1
|
Abdalla BA, Chen J, Nie Q, Zhang X. Genomic Insights Into the Multiple Factors Controlling Abdominal Fat Deposition in a Chicken Model. Front Genet 2018; 9:262. [PMID: 30073018 PMCID: PMC6060281 DOI: 10.3389/fgene.2018.00262] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Accepted: 06/28/2018] [Indexed: 12/12/2022] Open
Abstract
Genetic selection for an increased growth rate in meat-type chickens has been accompanied by excessive fat accumulation particularly in abdominal cavity. These progressed to indirect and often unhealthy effects on meat quality properties and increased feed cost. Advances in genomics technology over recent years have led to the surprising discoveries that the genome is more complex than previously thought. Studies have identified multiple-genetic factors associated with abdominal fat deposition. Meanwhile, the obesity epidemic has focused attention on adipose tissue and the development of adipocytes. The aim of this review is to summarize the current understanding of genetic/epigenetic factors associated with abdominal fat deposition, or as it relates to the proliferation and differentiation of preadipocytes in chicken. The results discussed here have been identified by different genomic approaches, such as QTL-based studies, the candidate gene approach, epistatic interaction, copy number variation, single-nucleotide polymorphism screening, selection signature analysis, genome-wide association studies, RNA sequencing, and bisulfite sequencing. The studies mentioned in this review have described multiple-genetic factors involved in an abdominal fat deposition. Therefore, it is inevitable to further study the multiple-genetic factors in-depth to develop novel molecular markers or potential targets, which will provide promising applications for reducing abdominal fat deposition in meat-type chicken.
Collapse
Affiliation(s)
- Bahareldin A. Abdalla
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, China
- National-Local Joint Engineering Research Center for Livestock Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
| | - Jie Chen
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, China
- National-Local Joint Engineering Research Center for Livestock Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
| | - Qinghua Nie
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, China
- National-Local Joint Engineering Research Center for Livestock Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
| | - Xiquan Zhang
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, China
- National-Local Joint Engineering Research Center for Livestock Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
- Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, The Key Lab of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture, Guangzhou, China
| |
Collapse
|
2
|
Kaczor U, Poltowicz K, Kucharski M, Sitarz AM, Nowak J, Wojtysiak D, Zieba DA. Effect of ghrelin and leptin receptors genes polymorphisms on production results and physicochemical characteristics of M. pectoralis superficialis in broiler chickens. ANIMAL PRODUCTION SCIENCE 2017. [DOI: 10.1071/an15152] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Ghrelin and leptin and their receptors GHSR and LEPR regulate food intake, the processes in adipose tissue, and the body’s energy homeostasis in mammals. The aim of the present study was to determine the effect of GHSR/Csp6I and LEPR/Bsh1236I polymorphisms on the meat production parameters of broiler chickens reared to 42 days of age. In 318 fast-growing Hubbard Flex and Ross 308 chickens, g.3051C > T substitution at the GHSR locus and a GGTCAA deletion at positions g.3407_3409del and g.3411_3413del were identified. The use of restriction enzyme Bsh1236I showed the presence of two transitions g.352C > T and g.427G > A in LEPR locus. The chickens were classified into four GHSR/Csp6I and into five LEPR/Bsh1236I diplotypes. GHSR and LEPR polymorphisms were found to influence final bodyweight, daily gain, dressing percentage without giblets, proportion of giblets and the quality characteristics of M. pectoralis superficialis. GHSR/Csp6I and LEPR/Bsh1236I had an effect on pH24 h (P < 0.05) and lightness (L*) of M. pectoralis superficialis (P < 0.05), whereas GHSR/Csp6I influenced shear force (P < 0.05) and thawing loss (P < 0.05). GHSR/Csp6I and LEPR/Bsh1236I were found to have no effect on the abdominal fat content in chicken carcasses. Single nucleotide polymorphisms reported in the present study could be used in breeding programs as selection markers for growth traits and poultry meat quality.
