BackgroundFat deposits in chickens contribute significantly to meat quality attributes such as juiciness, flavor, taste and other organoleptic properties. The quantity of fat deposited increases faster and earlier in the fast-growing chickens than in slow-growing chickens. In this study, Affymetrix Genechip® Chicken Genome Arrays 32773 transcripts were used to compare gene expression profiles in liver and hypothalamus tissues of fast-growing and slow-growing chicken at 8 wk of age. Real-time RT-PCR was used to validate the differential expression of genes selected from the microarray analysis. The mRNA expression of the genes was further examined in fat tissues. The association of single nucleotide polymorphisms of four lipid-related genes with fat traits was examined in a F2 resource population.ResultsFour hundred genes in the liver tissues and 220 genes hypothalamus tissues, respectively, were identified to be differentially expressed in fast-growing chickens and slow-growing chickens. Expression levels of genes for lipid metabolism (SULT1B1, ACSBG2, PNPLA3, LPL, AOAH) carbohydrate metabolism (MGAT4B, XYLB, GBE1, PGM1, HKDC1)cholesttrol biosynthesis (FDPS, LSS, HMGCR, NSDHL, DHCR24, IDI1, ME1) HSD17B7 and other reaction or processes (CYP1A4, CYP1A1, AKR1B1, CYP4V2, DDO) were higher in the fast-growing White Recessive Rock chickens than in the slow-growing Xinghua chickens. On the other hand, expression levels of genes associated with multicellular organism development, immune response, DNA integration, melanin biosynthetic process, muscle organ development and oxidation-reduction (FRZB, DMD, FUT8, CYP2C45, DHRSX, and CYP2C18) and with glycol-metabolism (GCNT2, ELOVL 6, and FASN), were higher in the XH chickens than in the fast-growing chickens. RT-PCR validated high expression levels of nine out of 12 genes in fat tissues. The G1257069A and T1247123C of the ACSBG2 gene were significantly associated with abdominal fat weight. The G4928024A of the FASN gene were significantly associated with fat bandwidth, and abdominal fat percentage. The C4930169T of the FASN gene was associated with abdominal fat weight while the A59539099G of the ELOVL 6 was significantly associated with subcutaneous fat. The A8378815G of the DDT was associated with fat band width.ConclusionThe differences in fat deposition were reflected with differential gene expressions in fast and slow growing chickens.

Food web and gene regulatory networks (GRNs) are large biological networks, both of which can be analyzed using the May–Wigner theory. According to the theory, networks as large as mammalian GRNs would require dedicated gene products for stabilization. We propose that microRNAs (miRNAs) are those products. More than 30% of genes are repressed by miRNAs, but most repressions are too weak to have a phenotypic consequence. The theory shows that (i) weak repressions cumulatively enhance the stability of GRNs, and (ii) broad and weak repressions confer greater stability than a few strong ones. Hence, the diffuse actions of miRNAs in mammalian cells appear to function mainly in stabilizing GRNs. The postulated link between mRNA repression and GRN stability can be seen in a different light in yeast, which do not have miRNAs. Yeast cells rely on non-specific RNA nucleases to strongly degrade mRNAs for GRN stability. The strategy is suited to GRNs of small and rapidly dividing yeast cells, but not the larger mammalian cells. In conclusion, the May–Wigner theory, supplanting the analysis of small motifs, provides a mathematical solution to GRN stability, thus linking miRNAs explicitly to ‘developmental canalization’.

BackgroundThe elevation of egg production and the inhibition of incubation behavior are the aims of modern poultry production. Prolactin (PRL) gene is confirmed to be critical for the onset and maintenance of these reproductive behaviors in birds. Through PRL, dopamine D1 receptor (DRD1) was also involved in the regulation of chicken reproductive behavior. However, the genetic effects of this gene on chicken egg production and broodiness have not been studied extensively. The objective of this research was to evaluate the genetic effects of the DRD1 gene on chicken egg production and broodiness traits.ResultsIn this study, the chicken DRD1 gene was screened for the polymorphisms by cloning and sequencing and 29 variations were identified in 3,342 bp length of this gene. Seven single nucleotide polymorphism (SNPs) among these variations, including a non-synonymous mutation (A+505G, Ser169Gly), were located in the coding region and were chosen to analyze their association with chicken egg production and broodiness traits in 644 Ningdu Sanhuang individuals. Two SNPs, G+123A and C+1107T, were significantly associated with chicken broody frequency (P < 0.05). Significant association was also found between the G+1065A - C+1107T haplotypes and chicken broody frequency (P < 0.05). In addition, the haplotypes of G+123A and T+198C were significantly associated with weight of first egg (EW) (P = 0.03). On the other hand, the distribution of the DRD1 mRNA was observed and the expression difference was compared between broodiness and non-broodiness chickens. The DRD1 mRNA was predominantly expressed in subcutaneous fat and abdominal fat of non-broodiness chicken, and then in heart, kidney, oviduct, glandular stomach, hypothalamus, and pituitary. In subcutaneous fat and abdominal fat, the level of non-broodiness was 26 to 28 times higher than that of broodiness. In pituitary, it was 5-fold higher. In heart, oviduct, and kidney, a 2-3 times decrease from non-broodiness to broodiness was displayed. In glandular stomach and hypothalamus, the level seen in non-broodiness and broodiness was almost the same.ConclusionThe polymorphisms of the DRD1 gene and their haplotypes were associated with chicken broody frequency and some egg production traits. The mRNA distribution was significant different between broodiness and non-broodiness chickens.

Why do microRNAs (miRNAs) weakly repress so many targets such that most targets do not have phenotypic effects? An increasingly accepted view posits that weak targeting has no biological function and each miRNA effectively has only a few functional targets. Here, we review the evolutionary arguments for this postulate and find these arguments seriously flawed. In contrast, from the systems perspective, the power of broad and weak targeting may reside in the cumulative effects of all repressions, which collectively stabilize gene regulatory networks. This view predicts that miRNAs would show little tendency to downsize their target pools. A survey of "twin-miRs" production indeed validates this prediction.

MCST shows a unique morphology with characteristic immunophenotype. β-catenin expression in the nucleus and β-catenin mutations were identified in the majority of cases, which suggests that the Wnt/β-catenin pathway may play a crucial role in the tumorigenesis of MCST.