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Natural variation in ARF18 gene simultaneously affects seed weight and silique length in polyploid rapeseed.

ABSTRACT: Seed weight (SW), which is one of the three major factors influencing grain yield, has been widely accepted as a complex trait that is controlled by polygenes, particularly in polyploid crops. Brassica napus L., which is the second leading crop source for vegetable oil around the world, is a tetraploid (4×) species. In the present study, we identified a major quantitative trait locus (QTL) on chromosome A9 of rapeseed in which the genes for SW and silique length (SL) were colocated. By fine mapping and association analysis, we uncovered a 165-bp deletion in the auxin-response factor 18 (ARF18) gene associated with increased SW and SL. ARF18 encodes an auxin-response factor and shows inhibitory activity on downstream auxin genes. This 55-aa deletion prevents ARF18 from forming homodimers, in turn resulting in the loss of binding activity. Furthermore, reciprocal crossing has shown that this QTL affects SW by maternal effects. Transcription analysis has shown that ARF18 regulates cell growth in the silique wall by acting via an auxin-response pathway. Together, our results suggest that ARF18 regulates silique wall development and determines SW via maternal regulation. In addition, our study reveals the first (to our knowledge) QTL in rapeseed and may provide insights into gene cloning involving polyploid crops.

SUBMITTER: Liu J

PROVIDER: S-EPMC4577148 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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Natural variation in ARF18 gene simultaneously affects seed weight and silique length in polyploid rapeseed.

Liu Jing J Hua Wei W Hu Zhiyong Z Yang Hongli H Zhang Liang L Li Rongjun R Deng Linbin L Sun Xingchao X Wang Xinfa X Wang Hanzhong H

Proceedings of the National Academy of Sciences of the United States of America 20150831 37

Seed weight (SW), which is one of the three major factors influencing grain yield, has been widely accepted as a complex trait that is controlled by polygenes, particularly in polyploid crops. Brassica napus L., which is the second leading crop source for vegetable oil around the world, is a tetraploid (4×) species. In the present study, we identified a major quantitative trait locus (QTL) on chromosome A9 of rapeseed in which the genes for SW and silique length (SL) were colocated. By fine mapp ...[more]

PMID: 26324896

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Project description:BACKGROUND: Seed weight (SW) and silique length (SL) are important determinants of the yield potential in rapeseed (Brassica napus L.). However, the genetic basis of both traits is poorly understood. The main objectives of this study were to dissect the genetic basis of SW and SL in rapeseed through the preliminary mapping of quantitative trait locus (QTL) by linkage analysis and fine mapping of the target major QTL by regional association analysis. RESULTS: Preliminary linkage mapping identified thirteen and nine consensus QTLs for SW and SL, respectively. These QTLs explained 0.7-67.1% and 2.1-54.4% of the phenotypic variance for SW and SL, respectively. Of these QTLs, three pairs of SW and SL QTLs were co-localized and integrated into three unique QTLs. In addition, the significance level and genetic effect of the three co-localized QTLs for both SW and SL showed great variation before and after the conditional analysis. Moreover, the allelic effects of the three QTLs for SW were highly consistent with those for SL. Two of the three co-localized QTLs, uq.A09-1 (mean R(2) = 20.1% and 19.0% for SW and SL, respectively) and uq.A09-3 (mean R(2) = 13.5% and 13.2% for SW and SL, respectively), were detected in all four environments and showed the opposite additive-effect direction. These QTLs were validated and fine mapped (their confidence intervals were narrowed down from 5.3 cM to 1 cM for uq.A09-1 and 13.2 cM to 2.5 cM for uq.A09-3) by regional association analysis with a panel of 576 inbred lines, which has a relatively rapid linkage disequilibrium decay (0.3 Mb) in the target QTL region. CONCLUSIONS: A few QTLs with major effects and several QTLs with moderate effects might contribute to the natural variation of SW and SL in rapeseed. The meta-, conditional and allelic effect analyses suggested that pleiotropy, rather than tight linkage, was the genetic basis of the three pairs of co-localized of SW and SL QTLs. Regional association analysis was an effective and highly efficient strategy for the direct fine mapping of target major QTL identified by preliminary linkage mapping.

