ORIGINAL RESEARCH article

Front. Plant Sci., 20 September 2019

Sec. Plant Breeding

Volume 10 - 2019 | https://doi.org/10.3389/fpls.2019.01152

Integration of QTL Mapping and Gene Fishing Techniques to Dissect the Multi-Main Stem Trait in Rapeseed (Brassica napus L.)

  • 1. Department of Biotechnology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China

  • 2. Hybrid Rape Research Center of Shaanxi Province, Shaanxi Rapeseed Branch of National Centre for Oil Crops Genetic Improvement, Yangling, China

Article metrics

View details

12

Citations

4,5k

Views

2,8k

Downloads

Abstract

Rapeseed is one of the most important oilseed crops in the world. Improving the production of rapeseed is beneficial to relieve the shortage of edible vegetable oil. As the organ of support and transport, the main stem of rapeseed controls the plant architecture, transports the water and nutrients, and determines the number of inflorescence. Increasing the number of main stems would be helpful for the yield improvement in Brassica napus (B. napus). This attractive multi-main stem (MMS) trait was observed in the KN DH population. We investigated not only the frequency of MMS traits but also dissected the genetic basis with QTL mapping analysis and Gene-Fishing technique. A total of 43 QTLs were identified for MMS based on high-density linkage map, which explained 2.95–14.9% of the phenotypic variation, among which two environmental stable QTLs (cqMMS.A3-2 and cqMMS.C3-5) were identified in winter and semi-winter environments. Epistatic interaction analysis indicated cqMMS.C3-5 was an important loci for MMS. According to the functional annotation, 159 candidate genes within QTL confidence intervals, corresponding to 148 Arabidopsis thaliana (A. thaliana) homologous genes, were identified, which regulated lateral bud development and tiller of stem, such as shoot meristemless (STM), WUSCHEL-regulated-related genes, cytokinin response factors (CRF5), cytokinin oxidase (CKX4), gibberellin-regulated (RDK1), auxin-regulated gene (ARL, IAR4), and auxin-mediated signaling gene (STV1). Based on Gene-Fishing analysis between the natural plants and the double-main stem (DMS) plant, 31 differentially expressed genes (DEGs) were also obtained, which were related to differentiation and formation of lateral buds, biotic stimulus, defense response, drought and salt-stress responses, as well as cold-response functional genes. In addition, by combining the candidate genes in QTL regions with the DEGs that were obtained by Gene-Fishing technique, six common candidate genes (RPT2A, HLR, CRK, LRR-RLK, AGL79, and TCTP) were identified, which might probably be related to the formation of MMS phenotype. The present results not only would give a new insight into the genetic basis underlying the regulation of MMS but also would provide clues for plant architecture breeding in rapeseed.

Introduction

Plant architecture is a significant agronomic trait that indirectly influence the seed yield by affecting the formation of photosynthetic product and storage of grain-filling substance. Notably, the first “Green Revolution” was one of the great successes, which had improved plant architecture, especially in significant reduction plant height and an increase of the overall seed yield and harvest index (Khush, 2001). Seed yield per unit area is closely related to many plant architecture elements, including yield component, plant height, tiller number, intersection angle of tiller, and leaf shape. Especially in rice and wheat, the increase of the effective tiller number could improve their seed yield per plant and thus increase the overall yield. Some studies that are focused on the mechanism of plant architecture formation have been reported in rice, Arabidopsis thaliana (A. thaliana) and tomato (Leibfried et al., 2005; Jiang et al., 2013; Zhou et al., 2016). Therefore, improving the plant architecture of crops could effectively increase the crop yield.

Rapeseed (Brassica napus, AACC genome, 2n = 38) originated from a spontaneous hybridization between Brassica rapa (AA, 2n = 20) and Brassica oleracea (CC, 2n = 18) (Nagaharu, 1935). Rapeseed is cultivated throughout the world for the production of vegetable oil, animal feed, and biodiesel. At present, the proportion of rapeseed oil in the total oil production of crop is as high as 57.2% in China (Xie et al., 2005; Yin et al., 2010); in the meanwhile, 60% of edible oil have to be imported from abroad (Wang and Yin, 2014). Seed yield of rapeseed is directly determined by yield-component traits, including seed number per silique, seed weight, and the number of effective siliques per plant (Qzer et al., 1999; Quarrie et al., 2006). Several indirectly related traits, including plant height, the number of the first effective branch, and the silique number of main inflorescence, were also important contributions. The genetic basis of the seed yield components and seed yield–related traits have been dissected by quantitative trait loci (QTL) mapping (Chen et al., 2007; Ding et al., 2012; Zhao et al., 2016) and genome-wide association studies (GWAS) (Liu et al., 2016; Lu et al., 2016).

In recent years, the new agronomic traits, multi-main stem trait (MMS, including double-main stems, three main stems, and over three main stems), have been discovered in rapeseed. MMS is an important seed yield–related trait, which was differentiated from shoot meristem. The plants with MMS have many advantages, such as multiple main stems (or tiller number), higher growth potential, fewer branches, and more seed number, which play an important role for increasing seed yield in rice and wheat (Lu et al., 2015; Shao et al., 2019; Hu et al., 2017). Favorable main stem number can also increase planting density, which contributes to a higher yield per unit area. In the process of differentiation, the morphological structure, physiological status, and endogenous hormonal content of the shoot apical meristem (SAM) undergo substantial change (Gordon et al., 2009). The SAM must maintain a balance between stem cell niches updating and peripheral organ initiation in order to fulfill this function. The genes that cause MMS might have a relationship with WUSCHEL (WUS) and CLAVATA (CLV) (Brand et al., 2002; Müller et al., 2006). In normal condition, the gene WUS is always expressed in a small group of cells in the organization center of the SAM, underneath the three outer cell layers (Weigel and Jürgens, 2002; Williams and Fletcher, 2005). Cells in center zone proliferate to form two kinds of cells (Haecker and Laux, 2001): one is progeny of stem cell holding multipotency, which maintain the structure of center zone, and the other is a daughter cell, who will develop into perimeter zone and then differentiate into various organizations. Only when the two progresses develop at the same pace, SAM will develop into normal structure; otherwise, the SAM will abnormally develop (Wang and Li, 2008). During development process of SAM, WUS functions in maintaining the stem cells undifferentiated to keep natural structure and function of SAM (Schoof et al., 2000). Loss of function of WUS would lead to a large amount of stem cells developed into perimeter zone, and then giving rise to the leaf primordiums and secondary SAMs that will come into being (Wang and Li, 2008). Another important gene in SAM is CLV that can promote stem cells to develop into perimeter zone. A WUS-CLV feedback loop in plant exists, which is of great importance to maintain normal structure of SAM. CLV3 encodes a kind of secreted protein to activate CLV1/CLV2 complex when the number of stem cells in SAM increase. When WUS is inhibited, the number of stem cells will decrease which in turn restrains the expression of CLV3 (Fletcher and Meyerowitz, 2000; Dodsworth, 2009). Based on the previous reports, the maintenance homeostasis of SAM mainly includes WUS-CLV feedback loop (Fletche, 2018), phytohormone (Brand et al., 2000), redox regulation (Schippers et al., 2016), and network consisting of various genes.

QTL mapping has been proved to be an important approach for dissecting complex traits (Paran and Zamir, 2003). Many agricultural traits, for example, seed yield (Zhao et al., 2016), seed yield–related traits (Shi et al., 2009; Zhao et al., 2016), oil content (Wang et al., 2013), and fatty acid composition (Jiang et al., 2014; Bao et al., 2018), have been dissected by QTL mapping. In addition, some important genes that regulated agricultural traits of rapeseed were identified by fine mapping and map-based cloning, such as recessive genic male serility BNAMS1 (Yi et al., 2006), seed weight TSWA5a and TSWA5c (Fan et al., 2010), and seed number per silique BnaC9.SMG7b (Li et al., 2015), etc. Gene-Fishing technology, based on PCR technology, could identify the differentially expressed genes quickly (Kim et al., 2004). For example, Choi et al. (2008) found 31 differentially expressed fragments in the grapevines inoculated with Rhizobium and salicylic acid by using Gene-Fishing (Choi et al., 2008). Junaedi et al. (2007) explored the effects of high allelopathic rice varieties on barnyard grass and discovered nine differentially expressed fragments (Junaedi et al., 2007). Park et al. (2006) screened the related genes that regulated seed epidermal needling of carrot, and 11 differentially expressed fragments were identified (Park et al., 2006). In addition, some other genes, including HIP1, CSH1, PPTSPO1, and SLFN-2, were also identified by Gene-Fishing technique (Cho et al., 2006; Bradley et al., 2007; Frank et al., 2007; Sohn et al., 2007).

In the present study, the MMS characteristics were investigated in a doubled-haploid population named as KN DH population. We counted the number of multi-main stem in each DH line in Yangling and Wuhan for two successive years. Based on QTL mapping and Gene-Fishing technique, the purposes of the present study focused on two aspects: (1) identify QTLs for MMS and obtain candidate genes within QTL regions (2) based on differentially expressed genes and candidate gene within QTL regions and identify several common candidate genes that regulated the MMS.

Materials and Methods

Plant Materials and Field Experimental Design in Two Different Ecological Regions

The KN doubled-haploid (DH) population were derived from bi-parental segregating populations by microspore culture (Figure 1) (Wang et al., 2013). The KN population and its parents were sown in the middle of September in the experimental field of Hybrid Rape Research Center of Shaanxi Province, Yangling of Shaanxi province (YL) in northwest China (34°16’N, 108°5’E), and in the early October in the experimental field of Huazhong Agriculture University, Wuhan of Hubei province (WH) in central China (30°47’N, 114°35’E), for two consecutive years from the years 2014 to 2015, respectively. Yangling belonged to the winter ecological region, and Wuhan belonged to the semi-winter ecological region. The KN population and their two parents were planted in Yangling and Wuhan with two replications, respectively. Meanwhile, each particular combination of experimental year × location was defined as an independent experiment. Each independent experiment consisted of 348 DH lines. Each line was grown in a two-row plot with 40 cm between rows and 20 cm between individuals, and row length of 250 cm in all independent experiments. The field experiments followed a randomized complete block design and the normal agricultural practice.

Figure 1

Figure 1

The phenotype of the multi-main stem and their parents in KN population. The parents of KN population include the male parent KenC-8 and the female parent N53-2. The double-main stem and three main stems are located in the KN population.

Phenotypic Statistics and Analysis of MMS

The total number of each line corresponding to the number of plant with MMS in each line was investigated, and the ratio of the MMS was calculated in Yangling of Shaanxi province and Wuhan of Hubei province for two consecutive years. The ratio of the MMS was calculated as the ratio of the number of the MMS to the total number of each line. Not all of the DH lines had MMS in the KN population. In addition, the variance analysis and broad-sense heritability (h2) was calculated by using SAS 8 (SAS Institute Inc, 2000). The formula was h2 = б2g/(б2g + б2ge/n+ б2e/nr) × 100%, б2g is the variance among DH lines, б2ge is the interaction variance of the genotype with environment, б2e is the error variance, n is the number of environments, and r is the number of replications. Meanwhile, a DH lines with double-main stem (DMS) in KN DH population were selected for germination and morphological observation. The early morphology was observed in the five growth stages of seedling stage (15, 25, 30, 35, and 50 days). The seedlings for early morphological observation of the DMS materials and their natural plant type were grown in the culture chamber with 16 h light per day at 22°C ± 4°C.

