yingxiao su

Ms. yingxiao su


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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16 March 2023 in Animals
Verified
Journal Article
Open access
PDF file
QCQian Chen
Qian Chen
CHChang Huang
Chang Huang
YSyingxiao su
yingxiao su
QZQian Zhao
Qian Zhao
YPYabin Pu
Yabin Pu
SYShaohui Ye
Shaohui Ye
Skeletal muscle satellite cells (SMSCs), which are highly multifunctional muscle-derived stem cells, play an essential role in myogenesis and regeneration. Here, the transcriptional profile of SMSCs during proliferation and differentiation were constructed using the RNA-Seq method. A total of 1954 differentially expressed genes (DEGs) and 1092 differentially alternative splicing genes (DAGs) were identified including 1288 upregulated genes as well as 666 downregulated genes. GO and KEGG analyses showed that the DEGs and DAGs were enriched in the MAPK (mitogen-activated protein kinase) signaling pathway, the PI3K-Akt (phosphatidylinositol-tris-phosphate kinase 3/protein kinase B) signaling pathway, the Wnt signaling pathway, and the Ras signaling pathway. In total, 1479 alternative splice events (AS) were also identified during SMSC proliferation and differentiation. Among them, a unique AS event was the major per-mRNA splicing type, and SE was the predominant splicing pattern. Furthermore, transcription factors with AS were scanned during SMSC differentiation such as myocyte enhancer factor-2C (MEF2C) and the nuclear receptor subfamily 4 group A member 2 (NR4A2). Our results imply that MEF2C and NR4A2 can interact, and we speculate that NR4A2 and MEF2C might regulate the myogenesis of ovine SMSCs through interaction. Together, our study provides useful information on the transcriptional regulation of SMSCs during proliferation and differentiation at the transcriptional level, and provides a valuable resource for understanding the molecular mechanism of myogenesis and muscle development.

28 February 2024 in Genes
Verified
Journal Article
Open access
PDF file
CHChang Huang
Chang Huang
QZQian Zhao
Qian Zhao
QCQian Chen
Qian Chen
YSyingxiao su
yingxiao su
MYMa Yuehui
Ma Yuehui
QZQianjun Zhao
Qianjun Zhao
Runs of Homozygosity (ROH) are continuous homozygous DNA segments in diploid genomes, which have been used to estimate the genetic diversity, inbreeding levels, and genes associated with specific traits in livestock. In this study, we analyzed the resequencing data from 10 local goat breeds in Yunnan province of China and five additional goat populations obtained from a public database. The ROH analysis revealed 21,029 ROH segments across the 15 populations, with an average length of 1.27 Mb, a pattern of ROH, and the assessment of the inbreeding coefficient indicating genetic diversity and varying levels of inbreeding. iHS (integrated haplotype score) was used to analyze high-frequency Single-Nucleotide Polymorphisms (SNPs) in ROH regions, specific genes related to economic traits such as coat color and weight variation. These candidate genes include OCA2 (OCA2 melanosomal transmembrane protein) and MLPH (melanophilin) associated with coat color, EPHA6 (EPH receptor A6) involved in litter size, CDKAL1 (CDK5 regulatory subunit associated protein 1 like 1) and POMC (proopiomelanocortin) linked to weight variation and some putative genes associated with high-altitude adaptability and immune. This study uncovers genetic diversity and inbreeding levels within local goat breeds in Yunnan province, China. The identification of specific genes associated with economic traits and adaptability provides actionable insights for utilization and conservation efforts.

28 July 2026 in Journal of Animal Science and Biotechnology
Verified
Journal Article
Open access
PDF file
BZBoyu Zhang
Boyu Zhang
SQShiyuan Qiu
Shiyuan Qiu
ZDZhenWei Du
ZhenWei Du
HXHao Xiao
Hao Xiao
YSyingxiao su
yingxiao su
CZCaihong Zheng
Caihong Zheng
Background: The genetic dissection of complex traits in livestock continues to pose a significant challenge in the field of animal genetics and breeding. Although traditional genome-wide association studies (GWAS) are capable of localizing genetic variants associated with specific traits, they are insufficient to elucidate the underlying physiological mechanisms. An integrated analysis of multi-trait GWAS and multi-transcriptomic data systematically identifies key tissues and cell types influencing complex traits in beef cattle and elucidates their genetic regulatory basis. Results: We systematically mapped tissue- and cell-type-specific regulatory architectures underlying 20 economically important traits in beef cattle. Tissue-level analyses revealed distinct trait-tissue associations: fatty acid traits, including C16:0 and C20:4, were enriched in liver; carcass traits, including marbling score and carcass weight, in renal cortex/medulla and longissimus dorsi muscle; meat-quality traits such as pH in cartilaginous tissues; and total fat content in bone marrow. At cellular resolution, analysis of eight trait-associated tissues identified 38 discrete cell types. Myofibers were significantly associated with most carcass traits, including rib-eye area and backfat thickness, whereas hepatocytes emerged as key regulators of fatty acid and meat-quality traits, such as C16:0 and crude protein content. Transcription factor analysis identified cell-type-specific regulators: TBX15, SOX6, and TCF12 in myofibers; FOXA2 and NR1H4 in hepatocytes; and IRF8 and IKZF1 in microglia. Notably, hepatocytes and microglia showed complementary, trait-specific association patterns: hepatocytes were enriched for C16:0 associated saturated fatty-acid metabolic pathways, while microglia were enriched for C16:1 and unsaturated fatty-acid–related pathways, suggesting potential cross-tissue coordination in lipid regulation. Conclusions: Our study links specific tissues and cell types to phenotypic variation in beef cattle and identifies core transcriptional regulators and pathways driving trait variation. These cell-resolved maps provide mechanistic insight into how genetic variation shapes economically important traits, offering a valuable resource for functional studies, cell-informed precision breeding strategies, and the design of large-scale molecular phenotyping.