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Genome-wide association study for carcass quality traits and growth in purebred and crossbred pigs1.

ABSTRACT: Carcass quality traits such as back fat (BF), loin depth (LD), and ADG are of extreme economic importance for the swine industry. This study aimed to (i) estimate the genetic parameters for such traits and (ii) conduct a single-step genome-wide association study (ssGWAS) to identify genomic regions that affect carcass quality and growth traits in purebred (PB) and three-way crossbred (CB) pigs. A total of 28,497 PBs and 135,768 CBs pigs were phenotyped for BF, LD, and ADG. Of these, 4,857 and 3,532 were genotyped using the Illumina PorcineSNP60K Beadchip. After quality control, 36,328 SNPs were available and were used to perform an ssGWAS. A bootstrap analysis (n = 1,000) and a signal enrichment analysis were performed to declare SNP significance. Genome regions were based on the variance explained by significant 10-SNP sliding windows. Estimates of PB heritability (SE) were 0.42 (0.019) for BF, 0.39 (0.020) for LD, and 0.35 (0.021) for ADG. Estimates of CB heritability were 0.49 (0.042) for BF, 0.27 (0.029) for LD, and 0.12 (0.021) for ADG. Genetic correlations (SE) across the two populations were 0.81 (0.02), 0.79 (0.04), and 0.56 (0.05), for BF, LD, and ADG, respectively. The variance explained by significant regions for each trait in PBs ranged from 1.51% to 1.35% for BF, from 4.02% to 3.18% for LD, and from 2.26% to 1.45% for ADG. In CBs, the variance explained by significant regions ranged from 1.88% to 1.37% for BF, from 1.29% to 1.23% for LD, and from 1.54% to 1.32% for ADG. In this study, we have described regions of the genome that determine carcass quality and growth traits of PB and CB pigs. These results provide evidence that there are overlapping and nonoverlapping regions in the genome influencing carcass quality and growth traits in PBs and three-way CB pigs.

SUBMITTER: Bergamaschi M

PROVIDER: S-EPMC6978898 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Genome-wide association study for carcass quality traits and growth in purebred and crossbred pigs1.

Bergamaschi Matteo M Maltecca Christian C Fix Justin J Schwab Clint C Tiezzi Francesco F

Journal of animal science 20200101 1

Carcass quality traits such as back fat (BF), loin depth (LD), and ADG are of extreme economic importance for the swine industry. This study aimed to (i) estimate the genetic parameters for such traits and (ii) conduct a single-step genome-wide association study (ssGWAS) to identify genomic regions that affect carcass quality and growth traits in purebred (PB) and three-way crossbred (CB) pigs. A total of 28,497 PBs and 135,768 CBs pigs were phenotyped for BF, LD, and ADG. Of these, 4,857 and 3, ...[more]

PMID: 31768540

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Project description:BACKGROUND: Genetic improvement of beef quality will benefit both producers and consumers, and can be achieved by selecting animals that carry desired quantitative trait nucleotides (QTN), which result from intensive searches using genetic markers. This paper presents a genome-wide association approach utilizing single nucleotide polymorphisms (SNP) in the Illumina BovineSNP50 BeadChip to seek genomic regions that potentially harbor genes or QTN underlying variation in carcass quality of beef cattle.This study used 747 genotyped animals, mainly crossbred, with phenotypes on twelve carcass quality traits, including hot carcass weight (HCW), back fat thickness (BF), Longissimus dorsi muscle area or ribeye area (REA), marbling scores (MRB), lean yield grade by Beef Improvement Federation formulae (BIFYLD), steak tenderness by Warner-Bratzler shear force 7-day post-mortem (LM7D) as well as body composition as determined by partial rib (IMPS 103) dissection presented as a percentage of total rib weight including body cavity fat (BDFR), lean (LNR), bone (BNR), intermuscular fat (INFR), subcutaneous fat (SQFR), and total fat (TLFR). RESULTS: At the genome wide level false discovery rate (FDR?<?10%), eight SNP were found significantly associated with HCW. Seven of these SNP were located on Bos taurus autosome (BTA) 6. At a less stringent significance level (P?<?0.001), 520 SNP were found significantly associated with mostly individual traits (473 SNP), and multiple traits (47 SNP). Of these significant SNP, 48 were located on BTA6, and 22 of them were in association with hot carcass weight. There were 53 SNP associated with percentage of rib bone, and 12 of them were on BTA20. The rest of the significant SNP were scattered over other chromosomes. They accounted for 1.90 - 5.89% of the phenotypic variance of the traits. A region of approximately 4 Mbp long on BTA6 was found to be a potential area to harbor candidate genes influencing growth. One marker on BTA25 accounting for 2.67% of the variation in LM7D may be worth further investigation for the improvement of beef tenderness. CONCLUSION: This study provides useful information to further assist the identification of chromosome regions and subsequently genes affecting carcass quality traits in beef cattle. It also revealed many SNP that acted pleiotropically to affect carcass quality. This knowledge is important in selecting subsets of SNP to improve the performance of beef cattle.

