Chunlin Yu

Chunlin Yu


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

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

Representative Publications

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17 July 2023 in Genes
Verified
Journal Article
Open access
PDF file
JLJingjing Li
Jingjing Li
QHQinke Huang
Qinke Huang
CYChaowu Yang
Chaowu Yang
CYChunlin Yu
Chunlin Yu
ZZZhang Zengrong
Zhang Zengrong
MQMohan Qiu
Mohan Qiu
Reducing abdominal fat (AF) accumulation and increasing the level of intramuscular fat (IMF) simultaneously is a major breeding goal in the poultry industry. To explore the different molecular mechanisms underlying AF and IMF, gene expression profiles in the breast muscle (BM) and AF from three chicken breeds were analyzed. A total of 4737 shared DEGs were identified between BM and AF, of which 2602 DEGs were upregulated and 2135 DEGs were downregulated in the BM groups compared with the AF groups. DEGs involved in glycerophospholipid metabolism and glycerolipid metabolism were potential regulators, resulting in the difference in lipid metabolite accumulation between IMF and AF. The PPAR signaling pathway was the most important pathway involved in tissue-specific lipid deposition. Correlation analysis showed that most representative DEGs enriched in the PPAR signaling pathway, such as FABP5, PPARG, ACOX1, and GK2, were negatively correlated with PUFA-enriched glycerophospholipid molecules. Most DEGs related to glycerophospholipid metabolism, such as GPD2, GPD1, PEMT, CRLS1, and GBGT1, were positively correlated with glycerophospholipid molecules, especially DHA- and arachidonic acid (ARA)-containing glycerophospholipid molecules. This study elucidated the molecular mechanism underlying tissue-specific lipid deposition and poultry meat quality.

27 September 2022 in Animals
Verified
Journal Article
Open access
PDF file
LDLonghuan Du
Longhuan Du
LYLi Yang
Li Yang
CYChaowu Yang
Chaowu Yang
CHChenming Hu
Chenming Hu
CYChunlin Yu
Chunlin Yu
XYXianlin Ye
Xianlin Ye
Indoor environmental control is usually applied in poultry farming to ensure optimum growth conditions for birds. However, these control methods represent a considerable share of total energy consumption, and the trend of applying new equipment in the future for precision livestock farming would further increase energy demand, resulting in an increase in greenhouse gas emissions and management costs. Therefore, to ensure optimum efficiency of both energy use and livestock productivity, a customized hourly model was developed in the present study to interpret and analyze the electronically collected data. The modules for estimating indoor gas concentrations were incorporated into the present model, as this has not been properly considered in previous studies. A validation test was performed in a manure-belt layer house using sensors and meters to measure the indoor environmental parameters and energy consumption. The predicted results, including indoor temperature, relative humidity, carbon dioxide and ammonia concentrations, showed good agreement with the measured data, indicating a similar overall trend with acceptable discrepancies. Moreover, the corresponding differences between the measured and simulated energy consumption for heating, tunnel ventilation and base ventilation were 13.7, 7.5, and 0.1%, respectively. The total energy demand estimated by the model showed a limited discrepancy of approximately 10.6% compared with that measured in reality. Although human factors, including inspection, cleaning, vaccination, etc., were not included in the model, the validation results still suggested that the customized model was able to accurately predict the indoor environment and overall energy consumption during poultry farming. The validated model provides a tool for poultry producers to optimize production planning and management strategies, increase the production rate of unit energy consumption and achieve precision livestock farming from an energy consumption standpoint.

27 January 2024 in Biochemical Genetics
Verified
Journal Article
Open access
PDF file
MQMohan Qiu
Mohan Qiu
ZZZengrong Zhang
Zengrong Zhang
SZShiliang Zhu
Shiliang Zhu
SLSiyang Liu
Siyang Liu
HPHan Peng
Han Peng
CYChaowu Yang
Chaowu Yang
The feather growth rate in chickens included early and late feathering. We attempted to characterize the genes and pathways associated with the feather growth rate in chickens that are not in agreement with Mendelian inheritance. Gene expression profiles in the hair follicle tissues of late-feathering cocks (LC), early-feathering cocks (EC), late-feathering hens (LH), and early-feathering hens (EH) were acquired using RNA sequencing (RNA-seq), mass spectrometry (MS), and quantitative reverse transcription PCR (qRT‑PCR). A total of 188 differentially expressed genes (DEGs) were ascertained in EC vs. LC and 538 DEGs were identified in EH vs. LH. We observed that 14 up-regulated genes and 9 down-regulated genes were screened both in EC vs. LC and EH vs. LH. MS revealed that 41 and 138 differentially expressed proteins (DEPs) were screened out in EC vs. LC and EH vs. LH, respectively. Moreover, these DEGs and DEPs were enriched in multiple feather-related pathways, including JAK-STAT, MAPK, WNT, TGF-β, and calcium signaling pathways. qRT-PCR assay showed that the expression of WNT8A was decreased in LC compared with EC, while ALK and GRM4 expression were significantly up-regulated in EH relative to LH. This study helps to elucidate the potential mechanism of the feather growth rate in chickens that do not conform to genetic law.