DOI QR코드

DOI QR Code

Genetic variation analysis of Guanling cattle based on whole-genome resequencing

  • Longxin Xu (Institute of Animal Husbandry and Veterinary Science, Guizhou Academy of Agricultural Sciences) ;
  • Xin Wang (Institute of Animal Husbandry and Veterinary Science, Guizhou Academy of Agricultural Sciences) ;
  • Junda Wu (Institute of Animal Husbandry and Veterinary Science, Guizhou Academy of Agricultural Sciences) ;
  • Hua Wang (Institute of Animal Husbandry and Veterinary Science, Guizhou Academy of Agricultural Sciences) ;
  • Wenzhang Zhou (Institute of Animal Husbandry and Veterinary Science, Guizhou Academy of Agricultural Sciences) ;
  • Jing Liu (Institute of Animal Husbandry and Veterinary Science, Guizhou Academy of Agricultural Sciences) ;
  • Mengmeng Ni (College of Animal Sciences, Guizhou University) ;
  • Kaikai Zhang (Institute of Animal Husbandry and Veterinary Science, Guizhou Academy of Agricultural Sciences) ;
  • Bo Yu (Institute of Animal Husbandry and Veterinary Science, Guizhou Academy of Agricultural Sciences) ;
  • Ruiyi Lin (College of Animal Sciences, Fujian Agriculture and Forestry University)
  • Received : 2024.03.26
  • Accepted : 2024.06.18
  • Published : 2024.12.01

Abstract

Objective: The objective of this study was to unravel the genetic traits of Guanling cattle, pinpoint genes advantageous for muscle growth, and lay a foundation for the preservation of genetic diversity and further analysis of regulation mechanism of important economic traits in local cattle breed. Methods: In this study, we sequenced the whole genome of 3 Guanling cattle in Guizhou province using the Illumina HiSeq cBo sequencing platform. And, high- multiplex polymerase chain reaction technology was employed to detect high-quality single nucleotide polymorphism (SNP) sites of other 55 Guanling cattle. Results: Our study identified 166,411 non-synonymous SNPs (nsSNPs) and 42,423 insertions and deletions (indels). Through SNP annotation, gene function enrichment analysis, and comparing with Simmental, Angus, and Limousin cattle, we identified six genes (LEPR, AKAP9, SIX4, SPIDR, PRG4, FASN) which are potentially influential on meat quality traits, playing crucial roles in muscle growth, fat metabolism, and bodily support. We also examined polymorphisms at seven SNP sites in Guanling cattle and found that all seven were in Hardy-Weinberg equilibrium. Conclusion: These findings suggested that these gene sites are stable and widespread in the Guanling cattle population. Our research lays the groundwork for future genetic enhancement and variety identification of Guanling cattle.

Keywords

Acknowledgement

This work were supported by Guizhou Department of Science and Technology (Major Project [2020] 3009, Key Project [2022] 027, General project [2021] No.144 and [2020] No. 1Y075, Basic research effort [2022] No.226) and Guizhou academy of agricultural sciences ("JBGS"[2024]No. 02).

