An integrated analysis of QTL mapping and RNA sequencing provides further insights and promising candidates for pod number variation in rapeseed (Brassica napus L.)

Genetic analysis and QTL mapping for silique density in rapeseed (Brassica napus L.)

KEY MESSAGE

Genetic models, QTLs and candidate gene for silique density on main inflorescence of rapeseed were identified. Silique density is one of the critical factors to determine seed yield and plant architecture in rapeseed (Brassica napus L.); however, the genetic control of this trait is largely unknown. In this study, the genetic model for silique density on main inflorescence (SDMI) of rapeseed was estimated according to the phenotypic data of P₁ (an inbreed line with high SDMI), P₂ (an inbreed line with low SDMI), F₁, F₂, BC₁P₁ and BC₁P₂ populations, revealing that SDMI is probably controlled by multi-minor genes with or without major gene. The QTLs for SDMI and its component characters including silique number on main inflorescence (SNMI) and main inflorescence length (MIL) were consequently mapped from a DH population derived from P₁ and P₂ by using a genetic linkage map constructed by restriction site-associated DNA sequencing (RAD seq) technology. A total of eight, 14 and three QTLs were identified for SDMI, SNMI and MIL under three environments, respectively, with an overlap among SDMI and SNMI in 55.7-75.4 cm on linkage group C06 which corresponding to 11.6-27.3 Mb on chromosome C06. Genomic resequencing was further conducted between a high- and a low-SDMI pool constructed from the DH population, and QTL-seq analysis identified a 0.15 Mb interval (25.98-26.13 Mb) from the C06-QTL region aforementioned. Transcriptome sequencing and qRT-PCR identified one possible candidate gene (BnARGOS) from the 0.15 Mb interval. This study will provide novel insights into the genetic basis of SD in rapeseed.

Discovery of common loci and candidate genes for controlling salt-alkali tolerance and yield-related traits in Brassica napus L

KEY MESSAGE

Common loci and candidate genes for controlling salt-alkali tolerance and yield-related traits were identified in Brassica napus combining QTL mapping with transcriptome under salt and alkaline stresses. The yield of rapeseed (Brassica napus L.) is determined by multiple yield-related traits, which are susceptible to environmental factors. Many yield-related quantitative trait loci (QTLs) have been reported in Brassica napus; however, no studies have been conducted to investigate both salt-alkali tolerance and yield-related traits simultaneously. Here, specific-locus amplified fragment sequencing (SLAF-seq) technologies were utilized to map the QTLs for salt-alkali tolerance and yield-related traits. A total of 65 QTLs were identified, including 30 QTLs for salt-alkali tolerance traits and 35 QTLs for yield-related traits, accounting for 7.61-27.84% of the total phenotypic variations. Among these QTLs, 18 unique QTLs controlling two to four traits were identified by meta-analysis. Six novel and unique QTLs were detected for salt-alkali tolerance traits. By comparing these unique QTLs for salt-alkali tolerance traits with those previously reported QTLs for yield-related traits, seven co-localized chromosomal regions were identified on A09 and A10. Combining QTL mapping with transcriptome of two parents under salt and alkaline stresses, thirteen genes were identified as the candidates controlling both salt-alkali tolerance and yield. These findings provide useful information for future breeding of high-yield cultivars resistant to alkaline and salt stresses.

Genome-Wide Association Studies of Salt Tolerance at the Seed Germination Stage and Yield-Related Traits in Brassica napus L

Salt stress severely affects crop growth and development and reduces the yield of Brassica napus. Exploring natural genetic variations for high salt tolerance in B. napus seedlings is an effective approach to improve productivity under salt stress. Using 10,658 high-quality single nucleotide polymorphic (SNP) markers developed by specific-locus amplified fragment sequencing (SLAF-seq) technology, genome-wide association studies (GWAS) were performed to investigate the genetic basis of salt tolerance and yield-related traits of B. napus. The results revealed that 77 and 497 SNPs were significantly associated with salt tolerance and yield-related traits, of which 40 and 58 SNPs were located in previously reported QTLs/SNPs, respectively. We identified nineteen candidate genes orthologous with Arabidopsis genes known to be associated with salt tolerance and seven potential candidates controlling both salt tolerance and yield. Our study provides a novel genetic resource for the breeding of high-yield cultivars resistant to salt stress.

