Functional Annotation of Genomic Data with Metabolic Inference

Lipid metabolism analysis in liver of different chicken genotypes and impact on nutritionally relevant polyunsaturated fatty acids of meat

Humans and mammalian species are unable to synthesize significant amounts of polyunsaturated fatty acids (PUFA), which therefore must be introduced with the diet. In birds, lipogenesis takes place primarily in the liver, whereas adipose tissue serves as the storage site for triacylglycerols (TG, composed by 80-85% esterified fatty acids). However, both the nature (unsaturation level, n-3, or n-6 series) and the allocation (such as constituents of complexed lipids) of PUFA are very important to evaluate their function in lipid metabolism. The objective of the present investigation was to study the liver lipid metabolism, with particular attention to non-esterified fatty acids (NEFA), TG, phospholipids (PL), FADS2 gene expression, and Δ6-desaturase activity of three chicken genotypes, Leghorn (Leg), Ross 308 (Ross), and their crossbreed (LxR), by LC/MS analysis. The concentration of single fatty acids in muscle was quantified by GC-FID. The results showed that the Ross has a lipid metabolism related mainly to storage and structural roles, exhibiting higher levels of TG, phosphatidylethanolamine (PE) and phosphatidylcholine (PC) that are largely unsaturated. Meanwhile Leg showed a relevant amount of n-3 NEFA characterized by a higher phosphatidylserine (PS) unsaturation level, FADS2 gene expression and enzyme activity. The LxR seem to have a moderate trend: n-6 and n-3 NEFA showed intermediate values compared with that of the Ross and Leg and the TG trend was similar to that of the Ross, while PE and PC were largely unsaturated (mainly 6 and 7 UNS most of the metabolic energy for storage fatty acids in their tissues (TG) whereas, the Leg birds were characterized by different lipid metabolism showing in their liver a higher content of n-3 NEFA and higher unsaturation level in PS. Furthers details are needed to better attribute the lipid energy to the different metabolic portion.

Very Low Crude Protein and Varying Glycine Concentrations in the Diet Affect Growth Performance, Characteristics of Nitrogen Excretion, and the Blood Metabolome of Broiler Chickens

BACKGROUND

The minimum to which dietary crude protein (CP) level for broiler chickens can be reduced without decreasing growth and the glycine equivalent (Glyequi) concentration required are not known. The plasma metabolome might reflect dietary influences on physiological processes.

OBJECTIVE

The aim of this study was to investigate the effect of 3 low CP levels with 4 Glyequi concentrations on growth and characteristics of nitrogen excretion, and to identify plasma metabolome variations.

METHODS

Male Ross308 broiler chickens were provided 1 of 12 dietary treatments in 84 metabolism cages (10/cage) from days 7 to 21. Three diets with 163 (CP163), 147 (CP147), and 132 (CP132) g CP/kg were formulated, each containing 12, 15, 18, and 21 g Glyequi/kg. Essential amino acid concentrations were the same in all diets. Animals and feed were weighed on days 7 and 21 to determine average daily gain (ADG) and gain:feed ratio (G:F). Excreta were collected from days 18 to 21 to analyze nitrogenous components, and blood was obtained on day 21 to conduct a metabolome analysis.

RESULTS

Two-factor ANOVA showed significant interaction effects for ADG, G:F, and nitrogen efficiency (P < 0.001). Reduction of CP decreased ADG and G:F, and increased nitrogen efficiency. Glyequi supplementation increased ADG (by 7.9 g/d) and G:F (by 0.07 g/g) at CP132. The ADG (by 2.4 g/d) at CP147 and G:F (by 0.02 g/g) at CP147 and CP163 increased up to 15 g Glyequi/kg. Multivariate statistical analysis showed an influence of Glyequi on plasma acylcarnitine and lysophosphatidylcholine concentrations, and a decrease of plasma phosphatidylcholine and sphingomyelin concentrations with reduced CP.

CONCLUSIONS

These results suggest that a nutrient other than Glyequi limited growth when CP was reduced from CP163 to CP147, and that the response of broiler chickens to Glyequi is dependent on the dietary CP level. Plasma metabolites indicate dietary influences on the physiological state of the animals.

Functional genomics of the chicken--a model organism

Since the sequencing of the genome and the development of high-throughput tools for the exploration of functional elements of the genome, the chicken has reached model organism status. Functional genomics focuses on understanding the function and regulation of genes and gene products on a global or genome-wide scale. Systems biology attempts to integrate functional information derived from multiple high-content data sets into a holistic view of all biological processes within a cell or organism. Generation of a large collection ( approximately 600K) of chicken expressed sequence tags, representing most tissues and developmental stages, has enabled the construction of high-density microarrays for transcriptional profiling. Comprehensive analysis of this large expressed sequence tag collection and a set of approximately 20K full-length cDNA sequences indicate that the transcriptome of the chicken represents approximately 20,000 genes. Furthermore, comparative analyses of these sequences have facilitated functional annotation of the genome and the creation of several bioinformatic resources for the chicken. Recently, about 20 papers have been published on transcriptional profiling with DNA microarrays in chicken tissues under various conditions. Proteomics is another powerful high-throughput tool currently used for examining the dynamics of protein expression in chicken tissues and fluids. Computational analyses of the chicken genome are providing new insight into the evolution of gene families in birds and other organisms. Abundant functional genomic resources now support large-scale analyses in the chicken and will facilitate identification of transcriptional mechanisms, gene networks, and metabolic or regulatory pathways that will ultimately determine the phenotype of the bird. New technologies such as marker-assisted selection, transgenics, and RNA interference offer the opportunity to modify the phenotype of the chicken to fit defined production goals. This review focuses on functional genomics in the chicken and provides a road map for large-scale exploration of the chicken genome.