Integrated multi-locus genome-wide association studies and transcriptome analysis for seed yield and yield-related traits in Brassica napus

Genome-wide association study reveals genetic loci for seed density per silique in rapeseed (Brassica napus L.)

KEY MESSAGE

Two stable QTLs controlling seed density per silique were detected on chromosomes A09 and C05 in rapeseed via GWAS, and ARF18 was the only causal gene of QTL qSDPS-A09. Seed density per silique (SDPS) is a key agronomic trait that directly or indirectly affects seed yield in rapeseed (Brassica napus L.). Exploring the genetic control of SDPS is beneficial for increasing rapeseed production. In this study, we evaluated the SDPS phenotypes of 413 rapeseed cultivars (lines) across five natural environments and genotyped them by resequencing. A GWAS analysis was performed using 5,277,554 high-quality variants with the MLM_PCA + K and FarmCPU models. A total of 51 loci were identified to be significantly (p < - log10(1.88 × 10-6)) associated with SDPS, of which 5 were detected in all environments (except for SNP-2095656) by both GWAS models. Among the five loci, three were located on chromosome A09, whereas the other two loci were located on chromosome C05. The three loci on chromosome A09 and the two loci on chromosome C05 were physically close to each other. Therefore, only the two common candidate QTLs were integrated and named QTL qSDPS-A09 (320 kb) and qSDPS-C05 (331.48 kb), respectively. Sixty-seven and forty-eight candidate genes were initially identified on A09 and C05 and then narrowed down to 17 and 13 candidate genes, respectively, via LD block analyses. Gene-based association studies, haplotype analyses and expression analyses confirmed that three homologs of Arabidopsis auxin-response factor 18 (BnaA09G0559300ZS) was the most likely candidate genes underlying the QTL qSDPS-A09. ARF18Hap4 was identified as a favorable haplotype for high SDPS. These findings will aid in elucidating the genetic and molecular mechanisms of SDPS and promoting genetic modifications in rapeseed breeding.

Fine mapping and candidate gene analysis of the major QTL qSW-A03 for seed weight in Brassica napus

Seed weight is a determining factor for improving rapeseed productivity. In the present study, a high-density genetic map was constructed via genome resequencing in an RIL population derived from a cross of two rapeseed varieties, ZS11 and DL704, with great differences in thousand-seed weight (TSW). A total of 1,306 bins involving 1,261,526 markers were used to construct the bin map. On the basis of the genetic map, QTL mapping for seed weight was performed. In total, 15 QTLs associated with TSW were detected. A major and stable QTL, qSW-A03, was mapped to a 2.8 cM interval on chromosome A03. Fine mapping delimited the qSW-A03 locus into a 59-kb region, and 11 genes within this region were predicted. By employing a combination of gene variation, gene expression difference and gene coexpression network analysis of seed weight, BnaDUF1666 was identified as a promising candidate gene. This study provides useful information for the genetic dissection of seed weight and promotes the molecular breeding of high-yield rapeseed.

Effects of combined application of nitrogen, phosphorus, and potassium fertilizers on seed yield, seed quality and economic returns of Elymus nutans in alpine region

The Qinghai-Tibetan Plateau (QTP), one of the most important ecological regions in the world, is experiencing a decline in ecological function as a result of severe grassland degradation. Elymus nutans is one of the ecological grass species for restoring degraded grasslands in QTP. The seed yield and seed quality are often limited by soil nutrients in QTP, so it is very important to optimize the application rates of fertilizer for E. nutans seed production. In this study, a "3414" fertilization experiment (nitrogen: 0 ~ 225 kg N ha- 1; phosphorus: 0 ~ 180 kg P2O5 ha- 1; potassium: 0 ~ 135 kg K2O ha- 1) was established in the third year of planting E. nutans seed field based on the soil nutrient supply situation in the planting area to explore the effects of combined application of N, P and K fertilizers on the seed yield and seed quality of E. nutans. The results showed that the balanced application of N, P and K fertilizers significantly improved the seed yield, seed quality and seed vigour of E. nutans. The seed yield of E. nutans was regulated by the seed yield components. Under different fertilization treatments, the number of fertile tillers and thousand kernel weight had a greater contribution to seed yield, followed by the number of spikelets per panicle. Compared to the no fertilization treatment, the combined application of N, P, and K fertilizers increased the seed yield of E. nutans by 23.05%-90.49%. The seed size, seed nutrient content, germination percentage and seedling growth of E. nutans were positively affected by the combined application of N, P and K fertilizers. The seed vigour of E. nutans increased by 38.23%-89.85% compared to the no fertilizer treatment. Fertilizer application promoted seed nutrient storage and increased seed size thereby promoting seed germination and seedling growth. The crude protein, soluble sugar and starch content of E. nutans seed increased by 9.70%-54.05%, 6.70%-25.70% and 4.31%-35.88%, respectively. Nitrogen fertilizer had a greater effect on seed yield and seed quality of E. nutans than phosphorus and potassium fertilizers. The balanced nitrogen, phosphorus and potassium fertilizers at an application rate of 150 kg N ha- 1, 120 kg P2O5 ha- 1, 90 kg K2O ha- 1 in the planting area of QTP was found to be the optimum fertilization amount for increasing seed yield, seed quality and net income. This study provides theoretical evidence and certain practical suggestions for sustainable forage seed production in alpine regions of QTP.