Identifying Soybean Pod Borer (Leguminivora glycinivorella) Resistance QTLs and the Mechanism of Induced Defense Using Linkage Mapping and RNA-Seq Analysis

The soybean pod borer (Leguminivora glycinivorella) (SPB) is a major cause of soybean (Glycine max L.) yield losses in northeast Asia, thus it is desirable to elucidate the resistance mechanisms involved in soybean response to the SPB. However, few studies have mapped SPB-resistant quantitative trait loci (QTLs) and deciphered the response mechanism in soybean. Here, we selected two soybean varieties, JY93 (SPB-resistant) and K6 (SPB-sensitive), to construct F₂ and F_2:3 populations for QTL mapping and collected pod shells before and after SPB larvae chewed on the two parents to perform RNA-Seq, which can identify stable QTLs and explore the response mechanism of soybean to the SPB. The results show that four QTLs underlying SPB damage to seeds were detected on chromosomes 4, 9, 13, and 15. Among them, qESP-9-1 was scanned in all environments, hence it can be considered a stable QTL. All QTLs explained 0.79 to 6.09% of the phenotypic variation. Meanwhile, 2298 and 3509 DEGs were identified for JY93 and K6, respectively, after the SPB attack, and most of these genes were upregulated. Gene Ontology enrichment results indicated that the SPB-induced and differently expressed genes in both parents are involved in biological processes such as wound response, signal transduction, immune response, and phytohormone pathways. Interestingly, secondary metabolic processes such as flavonoid synthesis were only significantly enriched in the upregulated genes of JY93 after SPB chewing compared with K6. Finally, we identified 18 candidate genes related to soybean pod borer resistance through the integration of QTL mapping and RNA-Seq analysis. Seven of these genes had similar expression patterns to the mapping parents in four additional soybean germplasm after feeding by the SPB. These results provide additional knowledge of the early response and induced defense mechanisms against the SPB in soybean, which could help in breeding SPB-resistant soybean accessions.

Further insight into decreases in seed glucosinolate content based on QTL mapping and RNA-seq in Brassica napus L

The QTL hotspots determining seed glucosinolate content instead of only four HAG1 loci and elucidation of a potential regulatory model for rapeseed SGC variation. Glucosinolates (GSLs) are amino acid-derived, sulfur-rich secondary metabolites that function as biopesticides and flavor compounds, but the high seed glucosinolate content (SGC) reduces seed quality for rapeseed meal. To dissect the genetic mechanism and further reduce SGC in rapeseed, QTL mapping was performed using an updated high-density genetic map based on a doubled haploid (DH) population derived from two parents that showed significant differences in SGC. In 15 environments, a total of 162 significant QTLs were identified for SGC and then integrated into 59 consensus QTLs, of which 32 were novel QTLs. Four QTL hotspot regions (QTL-HRs) for SGC variation were discovered on chromosomes A09, C02, C07 and C09, including seven major QTLs that have previously been reported and four novel major QTLs in addition to HAG1 loci. SGC was largely determined by superimposition of advantage allele in the four QTL-HRs. Important candidate genes directly related to GSL pathways were identified underlying the four QTL-HRs, including BnaC09.MYB28, BnaA09.APK1, BnaC09.SUR1 and BnaC02.GTR2a. Related differentially expressed candidates identified in the minor but environment stable QTLs indicated that sulfur assimilation plays an important rather than dominant role in SGC variation. A potential regulatory model for rapeseed SGC variation constructed by combining candidate GSL gene identification and differentially expressed gene analysis based on RNA-seq contributed to a better understanding of the GSL accumulation mechanism. This study provides insights to further understand the genetic regulatory mechanism of GSLs, as well as the potential loci and a new route to further diminish the SGC in rapeseed.

Analysis of transcriptome data and quantitative trait loci enables the identification of candidate genes responsible for fiber strength in Gossypium barbadense

Gossypium barbadense possesses a superior fiber quality because of its fiber length and strength. An in-depth analysis of the underlying genetic mechanism could aid in filling the gap in research regarding fiber strength and could provide helpful information for Gossypium barbadense breeding. Three quantitative trait loci related to fiber strength were identified from a Gossypium barbadense recombinant inbred line (PimaS-7 × 5917) for further analysis. RNA sequencing was performed in the fiber tissues of PimaS-7 × 5917 0–35 days postanthesis. Four specific modules closely related to the secondary wall-thickening stage were obtained using the weighted gene coexpression network analysis. In total, 55 genes were identified as differentially expressed from 4 specific modules. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes were used for enrichment analysis, and Gbar_D11G032910, Gbar_D08G020540, Gbar_D08G013370, Gbar_D11G033670, and Gbar_D11G029020 were found to regulate fiber strength by playing a role in the composition of structural constituents of cytoskeleton and microtubules during fiber development. Quantitative real-time PCR results confirmed the accuracy of the transcriptome data. This study provides a quick strategy for exploring candidate genes and provides new insights for improving fiber strength in cotton.

