Search bioRxiv⌕ Search

bioRxiv · 10.1101/2024.06.07.597568

Absence of Evidence is Not Evidence of Absence: The many flaws in the case against transgenerational epigenetic inheritance of pathogen avoidance in C. elegans

Abstract

After examining the data and methods presented in Gainey, et al., bioRxiv, 20241 we conclude that the authors did not use an experimental paradigm that would have allowed them to replicate our results on transgenerational epigenetic inheritance (TEI) of learned avoidance that we regularly observe2-5. That is, we agree with the authors that their experiments show no evidence of TEI. However, there are substantial differences in their execution of every step of the work that also make it impossible for the authors to claim that they are replicating our experiments or protocols. Based on these differences, we do not believe there is an issue of "robustness" and "reliability" in our TEI findings, but rather that Hunter and colleagues have in fact not tested the central condition of TEI - that is, small RNA production by bacteria and subsequent uptake by C. elegans - nor have they carried out proper behavioral and imaging assays to assess this behavior. Our subsequent work shows that indeed this example of transgenerational epigenetic inheritance is not just observed in laboratory settings with PA14, but is also induced by wild strains of Pseudomonas, exhibiting its robustness. Just as we offered advice and training to Hunter and colleagues, we are happy to advise anyone who wishes to learn this assay. We have now performed the experiments in the absence of azide, a deviation from our protocol that Hunter and colleagues deliberately made, and found that this omission may account for most if not all of the differences from our results. It is disingenuous for the authors to have presented their work as if they have used our protocol, given the fact that they chose to not use the same conditions for the most basic assay used in the work, the chemotaxis assay, which would have been necessary to replicate in order to reproduce our work. Therefore, Gainey et al.s claims that our protocol or results are "irreproducible" are not supported by their evidence.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kaletsky, R., Moore, R. S., Sengupta, T., Soto, R., Murphy, C.. 2024-06-07. Absence of Evidence is Not Evidence of Absence: The many flaws in the case against transgenerational epigenetic inheritance of pathogen avoidance in C. elegans. https://doi.org/10.1101/2024.06.07.597568

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Generation of a transgenic cephalopod

Coleoid cephalopods (cuttlefish, octopus, and squid) are marine mollusks with elaborate nervous systems that support a diverse repertoire of complex behaviors. These include the neural control of the color, pattern, and texture of the skin, facilitating both adaptive camouflage and innate patterning that may reflect internal state. The development of transgenic cephalopods expressing fluorescent proteins, optogenetic actuators, and reporters of neural activity would contribute a new and important technology to cephalopod biology. The generation of transgenic cephalopods, however, has remained a major challenge. Here, we report the development of stable transgenic dwarf cuttlefish (Ascarosepion bandense) expressing ubiquitous nuclear-localized mScarlet, a red fluorescent protein. We evaluated multiple strategies for transgenesis, and established cuttlefish lines using both CRISPR and the transposons Sleeping Beauty and Minos. The stable expression of transgenes enabled live imaging of cell dynamics during embryonic development. The Minos transposon emerged as the most efficient transgenesis strategy and is adaptable to promoters and transgenes of choice. These strategies now enable the generation of diverse genetic tools for mechanistic studies of cephalopod biology.

genetics↗

Large language model-based bibliometric evaluation of population descriptors in human genetics

As the use of population descriptors such as race, ethnicity, and ancestry have become increasingly common in modern genetics research, there have been growing calls to critically examine their use. Most notably, in 2023, the National Academies of Science, Engineering, and Medicine (NASEM) published a report titled Using Population Descriptors in Genetics and Genomics Research: A New Framework for an Evolving Field, which included eight specific and actionable recommendations for researchers to implement the ethical and accurate use of population descriptors in genetic research. Here, we use the 2023 NASEM report as a benchmark to analyze the use of population descriptors in genome-wide association studies (GWAS). We develop a general toolkit for large language model-based bibliometrics, operationalize the report's recommendations into an evaluation framework, and apply this framework to evaluate all 4,007 papers from the GWAS Catalog published between 2007 and 2025 with full text available on PubMedCentral. We find significant improvements in adherence to NASEM report recommendations over time. However, most improvements predate the publication of the NASEM report itself, suggesting the report functioned primarily as a synthesis of existing best practices rather than a catalyst for change. We conclude by highlighting opportunities for growth in the field of human genetics.

genetics↗

Mitigating biases of rescaling in forward-in-time population genetic simulations

Forward-in-time population genetic simulations are widely used in evolutionary analyses, but simulating large populations and long genomic regions remains computationally demanding. To reduce this cost, parameter rescaling is widely employed, in which the original evolutionary process is approximated by one with a smaller population size and fewer generations. Recently, several studies using the SLiM simulator have raised concerns about the accuracy of this rescaling approach. In this study, we show that many of the biases reported in these studies can be mitigated by using a different simulation algorithm. These results reveal that the accuracy of parameter rescaling depends on how well the simulation algorithm preserves diffusion-limit properties under rescaling.

genetics↗