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Next-Generation Sequencing Accelerates Crop Gene Discovery
KL. Nguyen, A. Grondin, B. Courtois, P. Gantet,
Jazyk angličtina Země Velká Británie
Typ dokumentu časopisecké články, práce podpořená grantem, přehledy
- MeSH
- fenotyp MeSH
- genetické asociační studie MeSH
- jednonukleotidový polymorfismus MeSH
- lokus kvantitativního znaku * MeSH
- mapování chromozomů MeSH
- vysoce účinné nukleotidové sekvenování * MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- přehledy MeSH
The identification and isolation of genes underlying quantitative trait loci (QTLs) associated with agronomic traits in crops have been recently accelerated thanks to next-generation sequencing (NGS)-based technologies combined with plant genetics. With NGS, various revisited genetic approaches, which benefited from higher marker density, have been elaborated. These approaches improved resolution in QTL position and assisted in determining functional causative variations in genes. Examples of QTLs/genes associated with agronomic traits in crops and identified using different strategies based on whole-genome sequencing (WGS)/whole-genome resequencing (WGR) or RNA-seq are presented and discussed in this review. More specifically, we summarize and illustrate how NGS boosted bulk-segregant analysis (BSA), expression profiling, and the construction of polymorphism databases to facilitate the detection of QTLs and causative genes.
CIRAD UMR AGAP F 34398 Montpellier France
LMI RICE 2 AGI Km2 Pham Van Dong Tu Liem Hanoi Vietnam
Université de Montpellier CIRAD INRA Montpellier SupAgro Montpellier France
Citace poskytuje Crossref.org
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- $a The identification and isolation of genes underlying quantitative trait loci (QTLs) associated with agronomic traits in crops have been recently accelerated thanks to next-generation sequencing (NGS)-based technologies combined with plant genetics. With NGS, various revisited genetic approaches, which benefited from higher marker density, have been elaborated. These approaches improved resolution in QTL position and assisted in determining functional causative variations in genes. Examples of QTLs/genes associated with agronomic traits in crops and identified using different strategies based on whole-genome sequencing (WGS)/whole-genome resequencing (WGR) or RNA-seq are presented and discussed in this review. More specifically, we summarize and illustrate how NGS boosted bulk-segregant analysis (BSA), expression profiling, and the construction of polymorphism databases to facilitate the detection of QTLs and causative genes.
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