RESUMO
The identities of genes that underlie population variation in adipose tissue development in farm animals are poorly understood. Previous studies in our laboratory have suggested that increased fat tissue involves the expression modulation of an array of genes in broiler chickens. Of special interest are eight genes, FGFR3, EPHB2, IGFBP2, GREM1, TNC, COL3A1, ACBD7, and SCD. To understand their expression regulation and response to dietary manipulation, we investigated their mRNA levels after dietary manipulation during early development. Chickens were fed either a recommended standard or a high caloric diet from hatch to eight weeks of age (WOA). The high caloric diet markedly affected bodyweight of the broiler birds. mRNA levels of the eight genes in the abdominal adipose tissue were assayed at 2, 4, 6, and 8 WOA using RT-qPCR. Results indicate that (1) FGFR3 mRNA level was affected significantly by diet, age, and diet:age interaction; (2) COL3A mRNA level was repressed by high caloric diet; (3) mRNA levels of EPHB2, ACBD7, and SCD were affected by age; (4) mRNA level of TNC was modulated by age:diet interaction; (5) changes in GREM1 and IGFBP2 mRNA levels were not statistically different.
RESUMO
BACKGROUND: Chromosomal segmental copy number variation (CNV) has been recently recognized as a very important source of genetic variability. Some CNV loci involve genes or conserved regulatory elements. Compelling evidence indicates that CNVs impact genome functions. The chicken is a very important farm animal species which has also served as a model for biological and biomedical research for hundreds of years. A map of CNVs in chickens could facilitate the identification of chromosomal regions that segregate for important agricultural and disease phenotypes. RESULTS: Ninety six CNVs were identified in three lines of chickens (Cornish Rock broiler, Leghorn and Rhode Island Red) using whole genome tiling array. These CNVs encompass 16 Mb (1.3%) of the chicken genome. Twenty six CNVs were found in two or more animals. Whereas most small sized CNVs reside in none coding sequences, larger CNV regions involve genes (for example prolactin receptor, aldose reductase and zinc finger proteins). These results suggest that chicken CNVs potentially affect agricultural or disease related traits. CONCLUSION: An initial map of CNVs for the chicken has been described. Although chicken genome is approximately one third the size of a typical mammalian genome, the pattern of chicken CNVs is similar to that of mammals. The number of CNVs detected per individual was also similar to that found in dogs, mice, rats and macaques. A map of chicken CNVs provides new information on genetic variations for the understanding of important agricultural traits and disease.
