Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Enhancing grapevine breeding efficiency through genomic prediction and selection index.

G3 (Bethesda, Md.) - 3 Apr 2024

Brault Charlotte, Segura Vincent, Roques Maryline, Lamblin Pauline, Bouckenooghe Virginie, Pouzalgues Nathalie, Cunty Constance, Breil Matthieu, Frouin Marina, Garcin Léa, Camps Louise, Ducasse Marie-Agnès, Romieu Charles, Masson Gilles, Julliard Sébastien, Flutre Timothée, Le Cunff Loïc

Abstract excerpt

Grapevine (Vitis vinifera) breeding reaches a critical point. New cultivars are released every year with resistance to powdery and downy mildews. However, the traditional process remains time-consuming, taking 20-25 years, and demands the evaluation of new traits to enhance grapevine adaptation to climate change. Until now, the selection process has relied on phenotypic data and a limited number of molecular...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Genome
Share to Genomics

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genotype

Share to Phenotype

Share to Plant Breeding

Share to Polymorphism, Single Nucleotide

Source

Open in PubMed Open full text

Identifiers

PMID: 38401528
DOI: 10.1093/g3journal/jkae038
PMCID: PMC10989862

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Enhancing grapevine breeding efficiency through genomic prediction and selection index.PMID 38401528Read ↗

Comparative assessment of genomic, phenomic, and metabolomic prediction models in biparental grapevine breeding populationsSemantic proximity Read ↗

Overview of Genomic Prediction Methods and the Associated Assumptions on the Variance of Marker Effect, and on the Architecture of the Target Trait.Semantic proximity Read ↗

Genome-wide prediction methods in highly diverse and heterozygous species: proof-of-concept through simulation in grapevine.Semantic proximity Read ↗

Genomic selection optimization in blueberry: Data-driven methods for marker and training population design.Semantic proximity Read ↗

Optimizing whole-genomic prediction for autotetraploid blueberry breeding.Semantic proximity Read ↗

A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs.Semantic proximity Read ↗

GS4PB: An R Shiny application to facilitate a genomic selection pipeline for plant breeding.Semantic proximity Read ↗

Integrating genomic predictions into an applied Central European wheat breeding program.Semantic proximity Read ↗

Comparing strategies for genomic predictions in interspecific biparental populations: a case study with the Rubus genusSemantic proximity Read ↗

Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.).Semantic proximity Read ↗

Uncovering the genetic basis of agronomic traits in over 1,000 grapevine genotypes derived from a disease resistance breeding programSemantic proximity Read ↗

Genomic selection in sugar beet breeding populations.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.