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Screening for candidate genes related with histological microstructure, meat quality and carcass characteristic in pig based on RNA-seq data

  • Ropka-Molik, Katarzyna (Department of Genomics and Animal Molecular Biology, National Research Institute of Animal Production) ;
  • Bereta, Anna (Department of Animal Genetics and Breeding, National Research Institute of Animal Production) ;
  • Zukowski, Kacper (Department of Animal Genetics and Breeding, National Research Institute of Animal Production) ;
  • Tyra, Miroslaw (Department of Animal Genetics and Breeding, National Research Institute of Animal Production) ;
  • Piorkowska, Katarzyna (Department of Genomics and Animal Molecular Biology, National Research Institute of Animal Production) ;
  • Zak, Grzegorz (Department of Animal Genetics and Breeding, National Research Institute of Animal Production) ;
  • Oczkowicz, Maria (Department of Genomics and Animal Molecular Biology, National Research Institute of Animal Production)
  • Received : 2017.09.21
  • Accepted : 2018.03.05
  • Published : 2018.10.01

Abstract

Objective: The aim of the present study was to identify genetic variants based on RNA-seq data, obtained via transcriptome sequencing of muscle tissue of pigs differing in muscle histological structure, and to verify the variants' effect on histological microstructure and production traits in a larger pig population. Methods: RNA-seq data was used to identify the panel of single nucleotide polymorphisms (SNPs) significantly related with percentage and diameter of each fiber type (I, IIA, IIB). Detected polymorphisms were mapped to quantitative trait loci (QTLs) regions. Next, the association study was performed on 944 animals representing five breeds (Landrace, Large White, Pietrain, Duroc, and native Puławska breed) in order to evaluate the relationship of selected SNPs and histological characteristics, meat quality and carcasses traits. Results: Mapping of detected genetic variants to QTL regions showed that chromosome 14 was the most overrepresented with the identification of four QTLs related to percentage of fiber types I and IIA. The association study performed on a 293 longissimus muscle samples confirmed a significant positive effect of transforming acidic coiled-coil-containing protein 2 (TACC2) polymorphisms on fiber diameter, while SNP within forkhead box O1 (FOXO1) locus was associated with decrease of diameter of fiber types IIA and IIB. Moreover, subsequent general linear model analysis showed significant relationship of FOXO1, delta 4-desaturase, sphingolipid 1 (DEGS1), and troponin T2 (TNNT2) genes with loin 'eye' area, FOXO1 with loin weight, as well as FOXO1 and TACC2 with lean meat percentage. Furthermore, the intramuscular fat content was positively associated (p<0.01) with occurrence of polymorphisms within DEGS1, TNNT2 genes and negatively with occurrence of TACC2 polymorphism. Conclusion: This study's results indicate that the SNP calling analysis based on RNA-seq data can be used to search candidate genes and establish the genetic basis of phenotypic traits. The presented results can be used for future studies evaluating the use of selected SNPs as genetic markers related to muscle histological profile and production traits in pig breeding.

