Rapid Assessment of the Temporal Function and Phenotypic Reversibility of Neurodevelopmental Disorder Risk Genes in C. elegans
Notice bibliographique
Résumé
Raw and processed data for “Rapid Assessment of the Temporal Function and Phenotypic Reversibility of Neurodevelopmental Disorder Risk Genes in C. elegans” Preprint (BioRxiv): https://doi.org/10.1101/2021.10.21.465355 Analysis source code repository (Github): https://github.com/troymcdiarmid/reversibility/ Abstract: Hundreds of genes have been implicated in neurodevelopmental disorders. Previous studies have indicated that some phenotypes caused by decreased developmental function of select risk genes can be reversed by restoring gene function in adulthood. However, very few risk genes have been assessed for adult reversibility. We developed a strategy to rapidly assess the temporal requirements and phenotypic reversibility of neurodevelopmental disorder risk gene orthologs using a conditional protein degradation system and machine vision phenotypic profiling in Caenorhabditis elegans. Using this approach, we measured the effects of degrading and re- expressing orthologs of 3 neurodevelopmental risk genes EBF3, BRN3A, and DYNC1H1 across 30 morphological, locomotor, sensory, and learning phenotypes at multiple timepoints throughout development. We found some degree of phenotypic reversibility was possible for each gene studied. However, the temporal requirements of gene function and degree of phenotypic reversibility varied by gene and phenotype. The data reflects the dynamic nature of gene function and the importance of using multiple time windows of degradation and re-expression to understand the many roles a gene can play over developmental time. This work also demonstrates a strategy of using a high-throughput model system to investigate temporal requirements of gene function across a large number of phenotypes to rapidly prioritize neurodevelopmental disorder genes for re-expression studies in other organisms. Further details about this project, including a web version README.md file included here and the R code necessary to regenerate all of the figures and formal analyses in the manuscript using the data in this repository can be found at: https://github.com/troymcdiarmid/reversibility The R packages required for this project are listed at the beginning of each markdown at the github repository. The code in each markdown is used to analyze the data from one gene (several experiments per gene). See the bioRxiv for further details about the project. The “Reversibility” folder includes all of the raw and processed Multi-Worm Tracker (https://sourceforge.net/projects/mwt/) output files. The files are organized to have one folder per gene, each with several experiments per gene. Each experiment consists of multiple raw Multi-Worm-Tracker output files pertaining to each individual plate of worms that was tracker (these are the time stamped files). The organized morphology summary (data.smorph) and reversal feature summaries (data.srev) are also included in case the user does not want to regenerate them using the code at the associated github (link included above). (2022-03-15) For questions or comments specific to this repository, please contact: Troy A. McDiarmid - GitHub - @Troy_McD_UBC Additional questions about the project, such as further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Catharine H. Rankin (crankin@psych.ubc.ca).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,026 | 0,016 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».