Xiaolong Yuan

Mr. Xiaolong Yuan

0000 0000 9546 5767, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, National Engineering Research Centre for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, China
orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

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

Representative Publications

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Journal Article
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YJYao Jiang
Yao Jiang
YHYingting He
Yingting He
XPXiangchun Pan
Xiangchun Pan
PWPenghao Wang
Penghao Wang
XYXiaolong Yuan
Xiaolong Yuan
BMBin Ma
Bin Ma
The quality and maturation of an oocyte not only play decisive roles in fertilization and embryo success, but also have long-term impacts on the later growth and development of the fetus. Female fertility declines with age, reflecting a decline in oocyte quantity. However, the meiosis of oocytes involves a complex and orderly regulatory process whose mechanisms have not yet been fully elucidated. This review therefore mainly focuses on the regulation mechanism of oocyte maturation, including folliculogenesis, oogenesis, and the interactions between granulosa cells and oocytes, plus in vitro technology and nuclear/cytoplasm maturation in oocytes. Additionally, we have reviewed advances made in the single-cell mRNA sequencing technology related to oocyte maturation in order to improve our understanding of the mechanism of oocyte maturation and to provide a theoretical basis for subsequent research into oocyte maturation.

13 November 2023 in Nucleic Acids Research
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Journal Article
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HZHaonan Zeng
Haonan Zeng
WZWenjing Zhang
Wenjing Zhang
QLQing Lin
Qing Lin
YGYahui Gao
Yahui Gao
JTJinyan Teng
Jinyan Teng
ZZZhe Zhang
Zhe Zhang
To fully unlock the potential of pigs as both agricultural species for animal-based protein food and biomedical models for human biology and disease, a comprehensive understanding of molecular and cellular mechanisms underlying various complex phenotypes in pigs and how the findings can be translated to other species, especially humans, are urgently needed. Here, within the Farm animal Genotype-Tissue Expression (FarmGTEx) project, we build the PigBiobank (http://pigbiobank.farmgtex.org) to systematically investigate the relationships among genomic variants, regulatory elements, genes, molecular networks, tissues and complex traits in pigs. This first version of the PigBiobank curates 71 885 pigs with both genotypes and phenotypes from over 100 pig breeds worldwide, covering 264 distinct complex traits. The PigBiobank has the following functions: (i) imputed sequence-based genotype-phenotype associations via a standardized and uniform pipeline, (ii) molecular and cellular mechanisms underlying trait-associations via integrating multi-omics data, (iii) cross-species gene mapping of complex traits via transcriptome-wide association studies, and (iv) high-quality results display and visualization. The PigBiobank will be updated timely with the development of the FarmGTEx-PigGTEx project, serving as an open-access and easy-to-use resource for genetically and biologically dissecting complex traits in pigs and translating the findings to other species.

26 September 2019 in Animals
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ZZZhe Zhang
Zhe Zhang
ZCZitao Chen
Zitao Chen
SYShaopan Ye
Shaopan Ye
YHYingting He
Yingting He
SHShuwen Huang
Shuwen Huang
JLJiaqi Li
Jiaqi Li
In the pig industry, reproductive traits constantly influence the production efficiency. To identify markers and candidate genes underlying porcine reproductive traits, a genome-wide association study (GWAS) was performed in a Duroc pig population. In total, 1067 pigs were genotyped using single-nucleotide polymorphism (SNP) chips, and four reproductive traits, including litter size at birth (LSB), litter weight at birth (LWB), litter size at weaning (LSW), and litter weight at weaning (LWW), were examined. The results showed that 20 potential SNPs reached the level of suggestive significance and were associated with these traits of interest. Several important candidate genes, including TXN2, KCNA1, ENSSSCG00000003546, ZDHHC18, MAP2K6, BICC1, FAM135B, EPHB2, SEMA4D, ST3GAL1, KCTD3, FAM110A, TMEM132D, TBX3, and FAM110A, were identified and might compose the underlying genetic architecture of porcine reproductive traits. These findings help to understand the genetic basis of porcine reproductive traits and provide important information for molecular breeding in pigs.

