundity, because courtship may proximately stimulate egg production [24]. 47 Alternatively, genetic variants underlying increased female sexual responsiveness towards her 48 social mate may be favored by selection because low responsiveness can lead to infertility and 49 hence reduced fitness [23]. Positive selection on alleles for increased responsiveness towards 50 the social mate could then lead to increased female responsiveness towards extra-pair males as 51 well. This hypothesis requires that female promiscuity is positively genetically correlated to 52 either female fecundity or to female responsiveness towards her social mate (i.e. within-sex 53 genetic covariance). 54 Empirical testing of these hypotheses using field data on extra-pair paternity is difficult, because 55 heritability of male and female promiscuity is low [25][26][27][28]. The main problem is that the realized 56 patterns of paternity also depend on factors other than the intrinsic inclination of an individual 57 to seek extra-pair copulations, such as sperm competition and mate guarding. 58 In an earlier study on captive zebra finches [ This study also amends a weakness of the initial study: previously, we measured the behavior of 75 a female only once, in the context of being paired to the partner she had chosen in an 76 experiment. The observed behavior was then assumed to be representative for that female. 77 However, extra-pair behavior might also have been a property of the female's social environment (e.g. strength of the social pair bond, characteristics of the available extra-pair 79 males). To resolve this, we here measured extra-pair behavior of each female with two 80 successive partners. This allows to assess the amount of variation that is due to the female and 81 to the environment. Thus, we examine the repeatability of female promiscuity and quantify its 82 heritability and genetic covariance with other traits. 83 To examine the 'intersexual pleiotropy' hypothesis, we quantified the sign and strength of the

90
Selection lines for male courtship rate 91 We established six selection lines and bred them over three consecutive generations: two lines 92 selected for high male courtship rate, two for low courtship rate, and two unselected control 93 lines. Figure 1 shows, for each generation, the actual phenotypes (courtship rate) of all male 94 offspring that were bred as a function of the mean breeding value of their parents (i.e. as a 95 function of the predicted offspring phenotypes based on a genetic model that includes the 96 observed phenotypes of parents and their relatives). The slope of the regression lines is close to 97 unity, indicating that the offspring generations behaved as predicted by the genetic model. With  Table S3).

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Indirect response to selection 106 We assessed whether the successful selection on male courtship rate resulted in correlated  Figure 5; estimates of 142 between-sex genetic correlations from 5-trait animal models based on the initial data ( Figure 5A 143 Table S10, S11) are contrasted with estimates from models based on data from the lines 144 artificially selected for high and low male courtship rate ( Figure 5B; Tables S12, S13). The latter 145 show between-sex genetic correlations close to zero for male courtship rate (median of four 146 estimates: r A = 0.04, Figure 5B; Table S18), and negative values (i.e. opposite to expectations) 147 for male extra-pair siring success (median r A = -0.34, Figure 5B; Table S18). These estimates 148 stand in strong contrast to the positive estimates derived from the initial data ( Figure 5A). An 149 updated matrix of genetic correlations estimated from the joint data (initial plus selection lines) 150 shows weekly positive genetic correlations that are not significantly different from zero ( Figure   151 5C; summary of Tables S6 to S9 showing medians of estimates from four types of models).

152
Testing the 'intrasexual pleiotropy' hypothesis 153 We found a moderately strong positive genetic correlation between female responsiveness to 154 extra-pair male courtship ('female extra-pair response') and female fecundity ( Figure 5D), yet its 155 estimated strength varied considerably across different models (between 0.05 and 0.59, Table   156 S14 to S17). Estimated genetic correlations between female extra-pair and within-pair response 157 were weakly positive ( Figure 5D), but also not robust (see Tables S14 to S17). Note that genetic  Table S4). 175 However, we base our conclusions on animal models that control for non-independence of 176 individuals in the different selection lines via genetic relatedness ( Figure 5). 177 We found a significant, positive genetic covariance between female responsiveness to extra-pair 178 males ('female extra-pair response') and female fecundity, and a somewhat lower positive 179 genetic covariance between female extra-pair responsiveness and her responsiveness to her 180 social mate ('female within-pair response') ( Figure 5D). This finding should be interpreted 181 cautiously (given that the estimates did not seem robust, see also below) and deserves more 182 study, in particular from populations of different species breeding in the wild. 183 Our study reveals strong context dependence of female extra-pair mating behavior: 'Pair ID' 184 explained more variation than female identity (Figure 3, Tables S6, S7). This could reflect 185 variation in the quality of the social pair bond, or in the set of available extra-pair males, which 186 can be studied further under a social network framework [5]. 187 Comparison of the initial study with this study 188 The conclusions from this study and from our earlier work [29] differ substantially. We discuss 189 several potential explanations for this difference. First, the initial study was based on a smaller In conclusion, we suggest that the significant finding in our initial study [29] is a type I error 203 resulting from relatively noisy data. There is no evidence that inadequate modelling caused the 204 difference, because updating the earlier models by including clutch and pair identity ('Clutch ID', 205 'Pair ID') as additional random effects, did not alter the conclusions (see Figure 5A and Tables 206 S10 and S11). Note that estimates from Bayesian models in MCMCglmm were smaller, had 207 larger standard errors and were closer to estimates from the follow-up study than those from 208 REML models in VCE (Table S18) (Table S1).  (Table S1) Table S19). For each line, we let 15 pairs breed in one 300 of 90 randomly assigned cages (60×40x45cm) distributed over two breeding rooms (45 cages 301 each). First, we randomly selected birds from the entire pool for the two control lines. Then, we 302 selected 30 birds of each sex with the highest breeding values for courtship rate for the two 303 'high' lines, and randomly allocated half of them to each replicate line. Thereafter, we also 304 selected six 'replacement' individuals of each sex (in case a high line bird would die during 305 breeding) with the next highest breeding values and distributed them randomly among the two 306 lines. The two low lines were selected in the same manner, but using the birds with the lowest 307 breeding values. 308 Within each line, the 15 breeding pairs were chosen in such a way as to minimize the level of 309 inbreeding (see Table S19). Each pair was allowed to breed in two 'rounds' over a total period of 310 about 14 months (from pair formation to independence of the last offspring). In each round, we 311 allowed pairs to breed until we obtained about 50 juveniles from each line. After round one, we 312 redistributed the birds within each line such that they obtained a new partner (breeding cages 313 again randomly assigned). In this way, we created maternal and paternal half sibs, which 314 facilitated the separation of maternal effects from additive genetic effects. We placed juveniles 315 (age: 35 to about 120 days) of each breeding round in one of two large, mixed-sex groups. Thus, 316 across both rounds of breeding of each generation (S0, S1 and S2, details see below), roughly 317 600 offspring were raised in four mixed-sex groups comprising roughly 75 males and 75 females 318 from all lines.

