Genes encode instructions that can influence the behaviour and physical traits of the individual that carries them. Individuals of the same species can carry different versions (or variants) of the same gene, leading to a variety of traits in the population. However, a gene expressed in one individual can also alter the traits of another individual. This is known as an indirect genetic effect. For example, a gene in a mother that affects her ability to provide care may influence how her offspring develop.

Researchers have predicted that offspring should be able to manipulate their mothers to try and gain more care than the mothers are willing to give. Furthermore, the offspring born to mothers who respond to this begging are predicted to save energy and beg less. However, few gene variants that indirectly modify the behaviour of mothers or offspring have so far been identified.

Ashbrook et al. used mice to test the idea that genetic variation in particular locations in the offspring’s genome can affect maternal behaviour, and vice versa. In the first experiment, mother mice with different gene variants fostered litters of mouse pups that were all genetically identical. In the other experiment, genetically identical mothers fostered litters of mouse pups with different gene variants. Ashbrook et al. identified several locations in the offspring’s genome that modified the behaviour of their foster mothers. Furthermore, the experiments also show that genetic variation among the mothers influenced the development of their offspring, independent of the genes carried by the offspring.

The next steps are to identify the specific genes underlying the changes in behaviour, and the molecular and genetic pathways by which they impact indirectly on the traits of other individuals.

The close interaction between mother and offspring in mammals is fundamental to offspring development and fitness. However, parent and offspring are in conflict over how much parents should invest in their young where offspring typically demand more than is optimal for the parent (Trivers, 1974; Godfray, 1995), and the existence of this genetic conflict has been demonstrated in empirical research (Kölliker et al., 2015). The resulting selection pressures are predicted to lead to the evolution of traits in offspring that influence parental behaviour (and thus investment). Conversely, parental traits should be selected for their effects on offspring traits that influence parental behaviour indirectly (Kilner and Hinde, 2012). The correlation between parental and offspring traits has been the focus of coadaptation models where specific combinations of demand and provisioning are selectively favoured (Wolf and Brodie III, 1998; Kölliker et al., 2005). The fundamental assumption underlying predictions about the evolution of traits involved in parent-offspring interactions is that genetic variation in offspring exists for traits that indirectly influence maternal investment and vice versa. However, it remains to be shown whether specific genetic variants in offspring indirectly influence maternal behaviour. In an experimental mouse population, we demonstrate that genes expressed in offspring modify the quality of maternal behaviour and thus affect, indirectly, offspring fitness.

To investigate the genetics of parent-offspring interactions we conducted a cross-fostering experiment between genetically variable and genetically uniform mice, using the largest genetic reference panel in mammals, the BXD mouse population. We generated families of genetically variable mothers and genetically uniform offspring by cross-fostering C57BL/6J (B6) litters, in which no genetic variation occurs between animals of this strain, to mothers of a given BXD strain. Conversely, a BXD female’s litter was cross-fostered to B6 mothers (Figure 1). Thus, we can analyse the effects of genetic variation in mothers or offspring while controlling for genetic variation in the other. This cross-fostering design has been successfully utilized in previous studies on family interactions because it breaks the correlation between maternal and offspring traits. Here, different families, or naturally occurring variation of maternal and offspring trait combinations across different broods, are assumed to represent distinct evolved strategies (Agrawal et al., 2001; Hager and Johnstone, 2003; Meunier and Kölliker, 2012). From birth until weaning at 3 weeks of age we recorded offspring and maternal body weights and behaviour, following Hager and Johnstone (2003).

