Genes Related to Fat Metabolism in Pigs and Intramuscular Fat Content of Pork: A Focus on Nutrigenetics and Nutrigenomics
Abstract
:Simple Summary
Abstract
1. Introduction
2. Introduction to Nutrigenetics and Nutrigenomics
“Nutrigenetics is concerned with how genetic variation affects the interaction between these bioactive dietary components and the health and disease potential of individual persons while nutrigenomics is concerned with the effects of bioactive dietary components on the genome, proteome (the sum total of all proteins), and metabolome (the sum of all metabolites)” [36]. “Nutrigenetics focuses on the potential effects of single-nucleotide polymorphisms, copy number variants, epigenetic marks, and other genomic markers on the biological and behavioural responses to micronutrients, macronutrients, and calories whereas nutrigenomics has evolved to signify the field concerned by the investigation of the effects of nutrients on gene expression and related downstream molecular and biological events. Nutrigenomics will increasingly incorporate transcriptomics, proteomics, and metabolomics” [37]. “Nutrigenomics has evolved to signify the field concerned by the investigation of the effects of nutrients on gene expression and related downstream molecular and biological events while nutrigenomics will increasingly incorporate transcriptomics, proteomics, and metabolomics” [38]. “Nutrigenetics aims to understand how the genetic makeup of an individual coordinates the response to a diet while nutrigenomics offers a powerful and exciting approach to unravelling the effects of diet on health” [39]. “The term nutrigenetics refers to the impact of inherited traits on the response to a specific dietary pattern, functional food or supplement on a specific health outcome while the term nutrigenomics refers to the effect of diet on gene expression” [40]. “Nutrigenetics includes the study of individual differences at the genetic level that sways individual responses to diet. These individual differences may be at the level of single nucleotide polymorphisms rather than at the gene level while nutrigenomics comprises the analysis of the effect of nutrient intake on the whole genome (complete genetic make-up; including epigenetic changes), the proteome (the sum total of all proteins), and the metabolome (the sum of all metabolites)” [41]. “Nutrigenetics studies the influence of the genetic variations in the body promoted by the nutrients while nutrigenomics studies the influence of the nutrients on gene expression” [42].
3. Genes Involved in Fat Metabolism and IMF Accretion in Pigs
3.1. Adipogenesis and Lipogenesis
3.2. The De Novo Fatty Acid (FA) Synthesis
3.3. Most Implicated Genes in Fat Metabolism and IMF Deposition in Pigs
4. QTL Regions and SNPs for Fat Metabolism and IMF Accretion in Pigs
5. Epigenetic Mechanisms: Role of mRNAs, miRNAs, DNA Methylation and Histone Modification in Fat Metabolism
5.1. Role of Messenger and Micro RNAs (mRNAs and miRNAs)
5.2. DNA Methylation and Histone Modification in Fat Metabolism
6. Nutritional Genomics in Pigs
6.1. Nutrigenetics and Nutrigenomics
6.2. Impact of Dietary Nutrient Supply on Some Genes Related to Fat Metabolism and IMF Deposition in Pigs
6.2.1. Impact of Dietary Crude Protein Supply
6.2.2. Effect of Lysine, Methionine, Vitamin A, Micro/Macro-Nutrients
- (i)
- How can nutrients be matched to an individual pig’s genetic predisposition especially when dealing with the same genes controlling desired/undesired phenotypic traits in pigs?
- (ii)
- How can we quantitatively define nutrient requirements in swine using an individual gene or whole-genome data to initiate an optimal metabolic or trait response?
- (iii)
- How can we fine-tune nutrients and bioactive compounds in a diet to ensure the heritability of genes related to production performance (meat and milk quality), metabolism and genome stability?
- (iv)
- How do we deal with genes capable of controlling different traits that are functionally interdependent such that altering one could lead to a responsive effect in another one?
- (v)
- How can we harmonize nutritional genomic information in modulating genes and their transcriptional factors and subsequently match them with reference dietary nutrients to alter epigenetic response in pigs?
