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:The purpose of this microarray experiment was to validate the Del-Mar 14K Chicken Integrated Systems Microarray for different chicken tissues and to determine the utility of this chicken cDNA microarray for other closely related and more distant avian species. The Del-Mar 14 K array was constructed from cDNAs amplified from EST clones sequenced from five normalized chicken cDNA libraries derived from neuroendocrine (5,929), abdominal fat (4,800), liver (2,635), skeletal muscle (2,398), reproductive tract (2,008), 387 long (70mer) oligonucleotides and 72 quality control spots. The array contains 17,770 cDNA clones, where protein matches were found by BlastX analysis for 68% of chicken contigs and 46% of singleton sequences represented on the array. A reference RNA design was used for the hybridization of total RNA from four chicken tissues (liver, abdominal fat, breast muscle and hypothalamus) and the cross-species hybridization (CSH) of total RNA from tissue from birds representing four orders of the Class Aves [Galliformes (chicken, Coturnix quail and domestic turkey), Anseriformes (Peking duck), Falconiformes (American kestrel) and Passeriformes (American tree sparrow)]. A reference RNA pool was made from an equal amount of high-quality total RNA extracted from chicken liver, abdominal fat, breast muscle and hypothalamus. Each of the 43 microarrays was co-hybridized with Cy3-labeled cDNA targets from one of the avian tissue samples and Cy5-labled cDNA targets from the reference chicken RNA pool. Loess-normalized data were used to determine the number of cDNAs expressed in chicken tissues and the number of genes (cDNAs) detectable by cross-hybridization with various avian tissue samples. The Cy5-labeled reference samples were used to determine the coefficient of variation across the 43 microarrays. This study shows a remarkably high level of cross hybridization of Cy3-labeled cDNA targets from a wide range of avian species to the Del-Mar 14K microarray, where 38 to 62% of the cDNA probes on the chicken array (genes) were detectable. Keywords: Transcriptional profiling, Del-Mar 14K Chicken Integrated Systems Microarray validation, multi-tissues, cross-species hybridization, class Aves

			Action	DRS
	SRR26595200_1.fastq.gz	Fastqsanger.gz
	SRR26595200_2.fastq.gz	Fastqsanger.gz
	SRR26595201_1.fastq.gz	Fastqsanger.gz
	SRR26595201_2.fastq.gz	Fastqsanger.gz
	SRR26595202_1.fastq.gz	Fastqsanger.gz

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