QTL Mapping and Identification of Candidate Genes

The ratio of MMS in the KN population was collected as phenotype and used for QTL mapping. A high-density genetic linkage map of the KN population with 3,207 markers, including single-nucleotide polymorphism (SNP), SSR (simple sequence repeat), STS (sequence-tagged site), SRAP (sequence-related amplified polymorphism), and IFLP (intron fragment length polymorphism) markers, was constructed. The total length reached 3072.7 cM, and the average distance was only 0.96 cM between adjacent markers (Chao et al., 2017). Combining the ratio data of MMS with the high-density linkage map of KN population, QTL detection for MMS was performed using a composite interval mapping (CIM) with Windows QTL Cartographer 2.5 software (Wang et al., 2007). The scan walking speed was 1 cM; the window size was 10 cM with five background cofactors. According to the 1,000-permutation test corresponding to P = 0.05, the LOD value 2.0 was used as threshold for detection of significant QTLs. All detected QTLs were denoted as significant identified QTLs (Burns et al., 2003). The method for QTL nomenclature was as described by Wang et al. (2013). QTL integration was by meta-analysis using BioMercator 4.1 (Arcade et al., 2004). One QTL that was detected in at least two environments was taken to be a stable QTL, otherwise a specific QTL.

The alignment of the genetic map to the physical map and the identification of candidate genes were the same as those described by Chao et al. (2017). According to the collinearity of the high-density genetic map and B. napusDarmor-bzh” reference genome (Chalhoub et al., 2014), genome regions corresponding to the QTL confidence intervals (CIs) were identified by using closely linked SNP within QTL CIs. The candidate genes within QTL CIs were regarded as candidate genes (Shi et al., 2015). The orthologs of A. thaliana involving SAM were gathered from previous reported (Wang and Li, 2008). The orthologous of candidate genes and their annotation were obtained by BLASTn based on A. thaliana database (http://www.arabidopsis.org/).

Additive × Additive Epistatic Interactions for MMS

To estimate the epistasis interaction of MMS, we used inclusive ICIM method with IciMapping software to analyze epistatic loci pairs (Li et al., 2008; Meng et al., 2015). To identify significant epistasis interaction loci, a walking speed was set to 1 cM, and significant LOD threshold was set at the same as default parameter of 5.0. The epistasis interaction loci were defined by abbreviation “Ep” of epistasis and trait name and chromosome number as well as location on chromosome (e.g., EpMMS.A8-115).

Acquisition of Differential Expression Genes Based on Gene-Fishing™ Technology

Differential expression genes (DEGs) were identified by using Gene-Fishing DEG Premix Kits (Seegene, Seoul, South Korea), with an annealing control primer (ACP)–based PCR method (Kim et al., 2004). The total RNA of the DMSs was extracted and then reversed transcription for cDNA by using ReverTra Ace-a-(code no. FSK-100, TOYOBO). According to Gene-Fishing PCR liquid system (20µl total volume system included cDNA 5µl, arbitrary ACP [5 µM] 2µl, dT-ACP2 [10 µM] 1µl, distilled water 2µl, 2×SeeAmpACPMaster Mix 10µl). The amplified PCR products were separated by 2% agarose gels electrophoresis with ethidium bromide, and differential expression fragments were discriminated. Differential expression fragments were isolated by using AxyPrep DNA Gel Extraction Kit (TIANGEN) and connected to a pMD 18-T Simple Vector (TaKaRa) and were sequenced. Sequencing data were confirmed with the GenBank database through the BlastX program of NCBI (http://www.ncbi.nlm.nih.gov/BLAST/) and/or the A. thaliana and B. napus database. Then, the sequence differences of genes were compared in natural plant and the DMS plant.

Quantitative Real-Time PCR (qPCR) Analysis of Six Potential Candidate Genes Regulating MMS

In order to investigate the potential candidate genes regulating MMS, several common candidate genes were selected for quantitative real-time PCR analysis. The shoot meristem of the natural plant and DMS plant in 5, 10, 15, and 20 days after germination was collected and used for relative expression analysis. The total RNA extraction and reversed transcription were the same as above method. Gene-specific primers were designed by using Primer 5.0, and the primers of the six target genes and reference gene actin were listed in Table S1. The RT-PCR reaction system was performed with three technical replicates by using TOYOBO SYBR® R Green Realtime PCR Master Mix (code no. QPK-201) Kit. The amplification program was as follow: 95°C for 10 min, then 40 cycles with 95°C for 15s, 60°C for 15 s, and 72°C for 30 s, the last 60 to 95°C to do the melting curve.

Results

Phenotype Investigation of KN DH Population and Performance of Multiple Main Stem

We investigated the plant with MMS for each line in the KN DH population for two consecutive years from the years 2014 to 2015 in Wuhan and Yangling. According to investigations in the years 2014 and 2015, 45 and 76 DH lines showed MMS phenotype in Yangling; however, only 25 and 29 DH lines showed MMS phenotype in Wuhan (Figure 2, Table 1). Only three lines (QT22, QT229, and QT236) of the 348 lines were found with MMS in all four environments. According to the number of plant with MMS and the total number of each line, the ratio of the MMS occurrence was calculated, the highest ratio of MMS was 100% in Yangling in the years 2014 and 2015, and in Wuhan in the year 2015, the lowest ratio was 20.1% in the year 2015 in Yangling (Table 1). In addition, 7.18–21.84% of plants in KN population had the phenotypes of MMS (from two to three main stems), with more leaves in comparison to their parents (Figure 1, Table 1). Furthermore, broad-sense heritability (h2) was also calculated for MMS (Table S2). MMS had an h2 value 62.26% in Yangling, and an h2 value of 70.23% in Wuhan; these results indicated that the MMS had greater sensitivity and plasticity and was easily influenced by environmental condition.

Figure 2

Figure 2

The number of multi-main stem in in different plant environments. (A) represents the number of multi-main stem in 2014 in Yangling of Shaanxi province. (B) represents the number of multi-main stem in 2015 in Yangling of Shaanxi province. (C) represents the number of multi-main stem in 2014 in Wuhan of Hubei province. (D) represented the number of multi-main stem in 2015 in Wuhan of Hubei province.

Table 1

Year/location14 Yangling15 Yangling14 Wuhan15 Wuhan
Mean 47.87%41.88%42.41%47.26%
Min21.70%20.10%20.50%22.20%
Max100.00%100.00%94.30%100.00%
MMS lines45762529
Total lines348348348348
MMS ratio12.93%21.84%7.18%8.33%
h262.26%70.23%

The multi-main stem phenotypic ratio of KN DH population in Yangling and Wuhan.

MMS, multiple main stem; 14 Yangling and 15 Yangling represent the years 2014 and 2015 in Yangling of Shaanxi province, respectively; 14 Wuhan and 15 Wuhan represent the years 2014 and 2015 in Wuhan of Hubei province; h2, broad-sense heritability.

Moreover, the plant with DMS and the natural normal plants from QT22 were used for germination and morphological development observation in 15, 25, 30, 35, and 50 days of different seedling stages (Figure 3). It was revealed that from germination to 25 days, no obvious differences were observed between the DMS plant and the normal plant, and DMS was first observed in 30 days. The stem base of the DMS plant hypertrophied gradually and had formed two main terminal buds. In 35 days, the DMS plant had formed two stems and could be obviously observed. In 50 days, the two main stems of DMS plants developed simultaneously and formed a plant type of DMS. These results indicated that the genes regulating the formation of the DMS function was in early developmental stages. The DMS plants had also grown more leaves and fewer branches compared to the natural plant (Figure 1, Figure 3E2).

Figure 3

Figure 3

Formation and development of the double-main stem in four seedling stages. (A1, B1, C1, D1, and E1) on the left represent the natural plant, and (A1, B1, C1, D1, and E1) on the right represent the double-main stem plant in 15, 25, 30, 35, and 50 days of seedling stages. (A2, B2, C2, D2, and E2) on the left show enlarge image of the natural plant, and (A2, B2, C2, D2, and E2) on the right show magnification of (A1, B1, C1, D1, and E1).

QTL Mapping for MMS in the KN Population and Candidate Genes Identification

The MMS ratio in Yangling and Wuhan of the years 2014 and 2015 was used for QTL identification. Totally, 43 identified QTLs for MMS were detected in the KN DH population, which were located on 14 chromosomes, except for A02, A09, C02, C04, and C08 (Figure 4, Table 2, Figure S2-1, Figure S2-2). It was revealed that q14WH7-2, q14WH15-1, and q15WH13-2 could explain the phenotypic variation more than 10%, which reached 11.38, 11.42, and 14.9%, respectively. Otherwise, QTL q14WH10-1 and q14WH10-2 were with the smallest phenotypic variation of 2.95%. In addition, the additive effects of QTLs were from −0.14 to 0.09, and the average CI was 4.77 cM (Table 2). QTLs for MMS with overlapping CIs were integrated into consensus QTLs by using BioMercator 4.2 software. Forty-three identified QTLs were integrated into 41 consensus QTLs, of which 39 consensus QTLs that were only expressed in Yangling or Wuhan, were considered as environmental specific QTLs (Table 2, Figure 4, Figure 5). The remaining two consensus QTLs (cqMMS.A3-2 and cqMMS.C3-5) were repeatedly detected in two successive years in Yangling and Wuhan (Table 2, Figure 5), respectively, which were considered to be environmental stable QTLs. These results indicated that the majority of consensus QTLs for MMS were expressed in a specific environment, and MMS was greatly affected by environmental conditions. Regretfully, no major QTL for MMS was identified in all environments.

Figure 4

Figure 4

Distribution of QTLs for multi-main stem on the KN high-density map. The 41 consensus QTLs for MMS are distributed on 14 linkage groups with the exception of A02, A09, C02, C04, and C08. : Red solid dot, QTL peak position. Blue bar length, QTL confidence interval.

