Earliness traits in rapeseed (Brassica napus): SNP loci and candidate genes identified by genome-wide association analysis.
ABSTRACT: Life cycle timing is critical for yield and productivity of Brassica napus (rapeseed) cultivars grown in different environments. To facilitate breeding for earliness traits in rapeseed, SNP loci and underlying candidate genes associated with the timing of initial flowering, maturity and final flowering, as well as flowering period (FP) were investigated in two environments in a diversity panel comprising 300 B. napus inbred lines. Genome-wide association studies (GWAS) using 201,817 SNP markers previously developed from SLAF-seq (specific locus amplified fragment sequencing) revealed a total of 131 SNPs strongly linked (P?0.6) or in 100 kb regions around significant trait-associated SNPs were screened, revealing 57 B. napus genes (33 SNPs) orthologous to 39 Arabidopsis thaliana flowering time genes. These results support the practical and scientific value of novel large-scale SNP data generation in uncovering the genetic control of agronomic traits in B. napus, and also provide a theoretical basis for molecular marker-assisted selection of earliness breeding in rapeseed.
Project description: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.
Project description:Brassica napus is a leading oilseed crop throughout many parts of the world. It is well adapted to long day photoperiods, however, it does not adapt well to short day subtropical regions. Short duration B. napus plants were resynthesized through ovary culture from interspecific crosses in which B. rapa cultivars were reciprocally crossed with B. oleracea. From five different combinations, 17 hybrid plants were obtained in both directions. By self-pollinating the F1 hybrids or introgressing them with cultivated B. napus, resynthesized (RS) F3 and semi-resynthesized (SRS) F2 generations were produced, respectively. In field trial in Bangladesh, the RS B. napus plants demonstrated variation in days to first flowering ranging from 29 to 73 days; some of which were similar to cultivated short duration B. napus, but not cultivated short duration B. rapa. The RS and SRS B. napus lines produced 2-4.6 and 1.6-3.7 times higher yields, respectively, as compared to cultivated short duration B. napus. Our developed RS lines may be useful for rapeseed breeding not only for subtropical regions, but also for areas such as Canada and Europe where spring rapeseed production can suffer from late spring frosts. Yield and earliness in RS lines are discussed.
Project description:Harvest index, defined as the ratio of reproductive yield to total plant biomass, and early ripening are traits with important agronomic value in processing tomatoes. The Solanum pennellii introgression-line (IL) population shows variation for harvest index and earliness. Most of the QTL mapped for these traits display negative agronomic effects; however, hi2-1 is a unique QTL displaying improved harvest index and earliness. This introgression was tested over several years and under different genetic backgrounds. Thirty-one nearly isogenic sub-lines segregating for the 18 cM TG33-TG276 interval were used for fine mapping of this multi-phenotypic QTL. Based on this analysis the phenotypic effects for plant weight, Brix, total yield and earliness were co-mapped to the same region. In a different mapping experiment these sub-lines were tested as heterozygotes in order to map the harvest index QTL which were only expressed in the heterozygous state. These QTL mapped to the same candidate region, suggesting that hi2-1 is either a single gene with pleiotropic effects or represents linked genes independently affecting these traits. Metabolite profiling of the fruit pericarp revealed that a number of metabolic QTL co-segregate with the harvest index trait including those for important transport assimilates such as sugars and amino acids. Analysis of the flowering pattern of these lines revealed induced flowering at IL2-1 plants, suggest that hi2-1 may also affect harvest index and early ripening by changing plant architecture and flowering rate.
Project description: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.
Project description: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.
Project description:Soil salinity is a serious threat to agriculture sustainability worldwide. Salt tolerance at the seedling stage is crucial for plant establishment and high yield in saline soils; however, little information is available on rapeseed (Brassica napus L.) salt tolerance. We evaluated salt tolerance in different rapeseed accessions and conducted a genome-wide association study (GWAS) to identify salt tolerance-related quantitative trait loci (QTL). A natural population comprising 368 B. napus cultivars and inbred lines was genotyped with a Brassica 60K Illumina Infinium SNP array. The results revealed that 75 single-nucleotide polymorphisms (SNPs) distributed across 14 chromosomes were associated with four salt tolerance-related traits. These SNPs integrated into 25 QTLs that explained 4.21-9.23% of the phenotypic variation in the cultivars. Additionally, 38 possible candidate genes were identified in genomic regions associated with salt tolerance indices. These genes fell into several functional groups that are associated with plant salt tolerance, including transcription factors, aquaporins, transporters, and enzymes. Thus, salt tolerance in rapeseed involves complex molecular mechanisms. Our results provide valuable information for studying the genetic control of salt tolerance in B. napus seedlings and may facilitate marker-based breeding for rapeseed salt tolerance.
