Shouzhi Wang

Profiling of chicken adipose tissue gene expression by genome array

BackgroundExcessive accumulation of lipids in the adipose tissue is a major problem in the present-day broiler industry. However, few studies have analyzed the expression of adipose tissue genes that are involved in pathways and mechanisms leading to adiposity in chickens. Gene expression profiling of chicken adipose tissue could provide key information about the ontogenesis of fatness and clarify the molecular mechanisms underlying obesity. In this study, Chicken Genome Arrays were used to construct an adipose tissue gene expression profile of 7-week-old broilers, and to screen adipose tissue genes that are differentially expressed in lean and fat lines divergently selected over eight generations for high and low abdominal fat weight.ResultsThe gene expression profiles detected 13,234–16,858 probe sets in chicken adipose tissue at 7 weeks, and genes involved in lipid metabolism and immunity such as fatty acid binding protein (FABP), thyroid hormone-responsive protein (Spot14), lipoprotein lipase(LPL), insulin-like growth factor binding protein 7(IGFBP7) and major histocompatibility complex (MHC), were highly expressed. In contrast, some genes related to lipogenesis, such as leptin receptor, sterol regulatory element binding proteins1 (SREBP1), apolipoprotein B(ApoB) and insulin-like growth factor 2(IGF2), were not detected. Moreover, 230 genes that were differentially expressed between the two lines were screened out; these were mainly involved in lipid metabolism, signal transduction, energy metabolism, tumorigenesis and immunity. Subsequently, real-time RT-PCR was performed to validate fifteen differentially expressed genes screened out by the microarray approach and high consistency was observed between the two methods.ConclusionOur results establish the groundwork for further studies of the basic genetic control of growth and development of chicken adipose tissue, and will be beneficial in clarifying the molecular mechanism of obesity in chickens.

Progress of genome wide association study in domestic animals

Domestic animals are invaluable resources for study of the molecular architecture of complex traits. Although the mapping of quantitative trait loci (QTL) responsible for economically important traits in domestic animals has achieved remarkable results in recent decades, not all of the genetic variation in the complex traits has been captured because of the low density of markers used in QTL mapping studies. The genome wide association study (GWAS), which utilizes high-density single-nucleotide polymorphism (SNP), provides a new way to tackle this issue. Encouraging achievements in dissection of the genetic mechanisms of complex diseases in humans have resulted from the use of GWAS. At present, GWAS has been applied to the field of domestic animal breeding and genetics, and some advances have been made. Many genes or markers that affect economic traits of interest in domestic animals have been identified. In this review, advances in the use of GWAS in domestic animals are described.

Fine-Mapping Quantitative Trait Loci for Body Weight and Abdominal Fat Traits: Effects of Marker Density and Sample Size

Highly significant QTL for BW and abdominal fat traits on chicken chromosome 1 were reported previously in a unique F2 population. The objective of this study was to confirm and refine the QTL locations. Compared with the previous experiment, this study added 8 new families, including all the animals in the pedigree, and genotyped 9 more microsatellite markers, including 6 novel ones. Linkage analyses were performed. The results of the linkage analyses showed that the confidence intervals for BW and abdominal fat percentage were narrowed sharply to a small interval spanning 5.5 and 3.7 Mb, respectively. The results of the present study showed that using more markers and individuals could decrease the confidence interval of QTL effectively. In the current QTL region, by combining the biological knowledge of genes and the results of a microarray analysis that was performed in divergently selected lean and fat lines, several genes stood out as potential candidate genes.

Selection signature analysis implicates the PC1/PCSK1 region for chicken abdominal fat content

We conducted a selection signature analysis using the chicken 60k SNP chip in two chicken lines that had been divergently selected for abdominal fat content (AFC) for 11 generations. The selection signature analysis used multiple signals of selection, including long-range allele frequency differences between the lean and fat lines, long-range heterozygosity changes, linkage disequilibrium, haplotype frequencies, and extended haplotype homozygosity. Multiple signals of selection identified ten signatures on chromosomes 1, 2, 4, 5, 11, 15, 20, 26 and Z. The 0.73 Mb PC1/PCSK1 region of the Z chromosome at 55.43-56.16 Mb was the most heavily selected region. This region had 26 SNP markers and seven genes, Mar-03, SLC12A2, FBN2, ERAP1, CAST, PC1/PCSK1 and ELL2, where PC1/PCSK1 are the chicken/human names for the same gene. The lean and fat lines had two main haplotypes with completely opposite SNP alleles for the 26 SNP markers and were virtually line-specific, and had a recombinant haplotype with nearly equal frequency (0.193 and 0.196) in both lines. Other haplotypes in this region had negligible frequencies. Nine other regions with selection signatures were PAH-IGF1, TRPC4, GJD4-CCNY, NDST4, NOVA1, GALNT9, the ESRP2-GALR1 region with five genes, the SYCP2-CADH4 with six genes, and the TULP1-KIF21B with 14 genes. Genome-wide association analysis showed that nearly all regions with evidence of selection signature had SNP effects with genome-wide significance (P<10–6) on abdominal fat weight and percentage. The results of this study provide specific gene targets for the control of chicken AFC and a potential model of AFC in human obesity.