Figure 1

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We first investigated whether there is evidence for indirect genetic effects in offspring influencing maternal behaviour, keeping maternal genotype constant. To find out if maternal behaviour is modified by genes expressed in offspring, we mapped variation in maternal behaviour as a function of their adoptive BXD offspring genotype. We found that variation in offspring genotype affects maternal behaviour, which in turn influences offspring development and fitness. Throughout, we denote loci as either maternal or offspring, Mat or Osp, followed by whether it is an indirect effect (Ige) or a direct effect locus (Dge). We provide a summary of all loci in Table 1, and mapping details in Supplementary files 1A-D. During the first postnatal week we mapped a locus on offspring chromosome 7, OspIge7.1, modifying maternal nestbuidling on day 6 (Figure 2). At this locus, the D2 allele increases the trait value such that B6 mothers showed more nestbuilding activity when fostering BXD pups carrying the D2 allele at the locus. Nestbuilding is particularly important for offspring fitness as thermoregulation is underdeveloped and hypothermia is the primary cause of early death, even if milk is supplied (Lynch and Possidente, 1978). We detected a further locus on offspring distal chromosome 5 (OspIge5.1) that affects maternal behaviour on day 14, around the time we expect the weaning conflict to be highest (Figure 3). Here, mothers showed increased levels of maternal behaviour when fostering BXD offspring carrying the D2 allele. Conversely, we can look at how variation in maternal genotype influences offspring traits, keeping offspring genotype constant, mapping variation in offspring traits as a function of BXD genotype. Here, we found that offspring growth during the second week is affected by a locus on maternal chromosome 17, MatIge17.1, where the B6 allele increases the trait value (Figure 4). In addition to looking at indirect genetic effects we can analyse direct genetic effects, i.e. how an individual’s genotype influences its own traits. In mothers we found a direct genetic effect locus for maternal behaviour on proximal chromosome 10, and for nestbuilding behaviour on chromosome 1 (MatDge10.1 and MatDge1.1, respectively), where the B6 allele increases the trait value in both cases. We also detected a locus for offspring solicitation behaviour on chromosome 5 (OspDge5.1) with the D2 allele increasing the level of solicitation shown. Its location is at the opposite end on chromosome 5 from where OspIge5.1 is located.

Figure 2

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Figure 2—source data 1

Source data for Figure 2 as uploaded to GeneNetwork, showing the B6 maternal nestbuilding behaviour on day 6 per pup for the BXD lines.

https://doi.org/10.7554/eLife.11814.005

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Figure 3

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Figure 3—source data 1

Source data for Figure 3 as uploaded to GeneNetwork, showing the B6 maternal behaviour on day 14 per pup for the BXD lines.

https://doi.org/10.7554/eLife.11814.007

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Figure 4

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Figure 4—source data 1

Source data for Figure 4 as uploaded to GeneNetwork, showing the B6 offspring growth in the second postnatal week per pup for the BXD lines.

https://doi.org/10.7554/eLife.11814.009

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Overall, our results show that IGEs, as well as DGEs, can be linked to specific loci that affect parent-offspring interaction, and it is thus possible that selection may occur on genes with indirect and direct effects on parental behaviour. Importantly, our result that variation in maternal behaviour is affected by genes expressed in offspring is also clearly borne out at the phenotypic level: offspring solicitation behaviour in genetically variable BXD pups is positively correlated with the level of maternal behaviour in their genetically uniform B6 adoptive mothers on all three days we measured behaviour with significant effects of maternal behaviour and day on offspring solicitation (GLM, F_1,103 = 17.62, P < 0.001 and F_2,103 = 14.22, P < 0.001, respectively; day 6: Pearsons’r = 0.56, P = 0.003; day 10: r = 0.63, P = 0.001, and day 14: r = 0.55, P = 0.008; Supplementary file 2, a). Similarly, we can investigate how traits in genetically uniform B6 offspring correlate with maternal traits in their genetically variable BXD mothers (i.e. within adoptive families). We found that maternal behaviour and day have a significant positive effect on offspring solicitation behaviour (GLM, F_1,118 = 6.33, P = 0.013, and F_2,118 = 6.33, P < 0.001; Supplementary file 2, b). While one might generally assume that mothers behave in response to offspring solicitation behaviour, these results show, perhaps surprisingly, that variation in maternal behaviour influences the level of solicitation: here, we need to remember that there is no variation in offspring genotype so we assume that across families differences in offspring behaviour are due to differences in the genotype of their adoptive mothers.

