Genome-Wide Association Study for Meat Quality Traits in a Multi-Breed Pig Population

Author:

Kamiński Stanisław1,Tarczyński Krystian2,Oleński Kamil1,Zybert Andrzej2,Sieczkowska Halina2,Krzęcio-Nieczyporuk Elżbieta3,Antosik Katarzyna2,Szwaczkowski Tomasz4

Affiliation:

1. Department of Animal Genetics , University of Warmia and Mazury , Oczapowskiego 5 , Olsztyn , Poland

2. Faculty of Agricultural Sciences , University of Siedlce , Prusa 14 , Siedlce , Poland

3. Faculty of Medical and Health Sciences , Siedlce University of Natural Sciences and Humanities , Prusa 14 , Siedlce , Poland

4. Department of Genetics and Animal Breeding , Poznan University of Life Sciences , Wołyńska 33 , Poznań , Poland

Abstract

Abstract This study aimed at identifying genomic regions that affect nine pork quality traits in purebred and crossbred fatteners. A total of 259 fatteners represented by six purebreds/crosses were genotyped for 45556 SNP markers by Illumina Porcine SNP60 BeadChip. The following traits were recorded: glycogen potential (GP), glycogen content (GC), lactate content (LC), pH35, pH24, pH48, drip loss after 48 hours (DL48), colour lightness (L *) and lean meat content (LMC). Multi-Locus Mixed Model methodology was applied to find associations between SNP markers and recorded traits. Several SNPs were found to be significantly associated with some pork quality traits: four SNPs (located on SSC7, SSC10 and SSC14) with GP, three SNPs (SSC10, SSC14) with GC, one SNP (SSC15) with DL48 and one SNP with pH48. Genetic variation explained by significant SNPs ranged from 7.6% to 9.1%. Moreover, some genes (e.g. CAPN10, ALDH5A1, PASK, SNITA1 and MYH7B) located in the close vicinity to significant markers are proposed to be candidate genes explaining the genetic background of the traits studied.

Publisher

Walter de Gruyter GmbH

Reference47 articles.

1. Bergmeyer H.U. (1974). Methods of enzymatic analysis. New York: Academic Press.

2. Bertram H.C., Petersen J.S., Andersen, H.J. (2000). Relationship between RN– genotype and drip loss in meat from Danish pigs. Meat Sci., 56: 49–55.

3. Bolormaa S., Hayes B.J., van der Werf J.H.J., Pethick D., Goddard M.E., Daetwyler H.D. (2016). Detailed phenotyping identifies genes with pleiotropic effects on body composition. BMC Genomics, 17: 224.

4. Choi I., Steibel J.P., Bates R.O., Raney N.E., Rumph J.M., Ernst C.W. (2011). Identification of carcass and meat quality QTL in F(2) Duroc × Pietrain pig resource population using different least-squares analysis models. Front. Genet., 2: 18.

5. Coudy-Gandilhon C., Gueugneau M., Taillandier D., Combaret L., Polge C., Roche F., Barthélémy J.C., Féasson L., Maier J.A., Mazur A., Béchet D. (2019). Magnesium transport and homeostasis-related gene expression in skeletal muscle of young and old adults: analysis of the transcriptomic data from the PROOF cohort Study. Magnes Res., 32: 72–82.

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