Genome-wide association study for wool production traits in a Chinese Merino sheep population.

Genome-wide association studies (GWAS) provide a powerful approach for identifying quantitative trait loci without prior knowledge of location or function. To identify loci associated with wool production traits, we performed a genome-wide association study on a total of 765 Chinese Merino sheep (JunKen type) genotyped with 50 K single nucleotide polymorphisms (SNPs). In the present study, five wool production traits were examined: fiber diameter, fiber diameter coefficient of variation, fineness dispersion, staple length and crimp. We detected 28 genome-wide significant SNPs for fiber diameter, fiber diameter coefficient of variation, fineness dispersion, and crimp trait in the Chinese Merino sheep. About 43% of the significant SNP markers were located within known or predicted genes, including YWHAZ, KRTCAP3, TSPEAR, PIK3R4, KIF16B, PTPN3, GPRC5A, DDX47, TCF9, TPTE2, EPHA5 and NBEA genes. Our results not only confirm the results of previous reports, but also provide a suite of novel SNP markers and candidate genes associated with wool traits. Our findings will be useful for exploring the genetic control of wool traits in sheep.

Comparison of serum biochemical parameters between two broiler chicken lines divergently selected for abdominal fat content

In humans, obesity is associated with increased or decreased levels of serum biochemical indicators. However, the relationship is not as well understood in chickens. Due to long-term intense selection for fast growth rate, modern broilers have the problem of excessive fat deposition, exhibiting biochemical or metabolic changes. In the current study, the Northeast Agricultural University broiler lines divergently selected for abdominal fat content (NEAUHLF) were used to identify differences in serum biochemical parameters between the 2 lines. A total of 18 serum biochemical indicators were investigated in the 16th, 17th, and 18th generation populations of NEAUHLF, and the genetic parameters of these serum biochemical indicators were estimated. After analyzing the data from these 3 generations together, the results showed that the levels of 16 of the tested serum biochemical parameters were significantly different between the lean and fat birds. In the fat birds, serum concentrations of high-density lipoprotein cholesterol (HDL-C), HDL-C:low-density lipoprotein cholesterol (LDL-C), total bile acid, total protein, albumin, globulin, aspartate transaminase (AST):alanine transaminase (ALT), γ-glutamyl transpeptidase (GGT), uric acid, and creatinine were very significantly higher (P < 0.01), whereas LDL-C, albumin:globulin, glucose, AST, ALT, and free fatty acids concentrations in serum were very significantly lower than those in the lean birds (P < 0.01). Of these 16 serum biochemical parameters, 5 (LDL-C, HDL-C:LDL-C, total bile acid, albumin, and albumin:globulin) had high heritabilities (0.58 ≤ h2 ≤ 0.89), 6 (HDL-C, total protein, globulin, AST:ALT, GGT, and creatinine) had moderate heritabilities (0.29 ≤ h2 ≤ 0.48), and the remaining 5 had low heritabilities (h2 < 0.20). Serum HDL-C, HDL-C:LDL-C, and glucose had higher positive genetic correlation coefficients (rg) with abdominal fat traits (0.30 ≤ rg ≤ 0.80), whereas serum globulin, AST, and uric acid showed higher negative genetic correlations with abdominal fat traits (–0.62 ≤ rg ≤ –0.30). The remaining 10 serum biochemical parameters had lower genetic correlations with abdominal fat traits (–0.30 < rg < 0.30). In conclusion, we identified serum HDL-C and HDL-C:LDL-C levels as potential biomarkers for selection of lean birds. These findings will also be useful in future studies for investigating obesity and lipid metabolism in humans as well as in other animal species.

Epigenetic DNA methylation in the promoters of peroxisome proliferator-activated receptor γ in chicken lines divergently selected for fatness.

