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Genying Li

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Genying Li
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Genying Li

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Now showing 1 - 6 of 6
  • Allelic variations of Puroindoline a and Puroindoline b genes in new type of synthetic hexaploid wheats from CIMMYT
    (Institute of Crop Sciences, 2007) Genying Li; Xianchun Xia; He Zhonghu; Sun, Qi-Xin
    Publication
  • Dissecting conserved cis-regulatory modules of Glu-1 promoters which confer the highly active endosperm-specific expression via stable wheat transformation
    (Elsevier, 2019) Jihu Li; Ke Wang; Genying Li; Yulian Li; Yong Zhang; Zhiyong Liu; Xingguo Ye; Xianchun Xia; He Zhonghu; Shuanghe Cao
    Wheat high-molecular-weight glutenin subunits (HMW-GS) determine dough elasticity and play an essential role in processing quality. HMW-GS are encoded by Glu-1 genes and controlled primarily at transcriptional level, implemented through the interactions between cis-acting elements and trans-acting factors. However, transcriptional mechanism of Glu-1 genes remains elusive. Here we made a comprehensive analysis of cis-regulatory elements within 1-kb upstream of the Glu-1 start codon (−1000 to −1) and identified 30 conserved motifs. Based on motif distribution pattern, three conserved cis-regulatory modules (CCRMs), CCRM1 (−300 to −101), CCRM2 (−650 to −400), and CCRM3 (−950 to −750), were defined, and their functions were characterized in wheat stable transgenic lines transformed with progressive 5′ deletion promoter
    Publication
  • Composition and functional analysis of low-molecular-weight glutenin alleles with Aroona near-isogenic lines of bread wheat
    (BioMed Central, 2012) Xiaofei Zhang; Hui Jin; Zhang, Y.; Dongcheng Liu; Genying Li; Xianchun Xia; He Zhonghu; Zhang Aimin
    Low-molecular-weight glutenin subunits (LMW-GS) strongly influence the bread-making quality of bread wheat. These proteins are encoded by a multi-gene family located at the Glu-A3, Glu-B3 and Glu-D3 loci on the short arms of homoeologous group 1 chromosomes, and show high allelic variation. To characterize the genetic and protein compositions of LMWGS alleles, we investigated 16 Aroona near-isogenic lines (NILs) using SDS-PAGE, 2DPAGE and the LMW-GS gene marker system. Moreover, the composition of glutenin macropolymers, dough properties and pan bread quality parameters were determined for functional analysis of LMW-GS alleles in the NILs. Results Using the LMW-GS gene marker system, 14?20 LMW-GS genes were identified in individual NILs. At the Glu-A3 locus, two m-type and 2?4 i-type genes were identified and their allelic variants showed high polymorphisms in length and nucleotide sequences. The Glu-A3d allele possessed three active genes, the highest number among Glu-A3 alleles. At the Glu-B3 locus, 2?3 m-type and 1?3 s-type genes were identified from individual NILs. Based on the different compositions of s-type genes, Glu-B3 alleles were divided into two groups, one containing Glu-B3a, B3b, B3f and B3g, and the other comprising Glu-B3c, B3d, B3h and B3i. Eight conserved genes were identified among Glu-D3 alleles, except for Glu-D3f. The protein products of the unique active genes in each NIL were detected using protein electrophoresis. Among Glu-3 alleles, the Glu-A3e genotype without i-type LMW-GS performed worst in almost all quality properties. Glu-B3b, B3g and B3i showed better quality parameters than the other Glu-B3 alleles, whereas the Glu-B3c allele containing s-type genes with low expression levels had an inferior effect on bread-making quality. Due to the conserved genes at Glu-D3 locus, Glu-D3 alleles showed no significant differences in effects on all quality parameters. Conclusions This work provided new insights into the composition and function of 18 LMW-GS alleles in bread wheat. The variation of i-type genes mainly contributed to the high diversity of Glu-A3 alleles, and the differences among Glu-B3 alleles were mainly derived from the high polymorphism of s-type genes. Among LMW-GS alleles, Glu-A3e and Glu-B3c represented inferior alleles for bread-making quality, whereas Glu-A3d, Glu-B3b, Glu-B3g and Glu-B3i were correlated with superior bread-making quality. Glu-D3 alleles played minor roles in determining quality variation in bread wheat. Thus, LMW-GS alleles not only affect dough extensibility but greatly contribute to the dough resistance, glutenin macro-polymers and bread quality.
    Publication
  • Molecular mapping of powdery mildew resistance gene in wheat cultivar Jimai 22
    (Institute of Crop Sciences, 2009) Guihong Yin; Genying Li; He Zhonghu; Jianjun Liu; Wang Hui; Xianchun Xia
    Wheat powdery mildew, caused by Blumeria graminis f. sp. tritici, is one of the most important diseases of wheat (Triticum aestivum L.) worldwide. Breeding resistant wheat cultivars is the most economical and effective approach to control the disease. Jimai 22, a newly released wheat cultivar with high yield, broad adaptability, and good quality, is related to broad-sprectrum resistance to the isolates of B. graminis f. sp. tritici at both seedling and adult plant stages. To map the resistance gene of Jimai 22 on wheat chromosome, we used a highly virulent isolate E20 to screen the F2 plants and F2:3 lines derived from the cross of Jimai 22/Chinese Spring. Genetic analysis indicated that Jimai 22 carried a single dominant genefor resistance to powdery mildew, designated PmJM22 tentatively. Using bulked segregant analysis (BSA) with SSR and STS markers, PmJM22 was located to chromosome 2BL. Linkage analysis indicated that the resistance gene was linked to four SSR and five EST markers, with genetic distances from 7.7 (Xwmc149) to 31.3 cM (Xbarc101).Based on the origins, chromosome locations, and reaction patterns, PmJM22 is different from all the known powdery mildew resistance genes Pm6, Pm26, Pm33, and Mlzec1 on chromosome 2BL.
