Lei Zhou

Dr. Lei Zhou

National Engineering Laboratory For Animal Breeding, College of Animal Science and Techonolgy, China Agricultural University, Beijing 100193, China
orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

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

Representative Publications

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21 April 2020 in Journal of Animal Science and Biotechnology
Verified
Journal Article
Open access
PDF file
XZXianrui Zheng
Xianrui Zheng
PZPengju Zhao
Pengju Zhao
KYKaijie Yang
Kaijie Yang
CNChao Ning
Chao Ning
Haifei WangHaifei Wang
Haifei Wang
JLJian-Feng Liu
Jian-Feng Liu
Background: Reproductive performance of livestock is an economically important aspect of global food production. The Chinese Meishan pig is a prolific breed, with an average of three to five more piglets per litter than European breeds; however, the genetic basis for this difference is not well understood. Results: In this study, we investigated copy number variations (CNVs) of 32 Meishan pigs and 29 Duroc pigs by next-generation sequencing. A genome-wide analysis of 61 pigs revealed 12,668 copy number variable regions (CNVRs) that were further divided into three categories based on copy number (CN) of the whole population, i.e., gain (n = 7,638), and loss (n = 5,030) CNVRs. We then compared Meishan and Duroc pigs and identified 17.17 Mb of 6,387 CNVRs that only existing in Meishan pigs CNVRs that overlapped the reproduction-related gene encoding the aryl hydrocarbon receptor (AHR) gene. We found that normal AHR CN was more frequent than CN loss in four different pig breeds. An association analysis showed that AHR CN had a positive effect on litter size (P < 0.05) and that a higher CN was associated with higher total number born (P < 0.05), number born alive (P < 0.05), number of weaned piglets, and birth weight. Conclusions: The present study provides comprehensive CNVRs for Meishan and Duroc pigs through large-scale population resequencing. Our results provide a supplement for the high-resolution map of copy number variation in the porcine genome and valuable information for the investigation of genomic structural variation underlying traits of interest in pig. In addition, the association results provide evidence for AHR as a candidate gene associated with reproductive traits that can be used as a genetic marker in pig breeding programs.

7 January 2023 in Genes
Verified
Journal Article
Open access
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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.

26 July 2022 in Animals
Verified
Journal Article
Open access
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Weining LiWeining Li
Weining Li
ZWZhaojun Wang
Zhaojun Wang
SLShenghao Luo
Shenghao Luo
JWJianliang Wu
Jianliang Wu
LZLei Zhou
Lei Zhou
JLJian-Feng Liu
Jian-Feng Liu
Feed efficiency (FE) traits are key factors that can influence the economic benefits of pig production. However, little is known about the genetic architecture of FE and FE-related traits. This study aimed to identify SNPs and candidate genes associated with FE and FE-related traits, namely, average daily feed intake (ADFI), average daily gain (ADG), the feed conversion ratio (FCR), and residual feed intake (RFI). The phenotypes of 5823 boars with genotyped data (50 K BeadChip) from 1365 boars from a nucleus farm were used to perform a genome-wide association study (GWAS) of two breeds, Duroc and Yorkshire. Moreover, we performed a genetic parameter estimation for four FE and FE-related traits. The heritabilities of the FE and FE-related traits ranged from 0.13 to 0.36, and there were significant genetic correlations (−0.69 to 0.52) of the FE and FE-related traits with two growth traits (age at 100 kg and backfat thickness at 100 kg). A total of 61 significant SNPs located on eight different chromosomes associated with the four FE and FE-related traits were identified. We further identified four regions associated with FE and FE-related traits that have not been previously reported, and they may be potential novel QTLs for FE. Considering their biological functions, we finally identified 35 candidate genes relevant for FE and FE-related traits, such as the widely reported MC4R and INSR genes. A gene enrichment analysis showed that FE and FE-related traits were highly enriched in the biosynthesis, digestion, and metabolism of biomolecules. This study deepens our understanding of the genetic mechanisms of FE in pigs and provides valuable information for using marker-assisted selection in pigs to improve FE.