Collapse
|
3
|
Khalifeh-Soltani A, Gupta D, Ha A, Iqbal J, Hussain M, Podolsky MJ, Atabai K. Mfge8 regulates enterocyte lipid storage by promoting enterocyte triglyceride hydrolase activity. JCI Insight 2016; 1:e87418. [PMID: 27812539 DOI: 10.1172/jci.insight.87418] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
The small intestine has an underappreciated role as a lipid storage organ. Under conditions of high dietary fat intake, enterocytes can minimize the extent of postprandial lipemia by storing newly absorbed dietary fat in cytoplasmic lipid droplets. Lipid droplets can be subsequently mobilized for the production of chylomicrons. The mechanisms that regulate this process are poorly understood. We report here that the milk protein Mfge8 regulates hydrolysis of cytoplasmic lipid droplets in enterocytes after interacting with the αvβ3 and αvβ5 integrins. Mice deficient in Mfge8 or the αvβ3 and αvβ5 integrins accumulate excess cytoplasmic lipid droplets after a fat challenge. Mechanistically, interruption of the Mfge8-integrin axis leads to impaired enterocyte intracellular triglyceride hydrolase activity in vitro and in vivo. Furthermore, Mfge8 increases triglyceride hydrolase activity through a PI3 kinase/mTORC2-dependent signaling pathway. These data identify a key role for Mfge8 and the αvβ3 and αvβ5 integrins in regulating enterocyte lipid processing.
Collapse
Affiliation(s)
- Amin Khalifeh-Soltani
- Department of Medicine.,Cardiovascular Research Institute.,Lung Biology Center, University of California, San Francisco, San Francisco, California, USA
| | - Deepti Gupta
- Department of Medicine.,Cardiovascular Research Institute.,Lung Biology Center, University of California, San Francisco, San Francisco, California, USA
| | - Arnold Ha
- Department of Medicine.,Cardiovascular Research Institute
| | - Jahangir Iqbal
- Departments of Cell Biology and Pediatrics, SUNY Downstate Medical Center, Brooklyn, New York, USA
| | - Mahmood Hussain
- Departments of Cell Biology and Pediatrics, SUNY Downstate Medical Center, Brooklyn, New York, USA
| | - Michael J Podolsky
- Department of Medicine.,Cardiovascular Research Institute.,Lung Biology Center, University of California, San Francisco, San Francisco, California, USA
| | - Kamran Atabai
- Department of Medicine.,Cardiovascular Research Institute.,Lung Biology Center, University of California, San Francisco, San Francisco, California, USA
| |
Collapse
|
4
|
Stainton JJ, Haley CS, Charlesworth B, Kranis A, Watson K, Wiener P. Detecting signatures of selection in nine distinct lines of broiler chickens. Anim Genet 2014; 46:37-49. [PMID: 25515710 DOI: 10.1111/age.12252] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/03/2014] [Indexed: 01/26/2023]
Abstract
Modern commercial chickens have been bred for one of two specific purposes: meat production (broilers) or egg production (layers). This has led to large phenotypic changes, so that the genomic signatures of selection may be detectable using statistical techniques. Genetic differentiation between nine distinct broiler lines was calculated using Weir and Cockerham's pairwise FST estimator for 11 003 genome-wide markers to identify regions showing evidence of differential selection across lines. Differentiation measures were averaged into overlapping sliding windows for each line, and a permutation approach was used to determine the significance of each window. A total of 51 regions were found to show significant differentiation between the lines. Several lines were consistently found to share significant regions, suggesting that the pattern of line divergence is related to selection for broiler traits. The majority of the 51 regions contain QTL relating to broiler traits, but only five of them were found to be significantly enriched for broiler QTL, including a region on chromosome 27 containing 39 broiler QTL and 114 genes. Additionally, a number of these regions have been identified by other selection mapping studies. This study has identified a large number of potential selection signatures, and further tests with higher-density marker data may narrow these regions down to individual genes.
Collapse
Affiliation(s)
- John J Stainton
- The Roslin Institute and R(D)SVS, University of Edinburgh, Midlothian, EH25 9RG, UK
| | | | | | | | | | | |
Collapse
|
5
|
Khalifeh-Soltani A, McKleroy W, Sakuma S, Cheung YY, Tharp K, Qiu Y, Turner SM, Chawla A, Stahl A, Atabai K. Mfge8 promotes obesity by mediating the uptake of dietary fats and serum fatty acids. Nat Med 2014; 20:175-83. [PMID: 24441829 DOI: 10.1038/nm.3450] [Citation(s) in RCA: 85] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2013] [Accepted: 12/11/2013] [Indexed: 12/14/2022]
Abstract
Fatty acids are integral mediators of energy storage, membrane formation and cell signaling. The pathways that orchestrate uptake of fatty acids remain incompletely understood. Expression of the integrin ligand Mfge8 is increased in human obesity and in mice on a high-fat diet, but its role in obesity is unknown. We show here that Mfge8 promotes the absorption of dietary triglycerides and the cellular uptake of fatty acid and that Mfge8-deficient (Mfge8(-/-)) mice are protected from diet-induced obesity, steatohepatitis and insulin resistance. Mechanistically, we found that Mfge8 coordinates fatty acid uptake through αvβ3 integrin- and αvβ5 integrin-dependent phosphorylation of Akt by phosphatidylinositide-3 kinase and mTOR complex 2, leading to translocation of Cd36 and Fatp1 from cytoplasmic vesicles to the cell surface. Collectively, our results imply a role for Mfge8 in regulating the absorption and storage of dietary fats, as well as in the development of obesity and its complications.
