1. Advances and Challenges for QTL Analysis and GWAS in the Plant-Breeding of High-Yielding: A Focus on Rapeseed
- Author
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Ferdinando Branca, Muhammad Hafeez Ullah Khan, Chuchuan Fan, Raheel Shahzad, Shahid Ullah Khan, Sunny Ahmar, Freddy Mora-Poblete, Osvin Arriagada, and Sumbul Saeed
- Subjects
Crops, Agricultural ,Rapeseed ,Genome-wide association study ,Crops ,Review ,Quantitative trait locus ,Biology ,Biochemistry ,Microbiology ,high-throughput genotyping ,multi-locus GWAS ,Humans ,Plant breeding ,Association mapping ,Molecular Biology ,Genotyping Techniques ,Selection (genetic algorithm) ,Agricultural ,Genome ,business.industry ,Brassica napus ,Chromosome Mapping ,food and beverages ,Plant ,Genetic architecture ,QR1-502 ,Biotechnology ,Plant Breeding ,Phenotype ,quantitative trait loci ,yield-related traits ,business ,Genome, Plant ,Genome-Wide Association Study - Abstract
Yield is one of the most important agronomic traits for the breeding of rapeseed (Brassica napus L), but its genetic dissection for the formation of high yield remains enigmatic, given the rapid population growth. In the present review, we review the discovery of major loci underlying important agronomic traits and the recent advancement in the selection of complex traits. Further, we discuss the benchmark summary of high-throughput techniques for the high-resolution genetic breeding of rapeseed. Biparental linkage analysis and association mapping have become powerful strategies to comprehend the genetic architecture of complex agronomic traits in crops. The generation of improved crop varieties, especially rapeseed, is greatly urged to enhance yield productivity. In this sense, the whole-genome sequencing of rapeseed has become achievable to clone and identify quantitative trait loci (QTLs). Moreover, the generation of high-throughput sequencing and genotyping techniques has significantly enhanced the precision of QTL mapping and genome-wide association study (GWAS) methodologies. Furthermore, this study demonstrates the first attempt to identify novel QTLs of yield-related traits, specifically focusing on ovule number per pod (ON). We also highlight the recent breakthrough concerning single-locus-GWAS (SL-GWAS) and multi-locus GWAS (ML-GWAS), which aim to enhance the potential and robust control of GWAS for improved complex traits.
- Published
- 2021