- Joint QTL mapping and transcriptome sequencing analysis reveal candidate flowering time genes in Brassica napus L. - Background: Optimum flowering time is a key agronomic trait in Brassica napus . - To investigate the genetic architecture and genetic regulation of flowering time in this important crop, we conducted quantitative trait loci (QTL) analysis of flowering time in a recombinant inbred line (RIL) population, including lines with extreme differences in flowering time, in six environments, along with RNA-Seq analysis.. - RNA-Seq analysis revealed 105 flowering time-related differentially expressed genes (DEGs) that play roles in the circadian clock/photoperiod, autonomous pathway, and hormone and vernalization pathways. - Conclusions: We identified 45 flowering time-related genes in these QTL regions, eight of which are DEGs, including key flowering time genes PSEUDO RESPONSE REGULATOR 7 ( PRR7 ) and FY (located in a major QTL region on C02). - These findings provide insights into the genetic architecture of flowering time in B. - Thus, flowering time is a vital trait that is a target of selection during crop breeding. - Flowering time is sensitive to various environmental signals (such as day length and temperature) and endogenous signals (e.g., developmental stage and age) [2, 3]. - To date, much is known about candidate genes controlling flowering time in Arabidopsis thaliana. - More than 300 flowering time genes have been identified, and several key regulators. - that function in pathways that control flowering time have been detected [4, 5]. - Six major pathways control flowering time in Arabidopsis: vernalization, the photoperiod/circadian clock, and the ambient temperature, gibberellin, autonomous, and endogen- ous pathways . - Flowering time in rapeseed not only has a crucial impact on yield, but it also influences. - Quantita- tive trait locus (QTL) analysis and genome-wide associ- ated mapping (GWAS) have been used to identify candidate flowering time genes in oilseed rape. - Many QTLs related to flowering time have been identified in this crop. - For example, one major QTL was identified that explains 50% of the total phenotypic variation for flowering time in B. - This QTL is related to VFN2, a major vernalization-responsive flowering time gene in Arabidopsis [17]. - (2016) identified 22 QTLs (including four major QTLs) for flowering time in B. - GWAS was also recently used to screen for candidate flowering time genes in B. - (2016) identified 41 SNPs associated with flowering time using GWAS of 523 B.. - Therefore, in this study, we performed joint QTL mapping and RNA-Seq analysis to uncover the genetic architecture of flowering time in B. - The flowering time trait was evaluated in six environ- ments (the temperature data in each environment was shown in Additional file 1: Table S1), including Giessen (E8.76/N50.56), Germany in 2009 (09Gi) and Beibei (E106.26/N29.82), Chongqing, China in Cq, 13Cq, 14Cq, 15Cq, and 16Cq, respectively). - Flowering time data were recorded for each line from the sowing day to the day when 50% of the plants showed the first blooming floret.. - Windows QTL Cartographer version 2.5 with default settings was used to detect QTLs for flowering time via the composite interval mapping method [26]. - Five early-flowering lines (marked “E”) and five late-flowering lines (marked “L”) were selected from the RIL population based on the flowering time in six envi- ronments. - napus homologs of flowering time-related genes. - To discover flowering time genes in B. - napus, 306 flowering-time related (FTR) genes in A. - Analysis of flowering time in six environments. - We analyzed flowering time traits in a population of 172 RILs. - The flowering time values of the two parental lines, as well as the mean, maximum, and minimum values of the RIL population for flowering time in six environments, were summarized in Table 1. - The trans- gressive segregation of flowering time traits in all six en- vironments was shown in Fig. - Our results indicate that flowering time is positively and significantly correlated among the six environments (r P <. - Mapping of QTLs for flowering time in six environments We detected 27 QTLs distributed on eight chromosomes in the six environments, with 5.2–25.1% phenotypic vari- ation (PV) and additive effects ranging from − 2.83 to 3.64 (Table 3). - To identify important genes responsible for flowering time variation, we selected 5498 and 3671 significant DEGs based on the criteria |log 2 (FPKM early /FPKM late. - In the current study, we identified 78 genes. - 1 Frequency distribution of the flowering time trait in RILs grown in six different environments. - Table 1 Phenotypic variation in flowering time in the RILs and their parents. - 3 Locations of significant QTLs for flowering time on a high-density SNP map. - 2 Graphs of QTLs for flowering time in an RIL population throughout the genome in plants grown in six different environments. - regulate flowering time [1]. - Table 2 Significant QTLs associated with flowering time in the RIL population. - Functional classification of common DEGs involved in flowering time pathways. - Expression analysis of homologous genes influencing flowering time in Arabidopsis. - We identified 1172 homologs of FTR genes in the B.. - early- and late-flowering bulks in leaf and shoot tissues: b Venn diagram of the number of genes detected in the four samples. - e Fold changes in the expression of DEGs detected between early- and late-flowering bulks in leaf and shoot tissues, respectively. - To identify DEGs related to the flowering pathway, we screened DEGs between two bulks with extreme differ- ences in flowering time among these putative FTR genes. - In total, 105 flowering time genes were identified as DEGs using the criteria: |log2 fold change| >. - Screening for candidate flowering time genes by integrating QTL mapping and RNA sequencing data As mentioned above, we detected 