Browsing by Person "Liu, Wenxin"

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    Genetic dissection of hybrid performance and heterosis for yield-related traits in maize
    (2021) Li, Dongdong; Zhou, Zhiqiang; Lu, Xiaohuan; Jiang, Yong; Li, Guoliang; Li, Junhui; Wang, Haoying; Chen, Shaojiang; Li, Xinhai; Würschum, Tobias; Reif, Jochen C.; Xu, Shizhong; Li, Mingshun; Liu, Wenxin
    Heterosis contributes a big proportion to hybrid performance in maize, especially for grain yield. It is attractive to explore the underlying genetic architecture of hybrid performance and heterosis. Considering its complexity, different from former mapping method, we developed a series of linear mixed models incorporating multiple polygenic covariance structures to quantify the contribution of each genetic component (additive, dominance, additive-by-additive, additive-by-dominance, and dominance-by-dominance) to hybrid performance and midparent heterosis variation and to identify significant additive and non-additive (dominance and epistatic) quantitative trait loci (QTL). Here, we developed a North Carolina II population by crossing 339 recombinant inbred lines with two elite lines (Chang7-2 and Mo17), resulting in two populations of hybrids signed as Chang7-2 × recombinant inbred lines and Mo17 × recombinant inbred lines, respectively. The results of a path analysis showed that kernel number per row and hundred grain weight contributed the most to the variation of grain yield. The heritability of midparent heterosis for 10 investigated traits ranged from 0.27 to 0.81. For the 10 traits, 21 main (additive and dominance) QTL for hybrid performance and 17 dominance QTL for midparent heterosis were identified in the pooled hybrid populations with two overlapping QTL. Several of the identified QTL showed pleiotropic effects. Significant epistatic QTL were also identified and were shown to play an important role in ear height variation. Genomic selection was used to assess the influence of QTL on prediction accuracy and to explore the strategy of heterosis utilization in maize breeding. Results showed that treating significant single nucleotide polymorphisms as fixed effects in the linear mixed model could improve the prediction accuracy under prediction schemes 2 and 3. In conclusion, the different analyses all substantiated the different genetic architecture of hybrid performance and midparent heterosis in maize. Dominance contributes the highest proportion to heterosis, especially for grain yield, however, epistasis contributes the highest proportion to hybrid performance of grain yield.
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    Genetic dissection of phosphorus use efficiency and genotype-by-environment interaction in maize
    (2022) Li, Dongdong; Li, Guoliang; Wang, Haoying; Guo, Yuhang; Wang, Meng; Lu, Xiaohuan; Luo, Zhiheng; Zhu, Xintian; Weiß, Thea Mi; Roller, Sandra; Chen, Shaojiang; Yuan, Lixing; Würschum, Tobias; Liu, Wenxin
    Genotype-by-environment interaction (G-by-E) is a common but potentially problematic phenomenon in plant breeding. In this study, we investigated the genotypic performance and two measures of plasticity on a phenotypic and genetic level by assessing 234 maize doubled haploid lines from six populations for 15 traits in seven macro-environments with a focus on varying soil phosphorus levels. It was found intergenic regions contributed the most to the variation of phenotypic linear plasticity. For 15 traits, 124 and 31 quantitative trait loci (QTL) were identified for genotypic performance and phenotypic plasticity, respectively. Further, some genes associated with phosphorus use efficiency, such as Zm00001eb117170, Zm00001eb258520, and Zm00001eb265410, encode small ubiquitin-like modifier E3 ligase were identified. By significantly testing the main effect and G-by-E effect, 38 main QTL and 17 interaction QTL were identified, respectively, in which MQTL38 contained the gene Zm00001eb374120, and its effect was related to phosphorus concentration in the soil, the lower the concentration, the greater the effect. Differences in the size and sign of the QTL effect in multiple environments could account for G-by-E. At last, the superiority of G-by-E in genomic selection was observed. In summary, our findings will provide theoretical guidance for breeding P-efficient and broadly adaptable varieties.
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    Genetic dissection of phosphorus use efficiency in a maize association population under two P levels in the field
    (2021) Li, Dongdong; Wang, Haoying; Wang, Meng; Li, Guoliang; Chen, Zhe; Leiser, Willmar L.; Weiß, Thea Mi; Lu, Xiaohuan; Wang, Ming; Chen, Shaojiang; Chen, Fanjun; Yuan, Lixing; Würschum, Tobias; Liu, Wenxin
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    How can we breed for phosphate efficiency in maize (Zea mays)?
