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Record W4403866340 · doi:10.1101/2024.10.27.620551

Dynamic birth and death of Argonaute gene family functional repertoire across <i>Caenorhabditis</i> nematodes

2024· preprint· en· W4403866340 on OpenAlexaff
Daniel D. Fusca, Katja R. Kasimatis, Hongyu Vicky Zhu, Asher D. Cutter

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsArgonauteRepertoireCaenorhabditis elegansBiologyGeneGeneticsRNA interferenceCell biologyRNA

Abstract

fetched live from OpenAlex

Abstract Diverse small RNA pathways, comprised of Argonaute effector proteins and their bound small RNA molecules, define critical systems for regulating gene expression in all domains of life. Some small RNA pathways have undergone significant evolutionary change in nematode roundworms, including gains of novel Argonaute genes and losses of entire pathways. Differences in the functional complement of Argonautes among species therefore profoundly influence the available repertoire of mechanisms for gene regulation. Despite intensive study of Argonaute function in Caenorhabditis elegans , the extent of Argonaute gene family dynamism and functional breadth remains unknown. We therefore comprehensively surveyed Argonautes across 51 Caenorhabditis species, yielding over 1200 genes from 11 subfamilies. We documented multiple cases of diversification, including the birth of a potentially novel Argonaute subfamily and the origin of the ALG-5 microRNA Argonaute near the base of the Caenorhabditis phylogeny, as well as evidence of adaptive sequence evolution and gain of a new splice isoform for CSR-1 in a clade of 31 species. We also detected repeated independent losses of multiple components of the piRNA pathway, mirroring other instances of piRNA pathway loss across the phylum. Gene gain and loss occurs significantly faster than expected within several Argonaute subfamilies, potentially associated with transposable element proliferation coevolving with WAGO-9/10/12 copy number variation. Our characterization of Argonaute diversity across Caenorhabditis demonstrates exceptional functional dynamism in the evolution of gene regulation, with broad implications for mechanisms of control over ontogenetic development and genome integrity. Author Summary For organisms to develop properly to survive and reproduce, they must express their genes in the right amount, in the appropriate cell types and time during development. One important mechanism that organisms use to regulate gene expression involves small RNA pathways, where short molecules of RNA serve as targeting guides by binding to Argonaute effector proteins. To understand how small RNA pathways evolve over time, we searched for Argonaute genes throughout the genomes of 51 species of Caenorhabditis nematode worms and found over 1200 Argonaute genes belonging to 11 different Argonaute subfamilies. We then documented cases where species have evolved potentially new types of Argonautes, or new protein isoforms of existing Argonautes. We also identified repeated cases of evolutionary loss of entire Argonaute subfamilies, including for the PRG-1 Argonaute needed in the piRNA regulatory pathway, and characterized how some Argonaute subfamilies gain and lose genes significantly faster than expected. Our findings demonstrate substantial variation in the functional repertoire of Argonaute genes found among Caenorhabditis species, with this evolutionary dynamism implicating fundamental differences between species in how they regulate gene expression across their genomes throughout development.

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 score0.002

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 head0.009
GPT teacher head0.217
Teacher spread0.208 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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