Asian-Australasian Journal of Animal Sciences

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
권호 표지
DOI QR코드

DOI QR Code

Identification of quantitative trait loci for the fatty acid composition in Korean native chicken

  • Jin, Shil (Division of Animal & Dairy Science, Chungnam National University) ;
  • Park, Hee Bok (Subtropical Livestock Research Institute, National Institute of Animal Science) ;
  • Seo, Dongwon (Division of Animal & Dairy Science, Chungnam National University) ;
  • Choi, Nu Ri (Division of Animal & Dairy Science, Chungnam National University) ;
  • Manjula, Prabuddha (Division of Animal & Dairy Science, Chungnam National University) ;
  • Cahyadi, Muhammad (Department of Animal Science, Faculty of Agriculture, Sebelas Maret University) ;
  • Jung, Samooel (Division of Animal & Dairy Science, Chungnam National University) ;
  • Jo, Cheorun (Department of Agricultural Biotechnology, Center for Food and Bioconvergence, and Research Institute of Agriculture and Life Science, Seoul National University) ;
  • Lee, Jun Heon (Division of Animal & Dairy Science, Chungnam National University)
  • Received : 2017.10.23
  • Accepted : 2018.01.20
  • Published : 2018.08.01
Download PDF
⟨ Previous Next ⟩

Abstract

Objective: Fatty acid composition is one of the most important meat quality traits because it can contribute to functional, sensorial, and nutritional factors. In this study, quantitative trait locus (QTL) analyses for fatty acid composition traits were investigated in thigh and breast meat of Korean native chicken (KNC). Methods: In total, 18 fatty acid composition traits were investigated from each meat sample using 83 parents, and 595 $F_1$ chicks of 20 week old. Genotype assessment was performed using 171 informative DNA markers on 26 autosomes. The KNC linkage map was constructed by CRI-MAP software, which calculated genetic distances, with map orders between markers. The half-sib and full-sib QTL analyses were performed using GridQTL and SOLAR programs, respectively. Results: In total, 30 QTLs (12 in the thigh and 18 in the breast meat) were detected by the half-sib analysis and 7 QTLs (3 in the thigh and 4 in the breast meat) were identified by the full-sib analysis. Conclusion: With further verification of the QTL regions using additional markers and positional candidate gene studies, these results can provide valuable information for determining causative mutations affecting the fatty acid composition of KNC meat. Moreover, these findings may aid in the selection of birds with favorable fatty acid composition traits.

