Transcriptomic analysis to elucidate the molecular mechanisms that underlie feed efficiency in meat-type chickens
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Feed efficiency phenotypes defined by genotypes or gene markers are unknown. To date, there are only limited studies on global gene expression profiling on feed efficiency. The objective of this study was to identify genes and pathways associated with residual feed intake (RFI) through transcriptional profiling of duodenum at two different ages in a chicken population divergently selected for low (LRFI) or high (HRFI) RFI. The global gene expression differences in LRFI and HRFI were assessed by the Affymetrix GeneChip® Chicken Genome Array and RT-PCR using duodenal tissue on days 35 and 42. The Ingenuity Pathway Analysis program was used to identify canonical and gene network pathways associated with RFI. A global view of gene expression differences between LRFI and HRFI suggest that RFI can be explained by differences in cell division, growth, proliferation and apoptosis, protein synthesis, lipid metabolism, and molecular transport of cellular molecules. Chickens selected for improved RFI achieve efficiency by reducing feed intake with a nominal or no change in weight gain by either up-regulating CD36, PPARα, HMGCS2, GCG or down-regulating PCSK2, CALB1, SAT1, and SGK1 genes within the lipid metabolism, small molecule biochemistry, molecular transport, cell death, and protein synthesis molecular and cellular functions. Chickens selected for reduced RFI via reduced feed intake with no change in weight gain achieve feed efficiency for growth by the up-regulation of genes that reduce appetite with increased cellular oxidative stress, prolonged cell cycle, DNA damage, and apoptosis in addition to increased oxidation of dietary fat and efficient fatty acids transported from the intestines.
KeywordsResidual feed intake Microarray RT-PCR Gene network Chickens
This work was supported by USDA NRI grant 2009-35205-05208 and Georgia Food Industry Partnership grant 10.26KR696-110. We appreciate the assistance of Christopher McKenzie of the Poultry Research Center of University of Georgia.
Conflict of interest
The authors declare that they have no conflict of interest.
- Aggrey SE, Sanglikar AP, Karnuah AB, McMurtry JP (2008) Molecular basis of feed efficiency in meat-type birds. In: Proceedings 23rd World Poultry Congress, CD Rom, Brisbane, p 8Google Scholar
- Gachon F, Leuenberger N, Claudel T, Gos P, Jouffe C, Olela FF, de Mollerat du Jeu X, Wahli W, Schibler U (2011) Proline- and acidic amino acid-rich basic leucine zipper proteins modulates peroxisome proliferator-activated receptor α (PPARα) activity. Proc Natl Acad Sci USA 108: 4794–4799Google Scholar
- Huang ZH, Luque RM, Kineman RD, Mazzone T (2007) Nutritional regulation of adipose tissue apolipoprotein E expression. Am J Phyisol 293:E203–E209Google Scholar
- Iqbal M, Pumford N, Lassiter K, Tang ZX, Wing T, Cooper M, Bottje WG (2005) Compromised liver mitochondrial function and complex activity in low feed efficient broilers within a single line associated with higher oxidative stress and differential protein expression. Poult Sci 84:933–941CrossRefPubMedGoogle Scholar
- Kong B-W, Song JJ, Lee JY, Hargis BM, Wing T, Lassiter K, Bottje W (2011) Gene expression in breast muscle associated with feed efficiency in a single broiler line using a chicken 44 K oligo microarray. I. Top differentially expressed genes. Poul Sci 90:2535–2547Google Scholar
- Lkhagvadorj S, Qu L, Cai W, Couture OP, Barb R, Hausman GJ, Nettleton D, Anderson LL, Dekkers JCM, Tuggle CK (2010) Gene expression profiling of the short-term adaptive response to acute restriction in liver and adipose tissues of pigs differing in feed efficiency. Am J Physiol Regul Integr Comp Physiol 298:R494–R507CrossRefPubMedGoogle Scholar
- Ramirez de Molina A, Gallego-Ortega D, Sarmentero-Estrada J, Lagares D, Gomez Del Pulgar T, Bandres E, Garcia-Foncillas J, Lacal JC (2008) Choline kinase as a link connecting phospholipid metabolism and cell cycle regulation: implications in cancer therapy. Int J Biochem Cell Biol 40:1753–1763CrossRefPubMedGoogle Scholar
- SAS Institute (2000) “SAS/STAT User’s Guide,” Version 8 edn. SAS Inst. Inc., Cary, NCGoogle Scholar