Wild worm embryogenesis harbors ubiquitous polygenic modifier variation

1) The authors discovered that knocking down the same genes in different isolates has different effects on embryonic lethality and the authors state that this observation indicates that there is cryptic genetic variation. It is not clear that this interpretation is correct. The alternative possibility is that the variation is not “cryptic”: i.e. that development (and/or embryonic lethality) is really phenotypically different in the different isolates.

[…]

2) The authors state that “We have uncovered pervasive CGV among wild C. elegans strains in the molecular and cellular processes of embryogenesis” and their title is “Wild worm embryogenesis harbors ubiquitous polygenic modifier variation”. However, the authors study embryonic lethality. While their results might certainly have interesting implications for the genetic basis of “cellular processes of embryogenesis” and other aspects of “embryogenesis”, strictly speaking, their data does not address phenotypes other than embryonic lethality. The paper would be improved by a more extensive discussion of the limitations of their results in this regard.

Points 1) and 2) identify important conceptual definitions in our work, and these definitions are inter-related.

We define cryptic genetic variation in terms of a focal phenotype (in our case, embryonic lethality). There is every expectation that the cryptic variation that affects embryonic lethality also causes variation in cellular or developmental phenotypes in a penetrant, non-cryptic manner, as the comment describes; we would interpret such variation as a potential mechanism for the cryptic differences in lethality. Wild isolates of C. elegans exhibit measureable variation in several aspects of early development (Farhadifar et al. 2015), but under standard conditions the embryos of all strains hatch into larvae at rates approaching 100%. Variation in hatching rates under standard conditions is radically amplified by RNAi perturbation, and this newly exposed variation is CGV (Paaby & Rockman). Thus, to address comment 1), we added the following paragraph to the Discussion, which expands upon our conceptualization of cryptic variation and in doing so follows suggestions i) and ii) above:

“We describe the variation we uncovered as “cryptic” because its effect on embryonic survival is dramatically magnified under perturbed conditions. Without gene perturbation, our strains exhibit little embryonic lethality. However, under ordinary conditions the strains vary in gene expression and other cellular or developmental phenotypes (Farhadifar et al. 2015; Grishkevich et al. 2012), which may be the mechanisms by which the cryptic alleles influence the penetrance of the primary perturbation. Previously, we and others have described such differences as variation in “intermediate” phenotypes (Félix & Wagner 2008; Paaby & Rockman 2014); whether a genetic variant is cryptic requires definition of the focal phenotype, since even at the morphological level an allele can be cryptic in one trait but penetrant in another (Duveau & Félix 2012).”

In defining the relationship between our embryonic lethality data and hypothetical observations of cellular or developmental phenotypes, the added paragraph more clearly delineates the extent of our results, which is the concern raised by point 2). We also agree with the reviewers that the language of “We have uncovered pervasive CGV among wild C. elegans strains in the molecular and cellular processes of embryogenesis” misstates the nature of our data, and we have rephrased this sentence in the Discussion to “We have uncovered pervasive CGV among wild C. elegans strains that modifies the probability that an embryo will survive a gene perturbation.”

3) The “non-informational” variants are of greatest interest to developmental and evolutionary biologists. It is thus important to rule out as much of this as possible. The authors themselves note that “gene-specific modifiers ... potentially include gene-specific variation in RNAi sensitivity, perhaps due to heritable variation in transcriptional licensing and variation in wild-type expression level of the targeted gene, due to cis- or trans-acting regulatory variation.” This could be tested by generating transcriptomes for five or so strains with unusually divergent phenotype distributions. This would then allow the authors to directly estimate the extent to which gene-by-strain interactions are due to expression levels. RNAi knockdown efficacy is also an important informational variation to explore, but much harder to address.

This is a very important point and we are glad to expand upon our understanding of the issue. We fully agree with the reviewers that experiments that evaluate variation in efficacy of RNAi across strains would be very valuable. Such an experiment would require extremely good estimates of transcript level (ideally across developmental stage), both with and without RNAi. As suggested, transcript data collected under standard conditions would also address whether and how the strains vary in native gene expression, which is an informative aspect of embryogenesis independent of the question of RNAi efficacy.

We also agree with the reviewers that the non-informational components of variation are potentially the most interesting. Unfortunately, the myriad and complex ways in which gene-specific knockdown might vary across strains, including by mechanisms that are just beginning to be elucidated (e.g. transcriptional licensing), preclude us from easily distinguishing between different classes of CGV mechanism. The review points to one class of mechanism, variation in wild-type expression level, that we can explicitly test. A very recently published paper (Vu et al. 2015) has shown that, across four strains with perturbations to genes involved in the electron transport chain, a strain with a more severe RNAi phenotype tends to have lower wild-type expression of the targeted gene. We acquired embryonic transcriptome data from the work of Grishkevich et al. (2012) and tested for a correlation between gene expression level and our estimates of embryonic lethality. These results do not address whether variation in expression is, for example, via a trans effect that elevates overall pathway activity and compensates for knockdown of a particular member (i.e., the gene expression and RNAi phenotype share a common cause), or a cis- or trans-acting effect specific to the targeted gene, revealing pre-existing dosage variation that is tolerated under unperturbed conditions but causal of the RNAi phenotype under perturbation (cf. Milloz et al. 2008). Nevertheless, this analysis adds a valuable component to our manuscript and a useful step forward in the larger exploration of the problem.

Overall, we found that wild-type gene expression in our 29 genes, examined across five strains, did not correlate with the embryonic lethality phenotypes of those strains. We added the following to the Results section:

“Extragenic modifiers may work by affecting, in trans, the expression level of the targeted gene. Recent work shows that differences in severity of RNAi phenotype, for four C. elegans strains perturbed at electron transport chain genes, are associated with differences in expression level of the targeted gene (Vu et al. 2015). However, we find no evidence for the reported pattern of lower expression explaining more severe phenotypes. […] Although undetectable differences in transcript level may nevertheless contribute to embryonic survival, these results suggest that much of the gene-specific modifier effect we observe depends on variation beyond the target gene.”

And we added the following to the Materials and methods (Comparison of gene expression and embryonic lethality data):

“To test whether native gene expression of our target genes correlates with the embryonic lethality phenotypes, we downloaded microarray transcriptome data published by Grishkevich et al. (2012). These data were collected on 4-cell embryos, which retain the maternally-inherited mRNA transcripts that were the targets of our study, and include three replicate values (following quantile normalization and log10 transformation) determined from three pools of 50 embryos each. […]For each gene, we looked for correlation between the average gene expression value for each of the five strains and the strain coefficients from the strain-by-gene interaction term in our statistical analysis. We used the same generalized linear model structure as described above; in this analysis, we included 29 genes and five strains. We used a two-tailed binomial sign test to assess whether the 29 correlations were disproportionately positive or negative.”