Project description:BackgroundDespite several RNA-Seq and microarray studies on differentially expressed genes (DEGs) between high- and low-abdominal fat deposition in different broiler lines, to our knowledge, gene coexpression analysis across multiple broiler lines has rarely been reported. Here, we constructed a consensus gene coexpression network focused on identifying consensus gene coexpression modules associated with abdominal fat deposition across multiple broiler lines using two public RNA-Seq datasets (GSE42980 and GSE49121).ResultsIn the consensus gene coexpression network, we identified eight consensus modules significantly correlated with abdominal fat deposition across four broiler lines using the consensus module analysis function in the weighted gene coexpression network analysis (WGCNA) package. The eight consensus modules were moderately to strongly preserved in the abdominal fat RNA-Seq dataset of another broiler line (SRP058295). Furthermore, we identified 5462 DEGs between high- and low-abdominal fat lines (FL and LL) (GSE42980) and 6904 DEGs between high- and low-growth (HG and LG) (GSE49121), including 1828 overlapping DEGs with similar expression profiles in both datasets, which were clustered into eight consensus modules. Pyruvate metabolism, fatty acid metabolism, and steroid biosynthesis were significantly enriched in the green, yellow, and medium purple 3 consensus modules. The PPAR signaling pathway and adipocytokine signaling pathway were significantly enriched in the green and purple consensus modules. Autophagy, mitophagy, and lysosome were significantly enriched in the medium purple 3 and yellow consensus modules.ConclusionBased on lipid metabolism pathways enriched in eight consensus modules and the overexpression of numerous lipogenic genes in both FL vs. LL and HG vs. LG, we hypothesize that more fatty acids, triacylglycerols (TAGs), and cholesterol might be synthesized in broilers with high abdominal fat than in broilers with low abdominal fat. According to autophagy, mitophagy, and lysosome enrichment in eight consensus modules, we inferred that autophagy might participate in broiler abdominal fat deposition. Altogether, these studies suggest eight consensus modules associated with abdominal fat deposition in broilers. Our study also provides an idea for investigating the molecular mechanism of abdominal fat deposition across multiple broiler lines.

Project description:BACKGROUND: The chicken (Gallus gallus) is an important model organism that bridges the evolutionary gap between mammals and other vertebrates. Copy number variations (CNVs) are a form of genomic structural variation widely distributed in the genome. CNV analysis has recently gained greater attention and momentum, as the identification of CNVs can contribute to a better understanding of traits important to both humans and other animals. To detect chicken CNVs, we genotyped 475 animals derived from two broiler chicken lines divergently selected for abdominal fat content using chicken 60 K SNP array, which is a high-throughput method widely used in chicken genomics studies. RESULTS: Using PennCNV algorithm, we detected 438 and 291 CNVs in the lean and fat lines, respectively, corresponding to 271 and 188 CNV regions (CNVRs), which were obtained by merging overlapping CNVs. Out of these CNVRs, 99% were confirmed also by the CNVPartition program. These CNVRs covered 40.26 and 30.60 Mb of the chicken genome in the lean and fat lines, respectively. Moreover, CNVRs included 176 loss, 68 gain and 27 both (i.e. loss and gain within the same region) events in the lean line, and 143 loss, 25 gain and 20 both events in the fat line. Ten CNVRs were chosen for the validation experiment using qPCR method, and all of them were confirmed in at least one qPCR assay. We found a total of 886 genes located within these CNVRs, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed they could play various roles in a number of biological processes. Integrating the results of CNVRs, known quantitative trait loci (QTL) and selective sweeps for abdominal fat content suggested that some genes (including SLC9A3, GNAL, SPOCK3, ANXA10, HELIOS, MYLK, CCDC14, SPAG9, SOX5, VSNL1, SMC6, GEN1, MSGN1 and ZPAX) may be important for abdominal fat deposition in the chicken. CONCLUSIONS: Our study provided a genome-wide CNVR map of the chicken genome, thereby contributing to our understanding of genomic structural variations and their potential roles in abdominal fat content in the chicken.

Project description:Background: The chicken (Gallus gallus) is an important model organism that bridges the evolutionary gap between mammals and other vertebrates. Copy number variations (CNVs) are a form of genomic structural variation widely distributed in the genome. CNV analysis has recently gained greater attention and momentum, as the identification of CNVs can contribute to a better understanding of traits important to both humans and other animals. To detect chicken CNVs, we genotyped 475 animals derived from two broiler chicken lines divergently selected for abdominal fat content using chicken 60K SNP array, which is a high-throughput method widely used in chicken genomics studies. Results: Using PennCNV algorithm, we detected 438 and 291 CNVs in the lean and fat lines, respectively, corresponding to 271 and 188 CNV regions (CNVRs), which were obtained by merging overlapping CNVs. Out of these CNVRs, 99% were confirmed also by the CNVPartition program. These CNVRs covered 40.26 and 30.60 Mb of the chicken genome in the lean and fat lines, respectively. Moreover, CNVRs included 176 loss, 68 gain and 27 both (i.e. loss and gain within the same region) events in the lean line, and 143 loss, 25 gain and 20 both events in the fat line. Ten CNVRs were chosen for the validation experiment using qPCR method, and all of them were confirmed in at least one qPCR assay. We found a total of 886 genes located within these CNVRs, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed they could play various roles in a number of biological processes. Integrating the results of CNVRs, known quantitative trait loci (QTL) and selective sweeps for abdominal fat content suggested that some genes (including SLC9A3, GNAL, SPOCK3, ANXA10, HELIOS, MYLK, CCDC14, SPAG9, SOX5, VSNL1, SMC6, GEN1, MSGN1 and ZPAX) may be important for abdominal fat deposition in the chicken. Conclusions: Our study provided a genome-wide CNVR map of the chicken genome, thereby contributing to our understanding of genomic structural variations and their potential roles in abdominal fat content in the chicken.