Table 2

Consensus QTLChrPeak (cM)CIs (cM)Range (cM)Identified QTLLODPV (%)AE
cqMMS.A1-1A0136.2133.20–38.004.80q15YL1-12.884.990.06YL
cqMMS.A1-2A0162.9162.20–63.501.30q15YL1-22.389.180.08YL
cqMMS.A1-3A0174.0169.50–78.408.90q14YL12.126.310.07YL
cqMMS.A3-1A03128.61 128.00–132.302.20q15YL3-13.666.05−0.04YL
cqMMS.A3-2A03141.91137.70–143.105.40 q15YL3-22.934.88−0.04YL
q15WH32.825.02−0.04WH
cqMMS.A4-1A0434.6133.10–35.502.40q14YL4-13.725.970.06YL
cqMMS.A4-2A0442.4139.20–46.407.20q14YL4-23.345.480.05YL
cqMMS.A5-1A0544.7141.00–45.204.20q14YL5-13.028.890.09YL
cqMMS.A5-2A0553.3151.50–54.603.10q14YL5-22.577.820.09YL
cqMMS.A6-1A0646.2145.50–46.701.20q14YL6-12.924.750.04YL
cqMMS.A6-2A0649.8148.90–50.01.70q15YL62.524.130.04YL
cqMMS.A6-3A0652.3151.20–53.001.80q14YL6-23.245.200.05YL
cqMMS.A7-1A0719.6117.60–20.603.00q14WH7-12.857.99−0.07WH
cqMMS.A7-2A0725.8124.80–26.301.50q14WH7-24.1311.38−0.09WH
cqMMS.A7-3A07106.91104.80–108.303.50q15WH72.455.90−0.06WH
cqMMS.A8-1A0840.5138.60–43.404.80q14YL8-12.734.41−0.04YL
cqMMS.A8-2A0849.0143.40–54.0010.60q14YL8-23.425.49−0.05YL
cqMMS.A8-3A0859.0154.00–62.208.20q14YL8-33.056.88−0.05YL
cqMMS.A10-1A109.317.50–9.702.20q14WH10-12.862.950.03WH
cqMMS.A10-2A1012.5112.2–12.900.70q14WH10-22.882.950.03WH
cqMMS.C1C0185.7182.70–90.107.40q14YL112.537.39−0.08YL
cqMMS.C3-1C034.214.00–5.901.90q14YL13-13.129.18−0.09YL
cqMMS.C3-2C0314.7114.30–16.201.90q14YL13-23.038.92−0.09YL
cqMMS.C3-3C0347.9144.30–49.705.40q15WH13-12.387.320.09WH
cqMMS.C3-4C0362.5161.00–64.103.10q15YL132.824.68−0.04YL
cqMMS.C3-5C0365.3164.20–66.302.10q14YL13-32.206.35−0.07YL
q15WH13-25.1714.90−0.14WH
cqMMS.C3-6C0369.6169.20–69.800.60q15WH13-32.537.66−0.10WH
cqMMS.C5-1C055.710.00–13.2013.20q14WH15-13.8611.420.09WH
cqMMS.C5-2C05115.01114.10–115.401.30q15WH15-13.288.860.07WH
cqMMS.C5-3C05122.21119.70–123.804.10q15WH15-22.226.110.06WH
cqMMS.C5-4C05136.01124.00–143.3019.30q15WH15-33.037.310.04WH
cqMMS.C5-5C05143.91143.30–154.3011.00q15WH15-42.764.930.03WH
cqMMS.C5-6C05164.11162.60–165.603.00q14WH15-22.526.850.07WH
cqMMS.C6-1C0653.1151.60–54.402.80q14WH16-12.296.27−0.07WH
cqMMS.C6-2C0660.3160.10–60.800.70q14WH16-22.155.85−0.07WH
cqMMS.C7-1C0734.9134.40–37.603.20q15WH17-13.085.56−0.03WH
cqMMS.C7-2C0754.4152.40–54.702.30q15WH17-23.115.60−0.03WH
cqMMS.C7-3C0787.7187.50–94.406.90q14WH174.0711.17−0.09WH
cqMMS.C9-1C0970.8165.80–72.807.00q15WH19-13.309.19−0.08WH
cqMMS.C9-2C0976.6172.80–84.0011.20q15WH19-23.9710.91−0.08WH
cqMMS.C9-3C0990.5184.00–92.508.50q15WH19-33.4210.29−0.08WH

Information of QTLs for multi-main stem in the KN population.

Chr, chromosome; CIs, confidence interval; LOD, log odds score; PV, phenotypic variation; A, additive effect; E, environment; YL, Shaanxi Yali; WH, Hubei Wuhan.

Figure 5

Figure 5

Environmental stable QTL and environmental specific QTL on A03, A07, and A08 chromosomes. In the left, orange QTL cqMMSa3-2 represents environmental stable QTL in Wuhan and Yangling. Middle green and red QTLs represent specific QTL in Wuhan. Right yellow QTLs represent specific QTL in Yangling.

According to the co-linearity relationship between the KN high-density genetic map and the B. napus reference genome (Chalhoub et al., 2014), 159 genes corresponding to 148 A. thaliana homologous genes within CIs of QTLs were identified; these genes were mainly involved in lateral bud development and tiller of stem (Table 3, Table S3). Both BnaC09g13580D (STM) and BnaC09g34650D (WOX2) were located in QTL region of cqMMS.C9-1, in which BnaC09g13580D participated in stem cell population maintenance (Müller et al., 2006) and cytokinin biosynthetic process (Yanai et al., 2005), and BnaC09g34650D belonged to homeobox genes family and mainly regulated the formation and maintenance of SAM (Clark et al., 1996; Laux et al., 1996). BnaA01g28990D (CUC1) was located in QTL region of cqMMS.A1-3, and it maintains boundaries between the SAM and lateral organ primordia (Aida et al., 1999), which was transcriptionally activated by gene STM (Spinelli et al., 2011). BnaA01g28990D and BnaC09g13580D (STM) are critical genes in lateral organ differentiation (Aida et al., 1999), of which STM promotes cell division by suppressing organ differentiation, and downregulation of STM is beneficial to the initiation of lateral organs (Heisler et al., 2005). BnaA03g50360D (BRS1), BnaA03g54090D (LBD39), and BnaA03g54110D (NPY5) were located in stable QTL region of cqMMS.A3-2 (Figure 5). BRS1 (BRI1 suppressor 1) is a serine carboxypeptidase that is involved in brassinosteroid signaling and was recognized to suppress the phenotypes of the brassinosteroid receptor weak mutant bri1-5 (Deng et al., 2017). NPY5 (naked pins in yuc mutants 5) was highly concentrated in cotyledons and was involved in auxin-mediated organogenesis (Cheng et al., 2008). LBD39 (LOB domain-containing protein 39) was a transcription factor in LOB family and could regulate lateral organ boundaries. BnaA07g02390D (WUS) within QTL region of cqMMS.A7-1 encodes a homeodomain protein and is expressed at the center of plant meristem, which induces cell proliferation of meristem and maintain the state of meristem (Kieffer et al., 2006; Sablowski, 2007). BnaC05g48100D (WOX11) was located in QTL region of qMMS.C5-2, and it was a transcription factor, which combines with WOX6 to control the shoot gravitropism and rice tiller angle by regulating asymmetric distribution of auxin (Zhang et al., 2018). BnaA10g02750D (YUC3) was located in QTL region of qMMS.A10-1, which is an important gene involved in auxin biosynthesis (Zhang et al., 2018; Zwack et al., 2016). Moreover, several related genes for cytokinins and auxins were found within QTL regions. BnaC03g29310D (CRF1) and BnaC03g25680D (CRF5) were located in cqMMS-C3-5 and cqMMS-C3-4 regions, respectively, and BnaC09g21990D (CRF6) were located in qMMS.C9-1 region, which were considered to be cytokinin response factors (Zwack et al., 2016; Striberny et al., 2017). BnaC09g33450D (CKX3) and BnaC09g36710D (CKX7) located in qMMS.C9-1 region, and BnaA03g49660D (CKX4) located in qMMS.A3-1 were considered to be involved in cytokinin catabolic process (Ding et al., 2015; Köllmer et al., 2014; Choi et al., 2014). In addition, BnaA06g14040D (MP) and BnaC05g11390D (EPR1) located in QTL region of qMMS.A6-2 and qMMS.C5-1, respectively, which were considered to be transcription factors and could regulate asymmetric distribution of auxin in upstream of auxin synthesis (Zhang et al., 2018; Krogan et al., 2016).

Table 3

QTL nameGene in B. napusHomologous gene in A. thalianaGene name
cqMMS.A1-1BnaA01g08980DAT1G20200EMB2719
BnaA01g09110DAT4G18370DEG5
BnaA01g09530DAT4G18710BIN2
BnaA01g09700DAT4G18890BEH3
BnaA01g24810DAT4G23180CRK10
cqMMS.A1-2BnaA01g02910DAT4G34220LRR-RLK
BnaA01g25310DAT3G21180ACA9
BnaA01g24690DAT3G22440FLA8
cqMMS.A1-3BnaA01g27090DAT1G48620HON5
BnaA01g28000DAT1G51800
BnaA01g30930DAT3G55200CPSF
BnaA01g28990DAT3G15170CUC1
BnaA01g28930DAT3G15500NAC3
BnaA01g28500DAT3G15790MBD11
BnaA01g28410DAT3G15880WSIP2
BnaA01g26700DAT3G18550BRC1
BnaA01g07860DAT4G29040RPT2A
cqMMS.A3-1BnaA03g31060DAT3G08770ERD10
BnaA03g51000DAT3G57230AGL16
BnaA03g58880DAT4G29040RPT2A
BnaA03g38750DAT2G14900RDK1
BnaA03g51450DAT4G31400CTF7
BnaA03g51900DAT4G32040KNAT5
BnaA03g52120DAT4G32551LUC
BnaA03g52290DAT4G32980ATH1
BnaA03g52520DAT4G33430BAK1
BnaA03g50910DAT4G34160CYCD3
BnaA03g53400DAT4G35550WOX13
BnaA03g53680DAT4G37180UIF1
BnaA03g49660DAT4G29740CKX4
cqMMS.A3-2BnaA03g50360DAT4G30610BRS1
BnaA03g54090DAT4G37540LBD39
BnaA03g54110DAT4G37590NPY5
cqMMS.A4-2BnaA04g18690DAT1G05230HDG2
BnaA04g12130DAT2G21330FBA1
BnaA04g18030DAT2G31085CLE6
BnaA04g18380DAT2G31310LBD14
BnaA04g27450DAT3G62040HAD
cqMMS.A5-1BnaA05g23180DAT3G16640MYB73
BnaA05g07510DAT2G36890RAX2
BnaA05g07510DAT2G36890RAX2
BnaA05g06540DAT2G38120AUX1
BnaA05g06890DAT2G37630AS1
BnaA05g07740DAT3G53020STV1
cqMMS.A5-2BnaA05g04890DAT2G45470FLA8
BnaA05g09820DAT2G33835FES1
BnaA05g09770DAT2G33880HB-3
BnaA05g09360DAT2G34440AGL29
BnaA05g09150DAT2G34650PID
BnaA05g09120DAT2G34710PHB
BnaA05g09060DAT2G34780MEE22
BnaA05g09010DAT2G34870MEE26
BnaA05g08960DAT2G34925CLE42
cqMMS.A6-1BnaA06g24200DAT4G01710CRK
BnaA06g22000DAT1G78700BEH4
BnaA06g22420DAT5G62940HCA2
BnaA06g06160DAT1G10370ERD9
cqMMS.A6-2BnaA06g30630DAT3G60900FLA10
BnaA06g11350DAT1G16880
BnaA06g14040DAT1G19850MP
cqMMS.A6-3BnaA06g13550DAT1G67720
cqMMS.A7-1BnaA07g02390DAT2G17950WUS
cqMMS.A7-2BnaA07g11450DAT1G20450ERD10
BnaA07g11930DAT5G67300MYBR1
BnaA07g27770DAT1G69220SIK1
BnaA07g28930DAT1G70830MLP28
BnaA07g26650DAT1G67720
cqMMS.A8-1BnaA08g14270DAT4G26850VTC2
BnaA08g15890DAT4G37930SHMI
BnaA08g15900DAT4G37940AGL21
BnaA08g16780DAT4G39070BZS1
BnaA08g16820DAT4G38970FBA2
BnaA08g16720DAT4G39110
BnaA08g16520DAT4G39400BRI1
BnaA08g16380DAT4G39650GGT2
BnaA08g16660DAT5G10720HK5
BnaA08g14480DAT5G48820ICK6
cqMMS.A10-1BnaA10g02750DAT1G04610YUC3
BnaA10g12480DAT5G59480HAD
BnaA10g23990DAT5G61410RPE
BnaA10g29350DAT5G57950HLR
cqMMS.C1BnaC01g21630DAT3G51030TRX1
BnaC01g21860DAT4G16280FCA
BnaC01g22100DAT4G16110RR2
BnaC01g22110DAT1G27320HK3
BnaC01g24570DAT3G46510PUB13
BnaC01g26510DAT3G50070CYCD3.3
BnaC01g26840DAT1G54990AXR4
BnaC01g27460DAT5G13010EMB3011
BnaC01g32740DAT3G20190PRK4
BnaC01g33180DAT5G60440AGL62
BnaC01g35230DAT3G16640TCTP
cqMMS.C3-3BnaC03g13380DAT5G56600PRF3
BnaC03g13120DAT5G57090EIR1
cqMMS.C3-4BnaC03g18890DAT1G78380GSTU19
cqMMS.C3-5BnaC03g25680DAT2G46310CRF5
BnaC03g29310DAT4G11140CRF1
BnaC03g26730DAT2G44080ARL
cqMMS.C3-6BnaC03g20740DAT2G38120AUX1
BnaC03g45610DAT2G14900
cqMMS.C5-1BnaC05g07890DAT1G10370ERD9
BnaC05g11390DAT1G18330EPR1
BnaC05g01780DAT1G03170DUF3049
cqMMS.C5-2BnaC05g46270DAT3G05530RPT2A
BnaC05g02370DAT1G04250AXR3
cqMMS.C5-3BnaC05g46030DAT3G05800AtBS1
cqMMS.C5-4BnaC05g45960DAT5G48670AGL80
BnaC05g45360DAT2G31530EMB2289
BnaC05g23630DAT1G30610EMB2279
BnaC05g48100DAT3G03660WOX11
cqMMS.C5-5BnaC05g47460DAT3G04100AGL57
cqMMS.C5-6BnaC05g46680DAT3G05120GID1A
BnaC05g48320DAT3G02310SEP2
cqMMS.C6-1BnaC06g23160DAT1G74260PUR4
BnaC06g35530DAT1G74660MIF1
BnaC06g21810DAT1G76520PILS3
BnaC06g20740DAT1G77690LAX3
BnaC06g19100DAT1G80350ERH3
BnaC06g19420DAT1G80680SAR3
BnaC06g19460DAT1G80730ZFP1
BnaC06g27630DAT2G26670TED4
BnaC06g20020DAT3G16830TPR2
BnaC06g30400DAT1G69220SIK1
BnaC06g34100DAT1G73190TIP3
BnaC06g28810DAT1G67720
BnaC06g16910DAT3G58780SHP1
BnaC06g24760DAT4G26000PEP
cqMMS.C6-2BnaC06g31170DAT1G24180IAR4
BnaC06g29550DAT1G68800TCP12
BnaC06g30690DAT1G69500CYP704B1
BnaC06g31090DAT1G69970CLE26
BnaC06g31830DAT1G70700TIFY7
cqMMS.C7-1BnaC07g15380DAT1G20450ERD10
BnaC07g16030DAT5G67300MYBR1
BnaC07g23630DAT3G26520TIP2
BnaC07g25970DAT3G30260AGL79
BnaC07g30600DAT5G23720PHS1
BnaC07g26970DAT5G24860FPF1
BnaC07g26450DAT5G48380BIR1
cqMMS.C7-3BnaC03g77490DAT4G30620RPT2A
cqMMS.C9-1BnaC09g32510DAT1G33390FAS4
BnaC09g31940DAT1G34355PS1
BnaC09g13580DAT1G62360STM
BnaC09g21990DAT3G61630CRF6
BnaC09g33500DAT5G57950HLR
BnaC09g34990DAT3G51550FER
BnaC09g32160DAT5G16560KAN
BnaC09g35030DAT5G19140AILP1
BnaC09g36930DAT5G20930TSL
BnaC09g36710DAT5G21482CKX7
BnaC09g36350DAT5G22650HD2B
BnaC09g36060DAT5G23000MYB37
BnaC09g30190DAT5G53760MLO11
BnaC09g31160DAT5G54770THI1
BnaC09g32460DAT5G55910D6PK
BnaC09g32470DAT5G55920OLI12
BnaC09g33450DAT5G56970CKX3
BnaC09g32610DAT5G57710SMAX1
BnaC09g34650DAT5G59340WOX2
BnaC09g34750DAT5G59370ACT4