Coadaptation of parental and offspring traits

While in the previous section we have focused on analysing traits within foster families, we now turn to the correlation between traits of biological families, i.e. mothers and their biological offspring. This correlation has been analysed in coadaptation models, which make specific predictions about how parental and offspring traits are correlated, and in empirical work (Kölliker et al., 2000; Agrawal et al., 2001; Curley et al., 2004; Lock et al., 2004; Kölliker et al., 2005; Hinde et al., 2010; Meunier and Kölliker, 2012). Prior experimental studies have found both a positive (Parus major; Kölliker et al., 2000: Nicrophorus vespilloides; Lock et al., 2004) and negative correlation between offspring solicitation and parental traits (Sehirus cinctus; Agrawal et al., 2001). In our study, we found a negative correlation. When we measured short-term provisioning, we found a negative correlation between BXD offspring short-term weight gain and the corresponding provisioning of their biological (BXD) mothers on day 10, as well as a negative correlation between BXD offspring solicitation and the corresponding provisioning of their biological (BXD) mothers on day 14 (GLM, F_1,32 = 4.77, P = 0.036; r = -0.34 and GLM, F_1,28 = 8.046, P = 0.008, r = -0.48; Figure 5 and Supplementary file 2, d). Thus, our results suggest that mothers who are generous providers produce young that solicit less maternal resources than offspring born to less generous mothers. Such a negative correlation is predicted to occur when maternal traits are predominantly under selection as long as parents respond to offspring demand (which we have shown above; Kölliker et al., 2005). One scenario to explain this negative correlation might be that each BXD line, i.e. genotype, is characterized by a unique (to this line, everything else being equal) combination of offspring and maternal behaviours where higher maternal provisioning is correlated with lower offspring solicitation. This may be due to the cost of increased solicitation (reflected in reduced bodyweight for the effort expended) for which we found evidence in our study. Bodyweight is indeed negatively correlated with the level of offspring solicitation (GLM, F_1,66 = 20.57, P < 0.001 e.g. day 10, r = -0.39, and day 14, r = -0.44; Figure 6 and Supplementary file 2, e).

Figure 5

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Figure 5—source data 1

Source data for Figure 5 as uploaded to GeneNetwork, showing BXD offspring short-term weight change on day 10 per pup, BXD maternal provisioning on day 10, BXD offspring solicitation on day 14 per pup and BXD maternal provisioning on day 14 for the BXD lines.

https://doi.org/10.7554/eLife.11814.012

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Figure 6

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Figure 6—source data 1

Source data for Figure 5 as uploaded to GeneNetwork, showing BXD offspring solicitation on day 10 per pup, BXD offspring weight on day 10 per pup, BXD offspring solicitation on day 14 per pup and BXD offspring weight on day 14 per pup for the BXD lines.

https://doi.org/10.7554/eLife.11814.014

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Our study of the genetics underlying family interactions has revealed that genes expressed in offspring can indirectly influence the quality of maternal behaviour and thus offspring fitness. At the same time, we detected specific loci in maternal genotype that indirectly modify offspring traits, which shows that IGEs can be an important component of the genetic architecture of complex traits (Bijma and Wade, 2008). We note that while postnatal cross-fostering controls for postnatal maternal effects, prenatal maternal effects can only be addressed (to some degree) by embryo transfer (e.g. Cowley et al., 1989), a procedure that is impractical in genetics experiments. Potentially, this may strengthen or weaken, for example, effects of BXD genotype on B6 maternal phenotype. At the same time, pre-natal maternal effects may also contribute to a phenotypic correlation between parent and biological offspring traits, as reported above on coadaptation. In-utero effect variation due to differences in BXD genotype may therefore contribute to differences in BXD offspring behaviour, in turn affecting the behaviour of their adoptive mothers. We now need to investigate the candidates identified here and how their effects on parental and offspring traits are integrated into the gene networks determining individual development. By controlling for genetic variation in either mothers or offspring we have been able to show that levels of maternal provisioning and offspring solicitation are unique to specific genotypes (here each BXD line) and that solicitation is costly. The ability to conduct complex systems genetics analyses in experimental systems of parent offspring interactions will enable us to concentrate now on understanding the underlying pathways involved, and how they are modified by social environmental conditions that determine adult phenotypes and associated reproductive success.

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Author details

1. David George Ashbrook

   Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom

   Contribution

   DGA, Analysis and interpretation of data, Drafting or revising the article

   For correspondence

   david.ashbrook@postgrad.manchester.ac.uk

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0002-7397-8910

2. Beatrice Gini

   Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom

   Contribution

   BG, Conception and design, Acquisition of data, Analysis and interpretation of data

   Competing interests

   The authors declare that no competing interests exist.

3. Reinmar Hager

   Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom

   Contribution

   RH, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   For correspondence

   Reinmar.Hager@manchester.ac.uk

   Competing interests

   The authors declare that no competing interests exist.

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