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Yongquan Luo

Publications and source records attributed to Yongquan Luo.

4 recordsLinked to original sources

Screening and identification of the ncRNA-mRNA regulatory network associated with DNA methylation in goose embryonic myoblasts.

BACKGROUND: Local goose breeds Shitou and Wuzong exhibit distinct growth rates, implying divergent embryonic muscle development. This study used embryonic myoblasts from the Magang goose, an established model with superior growth traits, to explore the underlying common regulatory mechanisms. Extending our previous findings that 5-AZA (DNA methylation inhibitor) and BC339 (DNA hydroxylation inhibitor) oppositely affect myoblast proliferation and differentiation, we performed whole-transcriptome sequencing on inhibitor-treated goose embryonic myoblasts. This aimed to identify DNA methylation-mediated ncRNA-mRNA networks governing myoblast fate, with key interactions being functionally validated. RESULT: 5-AZA significantly promotes cell proliferation and differentiation by inhibiting DNA methyltransferase activity and reducing DNA methylation levels, whereas BC339 significantly suppresses cell proliferation and differentiation by inhibiting demethylation and increasing DNA methylation levels. Specifically, we identified 6,309 mRNAs, 579 lncRNAs, 194 miRNAs, and 825 circRNAs that were differentially expressed in response to 5-AZA and BC339 treatment. Based on GO and KEGG enrichment analyses, differentially expressed genes related to muscle development were selected to construct a ceRNA network. This network comprises 5 differentially expressed lncRNAs (DELs: MSTRG.17572.1, XR_001211738.1, MSTRG.1886.1, XR_001212555.1, MSTRG.8995.2), 2 differentially expressed circRNAs (DECs: novel_circ_029953, novel_circ_017636), 11 differentially expressed miRNAs (DEMs: miR-383-x, miR-10174-y, miR-191-x, miR-24-x, miR-9619-y, novel-m0303-5p, novel-m0105-3p, miR-204-x, miR-211-z, novel-m0075, miR-26-y), 5 differentially expressed genes (DEGs: KIF3A, CCND1, PPM1A, Table 2, TGFBR1), forming a total of 24 interactions. This study identified miR-9619-y as a critical negative regulator of goose embryonic myoblast development through targeted inhibition of CCND1. Dual-luciferase reporter assays confirmed the direct binding of miR-9619-y to the 3'-untranslated region of CCND1. Functional experiments demonstrated that overexpression of miR-9619-y significantly reduced the EdU-positive cell ratio and myotube area percentage, accompanied by cell cycle arrest at the G0/G1 phase. Conversely, inhibition of miR-9619-y promoted myoblast proliferation and differentiation while decreasing the proportion of cells in G0/G1 phase. During the proliferation stage, miR-9619-y overexpression significantly suppressed CCND1 expression at both mRNA and protein levels, down-regulated MyoD expression, and reduced Myf5 mRNA abundance; whereas miR-9619-y inhibition up-regulated these genes and their corresponding proteins. During the differentiation stage, overexpression of miR-9619-y similarly decreased the mRNA levels of CCND1, Myh1, and MyoG, as well as the protein levels of MyHC and CCND1, with inhibition producing the opposite effects. CONCLUSION: In this study, we predicted a ceRNA network based on bioinformatics analysis governing goose embryonic myoblast development, identifying key molecular components including mRNAs, miRNAs, lncRNAs, and circRNAs, along with 24 regulatory axes. Functional experiments further demonstrated that miR-9619-y arrests cell cycle progression and negatively regulates the proliferation and differentiation of goose embryonic myoblasts, as evidenced by its impact on both the mRNA and protein expression of key myogenic factors through targeted inhibition of CCND1. These findings, together with the bioinformatically predicted ceRNA network, suggest potential complex post-transcriptional regulatory mechanisms underlying myogenesis in geese and offer candidate molecular targets for genetic improvement of meat production performance in waterfowl breeding programs.

Animals↗

Designing, testing, and validating a focused stem cell microarray for characterization of neural stem cells and progenitor cells.

Fetal neural stem cells (NSCs) have received great attention not only for their roles in normal development but also for their potential use in the treatment of neurodegenerative disorders. To develop a robust method of assessing the state of stem cells, we have designed, tested, and validated a rodent NSC array. This array consists of 260 genes that include cell type-specific markers for embryonic stem (ES) cells and neural progenitor cells as well as growth factors, cell cycle-related genes, and extracellular matrix molecules known to regulate NSC biology. The 500-bp polymerase chain reaction products amplified and validated by using gene-specific primers were arrayed along with positive controls. Blanks were included for quality control, and some genes were arrayed in duplicate. No cross-hybridization was detected. The quality of the arrays and their sensitivity were also examined by using probes prepared by conventional reverse transcriptase or by using amplified probes prepared by linear polymerase replication (LPR). Both methods showed good reproducibility, and probes prepared by LPR labeling appeared to detect expression of a larger proportion of expressed genes. Expression detected by either method could be verified by RT-PCR with high reproducibility. Using these stem cell chips, we have profiled liver, ES, and neural cells. The cell types could be readily distinguished from each other. Nine markers specific to mouse ES cells and 17 markers found in neural cells were verified as robust markers of the stem cell state. Thus, this focused neural stem array provides a convenient and useful tool for detection and assessment of NSCs and progenitor cells and can reliably distinguish them from other cell populations.

Animals↗

A link between maze learning and hippocampal expression of neuroleukin and its receptor gp78.

Neuroleukin (NLK) is a multifunctional protein involved in neuronal growth and survival, cell motility and differentiation, and glucose metabolism. We report herein that hippocampal expression of NLK and its receptor gp78 is associated with maze learning in rats. First, mRNA levels of NLK and gp78 were significantly increased in hippocampi of male Fischer-344 rats following training in the Stone T-maze and the Morris water maze. Second, a parallel increase was found in hippocampal NLK and gp78 proteins after maze learning. Third, NLK and gp78 mRNA and protein expression in hippocampus was reduced in a group of aged rats that showed more errors during the acquisition of the Stone maze task as compared with young rats. Finally, application of recombinant NLK to hippocampal neurons significantly enhanced glutamate-induced ion currents, functional molecular changes that have been correlated with learning in vivo. Taken together, our results identify a novel association of hippocampal expression of NLK and its receptor gp78 with rat maze learning. Interaction of NLK with gp78 and subsequent signaling may strengthen synaptic mechanisms underlying learning and memory formation.

Aging↗

Microarray analysis of selected genes in neural stem and progenitor cells.

To access and compare gene expression in fetal neuroepithelial cells (NEPs) and progenitor cells, we have used microarrays containing approximately 500 known genes related to cell cycle regulation, apoptosis, growth and differentiation. We have identified 152 genes that are expressed in NEPs and 209 genes expressed by progenitor cells. The majority of genes (141) detected in NEPs are also present in progenitor populations. There are 68 genes specifically expressed in progenitors with little or no expression in NEPs, and a few genes that appear to be present exclusively in NEPs. Using cell sorting, RT-PCR, in situ hybridization or immunocytochemistry, we have examined the segregation of expression to neuronal and glial progenitors, and identified several that appeared to be enriched in neuronal (e.g. CDK5, neuropilin, EphrinB2, FGF11) or glial (e.g. CXCR4, RhoC, CD44, tenascin C) precursors. Our data provide a first report of gene expression profiles of neural stem and progenitor cells at early stages of development, and provide evidence for the potential roles of specific cell cycle regulators, chemokines, cytokines and extracellular matrix molecules in neural development and lineage segregation.

Animals↗