Candidate genes in Brassica napus and homologous genes in Arabidopsis thaliana within QTL regions for MMS.

Additive × Additive Epistatic Interactions for MMS in Different Chromosomes

To estimate the epistasis interaction for MMS, epistatic loci pairs were detected by using IciMapping software. Totally, 26 statistically significant epistatic loci pairs were detected in three plant regions (Figure 6, Table S4), which were located on chromosome A01/A08, A01/C03, A02/C03, A02/A09, A03/A04, A04/A08, etc. which accounted for 1.76–17.70% of the phenotypic variance. Five epistatic interaction pairs, including EpMMS.A3-75/EpMMS.A3-25, EpMMS.A3-120/EpMMS.C2-105, EpMMS.A4-5/EpMMS.A8-115, EpMMS.A9-15/EpMMS.A9-160, and EpMMS.A9-160/EpMMS.C3-65, had positive epistatic effect, indicating that the effects of parents for MMS were larger than their the recombinant effects of epistatic interaction pairs. The remaining epistatic interaction pairs had negative epistatic effects, indicating that the recombinant effects of these epistatic interaction pairs for MMS were larger than their parental effects. Furthermore, we noted that seven epistatic interaction loci were located in the above-mentioned five QTL intervals. EpMMS.A7-105 was located in QTL region of cqMMS.A7-3, indicating that cqMMS.A7-3 also interacted with EpMMS.A7-125. In addition, three epistatic interaction pairs (EpMMS.A2-60/EpMMS.C3-65, EpMMS.C3-65/EpMMS.C3-75, and EpMMS.A9-160/EpMMS.C3-65) were closely related to cqMMS.C3-5, which indicated cqMMS.C3-5 was an important loci for MMS.

Figure 6

Figure 6

Distribution of epistatic interaction for MMS on different chromosomes. Violet lines represent epistatic interaction pairs of MMS; the epistatic interaction pairs were shown by links in the inside circle. The outside circle represents 19 chromosomes of Brassica napus.

Differentially Expressed Genes Between the Natural Plant and the DMS Plant by Gene-Fishing™ Technique

Total RNA of main stem apex of the natural plant and DMS in seedling of 20 days were extracted by using Invitrogen TRIzol Kit. The dT-ACP1 primers from Gene-Fishing technique were used as primers for reverse transcription. In order to identify differentially expressed genes (DEGs) in DMS and the natural plant of B. napus, the PCR amplification of cDNA using 36 random amplified primers was conducted. Totally, 46 differential expression bands were found, including 28 down-regulated and 18 up-regulated in the DMS compared to the natural plant (Figure 7, and a full scan of the entire original gels attached as Figures S1-1–Figure S1-6; Table S5). According to the sequence alignment results, 31 genes were obtained (Table 4). Based on functional annotation, seven underlying genes (DEG1, DEG2, DEG4, DEG5, DEG34, DEG36, and DEG46) were annotated to regulate the apical meristem, which might be related to the formation of DMS phenotypes (Table 4). In addition, some genes that are related to biotic stimulus, defense response, drought, and salt-stress responses, as well as cold-response functional genes were also identified (Table 4).

Figure 7

Figure 7

Differential expressed genes screen using ACPs primers based on Gene-Fishing. The numbers and arrows on image represent different differential expression genes. For better presentation, only cropped images of blots are shown here; a full scan of the entire original gels is submitted in the Supplementary Material (Figures S1-1–S1-6).

Table 4

DEG numberScoreE-valueMax identGene ID in B. napusChromosomeA. thaliana
DEG13723.00E−9999.00%BnaA01g07860DA01AT4G29040
BnaA08g13550DA08
BnaC01g09460DC01
BnaC07g41720DC07
BnaC08g13300DC08
DEG28110.00E+0097.00%BnaA10g29350DA10AT5G57950
BnaC09g33500DC09
DEG34571.00E−12499.00%BnaA01g02490DA01AT4G34670
BnaA03g28830DA03
BnaA03g52970DA03
BnaA08g11040DA08
BnaC01g03750DC01
BnaC01g39890DC01
BnaC03g33960DC03
BnaC03g65890DC03
BnaC05g47000DC05
BnaC07g45170DC07
DEG45554.00E−154100.00%BnaA06g24200DA06AT4G01710
DEG54685.00E−128100.00%BnaA01g02910DA01AT4G34220
BnaC01g04180DC01
DEG67370.00E+0099.00%BnaA07g11450DA07AT1G20450
BnaC05g15780DC05
BnaC07g15380DC07
DEG86970.00E+0099.00%BnaA07g11930DA07AT5G67300
BnaC02g16640DC02
BnaC07g16030DC07
DEG95032.00E−13896.00%BnaA01g00540DA01AT4G37410
BnaA08g15660DA08
BnaC01g01530DC01
BnaC03g61420DC03
DEG107970.00E+0099.00%BnaA03g21640DA03AT2G47130
BnaA09g42190DA09
BnaC03g72480DC03
BnaC08g34620DC08
DEG1111770.00E+00100.00%BnaA03g00940DA08AT5G03560
BnaC03g01290DC03
DEG127360.00E+0099.00%BnaA02g15190DA02AT1G70830
BnaA07g28930DA07
BnaA08g20650DA08
BnaC02g20340DC02
BnaC06g31980DC06
BnaC07g13200DC07
DEG145032.00E−13894.00%BnaC01g07930DC01AT4G30450
DEG154608.00E−2696.00%BnaA01g30930DA01AT3G55200
BnaA09g05750DA09
DEG1710500.00E+0098.00%BnaA06g05510DA06AT1G09690
BnaA08g26210DA08
BnaA09g48320DA09
BnaC05g07130DC05
BnaC08g13710DC08
DEG207780.00E+0099.00%BnaA02g24900DA02AT5G47030
BnaA06g35640DA06
BnaC04g00050DC04
BnaC02g33050DC02
BnaC07g19840DC07
BnaC08g25530DC08
BnaC09g19920DC09
DEG213422.00E−9099.00%BnaA06g06120DA06AT1G10330
BnaA06g06150DA06
BnaC05g07870DC05
DEG228060.00E+0099.00%BnaA03g17080DA03AT2G37220
BnaA04g04760DA04
BnaA05g07240DA05
BnaC02g22410DC02
BnaC04g08050DC04
BnaC06g04460DC06
BnaC09g41150DC09
DEG236308.00E−7799.00%BnaA01g26080DA01AT2G14900
BnaA03g38750DA03
BnaC03g40940DC03
BnaC03g45610DC03
DEG254976.00E−3799.00%BnaA04g17660DA04AT2G30570
BnaA05g11890DA05
BnaC04g13890DC04
BnaC04g41210DC04
BnaC05g04700DC05
BnaC09g18450DC09
DEG269420.00E+0099.00%BnaA07g29960DA07AT1G72230
BnaC02g21230DC02
BnaC06g33270DC06
DEG277820.00E+0098.00%BnaA02g28130DA02AT3G26520
BnaA06g32840DA06
BnaC02g36210DC02
BnaC07g23630DC07
DEG293463.00E−9187.00%BnaA03g40170DA03
BnaA10g23990DA10
BnaC09g48610DC09
DEG349220.00E+0098.00%BnaA06g40690DA06AT4G39270
BnaC07g47290DC07
DEG364014.00E−108100.00%BnaA06g30700DA06AT3G30260
BnaA09g02740DA09
BnaC02g38130DC02
BnaC07g25980DC07
BnaC09g02190DC09
DEG375231.00E−144100.00%BnaA04g26210DA04AT2G45470
BnaA05g04890DA05
BnaC04g04230DC04
BnaC04g50210DC04
DEG3912300.00E+00100.00%BnaA06g37230DA06AT4G38970
BnaA08g16820DA08
BnaC01g00070DC01
BnaC03g60280DC03
BnaC07g47470DC07
DEG415714.00E−159100.00%BnaA03g31050DA03AT3G08770
BnaA05g29430DA05
BnaC03g36390DC03
BnaC05g43760DC05
DEG424462.00E−121100.00%BnaA02g17680DA02AT4G30620
BnaA08g12990DA08
BnaC02g24220DC02
BnaC03g77490DC03
DEG434316.00E−11798.00%BnaA03g50940DA03AT4G34180
BnaC07g44780DC07
DEG445623.00E−156100.00%BnaA02g14620DA02AT1G69220
BnaA07g27770DA07
BnaC06g30400DC06
DEG462007.00E−4899.00%BnaA01g27710DA01AT3G16640
BnaA03g34250DA03
BnaA05g23180DA05
BnaC01g35230DC01
BnaC03g39720DC03
BnaC05g36580DC05

Homology comparison of all differential expression genes and corresponding to Brassica napus genes and Arabidopsis thaliana genes.

