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Record W2909082559 · doi:10.1101/518621

Molecular evolution across developmental time reveals rapid divergence in early embryogenesis

2019· preprint· en· W2909082559 on OpenAlexafffund
Asher D. Cutter, Rose H. Garrett, Stephanie Mark, Wei Wang, Lei Sun

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsBiologyGeneTranscriptomeEvolutionary biologyGene expressionPhenotypeDevelopmental biologyGeneticsEmbryoModel organismFunctional divergenceOntogenyGene family

Abstract

fetched live from OpenAlex

Abstract Ontogenetic development hinges on the changes in gene expression in time and space within an organism, suggesting that the demands of ontogenetic growth can impose or reveal predictable pattern in the molecular evolution of genes expressed dynamically across development. Here we characterize co-expression modules of the C. elegans transcriptome, using a time series of 30 points from early-embryo to adult. By capturing the functional form of expression profiles with quantitative metrics, we find fastest evolution in the distinctive set of genes with transcript abundance that declines through development from a peak in young embryos. These genes are highly enriched for oogenic function (maternal provisioning), are non-randomly distributed in the genome, and correspond to a life stage especially prone to inviability in inter-species hybrids. These observations conflict with the “early conservation model” for the evolution of development, though expression-weighted sequence divergence analysis provides some support for the “hourglass model.” Genes in co-expression modules that peak toward adulthood also evolve fast, being hyper-enriched for roles in spermatogenesis, implicating a history of sexual selection and relaxation of selection on sperm as key factors driving rapid change to ontogenetically distinguishable co-expression modules of genes. We propose that these predictable trends of molecular evolution for dynamically-expressed genes across ontogeny predispose particular life stages, early embryogenesis in particular, to hybrid dysfunction in the speciation process. Impact Summary The development of an organism from a single-celled embryo to a reproductive adult depends on dynamic gene expression over developmental time, with natural selection capable of shaping the molecular evolution of those differentially-expressed genes in distinct ways. We quantitatively analyzed the dynamic transcriptome profiles across 30 timepoints in development for the nematode C. elegans. In addition to rapid evolution of adult-expressed genes with functional roles in sperm, we uncovered the unexpected result that the distinctive set of genes that evolve fastest are those with peak expression in young embryos, conflicting with some models of the evolution of development. The rapid molecular evolution of genes in early embryogenesis contrasts with the exceptional conservation of embryonic cell lineages between species, and corresponds to a developmental period that is especially sensitive to inviability in inter-species hybrid embryos. We propose that these predictable trends of molecular evolution for dynamically-expressed genes across development predispose particular life stages, early embryogenesis in particular, to hybrid dysfunction in the speciation process.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.209
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2019
Admission routes2
Has abstractyes

Explore more

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