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Enregistrement W2055619857 · doi:10.1111/j.1439-0388.2009.00830.x

The bovine genome sequence – will it live up to the promise?

2009· editorial· en· W2055619857 sur OpenAlexaff
S. S. Moore

Notice bibliographique

RevueJournal of Animal Breeding and Genetics · 2009
Typeeditorial
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueAnimal Genetics and Reproduction
Établissements canadiensUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésBovine genomeBiologyGenomeReference genomeInternational HapMap ProjectGenomicsWhole genome sequencingDNA sequencingLivestockGeneticsEvolutionary biologyComputational biologyGeneHuman genomeEcology

Résumé

récupéré en direct d'OpenAlex

April 2009 was a watershed month in livestock genomics. Two papers appeared in the journal Science, one described the sequence of the bovine genome (The Bovine Genome Sequencing and Analysis Consortium, Science 324, 522–528), and the second the genetic history of the cow using information derived from Single Nucleotide Polymorphisms (SNP) obtained through the sequencing effort (The Bovine HapMap Consortium, Science 324: 528–532). We now have fine detail of the bovine genome structure and annotation of most of the genes to add to tools such as high density SNP chips and gene expression profiling using new generation sequencing technologies. These advances have already transformed the way we carry out genomics based research in cattle. Although not the first agricultural animal species to be sequenced, chicken was completed in 2004 (Nature 432, 695–716) the cow was the first agriculturally important mammal and the first ruminant. Of course, the cow is just one representative of this highly successful group of animals that have been important to humans in the course of our own history. Sheep, goats, deer, elk, water buffalo, bison, camels, llamas, alpacas and others, have played important roles as a source of food, motive power or fibre over millennia. The bovine genome sequence will form the template for future genome sequencing of many other ruminant species. Already other agricultural species are following hard on the heels of the cow including pig, sheep and even water buffalo. The horse, considered perhaps now as a companion animal, has had a draft sequence release in 2007, http://www.broad.mit.edu/mammals/horse). The concept that this many different species might be sequenced was unthinkable when the cattle sequencing effort began. So what is it we have actually achieved and how will it benefit the science, and people who rely on cattle for their livelihood? We now have a window into the genetic history of one of the most important domestic animals. Cattle have coexisted with humans for over 10 000 years, further they have been subject to selective breeding of one sort or another for much of this time. The genomic ‘footprints’ and signatures resulting from domestication and selection are emerging as an early by-product of the sequencing effort (The Bovine HapMap Consortium, 2009, Science 324: 528–532). An early application of the sequencing effort, that has already been adopted by some livestock-based industries, results from access to thousands of SNPs. The Bov50SNP Chip, developed as a direct result of the sequencing effort (Van Tassell et al. 2008, Nature Methods, 5: 247–252) and now available commercially though Illumina Inc., has already been adopted by the North American Dairy industry for genome selection (J.P. Chenais, personal communication). The rest of the world will follow apace, however, for other breeds of cattle, the situation turns out to be far more complex than we imagined. The success in dairy is largely attributable to the predominance worldwide of one breed (Holstein) and the availability of detailed performance records kept over decades of genetic selection. Indeed, there exists a system for the international exchange on data of dairy bulls through Interbull (http://www-interbull.slu.se/framesida-home.htm). Over 3500 Holsteins were genotyped to provide the basis for the development of algorithms for Genome Selection in North American animals (VanRaden et al., 2009, J Dairy Sci 92: 16–24)). This is in contrast to other dairy breeds and most beef breeds where the availability of sufficient animal numbers with good phenotypes and genotypes does not yet exist. Arguments over whether an even denser SNP chip is required need to be put in perspective given the statistical dilemma resulting from too many genotypes on too few animals, or over-parameterisation. International collaborations will be the only way forward for some breeds to achieve the animal numbers required. Finally, we must remember that only one animal has to date been fully sequenced. The Line 1 Hereford was chosen due to the relatively high level of inbreeding in this line, greatly simplifying the task of genome assembly (The Bovine Genome Sequencing and Analysis Consortium, 2009, Science 324, 522–528). Sequencing costs have dropped by as many as three orders of magnitude since the Bovine Genome Sequencing Project was first launched. Hold onto your hats, as we can expect resequencing efforts on many more animals will provide data on genetic diversity, relationships of breeds, and makeup of cross-bred animals, temporal changes to the genome resulting from intense selection pressure, other forms of mutations such as Copy Number Variation and Insertion/Deletion mutations and causal mutations underlying economically important traits, to name just a few. As the cost of sequencing reduces even further it may not be unreasonable to expect that full genome sequence will be available on most, if not all, key industry animals. The pace of research will provide tremendous challenges to how we carry out genome analysis, and technology transfer to industry at every level. Has the promise been fulfilled? The answer is mixed, and depends more on the nature of the animal populations under study than the power of the technology. We are back to biology after years of technology development, and this would be considered by most to be a huge step in the right direction.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,236
Score d'incertitude au seuil0,746

Scores Codex et Gemma par catégorie

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

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.

Tête enseignante Opus0,016
Tête enseignante GPT0,276
Écart entre enseignants0,261 · 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 tête enseignante, pas un consensus.

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

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

En bref

Citations3
Publié2009
Routes d'admission1
Résumé présentoui

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