DEG, different expression genes.

Subsequently, genes that regulate apical meristem were conducted for further analysis. DEG1 is homologous to the Arabidopsis gene AT4G29040 (RPT2A), and it had five copies distributed on A01 (BnaA01g07860D), A08 (BnaA08g13550D), C01 (BnaC01g09460D), C07 (BnaC07g41720D), and C08 (BnaC08g13300D). DEG2 had two copies found on A10 (BnaA10g29350D) and C09 (BnaC09g33500D) and are homologous to the Arabidopsis gene AT5G57950 (halted root, HLR). DEG4 (BnaA06g24200D) is homologous to the Arabidopsis gene AT4G01710 (crooked, CRK) and encodes ARP2/3 complex 16-kDa subunit. DEG5 had one copy on A01 (BnaA01g02910D), which is homologous to the Arabidopsis gene AT4G34220, and it was considered to be a leucine-rich repeat receptor-like protein kinase gene (LRR-RLK). DEG34 had two copies located on A06 (BnaA06g40690D) and C07 (BnaC07g47290D), and they were homologous to the Arabidopsis gene AT4G39270, which has the same function with DEG5 and was also considered to be leucine-rich repeat receptor-like protein kinase family gene (LRR-RLK). DEG36 is homologous to the Arabidopsis gene AT3G30260 (AGAMOUS-like MADS-box protein 79, AGL79), which has five copies found on A06 (BnaA06g30700D), A09 (BnaA09g02740D), C02 (BnaC02g38130D), C07 (BnaC07g25980D), and C09 (BnaC09g02190D). DEG46 (BnaC03g39720D) is homologous to the Arabidopsis gene AT3G16640 (TCTP), which is mainly expressed in meristematic regions of the shoot and root.

Relative Expression Level of Candidate Genes Based on QTL Mapping and Gene-Fishing

Based on the common candidate genes that were obtained from QTL mapping and Gene-Fishing technique, six commonly identified genes were annotated to be related to the formation of MMS, including RPT2A, HLR, CRK, LRR-RLK, AGL79, and TCTP, and these genes were further used to perform the relative expression analysis by quantitative real-time PCR between the normal plant and the DMS plant in four stages of seedling (5, 10, 15, and 20 days of seedling age) (Figure 8). It was revealed that the expression level of RPT2A was extremely and significantly higher in DMS plant than that of in natural plant in 15 days of seedling age, and in 10 and 20 days of seedling age, the expression level of RPT2A in DMS plant was extremely and significantly lower than that of in natural plant. For HLR, the expression level in DMS plant was much higher than that in natural plant in all four states of seedling age. Especially in 5, 10, and 15 days, the expression levels in DMS plant were significant or extremely and significantly higher than that in natural plant. In 10 to 20 days of seedling age, expression level were higher in natural plant than that in DMS plant, which were also consistent with Gene-Fishing results (Table 5). In addition, whether in natural plant or the DMS plant, expression of HLR also showed downward trend in all four states. For CRK, in 5 days of seedling age, expression level in DMS plant was extremely and significantly higher than that in natural plant; however, in 10 days of seedling age, the expression of CRK was severely inhibited in DMS plant. From 15 to 20 days, expressions of CRK were slowly rising again. The decline in gene expression of CRK might lead to a decrease in the activity of some regulated genes, which disrupted the balance of SAM. For LRR-RLK, the expression level in DMS plant was extremely and significantly lower than in natural plant of 10 and 20 days of seedling age; however, its expression level in DMS plant was extremely and significantly higher than in natural plant in 5 and 15 days of seedling age. In addition, the expression level of LRR-RLK in natural plant was the highest at fourth stage, which was compatible with result of Gene-Fishing (Table 5). For AGL79, the expression level in DMS plant was extremely and significantly lower than in natural plant in 5 days of seedling age. With the development of seedlings, the expression level in DMS plant was slightly higher (not significant) than in natural plant of 10 to 20 days of seedling age. For TCTP, the expression level in DMS was extremely and significantly lower than in natural plant of 5 to 15 days of seedling age. In 20 days of seedling age, the expression level of TCTP showed upward trend in DMS plant. Relative expression level of candidate genes showed that these six genes had different expression profile between the natural plant and the DMS plant in different seedling age stages.

Figure 8

Figure 8

Differential expression of six common genes in natural plant and double-main stem plant. qRT-PCR validation of cloning results of six predictive genes. Left, natural plant (natural). Right, the double-main stem plant (DMS plant). **Significant at p < 0.01. *Significant at p < 0.05. No significance p > 0.05.

Table 5

DEG numberDescriptionUp expression
DEG1RPA2A, Brassica napus 19S proteasome regulatory subunit 4 homolog A-like.Natural
DEG2HLR, Brassica napus 26S proteasome non-ATPase regulatory subunit 9-like.DMS
DEG4CRK, Brassica napus actin-related protein 2/3 complex subunit 5A-like.DMS
DEG5LRR-RLK, Brassica napus receptor protein kinase-like protein At4g34220.Natural
DEG36AGL79, Brassica napus uncharacterized LOC106436879.DMS
DEG46TCTP, Brassica napus translationally controlled tumor proteinDMS

Six differential expression gene description and differential expressed in natural plant and the double-main stem plant based on Gene-Fishing.

DEG, different expression genes; natural, natural plant; DMS, double-main plant.

Discussion

Rapeseed is an important oilseed crops worldwide (Cai et al., 2014). Although oil content and seed yield of rapeseed varieties have been effectively improved by rapeseed breeders (Zhao et al., 2011), the optimal plant architectural cultivated varieties are urgently needed for mechanized harvesting and high-density planting in the current agricultural management (Fu, 2008). Rapeseed plant architecture is characterized by plant height, branch number and angles, and inflorescence morphology (Li et al., 2018a), which indirectly influence rapeseed yield by affecting the major yield-component trait (Qiu et al., 2006; Zhou et al., 2014). Crop breeding has primarily focused on plant architecture, including plant height, branch or tiller number and angle, leaf shape, and size (Wang et al., 2018). MMS differentiated from shoot meristem, which is also one of the important factors for improving plant architecture and is conducive to increasing plant density and enhancing seed yield in rapeseed. In KN DH population, several MMS plants were found, and their main characteristics were composed of double- or three main stems from the base of a plant and had less lateral branches (Figure 1). Because of nutrient diversion, the MMS plant had slight lower plant height and stronger stem; thus, the MMS materials had stronger lodging resistance. In addition, under a small sowing amount of seeds, the multiple main stem materials not only can effectively increase plant density and the total number of siliques per unit, which finally might increase seed yield, but also, it is suitable for mechanized harvesting and to improve production efficiency. In total, the acquisition of the MMS material provided completely new ideas to improve the plant architecture and breed new varieties in crops.

According to the statistics of the number for MMS materials in different plant environments in several years, MMS was a complex quantitative trait and was significantly influenced by the environment. QTL mapping is considered to be an effective approach for dissecting quantitative traits (Paran and Zamir, 2003). In the present study, 43 QTLs for MMS that were located on 14 chromosomes were identified, explaining 2.95–14.9% of the phenotypic variation (Table 2). Two environment-stable QTLs, including qMMS.A3-2 and qMMS.C3-5, were expressed in both winter and semi-winter environments. More importantly, according to epistatic interaction analysis, QTL cqMMS.C3-5 had three epistatic interactions with other loci, which indicated that this stable QTL was an important loci for MMS. Several environment-stable QTLs for other agricultural traits in rapeseed have been reported, such as stable QTLs for flowering time (Li et al., 2018b; Shi et al., 2009) and thousand seed weight (Zhao et al., 2016). These environment-stable QTLs are suitable for developing new varieties of rapeseed with broad adaptability (Li et al., 2018b). Some genes within QTLs related to cell division and differentiation of shoot meristem were identified mainly included STM, WUS-related homeobox genes, cytokinin response factors, and auxin-related genes. Previous studies showed that cytokinin (CK) produced by root can promote cell division as well as maintenance of meristem, and the upward transport of CK in the root promotes axillary bud germination and the formation of lateral branches (Chatfield et al., 2000; Leyser, 2003; Ongaro and Leyser, 2008).

Gene-fishing technology has been widely used to identify DEGs in crops (Sanghoon et al., 2009; Liao et al., 2015). Some important differently expressed genes have been identified, such as salt-stress-induced up-regulated genes in barley leaves (Sanghoon et al., 2009) and pistillody genes in wheat (Liao et al., 2015). In the present study, 31 differentially expressed genes between DMS plants and the natural plants of B. napus were identified, in which six DEGs involved in the formation and regulation of DMS phenotype (Table 4), including RPT2A, HLR, CRK, LRR-RLK, AGL79 (AGAMOUS-LIKE 79), and TCTP (translationally controlled tumor protein). Among them, RPT2A is a 26S proteasome subunit and was located in QTL regions of cqMMS.A1-3, cqMMS.A3-1, cqMMS.C5-2, and cqMMS.C7-3 and was reported to be involved in maintenance of the post-embryonic meristems (Ueda et al., 2004). 26S proteasome is an important factor in signal transduction–mediated pathway; missing or mutation of 26S proteasome would lead to a decrease in strigolactones (SL) content, thereby promoting the excessive growth of axillary buds and other organs, such as branches and tillers (Wang and Bouwmeester, 2018). Therefore, changes of 26S proteasome may affect the growth of SAM and result in MMS phenotype. Abnormal expression of RPT2A in DMS plant might change the state of meristem and SL content in 5 to 20 days of seedling age, thereby forming MMS phenotype. HLR is located in QTL regions of cqMMS.A10-1 and cqMMS.C9-1, which encodes 26S proteasome regulatory subunit RPT2A, which is essential to maintain the size of SAM and might affect the growth of SAM by affecting the expression of WUS (Ueda et al., 2004). However, the expression level of HLR in DMS plant was much higher than that in natural plant in four states of seedling age, and overexpression of HLR might disturb the normal state of meristem and initiate bud differentiation. Meanwhile, HLR is also required to regulate the cell division pattern in SAM. In plants, the actin cytoskeleton is essential for various processes such as stomatal closure, cell proliferation, and cell morphogenesis (Akin and Zipursky, 2014). CRK encodes ARP2/3 complex 16-kDa subunit. In moss Physcomitrella, when the constituent part arpc4 of the CRK is lost, shoot growth of the apical cell slows down obviously. In the current study, CRK was located in QTL region of cqMMS.A6-1, and the decline in gene expression of CRK might lead to a decrease in the activity of some regulate genes in seedling. Studies in A. thaliana, when the CRK is absent, the actin of trichomes, hypocotyls cells, and epidermal pavement cells gather into bundles, downstream cell activity was interfered (Deeks and Hussey, 2003; Quatrano et al., 2006), which disrupted the balance of SAM. LRR-RLK represented a large family of protein kinases; it was located in QTL region of cqMMS.A1-2 (Gou et al., 2010). Expression of LRR-RLK had upward trend in DMS plant, which indicated that LRR-RLK might participate in the occurrence of axillary buds (Yaginuma et al., 2011). In addition, LRR-RLK contains ERECTA (ER) and CLV1. ER-family receptor kinases can regulate stem cell homeostasis to regulate organ shape and inflorescence architecture via cushioning its CK response in the SAM (Shchennikova et al., 2017). CLV1 interacts with the WUS gene to maintain the balance of differentiation of shoot and floral meristem cells in SAM (Gou et al., 2010). When CK stimulates the expression of WUS, the expression of CLV3 should have been inhibited to result in a SAM expansion; however, the morphology of SAM showed no difference with the normal plant. These phenomena could owe to the cushioning mechanism of ER family, which prevents the expression of CLV3 from increasing remarkably, thereby maintaining the normal development of stem meristem (Torii et al., 1996; Uchida et al., 2013). AGL79 is a transcription factor; relatively lower AGL79 overexpression would promote more lateral branches and rosette leaves (Gao et al., 2018). In addition, miR156/SPL10 modulated lateral root development and branching and leaf morphology in A. thaliana by silencing AGL79 (Gao et al., 2018). TCTP is a central regulator of cell proliferation and differentiation in animals and in plants, which is an important mitotic regulator (Amson et al., 2013; Roberto et al., 2015).

