Advances and Challenges for QTL Analysis and GWAS in the Plant-Breeding of High-Yielding: A Focus on Rapeseed

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.

A Correlation Study on In Vitro Physiological Activities of Soybean Cultivars, 19 Individual Isoflavone Derivatives, and Genetic Characteristics

“…GWASs have a higher resolution than linkage mapping, and can be used to explore natural populations, as well as interbreeding groups [ 28 ]. GWASs have been extensively used to locate genes associated with traits of interest in crops, improving the accuracy of associations between genetic markers, and natural population traits [ 29 , 30 ]. Thus, a GWAS analysis was conducted to investigate the genetic association of isoflavone derivatives, which have a high correlation with the activities of the aforementioned soybean cultivars ( Figure 5 ).…”

Transcriptomic analysis of rapeseed (Brassica napus. L.) seed development in Xiangride, Qinghai Plateau, reveals how its special eco-environment results in high yield in high-altitude areas

“…Although numerous studies have focused on seed yield genetic improvement of rapeseed through quantitative trait locus (QTL) mapping, high-throughput sequencing, and genotyping techniques ( Yang et al, 2012 ; Liu et al, 2015b ; Zhao et al, 2016 ; Shah et al, 2018 ; Zheng et al, 2020 ; Khan et al, 2021 ; Hu et al, 2022 ), the comprehensive study of seed development and the mechanism contributing to high yield in the high-yield field, especially the Xiangride area, Tsaldam Basin of Qinghai Province in China, is poor, which is a constraint to our in-depth understanding of the environmental influences of this important trait and provides valuable information for future rapeseed breeding.…”

“…With rapid increases in population and the need for renewable energy, the demand for rapeseed also continually rises. Therefore, the breeding and cultivation of high-yield rapeseed varieties have become top priorities ( Slafer, 2003 ; Hu et al, 2009 ; Khan et al, 2021 ). Seed yield can be improved by taking the direct component traits and the other indirect contributing traits into consideration.…”

A multi-locus genome-wide association study reveals the genetics underlying muscadine antioxidant in berry skin

“…The 2000-rhAmpSeq markers were applied to the muscadine population, obtaining a total of 1,283 markers after filtering. We used multi-locus GWAS methods because the multilocus GWAS is known to be more powerful than the singlelocus method in detecting QTNs for complex traits (Khan et al, 2019(Khan et al, , 2021Zhang et al, 2019;Muhammad et al, 2021). Through the multi-locus GWAS analysis, a total of 12 QTNs were identified from the four antioxidant-related traits (Figure 2 and Table 2).…”