Keywords

References

  1. Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 2009;10:57-63. https://doi.org/10.1038/nrg2484
  2. Ramaswami G, Zhang R, Piskol R, et al. Identifying RNA editing sites using RNA sequencing data alone. Nat Methods 2013;10:128-32. https://doi.org/10.1038/nmeth.2330
  3. Piskol R, Ramaswami G, Li JB. Reliable identification of genomic variants from RNA-seq data. Am J Hum Genet 2013;93:641-51. https://doi.org/10.1016/j.ajhg.2013.08.008
  4. Canovas A, Rincon G, Islas-Trejo A, Wickramasinghe S, Medrano JF. SNP discovery in the bovine milk transcriptome using RNA-Seq technology. Mamm Genome 2010;21:592-8. https://doi.org/10.1007/s00335-010-9297-z
  5. Lopez-Maestre H, Brinza L, Marchet C, et al. SNP calling from RNA-seq data without a reference genome: identification quantification differential analysis and impact on the protein sequence. Nucleic Acids Res 2016;44:e148.
  6. Jung WY, Kwon SG, Son M, et al. RNA-Seq approach for genetic improvement of meat quality in pig and evolutionary insight into the substrate specificity of animal carbonyl reductases. PLoS One 2012;7:e42198. https://doi.org/10.1371/journal.pone.0042198
  7. Lee YH, Cho ES, Kwon EJ, et al. Non-synonymous SNP in the ApoR gene associated with pork meat quality. Biosci Biotechnol Biochem 2011;75:2018-20. https://doi.org/10.1271/bbb.110152
  8. Piorkowska K, Zukowski K, Tyra M, Ropka-Molik K. Detection of genetic variants different between Polish Landrace and Pulawska pigs by means of RNA-seq analysis. Anim Genet 2018;49:215-25. https://doi.org/10.1111/age.12654
  9. Fischer D, Laiho A, Gyenesei A, Sironen A. Identification of reproduction-related gene polymorphisms using whole transcriptome sequencing in the Large White pig population. G3 (Bethesda) 2015;5:1351-60.
  10. Joo ST, Kim GD, Hwang YH, Ryu YC. Control of fresh meat quality through manipulation of muscle fiber characteristics. Meat Sci 2013;95:828-36. https://doi.org/10.1016/j.meatsci.2013.04.044
  11. Bereta A, Tyra M, Ropka-Molik K, et al. Histological profile of the longissimus dorsi muscle in Polish Large White and Polish Landrace pigs and its effect on loin parameters and intramuscular fat content (IMF). Ann Anim Sci 2014;14:955-66. https://doi.org/10.2478/aoas-2014-0040
  12. Shen LY, Luo J, Lei HG, et al. Effects of muscle fiber type on glycolytic potential and meat quality traits in different Tibetan pig muscles and their association with glycolysis-related gene expression. Genet Mol Res 2015;14:14366-78. https://doi.org/10.4238/2015.November.13.22
  13. Ropka-Molik K, Bereta A, Zukowski K, et al. Transcriptomic gene profiling of porcine muscle tissue depending on histological properties. Anim Sci J 2017;88:1178-88. https://doi.org/10.1111/asj.12751
  14. Dobin A, Davis CA, Schlesinger F, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 2013;29:15-21. https://doi.org/10.1093/bioinformatics/bts635
  15. McKenna A, Hanna M, Banks E, et al. The genome analysis toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 2010;20:1297-303. https://doi.org/10.1101/gr.107524.110
  16. Cingolani P, Platts A, Wang LL, 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 2012;6:80-92. https://doi.org/10.4161/fly.19695
  17. R Core Team. R: A language and environment for statistical computing [internet]. Vienna, Austria: R Foundation for Statistical Computing; 2017. Available from: https://www.R-project.org/
  18. Hu ZL, Park CA, Reecy JM. Developmental progress and current status of the Animal QTLdb. Nucleic Acids Res 2016;44:D827-33. https://doi.org/10.1093/nar/gkv1233
  19. Ropka-Molik K, Dusik A, Piorkowska K, et al. Polymorphisms of the membrane-associated ring finger 4 ubiquitin protein ligase gene (MARCH4) and its relationship with porcine production traits. Livest Sci 2015;178:18-26. https://doi.org/10.1016/j.livsci.2015.05.022
  20. Oczkowicz M, Tyra M, Ropka-Molik K, Mucha A, Zukowski K. Effect of IGF2 intron3-g. 3072G>A on intramuscular fat (IMF) content in pigs raised in Poland. Livest Sci 2012;149:301-4. https://doi.org/10.1016/j.livsci.2012.06.021
  21. Wojtysiak D, Kaczor U. Effect of g.2728G>A and g.3996 T>C polymorphisms at the leptin gene locus on microstructure and physicochemical properties of longissimus lumborum muscle of Polish Landrace pigs. Folia Biol 2011;59:77-82. https://doi.org/10.3409/fb59_1-2.77-82
  22. Zak G, Pieszka M. Improving pork quality through genetics and nutrition. Ann Anim Sci 2009;9:327-39.
  23. Karlsson AH, Klont RE, Fernandez X. Skeletal muscle fibres as factors for pork quality. In: Quality of meat and fat in pigs as affected by genetics and nUTRition. Wageningen, The Netherlands: Wageningen Academic Publishers; 2000. pp. 47-67.
  24. Wu F, Zuo JJ, Yu QP, et al. Effect of skeletal muscle fibers on porcine meat quality at different stages of growth. Genet Mol Res 2015;14:7873-82. https://doi.org/10.4238/2015.July.14.13
  25. Nii M, Hayashi T, Mikawa S, et al. Quantitative trait loci mapping for meat quality and muscle fiber traits in a Japanese wild boar$\times$Large White intercross. J Anim Sci 2005;83:308-15. https://doi.org/10.2527/2005.832308x
  26. Wimmers K, Fiedler I, Hardge T, et al. QTL for microstructural and biophysical muscle properties and body composition in pigs. BMC Genet 2006;7:15.
  27. Estelle J, Gil F, Vazquez JM, et al. A quantitative trait locus genome scan for porcine muscle fiber traits reveals overdominance and epistasis. J Anim Sci 2008;86:3290-9. https://doi.org/10.2527/jas.2008-1034
  28. de Koning DJ, Harlizius B, Rattink AP, et al. Detection and characterization of quantitative trait loci for meat quality traits in pigs. J Anim Sci 2001;79:2812-9. https://doi.org/10.2527/2001.79112812x
  29. Jiao S, Maltecca C, Gray KA, Cassady JP. Feed intake average daily gain feed efficiency and real-time ultrasound traits in Duroc pigs: II. Genomewide association. J Anim Sci 2014;92:2846-60. https://doi.org/10.2527/jas.2014-7337
  30. Takayama K, Horie-Inoue K, Suzuki T, et al. TACC2 is an androgen-responsive cell cycle regulator promoting androgenmediated and castration-resistant growth of prostate cancer. Mol Endocrinol 2012;26:748-61. https://doi.org/10.1210/me.2011-1242
  31. Schiaffino S, Mammucari C. Regulation of skeletal muscle growth by the IGF1-Akt/PKB pathway: insights from genetic models. Skelet Muscle 2011;1:4. https://doi.org/10.1186/2044-5040-1-4
  32. Kamei Y, Miura S, Suzuki et al. Skeletal muscle FOXO1 (FKHR) transgenic mice have less skeletal muscle mass down-regulated Type I (slow twitch/red muscle) fiber genes and impaired glycemic control. J Biol Chem 2004;279:41114-23. https://doi.org/10.1074/jbc.M400674200
  33. Xu M, Chen X, Chen D, Yu B, Huang Z. FoxO1: a novel insight into its molecular mechanisms in the regulation of skeletal muscle differentiation and fiber type specification. Oncotarget 2017;8:10662-74.

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