Furthermore, some genes also have similar functions in other crops. HLR gene is a homolog of the 26S proteasome subunit, which was strongly expressed both in the SAM and RAM of rice seedlings (Yanagawa et al., 2002). LRR-RLKs play an important role in regulating the SAM and microspores (Becraft, 2002), brassinosteroid perception, and floral abscission (Carles and Fletcher, 2003; Li, 2003). Rameneni et al. performed the whole-genome sequencing (WGS) of B. rapa and identified the LRR-RLK of B. rapa, which is involved in the plant morphological characters and plant stress resistance (Rameneni et al., 2015). ERECTA is one of LRR-RLK family, which coordinates Arabidopsis organ growth and flower development by promoting cell proliferation (Torii et al., 1996; Shpak et al., 2004). VEGETATIVE1 (VEG1) is an AGL79-like MADs-box gene; the secondary inflorescences in nutation were replaced by vegetative branches in pea (Berbel et al., 2012). In addition, AGL79 is involved in regulating leaf shape, shoot branching, and flowering time in A. thaliana (Gao et al., 2018). In addition, when maize is under stress response, TCTP expression showed a significant upward trend (Chen et al., 2014). Taken together, a series of balance will be broken when these genes mutated and may lead to disturbance in the growth of SAM and form abnormal organ morphology, such as clumping leaves and multiple axillary buds (Gou et al., 2010; Uchida et al., 2013).

Conclusion

The increase of yield and oil content is the ultimate goal in rapeseed breeding. Due to the lack of mechanized cultivated variety and high productive cost as well as low income, farmers prefer to idle the farmland rather than plant rapeseed, which seriously hampers the development of rapeseed in China. Importantly, the acquisition of MMS materials provides the possibility for breeding mechanized varieties, high-density planting varieties, and the yield improvement in rapeseed. In the present study, six common candidate genes within QTL regions and differentially expressed genes, including RPT2A, HLR, CRK, LRR-RLK, AGL79, and TCTP were identified by using QTL mapping and Gene-Fishing technique. Meanwhile, according to their functional annotation, these candidate genes might be related to the formation of MMS phenotype, in which genes might disrupt cell division and the differentiation of SAM and induce the formation of multiple buds, thereby promoting the formation and development of the MMS plant. MMS is an important agriculture trait, which is differentiated from shoot apical meristem. Relative expression level of candidate genes showed that these genes had different expression level between the natural plants and the DMS plants in different seedling age stages. Overall, the study would not only give a new insight into the genetic basis underlying the control of the MMS in rapeseed but also provide clues for plant architecture breeding in rapeseed.

Funding

This work was supported financially by the national key research project of China (2016YFD0101300, 2016YFD0101200), the Science and Technology Plan Project of Yangling Demonstration Zone of China (2017NY-20), Innovative Talents Promotion Plan of Shaanxi province- Key Technological Innovation Team Plan (2017KCT-23).

Statements

Data availability statement

All datasets generated for this study are included in the manuscript/Supplementary Files.

Ethics statement

The authors declare that the experiments comply with the current laws of the country in which they were performed.

Author contributions

WZ wrote the first draft of the manuscript. WZ and HC conducted all the field experiments, performed most of the experiments and data analysis for the overall study; HC, LnZ, NT, YZ, BL, KZ, ZG and HW helped and participated in the field trials and data collection for multiple-main stem. KC, LbZ and DH performed the phenotypic data processing and QTL detection. ML designed and conceived the overall study and revised the manuscript. All authors read and approved the final manuscript.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpls.2019.01152/full#supplementary-material

Figure S1

Differential expressed genes screen using ACPs amplified primer 1-9. Odd number lane represented natural plant and even number lane represented double-main stem plant.

Figure S2

Differential expressed genes screen using ACPs amplified primer 10-15. Odd number lane represented natural plant and even number lane represented double-main stem plant.

Figure S3

Differential expressed genes screen using ACPs amplified primer 16-20. Odd number lane represented natural plant and even number lane represented double-main stem plant.

Figure S4

Differential expressed genes screen using ACPs amplified primer 21-25. Odd number lane represented natural plant and even number lane represented double-main stem plant.

Figure S5

Differential expressed genes screen using ACPs amplified primer 26-31. Odd number lane represented natural plant and even number lane represented double-main stem plant.

Figure S6

Differential expressed genes screen using ACPs amplified primer 32-36. Odd number lane represented natural plant and even number lane represented double-main stem plant.

Figure S7

Distribution of QTLs for multi-main stem on A genome in B. napus

Figure S8

Distribution of QTLs for multi-main stem on C genome in B. napus

Abbreviations

B. napus, Brassica napus; A. thaliana, Arabidopsis thaliana; QTL, quantitative trait locus; SNPs, single nucleotide polymorphisms; DL, Dali in Shannxi Province, China; WH, Wuhan in Hubei Province, China; MMS, multiple main stem; DMS, double-main stem; DEGs, different expression genes; DH, doubled haploid; qPCR, quantitative real-time PCR.

References

  • 1

    AidaM.IshidaT.TasakaM. (1999). Shoot apical meristem and cotyledon formation during Arabidopsis embryogenesis: interaction among the CUP-SHAPED COTYLEDON and SHOOT MERISTEMLESS genes. Development126, 15631570. doi: 10.1007/s004290050234

  • 2

    AkinO.ZipurskyS. L. (2014). The shape of things to come. Cell156, 1314. doi: 10.1016/j.cell.2013.12.037

  • 3

    AmsonR.PeceS.MarineJ. C.Di FioreP. P.TelermanA. (2013). TPT1/TCTP-regulated pathways in phenotypic reprogramming. Trends Cell Biol.23, 3746. doi: 10.1016/j.tcb.2012.10.002

  • 4

    ArcadeA.LabourdetteA.FalqueM.ManginB.ChardonF.CharcossetA.et al. (2004). BioMercator: integrating genetic maps and QTL towards discovery of candidate genes. Bioinformatics20, 23242326. doi: 10.1093/bioinformatics/bth230

  • 5

    BaoB. H.ChaoH. B.WangH.ZhaoW. G.ZhangL. N.RaboanatahiryN.et al. (2018). Stable, environmental specific and novel QTL identification as well as genetic dissection of fatty acid metabolism in Brassica napus. Front. Plant Sci.9, 1018. doi: 10.3389/fpls.2018.01018

  • 6

    BecraftP. W. (2002). Receptor kinase signaling in plant development. Annu. Rev. Cell Dev. Biol.18, 163192. doi: 10.1146/annurev.cellbio.18.012502.083431

  • 7

    BerbelA.FerrándizC.HechtV.DalmaisM.LundO. S.SussmilchF. C.et al. (2012). VEGETATIVE1 is essential for development of the compound inflorescence in pea. Nat. Commun.4, 797. doi: 10.1038/ncomms1801

  • 8

    BradleyS. V.SmithM. R.HyunT. S.LucasP. C.LiL.AntonukD.et al. (2007). Aberrant Huntingtin interacting protein 1 in lymphoid malignancies. Cancer Res.67, 89238931. doi: 10.1158/0008-5472.CAN-07-2153

  • 9

    BrandU.FletcherJ.HobeM.MeyerowitzE.SimonR. (2000). Dependence of stem cell fate in Arabidopsis on a feedback loop regulated by CLV3 activity. Science289, 617619. doi: 10.1126/science.289.5479.617

  • 10

    BrandU.GrnewaldM.HobeM.SimonR. (2002). Regulation of CLV3 expression by two homeobox genes in Arabidopsis. Plant Physiol.129, 565575. doi: 10.1104/pp.001867

  • 11

    BurnsM. J.BarnesS. R.BowmanJ. G.ClarkeM. H. E.WernerC. P.KearseyM. J. (2003). QTL analysis of an intervarietal set of substitution lines in Brassica napus: (i) Seed oil content and fatty acid composition. Heredity90, 3948. doi: 10.1038/sj.hdy.6800176

  • 12

    CaiD.XiaoY.YangW.YeW.WangB.YounasM.et al. (2014). Association mapping of six yield-related traits in rapeseed (Brassica napus L.). Theor. Appl. Genet.127, 8596. doi: 10.1007/s00122-013-2203-9

  • 13

    CarlesC. C.FletcherJ. C. (2003). Shoot apical meristem maintenance: the art of a dynamic balance. Trends Plant Sci.8, 394401. doi: 10.1016/S1360-1385(03)00164-X

  • 14

    ChaoH. B.WangH.WangX. D.GuoL. X.GuJ. W.ZhaoW. G.et al. (2017). Genetic dissection of seed oil and protein content and identification of networks associated with oil content in Brassica napus. Sci. Rep.7, 46295. doi: 10.1038/srep46295

  • 15

    ChalhoubB.DenoeudF.LiuS.ParkinI. A.TangH.WangX.et al. (2014). Plant genetics. Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed genome. Science345, 950953. doi: 10.1126/science.1253435

  • 16

    ChatfieldS. P.StirnbergP.FordeB. G.LeyserO. (2000). The hormonal regulation of axillary bud growth in Arabidopsis. Plant J.24, 159169. doi: 10.1046/j.1365-313x.2000.00862.x

  • 17

    ChenW.ZhangY.LiuX.ChenB.TuJ.FuT.et al. (2007). Detection of QTL for six yield-related traits in oilseed rape (Brassica napus) using DH and immortalized F2 populations. Theor. Appl. Genet.115, 849858. doi: 10.1007/s00122-007-0613-2

  • 18

    ChenY.ChenX.WangH. J.BaoY. Q.ZhangW. (2014). Examination of the leaf proteome during flooding stress and the induction of programmed cell death in maize. Proteome Sci.12, 33. doi: 10.1186/1477-5956-12-33

  • 19

    ChengY.QinG.DaiX.ZhaoY. (2008). NPY genes and AGC kinases define two key steps in auxin-mediated organogenesis in Arabidopsis. Proc. Natl. Acad. Sci.105, 2101721022. doi: 10.1073/pnas.0809761106

  • 20

    ChoS.ChaD. H.ChangJ. B.LeeC. N.KwakI. P.LeeS. H. (2006). Decreased chorionic somatomammotropin 1(CSH1) and nectin-3 gene expression of the placenta in the patient of pre-eclampsia. Fertil. Steril.86, 514515. doi: 10.1016/j.fertnstert.2006.07.1429

  • 21

    ChoiY. I.NohE. W.KimH. J.ParkW. J. (2014). Differential regulation of cytokinin oxidase genes and cytokinin-induced auxin biosynthesis by cellular cytokinin level in transgenic poplars. Plant Cell Rep.33, 17371744. doi: 10.1007/s00299-014-1652-1

  • 22

    ChoiY.YunH.ParkK. (2008). Screening genes expressed by Rhizobium vitis inoculation and salicylic acid treatment in grapevines using GeneFishing. J. Jpn. Soc. Hortic. Sci.77, 137142. doi: 10.2503/jjshs1.77.137

  • 23

    ClarkS. E.JacobsenS. E.LevinJ. Z.MeyerowitzE. M. (1996). The CLAVATA and SHOOT MERISTEMLESS loci competitively regulate meristem activity in Arabidopsis. Development122, 15671575.

