Notice bibliographique
Résumé
Our genetic code – our genome or DNA – is what defines our biology, how we interact with the environment and which traits give us an advantage in adapting, surviving and reproducing. That was the staple of genetics for years, but it was not the complete story. Later, we found out that it is not only the genome but also something more dynamic that is important, something ‘above’ the genome: the epigenome. Conrad Waddington coined the term epigenetics in the 1940s to refer to the interactions between the environment and the genetic code. It is how our DNA quickly ‘learns’ during development, under changing environmental conditions, without any modifications to the genetic code. DNA methylation, histone modification, alterations to chromatin structure and small non-coding RNAs are some of the ways in which genes can be up-regulated or down-regulated, leading to different phenotypes without any changes to the genetic code. Recent studies have pointed to yet another epigenetic method, which may contribute to the development of resistance to various chemicals in insects: long non-coding RNAs (lncRNAs).Recent advances in deep sequencing techniques have made it possible to identify and classify various types of lncRNAs. Although in the past they had been considered nothing more than transcriptional noise, it is now becoming clear that lncRNAs are involved in a multitude of biological pathways, such as growth and development, cell differentiation and gene expression. Through their study, Kayvan Etebari and colleagues have provided, for the first time, a glimpse of the lncRNA profile of the cabbage moth (Plutella xylostella L.). They also analysed the role that long intergenic non-coding RNAs (lincRNAs), a class of lncRNAs, play in insecticide resistance.The authors found significant correlations between lincRNAs and the number of protein-coding genes in the genome scaffolds that they examined. As lincRNAs are generally expressed with their neighbouring proteins, the authors determined that cabbage moth lincRNAs play a role in protein-binding activities, such as DNA and RNA binding, and transcription regulation. When cabbage moth lincRNA sequences were compared with those of two closely related species, the silk moth (Bombyx mori) and the fall armyworm (Spodoptera frugiperda), only 14 similarities were detected among all three species. This lack of conservation among identified lincRNAs has been reported in vertebrates as well, making it difficult to identify the specific roles they play across various species.When the lincRNA expression profiles of pesticide-resistant and Bacillus thuringiensis (Bt) endotoxin-resistant cabbage moths were compared with those of susceptible individuals, Etebari and colleagues noticed that approximately 70% of the lincRNAs examined were over-expressed in insecticide-resistant populations, and only 50% were up-regulated in Bt-resistant individuals. While the same lincRNAs were commonly altered in the pesticide- and toxin-resistant individuals, the way in which they were modified differed from one population to another, suggesting that their roles in resistance are chemical specific. The authors also found that direct exposure of cabbage moth larvae to insecticides significantly impacted the transcript level of several lincRNAs in insecticide-resistant individuals when compared with non-exposed controls. Whether lincRNAs contribute to resistance development through epigenetic mechanisms, or are a part of the chemical detoxification pathways, remains to be resolved. However, it is now clear that what was previously known as transcriptional noise may indeed play a larger role in gene regulation than was initially thought.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».