Project description:Background: The chicken (Gallus gallus) is an important model organism that bridges the evolutionary gap between mammals and other vertebrates. Copy number variations (CNVs) are a form of genomic structural variation widely distributed in the genome. CNV analysis has recently gained greater attention and momentum, as the identification of CNVs can contribute to a better understanding of traits important to both humans and other animals. To detect chicken CNVs, we genotyped 475 animals derived from two broiler chicken lines divergently selected for abdominal fat content using chicken 60K SNP array, which is a high-throughput method widely used in chicken genomics studies. Results: Using PennCNV algorithm, we detected 438 and 291 CNVs in the lean and fat lines, respectively, corresponding to 271 and 188 CNV regions (CNVRs), which were obtained by merging overlapping CNVs. Out of these CNVRs, 99% were confirmed also by the CNVPartition program. These CNVRs covered 40.26 and 30.60 Mb of the chicken genome in the lean and fat lines, respectively. Moreover, CNVRs included 176 loss, 68 gain and 27 both (i.e. loss and gain within the same region) events in the lean line, and 143 loss, 25 gain and 20 both events in the fat line. Ten CNVRs were chosen for the validation experiment using qPCR method, and all of them were confirmed in at least one qPCR assay. We found a total of 886 genes located within these CNVRs, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed they could play various roles in a number of biological processes. Integrating the results of CNVRs, known quantitative trait loci (QTL) and selective sweeps for abdominal fat content suggested that some genes (including SLC9A3, GNAL, SPOCK3, ANXA10, HELIOS, MYLK, CCDC14, SPAG9, SOX5, VSNL1, SMC6, GEN1, MSGN1 and ZPAX) may be important for abdominal fat deposition in the chicken. Conclusions: Our study provided a genome-wide CNVR map of the chicken genome, thereby contributing to our understanding of genomic structural variations and their potential roles in abdominal fat content in the chicken. In total, 475 birds (203 and 272 individuals from the lean and fat lines, respectively) from the 11th generation population of Northeast Agricultural University broiler lines divergently selected for abdominal fat content (NEAUHLF) were used. These 475 birds were genotyped by the chicken 60k SNP chip and PennCNV method were used to perform genome-wide CNV detection.

Project description:This study investigated the effects of dietary corn-resistant starch on lipid metabolism of broilers and its potential relationship with cecal microbiota modulation. A total of three hundred twenty 1-day-old male broilers were randomly assigned into 5 dietary treatments: 1 normal corn-soybean (NC) diet, 1 corn-soybean-based diet supplementation with 20% corn starch (CS), and 3 corn-soybean-based diets supplementation with 4, 8, and 12% corn resistant starch (RS) (identified as 4%RS, 8%RS, and 12%RS, respectively). Each group had 8 replicates with 8 broilers per replicate. The experiment lasted 21 d. The results showed that the abdominal fat percentage were lower in birds from 8%RS and 12%RS groups (0.75 and 0.58%, respectively) than those from NC and CS groups (1.20 and 1.28%, respectively; P < 0.05). The birds from 8%RS and 12%RS groups exhibited lower concentrations of blood triglyceride and nonestesterified fatty acid than those in the NC and CS groups (P < 0.05). Moreover, birds fed diets supplementation with 12% RS decreased the relative mRNA expressions of peroxisome proliferator-activated receptor gamma, ATP citrate-lyase, fatty acid synthase, and acetyl-CoA carboxylase in liver, and glycerol-3-phosphate acyltransferase in abdominal adipose tissue (P < 0.05). Microbiota analysis revealed that birds fed diets supplementation with 8 and 12% RS decreased the abundance of cecal Firmicutes by 23.08 and 20.47% and increased the proportion of Bacteroidetes by 24.33 and 21.92%, respectively, compared with the NC group (P < 0.05). In addition, correlation analysis revealed that many Firmicutes members had highly positive relationship with blood lipid levels and fat storage capacity, which might contribute to the lower abdominal fat phenotype. Overall, broilers receiving diets containing a higher concentration of RS harbor less Firmicutes, which decreased liver fatty acid synthesis and suppress abdominal fat deposition of birds during the starter phase. These findings provide a profound understanding about the relationship between gut microbial composition and lipid metabolism in broilers.

Dataset Information

Analysis of selection signatures on the Z chromosome of bidirectional selection broiler lines for the assessment of abdominal fat content.

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