  • 24

    DeeksM. J.HusseyP. J. (2003). Arp2/3 and ‘The Shape of things to come. Curr. Opin. Plant Biol.6, 561567. doi: 10.1016/j.pbi.2003.09.013

  • 25

    DengQ.WangX.ZhangD.WangX.FengC.XuS. (2017). BRS1 function in facilitating lateral root emergence in Arabidopsis. Int. J. Mol. Sci.18, E1549. doi: 10.3390/ijms18071549

  • 26

    DingG.ZhaoZ.LiaoY.HuY.ShiL.LongY.et al. (2012). Quantitative trait loci for seed yield and yield-related traits, and their responses to reduced phosphorus supply in Brassica napus. Ann. Bot.-London109, 747759. doi: 10.1093/aob/mcr323

  • 27

    DingL.YanS.JiangL.ZhaoW.NingK.ZhaoJ.et al. (2015). Hanaba taranu (han) bridges meristem and organ primordia boundaries through pinhead, jagged, blade-on-petiole2 and cytokinin oxidase 3 during flower development in arabidopsis. Plos Genet.11, e1005479. doi: 10.1371/journal.pgen.1005479

  • 28

    DodsworthS. (2009). A diverse and intricate signaling network regulates stem cell fate in the shoot apical meristem. Dev. Biol.336, 19. doi: 10.1016/j.ydbio.2009.09.031

  • 29

    FanC.CaiG.QinJ.LiQ.YangM.WuJ.et al. (2010). Mapping of quantitative trait loci and development of allele-specific markers for seed weight in Brassica napus. Theor. Appl. Genet.121, 12891301. doi: 10.1007/s00122-010-1388-4

  • 30

    FletcherJ.MeyerowitzE. (2000). Cell signaling within the shoot meristem. Curr. Opin. Plant Biol.3, 2330. doi: 10.1016/S1369-5266(99)00033-3

  • 31

    FletcheJ. C. (2018). The CLV-WUS stem cell signaling pathway: a roadmap to crop yield optimization. Plants (Basel)7, 87. doi: 10.3390/plants7040087

  • 32

    FrankW.Kim-MiriamB.QudeimatE.WoriedhM.AlawadyA.RatnadewiD.et al. (2007). A mitochondrial protein homologous to the mammalian peripheral-type benzodiazepine receptor is essential for stress adaptation in plants. Plant J.51, 10041018. doi: 10.1111/j.1365-313X.2007.03198.x

  • 33

    FuT. D. (2008). On research and application of heterosis in rapeseed. Agric. Sci. Technol. Equip.5, 1011. doi: 10.3969/j.issn.1673-887X.2008.05.005

  • 34

    GaoR.WangY.GruberM. Y.HannoufaA. (2018). miR156/SPL10 modulates lateral root development, branching and leaf morphology in Arabidopsis by silencing AGAMOUS-LIKE 79. Front. Plant Sci.8, 2226. doi: 10.3389/fpls.2017.02226

  • 35

    GordonS.ChickarmaneV.OhnoC.MeyerowitzE. (2009). Multiple feedback loops through cytokinin signaling control stem cell number within the Arabidopsis shoot meristem. Proc. Natl. Acad. Sci.106, 1652916534. doi: 10.1073/pnas.0908122106

  • 36

    GouX.HeK.YangH.YuanT.LinH.ClouseS. D.et al. (2010). Genome-wide cloning and sequence analysis of leucine-rich repeat receptor-like protein kinase genes in Arabidopsis thaliana. BMC Genomics11, 115. doi: 10.1186/1471-2164-11-19

  • 37

    HaeckerA.LauxT. (2001). Cell-cell signaling in the shoot meristem. Curr. Opin. Plant Biol.4, 441446. doi: 10.1016/S1369-5266(00)00198-9

  • 38

    HeislerM. G.OhnoC.DasP.SieberP.ReddyG. V.LongJ. A.et al. (2005). Patterns of auxin transport and gene expression during primordium development revealed by live imaging of the Arabidopsis inflorescence meristem. Curr Biol15, 18991911. doi: 10.1016/j.cub.2005.09.052

  • 39

    HuY.RenT.LiZ.TangY.RenZ.YanB. (2017). Molecular mapping and genetic analysis of a QTL controlling spike formation rate and tiller number in wheat. Gene634, 1521. doi: 10.1016/j.gene.2017.08.039

  • 40

    JiangC.ShiJ.LiR.LongY.WangH.LiD.et al. (2014). Quantitative trait loci that control the oil content variation of rapeseed (Brassica napus L.). Theor. Appl. Genet.127, 957968. doi: 10.1007/s00122-014-2271-5

  • 41

    JiangL.LiuX.XiongG.LiuH.ChenF.WangL.et al. (2013). DWARF 53 acts as a repressor of strigolactone signalling in rice. Nature504, 401405. doi: 10.1038/nature12870

  • 42

    JunaediA.JungW.ChungI.KimK. (2007). Differentially expressed gene of potentially allelopathic rice in response against Barnyardgrass. Crop Sci. Biotech. J.10, 231236.

  • 43

    KhushG. (2001). Green revolution: the way forward. Nat. Rev. Genet.2, 815-822. doi: 10.1038/35093585

  • 44

    KiefferM.SternY.CookH.ClericiE.MaulbetschC.LauxT.et al. (2006). Analysis of the transcription factor WUSCHEL and its functional homologue in Antirrhinum reveals a potential mechanism for the irroles in meristem maintenance. Plant Cell18, 560573. doi: 10.1105/tpc.105.039107

  • 45

    KimY.KwakC.GuY.HwangI.ChunJ. (2004). Annealing control primer system for identification of differentially expressed genes on agarose gels. Bio. Technol.36, 424426. doi: 10.2144/04363ST02

  • 46

    KroganN. T.MarcosD.WeinerA. I.BerlethT. (2016). The auxin response factor MONOPTEROS controls meristem function and organogenesis in both the shoot and root through the direct regulation of PIN genes. New Phytol.212, 4250. doi: 10.1111/nph.14107

  • 47

    KöllmerI.NovákO.StrnadM.ThomasS.TomáW. (2014). Overexpression of the cytosolic cytokinin oxidase/dehydrogenase (CKX7) from Arabidopsis causes specific changes in root growth and xylem differentiation. Plant J. Cell Mol. Biol.78, 359371. doi: 10.1111/tpj.12477

  • 48

    LauxT.MayerK. F.BergerJ.JurgensG. (1996). The WUSCHEL gene is required for shoot and floral meristem integrity in Arabidopsis. Development122, 8796.

  • 49

    LeibfriedA.ToJ.BuschW.StehlingS.KehleA.DemarM.et al. (2005). WUSCHEL controls meristem function by direct regulation of cytokinin-inducible response regulators. Nature438, 11721175. doi: 10.1038/nature04270

  • 50

    LeyserO. (2003). Regulation of shoot branching by auxin. Trends Plant Sci.8, 541545. doi: 10.1016/j.tplants.2003.09.008

  • 51

    LiH.RibautJ.LiZ.WangJ. (2008). Inclusive composite interval mapping (ICIM) for digenic epistasis of quantitative traits in biparental populations. Theor. Appl. Genet.116, 243260. doi: 10.1007/s00122-007-0663-5

  • 52

    LiH.LiJ.SongJ.ZhaoB.GuoC. H.WangB.et al. (2018a). An auxin signaling gene BnaA3.IAA7 contributes to improved plant architecture and yield heterosis in rapeseed. New Phytol.11, 15632. doi: 10.1111/nph.15632

  • 53

    LiB.ZhaoW.LiD.ChaoH.ZhaoX.TaN.et al. (2018b). Genetic dissection of the mechanism of flowering time based on an environmentally stable and specific QTL in Brassica napus. Plant Sci.277, 296310. doi: 10.1016/j.plantsci.2018.10.005

  • 54

    LiJ. (2003). Brassinosteroids signal through two receptor-like kinases. Curr. Opin. Plant Biol.6, 494499. doi: 10.1016/S1369-5266(03)00088-8

  • 55

    LiS.ChenL.ZhangL.LiX.LiuY.WuZ.et al. (2015). Bna C9.SMG7b functions as a positive regulator of number of seeds per silique in Brassica napus by regulating the formation of functional female gametophytes. Plant Physiol.169, 27442760. doi: 10.1104/pp.15.01040

  • 56

    LiaoM. L.PengZ. S.YangZ. J.WeiS. H.MartinekP. (2015). Identification of differentially expressed genes in a pistillody common wheat mutant using an annealing control primer system. Genet. Mol. Res.14, 39954004. doi: 10.4238/2015.April.27.14

  • 57

    LiuS.FanC.LiJ.CaiG.YangQ.WuJ.et al. (2016). A genome wide association study reveals novel elite allelic variations in seed oil content of Brassica napus. Theor. Appl. Genet.129, 12031215. doi: 10.1007/s00122-016-2697-z

  • 58

    LuK.XiaoZ.JianH.PengL.QuC.FuM.et al. (2016). A combination of genome-wide association and transcriptome analysis reveals candidate genes controlling harvest index-related traits in Brassica napus. Sci. Rep.6, 36452. doi: 10.1038/srep36452

  • 59

    LuZ.ShaoG.XiongJ.JiaoY.WangJ.LiuG.et al. (2015). MONOCULM 3, an ortholog of WUSCHEL in rice, is required for tiller bud formation. J. Genet. Genomics42, 7178. doi: 10.1016/j.jgg.2014.12.005

  • 60

    MengL.LiH.ZhangL.WangJ. (2015). QTL IciMapping Integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations. Crop J.3, 269283. doi: 10.1016/j.cj.2015.01.001

  • 61

    MüllerR.BorghiL.KwiatkowskaD.LaufsP.SimonR. (2006). Dynamic and compensatory responses of Arabidopsis shoot and floral meristems to CLV3 signaling. Plant Cell18, 11881198. doi: 10.1105/tpc.105.040444

  • 62

    NagaharuU. (1935). Genome analysis in Brassica with special reference to the experimental formation of B. napus and peculiar mode of fertilization. Jpn. J. Bot.7, 389452.

  • 63

    ParanI.ZamirD. (2003). Quantitative traits in plants: beyond the QTL. Trends Genet.19, 303306. doi: 10.1016/S0168-9525(03)00117-3

  • 64

    ParkJ. S.KimI. S.ChoM. S.ParkS.ParkS. G. (2006). Identification of differentially expressed genes involved in spine formation on seeds of Daucus carota L. (carrot), using annealing control primer (ACP) system. J. Plant Biol.49, 133140. doi: 10.1007/BF03031009

  • 65

    OngaroV.LeyserO. (2008). Hormonal control of shoot branching. J. Exp. Bot.59, 6774. doi: 10.1093/jxb/erm134

  • 66

    QiuD.MorganC.ShiJ.LongY.LiuJ.LiR.et al. (2006). A comparative linkage map of oilseed rape and its use for QTL analysis of seed oil and erucic acid content. Theor. Appl. Genet.114, 6780. doi: 10.1007/s00122-006-0411-2

  • 67

    QuarrieS.PekicQ. S.RadosevicR.KaminskaA.BarnesJ. D.LeveringtonM.et al. (2006). Dissecting a wheat QTL for yield present in a range of environments: from the QTL to candidate genes. J. Exp. Bot.57, 26272637. doi: 10.1093/jxb/erl026

  • 68

    QuatranoR. S.PerroudP. F.HarriesP.BezanillaM.PanA.KluehR.et al. (2006). The role of ARP2/3 and Scar/WAVE complexes in polar growth of the apical cell of the moss Physcomitrella. Dev. Biol.295, 342344. doi: 10.1016/j.ydbio.2006.04.059

  • 69

    QzerH.OralE.DogruU. (1999). Relationships between yield and yield components on currently improved spring rapeseed cultivars. Tr. J. Agric. For.23, 603607.