    Publication
  • Distribution of grain hardness and puroindoline alleles in landraces, historical and current wheats in Shandong province
    (Institute of Crop Sciences, 2007) Genying Li; Xianchun Xia; He Zhonghu; Sun, Qi-Xin; Huang Cheng-Yan
    Studies on the grain hardness and puroindolines alleles in wheat cultivars released in different historical periods, are helpful for breeding wheat cultivar with optimal endosperm texture. In the present study, 523 accessions from Shandong Province including 431 landraces, 63 historical cultivars and 29 current cultivars were used to evaluate the SKCS hardness and distribution of puroindoline alleles (Pins). Distribution of grain hardness differed in landraces, historical cultivars and current wheats, with 75.6%, 20.4%, and 3.9% of hard texture, and 20.4%, 19.0%, and 13.8% of mixed wheats, and 3.9%, 68.3%, and 58.6% of soft grains, respectively. Six genotypes of Pina and Pinb were present in landraces, in which Pina-D1a/Pinb-D1p and Pina-D1b/Pinb-D1b were the dominant genotypes, accounting for 38.0% and 59.6% of hard wheat, respectively. Compared with landraces, the polymorphism of Pina and Pinb was decreased in historical cultivars. Pina-D1b/Pinb-D1a, Pina-D1a/Pinb-D1b, and Pina-D1a/Pinb-D1p accounted for 37.5%, 37.5%, and 25.0% of hard wheat, respectively, whereas, Pina-D1a/Pinb-D1b was the only genotype presented in hard genotype of current cultivars surveyed. A novel Pinb allele with double mutations at the positions of 96th (C to A) and 265th (deletion of A) was found in three landraces, and was designated as Pinb-D1aa.
    Publication
  • Development of a fingerprinting database and assembling an SSR reference kit for genetic diversity analysis of wheat
    (Institute of Crop Sciences, 2006) Genying Li; Dreisigacker, S.; Warburton, M.; Xianchun Xia; He Zhonghu; Sun, Qi-Xin
    Understanding of the current and expanded genetic diversity is very important for raising the yield of wheat. Genetic diversity based on molecular markers has been studied in plants for over thirty decades. SSR is the currently most popular marker system in wheat. In order to utilize the diversity held in NARS (National Agricultural Research Station) and CGIAR (Consultative Group on International Agricultural Research) germplasm collections, one of the GCP’s (Generation Challenge Program) premier capacity building activities is to build databases that contain traditional and molecular data on germplasm so that scientists all over the world can access information with relevance to their region on traits, genes, and sequences. In the present study, a fingerprinting database was established containing 134 SSR primers and 2 457 wheat genotypes with the data from CIMMYT and three collaborators: ICARDA, Agropolis, and CAAS. On the base of the database, a SSR reference kit for wheat genetic diversity analysis was developed, which will facilitate the use of this data in new projects and cross-laboratory comparisons. In total, 46 SSR primers with comparatively high polymorphism were selected as the reference markers to constitute the standard allele kit, 334 genotypes fingerprinted within the GCP tier 1 project “Genotyping a composite germplasm set in wheat” were chosen to represent the SSR allele kit consisting of 794 alleles amplified by 46 SSR markers. Genotypes were originally selected and DNA extracted by CIMMYT and 3 additional collaborators: ICARDA, Agropolis, and CAAS. These 334 genotypes, when taken as a group, amplify every allele seen for the wheat genotypes for all the 46 SSRs. The Genotypes were originally amplified with 26 SSRs at CIMMYT, with 8 SSRs at INRA, France, and with 12 SSRs at CAAS. Genotypes were amplified with all SSRs at CIMMYT again to confirm the results. For reamplification at CIMMYT, forward primers were labeled at the 5’ end with either one of three phosphoramidite fluorescent dyes 6-carboxyflouresein (6-Fam), tetrachloro-6-carboxyflouresein (Tet) or hexachloro-6- carboxyflouresein (Hex). PCR-reactions were carried out in an MJ-Research thermocycler model PTC225. Amplification products were separated on an ABI-Prism SequencerTM377 using 4.5% polyacrylamide denaturing gels. Fragment sizes were calculated semi-automatically with the computer software GeneScan 3.1 by comparing to fragments of an internal size standard (GeneScan 350 or 500) labeled with N,N,N,N, -tetramethyl-6-carboxyrhodamine (Tamra). GeneScan fragments were assigned to alleles using the category function of the software Genotyper 2.1. The two genotypes, Opata and Synthetic were run in each gel as controls. Finally, a SSR reference kit was assembled which includes 46 pairs of SSR primers, protocols (PCR condition, detection of polymorphisms, etc), description of polymorphism in the reference samples, reference DNA samples for a complete range of repeatable 592 alleles, methods for comparing new to preexisting data, and classification of various genotypes. The database and the reference kit will provide a powerful tool for genetic diversity studies of wheat germplasm worldwide.
    Publication