气候变化领域集成服务门户(CCPortal): Enhancing grapevine breeding efficiency through genomic prediction and selection index

CCPortal

DOI	10.1093/g3journal/jkae038
	Enhancing grapevine breeding efficiency through genomic prediction and selection index
	Brault, Charlotte; Segura, Vincent; Roques, Maryline; Lamblin, Pauline; Bouckenooghe, Virginie; Pouzalgues, Nathalie; Cunty, Constance; Breil, Matthieu; Frouin, Marina; Garcin, Lea; Camps, Louise; Ducasse, Marie-Agnes; Romieu, Charles; Masson, Gilles; Julliard, Sebastien; Flutre, Timothee; Le Cunff, Loic
发表日期	2024
ISSN	2160-1836
起始页码	14
结束页码	4
卷号	14 期号:4
英文摘要	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 markers for simple genetic traits such as resistance to pathogens, without a clearly defined ideotype, and was carried out on a large scale. To accelerate the breeding process and address these challenges, we investigated the use of genomic prediction, a methodology using molecular markers to predict genotypic values. In our study, we focused on 2 existing grapevine breeding programs: Rose wine and Cognac production. In these programs, several families were created through crosses of emblematic and interspecific resistant varieties to powdery and downy mildews. Thirty traits were evaluated for each program, using 2 genomic prediction methods: Genomic Best Linear Unbiased Predictor and Least Absolute Shrinkage Selection Operator. The results revealed substantial variability in predictive abilities across traits, ranging from 0 to 0.9. These discrepancies could be attributed to factors such as trait heritability and trait characteristics. Moreover, we explored the potential of across-population genomic prediction by leveraging other grapevine populations as training sets. Integrating genomic prediction allowed us to identify superior individuals for each program, using multivariate selection index method. The ideotype for each breeding program was defined collaboratively with representatives from the wine-growing sector.
英文关键词	genomic prediction; grapevine; plant breeding; selection index; ideotype; Cognac; Rose; genomic selection; Genomic Prediction; GenPred; Shared Data Resource
语种	英语
WOS研究方向	Genetics & Heredity
WOS类目	Genetics & Heredity
WOS记录号	WOS:001182665400001
来源期刊	G3-GENES GENOMES GENETICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/298864
作者单位	Institut Agro; INRAE; INRAE; CIRAD; Institut Agro; Universite de Montpellier; INRAE; AgroParisTech; Universite Paris Cite; Centre National de la Recherche Scientifique (CNRS); Universite Paris Saclay
推荐引用方式 GB/T 7714	Brault, Charlotte,Segura, Vincent,Roques, Maryline,et al. Enhancing grapevine breeding efficiency through genomic prediction and selection index[J],2024,14(4).
APA	Brault, Charlotte.,Segura, Vincent.,Roques, Maryline.,Lamblin, Pauline.,Bouckenooghe, Virginie.,...&Le Cunff, Loic.(2024).Enhancing grapevine breeding efficiency through genomic prediction and selection index.G3-GENES GENOMES GENETICS,14(4).
MLA	Brault, Charlotte,et al."Enhancing grapevine breeding efficiency through genomic prediction and selection index".G3-GENES GENOMES GENETICS 14.4(2024).