Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed

Martínez-Montes, Ángel M; Fernández, Almudena; Muñoz, María; Noguera, J. L.; Folch, Josep María; Fernández, Ana

doi:10.1371/journal.pone.0190184

Cited by 23 publications

(14 citation statements)

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“…Thus, most of the genetic variance is explained by minor loci that were not detected in the GWAS. Taken together, these results confirm that backfat thickness has a polygenic architecture, although some major genes that agree with previous studies [ 13 , 17 , 22 ] contribute large proportions of the genetic variance of the trait in some lines. In that regard, shifting towards an omnigenic model [ 33 ] may provide a more suitable conceptualisation of the genetic architecture of backfat thickness.…”

Section: Discussionsupporting

confidence: 91%

“…Of these, LRP5 and BRSK2 are in the 0.00–4.82 Mb genomic region on SSC2. Although we detected a significant association for this region in only one line, several GWAS on backfat thickness in pigs have revealed a significant association of this genomic region with backfat thickness, average daily gain, and meat-to-fat ratio in diverse genetic backgrounds, from F 2 populations derived from breeds such as Pietrain, Large White and Landrace [ 32 ] to crosses of Iberian pigs with Landrace, Pietrain, and Duroc [ 13 ], and many QTL reports support these findings. This region is gene-rich and includes many candidate genes, such as the INS gene, which encodes insulin that regulates blood glucose levels, promotes cell fat storage, and regulates the activity of enzymes that intervene in lipid metabolism [ 53 ], and the IGF2 gene, which encodes the insulin-like growth factor 2, and is widely considered as a major candidate gene for muscle mass and fat deposition in pigs [ 7 – 9 , 22 , 32 , 54 , 55 ].…”

Section: Discussionmentioning

confidence: 99%

“…Results from these studies showed that backfat thickness is a polygenic trait that is regulated by a large number of small-effect variants. With the advent of single-nucleotide polymorphism (SNP) genotyping arrays, gene expression analyses, and other high-throughput genotyping technologies, many more candidate genes for backfat thickness have been reported that are involved in very diverse biological functions and metabolic pathways, such as: adipogenesis [ 13 , 14 ]; lipid metabolism (biosynthesis, absorption, transport, catabolism and homeostasis) pathways, including those related to fatty acids and triglycerides [ 13 , 15 , 16 ]; regulation of feed intake and energy homeostasis, through hormone-mediated responses [ 17 – 20 ] or even taste perception [ 21 ]; the adipocytokine signalling pathway [ 17 , 19 ]; the vitamin D metabolic pathway [ 13 ]; and nervous system development and regulation [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

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Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds

et al. 2021

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Background Backfat thickness is an important carcass composition trait for pork production and is commonly included in swine breeding programmes. In this paper, we report the results of a large genome-wide association study for backfat thickness using data from eight lines of diverse genetic backgrounds. Methods Data comprised 275,590 pigs from eight lines with diverse genetic backgrounds (breeds included Large White, Landrace, Pietrain, Hampshire, Duroc, and synthetic lines) genotyped and imputed for 71,324 single-nucleotide polymorphisms (SNPs). For each line, we estimated SNP associations using a univariate linear mixed model that accounted for genomic relationships. SNPs with significant associations were identified using a threshold of p < 10–6 and used to define genomic regions of interest. The proportion of genetic variance explained by a genomic region was estimated using a ridge regression model. Results We found significant associations with backfat thickness for 264 SNPs across 27 genomic regions. Six genomic regions were detected in three or more lines. The average estimate of the SNP-based heritability was 0.48, with estimates by line ranging from 0.30 to 0.58. The genomic regions jointly explained from 3.2 to 19.5% of the additive genetic variance of backfat thickness within a line. Individual genomic regions explained up to 8.0% of the additive genetic variance of backfat thickness within a line. Some of these 27 genomic regions also explained up to 1.6% of the additive genetic variance in lines for which the genomic region was not statistically significant. We identified 64 candidate genes with annotated functions that can be related to fat metabolism, including well-studied genes such as MC4R, IGF2, and LEPR, and more novel candidate genes such as DHCR7, FGF23, MEDAG, DGKI, and PTN. Conclusions Our results confirm the polygenic architecture of backfat thickness and the role of genes involved in energy homeostasis, adipogenesis, fatty acid metabolism, and insulin signalling pathways for fat deposition in pigs. The results also suggest that several less well-understood metabolic pathways contribute to backfat development, such as those of phosphate, calcium, and vitamin D homeostasis.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds

et al. 2021

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“…Pigs were raised in an intensive system and fed ad libitum with a cereal-based commercial diet until slaughtered at 187.4 ± 10.1 days of age on NOVA GENÈTICA S. A. experimental farm (Lleida, Spain). Detailed information of generation schemes, diet, growth, and housing conditions of the three backcrosses is described in Martínez-Montes et al 30 .…”

Section: Methodsmentioning

confidence: 99%

Identification of strong candidate genes for backfat and intramuscular fatty acid composition in three crosses based on the Iberian pig