Project description:The aim of the present study was to compare the power of single nucleotide polymorphism (SNP)-based genome-wide association study (GWAS) and haplotype-based GWAS for quantitative trait loci (QTL) detection, and to detect novel candidate genes affecting economically important traits in a purebred Duroc population comprising seven-generation pedigree. First, we performed a simulation analysis using real genotype data of this population to compare the power (based on the null hypothesis) of the two methods. We then performed GWAS using both methods and real phenotype data comprising 52 traits, which included growth, carcass, and meat quality traits.In total, 836 animals were genotyped using the Illumina PorcineSNP60 BeadChip and 14 customized SNPs from regions of known candidate genes related to the traits of interest. The power of SNP-based GWAS was greater than that of haplotype-based GWAS in a simulation analysis. In real data analysis, a larger number of significant regions was obtained by SNP-based GWAS than by haplotype-based GWAS. For SNP-based GWAS, 23 genome-wide significant SNP regions were detected for 17 traits, and 120 genome-wide suggestive SNP regions were detected for 27 traits. For haplotype-based GWAS, 6 genome-wide significant SNP regions were detected for four traits, and 11 genome-wide suggestive SNP regions were detected for eight traits. All genome-wide significant SNP regions detected by haplotype-based GWAS were located in regions also detected by SNP-based GWAS. Four regions detected by SNP-based GWAS were significantly associated with multiple traits: on Sus scrofa chromosome (SSC) 1 at 304 Mb; and on SSC7 at 35-39 Mb, 41-42 Mb, and 103 Mb. The vertnin gene (VRTN) in particular, was located on SSC7 at 103 Mb and was significantly associated with vertebrae number and carcass lengths. Mapped QTL regions contain some candidate genes involved in skeletal formation (FUBP3; far upstream element binding protein 3) and fat deposition (METTL3; methyltransferase like 3).Our results show that a multigenerational pig population is useful for detecting QTL, which are typically segregated in a purebred population. In addition, a novel significant region could be detected by SNP-based GWAS as opposed to haplotype-based GWAS.

Project description:Imputed whole-genome sequence (WGS) has been proposed to improve genome-wide association studies (GWAS), since all causative mutations responsible for phenotypic variation are expected to be present in the data. This approach was applied on a large number of purebred (PB) and crossbred (CB) pigs for 18 pork color traits to evaluate the impact of using imputed WGS relative to medium-density marker panels. The traits included Minolta A*, B*, and L* for fat (FCOL), quadriceps femoris muscle (QFCOL), thawed loin muscle (TMCOL), fresh ham gluteus medius (GMCOL), ham iliopsoas muscle (ICOL), and longissimus dorsi muscle on the fresh loin (FMCOL). Sequence variants were imputed from a medium-density marker panel (61K for CBs and 50K for PBs) in all genotyped pigs using BeagleV5.0. We obtained high imputation accuracy (average of 0.97 for PBs and 0.91 for CBs). GWAS were conducted for three datasets: 954 CBs and 891 PBs, and the combined CBs and PBs. For most traits, no significant associations were detected, regardless of panel density or population type. However, quantitative trait loci (QTL) regions were only found for a few traits including TMCOL Minolta A* and GMCOL Minolta B* (CBs), FMCOL Minolta B*, FMCOL Minolta L*, and ICOL Minolta B* (PBs) and FMCOL Minolta A*, FMCOL Minolta B*, GMCOL Minolta B*, and ICOL Minolta B* (Combined dataset). More QTL regions were identified with WGS (n = 58) relative to medium-density marker panels (n = 22). Most of the QTL were linked to previously reported QTLs or candidate genes that have been previously reported to be associated with meat quality, pH and pork color; e.g., VIL1, PRKAG3, TTLL4, and SLC11A1, USP37. CTDSP1 gene on SSC15 has not been previously associated with meat color traits in pigs. The findings suggest any added value of WGS was only for detecting novel QTL regions when the sample size is sufficiently large as with the Combined dataset in this study. The percentage of phenotypic variance explained by the most significant SNPs also increased with WGS compared with medium-density panels. The results provide additional insights into identification of a number of candidate regions and genes for pork color traits in different pig populations.