  • 70

    RameneniJ. J.LeeY.DhandapaniV.YuX.ChoiS. R.OhM.-H.et al. (2015). Genomic and post-translational modification analysis of leucine-rich-repeat receptor-like kinases in Brassica rapa. Plos One10, e0142255. doi: 10.1371/journal.pone.0142255

  • 71

    RobertoT. M.BeatrizX. C.JoséL. C. P.JesúsH. M.JorgeL. R. S.SantiagoV. G. G.et al. (2015). AtTCTP2, an Arabidopsis thaliana homolog of translationally controlled tumor protein, enhances in vitro plant regeneration. Front. Plant Sci.6, 468. doi: 10.3389/fpls.2015.00468

  • 72

    SablowskiR. (2007). Flowering and determinacy in Arabidopsis. J. Exp. Bot.58, 899907. doi: 10.1093/jxb/erm002

  • 73

    SanghoonL.KiwonL.KiyongK.GijunC.SeihyungY.JiH. C.et al. (2009). Identification of salt-stress induced differentially expressed genes in barley leaves using the annealing-control-primer-based gene fishing technique. Afr. J. Biotechnol.8, 13261331. doi: 10.5897/AJB2009.000-9212

  • 74

    SAS Institute Inc. (2000). SAS/STAT User’s Guide, Version 8. Cary, NC: SAS Institute Inc.

  • 75

    SchippersJ. H.FoyerC. H.Van DongenJ. T. (2016). Redox regulation in shoot growth, SAM maintenance and flowering. Curr. Opin. Plant Biol.29, 121128. doi: 10.1016/j.pbi.2015.11.009

  • 76

    SchoofH.LenhardM.HaeckerA.MayerK.JürgensG.LauxT. (2000). The stem cell population of Arabidopsis shoot, meristems is maintained by a regulatory loop between the CLAVATA and WUSCHEL genes. Cell100, 635644. doi: 10.1016/S0092-8674(00)80700-X

  • 77

    ShaoG.LuZ.XiongJ.WangB.JingY.MengX.et al. (2019). Tiller bud formation regulators MOC1 and MOC3 cooperatively promote tiller bud outgrowth by activating FON1 expression in rice. Mol. Plant19, 113. doi: 10.1016/j.molp.2019.04.008

  • 78

    ShchennikovaA. V.KochievaE. Z.BeletskyA. V.FilyushiM. A.ShulgaO. A.RavinN. V.et al. (2017). Identification and expression analysis of receptor-like kinase gene ERECTA in mycoheterotrophic plant Monotropa hypopitys. Mol. Biol.51, 681686. doi: 10.1134/S002689331705017X

  • 79

    ShiJ.LiR.QiuD.JiangC.LongY.MorganC.et al. (2009). Unraveling the complex trait of crop yield with quantitative trait loci mapping in Brassica napus. Genetics182, 851861. doi: 10.1534/genetics.109.101642

  • 80

    ShiJ.ZhanJ.YangY.YeJ.HuangS.LiR.et al. (2015). Linkage and regional association analysis reveal two new tightly linked major-QTLs for pod number and seed number per pod in rapeseed (Brassica napus L.). Sci. Rep.5, 14481. doi: 10.1038/srep14481

  • 81

    ShpakE. D.BerthiaumeC. T.HillE. J.ToriiK. U. (2004). Synergistic interaction of three ERECTA-family receptor-like kinases controls Arabidopsis organ growth and flower development by promoting cell proliferation. Development131, 14911501. doi: 10.1242/dev.01028

  • 82

    SohnW. J.KimD.LeeK. W.KimM. S.KwonS.LeeY.et al. (2007). Novel transcriptional regulation of the schlafen-2 gene in macrophages in response to TLR-triggered stimulation. Mol. Immunol.44, 32733282. doi: 10.1016/j.molimm.2007.03.001

  • 83

    SpinelliS. V.MartinA. P.ViolaI. L.GonzalezD. H.PalatnikJ. F. (2011). A mechanistic link between STM and CUC1 during Arabidopsis development. Plant Physiol.156, 18941904. doi: 10.1104/pp.111.177709

  • 84

    StribernyB.MeltonA. E.SchwackeR.KrauseK.FischerK.GoertzenL. R.et al. (2017). Cytokinin response factor 5 has transcriptional activity governed by its C-terminal domain. Plant Signaling Behav.12, e1276684. doi: 10.1080/15592324.2016.1276684

  • 85

    ToriiK. U.MitsukawaN.OosumiT.MatsuuraY.YokoyamaR.WhittierR. F.et al. (1996). The Arabidopsis ERECTA gene encodes a putative receptor protein kinase with extracellular leucine-rich repeats. Plant Cell8, 735746. doi: 10.1105/tpc.8.4.735

  • 86

    UchidaN.ShimadaM.TasakaM. (2013). ERECTA-family receptor kinases regulate stem cell homeostasis via buffering its cytokinin responsiveness in the shoot apical meristem. Plant Cell Physiol.54, 343351. doi: 10.1093/pcp/pcs109

  • 87

    UedaM.MatsuiK.IshiguroS.SanoR.WadaT.PaponovL.et al. (2004). The HALTED ROOT gene encoding the 26S proteasome subunit RPT2a is essential for the maintenance of Arabidopsis meristems. Development131, 21012111. doi: 10.1242/dev.01096

  • 88

    WangB.SmithM. S.LiJ. (2018). Genetic regulation of shoot architecture. Annu. Rev. Plant Biol.69, 437468. doi: 10.1146/annurev-arplant-042817-040422

  • 89

    WangH.YinY. (2014). Analysis and strategy for oil crop industry in China. Chin. J. Oil Crop Sci.36, 414421. doi: 10.7505/j.issn.1007-9084.2014.03.020

  • 90

    WangS.BastenC.ZengZ. (2007). Windows QTL Cartographer 2.5. Raleigh, NC: North Carolina State University.

  • 91

    WangY.LiJ. (2008). Molecular basis of plant architecture. Annu. Rev. Plant Biol.59, 253279. doi: 10.1146/annurev.arplant.59.032607.092902

  • 92

    WangX.WangH.LongY.LiD.YinY.TianJ.et al. (2013). Identification of QTLs associated with oil content in a high-oil Brassica napus cultivar and construction of a high-density consensus map for QTLs comparison in B. napus. PLoS One8, e80569. doi: 10.1371/journal.pone.0080569

  • 93

    WangY.BouwmeesterH. J. (2018). Structural diversity in the strigolactones. J. Exp. Bot.69, 22192230. doi: 10.1093/jxb/ery091

  • 94

    WeigelD.JürgensG. (2002). Stem cells that make stems. Nature415, 751754. doi: 10.1038/415751a

  • 95

    WilliamsL.FletcherJ. (2005). Stem cell regulation in the Arabidopsis shoot apical meristem. Curr. Opin. Plant Biol.8, 582586. doi: 10.1016/j.pbi.2005.09.010

  • 96

    XieL.LiP.ZhangW.YangM. (2005). A review on the development potential of bioenergy rapeseed. Chin. J. Bioprocess Eng.3, 2831. doi: 10.3969/j.issn.1672-3678.2005.01.007

  • 97

    YaginumaH.HirakawaY.KondoY.Ohashi-ItoK.FukudaH. (2011). A novel function of TDIF-related peptides: promotion of axillary bud formation. Plant Cell Physiol.52, 13541364. doi: 10.1093/pcp/pcr081

  • 98

    YanaiO.ShaniE.DolezalK.TarkowskiP.SablowskiR.SandbergG.et al. (2005). Arabidopsis KNOXI proteins activate cytokinin biosynthesis. Curr. Biol.15, 15661571. doi: 10.1016/j.cub.2005.07.060

  • 99

    YanagawaY.KimuraS.TakaseT.SakaguchiK.UmedaM.KomamineA.et al. (2002). Spatial distribution of the 26S proteasome in meristematic tissues and primordia of rice (Oryza sativa L.). Planta214, 703707. doi: 10.1007/s00425-001-0676-2

  • 100

    YiB.ChenY.LeiS.TuJ.FuT. (2006). Fine mapping of the recessive genie male sterile gene (Bnmsl) in Brassica napus. Theor. Appl. Genet.113, 643650. doi: 10.1016/S1369-5266(99)00033-3

  • 101

    YinY.ChenZ.YuJ.WangH.FengZ. (2010). Analysis of potential for rapeseed production in China. J. Agric. Sci. Technol.12, 1621. doi: 10.3969/j.issn.1008-0864.2010.03.03

  • 102

    ZhangN.YuH.YuH.CaiY.HuangL.XuC.et al. (2018). A core regulatory pathway controlling rice tiller angle mediated by the LAZY1-dependent asymmetric distribution of auxin. Plant Cell30, 14611475. doi: 10.1105/tpc.18.00063

  • 103

    ZhaoW.WangH.LiD.TianJ.ZhaoY.LiB.et al. (2011). Fingerprinting construction of Brassica napus germplasm with super-high oil content and main rapeseed cultivars. J. Plant Genet. Resour.12, 904909. doi: 10.13430/j.cnki.jpgr.2011.06.012

  • 104

    ZhaoW.WangX.WangH.TianJ. H.LiB. J.ChenL.et al. (2016). Genome-wide identification of QTL for seed yield and yield-related traits and construction of a high-density consensus map for QTL comparison in Brassica napus. Front. Plant Sci.7, 17. doi: 10.3389/fpls.2016.00017

  • 105

    ZhouF.LinQ.ZhuL.RenY.ZhouK.ShabekN.et al. (2016). Corrigendum: D14-SCF (D3)-dependent degradation of D53 regulates strigolactone signalling. Nature532, 406410. doi: 10.1038/nature16537

  • 106

    ZhouQ.FuD.MasonA.ZengY.ZhaoC.HuangY. (2014). In silico integration of quantitative trait loci for seed yield and yield-related traits in Brassica napus. Mol. Breed.33, 881894. doi: 10.1007/s11032-013-0002-2

  • 107

    ZwackP. J.De ClercqI.HowtonT. C.HallmarkH. T.HurnyA.KeshishianE. A.et al. (2016). Cytokinin response factor 6 represses cytokinin-associated genes during oxidative stress. Plant Physiol.172, 1249. doi: 10.1104/pp.16.00415

Summary

Keywords

Brassica napus, multi-main stem trait, QTL mapping, Gene-Fishing, candidate genes

Citation

Zhao W, Chao H, Zhang L, Ta N, Zhao Y, Li B, Zhang K, Guan Z, Hou D, Chen K, Li H, Zhang L, Wang H and Li M (2019) Integration of QTL Mapping and Gene Fishing Techniques to Dissect the Multi-Main Stem Trait in Rapeseed (Brassica napus L.). Front. Plant Sci. 10:1152. doi: 10.3389/fpls.2019.01152

Received

21 April 2019

Accepted

23 August 2019

Published

20 September 2019

Volume

10 - 2019

Edited by

Jianjun Chen, University of Florida, United States

Reviewed by

Zhongyun Piao, Shenyang Agricultural University, China; Rodrigo Gazaffi, Federal University of São Carlos, Brazil

Updates

Copyright

*Correspondence: Maoteng Li,

This article was submitted to Plant Breeding, a section of the journal Frontiers in Plant Science

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Outline

Figures

Cite article

Copy to clipboard


Export citation file


Share article

Article metrics