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Enregistrement W2528053134 · doi:10.1093/biosci/biw106

Taming the Wild Carrot

2016· article· en· W2528053134 sur OpenAlexaff
M. Jean Stone

Notice bibliographique

RevueBioScience · 2016
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueEnvironmental, Ecological, and Cultural Studies
Établissements canadiensWorld Federation of Science Journalists
Organismes subventionnairesnon disponible
Mots-clésHorticultureBiology

Résumé

récupéré en direct d'OpenAlex

Selective breeding has serendipitously made orange domestic carrots far more healthful than their wild ancestors. “The popularity of this carrot is fortuitous for modern consumers because the orange pigmentation results from high quantities of alpha- and beta-carotene, making carrots the richest source of provitamin A in the US diet,” according to an international team of 21 scientists who recently reported an extensive genome assembly and analysis of the orange carrot. It is, in fact, one of the most complete vegetable genomes ever assembled, as described in a recent Nature Genetics article (doi:10.1038/ng.3565). Importantly, this first full genomic analysis of a carrot (Daucus carota) reveals a candidate gene, DCAR-032551, responsible for carotene accumulation and helps explain how it works. It appears that the primary carotene regulatory mechanism is not at the biosynthetic level but rather at the developmental one, where it drives light-mediated development, or photomorphogenesis, and responses of shoots to sunlight, or de-etiolation. The study's principal investigator, Philipp Simon, at the US Department of Agriculture's (USDA) Agricultural Research Service, and his colleagues propose that the subsequent loss of repression by genes responsible for photomorphogenesis and de-etiolation in nonphotosynthetic carrot tissue activates a metabolic cascade resulting in the high levels of carotenoid accumulation. “Wild carrots are white, or off white, like their close relative the parsnip,” says Simon. “Color provides no advantage to the carrot, but it's worth ­noting that it also imparts no [major] disadvantage.” However, because cosmetic changes are generally made at the expense of fitness, domestic plants tend to be less robust than their wild ancestors, resulting in the ever-escalating need for crop-protecting pesticides and fertilizers. The advantage of color may have been to early farmers, enabling them to identify outcrosses to wild carrots more easily, Simon speculates. “Wild carrots are still abundant in Europe and Asia where domestic carrots originated, as well as throughout the United States, where we know them as Queen Anne's lace.” Steve Wiley at Murdoch University, in Perth, Australia, notes that the USDA lists wild carrots as “noxious” weeds. However, wild carrots are edible and free with a little digging. Perhaps a little digging into the wild carrot's genome could find genes that, when transferred, would increase the fitness of domestic carrots. Yellow and purple domesticated carrot roots were first discovered in Central Asia and date back approximately 1100 years. Reliable evidence of orange carrots has been found in Europe but not before the sixteenth century. Notably, carrots are the most important crop in the Apiaceae family, which includes celery, parsley, fennel, coriander, and cumin, as well as parsnips and a number of other important vegetables and spices. Simon and his collaborators identified a total of 32,113 genes from an orange carrot, of which 10,530 were unique to carrots, in general. Then, they sequenced 35 different wild and cultivated carrot specimens to establish domestication patterns. “This work is quality; it's extremely thorough and well done,” comments Anthony Trewavas, from the Institute of Molecular Plant Science in Edinburgh, who was not involved in the project. “It's an outstanding investigation involving a huge amount of research.” In stark contrast to genetically challenged domestic plants bred for features other than fitness and despite having one of the smallest genomes of any known agricultural weed, horseweed (Conyza canadenis) is one of the most successful plants in the world. Carrots and other domestic plants could benefit greatly from the acquisition of some of horseweed's many survival genes. For example, with only 44,592 protein-coding nuclear genes, horseweed manages to produce well over 200,000 small seeds per plant. Each seed is able to travel long distances on wind and water, germinate quickly, dig its roots in deep, retreat into dormancy when necessary, regenerate, and self-fertilize. All of this combined with other weedy attributes, such as the ability to evolve herbicide resistance, enables horseweed to easily outcompete pampered crop plants, as well as the humans who raise them. Research is under way to build a genomic resource for horseweed substantial enough to explain the genomic basis of “weediness,” say C. Neal Stewart Jr. and his colleagues in the November 2014 issue of Plant Physiology. Once this is accomplished, it might be possible to protect our food plants on a molecular level. Expert scientists consider this important. Among them, members of the Unified Microbiome Initiative Consortium say in a consensus statement released in late 2015, “By manipulating interactions at the root-soil-microbe interface, we may reduce agricultural pesticide, fertilizer, and water use, enrich marginal land, and rehabilitate degraded soil.”

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,017
Score d'incertitude au seuil0,055

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0080,007
Communication savante0,0030,002
Science ouverte0,0010,002
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0170,001

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.

Tête enseignante Opus0,037
Tête enseignante GPT0,276
Écart entre enseignants0,239 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2016
Routes d'admission1
Résumé présentnon

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