MFMengmeng Fu

Mengmeng Fu

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article

Previous Organizations / Institutes

The organizations / institutes from the scholar's other articles in the past ten years


Mengmeng Fu has a total of 29 co-authors. Here are the top co-authors by number of shared publications:

  • Haifeng Xu

    Huai’an Key Laboratory for Agricultural Biotechnology, Key Laboratory of Germplasm Innovation in Lower Reaches of the Huaihe River, Ministry of Agriculture and Rural Affairs, Huaiyin Institute of Agricultural Sciences of Xuhuai Region in Jiangsu, Huai’an 223001, China

    4 shared publications
  • Shuguang Li

    Huai’an Key Laboratory for Agricultural Biotechnology, Key Laboratory of Germplasm Innovation in Lower Reaches of the Huaihe River, Ministry of Agriculture and Rural Affairs, Huaiyin Institute of Agricultural Sciences of Xuhuai Region in Jiangsu, Huai’an 223001, China

    4 shared publications
  • Yaqi Wang

    Huai’an Key Laboratory for Agricultural Biotechnology, Key Laboratory of Germplasm Innovation in Lower Reaches of the Huaihe River, Ministry of Agriculture and Rural Affairs, Huaiyin Institute of Agricultural Sciences of Xuhuai Region in Jiangsu, Huai’an 223001, China

    4 shared publications
  • Xiwen Yu

    Huai’an Key Laboratory for Agricultural Biotechnology, Key Laboratory of Germplasm Innovation in Lower Reaches of the Huaihe River, Ministry of Agriculture and Rural Affairs, Huaiyin Institute of Agricultural Sciences of Xuhuai Region in Jiangsu, Huai’an 223001, China

    2 shared publications
  • Xiwen Yu

    Huai’an Key Laboratory for Agricultural Biotechnology, Key Laboratory of Germplasm Innovation in Downstream of Huaihe River, Ministry of Agriculture and Rural Affairs, Huaiyin Institute of Agricultural Sciences of Xuhuai Region in Jiangsu, Huai’an 223001, China

    2 shared publications
  • Zhixin Zhao

    Huai’an Key Laboratory for Agricultural Biotechnology, Key Laboratory of Germplasm Innovation in Lower Reaches of the Huaihe River, Ministry of Agriculture and Rural Affairs, Huaiyin Institute of Agricultural Sciences of Xuhuai Region in Jiangsu, Huai’an 223001, China

    2 shared publications

Latest Publications

  • Open Access

    Genome-Wide Mapping Reveals Major and Stable Quantitative Trait Loci for Seed Oil Content in Soybean

    by Shuguang Li, Mengmeng Fu, Yaqi Wang, Xiwen Yu, Zhixin Zhao, Jinming Zhao, Na Guo, Haifeng Xu

    Seed oil content is one of the primary breeding objectives in soybean. However, the genetic basis of seed oil content remains largely unexplored. In this study, we employed a recombinant inbred line (RIL) population consisting of 201 lines derived from a cross between Feidong and Guanyun, to identify quantitative trait loci (QTLs) for seed oil content in soybean under five environments. High broad-sense heritability (92.34%) indicates a substantial genetic contribution to phenotypic variation in this population and set of environments. A high-density genetic map containing 11,220 SNP markers was constructed, spanning 2507.62 cM, with an average distance of 0.22 cM between markers. By jointly using five QTL mapping methods, a total of 24 QTLs for seed oil content were identified, including eight stable QTLs detected in at least three environments and seven QTLs identified by all five methods. Out of these QTLs, qOil-5-4, qOil-9-2 and qOil-10-3 were considered as the major and stable QTLs. Within these three major and stable QTL intervals, except that Glyma.05g244100 (GmMFT/GmST05) is an experimentally validated gene, the other six genes that were highly expressed during seed development stages were identified as putative candidate genes requiring further validation. In conclusion, the major stable QTLs and candidate genes identified in this study facilitate the dissection of the genetic architecture underlying seed oil content and hold great potential for application in developing new high-oil soybean cultivars after further fine mapping and validation in independent genetic backgrounds.