RAD-Seq-Based High-Density Linkage Maps Construction and Quantitative Trait Loci Mapping of Flowering Time Trait in Alfalfa (Medicago sativa L.)

Alfalfa (Medicago sativa L.) is a perennial forage crop known as the "Queen of Forages." To dissect the genetic mechanism of flowering time (FT) in alfalfa, high-density linkage maps were constructed for both parents of an F1 mapping population derived from a cross between Cangzhou (P1) and ZhongmuNO.1 (P2), consisting of 150 progenies. The FT showed a transgressive segregation pattern in the mapping population. A total of 13,773 single-nucleotide polymorphism markers was obtained by using restriction-site associated DNA sequencing and distributed on 64 linkage groups, with a total length of 3,780.49 and 4,113.45 cM and an average marker interval of 0.58 and 0.59 cM for P1 and P2 parent, respectively. Quantitative trait loci (QTL) analyses were performed using the least square means of each year as well as the best linear unbiased prediction values across 4 years. Sixteen QTLs for FT were detected for P1 and 22 QTLs for P2, accounting for 1.40-16.04% of FT variation. RNA-Seq analysis at three flowering stages identified 5,039, 7,058, and 7,996 genes that were differentially expressed between two parents, respectively. Based on QTL mapping, DEGs analysis, and functional annotation, seven candidate genes associated with flowering time were finally detected. This study discovered QTLs and candidate genes for alfalfa FT, making it a useful resource for breeding studies on this essential crop.

Construction of a Quantitative Genomic Map, Identification and Expression Analysis of Candidate Genes for Agronomic and Disease-Related Traits in Brassica napus

Rapeseed is the second most important oil crop in the world. Improving seed yield and seed oil content are the two main highlights of the research. Unfortunately, rapeseed development is frequently affected by different diseases. Extensive research has been made through many years to develop elite cultivars with high oil, high yield, and/or disease resistance. Quantitative trait locus (QTL) analysis has been one of the most important strategies in the genetic deciphering of agronomic characteristics. To comprehend the distribution of these QTLs and to uncover the key regions that could simultaneously control multiple traits, 4,555 QTLs that have been identified during the last 25 years were aligned in one unique map, and a quantitative genomic map which involved 128 traits from 79 populations developed in 12 countries was constructed. The present study revealed 517 regions of overlapping QTLs which harbored 2,744 candidate genes and might affect multiple traits, simultaneously. They could be selected to customize super-rapeseed cultivars. The gene ontology and the interaction network of those candidates revealed genes that highly interacted with the other genes and might have a strong influence on them. The expression and structure of these candidate genes were compared in eight rapeseed accessions and revealed genes of similar structures which were expressed differently. The present study enriches our knowledge of rapeseed genome characteristics and diversity, and it also provided indications for rapeseed molecular breeding improvement in the future.

Combining QTL Mapping and Transcriptomics to Decipher the Genetic Architecture of Phenolic Compounds Metabolism in the Conifer White Spruce

Conifer forests worldwide are becoming increasingly vulnerable to the effects of climate change. Although the production of phenolic compounds (PCs) has been shown to be modulated by biotic and abiotic stresses, the genetic basis underlying the variation in their constitutive production level remains poorly documented in conifers. We used QTL mapping and RNA-Seq to explore the complex polygenic network underlying the constitutive production of PCs in a white spruce (Picea glauca) full-sib family for 2 years. QTL detection was performed for nine PCs and differentially expressed genes (DEGs) were identified between individuals with high and low PC contents for five PCs exhibiting stable QTLs across time. A total of 17 QTLs were detected for eight metabolites, including one major QTL explaining up to 91.3% of the neolignan-2 variance. The RNA-Seq analysis highlighted 50 DEGs associated with phenylpropanoid biosynthesis, several key transcription factors, and a subset of 137 genes showing opposite expression patterns in individuals with high levels of the flavonoids gallocatechin and taxifolin glucoside. A total of 19 DEGs co-localized with QTLs. Our findings represent a significant step toward resolving the genomic architecture of PC production in spruce and facilitate the functional characterization of genes and transcriptional networks responsible for differences in constitutive production of PCs in conifers.

