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Volkova N.A., German N.Yu., Larionova P.V., Vetokh A.N., Romanov M.N., Zinovieva N.A. Identification of SNPs and candidate genes associated with abdominal fat deposition in quails (Coturnix japonica). Sel'skokhozyaistvennaya Biologiya [Agricultural Biology], 2023, Vol. 58, № 6, p. 1079-1087.
(how to cite this article)

doi: 10.15389/agrobiology.2023.6.1079eng

UDC: 636.5:577.2

Acknowledgements:
Supported financially by Russian Science Foundation, grant No. 21-16-00086

 

IDENTIFICATION OF SNPs AND CANDIDATE GENES ASSOCIATED WITH ABDOMINAL FAT DEPOSITION IN QUAILS (Coturnix japonica)

N.A. Volkova1 ✉ , N.Yu. German1, P.V. Larionova1,
A.N. Vetokh1, M.N. Romanov1, 2, N.A. Zinovieva1

1Ernst Federal Research Center for Animal Husbandry,60, pos. Dubrovitsy, Podolsk District, Moscow Province, 142132 Russia, e-mail natavolkova@inbox.ru (✉ corresponding author), ngerman9@gmail.com, volpolina@mail.ru,
anastezuya@mail.ru, n_zinovieva@mail.ru;
2School of Biosciences, University of Kent, Canterbury, Kent CT2 7NJ, UK, e-mail m.romanov@kent.ac.uk

ORCID:
Volkova N.A. orcid.org/0000-0001-7191-3550
Vetokh A.N. orcid.org/0000-0002-2865-5960
German N.Yu. orcid.org/0000-0001-5888-4695
Romanov M.N. orcid.org/0000-0003-3584-4644
Larionova P.V. orcid.org/0000-0001-5047-1888
Zinovieva N.A. orcid.org/0000-0003-4017-6863

Final revision received October 12. 2023
Accepted November 10, 2023

The rate of fat deposition, including abdominal fat, is one of the important indicators characterizing both meat performance and product quality, as well as the poultry welfare in general. This trait positively correlates with the bird’s rapid growth and largely depends not only on feeding and housing conditions, but also on genetic factors. Mostly, data on the genetic mechanisms that determine fat metabolism and fat deposition rate have been obtained in chickens; SNPs and candidate genes that determine the deposition of both intramuscular and abdominal fat have been identified. The number of similar studies on quail is relatively small. To date, there is not enough information in the specialized literature about quantitative trait loci (QTLs) that are reliably associated with fat metabolism indices in quails. The present work reports for the first time the identified SNPs that are highly significantly (p < 0.00001) associated with the intensity of abdominal fat deposition in 8-week-old quails from the F2 model resource population. In the region of identified SNPs, candidate genes reliably associated with this trait were established. The objective of the study was to search for SNPs and identify candidate genes associated with abdominal fat deposition in quails. The studies were carried out on F2 males of the model resource population (n = 146) obtained by crossing two quail breeds contrasting in growth rate and meat quality, Japanese (slow growth) and Texas (fast growth). F2 individuals were genotyped using the GBS (genotyping-by-sequencing) method. To identify associations between genome-wide genotyping data and the amount of abdominal fat, PLINK 1.9 software was used with accepted filter settings (geno 0.1, mind 0.1, maf 0.05). The threshold significance criterion was set to p < 0.00001. The resultant F2 resource population of quail was characterized by high variability in the content of abdominal fat in the carcass. At the age of 56 days, this indicator varied from 0.01 to 10.46 g and averaged 2.41±0.16 g. Based on the GWAS (genome-wide association study) analysis, we identified 29 SNPs and 11 candidate genes located in the regions of these SNPs that were associated with abdominal fat deposition in quail. The determined SNPs are localized on chromosomes 1, 2, 7, 8, 17, 19, 21, 24 and 28. The candidate genes identified (CNTN5, GNAL, PDE1A, RBMS1, PTPRF, SH3GLB2, SLC27A4, TRIM62, IGSF9B, USHBP1, and NR2F6) were established on chromosomes CJA1 (1 gene), CJA2 (1 gene), CJA7 (2 genes), CJA8 (1 gene), CJA17 (2 genes), CJA21 (1 gene), CJA24 (1 gene) and CJA28 (2 genes). The detected SNPs and candidate genes can serve as genetic markers in breeding programs to improve the meat quality of quails and reduce the fat content in carcasses.

