A genome-wide association analysis for porcine serum lipid traits reveals the existence of age-specific genetic determinants

Manunza, Arianna; Casellas, J.; Quintanilla, Raquel; González-Prendes, Rayner; Pena, Ramona N.; Tibau, J.; Mercadé, A.; Castelló, Anna; Aznárez, Nitdia; Hernández-Sánchez, Jules; Amills, Marcel

doi:10.1186/1471-2164-15-758

Cited by 25 publications

(31 citation statements)

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“…A). QTL and GWAS techniques have also identified seemingly modular age‐specific allelic effects in a wide range of organisms . These studies have all reported that the polymorphisms contributing to trait variation are different at different ages.…”

Section: Genetic Modularity Of Life Histories: the Case For Evolutionmentioning

confidence: 99%

Pleiotropy, constraint, and modularity in the evolution of life histories: insights from genomic analyses

Hughes

Leips

2016

Annals of the New York Academy of Sciences

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Multicellular organisms display an enormous range of life history strategies and present an evolutionary conundrum; despite strong natural selection, life history traits are characterized by high levels of genetic variation. To understand the evolution of life histories and the maintenance of this variation, the specific phenotypic effects of segregating alleles and the genetic networks in which they act need to be elucidated. In particular, the extent to which life history evolution is constrained by the pleiotropy of alleles contributing to life history variation is generally unknown. Here we review recent empirical results that shed light on this question, with an emphasis on studies employing genomic analyses. While genome-scale analyses are increasingly practical and affordable, they face limitations of genetic resolution and statistical power. We describe new research approaches that we believe can produce new insights and evaluate their promise and applicability to different kinds of organisms. Two approaches seem particularly promising: experiments that manipulate selection in multiple dimensions and measure phenotypic and genomic response, and analytical approaches that take into account genome-wide associations between markers and phenotypes, rather than applying a traditional marker-by-marker approach.

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Section: Genetic Modularity Of Life Histories: the Case For Evolutionmentioning

confidence: 99%

Pleiotropy, constraint, and modularity in the evolution of life histories: insights from genomic analyses

Hughes

Leips

2016

Annals of the New York Academy of Sciences

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“…GEMMA was also employed to estimate the proportion of variance in phenotypes explained by SNP genotypes (i.e. “chip heritability”) using the following formula:

h_{SNP}^{2} = \frac{σ_{G}^{2}}{{normalσ}_{G}^{2} + {normalσ}_{E}^{2}}

where

σ_{G}^{2}

is the variance due to SNPs and

σ_{E}^{2}

is the variance of residuals (Manunza et al., ).…”

Section: Methodsmentioning

confidence: 99%

Genome‐wide association studies for two exterior traits in Chinese Dongxiang spotted pigs

Wang

Tang

et al. 2018

Animal Science Journal

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Pigs show extensive variation in exterior appearance. This variation has been explored as one of the selection targets to form breeding features in the pig industry. In this study, a customized Affymetrix Axiom Pig1.4M array plate was used to conduct genome-wide association studies (GWAS) for two exterior traits-spotted coat color (SC) and facial type (FT)-in Chinese Dongxiang spotted pigs. Two and 12 single nucleotide polymorphisms (SNPs) were identified to be associated with SC and FT at the 5% genome-wide significant level, respectively. Of these SNPs, two associated with SC were located around the DACH1 gene on Sus Scrofa chromosome (SSC)11. Eleven SNPs associated with FT were located within a 7.68 Mb region (29.03-36.71 Mb) on SSC7. Based on the GWAS results and the biological functions of genes, we highlight EDNRB as a candidate gene for SC and HMGA1 and RPS10 as the potential genes affecting facial variation. The findings contribute to the final characterization of causative genes and mutations underlying the effects of the SSC7 and SSC11 loci and improve our understanding of the genetic basis of phenotypic variation in Chinese indigenous pigs.

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“…Quality genotyping analyses were carried out with the GenomeStudio software (Illumina), as previously reported14. We removed SNPs (a) mapping to the X chromosome, (b) with a rate of missing genotypes higher than 5%, (c) that did not conform Hardy-Weinberg expectations (threshold set at a P -value ≤ 0.001), (d) that had a minor allele frequency below 0.05, (e) that had a GenCall score < 0.15, (f) that had a call rate < 95% or (g) that could not be mapped to the pig genome ( Sus scrofa 10.2 assembly).…”

Section: Methodsmentioning

confidence: 99%

Joint QTL mapping and gene expression analysis identify positional candidate genes influencing pork quality traits

González-Prendes

Quintanilla

Cánovas

et al. 2017

Sci Rep

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Meat quality traits have an increasing importance in the pig industry because of their strong impact on consumer acceptance. Herewith, we have combined phenotypic and microarray expression data to map loci with potential effects on five meat quality traits recorded in the longissimus dorsi (LD) and gluteus medius (GM) muscles of 350 Duroc pigs, i.e. pH at 24 hours post-mortem (pH24), electric conductivity (CE) and muscle redness (a*), lightness (L*) and yellowness (b*). We have found significant genome-wide associations for CE of LD on SSC4 (~104 Mb), SSC5 (~15 Mb) and SSC13 (~137 Mb), while several additional regions were significantly associated with meat quality traits at the chromosome-wide level. There was a low positional concordance between the associations found for LD and GM traits, a feature that reflects the existence of differences in the genetic determinism of meat quality phenotypes in these two muscles. The performance of an eQTL search for SNPs mapping to the regions associated with meat quality traits demonstrated that the GM a* SSC3 and pH24 SSC17 QTL display positional concordance with cis-eQTL regulating the expression of several genes with a potential role on muscle metabolism.

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A genome-wide association analysis for porcine serum lipid traits reveals the existence of age-specific genetic determinants

Cited by 25 publications

References 50 publications

Pleiotropy, constraint, and modularity in the evolution of life histories: insights from genomic analyses

Pleiotropy, constraint, and modularity in the evolution of life histories: insights from genomic analyses

Genome‐wide association studies for two exterior traits in Chinese Dongxiang spotted pigs

Joint QTL mapping and gene expression analysis identify positional candidate genes influencing pork quality traits

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