    (2022) Weiß, Thea M.; Li, Dongdong; Roller, Sandra; Liu, Wenxin; Hahn, Volker; Leiser, Willmar L.; Würschum, Tobias
    Future farming is required to produce high yields with reduced inputs. Increased fertilizer prices and policy goals underline the need to breed for nutrient‐efficient varieties. We therefore conducted a multienvironmental field trial comprising 400 maize genotypes, half elite lines and half doubled haploid lines from six European landraces and assessed yield parameters and corresponding phosphorus concentrations at two developmental stages. From these traits, we derived several measures for phosphate efficiency and evaluated them phenotypically and genetically. The results of this study revealed that ample variation for phosphate efficiency is present in maize. However, while elite material clearly outperformed all landraces with regard to yield‐related traits, some landrace genotypes indicated superior early development characteristics. The phosphate efficiency measures showed a complex genetic architecture, and hence, genomic selection appears best suited to assist their improvement. Taken together, breeding for phosphate efficiency is feasible but should be performed under the same conditions in which the crops are eventually grown because phosphate efficiency and what is deemed a sustainable P balance largely depends on the context.
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    Maize characteristics estimation and classification by spectral data under two soil phosphorus levels
    (2022) Qiao, Baiyu; He, Xiongkui; Liu, Yajia; Zhang, Hao; Zhang, Lanting; Liu, Limin; Reineke, Alice-Jacqueline; Liu, Wenxin; Müller, Joachim
    As an essential element, the effect of Phosphorus (P) on plant growth is very significant. In the early growth stage of maize, it has a high sensitivity to the deficiency of phosphorus. The main purpose of this paper is to monitor the maize status under two phosphorus levels in soil by a nondestructive testing method and identify different phosphorus treatments by spectral data. Here, the Analytical Spectral Devices (ASD) spectrometer was used to obtain canopy spectral data of 30 maize inbred lines in two P-level fields, whose reflectance differences were compared and the sensitive bands of P were discovered. Leaf Area Index (LAI) and yield under two P levels were quantitatively analyzed, and the responses of different varieties to P content in soil were observed. In addition, the correlations between 13 vegetation indexes and eight phenotypic parameters were compared under two P levels so as to find out the best vegetation index for maize characteristics estimation. A Back Propagation (BP) neural network was used to evaluate leaf area index and yield, and the corresponding prediction model was established. In order to classify different P levels of soil, the method of support vector machine (SVM) was applied. The results showed that the sensitive bands of P for maize canopy included 763 nm, 815 nm, and 900–1000 nm. P-stress had a significant effect on LAI and yield of most varieties, whose reduction rate reached 41% as a whole. In addition, it was found that the correlations between vegetation indexes and phenotypic parameters were weakened under low-P level. The regression coefficients of 0.75 and 0.5 for the prediction models of LAI and yield were found by combining the spectral data under two P levels. For the P-level identification in soil, the classification accuracy could reach above 86%. These abilities potentially allow for phenotypic parameters prediction of maize plants by spectral data and different phosphorus contents identification with unknown phosphorus fertilizer status.
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    Meta-quantitative trait loci analysis and candidate gene mining for drought tolerance-associated traits in maize (Zea mays L.)
    (2024) Li, Ronglan; Wang, Yueli; Li, Dongdong; Guo, Yuhang; Zhou, Zhipeng; Zhang, Mi; Zhang, Yufeng; Würschum, Tobias; Liu, Wenxin
    Drought is one of the major abiotic stresses with a severe negative impact on maize production globally. Understanding the genetic architecture of drought tolerance in maize is a crucial step towards the breeding of drought-tolerant varieties and a targeted exploitation of genetic resources. In this study, 511 quantitative trait loci (QTL) related to grain yield components, flowering time, and plant morphology under drought conditions, as well as drought tolerance index were collected from 27 published studies and then projected on the IBM2 2008 Neighbors reference map for meta-analysis. In total, 83 meta-QTL (MQTL) associated with drought tolerance in maize were identified, of which 20 were determined as core MQTL. The average confidence interval of MQTL was strongly reduced compared to that of the previously published QTL. Nearly half of the MQTL were confirmed by co-localized marker-trait associations from genome-wide association studies. Based on the alignment of rice proteins related to drought tolerance, 63 orthologous genes were identified near the maize MQTL. Furthermore, 583 candidate genes were identified within the 20 core MQTL regions and maize–rice homologous genes. Based on KEGG analysis of candidate genes, plant hormone signaling pathways were found to be significantly enriched. The signaling pathways can have direct or indirect effects on drought tolerance and also interact with other pathways. In conclusion, this study provides novel insights into the genetic and molecular mechanisms of drought tolerance in maize towards a more targeted improvement of this important trait in breeding.