  • Open Access

    Identification of Transcription Factors of GmHPL Involved in Modulating Pathogen Stresses in Soybean

    by Yaqi Wang, Wenhuan Lyu, Shuguang Li, Mengmeng Fu, Xiwen Yu, Zhixin Zhao, Shanshan Hu, Haifeng Xu

    As an important branch of the lipoxygenase (LOX) metabolism pathway, hydroperoxide lyase (HPL) is involved in regulating plant development and defense responses. However, the upstream regulatory mechanism of HPL remains unclear in soybean. In the present study, by analyzing the upstream promoter region of the GmHPL gene, cis-elements such as MYB motifs, G-box motifs, ERE motifs and W-box motifs were predicted, which were related to the stress response. Yeast one-hybrid was employed and two transcription factors were identified, GmERF36 and GmILR3. The orthologs of ERF36 and ILR3 in Arabidopsis were involved in pathogen stress. A dual-luciferase reporter assay verified the yeast one-hybrid results and indicated that GmERF36 and GmILR3 suppressed the expression of the GmHPL protein. The qRT-PCR results indicated that GmHPL and GmERF36 initially displayed inverse expression patterns within 24 h after Colletotrichum truncatum treatment (GmERF36 was upregulated while GmHPL was downregulated); then, both of them were upregulated before decreasing. The results indicated that the response of GmHPL to pathogen stress partially depended on GmERF36. Our study gives rise to new insights into the upstream regulatory network of the GmHPL gene.

  • Open Access

    Gene Mapping of a Yellow-to-Lethal Mutation Based on Bulked-Segregant Analysis-Seq in Soybean

    by Yaqi Wang, Fangguo Chang, G M Al Amin, Shuguang Li, Mengmeng Fu, Xiwen Yu, Zhixin Zhao, Haifeng Xu, Tuanjie Zhao

    Plant photosynthesis is mainly dependent on leaf color, and this has an impact on yield. Mutants lacking in chlorophyll have been analyzed to gain insight into the genetic processes involved in photosynthesis, chloroplast development, and chlorophyll metabolism. A yellow-to-lethal mutant, ytl, was selected from the M6 generation of the 60Coγ ray irradiation-treated soybean cultivar Nannong 1138-2. The mutant exhibited reduced chlorophyll content, with the thylakoid structure disrupted. Segregation of the cross between Williams 82 (W82) and ytl indicated that a recessive allele controlled yellow-to-lethal traits. The bulked-segregant analysis (BSA)-Seq method performed preliminary mapping, followed by simple sequence repeat (SSR) marker validation and further mapping. The candidate gene was mapped to a 418 Kb region containing 53 genes. High-throughput sequencing and first-generation sequencing results showed a two bp deletion in the second exon of Glyma.08g106500, leading to a frameshift mutation in ytl. As a promising candidate gene, Glyma.08g106500 encoded a chloroplast-localized pentatricopeptide repeat (PPR) domain-containing protein involved in the assembly of chloroplast proteins. These results will contribute to cloning the mutant ytl gene and provide insight into the regulatory processes controlling photosynthesis and chloroplast development and growth in soybean.


  • Open Access

    Detection of Hub QTLs Underlying the Genetic Basis of Three Modules Covering Nine Agronomic Traits in an F2 Soybean Population

    by Mengmeng Fu, Bo Qi, Shuguang Li, Haifeng Xu, Yaqi Wang, Zhixin Zhao, Xiwen Yu, Liyuan Pan, Jiayin Yang