Keywords

References

  1. Rikimaru K, Takahashi H. A method for discriminating a Japanese brand of chicken, the Hinai-jidori, using microsatellite markers. Poult Sci 2007;86:1881-6.
  2. Tang H, Gong Y, Wu C, et al. Variation of meat quality traits among five genotypes of chicken. Poult Sci 2009;88:2212-8. https://doi.org/10.3382/ps.2008-00036
  3. Chumngoen W, Tan F-J. Relationships between descriptive sensory attributes and physicochemical analysis of broiler and Taiwan native chicken breast meat. Asian-Australas J Anim Sci 2015;28:1028-37. https://doi.org/10.5713/ajas.14.0275
  4. Sasaki K, Motoyama M, Tagawa Y, et al. Qualitative and quantitative comparisons of texture characteristics between broiler and jidori-niku, Japanese indigenous chicken meat, assessed by a trained panel. Nippon Kakin Gakkaishi 2017;54:87-96.
  5. Choe J-H, Nam K-C, Jung S, et al. Differences in the quality characteristics between commercial Korean native chickens and broilers. Korean J Food Sci Anim Resour 2010;30:13-9. https://doi.org/10.5851/kosfa.2010.30.1.13
  6. Jayasena DD, Jung S, Kim HJ, et al. Comparison of quality traits of meat from Korean native chickens and broilers used in two different traditional Korean cuisines. Asian-Australas J Anim Sci 2013;26:1038-46. https://doi.org/10.5713/ajas.2012.12684
  7. Jayasena DD, Jung S, Kim HJ, et al. Taste-active compound levels in Korean native chicken meat: The effects of bird age and the cooking process. Poult Sci 2015;94:1964-72. https://doi.org/10.3382/ps/pev154
  8. De Smet S, Raes K, Demeyer D. Meat fatty acid composition as affected by fatness and genetic factors: a review. Anim Res 2004;53:81-98. https://doi.org/10.1051/animres:2004003
  9. Miller S, Dykes D, Polesky H. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res 1988;16:1215. https://doi.org/10.1093/nar/16.3.1215
  10. Green P. Construction and comparison of chromosome 21 radiation hybrid and linkage maps using CRI-MAP. Cytogenet Cell Genet 1992;59:122-4. https://doi.org/10.1159/000133221
  11. Jin S, Lee JH, Seo DW, et al. A major locus for quantitatively measured shank skin color traits in Korean native chicken. Asian-Australas J Anim Sci 2016;29:1555-61. https://doi.org/10.5713/ajas.16.0183
  12. Folch J, Lees M, Sloane-Stanley G. A simple method for the isolation and purification of total lipids from animal tissues. J Biol Chem 1957;226:497-509.
  13. Wilson AJ, Reale D, Clements MN, et al. An ecologist's guide to the animal model. J Anim Ecol 2010;79:13-26. https://doi.org/10.1111/j.1365-2656.2009.01639.x
  14. Seaton G, Hernandez J, Grunchec J-A, et al. GridQTL: a grid portal for QTL mapping of compute intensive datasets. In: Proceedings of the 8th world congress on genetics applied to livestock production; 2006 August 13-18: Belo Horizonte, MG, Brasil.
  15. Churchill GA, Doerge RW. Empirical threshold values for quantitative trait mapping. Genetics 1994;138:963-71.
  16. Almasy L, Blangero J. Variance component methods for analysis of complex phenotypes. Cold Spring Harb Protoc 2010;2010:pdb.top77.
  17. Piepho H-P. A quick method for computing approximate thresholds for quantitative trait loci detection. Genetics 2001;157:425-32.
  18. Lander ES, Botstein D. Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 1989;121:185-99.
  19. Seo D, Park H, Jung S, et al. QTL analyses of general compound, color, and pH traits in breast and thigh muscles in Korean native chicken. Livest Sci 2015;182:145-50. https://doi.org/10.1016/j.livsci.2015.09.020
  20. Lihn A, Pedersen SB, Richelsen B. Adiponectin: action, regulation and association to insulin sensitivity. Obes Rev 2005;6:13-21. https://doi.org/10.1111/j.1467-789X.2005.00159.x
  21. May P, Woldt E, Matz RL, Boucher P. The LDL receptor-related protein (LRP) family: An old family of proteins with new physiological functions. Ann Med 2007;39:219-28. https://doi.org/10.1080/07853890701214881
  22. Canovas E, Quintanilla R, Badaoui B, et al. Pig HDL-binding protein (HDLBP) genotype is associated with intramuscular fat percentage. Livest Sci 2009;126:298-301. https://doi.org/10.1016/j.livsci.2009.06.005
  23. Chmurzynska A. The multigene family of fatty acid-binding proteins (FABPs): function, structure and polymorphism. J Appl Genet 2006;47:39-48. https://doi.org/10.1007/BF03194597
  24. Brolinson A. Regulation of Elovl and fatty acid metabolism [Doctoral thesis]. Stockholm, Sweden: Stockholm University; 2009.
  25. Xue X, Feng CY, Hixson SM, et al. Characterization of the fatty acyl elongase (elovl) gene family, and hepatic elovl and delta-6 fatty acyl desaturase transcript expression and fatty acid responses to diets containing camelina oil in Atlantic cod (Gadus morhua). Comp Biochem Physiol Part B: Biochem Mol Biol 2014;175:9-22. https://doi.org/10.1016/j.cbpb.2014.06.005
  26. Lairson L, Henrissat B, Davies G, Withers S. Glycosyltransferases: structures, functions, and mechanisms. Annu Rev Biochem 2008;77:521-55. https://doi.org/10.1146/annurev.biochem.76.061005.092322
  27. D’Andre HC, Paul W, Shen X, et al. Identification and characterization of genes that control fat deposition in chickens. J Anim Sci Biotechnol 2013;4:43. https://doi.org/10.1186/2049-1891-4-43
  28. Arashiki N, Takakuwa Y, Mohandas N, et al. ATP11C is a major flippase in human erythrocytes and its defect causes congenital hemolytic anemia. Haematologica 2016;101:559-65. https://doi.org/10.3324/haematol.2016.142273
  29. Berner HS, Lyngstadaas SP, Spahr A, et al. Adiponectin and its receptors are expressed in bone-forming cells. Bone 2004;35:842-9. https://doi.org/10.1016/j.bone.2004.06.008
  30. Dall'Olio S, Davoli R, Buttazzoni L, Zambonelli P, Russo V. Study of porcine adiponectin (ADIPOQ) gene and association of a missense mutation with EBVs for production and carcass traits in Italian Duroc heavy pigs. Livest Sci 2009;125:101-4. https://doi.org/10.1016/j.livsci.2009.03.003
  31. Shin S, Chung E. Novel SNPs in the bovine ADIPOQ and PPARGC1A genes are associated with carcass traits in Hanwoo (Korean cattle). Mol Biol Rep 2013;40:4651-60. https://doi.org/10.1007/s11033-013-2560-0
  32. Choi Y, Davis ME, Chung H. Effects of genetic variants in the promoter region of the bovine adiponectin (ADIPOQ) gene on marbling of Hanwoo beef cattle. Meat Sci 2015;105:57-62. https://doi.org/10.1016/j.meatsci.2015.02.014
  33. Michal J, Zhang Z, Gaskins C, Jiang Z. The bovine fatty acid binding protein 4 gene is significantly associated with marbling and subcutaneous fat depth in $Wagyu{\times}Limousin$ F2 crosses. Anim Genet 2006;37:400-2. https://doi.org/10.1111/j.1365-2052.2006.01464.x
  34. Hoashi S, Hinenoya T, Tanaka A, et al. Association between fatty acid compositions and genotypes of FABP4 and LXR-alpha in Japanese Black cattle. BMC Genet 2008;9:84.
  35. Barendse W, Bunch R, Thomas M, Harrison B. A splice site single nucleotide polymorphism of the fatty acid binding protein 4 gene appears to be associated with intramuscular fat deposition in longissimus muscle in Australian cattle. Anim Genet 2009;40:770-3. https://doi.org/10.1111/j.1365-2052.2009.01913.x
  36. Chen Q-M, Wang H, Zeng Y-Q, Chen W. Developmental changes and effect on intramuscular fat content of H-FABP and A-FABP mRNA expression in pigs. J Appl Genet 2013;54:119-23. https://doi.org/10.1007/s13353-012-0122-0

Cited by

  1. Genome‐wide association study and pathway analysis for fat deposition traits in nellore cattle raised in pasture–based systems vol.138, pp.3, 2018, https://doi.org/10.1111/jbg.12525
  2. Omics-Based Analytical Approaches for Assessing Chicken Species and Breeds in Food Authentication vol.26, pp.21, 2021, https://doi.org/10.3390/molecules26216502