319
Breeding generations 'S1' to 'S3' 320 Birds of the S0 generation produced 568 offspring of which 546 survived until we started 321 breeding the next generation (see Table S19). 'Male courtship rate' and 'female unpaired 322 response' of these offspring were measured four times per individual (age of testing is given in 323 Table S19). These new measurements were added to update the animal model (with the same 324 fixed and random effects) for the calculation of predicted breeding values for all individuals (n = 325 1,929). The new model included 4,362 measurements of courtship rate from 947 males. 326 We selected the S1 breeders (15 pairs plus five replacement birds of each sex in each line) as 327 described above (random selection for control lines and based on breeding values for high and 328 low lines; Table S19). Again, we assigned breeding pairs in such a way as to minimize and 329 standardize the average inbreeding coefficient. Specifically, in the most inbred line (high 2), we 330 minimized inbreeding, while in the other five lines we chose pairs to match the mean value for 331 this line. The mean inbreeding coefficients of the resulting offspring for each line are given in 332   Table S19. The following generations S2 and S3 were bred following the same principles (see 333 Table S19 for summary statistics).  Table S19). individual females based on the assignment of 9,127 eggs (mean ± SD = 10.7 ± 6.8, range 0-38). 418 We statistically accounted for potential differences between the eight breeding experiments 419 (see below). 420

421
Sample sizes and descriptive statistics of the data used for quantitative genetic analyses are 422 given in Table S1 (including the data from the initial study, [29]). We used similar models as in 423 the initial study, except that we included additional random effects (e.g. 'Pair ID' and 'Clutch ID') 424 and modelled an effect as random instead of fixed (e.g. 'Test Batch ID'), where appropriate. To 425 examine whether conclusions of the initial study depended on these decisions about model 426 structure, we repeated the initial analyses with the updated model structure.   453 The number of extra-pair eggs males sired within each breeding round ('Male EPP') was square-454 root transformed to approach normality, and was modelled as the dependent variable (Table   455   S1). 'Male EPP' increased strongly with the number of days the male was paired. This fixed 456 effect controls for variation in the duration of the breeding period and in the duration of the 457 period a male was unpaired. 'Male EPP' also declined with male inbreeding coefficient (Table   458   S2). The random effects 'Male ID' and 'breeding year' (six levels) explained 21% and 8% of the 459 variance, respectively.

460
Female unpaired response 461 The responsiveness of unpaired females to male courtship ('female unpaired response' in cages) 462 differed significantly among consecutive test days (4 levels) and was higher for females reared 463 in mixed-sex as opposed to unisex groups (   (Table S2). The random effects 'Female ID', 'Pair ID' (i.e. the 476 combination of identities of the courted female and the courting extra-pair male) and 'Year' 477 explained 5%, 23% and 1% of the variance, respectively. 478 The 'female within-pair response' declined strongly with time after sunrise, and increased 479 strongly with the duration of the pair bond (days paired). Within-pair responsiveness varied 480 similarly over the fertile cycle as extra-pair responsiveness (Table S2). The random effects 481 'Female ID', 'Pair ID', and 'Year' accounted for 1%, 15% and 5% of the variance, respectively.  (Table S2). The random effects 'Female ID', 'Pair ID' 489 and 'clutch ID' (a clutch was defined as having no laying gaps longer than 4 days) explained 9%, 490 26% and 37% of the variance, respectively. 491 Female fecundity 492 'Female fecundity' (number of eggs laid per breeding round) was square-root transformed to 493 approach normality. Female fecundity increased with the number of days a female spent in the 494 aviary (mean ± SD = 60 ± 23 days, range 1-112), and decreased with female age (mean ± SD = 495 735 ± 285 days, range 265-1511 days; Table S2). The random effects 'Female ID' and 496 'Experiment ID' (18 levels after differentiating testing cohorts and breeding rounds) explained 497 45% and 10% of the variance, respectively. 498 c) Quantitative Genetic Analyses 499 We used animal models to carry out quantitative genetic analyses, closely following the initial 500 study [29]. To calculate the parameters, we implemented both a restricted maximum likelihood 501 (REML) method using VCE 6.0.  Table S2. All 512 models are based on the joint data from the initial study [29] and the selection lines. 513 For comparison between earlier and new findings, we also ran models 1 and 2 on the respective 514 subsets of data (initial data: models 5 and 6 which are updated for model structure compared to 515 the ones published previously; new data: models 7 and 8). 516 To test the 'intrasexual pleiotropy' hypothesis, we used four versions of animal models (similar 517 to models 1 to 4 above) to estimate the heritability and genetic correlations within females (five