3436 genes in QTL regions and determined their expression levels via RNA-Seq (Additional file 8: Table S8). - Of these, seven flowering time-related genes were also detected (Table 5).. - Like many other important traits, flowering time is con- ditioned by the interaction of genes, endogenous signals, and environmental factors [2, 5]. - In the present study, we investigated the variation in flowering time among an RIL population in six environments and in leaf and shoot tissues from early- and late-flowering lines via RNA-Seq analysis.. - Flowering time QTLs located on chromosome A02, A03, A10, C02, and C03 were previously identified in B. - In the current study, flowering time QTLs were. - Finally, two QTLs located on A06 were detected in three environ- ments, and 33 flowering time genes (e.g., CO, PRR9, and AGL31, Fig. - Differential expression of FTR genes regulates flowering time in two contrasting bulks of RILs. - In the present study, we detected important genes in- volved in flowering time and explored the mechanisms that regulate the flowering pathway in oilseed rape using RNA-Seq technology. - We subjected leaf and shoot tissues from early- and late-flowering time lines at the vegetative stage to RNA-Seq analysis. - These three genes are positive regu- lators in the autonomous pathway, suggesting that this pathway may be partially responsible for the differences in flowering time between the two types of plants.. - Candidate genes involved in flowering time through four major pathways. - Genes in the circadian clock/. - We propose that the circa- dian clock/photoperiod pathway is closely associated with the differences in flowering time between two con- trasting bulks of RILs. - Like the circadian clock/photoperiod pathway, the ex- pression of autonomous pathway-associated genes corre- sponded with the differences in flowering time between two contrasting bulks of RILs. - Interestingly, the Arabidopsis ga2ox1 single mutant does not display an altered flowering-time phenotype, but a quintuple ga2ox mutant, ga2ox1;2;3;4;6, flowers early under both short-day (SD) and long-day (LD) conditions [55].. - In detail, VRN1 and VIN3, encod- ing positive regulators of flowering time in the vernalization pathway, were upregulated in shoot tissues and leaves, respectively. - These results suggest that the vernalization path- way may not be the main factor influencing the variation in flowering time investigated in our study.. - Together, our RNA-Seq analysis identified candidate genes involved in flowering time variance in B. - As mentioned above, we identified 3436 genes in QTL regions, including 45 flowering time genes. - Overexpression of FY in fy complements the mu- tant phenotype, leading to a normal flowering-time phenotype . - PRR7, a transcriptional repressor of CCA1 and LHY, is involved in both positive and negative feedback loops of the circadian clock, thereby influencing flowering time [66].. - napus leaves in the current study. - Together, these findings highlight the complexity of the regulatory mechanisms controlling flowering time in rapeseed.. - RNA-Seq analysis revealed 105 flowering time-related differentially expressed genes (DEGs) that play roles in the circadian clock/photo- period, autonomous pathway, and hormone and vernalization pathways. - We identified 45 flowering time-related genes in these QTL regions, eight of which are DEGs,. - including key flowering time genes PSEUDO RESPONSE REGULATOR 7 (PRR7) and FY (located in a major QTL region on C02). - Flowering time-related (FTR) genes in B.. - thaliana flowering time genes as queries. - FCA: FLOWERING TIME CONTROL PROTEIN. - FTR: Flowering-time related. - Regulation of flowering time: all roads lead to Rome.. - Transcriptional mechanism of Jasmonate receptor COI1-mediated delay of flowering time in Arabidopsis. - FLOR-ID: an interactive database of flowering-time gene networks in Arabidopsis thaliana. - It's time to flower: the genetic control of flowering time. - Genome wide analysis of flowering time trait in multiple environments via High-throughput genotyping technique in Brassica napus L. - Comparison of flowering time genes in Brassica rapa, B-napus and Arabidopsis thaliana. - Genetic and physical mapping of flowering time loci in canola ( Brassica napus L. - Xu LP, Hu KN, Zhang ZQ, Guan CY, Chen S, Hua W, Li JN, Wen J, Yi B, Shen JX et al: Genome-wide association study reveals the genetic architecture of flowering time in rapeseed ( Brassica napus L. - Genome-wide association analyses reveal complex genetic architecture underlying natural variation for flowering time in canola. - A naturally occurring splicing site mutation in the Brassica rapa FLC1 gene is associated with variation in flowering time. - Mapping and characterization of FLC homologs and QTL analysis of flowering time in Brassica oleracea. - Flowering time regulation in crops - what did we learn from Arabidopsis? Curr Opin Biotech. - Characterization and effects of the replicated flowering time gene FLC in Brassica rapa. - Flowering time quantitative trait loci analysis of oilseed Brassica in multiple environments and genomewide alignment with Arabidopsis.. - Flowering time gene variation in Brassica species shows evolutionary principles. - The autonomous pathway: epigenetic and post-transcriptional gene regulation in the control of Arabidopsis flowering time. - Divergent roles of a pair of homologous jumonji/zinc-finger- class transcription factor proteins in the regulation of Arabidopsis flowering time. - A physiological overview of the genetics of flowering time control. - Arabidopsis clock-associated pseudo-response regulators PRR9, PRR7 and PRR5 coordinately and positively regulate flowering time through the canonical CONSTANS-dependent photoperiodic pathway. - Multiple bHLH proteins form heterodimers to mediate CRY2-dependent regulation of flowering-time in Arabidopsis
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