17 August 2021 in Animal Genetics
Verified
Journal Article
Closed access
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WYW. Yang
W. Yang
JWJ. Wu
J. Wu
JYJ. Yu
J. Yu
XZX. Zheng
X. Zheng
HKH. Kang
H. Kang
JLJian-Feng Liu
Jian-Feng Liu

24 March 2022 in Frontiers in Genetics
Verified
Journal Article
Open access
WYWenjing Yang
Wenjing Yang
ZLZhen Liu
Zhen Liu
QZQiqi Zhao
Qiqi Zhao
HDHeng Du
Heng Du
JYJian Yu
Jian Yu
JLJian-Feng Liu
Jian-Feng Liu
Beijing Black pig is an excellent cultivated black pig breed in China, with desirable body shape, tender meat quality and robust disease resistance. To explore the level of admixture and selection signatures of Beijing Black pigs, a total number of 90 individuals covering nine pig breeds were used in our study, including Beijing Black pig, Large White, Landrace, Duroc, Lantang pig, Luchuan pig, Mashen pig, Huainan pig and Min pig. These animals were resequenced with 18.19 folds mapped read depth on average. Generally, we found that Beijing Black pig was genetically closer to commercial pig breeds by population genetic structure and genetic diversity analysis, and was also affected by Chinese domestic breeds Huainan pig and Min pig. These results are consistent with the cross-breeding history of Beijing Black pig. Selection signal detections were performed on three pig breeds, Beijing Black pig, Duroc and Large White, using three complementary methods (FST, θπ, and XP-EHH). In total, 1,167 significant selected regions and 392 candidate genes were identified. Functional annotations were enriched to pathways related to immune processes and meat and lipid metabolism. Finally, potential candidate genes, influencing meat quality (GPHA2, EHD1, HNF1A, C12orf43, GLTP, TRPV4, MVK, and MMAB), reproduction (PPP2R5B and MAP9), and disease resistance (OASL, ANKRD13A, and GIT2), were further detected by gene annotation analysis. Our results advanced the understanding of the genetic mechanism behind artificial selection of Beijing Black pigs, and provided theoretical basis for the subsequent breeding and genetic research of this breed.

13 May 2022 in G3: Genes, Genomes, Genetics
Verified
Journal Article
Open access
PDF file
YZYu Zhang
Yu Zhang
YZYue Zhuo
Yue Zhuo
CNChao Ning
Chao Ning
LZLei Zhou
Lei Zhou
JLJian-Feng Liu
Jian-Feng Liu
With the broad application of genomic information, SNP-based measures of estimating inbreeding have been widely used in animal breeding, especially based on runs of homozygosity. Inbreeding depression is better estimated by SNP-based inbreeding coefficients than pedigree-based inbreeding in general. However, there are few comprehensive comparisons of multiple methods in pigs so far, to some extent limiting their application. In this study, to explore an appropriate strategy for estimating inbreeding depression on both growth traits and reproductive traits in a Large White pig population, we compared multiple methods for the inbreeding coefficient estimation based on both pedigree and genomic information. This pig population for analyzing the influence of inbreeding was from a pig breeding farm in the Inner Mongolia of China. There were 26,204 pigs with records of age at 100 kg (AGE) and back-fat thickness at 100 kg (BF), and 6,656 sows with reproductive records of the total number of piglets at birth (TNB), and the number of alive piglets at birth (NBA), and litter weight at birth. Inbreeding depression affected growth and reproductive traits. The results indicated that pedigree-based and SNP-based inbreeding coefficients had significant effects on AGE, TNB, and NBA, except for BF. However, only SNP-based inbreeding coefficients revealed a strong association with inbreeding depression on litter weight at birth. Runs of homozygosity-based methods showed a slight advantage over other methods in the correlation analysis of inbreeding coefficients and estimation of inbreeding depression. Furthermore, our results demonstrated that the model-based approach (RZooRoH) could avoid miscalculations of inbreeding and inbreeding depression caused by inappropriate parameters, which had a good performance on both AGE and reproductive traits. These findings might improve the extensive application of runs of homozygosity analysis in pig breeding and breed conservation.