Project description:There have been several genome-wide association study (GWAS) reported for carcass, growth, and meat traits in chickens. Most of these studies have been based on single SNPs GWAS. In contrast, haplotype-based GWAS reports have been limited. In the present study, 2 Northeast Agricultural University broiler lines divergently selected for abdominal fat content (NEAUHLF) and genotyped with the chicken 60K SNP chip were used to perform a haplotype-based GWAS. The lean and fat chicken lines were selected for abdominal fat content for 11 yr. Abdominal fat weight was significantly different between the 2 lines; however, there was no difference for body weight between the lean and fat lines. A total of 132 haplotype windows were significantly associated with abdominal fat weight. These significantly associated haplotype windows were primarily located on chromosomes 2, 4, 8, 10, and 26. Seven candidate genes, including SHH, LMBR1, FGF7, IL16, PLIN1, IGF1R, and SLC16A1, were located within these associated regions. These genes may play important roles in the control of abdominal fat content. Two regions on chromosomes 3 and 10 were significantly associated with testis weight. These 2 regions were previously detected by the single SNP GWAS using this same resource population. TCF21 on chromosome 3 was identified as a potentially important candidate gene for testis growth and development based on gene expression analysis and the reported function of this gene. TCF12, which was previously detected in our SNP by SNP interaction analysis, was located in a region on chromosome 10 that was significantly associated with testis weight. Six candidate genes, including TNFRSF1B, PLOD1, NPPC, MTHFR, EPHB2, and SLC35A3, on chromosome 21 may play important roles in bone development based on the known function of these genes. In addition, several regions were significantly associated with other carcass and growth traits, but no candidate genes were identified. The results of the present study may be helpful in understanding the genetic mechanisms of carcass and growth traits in chickens.

Project description:The objectives of this study were to identify informative genomic regions that affect the exterior traits of purebred Korean Yorkshire pigs and to investigate and compare the accuracy of genomic prediction for response variables. Phenotypic data on body height (BH), body length (BL), and total teat number (TTN) from 2,432 Yorkshire pigs were used to obtain breeding values including as response variable the estimated breeding value (EBV) and 2 types of deregressed EBVs-one including the parent average (DEBVincPA) and the other excluding it (DEBVexcPA). A final genotype panel comprising 46,199 SNP markers was retained for analysis after quality control for common SNPs. The BayesB and BayesC methods-with various π and weighted response variables (EBV, DEBVincPA, or DEBVexcPA)-were used to estimate SNP effects, through the genome-wide association study. The significance of genomic windows (1 Mb) was obtained at 1.0% additive genetic variance and was subsequently used to identify informative genomic regions. Furthermore, SNPs with a high model frequency (≥0.90) were considered informative. The accuracy of genomic prediction was estimated using a 5-fold cross-validation with the K-means clustering method. Genomic accuracy was measured as the genomic correlation between the molecular breeding value and the individual weighted response variables (EBV, DEBVincPA, or DEBVexcPA). The number of identified informative windows (1 Mb) for BH, BL, and TTN was 4, 3, and 4, respectively. The number of significant SNPs for BH, BL, and TTN was 6, 4, and 5, respectively. Diversity π did not influence the accuracy of genomic prediction. The BayesB method showed slightly higher genomic accuracy for exterior traits than BayesC method in this study. In addition, the genomic accuracy using DEBVincPA as response variable was higher than that using other response variables. Therefore, the genomic accuracy using BayesB (π = 0.90) with DEBVinPA as a response variable was the most effective in this study. The genomic accuracy values for BH, BL, and TTN were calculated to be 0.52, 0.60, and 0.51, respectively.

Project description:For swine breeding programs, testing and selection programs are usually within purebred (PB) populations located in nucleus units that are generally managed differently and tend to have a higher health level than the commercial herds in which the crossbred (CB) descendants of these nucleus animals are expected to perform. This approach assumes that PB animals selected in the nucleus herd will have CB progeny that have superior performance at the commercial level. There is clear evidence that this may not be the case for all traits of economic importance and, thus, including data collected at the commercial herd level may increase the accuracy of selection for commercial CB performance at the nucleus level. The goal for this study was to estimate genetic parameters for five maternal reproductive traits between two PB maternal nucleus populations (Landrace and Yorkshire) and their CB offspring: Total Number Born (TNB), Number Born Alive (NBA), Number Born Alive > 1 kg (NBA > 1 kg), Total Number Weaned (TNW), and Litter Weight at Weaning (LWW). Estimates were based on single-step GBLUP by analyzing any two combinations of a PB and the CB population, and by analyzing all three populations jointly. The genomic relationship matrix between the three populations was generated by using within-population allele frequencies for relationships within a population, and across-population allele frequencies for relationships of the CB with the PB animals. Utilization of metafounders for the two PB populations had no effect on parameter estimates, so the two PB populations were assumed to be genetically unrelated. Joint analysis of two (one PB plus CB) vs. three (both PB and CB) populations did not impact estimates of heritability, additive genetic variance, and genetic correlations. Heritabilities were generally similar between the PB and CB populations, except for LWW and TNW, for which PB populations had about four times larger estimates than CB. Purebred-crossbred genetic correlations (rpc) were larger for Landrace than for Yorkshire, except for NBA > 1 kg. These estimates of rpc indicate that there is potential to improve selection of PB animals for CB performance by including CB information for all traits in the Yorkshire population, but that noticeable additional gains may only occur for NBA > 1 kg and TNW in the Landrace population.

Dataset Information

Genome-wide association study for carcass quality traits and growth in purebred and crossbred pigs1.

Publications

Genome-wide association study for carcass quality traits and growth in purebred and crossbred pigs1.

Similar Datasets

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