Yong Guo

Yong Guo


Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

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

Representative Publications

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26 November 2021 in Science Advances
Verified
Journal Article
Open access
XLXukun Lu
Xukun Lu
YZYu Zhang
Yu Zhang
LWLijuan Wang
Lijuan Wang
LWLeyun Wang
Leyun Wang
HWHuili Wang
Huili Wang
WXWei Xie
Wei Xie
Evolutionary analyses reveal conservation and divergence of epigenetic transition during early development across mammals.

14 June 2017 in BMC Genomics
Verified
Journal Article
Open access
PDF file
BZBo Zhu
Bo Zhu
HNHong Niu
Hong Niu
WZWengang Zhang
Wengang Zhang
ZWZezhao Wang
Zezhao Wang
YLYonghu Liang
Yonghu Liang
JLJunya Li
Junya Li
Fatty acid composition of muscle is an important trait contributing to meat quality. Recently, genome-wide association study (GWAS) has been extensively used to explore the molecular mechanism underlying important traits in cattle. In this study, we performed GWAS using high density SNP array to analyze the association between SNPs and fatty acids and evaluated the accuracy of genomic prediction for fatty acids in Chinese Simmental cattle. Using the BayesB method, we identified 35 and 7 regions in Chinese Simmental cattle that displayed significant associations with individual fatty acids and fatty acid groups, respectively. We further obtained several candidate genes which may be involved in fatty acid biosynthesis including elongation of very long chain fatty acids protein 5 (ELOVL5), fatty acid synthase (FASN), caspase 2 (CASP2) and thyroglobulin (TG). Specifically, we obtained strong evidence of association signals for one SNP located at 51.3 Mb for FASN using Genome-wide Rapid Association Mixed Model and Regression-Genomic Control (GRAMMAR-GC) approaches. Also, region-based association test identified multiple SNPs within FASN and ELOVL5 for C14:0. In addition, our result revealed that the effectiveness of genomic prediction for fatty acid composition using BayesB was slightly superior over GBLUP in Chinese Simmental cattle. We identified several significantly associated regions and loci which can be considered as potential candidate markers for genomics-assisted breeding programs. Using multiple methods, our results revealed that FASN and ELOVL5 are associated with fatty acids with strong evidence. Our finding also suggested that it is feasible to perform genomic selection for fatty acids in Chinese Simmental cattle.

9 September 2019 in Scientific Reports
Verified
Journal Article
Open access
PDF file
KXKai Xing
Kai Xing
KWKejun Wang
Kejun Wang
HAHong Ao
Hong Ao
SCShaokang Chen
Shaokang Chen
ZTZhen Tan
Zhen Tan
CWChuduan Wang
Chuduan Wang
Fatness traits are important in pigs because of their implications for fattening efficiency, meat quality, reproductive performance and immunity. Songliao black pigs and Landrace pigs show important differences in production and meat quality traits, including fatness and muscle growth. Therefore, we used a high-throughput massively parallel RNA-seq approach to identify genes differentially expressed in backfat tissue between these two breeds (six pigs in each). An average of 37.87 million reads were obtained from the 12 samples. After statistical analysis of gene expression data by edgeR, a total of 877 differentially expressed genes were detected between the two pig breeds, 205 with higher expression and 672 with lower expression in Songliao pigs. Candidate genes (LCN2, CES3, DGKB, OLR1, LEP, PGM1, PCK1, ACACB, FADS1, FADS2, MOGAT2, SREBF1, PPARGC1B) with known effects on fatness traits were included among the DEGs. A total of 1071 lncRNAs were identified, and 85 of these lncRNAs were differentially expressed, including 53 up-regulated and 32 down-regulated lncRNAs, respectively. The differentially expressed genes and lncRNAs involved in glucagon signaling pathway, glycolysis/gluconeogenesis, insulin signaling pathway, MAPK signaling pathway and so on. Integrated analysis potential trans-regulating or cis-regulating relation between DEGs and DE lncRNAs, suggested lncRNA MSTRG.2479.1 might regulate the expressed level of VLDLR affecting porcine fat metabolism. These results provide a number of candidate genes and lncRNAs potentially involved in porcine fat deposition and provide a basis for future research on the molecular mechanisms underlying in fat deposition.

7 January 2023 in Genes
Verified
Journal Article
Open access
PDF file
YZYanhui Zhao
Yanhui Zhao
SCShaokang Chen
Shaokang Chen
JYJiani Yuan
Jiani Yuan
YSYumei Shi
Yumei Shi
YWYan Wang
Yan Wang
KXKai Xing
Kai Xing
Intramuscular fat (IMF) is an essential trait closely related to meat quality. The IMF trait is a complex quantitative trait that is regulated by multiple genes. In order to better understand the process of IMF and explore the key factors affecting IMF deposition, we identified differentially expressed mRNA, miRNA, and lncRNA in the longissimus dorsi muscle (LD) between Songliao Black (SL) pigs and Landrace pigs. We obtained 606 differentially expressed genes (DEGs), 55 differentially expressed miRNAs (DEMs), and 30 differentially expressed lncRNAs (DELs) between the SL pig and Landrace pig. Enrichment results from GO and KEGG indicate that DEGs are involved in fatty acid metabolism and some pathways related to glycogen synthesis. We constructed an lncRNA–miRNA–mRNA interaction network with 18 DELs, 11 DEMs, and 42 DEGs. Finally, the research suggests that ARID5B, CPT1B, ACSL1, LPIN1, HSP90AA1, IRS1, IRS2, PIK3CA, PIK3CB, and PLIN2 may be the key genes affecting IMF deposition. The LncRNAs MSTRG.19948.1, MSTRG.13120.1, MSTRG.20210.1, and MSTRG.10023.1, and the miRNAs ssc-miRNA-429 and ssc-miRNA-7-1, may play a regulatory role in IMF deposition through their respective target genes. Our research provides a reference for further understanding the regulatory mechanism of IMF.

1 June 2019 in Theriogenology
Verified
Journal Article
Closed access
XQXiaolong Qi
Xiaolong Qi
MSMingyu Shang
Mingyu Shang
CCChen Chen
Chen Chen
YCYu Chen
Yu Chen
JHJing Hua
Jing Hua
YGYong Guo
Yong Guo

28 February 2023 in Foods
Verified
Journal Article
Open access
PDF file
KGKai Gai
Kai Gai
YGYu Ge
Yu Ge
DLDapeng Liu
Dapeng Liu
HZHe Zhang
He Zhang
BCBailin Cong
Bailin Cong
XSXihui Sheng
Xihui Sheng
The flavor of chicken meat is influenced by muscle metabolites and regulatory genes and varies with age. In this study, the metabolomic and transcriptomic data of breast muscle at four developmental stages (days 1, 56, 98, and 120) of Beijing-You chickens (BJYs) were integrated and 310 significantly changed metabolites (SCMs) and 7,225 differentially expressed genes (DEGs) were identified. A Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that SCMs and DEGs were enriched in amino acid, lipid, and inosine monophosphate (IMP) metabolism pathways. Furthermore, genes highly associated with flavor amino acids, lipids, and IMP were identified by a weighted gene co-expression network analysis (WGCNA), including cystathionine β-synthase (CBS), glycine amidinotransferase (GATM), glutamate decarboxylase 2 (GAD2), patatin-like phospholipasedomain containing 6 (PNPLA6), low-specificity L-threonine aldolase (ItaE), and adenylate monophosphate deaminase 1 (AMPD1) genes. A regulatory network related to the accumulation of key flavor components was constructed. In conclusion, this study provides new perspectives regarding the regulatory mechanisms of flavor metabolites in chicken meat during development.