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SNP- and haplotype-based genome-wide association studies for growth, carcass, and meat quality traits in a Duroc multigenerational population.

Sato S, Uemoto Y, Kikuchi T, Egawa S, Kohira K, Saito T, Sakuma H, Miyashita S, Arata S, Kojima T, Suzuki K - BMC Genet. (2016)

Bottom Line: 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.In addition, a novel significant region could be detected by SNP-based GWAS as opposed to haplotype-based GWAS.

View Article: PubMed Central - PubMed

Affiliation: National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan. s0sato@nlbc.go.jp.

ABSTRACT

Background: 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 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.

Results: 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).

Conclusion: 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.

No MeSH data available.


Related in: MedlinePlus

Trait associations across genomic regions analyzed by SNP-based and haplotype-based genome-wide association studies (GWAS). Each row represents a trait, and each column, a genomic region containing SNPs that are genome-wide suggestively or significantly associated with a trait. Only traits with at least one associated SNP and SNPs associated with at least one trait are shown. Each summary shows the results of growth traits (a) carcass traits (b) and meat quality traits (c). SSC, Sus scrofa chromosome; DG, Average daily gain; LEA, Ultrasound loin muscle area; BF, Ultrasound backfat thickness; HEIGHT, Height at withers; FW, Front width; CW, Chest width; CD, Chest depth; CC, Circumference of chest; CCB at F(/R) 30(/105), Circumference of cannon bone at front (/Rear) (at 30 kg/105 kg); SCORE at F(/R) 30(/105), Front (/Rear) leg score at 30 kg (/105 kg); CL, Carcass length; CL1, Carcass length I; CL2, Carcass length II; CL3, Carcass length III; CT, Carcass thickness; TVN, Thoracic vertebrae number; LVN, Lumbar vertebrae number; BSFT, Subcutaneous fat thickness (Back); LSFT, Subcutaneous fat thickness (Loin); 45r, carcass cross section at fourth–fifth rib; HBL, carcass cross section at half-body length; LEA at 45r, Longissimus muscle area at 45r; LEA at HBL, Longissimus muscle area at HBL; IFA at 45r, Intermuscular fat area at 45r; ALLFA at 45r, All fat area of 45r; SFA at HBL, Subcutaneous fat area at HBL; IFA at HBL, Intermuscular fat area at HBL; ALLFA at HBL, All fat area at HBL; MOS, Moisture; IMF, Intramuscular fat; PROT, Protein; COOK, Cooking loss; WHC, Centrifugal water-holding capacity; SF, Shear force value; M-a*, Redness of longissimus muscle; M-b*, Yellowness of longissimus muscle; F-L*, Lightness of subcutaneous fat; F-a*, Redness of subcutaneous fat; F-b*, Yellowness of subcutaneous fat
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Fig3: Trait associations across genomic regions analyzed by SNP-based and haplotype-based genome-wide association studies (GWAS). Each row represents a trait, and each column, a genomic region containing SNPs that are genome-wide suggestively or significantly associated with a trait. Only traits with at least one associated SNP and SNPs associated with at least one trait are shown. Each summary shows the results of growth traits (a) carcass traits (b) and meat quality traits (c). SSC, Sus scrofa chromosome; DG, Average daily gain; LEA, Ultrasound loin muscle area; BF, Ultrasound backfat thickness; HEIGHT, Height at withers; FW, Front width; CW, Chest width; CD, Chest depth; CC, Circumference of chest; CCB at F(/R) 30(/105), Circumference of cannon bone at front (/Rear) (at 30 kg/105 kg); SCORE at F(/R) 30(/105), Front (/Rear) leg score at 30 kg (/105 kg); CL, Carcass length; CL1, Carcass length I; CL2, Carcass length II; CL3, Carcass length III; CT, Carcass thickness; TVN, Thoracic vertebrae number; LVN, Lumbar vertebrae number; BSFT, Subcutaneous fat thickness (Back); LSFT, Subcutaneous fat thickness (Loin); 45r, carcass cross section at fourth–fifth rib; HBL, carcass cross section at half-body length; LEA at 45r, Longissimus muscle area at 45r; LEA at HBL, Longissimus muscle area at HBL; IFA at 45r, Intermuscular fat area at 45r; ALLFA at 45r, All fat area of 45r; SFA at HBL, Subcutaneous fat area at HBL; IFA at HBL, Intermuscular fat area at HBL; ALLFA at HBL, All fat area at HBL; MOS, Moisture; IMF, Intramuscular fat; PROT, Protein; COOK, Cooking loss; WHC, Centrifugal water-holding capacity; SF, Shear force value; M-a*, Redness of longissimus muscle; M-b*, Yellowness of longissimus muscle; F-L*, Lightness of subcutaneous fat; F-a*, Redness of subcutaneous fat; F-b*, Yellowness of subcutaneous fat

Mentions: In real data analysis, SNP-based GWAS and haplotype-based GWAS were performed for 52 traits related to growth, carcass, and meat quality. We summarized the genome-wide significant and suggestive SNP regions for these traits in Fig. 3 and Additional file 7: Table S2. For SNP-based GWAS, 23 genome-wide significant SNP regions were detected in 17 traits, and 120 genome-wide suggestive SNP regions were detected in 27 traits. For haplotype-based GWAS, 6 genome-wide significant SNP regions were detected in four traits, and 11 genome-wide suggestive SNP regions were detected in eight traits. All genome-wide significant SNP regions detected by haplotype-based GWAS were located in regions that were also detected by SNP-based GWAS. Most of the genome-wide suggestive SNP regions detected by haplotype-based GWAS were located in regions that were also detected by SNP-based GWAS. However, four of these regions were detected by haplotype-based GWAS only.Fig. 3


SNP- and haplotype-based genome-wide association studies for growth, carcass, and meat quality traits in a Duroc multigenerational population.

