Genomics & Informatics

Korea Genome Organization (한국유전체학회)
권호 표지
DOI QR코드

DOI QR Code

Estimation of the Genetic Substitution Rate of Hanwoo and Holstein Cattle Using Whole Genome Sequencing Data

  • Lee, Young-Sup (Department of Animal Biotechnology, Chonbuk National University) ;
  • Shin, Donghyun (Department of Animal Biotechnology, Chonbuk National University)
  • Received : 2018.01.05
  • Accepted : 2018.02.14
  • Published : 2018.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

Despite the importance of mutation rate, some difficulties exist in estimating it. Next-generation sequencing (NGS) data yields large numbers of single-nucleotide polymorphisms, which can make it feasible to estimate substitution rates. The genetic substitution rates of Hanwoo and Holstein cattle were estimated using NGS data. Our main findings was to calculate the gene's substitution rates. Through estimation of genetic substitution rates, we found: diving region of altered substitution density exists. This region may indicate a boundary between protected and unprotected genes. The protected region is mainly associated with the gene ontology terms of regulatory genes. The genes that distinguish Hanwoo from Holstein in terms of substitution rate predominantly have gene ontology terms related to blood and circulatory system. This might imply that Hanwoo and Holstein evolved with dissimilar mutation rates and processes after domestication. The difference in meat quality between Hanwoo and Holstein could originate from differential evolution of the genes related to these blood and circulatory system ontology terms.

Keywords

References

  1. Kumar S, Subramanian S. Mutation rates in mammalian genomes. Proc Natl Acad Sci U S A 2002;99:803-808. https://doi.org/10.1073/pnas.022629899
  2. Lee KT, Chung WH, Lee SY, Choi JW, Kim J, Lim D, et al. Whole-genome resequencing of Hanwoo (Korean cattle) and insight into regions of homozygosity. BMC Genomics 2013;14:519. https://doi.org/10.1186/1471-2164-14-519
  3. Melka HD, Jeon EK, Kim SW, Han JB, Yoon D, Kim KS. Identification of genomic differences between Hanwoo and Holstein breeds using the Illumina Bovine SNP50 BeadChip. Genomics Inform 2011;9:69-73. https://doi.org/10.5808/GI.2011.9.2.69
  4. Lee HJ, Kim J, Lee T, Son JK, Yoon HB, Baek KS, et al. Deciphering the genetic blueprint behind Holstein milk proteins and production. Genome Biol Evol 2014;6:1366-1374. https://doi.org/10.1093/gbe/evu102
  5. Rhee MS, Ryu YC, Imm JY, Kim BC. Combination of low voltage electrical stimulation and early postmortem temperature conditioning on degradation of myofibrillar proteins in Korean native cattle (Hanwoo). Meat Sci 2000;55:391-396. https://doi.org/10.1016/S0309-1740(99)00167-9
  6. Lee SH, Park BH, Sharma A, Dang CG, Lee SS, Choi TJ, et al. Hanwoo cattle: origin, domestication, breeding strategies and genomic selection. J Anim Sci Technol 2014;56:2. https://doi.org/10.1186/2055-0391-56-2
  7. Srivathsan A, Meier R. On the inappropriate use of Kimura- 2-parameter (K2P) divergences in the DNA-barcoding literature. Cladistics 2012;28:190-194. https://doi.org/10.1111/j.1096-0031.2011.00370.x
  8. Yang Z. Estimating the pattern of nucleotide substitution. J Mol Evol 1994;39:105-111.
  9. Yang Z. Statistical properties of the maximum likelihood method of phylogenetic estimation and comparison with distance matrix methods. Syst Biol 1994;43:329-342. https://doi.org/10.1093/sysbio/43.3.329
  10. Steel MA, Fu YX. Classifying and counting linear phylogenetic invariants for the Jukes-Cantor model. J Comput Biol 1995;2:39-47. https://doi.org/10.1089/cmb.1995.2.39
  11. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014;30:2114-2120. https://doi.org/10.1093/bioinformatics/btu170
  12. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods 2012;9:357-359. https://doi.org/10.1038/nmeth.1923
  13. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 2010;20:1297-1303. https://doi.org/10.1101/gr.107524.110
  14. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The sequence Alignment/Map format and SAMtools. Bioinformatics 2009;25:2078-2079. https://doi.org/10.1093/bioinformatics/btp352
  15. Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. The variant call format and VCFtools. Bioinformatics 2011;27:2156-2158. https://doi.org/10.1093/bioinformatics/btr330
  16. Cingolani P, Platts A, Wang le L, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin) 2012;6:80-92. https://doi.org/10.4161/fly.19695
  17. Kimura M. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol 1980;16:111-120. https://doi.org/10.1007/BF01731581
  18. Tajima F, Nei M. Estimation of evolutionary distance between nucleotide sequences. Mol Biol Evol 1984;1:269-285.
  19. Casanellas M, Fernandez-Sanchez J. Geometry of the Kimura 3-parameter model. Adv Appl Math 2008;41:265-292. https://doi.org/10.1016/j.aam.2007.09.003
  20. Murray C, Huerta-Sanchez E, Casey F, Bradley DG. Cattle demographic history modelled from autosomal sequence variation. Philos Trans R Soc Lond B Biol Sci 2010;365:2531-2539. https://doi.org/10.1098/rstb.2010.0103
  21. Bovine HapMap Consortium, Gibbs RA, Taylor JF, Van Tassell CP, Barendse W, Eversole KA, et al. Genome-wide survey of SNP variation uncovers the genetic structure of cattle breeds. Science 2009;324:528-532. https://doi.org/10.1126/science.1167936
  22. Roach JC, Glusman G, Smit AF, Huff CD, Hubley R, Shannon PT, et al. Analysis of genetic inheritance in a family quartet by whole-genome sequencing. Science 2010;328:636-639. https://doi.org/10.1126/science.1186802
  23. Nei M, Maruyama T, Chakraborty R. The bottleneck effect and genetic variability in populations. Evolution 1975;29:1-10. https://doi.org/10.1111/j.1558-5646.1975.tb00807.x
  24. Ladizinsky G. Founder effect in crop-plant evolution. Econ Bot 1985;39:191-199. https://doi.org/10.1007/BF02907844