References

  1. Editorial Committee for Livestock, Poultry Variety Catalogue, Variety Atlas in Guizhou Province. Guanling cattle (in Chinese). Guizhou J Anim Husb Vet Med 1983:115-8.
  2. Liu R, Yang G, Xia X, et al. Analysis on the genetic diversity of mitochondrial DNA D-loop region complete sequence of Guanling cattle in Guizhou province (in Chinese). J Mt Agric 2005;1:33-6.
  3. The International HapMap Consortium. The international HapMap project. Nature 2003;426:789-96. https://doi.org/10.1038/nature02168
  4. Eck SH, Benet-Pages A, Flisikowski K, Meitinger T, Fries R, Strom TM. Whole genome sequencing of a single Bos taurus animal for single nucleotide polymorphism discovery. Genome Biol 2009;10:R82. https://doi.org/10.1186/gb-2009-10-8-r82
  5. Stothard P, Choi JW, Basu U, et al. Whole genome resequencing of black Angus and Holstein cattle for SNP and CNV discovery. BMC Genomics 2011;12:559. https://doi.org/10.1186/1471-2164-12-559
  6. Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 2018;34:i884-90. https://doi.org/10.1093/bioinformatics/bty560
  7. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 2009;25:1754-60. https://doi.org/10.1093/bioinformatics/btp324
  8. Van der Auwera GA, Carneiro MO, Hartl C, et al. From fastQ data to high-confidence variant calls: the genome analysis toolkit best practices pipeline. Curr Protoc Bioinformatics 2013;43:11.0.1-33. https://doi.org/https://doi.org/10.1002/0471250953.bi1110s43
  9. Igoshin AV, Yudin NS, Belonogova NM, Larkin DM. Genome-wide association study for body weight in cattle populations from Siberia. Anim Genet 2019;50:250-3. https://doi.org/10.1111/age.12786
  10. Raza SHA, Khan S, Amjadi M, et al. Genome-wide association studies reveal novel loci associated with carcass and body measures in beef cattle. Arch Biochem Biophys 2020;694:108543. https://doi.org/10.1016/j.abb.2020.108543
  11. Abd El-Hack ME, Abdelnour SA, Swelum AA, Arif M. The application of gene marker-assisted selection and proteomics for the best meat quality criteria and body measurements in Qinchuan cattle breed. Mol Biol Rep 2018;45:1445-56. https://doi.org/10.1007/s11033-018-4211-y
  12. Sun T, Pei S, Liu Y, et al. Whole genome sequencing of sim-mental cattle for SNP and CNV discovery. BMC Genomics 2023;24:179. https://doi.org/10.1186/s12864-023-09248-x
  13. The 1000 Genomes Project Consortium. An integrated map of genetic variation from 1,092 human genomes. Nature 2012;491:56-65. https://doi.org/10.1038/nature11632
  14. Albers CA, Lunter G, MacArthur DG, McVean G, Ouwehand WH, Durbin R. Dindel: accurate indel calls from short-read data. Genome Res 2011;21:961-73. https://doi.org/10.1101/gr.112326.110
  15. Choi JW, Liao X, Stothard P, et al. Whole-genome analyses of Korean native and Holstein cattle breeds by massively parallel sequencing. PLoS ONE 2014;9:e101127. https://doi.org/10.1371/journal.pone.0101127
  16. Kawahara-Miki R, Tsuda K, Shiwa Y, et al. Whole-genome resequencing shows numerous genes with nonsynonymous SNPs in the Japanese native cattle Kuchinoshima - Ushi. BMC Genomics 2011;12:103. https://doi.org/10.1186/1471-2164-12-103
  17. Choi JW, Chung WH, Lee KT, et al. Whole genome resequencing of Heugu (Korean black cattle) for the genome-wide SNP discovery. Korean J Food Sci Anim Resour 2013;33:715-22. https://doi.org/10.5851/kosfa.2013.33.6.715
  18. Fujimoto A, Nakagawa H, Hosono N, et al. Whole-genome sequencing and comprehensive variant analysis of a Japanese individual using massively parallel sequencing. Nat Genet 2010;42:931-6. https://doi.org/10.1038/ng.691
  19. Makova KD, Li WH. Strong male-driven evolution of DNA sequences in humans and apes. Nature 2002;416:624-6. https://doi.org/10.1038/416624a
  20. Chelikani PK, Glimm DR, Kennelly JJ. Short communication: tissue distribution of leptin and leptin receptor mRNA in the bovine. J Dairy Sci 2003;86:2369-72. https://doi.org/10.3168/jds.S0022-0302(03)73830-2
  21. Raza SHA, Liu GY, Zhou L, et al. Detection of polymorphisms in the bovine leptin receptor gene affects fat deposition in two Chinese beef cattle breeds. Gene 2020;758:144957. https://doi.org/10.1016/j.gene.2020.144957
  22. Meng X, Gao Z, Liang Y, et al. Longissimus dorsi muscle transcriptomic analysis of simmental and Chinese native cattle differing in meat quality. Front Vet Sci 2020;7:601064. https://doi.org/10.3389/fvets.2020.601064
  23. Grifone R, Demignon J, Houbron C, et al. Six1 and Six4 homeoproteins are required for Pax3 and Mrf expression during myogenesis in the mouse embryo. Development 2005;132:2235-49. https://doi.org/10.1242/dev.01773
  24. Wang G, Zhang S, Wei S, et al. Novel polymorphisms of SIX4 gene and their association with body measurement traits in Qinchuan cattle. Gene 2014;539:107-10. https://doi.org/10.1016/j.gene.2014.01.042
  25. Huang T, Wu X, Wang S, et al. SPIDR is required for homologous recombination during mammalian meiosis. Nucleic Acids Res 2023;51:3855-68. https://doi.org/10.1093/nar/gkad154
  26. Zhang W, Xu L, Gao H, et al. Detection of candidate genes for growth and carcass traits using genome-wide association strategy in Chinese Simmental beef cattle. Anim Prod Sci 2018;58:224-33. https://doi.org/10.1071/an16165
  27. Schmidt TA, Plaas AHK, Sandy JD. Disulfide-bonded multimers of proteoglycan 4 (PRG4) are present in normal synovial fluids. Biochim Biophys Acta Gen Subj 2009;1790:375-84. https://doi.org/10.1016/j.bbagen.2009.03.016
  28. Abubacker S, Ponjevic D, Ham HO, Messersmith PB, Matyas JR, Schmidt TA. Effect of disulfide bonding and multimerization on proteoglycan 4's cartilage boundary lubricating ability and adsorption. Connect Tissue Res 2016;57:113-23. https://doi.org/10.3109/03008207.2015.1113271
  29. Wakil SJ, Stoops JK, Joshi VC. Fatty acid synthesis and its regulation. Annu Rev Biochem 1983;52:537-79. https://doi.org/10.1146/annurev.bi.52.070183.002541
  30. Oztabak K, Gursel FE, Akis I, Ates A, Hasret Y, Gulhan T. FASN gene polymorphism in indigenous cattle breeds of turkey. Folia Biol (Krakow) 2014;62:29-35. https://doi.org/10.3409/fb62_1.29
  31. Roy R, Ordovas L, Zaragoza P, et al. Association of polymorphisms in the bovine FASN gene with milk-fat content. Anim Genet 2006;37:215-8. https://doi.org/10.1111/j.1365-2052.2006.01434.x
  32. Chu M, Wu XY, Guo X, et al. Association between single-nucleotide polymorphisms of fatty acid synthase gene and meat quality traits in Datong Yak (Bos grunniens). Genet Mol Res 2015;14:2617-25. https://doi.org/10.4238/2015.March.30.21
  33. Ji S, Yang R, Lu C, Qiu Z, Yan C, Zhao Z. Differential expression of PPARγ, FASN, and ACADM genes in various adipose tissues and Longissimus dorsi muscle from Yanbian Yellow cattle and Yan Yellow cattle. Asian-Australas J Anim Sci 2014;27:10-8. https://doi.org/10.5713/ajas.2013.13422
  34. Hayakawa K, Sakamoto T, Ishii A, et al. The g.841G>C SNP of FASN gene is associated with fatty acid composition in beef cattle. Anim Sci J 2015;86:737-46. https://doi.org/10.1111/asj.12357