Sato S, Uemoto Y, Kikuchi T, Egawa S, Kohira K, Saito T, Sakuma H, Miyashita S, Arata S, Kojima T, Suzuki K - BMC Genet. (2016)

Trait associations across genomic regions analyzed by SNP-based and haplotype-based genome-wide association studies (GWAS). Each row represents a trait, and each column, a genomic region containing SNPs that are genome-wide suggestively or significantly associated with a trait. Only traits with at least one associated SNP and SNPs associated with at least one trait are shown. Each summary shows the results of growth traits (a) carcass traits (b) and meat quality traits (c). SSC, Sus scrofa chromosome; DG, Average daily gain; LEA, Ultrasound loin muscle area; BF, Ultrasound backfat thickness; HEIGHT, Height at withers; FW, Front width; CW, Chest width; CD, Chest depth; CC, Circumference of chest; CCB at F(/R) 30(/105), Circumference of cannon bone at front (/Rear) (at 30 kg/105 kg); SCORE at F(/R) 30(/105), Front (/Rear) leg score at 30 kg (/105 kg); CL, Carcass length; CL1, Carcass length I; CL2, Carcass length II; CL3, Carcass length III; CT, Carcass thickness; TVN, Thoracic vertebrae number; LVN, Lumbar vertebrae number; BSFT, Subcutaneous fat thickness (Back); LSFT, Subcutaneous fat thickness (Loin); 45r, carcass cross section at fourth–fifth rib; HBL, carcass cross section at half-body length; LEA at 45r, Longissimus muscle area at 45r; LEA at HBL, Longissimus muscle area at HBL; IFA at 45r, Intermuscular fat area at 45r; ALLFA at 45r, All fat area of 45r; SFA at HBL, Subcutaneous fat area at HBL; IFA at HBL, Intermuscular fat area at HBL; ALLFA at HBL, All fat area at HBL; MOS, Moisture; IMF, Intramuscular fat; PROT, Protein; COOK, Cooking loss; WHC, Centrifugal water-holding capacity; SF, Shear force value; M-a*, Redness of longissimus muscle; M-b*, Yellowness of longissimus muscle; F-L*, Lightness of subcutaneous fat; F-a*, Redness of subcutaneous fat; F-b*, Yellowness of subcutaneous fat
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
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Fig3: Trait associations across genomic regions analyzed by SNP-based and haplotype-based genome-wide association studies (GWAS). Each row represents a trait, and each column, a genomic region containing SNPs that are genome-wide suggestively or significantly associated with a trait. Only traits with at least one associated SNP and SNPs associated with at least one trait are shown. Each summary shows the results of growth traits (a) carcass traits (b) and meat quality traits (c). SSC, Sus scrofa chromosome; DG, Average daily gain; LEA, Ultrasound loin muscle area; BF, Ultrasound backfat thickness; HEIGHT, Height at withers; FW, Front width; CW, Chest width; CD, Chest depth; CC, Circumference of chest; CCB at F(/R) 30(/105), Circumference of cannon bone at front (/Rear) (at 30 kg/105 kg); SCORE at F(/R) 30(/105), Front (/Rear) leg score at 30 kg (/105 kg); CL, Carcass length; CL1, Carcass length I; CL2, Carcass length II; CL3, Carcass length III; CT, Carcass thickness; TVN, Thoracic vertebrae number; LVN, Lumbar vertebrae number; BSFT, Subcutaneous fat thickness (Back); LSFT, Subcutaneous fat thickness (Loin); 45r, carcass cross section at fourth–fifth rib; HBL, carcass cross section at half-body length; LEA at 45r, Longissimus muscle area at 45r; LEA at HBL, Longissimus muscle area at HBL; IFA at 45r, Intermuscular fat area at 45r; ALLFA at 45r, All fat area of 45r; SFA at HBL, Subcutaneous fat area at HBL; IFA at HBL, Intermuscular fat area at HBL; ALLFA at HBL, All fat area at HBL; MOS, Moisture; IMF, Intramuscular fat; PROT, Protein; COOK, Cooking loss; WHC, Centrifugal water-holding capacity; SF, Shear force value; M-a*, Redness of longissimus muscle; M-b*, Yellowness of longissimus muscle; F-L*, Lightness of subcutaneous fat; F-a*, Redness of subcutaneous fat; F-b*, Yellowness of subcutaneous fat
Mentions: In real data analysis, SNP-based GWAS and haplotype-based GWAS were performed for 52 traits related to growth, carcass, and meat quality. We summarized the genome-wide significant and suggestive SNP regions for these traits in Fig. 3 and Additional file 7: Table S2. For SNP-based GWAS, 23 genome-wide significant SNP regions were detected in 17 traits, and 120 genome-wide suggestive SNP regions were detected in 27 traits. For haplotype-based GWAS, 6 genome-wide significant SNP regions were detected in four traits, and 11 genome-wide suggestive SNP regions were detected in eight traits. All genome-wide significant SNP regions detected by haplotype-based GWAS were located in regions that were also detected by SNP-based GWAS. Most of the genome-wide suggestive SNP regions detected by haplotype-based GWAS were located in regions that were also detected by SNP-based GWAS. However, four of these regions were detected by haplotype-based GWAS only.Fig. 3

Bottom Line: 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.In addition, a novel significant region could be detected by SNP-based GWAS as opposed to haplotype-based GWAS.

View Article: PubMed Central - PubMed

Affiliation: National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan. s0sato@nlbc.go.jp.

ABSTRACT

Background: 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 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.

Results: 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).

Conclusion: 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.

No MeSH data available.


Related in: MedlinePlus