Insights on SNP types, detection methods and their utilization in Brassica species: Recent progress and future perspectives

The genus Brassica, family Brassicaceae (Cruciferae), comprises many important species of oil crops, vegetables and medicinal plants including B. rapa, B. oleracea, B. nigra, B. napus, B. juncea, B. carinata. Genomic researches in Brassica species is constrained by polyploidization, mainly due to its complicated genomic structure. However, rapid development of methods for detecting single nucleotide polymorphisms (SNP), such as next generation sequencing and SNP microarray, has accelerated release of reference Brassica species genomes as well as discovery of large numbers and genome-wide SNPs, thus intensifying forward genetics in this genus. In this review, we summarize biological characteristics, classification and various methods for detecting SNPs, focusing on high-throughput techniques. Moreover, we describe the pivotal roles of SNPs in genetic diversity, linkage map construction and QTL mapping, comparative genomics, linkage disequilibrium and genome-wide association studies. These insights are expected to deepen our understanding and guide further advancements in Brassica species research.

A recessive high-density pod mutant resource of Brassica napus

In Brassica napus, pod number and pod density are critical factors to determine seed yield. Although the pod density is an essential yield trait, the regulation of yield formation in oil crops, as well as the genetic and molecular mechanisms, are poorly understood. In this study, we characterized a rapeseed high-density pod mutant (dpt247) from composite hybridization. To shed some light on the nature of this mutation, it was investigated morphologically, anatomically, physiologically, genetically and transcriptomically. The mutant plant showed noticeable phenotypic differences in comparison with the control plant, including reduced plant height and primary branch length, decreased number of primary branches, significantly increased number of pod on the main inflorescence, and more compact pod distribution. Besides, the mutant had higher levels of indole-3-acetic acid (IAA) and zeatin riboside (ZR) in the shoot apical meristem (SAM). The dense pod trait was controlled by two major recessive genes identified in the segregating genetic populations of GRE501 and dpt247. RNA sequencing indicated genes participated in auxin, cytokinin and WUS/CLV signalling pathway in dpt247 were more active in the mutant. These results provide important information for understanding the regulation of yield formation and high yield breeding in rapeseed.

A systematic dissection of the mechanisms underlying the natural variation of silique number in rapeseed (Brassica napus L.) germplasm

Silique number is the most important component of yield in rapeseed (Brassica napus L.). To dissect the mechanism underlying the natural variation of silique number in rapeseed germplasm, a series of studies were performed. A panel of 331 core lines was employed to genome-wide association study (GWAS), and 27 loci (including 20 novel loci) were identified. The silique number difference between the more- and fewer-silique lines can be attributed to the accumulative differences in flower number and silique setting rate. Each of them accounted for 75.2% and 24.8%, respectively. The silique number was highly associated with the total photosynthesis and biomass. Microscopic analysis showed that the difference between extremely more- and fewer-silique lines normally occurred at the amount of flower bud but not morphology. Transcriptome analysis of shoot apical meristem (SAM) suggested that most of enriched groups were associated with the auxin biosynthesis/metabolism, vegetative growth and nutrition/energy accumulation. By integrating GWAS and RNA-seq results, six promising candidate genes were identified, and some of them were related to biomass accumulation. In conclusion, the natural variation of silique number is largely affected by the biomass and nutrition accumulation, which essentially reflects the positive regulatory relationship between the source and sink. Our study provides a comprehensive and systematic explanation for natural variation of silique number in rapeseed, which provides a foundation for its improvement.

Integrating GWAS, linkage mapping and gene expression analyses reveals the genetic control of growth period traits in rapeseed (Brassica napus L.)

BACKGROUND

Brassica napus is one of the most important oilseed crops, and also an important biofuel plant due to its low air pollution and renewability. Growth period are important traits that affect yield and are crucial for its adaptation to different environments in B. napus.

RESULTS

To elucidate the genetic basis of growth period traits, genome-wide association analysis (GWAS) and linkage mapping were employed to detect the quantitative trait loci (QTL) for days to initial flowering (DIF), days to final flowering (DFF), flowering period (FP), maturity time (MT), and whole growth period (GP). A total of 146 SNPs were identified by association mapping, and 83 QTLs were identified by linkage mapping using the RIL population. Among these QTLs, 19 were pleiotropic SNPs related to multiple traits, and six (q18DFF.A03-2, q18MT.A03-2, q17DFF.A05-1, q18FP.C04, q17DIF.C05 and q17GP.C09) were consistently detected using both mapping methods. Additionally, we performed RNA sequencing to analyze the differential expression of gene (DEG) transcripts between early- and late-flowering lines selected from the RIL population, and the DEGs were integrated with association mapping and linkage analysis to confirm their roles in the growth period. Consequently, 12 candidate genes associated with growth period traits were identified in B. napus. Among these genes, seven have polymorphic sites in the coding sequence and the upstream 2-kb sequence based on the resequencing data. The haplotype BnaSOC1.A05-Haplb and BnaLNK2.C06-Hapla showed more favorable phenotypic traits.