Keywords: Coturnix japonica, quail, QTL, SNP, genotyping-by-sequencing, GBS, genome-wide association study, GWAS, candidate genes, abdominal fat.

 

REFERENCES

  1. Fisinin V.I., Buyarov V.S., Buyarov A.V., Shumetov V.G. Agrarnaya nauka, 2018, 2: 30-38 (in Russ.).
  2. Zykov S.A. Effektivnoe zhivotnovodstvo, 2019, 4(152): 51-54 (in Russ.).
  3. Priti M., Satish S. Quail farming: an introduction. International Journal of Life Sciences, 2014, 2: 190-193.
  4. Minvielle F. The future of Japanese quail for research and production. World’s Poultry Science Journal, 2004, 60(4): 500-507 CrossRef
  5. Quaresma M.A.G., Antunes I.C., Gil Ferreira B., Parada A., Elias A., Barros M., Santos C., Partidário A., Mourato M., Roseiro L.C. The composition of the lipid, protein and mineral fractions of quail breast meat obtained from wild and farmed specimens of Common quail (Coturnix coturnix) and farmed Japanese quail (Coturnix japonica domestica). Poultry Science, 2022, 101(1): 101505 CrossRef
  6. Genchev A., Mihaylova G., Ribarski S., Pavlov A., Kabakchiev M. Meat quality and composition in Japanese quails. Trakia Journal of Sciences, 2008, 6(4): 72-82,
  7. Hu Z.-L., Park C.A., Reecy J.M. Bringing the Animal QTLdb and CorrDB into the future: meeting new challenges and providing updated services. Nucleic Acids Research, 2022, 50(D1): D956-D961 CrossRef
  8. Korshunova L.G., Karapetyan R.V., Komarchev A.S., Kulikov E.I.  Association of single nucleotide polymorphisms in candidate genes with economically useful traits in chickens (Gallus gallus domesticus L.) (review). Sel'skokhozyaistvennaya biologiya [Agricultural Biology], 2023, 58(2): 205-222 CrossRef
  9. Sarsenbek A., Wang T., Zhao J., Jiang W. Comparison of carcass yields and meat quality between Baicheng-You chickens and Arbor Acres broilers. Poultry Science, 2013, 92:  2776-2782 CrossRef
  10. Yang Y., Wen J., Fang G.Y., Li Z.R., Dong Z.Y., Liu J. The effects of raising system on the lipid metabolism and meat quality traits of slow-growing chickens. Journal of Applied Animal Research, 2015, 43(2): 147-152 CrossRef
  11. Fouad A., El-Senousey H. Nutritional factors affecting abdominal fat deposition in poultry: a review. Asian-Australasian Journal of Animal Sciences, 2014, 27: 1057-1068 CrossRef
  12. Zhao S.M., Ma H.T., Zou S.X., Chen W.H., Zhao R.Q. Hepatic lipogenesis gene expression in broiler chicken with different fat deposition during embryonic development. Journal of Veterinary Medicine, 2007, 54: 1-6 CrossRef
  13. Xing J., Kang L., Hu Y., Xu Q., Zhang N., Jiang Y. Effect of dietary betaine supplementation on mRNA expression and promoter CpG methylation of lipoprotein lipase gene in laying hens. Journal of Poultry Science, 2009, 46: 224-228 CrossRef
  14. Dikici A., Nacak B., Yel N., Zaimoğulları K., İpek G., Özer M. Quality characteristics and oxidative stability of chicken kavurma formulated with chicken abdominal fat as beef fat replacer. Journal of the Hellenic Veterinary Medical Society, 2022, 73(3): 4525-4534 CrossRef
  15. Santos M.F., Lima D.A.S., Madruga M. S., Silva F.A.P. Lipid and protein oxidation of emulsified chicken patties prepared using abdominal fat and skin. Poultry Science, 2020, 99(3): 1777-1787 CrossRef
  16. Li J., Cheng Y., Chen Y., Qu H., Zhao Y., Wen C., Zhou Y. Effects of dietary synbiotic supplementation on growth performance, lipid metabolism, antioxidant status, and meat quality in Partridge shank chickens. Journal of Applied Animal Research, 2019, 47(1): 586-590 CrossRef
