Runbang Zhu

Runbang Zhu

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

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Runbang Zhu has a total of 19 co-authors. Here are the top co-authors by number of shared publications:

  • Jianfei Chen

    Jiangsu Key Laboratory of Sericultural and Animal Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang 212100, China; Key Laboratory of Silkworm and Mulberry Genetic Improvement, Ministry of Agriculture and Rural Affairs, Sericultural Scientific Research Center, Chinese Academy of Agricultural Sciences, Zhenjiang 212100, China

    2 shared publications
  • Manman Shen

    Jiangsu Key Laboratory of Sericultural and Animal Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang 212100, China

    2 shared publications
  • Xiaotong Zheng

    Jiangsu Key Laboratory of Sericultural and Animal Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang 212100, China

    2 shared publications
  • Ashi Li

    Jiangsu Key Laboratory of Sericultural and Animal Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, China

    1 shared publication
  • Cangning Zhang

    Jiangsu Key Laboratory of Sericultural and Animal Biotechnology, School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang 212100, China

    1 shared publication
  • Guoying Hua

    Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China

    1 shared publication

Latest Publications

  • Open Access

    Association analysis and in silico functional predictions of RMDN2 variants in chickens

    by Ashi Li, Yuechen Liao, Yangqiwen Luo, Runbang Zhu, Cangning Zhang, Xingguo Wang, Meng Ma, LiumeiLiumei Sun, Liang Qu, Manman Shen

    Objective: Microtubule dynamics regulator protein 2 (RMDN2) plays a crucial role in cell division, cytoskeleton maintenance, and various cellular processes, thereby establishing it as a candidate gene influencing chicken follicle development in our previous studies. This research aims to explore single-nucleotide polymorphisms (SNPs), perform phylogenetic analysis, and assess sequence characteristics of RMDN2, offering valuable insights for molecular marker-assisted breeding and enhancing the understanding of its regulatory mechanisms.Methods: SNPs within the RMDN2 coding sequence region were identified in an F2 resource population. Bioinformatics tools were employed to investigate the effects of SNP mutations on the structure and function of RMDN2 protein. Additionally, a phylogenetic tree was constructed to elucidate the potential mechanisms underlying the role of RMDN2 in chicken laying traits.Results: Four novel exonic SNPs were identified: SNP1 (c.250G>A, p.Val84Ile), SNP2 (c.270G>C, p.Lys90Asn), SNP3 (c.533G>T, p.Gly178Val), and SNP4 (c.606G>A). The heterozygous genotypes of SNP1, SNP3, and SNP4 showed a significant association with increased egg number at 66 weeks (p<0.05). In contrast, the heterozygous genotype of SNP2 is associated with higher body weight at first egg (BWFE) (p<0.05). Notably, the H1H1 haplotype combination demonstrated a significant association with reduced BWFE, body weight at 105 days, and first egg weight (p<0.05). Missense mutations in SNP1, SNP2, and SNP3 may influence the hydrophilic/hydrophobic properties, transmembrane regions, functional domains, and secondary structure of the RMDN2 protein, potentially reducing its stability. Phylogenetic analysis demonstrated complete sequence homology between chicken and quail, indicating substantial conservation within species of the same order, while showing a marked decrease across different taxonomic orders.Conclusion: These findings enrich the candidate gene pool associated with the regulation of laying traits in chickens. However, further validation through in vivo and in vitro experiments remains necessary to strengthen the theoretical foundation for molecular breeding strategies.

  • Open Access

    Supplemental L-arginine promotes hepatocyte proliferation and alters liver fatty acid metabolism in the late embryonic phase: an RNA-seq analysis

    by Ziwei Chen, Xiaotong Zheng, Xin Shu, Guoying Hua, Runbang Zhu, Liumei Sun, Jianfei Chen


  • Open Access

    Establishment of a Steatosis Model in LMH Cells, Chicken Embryo Hepatocytes, and Liver Tissues Based on a Mixture of Sodium Oleate and Palmitic Acid

    by Wuchao Zhuang, Ziwei Chen, Xin Shu, Jilong Zhang, Runbang Zhu, Manman Shen, Jianfei Chen, Xiaotong Zheng

    Research on hepatic steatosis in animal husbandry has been a prominent area of study. Developing an appropriate in vitro cellular steatosis model is crucial for comprehensively investigating the mechanisms involved in liver lipid deposition in poultry and for identifying potential interventions to address abnormalities in lipid metabolism. The research on the methods of in vitro liver steatosis in chickens, particularly the effects of different fat mixtures, is still lacking. In this study, LMH cells were utilized to investigate the effects of OA, SO, PA, SP, and their pairwise combinations on steatosis development, with the aim of identifying the optimal conditions for inducing steatosis. Analysis of triglyceride (TG) content in LMH cells revealed that OA and SP had limited efficacy in increasing TG content, while a combination of SO and PA in a 1:2 ratio exhibited the highest TG content. Moreover, Oil Red O staining results in LMH cells demonstrated that the combination treatment had a more pronounced induction effect compared to 0.375 mM SO. Additionally, RNA-seq analysis showed that 0.375 mM SO significantly influenced the expression of genes associated with fatty acid metabolism compared to the control group, whereas the combination of SO and PA led to an enrichment of key GO terms associated with programmed cell death. These findings suggest that varying conditions of cellular steatosis could lead to distinct disruptions in gene expression. The optimal conditions for inducing steatosis in LMH cells were also tested on chicken embryonic liver cells and embryos. TG detection and Oil Red O staining assays showed that the combination of SO and PA successfully induced steatosis. However, the gene expression pattern differed from that of LMH cells. This study lays the foundations for further investigations into avian hepatic steatosis.