    Deciphering the genetic basis underlying agronomic traits is of importance for soybean improvement. However, covariation, modulated by genetic correlations between complicated traits via hub QTLs, commonly affects the efficiency and accuracy of soybean improvement. The goals of soybean improvement have nearly all focused on agronomic traits, including yield, plant type traits, and seed-related traits especially. To decipher the hub QTLs of yield, plant type, and seed, nine pertinent traits of an F2 population (181 plants) derived from a cross between KeXin No.03 and JiDou 17, which were different in multiple traits such as plant height, seed protein, and 100-seed weight, were investigated with a high-density genetic map covering 2708.63 cM. A highly significant negative phenotypic correlation (−0.95) was found between seed protein (Pro) and seed oil (Oil). A total of 35 final QTLs after combining the ones closely linked physically were identified for eight traits explaining from 0.10% to 24.63% of the phenotypic variance explained (PVE) using composite interval mapping (CIM) and inclusive composite interval mapping (ICIM) procedures, and 13 QTLs were novel genes. A genomic region on chromosome 14 (qPro14, qOil14.2, and qSw14) was associated with three seed-related traits based on the relationship within and among the three trait modules. In addition, four genomic regions were detected as hub QTLs which linked to the seed-related module and plant-type model, including the E loci (E1 and E2). From the QTL results, 31 candidate genes were annotated, including the verified genes E1, E2, and QNE1, and they were grouped into three categories of biological processes. These results illustrate the genetic architecture as correlations among various soybean traits, and the hub QTLs should provide insights into the genetic improvement of complex traits in soybean.


  • Exploring the QTL–allele constitution of main stem node number and its differentiation among maturity groups in a Northeast China soybean population

    by Mengmeng Fu, Yanping Wang, Haixiang Ren, Weiguang Du, Xingyong Yang, Deliang Wang, Yanxi Cheng, Jinming Zhao, Junyi Gai

    Northeast China (NEC) is a major soybean [Glycine max (L.) Merr.] production region in China, where the germplasm of American soybeans are mainly from. The main stem node number (MSN) is a trait related to plant type and yield potential. With the soybeans expanded to higher latitudes in NEC, earlier maturity groups (MG 0, MG 00, and MG 000) formed based on MG I + MG II (MG I+II), and correspondingly the MSN decreased. To explore the MSN quantitative trait locus (QTL)–allele constitution, 306 accessions from NEC were studied using the restricted two‐stage multilocus genome‐wide association study (RTM‐GWAS) procedure. In total, 76 MSN QTLs and 183 alleles were identified, with their genetic contribution about 0.04–9.83% per locus for a total of 65.63% for all loci. With the MSN reduction from MG I+II to MG 0, MG 00, and MG 000 (17.89 to 13.11), the changed alleles accounted for 28.42% of all alleles (6.56% for new allele emergence plus 21.86% for old allele exclusion), whereas the major part of the alleles were those inherited from MG I+II (71.58%). Thus in the evolution of MSN in the NEC soybean population, inheritance is the first genetic motivation, exclusion and selection (positive allele exclusion, 65.00%) is the second, emergence and mutation (negative allele emergence, 95.67%) is the third, and recombination among retained alleles is the fourth. A potential of 2–5 MSN improvement keeping the MG earliness was predicted, and 49 candidate genes were identified.


  • Open Access

    Mechanism of Inactivation of Escherichia coli Aspartate Aminotransferase by (S)-4-Amino-4,5-dihydro-2-furancarboxylic Acid,

    by Dali Liu, Edwin Pozharski, Mengmeng Fu, Richard B. Silverman, Dagmar Ringe

    As a potential drug to treat neurological diseases, the mechanism-based inhibitor (S)-4-amino-4,5-dihydro-2-furancarboxylic acid (S-ADFA) has been found to inhibit the γ-aminobutyric acid aminotransferase (GABA-AT) reaction. To circumvent the difficulties in structural studies of a S-ADFA−enzyme complex using GABA-AT, l-aspartate aminotransferase (l-AspAT) from Escherichia coli was used as a model PLP-dependent enzyme. Crystal structures of the E. coli aspartate aminotransferase with S-ADFA bound to the active site were obtained via cocrystallization at pH 7.5 and 8. The complex structures suggest that S-ADFA inhibits the transamination reaction by forming adducts with the catalytic lysine 246 via a covalent bond while producing 1 equiv of pyridoxamine 5′-phosphate (PMP). Based on the structures, formation of the K246-S-ADFA adducts requires a specific initial binding configuration of S-ADFA in the l-AspAT active site, as well as deprotonation of the ε-amino group of lysine 246 after the formation of the quinonoid and/or ketimine intermediate in the overall inactivation reaction.