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Zifeng Guo

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Zifeng Guo
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Zifeng Guo

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Now showing 1 - 7 of 7
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    Genomic insights into the modifications of spike morphology traits during wheat breeding
    (John Wiley & Sons Ltd., 2024) Yangyang Liu; Rui Yu; Liping Shen; Mengjing Sun; Yanchun Peng; Qingdong Zeng; Kuocheng Shen; Xuchang Yu; He Wu; Botao Ye; Ziying Wang; Zhiweng Sun; Danning Liu; Xiaohui Sun; Zhiliang Zhang; Jiayu Dong; Jing Dong; Dejun Han; He Zhonghu; Yuanfeng Hao; Jianhui Wu; Zifeng Guo
    Publication
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    The wheat sucrose synthase gene TaSus1 is a determinant of grain number per spike
    (ICS, 2024) Liping Shen; Lili Zhang; Changbin Yin; Xiaowan Xu; Yangyang Liu; Kuocheng Shen; He Wu; Zhiwen Sun; Ke Wang; He Zhonghu; Xueyong Zhang; Chenyang Hao; Jian Hou; Aoyue Bi; Xuebo Zhao; Daxing Xu; Botao Ye; Xuchang Yu; Ziying Wang; Danni Liu; Yuanfeng Hao; Fei Lu; Zifeng Guo
    Publication
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    Development of high-resolution multiple-SNP arrays for genetic analyses and molecular breeding through genotyping by target sequencing and liquid chip
    (Elsevier, 2021) Zifeng Guo; Quannv Yang; Feifei Huang; Hongjian Zheng; Zhiqin Sang; YanFen Xu; Cong Zhang; Kunsheng Wu; Jiajun Tao; Prasanna, B.M.; Olsen, M.; Yunbo Wang; Jianan Zhang; Yunbi Xu
    Publication
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    Factors affecting genomic selection revealed by empirical evidence in maize
    (Elsevier, 2018) Xiaogang Liu; Hongwu Wang; Hui Wang; Zifeng Guo; Xiaojie Xu; Jiacheng Liu; Shanhong Wang; Wen-Xue Li; Cheng Zou; Prasanna, B.M.; Olsen, M.; Changling Huang; Yunbi Xu
    Genomic selection (GS) as a promising molecular breeding strategy has been widely implemented and evaluated for plant breeding, because it has remarkable superiority in enhancing genetic gain, reducing breeding time and expenditure, and accelerating the breeding process. In this study the factors affecting prediction accuracy (rMG) in GS were evaluated systematically, using six agronomic traits (plant height, ear height, ear length, ear diameter, grain yield per plant and hundred-kernel weight) evaluated in one natural and two biparental populations. The factors examined included marker density, population size, heritability, statistical model, population relationships and the ratio of population size between the training and testing sets, the last being revealed by resampling individuals in different proportions from a population. Prediction accuracy continuously increased as marker density and population size increased and was positively correlated with heritability; rMG showed a slight gain when the training set increased to three times as large as the testing set. Low predictive performance between unrelated populations could be attributed to different allele frequencies, and predictive ability and prediction accuracy could be improved by including more related lines in the training population. Among the seven statistical models examined, including ridge regression best linear unbiased prediction (RR-BLUP), genomic BLUP (GBLUP), BayesA, BayesB, BayesC, Bayesian least absolute shrinkage and selection operator (Bayesian LASSO), and reproducing kernel Hilbert space (RKHS), the RKHS and additive-dominance model (Add + Dom model) showed credible ability for capturing non-additive effects, particularly for complex traits with low heritability. Empirical evidence generated in this study for GS-relevant factors will help plant breeders to develop GS-assisted breeding strategies for more efficient development of varieties.
