Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example

Abstract

Key message A comprehensive linkage atlas for seed yield in rapeseed. AbstractMost agronomic traits of interest for crop improvement (including seed yield) are highly complex quantitative traits controlled by numerous genetic loci, which brings challenges for comprehensively capturing associated markers/genes. We propose that multiple trait interactions underlie complex traits such as seed yield, and that considering these component traits and their interactions can dissect individual quantitative trait loci (QTL) effects more effectively and improve yield predictions. Using a segregating rapeseed (Brassica napus) population, we analyzed a large set of trait data generated in 19 independent experiments to investigate correlations between seed yield and other complex traits, and further identified QTL in this population with a SNP-based genetic bin map. A total of 1904 consensus QTL accounting for 22 traits, including 80 QTL directly affecting seed yield, were anchored to the B. napus reference sequence. Through trait association analysis and QTL meta-analysis, we identified a total of 525 indivisible QTL that either directly or indirectly contributed to seed yield, of which 295 QTL were detected across multiple environments. A majority (81.5%) of the 525 QTL were pleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrasting genetic effects, as well as 31 QTL with minor complementary effects. Implementation of the 525 QTL in genomic prediction models improved seed yield prediction accuracy. Dissecting the genetic and phenotypic interrelationships underlying complex quantitative traits using this method will provide valuable insights for genomics-based crop improvement.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-017-2911-7) contains supplementary material, which is available to authorized users.

Reconstituting the genome of a young allopolyploid crop, Brassica napus, with its related species

“…Considering the detection of multiple alleles of the homologous loci and the high heterozygosity of the RS lines, A and C genomic SSR markers were selected based on the genetic map of B. napus and B. carinata (Guo et al ., ; Luo et al ., ) and traditional B. napus , B. rapa and B. carinata accessions were used as a reference to evaluate the heterozygote RS population. We observed rich genetic variation in the gene pool and significant divergence from the traditional B. napus (Figure ; Table ).…”

“…To accomplish this, we constructed a novel gene pool of B. napus (A r A r C c C c ) based on one accession of B. napus, 74 accessions of B. carinata, and 122 accessions of B. rapa by incorporating thousands of lines of the Poly-A r and the Poly-C c subpopulations of the new-type B. napus Zou et al, 2018) using the DGMS system followed by intensive recurrent selection (Figure 1). With this approach, novel genetic variation was generated from (i) Considering the detection of multiple alleles of the homologous loci and the high heterozygosity of the RS lines, A and C genomic SSR markers were selected based on the genetic map of B. napus and B. carinata (Guo et al, 2012;Luo et al, 2017) and traditional B. napus, B. rapa and B. carinata accessions were used as a reference to evaluate the heterozygote RS population. We observed rich genetic variation in the gene pool and significant divergence from the traditional B. napus (Figure 2, 3; Table 1).…”

“…Comparatively, the improvements in the EAC and GSLC were the most rapid, because they have relatively high heritability with simple genetic architecture controlled by a few major genes. As a result, the rapid reduction in the EAC may promote the increase in oleic acid (Table S6), because erucic acid is synthesized with oleic acid as a substrate under the control of the FAE1 gene (Han et al, 2001;Lassner et al, 1996) and negatively correlated with oleic acid (Luo et al, 2017). For agronomic traits, which have complex genetic architecture and low heritability, their improvement was not remarkable from RS1 to RS3, because the field selection was not as accurate as the indoor phenotype selection performed in RS4 and RS5, which leads to improved agronomic traits from RS3 to RS5 ( Figure 5, Table S6).…”

“…All the DNA samples were extracted from young leaves using a modified version of the CTAB method as previously described (Stewart and Via, ). Eighty pairs of SSR primers covering 19 chromosomes of the A and C genome were selected from the markers mapped in the genetic map of the BnaTN DH population (Luo et al ., ) and the BcYW DH population (Guo et al ., ), and two Indel markers (Larkan et al ., ) were used in this study (Table S2); most of those markers located in the QTL regions accounted for important traits. An ABI 3500xL Genetic Analyzer analysed the PCR products.…”

Genome‐wide selection footprints and deleterious variations in young Asian allotetraploid rapeseed

“…In this study, we sequenced and de novo assembled the genome of Ningyou7 (NY7), an elite Chinese semi-winter B. napus cultivar developed from early SL cultivars with introgressions from local diploid rapeseed B. rapa but without introgression of the double-low traits from European rapeseed (Luo et al, 2017;Qiu et al, 2006) (Figure 1a). This result contrasts with the recently sequenced Asian cultivar ZS11, which carries double-low alleles .…”