CONCLUSIONS

The candidate genes identified in this study will contribute to our genetic understanding of growth period traits and can be used as targets for target mutations or marker-assisted breeding for rapeseed adapted to different environments.

Identification of heat-tolerance QTLs and high-temperature stress-responsive genes through conventional QTL mapping, QTL-seq and RNA-seq in tomato

BACKGROUND

High temperature is one of the major abiotic stresses in tomato and greatly reduces fruit yield and quality. Identifying high-temperature stress-responsive (HSR) genes and breeding heat-tolerant varieties is an effective way to address this issue. However, there are few reports on the fine mapping of heat-tolerance quantitative trait locus (QTL) and the identification of HSR genes in tomato. Here, we applied three heat tolerance-related physiological indexes, namely, relative electrical conductivity (REC), chlorophyll content (CC) and maximum photochemical quantum efficiency (Fv/Fm) of PSII (photosystem II), as well as the phenotypic index, the heat injury index (HII), and conventional QTL analysis combined with QTL-seq technology to comprehensively detect heat-tolerance QTLs in tomato seedlings. In addition, we integrated the QTL mapping results with RNA-seq to identify key HSR genes within the major QTLs.

RESULTS

A total of five major QTLs were detected: qHII-1-1, qHII-1-2, qHII-1-3, qHII-2-1 and qCC-1-5 (qREC-1-3). qHII-1-1, qHII-1-2 and qHII-1-3 were located, respectively, in the intervals of 1.43, 1.17 and 1.19 Mb on chromosome 1, while the interval of qHII-2-1 was located in the intervals of 1.87 Mb on chromosome 2. The locations observed with conventional QTL mapping and QTL-seq were consistent. qCC-1-5 and qREC-1-3 for CC and REC, respectively, were located at the same position by conventional QTL mapping. Although qCC-1-5 was not detected in QTL-seq analysis, its phenotypic variation (16.48%) and positive additive effect (0.22) were the highest among all heat tolerance QTLs. To investigate the genes involved in heat tolerance within the major QTLs in tomato, RNA-seq analysis was performed, and four candidate genes (SlCathB2, SlGST, SlUBC5, and SlARG1) associated with heat tolerance were finally detected within the major QTLs by DEG analysis, qRT-PCR screening and biological function analysis.

CONCLUSIONS

In conclusion, this study demonstrated that the combination of conventional QTL mapping, QTL-seq analysis and RNA-seq can rapidly identify candidate genes within major QTLs for a complex trait of interest to replace the fine-mapping process, thus greatly shortening the breeding process and improving breeding efficiency. The results have important applications for the fine mapping and identification of HSR genes and breeding for improved thermotolerance.

Temporal genetic patterns of root growth in Brassica napus L. revealed by a low-cost, high-efficiency hydroponic system

Application of a low-cost and high-efficiency hydroponic system in a rapeseed population verified two types of genetic factors ("persistent" and "stage-specific") that control root development. The root system is a vital plant component for nutrient and water acquisition and is targeted to enhance plant productivity. Genetic dissection of the root system generally focuses on a single stage, but roots grow continuously during plant development. To reveal the temporal genetic patterns of root development, we measured nine root-related traits in a rapeseed recombinant inbred line population at six continuous stages during vegetative growth, using a modified hydroponic system with low-cost and high-efficiency features that could synchronize plant growth under controlled conditions. Phenotypic correlation and growth dynamic analysis suggested the existence of two types of genetic factors ("persistent" and "stage-specific") that control root development. Dynamic (unconditional and conditional) quantitative trait loci (QTL) mapping detected 28 stage-specific and 23 persistent QTLs related to root growth. Among them, 13 early stage-specific, 19 persistent and 8 later stage-specific QTLs were detected at 7 DAS (days after sowing), 16 DAS and 5 EL (expanding leaf stage), respectively, providing efficient and adaptable stages for QTL identification. The effective prediction of biomass accumulation using root morphological traits (up to 96.6% or 92.64% at a specific stage or the final stage, respectively) verified that root growth allocation with maximum root uptake area facilitated biomass accumulation. Furthermore, marker-assistant selection, which combined the "persistent" and "stage-specific" QTLs, proved their effectiveness for root improvement with an excellent uptake area. Our results highlight the potential of high-throughput and precise phenotyping to assess the dynamic genetics of root growth and provide new insights into ideotype root system-based biomass breeding.

