Indirect parental effects on offspring fitness by egg-derived fluids in an external fertiliser

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.,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.,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.,

父母辈通过非基因遗传（nongenetic inheritance）影响子代表型的能力，目前是进化生物学领域的核心研究热点之一。近年来的有趣证据表明，交配前后雌雄个体间的性相互作用，是介导这类效应的重要因子。性相互作用通常不限于配子释放，还涉及精子、卵子及其相关体液。然而，配子水平的相互作用诱导跨代亲本效应的潜力仍未得到充分研究。

本研究以一种新兴的配子相互作用研究模型系统——体外受精物种地中海贻贝（Mytilus galloprovincialis）为对象，对这类效应进行了检验。我们采用拆分精液设计（split-ejaculate design），检验将精子暴露于某一雌性的卵源化学物质（egg-derived chemicals, ECs）后，当该精子用于授精另一雌性的卵子时，是否会影响受精率与子代存活率。

研究发现，未参与受精的雌性的卵源化学物质，对受精率和子代存活率均存在显著且独立的影响。子代存活率效应表明，由卵源化学物质介导的相互作用，可对子代适合度产生跨代影响，且这种影响独立于子代所继承的基因型。本研究结果为仅由配子水平相互作用驱动的间接亲本效应提供了罕见的实证检验，据我们所知，也是首个证明此类效应可通过雌性配子体液实现的证据。

我们的实验以一系列‘批次（blocks）’开展（实验设计示意图见图1）。本实验旨在估算未参与受精的雌性所产生的卵源化学物质，是否会对另一雌性的子代受精率与生存活力产生影响。每个批次均包含来自单只雄性的精液、4只未受精雌性的‘卵水’（即此前悬浮过卵子并释放化学物质的海水，详见下文），以及单独的‘标准’雌性的卵子。

在单个批次内，将雄性的精液均分为8份等分样，将其中2份与每只未受精雌性的卵水混合（即每个卵水对应两份重复暴露的等分样）。将精子暴露于卵水后，再将等分样与标准雌性的卵子混合以开展受精试验。待受精卵发育至多细胞阶段（详见下文）后，将受精池分为两份子样本：(a) 用于测量受精率；(b) 继续培养48小时以评估子代生存活力。

本研究共完成10个实验批次（即共采集40只目标雌性的卵水、10只雄性的精液、10只标准雌性的卵子，总受精试验数n=80）。数据采用R语言3.6.0版本中的广义线性混合效应模型（generalised linear mixed-effects models）进行处理。

我们将受精率设为二项分布响应变量（binomial response variable，每份样本随机抽取100枚卵的受精与未受精数量），采用logit连接函数（logit link function），模型包含固定截距项，以及‘Block’（批次）ID和批次内未受精雌性卵水ID的随机效应，同时加入观测水平随机效应以处理过度离散（overdispersion）问题。

我们随后将子代存活率（存活子代数量）设为泊松分布响应变量（Poisson response variable），采用log连接函数（log link function），同样纳入‘Block’和‘未受精雌性’的随机效应，以及观测水平随机效应以处理过度离散问题；此外，本模型还纳入受精率（比例值）作为固定协变量，以控制由受精率差异导致的样本间子代数量差异。

本数据集以实验样本为行，变量为列。所包含的列变量为：'Block'、'Female'（采集卵水的批次内未受精雌性个体）、'Repeated_measure'（表示每个批次-雌性组合的两次重复测量）、'ID'（每份样本的唯一标识符）、'N_Fertilised_Eggs'（随机抽取100枚卵中的受精卵数量）、'N_Unfertilised_Eggs'（随机抽取100枚卵中的未受精卵数量），以及'N_Offspring_Surviving'（48小时后存活的子代数量）。

需注意，本研究手稿中鉴定出的子代存活率层面的雌性水平异常值（经自然对数转换并按受精率校正后）为B3_EW1。手稿中鉴定出的5个个体数据点水平异常值分别为B3_EW1_2、B7_EW1_1、B7_EW3_1和B10_EW2_1。