  17. Sugiharto S., Pratama A.R., Yudiarti T., Wahyuni H.I., Widiastuti  E., Sartono T.A. Effect of acidified turmeric and/or black pepper on growth performance and meat quality of broiler chickens. International Journal of Veterinary Science and Medicine, 2020, 8(1): 85-92 CrossRef
  18. Narinc D., Karaman E., Aksoy T. Effects of slaughter age and mass selection on slaughter and carcass characteristics in 2 lines of Japanese quail. Poultry Science, 2014, 93(3): 762-769 CrossRef
  19. Abou-Kassem D.E., El-Kholy M.S., Alagawany M., Laudadio V., Tufarelli V. Age and sex-related differences in performance, carcass traits, hemato–biochemical parameters, and meat quality in Japanese quails. Poultry Science, 2019, 98(4): 1684-1691 CrossRef
  20. Lotfi E., Zerehdaran S., Azari M.A. Genetic evaluation of carcass composition and fat deposition in Japanese quail. Poultry Science, 2011, 90(10): 2202-2208 CrossRef
  21. Narinc D., Aksoy T., Karaman E., Aygun A., Firat M.Z., Uslu M.K. Japanese quail meat quality: Characteristics, heritabilities, and genetic correlations with some slaughter traits. Poultry Science, 2013, 92(7): 1735-1744 CrossRef
  22. Jiang M., Fan W.L., Xing S.Y., Wang J., Li P., Liu R.R., Li Q.H., Zheng M.Q., Cui H.X., Wen J., Zhao G.P. Effects of balanced selection for intramuscular fat and abdominal fat percentage and estimates of genetic parameters. Poultry Science, 2017, 96(2): 282-287 CrossRef
  23. Glazko V.I., Kosovsky G.Yu., Glazko T.T., Fedorova L.M. DNA markers and microsatellite code (review). Sel'skokhozyaistvennaya biologiya [Agricultural Biology], 2023, 58(2): 223-248 CrossRef
  24. Wang D., Qin P., Zhang K., Wang Y., Guo Y., Cheng Z., Li Z., Tian Y., Kang X., Li H., Liu X. Integrated LC/MS-based lipidomics and transcriptomics analyses revealed lipid composition heterogeneity between pectoralis intramuscular fat and abdominal fat and its regulatory mechanism in chicken. Food Research International, 2023, 172: 113083 CrossRef
  25. Moreira G.C.M., Boschiero C., Cesar A.S.M., Reecy J. M., Godoy T. F., Trevisoli P. A., Cantão M.E., Ledur M.C., Ibelli A.M.G., Peixoto J.O., Moura M.T., Garrick D., Coutinho L.L. A genome-wide association study reveals novel genomic regions and positional candidate genes for fat deposition in broiler chickens. BMC Genomics,2018, 19: 374 CrossRef
  26. Zhang H., Hu X., Wang Z., Zhang Y., Wang S., Wang N., Ma L., Leng L., Wang S., Wang Q., Wang Y., Tang Z, Li N., Da Y., Li H. Selection signature analysis implicates the PC1/PCSK1 region for chicken abdominal fat content. PLoS ONE, 2012, 7(7): e40736 CrossRef
  27. Trevisoli P.A., Moreira G.C.M., Boschiero C., Cesar A.S.M., Petrini J., Margarido G.R.A., Ledur M.C., Mourão G.B., Garrick D., Coutinho L.L. A missense mutation in the MYBPH gene is associated with abdominal fat traits in meat-type chickens. Frontiers in Genetics, 2021, 11(12): 698163 CrossRef
  28. Zhang H., Shen L.Y., Xu Z.C., Kramer L.M., Yu J.Q., Zhang X.Y., Na W., Yang L.L., Cao Z.P., Luan P., Reecy J.M., Li H. Haplotype-based genome-wide association studies for carcass and growth traits in chicken. Poultry Science, 2020, 99(5): 2349-2361 CrossRef
  29. Tavaniello S., Maiorano G., Siwek M., Knaga S., Witkowski A., Di Memmo D., Bednarczyk M. Growth performance, meat quality traits, and genetic mapping of quantitative trait loci in 3 generations of Japanese quail populations (Coturnix japonica). Poultry Science, 2014, 93(8): 2129-2140 CrossRef