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Study | Gene Name | Breed | Tissue | Sampling Age (d) or Body Weight (kg) | Trait |
---|---|---|---|---|---|
[60] | FABP4, FASN | Chinese local and Large White | LD, L | 150 d | IMF |
[61] | ADIPOQ, PPARG, LIPE, CIDEC, PLIN1, CIDEA, and FABP4 | Purebred Duroc | LD | 108 kg | IMF |
[62] | ATGL, FAS, HSL, CPT-1B, SREBP-1c, SCD, A-FABP and H-FABP | Wujin and Landrace | LD | 100 kg | IMF |
[63] | RAD9A, IGF2R, SCAP, TCAP, SMYD1, PFKM, DGAT1, GPS2, IGF1, MAPK8, FABP, FABP5, LEPR, UCP3, APOF, and FASN | Landrace and Songliao Black sows | SF, LD, L | 100 kg | Fat deposition |
[64] | H-FABP and LEPR | Duroc, Pietrain, Puławska, Polish Large White (PLW), and Polish Landrace (PL) | LD, SMM, L | Slaughter at 6 age groups 60-, 90-, 120-, 150-, 180- and 210-d-old pig | Fat deposition and IMF |
[65] | FABP3 and LEPR | Duroc, Pietrain, Puławska, Polish Large White (PLW) and Polish Landrace (PL) | LD | 100 kg | Fatty acid metabolism and IMF levels |
[66] | FABP3 and LEPR | Korean native pig and Yorkshire crossed animals. | LD | 90–100 kg | IMF |
[67] | H-FABP and MASTR | Large White | BL | 95–105 kg | IMF |
[68] | PRKAG3 | Large White X Duroc X Pietrain | SM | 110 kg | IMF |
[69] | EEF1A2, FABP3, LDLR, OBSCN, PDHB, TRDN and RYR1 | Landrace X Large White X Pietrain | LD | 30, 60, 90 and 120 kg | IMF |
[70] | IGF2 | Large White, Polish Landrace and Puławska pigs | BL | 100 kg | IMF |
[71] | PPARG and ADRP | Laiwu, Lulai Black, and Large Whites | LD | 114 kg | Fat deposition and IMF |
[72] | PPARA, PPARG, SCD and PCK2 | Shanzhu X Duroc commercial crossbreds | LD | 90 kg | Lipid deposition and IMF |
[73] | BMPER promoter | Duroc X Large White X Yorkshire | LD | - | IMF |
[74] | FABP3 promoter | Large White X Landrace background X Pietrain | LTL, SMM, BL | - | IMF |
[75] | SCD and LEPR | Duroc | GM, LD | 128 kg | IMF and fatty acid composition |
[76] | FASN and LIPE | Jinhua and Landrace | SA | Slaughtered at 35, 80 and 125 days of age | IMF |
[77] | CAV2, MYOZ2, FRZB, FASN, SCD, ESR1, and ADORA1, | Chinese Diannan Small-ear pig, Tibetan, Landrace and Yorkshire | LD | - | Lipid deposition and muscle growth |
[78] | SCD, ACACA, and FASN | Puławska, Polish Large White and Polish Landrace | LD, BL | 100 kg | IMF and lipid metabolism |
[79] | MSTN | MSTN-knockout (KO) cloned Meishan | SF, BL | 70 kg | Fatty acid metabolism |
[80] | FGF2 | Italian Large White | SMM | 150 kg | IMF |
[81] | FABP3, LIPE, IGF1, IGF2, LEP, LEPR, MC4R, PHKG1, RETN, RYR1, SCD, and UBE3C | Chinese Shuai pigs | LD | 80–90 kg | IMF |
[82] | FASN, SCD, ELOVL6, DGAT2, PLIN1, CIDEC, and ADIPOQ | Iberian | LD | 165 kg | Lipid metabolism and higher content of IMF |
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Malgwi, I.H.; Halas, V.; Grünvald, P.; Schiavon, S.; Jócsák, I. Genes Related to Fat Metabolism in Pigs and Intramuscular Fat Content of Pork: A Focus on Nutrigenetics and Nutrigenomics. Animals 2022, 12, 150. https://doi.org/10.3390/ani12020150
Malgwi IH, Halas V, Grünvald P, Schiavon S, Jócsák I. Genes Related to Fat Metabolism in Pigs and Intramuscular Fat Content of Pork: A Focus on Nutrigenetics and Nutrigenomics. Animals. 2022; 12(2):150. https://doi.org/10.3390/ani12020150
Chicago/Turabian StyleMalgwi, Isaac Hyeladi, Veronika Halas, Petra Grünvald, Stefano Schiavon, and Ildikó Jócsák. 2022. "Genes Related to Fat Metabolism in Pigs and Intramuscular Fat Content of Pork: A Focus on Nutrigenetics and Nutrigenomics" Animals 12, no. 2: 150. https://doi.org/10.3390/ani12020150
APA StyleMalgwi, I. H., Halas, V., Grünvald, P., Schiavon, S., & Jócsák, I. (2022). Genes Related to Fat Metabolism in Pigs and Intramuscular Fat Content of Pork: A Focus on Nutrigenetics and Nutrigenomics. Animals, 12(2), 150. https://doi.org/10.3390/ani12020150