Whole-transcriptome analysis reveals genetic factors underlying flowering time regulation in rapeseed (Brassica napus L.)

Rapeseed (Brassica napus L.), one of the most important sources of vegetable oil and protein-rich meals worldwide, is adapted to different geographical regions by modification of flowering time. Rapeseed cultivars have different day length and vernalization requirements, which categorize them into winter, spring, and semiwinter ecotypes. To gain a deeper insight into genetic factors controlling floral transition in B. napus, we performed RNA sequencing (RNA-seq) in the semiwinter doubled haploid line, Ningyou7, at different developmental stages and temperature regimes. The expression profiles of more than 54,000 gene models were compared between different treatments and developmental stages, and the differentially expressed genes were considered as targets for association analysis and genetic mapping to confirm their role in floral transition. Consequently, 36 genes with association to flowering time, seed yield, or both were identified. We found novel indications for neofunctionalization in homologs of known flowering time regulators like VIN3 and FUL. Our study proved the potential of RNA-seq along with association analysis and genetic mapping to identify candidate genes for floral transition in rapeseed. The candidate genes identified in this study could be subjected to genetic modification or targeted mutagenesis and genotype building to breed rapeseed adapted to certain environments.

A multiple near isogenic line (multi-NIL) RNA-seq approach to identify candidate genes underpinning QTL

This study demonstrates how identification of genes underpinning disease-resistance QTL based on differential expression and SNPs can be improved by performing transcriptomic analysis on multiple near isogenic lines. Transcriptomic analysis has been widely used to understand the genetic basis of a trait of interest by comparing genotypes with contrasting phenotypes. However, these approaches identify such large sets of differentially expressed genes that it proves difficult to isolate which genes underpin the phenotype of interest. This study tests whether using multiple near isogenic lines (NILs) can improve the resolution of RNA-seq-based approaches to identify genes underpinning disease-resistance QTL. A set of NILs for a major effect Fusarium crown rot-resistance QTL in barley on the 4HL chromosome arm were analysed under Fusarium crown rot using RNA-seq. Differential gene expression and single nucleotide polymorphism detection analyses reduced the number of putative candidates from thousands within individual NIL pairs to only one hundred and two genes, which were differentially expressed or contained SNPs in common across NIL pairs and occurred on 4HL. Our findings support the value of performing RNA-seq analysis using multiple NILs to remove genetic background effects. The enrichment analyses indicated conserved differences in the response to infection between resistant and sensitive isolines suggesting that sensitive isolines are impaired in systemic defence response to Fusarium pseudograminearum.

QTL Alignment for Seed Yield and Yield Related Traits in Brassica napus

Worldwide consumption of oil is increasing with the growing population in need for edible oil and the expansion of industry using biofuels. Then, demand for high yielding varieties of oil crops is always increasing. Brassica napus (rapeseed) is one of the most important oil crop in the world, therefore, increasing rapeseed yield through breeding is inevitable in order to cater for the high demand of vegetable oil and high-quality protein for live stocks. Quantitative trait loci (QTL) analysis is a powerful tool to identify important loci and which is also valuable for molecular marker assisted breeding. Seed-yield (SY) is a complex trait that is controlled by multiple loci and is affected directly by seed weight, seeds per silique and silique number. Some yield-related traits, such as plant height, biomass yield, flowering time, and so on, also affect the SY indirectly. This study reports the assembly of QTLs identified for seed-yield and yield-related traits in rapeseed, in one unique map. A total of 972 QTLs for seed-yield and yield-related were aligned into the physical map of B. napus Darmor-bzh and 92 regions where 198 QTLs overlapped, could be discovered on 16 chromosomes. Also, 147 potential candidate genes were discovered in 65 regions where 131 QTLs overlapped, and might affect nine different traits. At the end, interaction network of candidate genes was studied, and showed nine genes that could highly interact with the other genes, and might have more influence on them. The present results would be helpful to develop molecular markers for yield associated traits and could be used for breeding improvement in B. napus.