Kai Xing

Dr. Kai Xing


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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11 August 2017 in Frontiers in Microbiology
Verified
Journal Article
Open access
ZTZhen Tan
Zhen Tan
TYTing Yang
Ting Yang
YWYuan Wang
Yuan Wang
KXKai Xing
Kai Xing
FZFengxia Zhang
Fengxia Zhang
CWChuduan Wang
Chuduan Wang
Feed efficiency appears to vary even within closely related pigs, and may be partly affected by the diversity in the composition and function of gut microbes. To investigate the components and functional differences of gut microbiota of low and high feed efficiency (FE) pigs, high throughput sequencing and de novo metagenomics were performed on pig cecal contents. Pigs were selected in pairs with low and high feed conversion ratio. The microorganisms of individuals with different feed efficiency were clustered according to diversity. The genus Prevotella was the most enriched in both groups, and the abundance of species Prevotella sp. CAG:604 was significantly increased in low efficiency individuals compared to that in animals showing high efficiency. In contrast, other differential species, including lactic acid bacteria, were all enriched in the group with good feeding characteristics. Functional analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases demonstrated that differential genes for the metabolism of carbohydrates were most abundant in both groups, but pathways of pyruvate-related metabolism were more intense in pigs with higher feed efficiency. All these data indicated that the microbial environment was closely related to the growth traits of pigs, and regulating microbial composition could aid developing strategies to improve feed efficiency for pigs.

7 February 2018 in Animal Genetics
Verified
Journal Article
Open access
PDF file
YWY. Wang
Y. Wang
XDX. Ding
X. Ding
ZTZhen Tan
Zhen Tan
KXKai Xing
Kai Xing
TYT. Yang
T. Yang
SMS. Mi
S. Mi
Summary: Using the PorcineSNP80 BeadChip, we performed a genome‐wide association study for seven reproductive traits, including total number born, number born alive, litter birth weight, average birth weight, gestation length, age at first service and age at first farrowing, in a population of 1207 Large White pigs. In total, we detected 12 genome‐wide significant and 41 suggestive significant SNPs associated with six reproductive traits. The proportion of phenotypic variance explained by all significant SNPs for each trait ranged from 4.46% (number born alive) to 11.49% (gestation length). Among them, 29 significant SNPs were located within known QTL regions for swine reproductive traits, such as corpus luteum number, stillborn number and litter size, of which one QTL region associated with litter size contained the ALGA0098819 SNP for total number born. Subsequently, we found that 376 functional genes contained or were near these significant SNPs. Of these, 14 genes—BHLHA15, OCM2, IL1B2, GCK, SMAD2, HABP2, PAQR5, GRB10, PRELID2, DMKN, GPI, GPIHBP1, ADCY2 and ACVR2B—were considered important candidates for swine reproductive traits based on their critical roles in embryonic development, energy metabolism and growth development. Our findings contribute to the understanding of the genetic mechanisms for reproductive traits and could have a positive effect on pig breeding programs.

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.

1 March 2018 in Antonie van Leeuwenhoek
Verified
Journal Article
Open access
PDF file
ZTZhen Tan
Zhen Tan
YWYuan Wang
Yuan Wang
TYTing Yang
Ting Yang
HAHong Ao
Hong Ao
SCShaokang Chen
Shaokang Chen
CWChuduan Wang
Chuduan Wang
The goal of this study was to evaluate the microbial communities in the gut and feces from female finishing Landrace pigs with high and low feed conversion ratio (FCR) by 16S rRNA gene amplicon sequencing. Many potential biomarkers can distinguish between high and low FCR groups in the duodenum, ileum, cecum, colon, and rectum, according to linear discriminant analysis effect sizes. The relative abundance of microbes were tested by Mann–Whitney test between the high and low FCR groups in different organs: Campylobacter, Prevotella and Sphaerochaeta were different in the duodenum (P < 0.05); Sanguibacter, Kingella and Anaeroplasma in jejunum; Anaeroplasma, Arthrobacter, Kingella, Megasphaera and SMB53 in the ileum; Butyricicoccus, Campylobacter, Mitsuokella, and Coprobacillus in the cecum; Lactococcus and Peptococcus in the colon; Staphylococcus in the rectum; and Rothia in feces. The prevalence of microbial genera in certain locations could potentially be used as biomarkers to distinguish between high and low FCR. Functional prediction clustering analysis suggested that bacteria in the hindgut mainly participated in carbohydrate metabolism and amino acid metabolism, and different in the relative abundance of metabolic pathways, as predicted from the microbial taxa present, were identified by comparing the high and low groups of each location. The results may provide insights for the alteration of the intestinal microbial communities to improve the growth rate of pigs.