Project description:Seed number is a key character/trait tightly related to the plant fitness/evolution and crop domestication/improvement. The seed number per silique (SNPS) shows a huge variation from several to more than 30, however the underlying regulatory mechanisms are poorly known, which has hindered its improvement. To answer this question, several representative lines with extreme SNPS were previously subjected to systematic genetic and cytological analyses. The results showed that the natural variation of seed number per silique is mainly controlled by maternal and embryonic genotype, which are co-determined by ovule number per ovary, fertile ovule ratio, ovule fertilization rate, and fertilized ovule development rate. More importantly, we also mapped two repeatable quantitative trait loci (QTLs) for SNPS using the F2:3 population derived from Zhongshuang11 and No. 73290, of which the major QTL qSN.A6 has been fine-mapped. In the current study, the near-isogenic lines (NILs) of qSN.A7 were successfully developed by the successive backcross of F1 with Zhongshuang11. First, the effect of qSN.A7 was validated by evaluating the SNPS of two types of homozygous NILs from BC3F2 population, which showed a significant difference of 2.23 on average. Then, qSN.A7 was successfully fine-mapped from the original 4.237 to 1.389 Mb, using a BC4F2 segregating population of 2,551 individuals. To further clarify the regulatory mechanism of qSN.A7, the two types of homologous NILs were subjected to genetic and cytological analyses. The results showed that the difference in SNPS between the two homologous NILs was determined by the embryonic genotypic effect. Highly accordant with this, no significant difference was observed in ovule number per ovary, ovule fertility, fertilization rate, and pollen fertility between the two homologous NILs. Therefore, the regulatory mechanism of qSN.A7 is completely different from the cloned qSS.C9 and qSN.A6. These results will advance the understanding of SNPS and facilitate gene cloning and molecular breeding in Brassica napus.

Project description:BackgroundResearchers interested in the seed size of rapeseed need to quantify the cell size and number of cells in the seed coat, embryo and silique wall. Scanning electron microscope-based methods have been demonstrated to be feasible but laborious and costly. After image preparation, the cell parameters are generally evaluated manually, which is time consuming and a major bottleneck for large-scale analysis. Recently, two machine learning-based algorithms, Trainable Weka Segmentation (TWS) and Cellpose, were released to overcome this long-standing problem. Moreover, the MorphoLibJ and LabelsToROIs plugins in Fiji provide user-friendly tools to deal with cell segmentation files. We attempted to verify the practicability and efficiency of these advanced tools for various types of cells in rapeseed.ResultsWe simplified the current image preparation procedure by skipping the fixation step and demonstrated the feasibility of the simplified procedure. We developed three methods to automatically process multicellular images of various tissues in rapeseed. The TWS-Fiji (TF) method combines cell detection with TWS and cell measurement with Fiji, enabling the accurate quantification of seed coat cells. The Cellpose-Fiji (CF) method, based on cell segmentation with Cellpose and quantification with Fiji, achieves good performance but exhibits systematic error. By removing border labels with MorphoLibJ and detecting regions of interest (ROIs) with LabelsToROIs, the Cellpose-MorphoLibJ-LabelsToROIs (CML) method achieves human-level performance on bright-field images of seed coat cells. Intriguingly, the CML method needs very little manual calibration, a property that makes it suitable for massive-scale image processing. Through a large-scale quantitative evaluation of seed coat cells, we demonstrated the robustness and high efficiency of the CML method at both the single-cell level and the sample level. Furthermore, we extended the application of the CML method to developing seed coat, embryo and silique wall cells and acquired highly precise and reliable results, indicating the versatility of this method for use in multiple scenarios.ConclusionsThe CML method is highly accurate and free of the need for manual correction. Hence, it can be applied for the low-cost, high-throughput quantification of diverse cell types in rapeseed with high efficiency. We envision that this method will facilitate the functional genomics and microphenomics studies of rapeseed and other crops.

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Natural variation in ARF18 gene simultaneously affects seed weight and silique length in polyploid rapeseed.

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Natural variation in ARF18 gene simultaneously affects seed weight and silique length in polyploid rapeseed.

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