Collapse
Affiliation(s)
- Amin Khalifeh-Soltani
- 1] Cardiovascular Research Institute, University of California, San Francisco, San Francisco, California, USA. [2] Lung Biology Center, University of California, San Francisco, San Francisco, California, USA. [3] Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - William McKleroy
- 1] Cardiovascular Research Institute, University of California, San Francisco, San Francisco, California, USA. [2] Lung Biology Center, University of California, San Francisco, San Francisco, California, USA. [3] Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Stephen Sakuma
- 1] Cardiovascular Research Institute, University of California, San Francisco, San Francisco, California, USA. [2] Lung Biology Center, University of California, San Francisco, San Francisco, California, USA. [3] Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Yuk Yin Cheung
- 1] Cardiovascular Research Institute, University of California, San Francisco, San Francisco, California, USA. [2] Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Kevin Tharp
- 1] Metabolic Biology, University of California, Berkeley, Berkeley, California, USA. [2] Department of Nutritional Sciences and Toxicology, University of California, Berkeley, Berkeley, California, USA
| | - Yifu Qiu
- Cardiovascular Research Institute, University of California, San Francisco, San Francisco, California, USA
| | | | - Ajay Chawla
- 1] Cardiovascular Research Institute, University of California, San Francisco, San Francisco, California, USA. [2] Department of Medicine, University of California, San Francisco, San Francisco, California, USA. [3] Department of Physiology, University of California, San Francisco, San Francisco, California, USA
| | - Andreas Stahl
- 1] Metabolic Biology, University of California, Berkeley, Berkeley, California, USA. [2] Department of Nutritional Sciences and Toxicology, University of California, Berkeley, Berkeley, California, USA
| | - Kamran Atabai
- 1] Cardiovascular Research Institute, University of California, San Francisco, San Francisco, California, USA. [2] Lung Biology Center, University of California, San Francisco, San Francisco, California, USA. [3] Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| |
Collapse
|
6
|
Qanbari S, Strom TM, Haberer G, Weigend S, Gheyas AA, Turner F, Burt DW, Preisinger R, Gianola D, Simianer H. A high resolution genome-wide scan for significant selective sweeps: an application to pooled sequence data in laying chickens. PLoS One 2012; 7:e49525. [PMID: 23209582 PMCID: PMC3510216 DOI: 10.1371/journal.pone.0049525] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2012] [Accepted: 10/10/2012] [Indexed: 12/12/2022] Open
Abstract
In most studies aimed at localizing footprints of past selection, outliers at tails of the empirical distribution of a given test statistic are assumed to reflect locus-specific selective forces. Significance cutoffs are subjectively determined, rather than being related to a clear set of hypotheses. Here, we define an empirical p-value for the summary statistic by means of a permutation method that uses the observed SNP structure in the real data. To illustrate the methodology, we applied our approach to a panel of 2.9 million autosomal SNPs identified from re-sequencing a pool of 15 individuals from a brown egg layer line. We scanned the genome for local reductions in heterozygosity, suggestive of selective sweeps. We also employed a modified sliding window approach that accounts for gaps in the sequence and increases scanning resolution by moving the overlapping windows by steps of one SNP only, and suggest to call this a “creeping window” strategy. The approach confirmed selective sweeps in the region of previously described candidate genes, i.e. TSHR, PRL, PRLHR, INSR, LEPR, IGF1, and NRAMP1 when used as positive controls. The genome scan revealed 82 distinct regions with strong evidence of selection (genome-wide p-value<0.001), including genes known to be associated with eggshell structure and immune system such as CALB1 and GAL cluster, respectively. A substantial proportion of signals was found in poor gene content regions including the most extreme signal on chromosome 1. The observation of multiple signals in a highly selected layer line of chicken is consistent with the hypothesis that egg production is a complex trait controlled by many genes.
Collapse
Affiliation(s)
- Saber Qanbari
- Animal Breeding and Genetics Group, Department of Animal Sciences, Georg-August University, Göttingen, Germany.
| | | | | | | | | | | | | | | | | | | |
Collapse
|