21 March 2016 in Scientific Reports
Verified
Journal Article
Open access
KXKai Xing
Kai Xing
FZFeng Zhu
Feng Zhu
LZLiWei Zhai
LiWei Zhai
SCShaoKang Chen
ShaoKang Chen
ZTZhen Tan
Zhen Tan
CWChuduan Wang
Chuduan Wang
Backfat thickness is strongly associated with meat quality, fattening efficiency, reproductive performance, and immunity in pigs. Fat storage and fatty acid synthesis mainly occur in adipose tissue. Therefore, we used a high-throughput massively parallel sequencing approach to identify transcriptomes in adipose tissue, and whole-genome differences from three full-sibling pairs of pigs with opposite (high and low) backfat thickness phenotypes. We obtained an average of 38.69 million reads for six samples, 78.68% of which were annotated in the reference genome. Eighty-nine overlapping differentially expressed genes were identified among the three pair comparisons. Whole-genome resequencing also detected multiple genetic variations between the pools of DNA from the two groups. Compared with the animal quantitative trait loci (QTL) database, 20 differentially expressed genes were matched to the QTLs associated with fatness in pigs. Our technique of integrating transcriptome, whole-genome resequencing, and QTL database information provided a rich source of important differentially expressed genes and variations. Associate analysis between selected SNPs and backfat thickness revealed that two SNPs and one haplotype of ME1 significantly affected fat deposition in pigs. Moreover, genetic analysis confirmed that variations in the differentially expressed genes may affect fat deposition.

28 November 2017 in Frontiers in Genetics
Verified
Journal Article
Open access
YWYuan Wang
Yuan Wang
XDXiangdong Ding
Xiangdong Ding
ZTZhen Tan
Zhen Tan
CNChao Ning
Chao Ning
KXKai Xing
Kai Xing
CWChuduan Wang
Chuduan Wang
Piglet uniformity (PU) and farrowing interval (FI) are important reproductive traits related to production and economic profits in the pig industry. However, the genetic architecture of the longitudinal trends of reproductive traits still remains elusive. Herein, we performed a genome-wide association study (GWAS) to detect potential genetic variation and candidate genes underlying the phenotypic records at different parities for PU and FI in a population of 884 Large White pigs. In total, 12 significant SNPs were detected on SSC1, 3, 4, 9, and 14, which collectively explained 1–1.79% of the phenotypic variance for PU from parity 1 to 4, and 2.58–4.11% for FI at different stages. Of these, seven SNPs were located within 16 QTL regions related to swine reproductive traits. One QTL region was associated with birth body weight (related to PU) and contained the peak SNP MARC0040730, and another was associated with plasma FSH concentration (related to FI) and contained the SNP MARC0031325. Finally, some positional candidate genes for PU and FI were identified because of their roles in prenatal skeletal muscle development, fetal energy substrate, pre-implantation, and the expression of mammary gland epithelium. Identification of novel variants and candidate genes will greatly advance our understanding of the genetic mechanisms of PU and FI, and suggest a specific opportunity for improving marker assisted selection or genomic selection in pigs.