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| 1 | Genome-wide prediction in a hybrid maize population adapted to Northwest China显示文摘Genome-wide prediction is a promising approach to boost selection gain in hybrid breeding.Our main objective was to evaluate the potential and limits of genome-wide prediction to identify superior hybrid combinations adapted to Northwest China.A total of 490 hybrids derived from crosses among 119 inbred lines from the Shaan A and Shaan B heterotic pattern were used for genome-wide prediction of ten agronomic traits.We tested eight different statistical prediction models considering additive(A)effects and in addition evaluated the impact of dominance(D)and epistasis(E)on the prediction ability.Employing five-fold cross validation,we show that the average prediction ability ranged from 0.386 to 0.794 across traits and models.Six parametric methods,i.e.ridge regression,LASSO,Elastic Net,Bayes B,Bayes C and reproducing kernel Hilbert space(RKHS)approach,displayed a very similar prediction ability for each trait and two non-parametric methods(random forest and support vector machine)had a higher prediction performance for the trait rind penetrometer resistance of the third internode above ground(RPR_TIAG).The models of A+D RKHS and A+D+E RKHS were slightly better for predicting traits with a relatively high non-additive variance.Integrating trait-specific markers into the A+D RKHS model improved the prediction ability of grain yield by 3%,from 0.528 to 0.558.Of all 6328 potential hybrids,selection of the top 44 hybrids would lead to a 6%increase in grain yield compared with Zhengdan 958,a commercially successful hybrid variety.In conclusion,our results substantiate the value of genome-wide prediction for hybrid breeding and suggest dozens of promising single crosses for developing high-yielding hybrids for Northwest China. | Guoliang Li Yuan Dong Yusheng Zhao Xiaokang Tian Tobias Würschum Jiquan Xue Shaojiang Chen Jochen C.Reif Shutu Xu Wenxin Liu | 2020 | The Crop Journal2020，8，5： | 4 |
| 2 | ZmcrtRB3 Encodes a Carotenoid Hydroxylase that Affects the Accumulation of α-carotene in Maize Kernel显示文摘α-carotene is one of the important components of pro-vitamin A,which is able to be converted into vitamin A in the human body.One maize(Zea mays L.) ortholog of carotenoid hydroxylases in Arabidopsis thaliana,ZmcrtRB3,was cloned and its role in carotenoid hydrolyzations was addressed.ZmcrtRB3 was mapped in a quantitative trait locus(QTL) cluster for carotenoid-related traits on chromosome 2(bin 2.03) in a recombinant inbred line(RIL) population derived from By804 and B73.Candidate-gene association analysis identified 18 polymorphic sites in ZmcrtRB3 significantly associated with one or more carotenoid-related traits in 126 diverse yellow maize inbred lines.These results indicate that the enzyme ZmcrtRB3 plays a role in hydrolyzing both α-and β-carotenes,while polymorphisms in ZmcrtRB3 contributed more variation in α-carotene than that in β-carotene.Two single nucleotide polymorphisms(SNPs),SNP1343 in 5 untranslated region and SNP2172 in the second intron,consistently had effects on α-carotene content and composition with explained phenotypic variations ranging from 8.7% to 34.8%.There was 1.7-to 3.7-fold change between the inferior and superior haplotype for α-carotene content and composition.Thus,SNP1343 and SNP2172 are potential polymorphic sites to develop functional markers for applying marker-assisted selection in the improvement of pro-vitamin A carotenoids in maize kernels. | Yi Zhou Yingjia Han Zhigang Li Yang Fu Zhiyuan Fu Shutu Xu Jiansheng Li Jianbing Yan Xiaohong Yang | 2012 | Journal of Integrative Plant Biology2012，54，4： | 2 |
| 3 | Performance and stability of yield in response to plant density,year and location in maize hybrids of Northwest China显示文摘Identifying desirable genotypes with the best performance in diverse environments is a perpetual aim of plant breeding,and the interaction between genotype and environment(G×E)always plays a key role.This study was conducted to elucidate the genetic behaviour of different hybrid combinations at various densities in diverse environments.According to a line×tester design,32 hybrid combinations were obtained from 16 inbred individuals crossed with two testers and planted at three locations at three density levels(45,000,67,500 and 90,000 plants ha-1)during 2014-2017.Genotype(G),environment(E)and the interaction of genotype and environment(G×E)significantly affected grain yield at different densities.Increasing planting density enhanced grain yield and improved the efficiency of germplasm screening,where the effect of location on grain yield at different densities was larger than that of year and the GCA was larger than the SCA.Finally,four inbred lines(KB102,KB081,KA105,and KB106)with a high GCA,environmental adaptability,and several combinations using them as parents have been approved in ShannXi Province and National of China.In conclusion,the evaluation of combining ability at multiple densities and locations can effectively screen inbred lines and improve breeding efficiency. | Yuan Dong Zhiqian Feng Ting Li Ali Farhan Xiaokang Tian Yonghui Lao Yinxin Duan Leiyong Si Xinghua Zhang Jiquan Xue Shutu Xu | 2022 | Technology in Agronomy2022，2，1： | 1 |
| 4 | Characterization of a global germplasm collection and its potential utilization for analysis of complex quantitative traits in maize显示文摘 | Xiaohong Yang Shibin Gao Shutu Xu | 2010 | Mol Breeding2010，28，： | 1 |