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    Maize (Zea mays L.) genome size indicated by 180-bp knob abundance is associated with flowering time
    (Nature Publishing Group, 2017) Yinqiao Jian; Cheng Xu; Zifeng Guo; Shanhong Wang; Yunbi Xu; Cheng Zou
    Flowering time is considered one of the most important agronomic traits in maize (Zea mays L.), and previous studies have indicated that this trait is correlated with genome size. We observed a significant difference in genome size between tropical and temperate inbred lines and a moderate positive correlation between genome size and 180-bp knob abundance determined by high-throughput sequencing in maize inbred lines in this study. We assembled the reads that were mapped to 180-bp knob sequences and found that the top ten abundant 180-bp knob sequences are highly variable. Moreover, our results indicate that genome size is associated with the flowering time of both male and female flowers, in both tropical and temperate inbred lines and under both tropical and temperate environments. To identify loci associated with genome size, we performed a genome-wide association study. The analysis identified three genomic regions associated with genome size, of which two were novel while the third one is located close to the known knobs K8L1 and K8L2. Overall, our results indicate that selection for breeding materials with earlier flowering times can be assisted by choosing germplasms with smaller genome sizes and that genome size can be determined based on the abundance of 180-bp knobs
    Publication
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    Development of a multiple-hybrid population for genome-wide association studies: theoretical consideration and genetic mapping of flowering traits in maize
    (Nature Publishing Group, 2017) Hui Wang; Cheng Xu; Xiaogang Liu; Zifeng Guo; Xiaojie Xu; Shanhong Wang; Chuanxiao Xie; Wen-Xue Li; Cheng Zou; Yunbi Xu
    Various types of populations have been used in genetics, genomics and crop improvement, including bi- and multi-parental populations and natural ones. The latter has been widely used in genome-wide association study (GWAS). However, inbred-based GWAS cannot be used to reveal the mechanisms involved in hybrid performance. We developed a novel maize population, multiple-hybrid population (MHP), consisting of 724 hybrids produced using 28 temperate and 23 tropical inbreds. The hybrids can be divided into three subpopulations, two diallels and NC (North Carolina Design) II. Significant genetic differences were identified among parents, hybrids and heterotic groups. A cluster analysis revealed heterotic groups existing in the parental lines and the results showed that MHPs are well suitable for GWAS in hybrid crops. MHP-based GWAS was performed using 55 K SNP array for flowering time traits, days to tassel, days to silk, days to anthesis and anthesis-silking interval. Two independent methods, PEPIS developed for hybrids and TASSEL software designed for inbred line populations, revealed highly consistent results with five overlapping chromosomal regions identified and used for discovery of candidate genes and quantitative trait nucleotides. Our results indicate that MHPs are powerful in GWAS for hybrid-related traits with great potential applications in the molecular breeding era.
    Publication
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    Development of a maize 55 K SNP array with improved genome coverage for molecular breeding
    (Springer Verlag, 2017) Cheng Xu; Yonghong Ren; Yinqiao Jian; Zifeng Guo; Zhang, Y.; Chuanxiao Xie; Junjie Fu; Hongwu Wang; Guoying Wang; Yunbi Xu; Zhang Li-Ping; Cheng Zou
    With the decrease of cost in genotyping, single nucleotide polymorphisms (SNPs) have gained wide acceptance because of their abundance, even distribution throughout the maize (Zea mays L.) genome, and suitability for high-throughput analysis. In this study, a maize 55 K SNP array with improved genome coverage for molecular breeding was developed on an Affymetrix® Axiom® platform with 55,229 SNPs evenly distributed across the genome, including 22,278 exonic and 19,425 intronic SNPs. This array contains 451 markers that are associated with 368 known genes and two traits of agronomic importance (drought tolerance and kernel oil biosynthesis), 4067 markers that are not covered by the current reference genome, 734 markers that are differentiated significantly between heterotic groups, and 132 markers that are tags for important transgenic events. To evaluate the performance of 55 K array, we genotyped 593 inbred lines with diverse genetic backgrounds. Compared with the widely-used Illumina® MaizeSNP50 BeadChip, our 55 K array has lower missing and heterozygous rates and more SNPs with lower minor allele frequency (MAF) in tropical maize, facilitating in-depth dissection of rare but possibly valuable variation in tropical germplasm resources. Population structure and genetic diversity analysis revealed that this 55 K array is also quite efficient in resolving heterotic groups and performing fine fingerprinting of germplasm. Therefore, this maize 55 K SNP array is a potentially powerful tool for germplasm evaluation (including germplasm fingerprinting, genetic diversity analysis, and heterotic grouping), marker-assisted breeding, and primary quantitative trait loci (QTL) mapping and genome-wide association study (GWAS) for both tropical and temperate maize.
    Publication