  30. Volkova N.A., Romanov M.N., Abdelmanova A.S., Larionova P.V., German N.Y., Vetokh A.N., Shakhin A.V., Volkova L.A., Anshakov D.V., Fisinin V.I., Narushin V.G., Griffin D.K., Sölkner J., Brem G., McEwan J.C., Brauning R., Zinovieva N.A. Genotyping-by-sequencing strategy for integrating genomic structure, diversity and performance of various Japanese quail (Coturnix japonica) breeds. Animals, 2023, 13: 3439 CrossRef
  31. Andrews S. FastQC: A quality control tool for high throughput sequence data; Version 0.10.1. Bioinformatics Group, Babraham Institute, Cambridge, UK, 2012. Available: http://www.bioinformatics.babraham.ac.uk/projects/fastqc. Accessed: 09/25/2023.
  32. Langmead B. bowtie2: a fast and sensitive gapped read aligner. Version 2.4.4. GitHub, Inc. 2021. Available: https://github.com/BenLangmead/bowtie2. Accessed: 09/25/2023.
  33. Turner S.D. qqman: an R package for visualizing GWAS results using Q-Q and Manhattan plots. Journal of Open Source Software, 2018, 3(25): 731 CrossRef
  34. Gao Z., Ding R., Zhai X., Wang Y., Chen Y., Yang C-X., Du Z-Q. Common gene modules identified for chicken adiposity by network construction and comparison. Frontiers in Genetics, 2020, 11: 537 CrossRef
  35. Zhang H., Du Z.Q., Dong J.Q. Detection of genome-wide copy number variations in two chicken lines divergently selected for abdominal fat content. BMC Genomics, 2014, 15: 517 CrossRef
  36. Lee Y.S., Shin D. Genome-wide association studies associated with backfat thickness in landrace and Yorkshire pigs. Genomics Inform, 2018, 16(3): 59-64 CrossRef
  37. Revilla M., Puig-Oliveras A., Crespo-Piazuelo D., Criado-Mesas L., Castelló A., Fernández A.I., Ballester M., Folch J.M. Expression analysis of candidate genes for fatty acid composition in adipose tissue and identification of regulatory regions. Scientific Reports, 2018, 8(1): 2045 CrossRef
  38. Maganti A., Chi J., Cohen P. Arx and Nr2f6 transcriptionally regulate visceral and brown fat phenotype. Diabetes, 2021, 70(S1): 201-LB CrossRef
  39. Zhou B., Jia L., Zhang Z., Xiang L., Yuan Y., Zheng P., Liu B., Ren X., Bian H., Xie L., Li Y., Lu J., Zhang H., Lu Y. The nuclear orphan receptor NR2F6 promotes hepatic steatosis through upregulation of fatty acid transporter CD36. Advanced Science, 2020, 7(21): 2002273 CrossRef
  40. Kim N.J., Baek J.H., Lee J., Kim H., Song J-K., Chun K-H. A PDE1 inhibitor reduces adipogenesis in mice via regulation of lipolysis and adipogenic cell signaling. Experimental & Molecular Medicine, 2019, 51: 1-15 CrossRef
  41. Dairi G., Al Mahri S., Benabdelkamel H., Alfadda A.A., Alswaji A.A., Rashid M., Malik S.S., Iqbal J., Ali R., Al Ibrahim M., Al-Regaiey K., Mohammad S. Transcriptomic and proteomic analysis reveals the potential role of RBMS1 in adipogenesis and adipocyte metabolism. International Journal of Molecular Sciences, 2023, 24(14): 11300 CrossRef
  42. Li G-S., Liu W-W., Zhang F., Zhu F., Yang F-X., Hao J-P., Hou Z.-C. Genome-wide association study of bone quality and feed efficiency-related traits in Pekin ducks. Genomics, 2020, 112(6): 5021-5028 CrossRef
  43. Zhao Y., He S., Huang J., Liu M. Genome-wide association analysis of muscle pH in Texel sheep ½ Altay sheep F2 resource population. Animals, 2023, 13(13): 2162 CrossRef
  44. Hardie L.C., VandeHaar M.J., Tempelman R.J., Weigel K.A., Armentano L.E., Wiggans G.R., Veerkamp R.F., de Haas Y., Coffey M.P., Connor E.E., Hanigan M.D., Staples C., Wang Z., Dekkers J.C.M., Spurlock D.M. The genetic and biological basis of feed efficiency in mid-lactation Holstein dairy cows. Journal of Dairy Science, 2017, 100(11): 9061-9075 CrossRef

 

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