Project description:Flowering time adaptation is a major breeding goal in the allopolyploid species Brassica napus. To investigate the genetic architecture of flowering time, a genome-wide association study (GWAS) of flowering time was conducted with a diversity panel comprising 523 B. napus cultivars and inbred lines grown in eight different environments. Genotyping was performed with a Brassica 60K Illumina Infinium SNP array. A total of 41 single-nucleotide polymorphisms (SNPs) distributed on 14 chromosomes were found to be associated with flowering time, and 12 SNPs located in the confidence intervals of quantitative trait loci (QTL) identified in previous researches based on linkage analyses. Twenty-five candidate genes were orthologous to Arabidopsis thaliana flowering genes. To further our understanding of the genetic factors influencing flowering time in different environments, GWAS was performed on two derived traits, environment sensitivity and temperature sensitivity. The most significant SNPs were found near Bn-scaff_16362_1-p380982, just 13 kb away from BnaC09g41990D, which is orthologous to A. thaliana CONSTANS (CO), an important gene in the photoperiod flowering pathway. These results provide new insights into the genetic control of flowering time in B. napus and indicate that GWAS is an effective method by which to reveal natural variations of complex traits in B. napus.
Project description:Pigeonpea productivity is greatly constrained by poor plant ideotype of existing Indian cultivars. Enhancing pigeonpea yield demands a renewed focus on restructuring the ideal plant type by using more efficient approaches like genomic tools. Therefore, the present study aims to identify and validate a set of QTLs/gene(s) presumably associated with various plant ideotype traits in pigeonpea. A total of 133 pigeonpea germplasms were evaluated along with four checks in the augmented design for various ideotype traits i.e. initiation of flowering (IF), days to 50% flowering (DFF), days to maturity (DM), plant height (PH), primary branches (PB), seeds per pod (SP) and pod length (PL). We observed significant genetic diversity in the germplasm lines for these traits. The genetic control of IF, DFF, DM and PH renders these traits suitable for detection of marker trait associations. By using residual maximum likelihood algorithm, we obtained appropriate variance-covariance structures for modeling heterogeneity, correlation of genetic effects and non-genetic residual effects. The estimates of genetic correlations indicated a strong association among earliness traits. The best linear unbiased prediction values were calculated for individual traits, and association analysis was performed in a panel of 95 diverse genotypes with 19 genic SSRs. Out of five QTL-flanking SSRs used here for validation, only ASSR295 could show significant association with FDR and Bonferroni corrections, and accounted for 15.4% IF, 14.2% DFF and 16.2% DM of phenotypic variance (PV). Remaining SSR markers (ASSR1486, ASSR206 and ASSR408) could not qualify false discovery rate (FDR) and Bonferroni criteria, hence declared as false positives. Additionally, we identified two highly significant SSR markers, ASSR8 and ASSR390 on LG 1 and LG 2, respectively. The SSR marker ASSR8 explained up to 22 and 11% PV for earliness traits and PB respectively, whereas ASSR390 controlled up to 17% PV for earliness traits. The validation and identification of new QTLs in pigeonpea across diverse genetic backgrounds brightens the prospects for marker-assisted selection to improve yield gains in pigeonpea.
Project description:Rapeseed (Brassica napus L.) is an important oilseed crop. Despite a short period of domestication and breeding, rapeseed has formed three diverse ecotype groups, namely spring, winter, and semi-winter. However, the genetic changes among the three ecotype groups have remained largely unknown. To detect selective signals, a set of 327 accessions from a worldwide collection were genotyped using a Brassica array, producing 33 186 high-quality single nucleotide polymorphisms (SNPs). Linkage disequilibrium (LD) was unevenly distributed across the genome. A total of 705 (78.2%) weak LD regions were found in the A subgenome, whereas 445 (72.6%) strong LD regions were in the C subgenome. By calculating the nucleotide diversity and population differentiation indices, a total of 198 selective sweeps were identified across ecotype groups, spanning 5.91% (37.9 Mb) of the genome. Within these genome regions, a few known functional genes or loci were found to be in association with environmental adaptability and yield-related traits. In particular, all 12 SNPs detected in significant association with flowering time among accessions were in the selection regions between ecotype groups. These findings provide new insights into the structure of the B. napus genome and uncover the footprints of domestication and breeding.
Project description:A stable yellow-seeded variety is the breeding goal for obtaining the ideal rapeseed (Brassica napus L.) plant, and the amount of acid detergent lignin (ADL) in the seeds and the hull content (HC) are often used as yellow-seeded rapeseed screening indices. In this study, a genome-wide association analysis of 520 accessions was performed using the Q + K model with a total of 31,839 single-nucleotide polymorphism (SNP) sites. As a result, three significant associations on the B. napus chromosomes A05, A09, and C05 were detected for seed ADL content. The peak SNPs were within 9.27, 14.22, and 20.86 kb of the key genes BnaA.PAL4, BnaA.CAD2/BnaA.CAD3, and BnaC.CCR1, respectively. Further analyses were performed on the major locus of A05, which was also detected in the seed HC examination. A comparison of our genome-wide association study (GWAS) results and previous linkage mappings revealed a common chromosomal region on A09, which indicates that GWAS can be used as a powerful complementary strategy for dissecting complex traits in B. napus. Genomic selection (GS) utilizing the significant SNP markers based on the GWAS results exhibited increased predictive ability, indicating that the predictive ability of a given model can be substantially improved by using GWAS and GS.