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Jiankang Wang

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Jiankang Wang
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Jiankang Wang

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Now showing 1 - 4 of 4
  • Enhancing genetic gain through genomic selection: from livestock to plants
    (Elsevier, 2020) Yunbi Xu; Xiaogang Liu; Junjie Fu; Hongwu Wang; Jiankang Wang; Changling Huang; Prasanna, B.M.; Olsen, M.; Guoying Wang; Zhang Aimin
    Publication
  • Quantitative genetic studies with applications in plant breeding in the omics era
    (Elsevier, 2020) Jiankang Wang; Crossa, J.; Junyi Gai
    Publication
  • Use of genomic selection and breeding simulation in cross prediction for improvement of yield and quality in wheat (Triticum aestivum L.)
    (Elsevier, 2018) Ji Yao; Dehui Zhao; Xinmin Chen; Yong Zhang; Jiankang Wang
    In wheat breeding, it is a difficult task to select the most suitable parents for making crosses aimed at the improvement of both grain yield and grain quality. By quantitative genetics theory, the best cross should have high progeny mean and large genetic variance, and ideally yield and quality should be less negatively or positively correlated. Usefulness is built on population mean and genetic variance, which can be used to select the best crosses or populations to achieve the breeding objective. In this study, we first compared five models (RR-BLUP, Bayes A, Bayes B, Bayes ridge regression, and Bayes LASSO) for genomic selection (GS) with respect to prediction of usefulness of a biparental cross and two criteria for parental selection, using simulation. The two parental selection criteria were usefulness and midparent genomic estimated breeding value (GEBV). Marginal differences were observed among GS models. Parental selection with usefulness resulted in higher genetic gain than mid parent GEBV. In a population of 57 wheat fixed lines genotyped with 7588 selected markers, usefulness of each biparental cross was calculated to evaluate the cross performance, a key target of breeding programs aimed at developing pure lines. It was observed that progeny mean was a major determinant of usefulness, but the usefulness ratings of quality traits were more influenced by their genetic variances in the progeny population. Near-zero or positive correlations between yield and major quality traits were found in some crosses, although they were negatively correlated in the population of parents. A selection index incorporating yield, extensibility, and maximum resistance was formed as a new trait and its usefulness for selecting the crosses with the best potential to improve yield and quality simultaneously was calculated. It was shown that applying the selection index improved both yield and quality while retaining more genetic variance in the selected progenies than the individual trait selection. It was concluded that combining genomic selection with simulation allows the prediction of cross performance in simulated progenies and thereby identifies candidate parents before crosses are made in the field for pure-line breeding programs.
    Publication
  • Revisiting the hetero-fertilization phenomenon in maize
    (Public Library of Science, 2011) Shibin Gao; Babu, R.; Yanli Lu; Martínez, C.A.; Zhuanfang Hao; Krivanek, A.F.; Jiankang Wang; Tingzhao Rong; Crouch, J.H.; Yunbi Xu
    Development of a seed DNA-based genotyping system for marker-assisted selection (MAS) has provided a novel opportunity for understanding aberrant reproductive phenomena such as hetero-fertilization (HF) by observing the mismatch of endosperm and leaf genotypes in monocot species. In contrast to conventional approaches using specific morphological markers, this approach can be used for any population derived from diverse parental genotypes. A large-scale experiment was implemented using seven F2 populations and four three-way cross populations, each with 534 to 1024 individuals. The frequency of HF within these populations ranged from 0.14% to 3.12%, with an average of 1.46%. The highest frequency of HF in both types of population was contributed by the pollen gametes. Using three-way crosses allowed, for the first time, detection of the HF contributed by maternal gametes, albeit at very low frequency (0.14%?0.65%). Four HF events identified from each of two F2 populations were tested and confirmed using 1032 single nucleotide polymorphic markers. This analysis indicated that only 50% of polymorphic markers can detect a known HF event, and thus the real HF frequency can be inferred by doubling the estimate obtained from using only one polymorphic marker. As expected, 99% of the HF events can be detected by using seven independent markers in combination. Although seed DNA-based analysis may wrongly predict plant genotypes due to the mismatch of endosperm and leaf DNA caused by HF, the relatively low HF frequencies revealed with diverse germplasm in this study indicates that the effect on the accuracy of MAS is limited. In addition, comparative endosperm and leaf DNA analysis of specific genetic stocks could be useful for revealing the relationships among various aberrant fertilization phenomena including haploidy and apomixis.
    Publication