Peroxisome proliferator-activated receptor γ is a master regulator of adipocyte differentiation and function. Expression of PPARγ in mammals is regulated by DNA methylation; however, it is currently unknown whether chicken PPARγ expression is regulated by DNA methylation. To enhance our understanding of molecular mechanisms underlying chicken adipose tissue development and adipogenesis, we investigated the promoter methylation status and gene expression of PPARγ gene in Northeast Agricultural University broiler lines divergently selected for abdominal fat content (NEAUHLF). Deoxyribonucleic acid methylation was analyzed by bisulfite sequencing method, and mRNA expression was detected by real-time quantitative real time reverse-transcription polymerase chain reaction (RT-PCR). The analyzed region located from -1,175 to -301 bp upstream of the translation start codon ATG contains 6 CpG dinucleotides, which are located at positions -1,014, -796, -625, -548, -435, and -383 bp, respectively. The results revealed that the 3 CpGs at positions -548, -435, and -383 bp showed differential methylation between the lean and fat chicken lines, but the other 3 CpG sites at positions -1,014, -796, and -625 bp did not. PPARγ gene promoter methylation in both chicken lines decreased with age, and PPARγ promoter methylation levels were significantly higher in lean than fat broilers at 2 wk of age (79.9 to 64.5%; P < 0.0001), at 3 wk of age (66.7 to 58.3%; P < 0.0001), and at 7 wk of age (50.0 to 42.7%; P = 0.0004). Real-time quantitative RT-PCR analysis showed that, negatively correlated with DNA methylation (Pearsons r = -0.653, P = 0.0057), PPARγ expression was increased with age and significantly lower in lean than fat chicken lines at 2, 3, and 7 wk of age (P < 0.0001). In conclusion, our findings suggest that chicken PPARγ is regulated by DNA methylation during adipose tissue development.

Genetic epistasis analysis of 10 peroxisome proliferator-activated receptor γ-correlated genes in broiler lines divergently selected for abdominal fat content

Chicken peroxisome proliferator-activated receptor γ (PPARγ), which is highly expressed in adipose tissues, is a key factor in fat accumulation in the abdominal fat pad. In this study, association and pairwise epistasis analyses were performed for all the polymorphisms detected in PPARγ and for 9 genes from PPARγ-correlated lipid metabolic pathways for abdominal fat weight (AFW) in 10th-generation populations of Northeast Agricultural University broiler lines divergently selected for abdominal fat content. Epistatic networks were then reconstructed with the identified epistatic effects. Single-marker association analyses showed that 5 of the 20 screened polymorphisms were significantly associated with AFW (P < 0.05), and CCAAT/enhancer-binding protein α (C/EBPα) c.552G>A was 1 of the 5 significant loci. Pairwise interaction analyses showed that 15 pairs of polymorphisms reached a significance level of P < 2.64 × 10(-4) (adjusted by Bonferroni correction) in the lean line, 41 pairs reached significance in the fat line, and 7 pairs reached significance in both lines. Interestingly, many other loci interacted with C/EBPα c.552G>A in both lines. In epistatic network analyses, C/EBPα c.552G>A seemed to behave as a hub for the epistatic network in both lines. All these results revealed that the genetic architecture of C/EBPα c.552G>A for AFW seemed to be an apparent individual main-effect QTL but that it could be dissected into a genetic epistatic network. Our results suggest that C/EBPα c.552G>A might be the most important locus contributing to phenotypic variation in AFW among all the polymorphisms detected in this study.

Detection and fine mapping of quantitative trait loci for bone traits on chicken chromosome one.

In broiler chickens, bone problems are an important welfare issue that has been linked to genetic selection for rapid growth. The objectives of this study were to identify and fine map quantitative trait loci (QTL) associated with bone traits. The Northeast Agricultural University resource population (NEAURP) being an F(2) population was used in this study, and a total of 17 bone traits were measured. In primary genome scan, the linkage map was constructed with 23 microsatellite markers across the entire chicken chromosome 1. Seventeen QTLs for bone traits were identified and 12 of these were found between LEI0079 and ROS0025 (50.8 cM apart). To fine map the QTLs located between LEI0079 and ROS0025, more markers and more individuals were used and a new partial linkage map was constructed. The confidence intervals for QTLs were sharply narrowed down from 24.5∼52.6 to 2.7∼17.0 Mb. This study identified chromosome regions harbouring significant QTLs affecting bone traits and showed that the use of more markers and individuals could decrease the confidence interval of QTL effectively. The results provide a useful reference for further candidate gene research and MAS for bone traits.

A single nucleotide polymorphism of chicken acetyl-CoA carboxylase A gene associated with fatness traits.

Acetyl-CoA carboxylase α (ACCα) is a major rate-limiting enzyme in the biogenesis of long-chain fatty acids. It can catalyze the carboxylation of acetyl-CoA to form malonyl-CoA that plays a key role in the regulation of fatty acid metabolism. The objective of the present study was to investigate the associations of ACCα gene polymorphisms with chicken growth and body composition traits. The Northeast Agricultural University broiler lines divergently selected for abdominal fat content and the Northeast Agricultural University F2 Resource Population were used in the current study. Body weight and body composition traits were measured in the aforementioned two populations. A synonymous mutation was detected in the exon 19 region of ACCα gene, then polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method was developed to genotype all the individuals derived from the aforementioned populations. Association analysis revealed that the polymorphism was associated with abdominal fat weight and percentage of abdominal fat in the two populations. The results suggested that ACCα gene could be a candidate locus or linked to a major gene that affects abdominal fat content in the chicken.