24 December 2022 in Cell Death & Differentiation
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XZXiaofeng Zhou
Xiaofeng Zhou
YHYingting He
Yingting He
XPXiangchun Pan
Xiangchun Pan
HQHongyan Quan
Hongyan Quan
BHBo He
Bo He
XYXiaolong Yuan
Xiaolong Yuan
DNA methylation and long noncoding RNAs (lncRNAs) exhibit an indispensable role in follicular development. However, the specific mechanisms regarding lncRNAs mediated by DNA methylation in follicular development remain unclearly. In this study, we found that inhibiting the expression of DNMT1 promoted granulosa cells (GCs) apoptosis to inhibit follicular development. A novel follicular development-associated lncRNA named inhibitory factor of follicular development (IFFD) was mediated by DNMT1 and showed to arrest follicular development by inhibiting GCs proliferation and estrogen (E2) secretion but promoting GCs apoptosis. Mechanistically, the deactivated Cas9-TET1 demonstrated that the hypomethylation in −1261/−1254 region of IFFD promoted the transcription of IFFD by recruiting SP1. IFFD induced the expression of GLI family zinc finger 1 through competitive binding miR-370, thereby up-regulating the expression of CASP3 to promote GCs apoptosis, as well as downregulating the expressions of PCNA and CYP19A1 to inhibit GCs proliferation and E2 secretion. Collectively, DNMT1-mediated IFFD might be a novel target for the regulation of follicular development.

7 May 2019 in Genes
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SDShuqi Diao
Shuqi Diao
SHShuwen Huang
Shuwen Huang
ZCZitao Chen
Zitao Chen
JTJinyan Teng
Jinyan Teng
YMYunlong Ma
Yunlong Ma
ZZZhe Zhang
Zhe Zhang
South China indigenous pigs are famous for their superior meat quality and crude feed tolerance. Saba and Baoshan pigs without saddleback were located in the high-altitude area of Yunnan Province, while Tunchang and Ding’an pigs with saddleback were located in the low-altitude area of Hainan Province. Although these pigs are different in appearance, the underlying genetic differences have not been investigated. In this study, based on the single-nucleotide polymorphism (SNP) genotypes of 124 samples, both the cross-population extended haplotype homozygosity (XP-EHH) and the fixation index (FST) statistic were used to identify potential signatures of selection in these pig breeds. We found nine potential signatures of selection detected simultaneously by two methods, annotated 22 genes in Hainan pigs, when Baoshan pigs were used as the reference group. In addition, eleven potential signatures of selection detected simultaneously by two methods, annotated 24 genes in Hainan pigs compared with Saba pigs. These candidate genes were most enriched in GO: 0048015~phosphatidylinositol-mediated signaling and ssc00604: Glycosphingolipid biosynthesis—ganglio series. These selection signatures were likely to overlap with quantitative trait loci associated with meat quality traits. Furthermore, one potential selection signature, which was associated with different coat color, was detected in Hainan pigs. These results contribute to a better understanding of the underlying genetic architecture of South China indigenous pigs.

17 February 2025 in National Science Review
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Journal Article
Open access
ZXZhiting Xu
Zhiting Xu
QLQing Lin
Qing Lin
XCXiaodian Cai
Xiaodian Cai
ZZZhanming Zhong
Zhanming Zhong
JTJinyan Teng
Jinyan Teng
ZZZhe Zhang
Zhe Zhang
Understanding the molecular and cellular mechanisms underlying complex traits in pigs is crucial for enhancing genetic gain via artificial selection and utilizing pigs as models for human disease and biology. Here, we conducted comprehensive genome-wide association studies (GWAS) followed by a cross-breed meta-analysis for 232 complex traits and a within-breed meta-analysis for 12 traits, using 28.3 million imputed sequence variants in 70 328 animals across 14 pig breeds. We identified 6878 quantitative trait loci (QTL) for 139 complex traits. Leveraging the Pig Genotype-Tissue Expression resource, we systematically investigated the biological context and regulatory mechanisms behind these trait-QTLs, ultimately prioritizing 14 829 variant-gene-tissue-trait regulatory circuits. For instance, rs344053754 regulates UGT2B31 expression in the liver and intestines, potentially by modulating enhancer activity, ultimately influencing litter weight at weaning in pigs. Furthermore, we observed conservation of certain genetic and regulatory mechanisms underlying complex traits between humans and pigs. Overall, our cross-breed meta-GWAS in pigs provides invaluable resources and novel insights into the genetic regulatory and evolutionary mechanisms of complex traits in mammals.