Crespo-Piazuelo

Criado-Mesas

Revilla

et al. 2020

Sci Rep

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Meat quality has an important genetic component and can be modified by the fatty acid (FA) composition and the amount of fat contained in adipose tissue and muscle. The present study aimed to find genomic regions associated with the FA composition in backfat and muscle (longissimus dorsi) in 439 pigs with three different genetic backgrounds but having the Iberian breed in common. Genome-wide association studies (GWAS) were performed between 38,424 single-nucleotide polymorphisms (SNPs) covering the pig genome and 60 phenotypic traits related to backfat and muscle FA composition. Nine significant associated regions were found in backfat on the Sus scrofa chromosomes (SSC): SSC1, SSC2, SSC4, SSC6, SSC8, SSC10, SSC12, and SSC16. For the intramuscular fat, six significant associated regions were identified on SSC4, SSC13, SSC14, and SSC17. A total of 52 candidate genes were proposed to explain the variation in backfat and muscle FA composition traits. GWAS were also reanalysed including SNPs on five candidate genes (ELOVL6, ELOVL7, FADS2, FASN, and SCD). Regions and molecular markers described in our study may be useful for meat quality selection of commercial pig breeds, although several polymorphisms were breed-specific, and further analysis would be needed to evaluate possible causal mutations. Meat quality depends on the consumer's perception, which is subjected to the socio-demographic backgrounds of the consumer 1 , and is based on factors such as the nutritional value and the organoleptic properties of meat 2. These factors can be modified by the fatty acid (FA) composition and the amount of fat that is contained in adipose tissue and muscle 3. In addition, the consumer is becoming more concerned about the healthfulness of meat 1. Certain saturated FAs (SFAs) raise the cholesterol and low-density lipoprotein (LDL) levels in blood, which increase the risk of suffering a cardiovascular disease 4,5 ; whereas monounsaturated FAs (MUFAs) reduce plasma total LDL-cholesterol without affecting high-density lipoprotein (HDL) levels, which have an anti-atherogenic effect 4,5. Polyunsaturated FAs (PUFAs), especially long-chain omega-3 fatty acids, also reduce LDL-cholesterol levels and the risk of cardiovascular disease 6 , but high amount of PUFAs in meat increase its susceptibility to oxidation, producing meat with undesirable sensory properties 3. In contrast, a high concentration of MUFAs improve meat flavour 7. The Iberian pig is a breed characterized by its great meat quality, due to its high intramuscular fat (IMF) content with an increased proportion of MUFAs (mostly oleic acid) and a reduced quantity of PUFAs 8,9. Conversely, other commercial breeds such as Pietrain and Landrace produce lean meat with a lower proportion of fat,

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“…Fat deposition is also a critical biological process, generally measured by backfat thickness (BFT) or intermuscular fat content. Until now, Considerable association analysis has been focused on nding single-site variants, quantitative trait loci (QTLs), and related candidate functional genes that might in uence growth and fatness traits [20][21][22]. However, the systematic association studies for complex quantitative traits based on CNVs were rarely explored [18,23], and the full relevance of CNVs to the genetic basis involved is yet to be clari ed.…”

Section: Introductionmentioning

confidence: 99%

Genome-wide detection of CNV regions and their potential association with growth and fatness traits in Duroc pigs

Qiu

Ding²,

Zhuang

et al. 2020

Preprint

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Background: In the process of pig breeding, the average daily gain (ADG), days to 100 kg (AGE), and backfat thickness (BFT) are directly related to growth rate and fatness. However, the genetic mechanisms involved are not well understood. As an essential source of genetic diversity, copy number variation (CNV) that can affect a variety of complex traits and diseases, has gradually been thrust into the limelight. In this study, we reported the genome-wide CNVs of Duroc pigs by SNP genotyping data of 6,627 Duroc pigs. Moreover, we also performed CNV region (CNVR) based association analysis for growth and fatness traits in two Duroc populations.Results: Our study identified a total of 835 nonredundant CNVRs in American and Canadian Duroc pigs, which covered 226.73 Mb (~ 10.00%) of the pig autosomal genome. Among them, we identified 682 CNVRs in the American Duroc pigs and 424 CNVRs in the Canadian Duroc pigs, and 271 CNVRs were detected in both populations. Experimentally, 77.8% of randomly selected CNVRs were validated by quantitative PCR (qPCR). We also identified 24 significant CNVRs for growth and fatness traits though CNVR-based association analysis. Among these, six and three CNVRs in American and Canadian Duroc pigs were found to be associated with both ADG and AGE traits, respectively. Notably, four CNVRs showed both significant in ADG, AGE, and BFT, indicating that these CNVRs may play a pleiotropic role in regulating pig growth and fat deposition. Besides, further bioinformatics analysis determined a subset of potential candidate genes, such as PDGFRB, INSIG1, GPER1, PDGFA, and LPCAT1.Conclusions: The present study provides a necessary supplement to the CNV map of the Duroc genome through a large-scale population genotyping. Also, the CNVR-based association results provide a meaningful way to elucidate the genetic mechanisms of complex traits. The identified CNVRs can be used as molecular markers for genetic improvement in molecular-guided breeding of modern commercial pigs

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Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed

Cited by 23 publications

References 95 publications

Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds

Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds

Identification of strong candidate genes for backfat and intramuscular fatty acid composition in three crosses based on the Iberian pig

Genome-wide detection of CNV regions and their potential association with growth and fatness traits in Duroc pigs

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