Flowering time control and applications in plant breeding

Rapeseed (Brassica napus) is the second most important oilseed crop in the world but the genetic diversity underlying its massive phenotypic variations remains largely unexplored. Here, we report the sequencing, de novo assembly and annotation of eight B. napus accessions. Using pan-genome comparative analysis, millions of small variations and 77.2–149.6 megabase presence and absence variations (PAVs) were identified. More than 9.4% of the genes contained large-effect mutations or structural variations. PAV-based genome-wide association study (PAV-GWAS) directly identified causal structural variations for silique length, seed weight and flowering time in a nested association mapping population with ZS11 (reference line) as the donor, which were not detected by single-nucleotide polymorphisms-based GWAS (SNP-GWAS), demonstrating that PAV-GWAS was complementary to SNP-GWAS in identifying associations to traits. Further analysis showed that PAVs in three FLOWERING LOCUS C genes were closely related to flowering time and ecotype differentiation. This study provides resources to support a better understanding of the genome architecture and acceleration of the genetic improvement of B. napus. The assembly of eight high-quality rapeseed genomes allows identification of presence and absence variations (PAVs) and small variations. PAV-based genome-wide association analysis uncovered causal variations for agronomic traits and ecotype differentiation.

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Eight high-quality genomes reveal pan-genome architecture and ecotype differentiation of Brassica napus.

Yield is the most important and complex trait for the genetic improvement of crops. Although much research into the genetic basis of yield and yield-associated traits has been reported, in each such experiment the genetic architecture and determinants of yield have remained ambiguous. One of the most intractable problems is the interaction between genes and the environment. We identified 85 quantitative trait loci (QTL) for seed yield along with 785 QTL for eight yield-associated traits, from 10 natural environments and two related populations of rapeseed. A trait-by-trait meta-analysis revealed 401 consensus QTL, of which 82.5% were clustered and integrated into 111 pleiotropic unique QTL by meta-analysis, 47 of which were relevant for seed yield. The complexity of the genetic architecture of yield was demonstrated, illustrating the pleiotropy, synthesis, variability, and plasticity of yield QTL. The idea of estimating indicator QTL for yield QTL and identifying potential candidate genes for yield provides an advance in methodology for complex traits.

https://www.genetics.org/content/genetics/182/3/851.full.pdf

Unraveling the Complex Trait of Crop Yield With Quantitative Trait Loci Mapping in Brassica napus

One of the most remarkable biological insights in the past 30 years has been that many genetic programs for complex traits, such as flower or limb development, are shared across broad groups of organisms. These conserved pathways in turn can be tuned to produce tremendous phenotypic differences, not

Natural Variation in Arabidopsis: From Molecular Genetics to Ecological Genomics 1(W)(OA)

http://www.plantphysiol.org/content/plantphysiol/158/1/2.full.pdf

Natural Variation in Arabidopsis: From Molecular Genetics to Ecological Genomics

Most agronomical traits exhibit quantitative variation, which is controlled by multiple genes and are environmentally dependent. To study the genetic variation of flowering time in Brassica napus, a DH population and its derived reconstructed F(2) population were planted in 11 field environments. The flowering time varied greatly with environments; 60% of the phenotypic variation was attributed to genetic effects. Five to 18 QTL at a statistically significant level (SL-QTL) were detected in each environment and, on average, two new SL-QTL were discovered with each added environment. Another type of QTL, micro-real QTL (MR-QTL), was detected repeatedly from at least 2 of the 11 environments; resulting in a total of 36 SL-QTL and 6 MR-QTL. Sixty-three interacting pairs of loci were found; 50% of them were involved in QTL. Hundreds of floral transition genes in Arabidopsis were aligned with the linkage map of B. napus by in silico mapping; 28% of them aligned with QTL regions and 9% were consistent with interacting loci. One locus, BnFLC10, in N10 and a QTL cluster in N16 were specific to spring- and winter-cropped environments respectively. The number of QTL, interacting loci, and aligned functional genes revealed a complex genetic network controlling flowering time in B. napus.

https://www.genetics.org/content/genetics/177/4/2433.full.pdf

L Shi

Papers

Flowering Time Quantitative Trait Loci Analysis of Oilseed Brassica in Multiple Environments and Genomewide Alignment with Arabidopsis