DOI: 10.5061/dryad.fttdz08r3
title: Indirect parental effects on offspring fitness by egg-derived fluids in an external fertiliser

description: The capacity for parents to influence offspring phenotypes via nongenetic
 inheritance is currently a major area of focus in evolutionary biology.
 Intriguing recent evidence suggests that sexual interactions among males
 and females, both before and during mating, are important mediators of
 such effects. Sexual interactions typically extend beyond gamete release,
 involving both sperm and eggs, and their associated fluids. However, the
 potential for gamete-level interactions to induce transgenerational
 parental effects remains under-investigated. Here, we test for such
 effects using an emerging model system for studying gamete interactions,
 the external fertiliser Mytilus galloprovincialis. We employed a
 split-ejaculate design to test whether exposing sperm to egg-derived
 chemicals (ECs) from one female would affect fertilisation rate and
 offspring survival when those sperm were used to fertilise a different
 female’s eggs. We found significant and separate effects of ECs from
 non-fertilising females on both fertilisation rate and offspring survival.
 The offspring survival effect indicates that EC-driven interactions can
 have transgenerational implications for offspring fitness independent of
 the genotypes inherited by those offspring. These findings provide a rare
 test of indirect parental effects driven exclusively by gamete-level
 interactions, and to our knowledge the first evidence that such effects
 occur via the gametic fluids of females.
description: We conducted our experiment in a series of ‘blocks’ (see Fig. 1
 for schematic overview of our experimental design). The experiment was
 designed to estimate whether chemicals derived from the eggs of
 non-fertilising females can contribute to variance in fertilisation rate
 and the viability of offspring from a different female. Each block was
 comprised of sperm from a single male, the ‘egg water’ (seawater in which
 eggs had previously been suspended and releasing chemicals; see below)
 from four non-fertilising females, and eggs from a separate ‘standard’
 female. Within a block, the male’s ejaculate was split into eight
 aliquots, and two aliquots were mixed with egg water from each
 non-fertilising female (i.e. separate aliquots were exposed to each egg
 water in replicate). Following exposure to egg water, the aliquots were
 then mixed with eggs from the standard female for the fertilisation
 trials. After allowing fertilised eggs to develop to the multi-cell stage
 (see below), we split the fertilisation pool into subsamples for (a)
 measuring fertilisation rates, and (b) development over an additional 48 h
 in order to derive an estimate of offspring viability. We collected data
 from a total of ten experimental blocks (i.e. egg water from 40 focal
 females, sperm from ten males, eggs from ten standard females, n = 80
 fertilisations total). Data were processed
 using generalised linear mixed-effects models in R version 3.6.0. We
 modelled fertilisation rate as a binomial response variable (number of
 fertilised and unfertilised eggs out of 100 in each sample) using a logit
 link function, with a fixed intercept term and random effects for ‘block’
 ID and ‘egg water (non-fertilising) female’ ID within block, along with an
 observation-level random effect to account for overdispersion. We next
 offspring survival (count of surviving offspring) as a Poisson response
 variable using a log link function, again with random effects for ‘block’
 and ‘non-fertilising female’, aling with an observation-level random
 effect to account for overdispersion, and in this case with a fixed
 covariate of fertilisation rate (proportion). This fixed covariate was
 necessary to control for variation in offspring numbers among samples that
 was due to variation in fertilisation rate.
description: The dataset contains variables in columns and samples in rows.
 The columns included are 'Block', 'Female'
 (non-fertilising females within blocks from which egg water was
 collected), 'Repeated_measure' (denoting the two repeated
 measures for each block-female combination), 'ID' (a unique ID
 for every sample), 'N_Fertilised_Eggs' (number of fertilised
 eggs out of haphazard sample of 100), 'N_Unfertilised_Eggs'
 (number of unfertilised eggs out of haphazard sample of 100), and
 'N_Offspring_Surviving' (count of surviving offspring after 48
 hours). Note that the female-level outlier for
 offspring survival (after natural-log transforming and correcting by
 fertilisation rate) we identify in our manuscript is B3_EW1. The five
 outliers at the individual data point level that we identify in our
 manuscript are B3_EW1_2, B7_EW1_1, B7_EW3_1 and B10_EW2_1.