Phenomic Selection for Hybrid Rapeseed Breeding

Phenomic selection is a recent approach suggested as a low-cost, high-throughput alternative to genomic selection. Instead of using genetic markers, it employs spectral data to predict complex traits using equivalent statistical models. Phenomic selection has been shown to outperform genomic selection when using spectral data that was obtained within the same generation as the traits that were predicted. However, for hybrid breeding, the key question is whether spectral data from parental genotypes can be used to effectively predict traits in the hybrid generation. Here, we aimed to evaluate the potential of phenomic selection for hybrid rapeseed breeding. We performed predictions for various traits in a structured population of 410 test hybrids, grown in multiple environments, using near-infrared spectroscopy data obtained from harvested seeds of both the hybrids and their parental lines with different linear and nonlinear models. We found that phenomic selection within the hybrid generation outperformed genomic selection for seed yield and plant height, even when spectral data was collected at single locations, while being less affected by population structure. Furthermore, we demonstrate that phenomic prediction across generations is feasible, and selecting hybrids based on spectral data obtained from parental genotypes is competitive with genomic selection. We conclude that phenomic selection is a promising approach for rapeseed breeding that can be easily implemented without any additional costs or efforts as near-infrared spectroscopy is routinely assessed in rapeseed breeding.

Dissection of quantitative trait nucleotides and candidate genes associated with agronomic and yield-related traits under drought stress in rapeseed varieties: integration of genome-wide association study and transcriptomic analysis

Introduction

An important strategy to combat yield loss challenge is the development of varieties with increased tolerance to drought to maintain production. Improvement of crop yield under drought stress is critical to global food security.

Methods

In this study, we performed multiomics analysis in a collection of 119 diverse rapeseed (Brassica napus L.) varieties to dissect the genetic control of agronomic traits in two watering regimes [well-watered (WW) and drought stress (DS)] for 3 years. In the DS treatment, irrigation continued till the 50% pod development stage, whereas in the WW condition, it was performed throughout the whole growing season.

Results

The results of the genome-wide association study (GWAS) using 52,157 single-nucleotide polymorphisms (SNPs) revealed 1,281 SNPs associated with traits. Six stable SNPs showed sequence variation for flowering time between the two irrigation conditions across years. Three novel SNPs on chromosome C04 for plant weight were located within drought tolerance-related gene ABCG16, and their pleiotropically effects on seed weight per plant and seed yield were characterized. We identified the C02 peak as a novel signal for flowering time, harboring 52.77% of the associated SNPs. The 288-kbps LD decay distance analysis revealed 2,232 candidate genes (CGs) associated with traits. The CGs BIG1-D, CAND1, DRG3, PUP10, and PUP21 were involved in phytohormone signaling and pollen development with significant effects on seed number, seed weight, and grain yield in drought conditions. By integrating GWAS and RNA-seq, 215 promising CGs were associated with developmental process, reproductive processes, cell wall organization, and response to stress. GWAS and differentially expressed genes (DEGs) of leaf and seed in the yield contrasting accessions identified BIG1-D, CAND1, and DRG3 genes for yield variation.

Discussion

The results of our study provide insights into the genetic control of drought tolerance and the improvement of marker-assisted selection (MAS) for breeding high-yield and drought-tolerant varieties.