| 5 | Time-resolved multiomics analysis of the genetic regulation of maize kernel moisture显示文摘Maize kernel moisture content(KMC)at harvest greatly affects mechanical harvesting,transport and storage.KMC is correlated with kernel dehydration rate(KDR)before and after physiological maturity.KMC and KDR are complex traits governed by multiple quantitative trait loci(QTL).Their genetic architecture is incompletely understood.We used a multiomics integration approach with an association panel to identify genes influencing KMC and KDR.A genome-wide association study using time-series KMC data from 7 to 70 days after pollination and their transformed KDR data revealed respectively 98and 279 loci significantly associated with KMC and KDR.Time-series transcriptome and proteome datasets were generated to construct KMC correlation networks,from which respectively 3111 and 759 module genes and proteins were identified as highly associated with KMC.Integrating multiomics analysis,several promising candidate genes for KMC and KDR,including Zm00001d047799 and Zm00001d035920,were identified.Further mutant experiments showed that Zm00001d047799,a gene encoding heat shock 70 kDa protein 5,reduced KMC in the late stage of kernel development.Our study provides resources for the identification of candidate genes influencing maize KMC and KDR,shedding light on the genetic architecture of dynamic changes in maize KMC. | Jianzhou Qu Shutu Xu Xiaonan Gou Hao Zhang Qian Cheng Xiaoyue Wang Chuang Ma Jiquan Xue | 2023 | The Crop Journal2023，11，1： | 1 |
| 6 | Genome assembly of KA105,a new resource for maize molecular breeding and genomic research显示文摘Superior inbred lines are central to maize breeding as sources of natural variation.Although many elite lines have been sequenced,less sequencing attention has been paid to newly developed lines.We constructed a genome assembly of the elite inbred line KA105,which has recently been developed by an arti-ficial breeding population named Shaan A and has shown desirable characteristics for breeding.Its pedigree showed genetic divergence from B73 and other lines in its pedigree.Comparison with the B73 reference genome revealed extensive structural variation,58 presence/absence variation(PAV)genes,and 1023 expanded gene families,some of which may be associated with disease resistance.A network-based integrative analysis of stress-induced transcriptomes identified 13 KA105-specific PAV genes,of which eight were induced by at least one kind of stress,participating in gene modules responding to stress such as drought and southern leaf blight disease.More than 200,000 gene pairs were differentially correlated between KA105 and B73 during kernel development.The KA105 reference genome and transcriptome atlas are a resource for further germplasm improvement and surveys of maize genomic variation and gene function. | Ting Li Shutu Xu Jiawen Zhao Yapeng Wang Jun Zhang Xin Wei Jianzhou Qu Ruisu Yu Xinghua Zhang Chuang Ma Jiquan Xue | 2023 | The Crop Journal2023，11，6： | 0 |
| 7 | The light and hypoxia induced gene ZmPORB1 determines tocopherol content in the maize kernel显示文摘Tocopherol is an important lipid-soluble antioxidant beneficial for both human health and plant growth. Here, we fine mapped a major QTLqVE1 affecting γ-tocopherol content in maize kernel, positionally cloned and confirmed the underlying gene ZmPORB1(por1), as a protochlorophyllide oxidoreductase. A 13.7 kb insertion reduced the tocopherol and chlorophyll content, and the photosynthetic activity by repressing ZmPORB1 expression in embryos of NIL-K22, but did not affect the levels of the tocopherol precursors HGA(homogentisic acid)and PMP(phytyl monophosphate). Furthermore, ZmPORB1 is inducible by low oxygen and light, thereby involved in the hypoxia response in developing embryos. Concurrent with natural hypoxia in embryos, the redox state has been changed with NO increasing and H_(2)O_(2) decreasing, which lowered γ-tocopherol content via scavenging reactive nitrogen species. In conclusion, we proposed that the lower lightharvesting chlorophyll content weakened embryo photosynthesis, leading to fewer oxygen supplies and consequently diverse hypoxic responses including an elevated γ-tocopherol consumption. Our findings shed light on the mechanism for fine-tuning endogenous oxygen concentration in the maize embryo through a novel feedback pathway involving the light and low oxygen regulation of ZmPORB1 expression and chlorophyll content. | Nannan Liu Yuanhao Du Shijuan Yan Wei Chen Min Deng Shutu Xu Hong Wang Wei Zhan Wenjie Huang Yan Yin Xiaohong Yang Qiao Zhao Alisdair R.Fernie Jianbing Yan | 2024 | Science China(Life Sciences)2024，67，3： | 0 |
| 8 | A cost-effective ts CUT&Tag method for profiling transcription factor binding landscape显示文摘Knowledge of the transcription factor binding landscape(TFBL)is necessary to analyze gene regulatory networks for important agronomic traits.However,a low-cost and high-throughput in vivo chromatin profiling method is still lacking in plants.Here,we developed a transient and simplified cleavage under targets and tagmentation(tsCUT&Tag)that combines transient expression of transcription factor proteins in protoplasts with a simplified CUT&Tag without nucleus extraction.Our tsCUT&Tag method provided higher data quality and signal resolution with lower sequencing depth compared with traditional ChIP-seq.Furthermore,we developed a strategy combining tsCUT&Tag with machine learning,which has great potential for profiling the TFBL across plant development. | Leiming Wu Zi Luo Yanni Shi Yizhe Jiang Ruonan Li Xinxin Miao Fang Yang Qing Li Han Zhao Jiquan Xue Shutu Xu Tifu Zhang Lin Li | 2022 | Journal of Integrative Plant Biology2022，64，11： | 0 |
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