Yun-Mi Lee

Genome Scan for Parent-of-Origin QTL Effects on Bovine Growth and Carcass Traits

Parent-of-origin effects (POE) such as genomic imprinting influence growth and body composition in livestock, rodents, and humans. Here, we report the results of a genome scan to detect quantitative trait loci (QTL) with POE on growth and carcass traits in Angus × Brahman cattle crossbreds. We identified 24 POE–QTL on 15 Bos taurus autosomes (BTAs) of which six were significant at 5% genome-wide (GW) level and 18 at the 5% chromosome-wide (CW) significance level. Six QTL were paternally expressed while 15 were maternally expressed. Three QTL influencing post-weaning growth map to the proximal end of BTA2 (linkage region of 0–9 cM; genomic region of 5.0–10.8 Mb), for which only one imprinted ortholog is known so far in the human and mouse genomes, and therefore may potentially represent a novel imprinted region. The detected QTL individually explained 1.4 ∼ 5.1% of each trait’s phenotypic variance. Comparative in silico analysis of bovine genomic locations show that 32 out of 1,442 known mammalian imprinted genes from human and mouse homologs map to the identified QTL regions. Although several of the 32 genes have been associated with quantitative traits in cattle, only two (GNAS and PEG3) have experimental proof of being imprinted in cattle. These results lend additional support to recent reports that POE on quantitative traits in mammals may be more common than previously thought, and strengthen the need to identify and experimentally validate cattle orthologs of imprinted genes so as to investigate their effects on quantitative traits.

Characterizations of Shell and Mantle Edge Pigmentation of a Pacific Oyster, Crassostrea gigas, in Korean Peninsula

The objectives of this study were to investigate color patterns of shell and mantle edge pigmentation of a Pacific oyster, C. gigas, and to estimate variance components of the two colors. A sample of 240 F0 oysters was collected from six aquaculture farms in Tongyeong, Korea to measure shell color and mantle edge pigmentation. Among the F0s, male and female individuals with black (white) shell and black (white) mantle edge were selected and mated to generate three F1 full-sib black (white) cross families (N = 265). Two and four F2 cross families (N = 286) were also produced from black and white F1 selected individuals, respectively. Variance component estimates due to residuals and families within color were obtained using SAS PROC VARCOMP procedures to estimate heritability of shell and mantle edge pigmentation. In the F0 generation, about 29% (11%) had black (white) color for both shell and mantle edge. However, in the F1 and F2 black (white) cross families, 75% (67%) and 100% (100%) of oysters had black (white) shell colors, and 59% (23%) and 79% (55%) had black (white) mantle edge, respectively. Spearman correlation coefficients between shell and mantle edge color were 0.25, 0.74, and 0.92 in F0, F1, and F2 generations, respectively, indicating that, with generations of selection process, an individual with black (white) shell color is more likely to have black (white) mantle edge pigmentation. This suggests that shell color could be a good indicator trait for mantle edge pigmentation if selection of both the colors is implemented for a couple of generations. Estimates of heritability were 0.41 and 0.77 for shell color and 0.27 and 0.08 for mantle edge pigmentation in the F1 and F2 generations, respectively, indicating that, in general, significant proportions of phenotypic variations for the shell and mantle edge colors are explained by genetic variations between individuals. These results suggest that the two color traits are inheritable and correlated, enabling effective selection on shell and mantle edge color.

Development of SNP Markers for Domestic Pork Traceability

The purpose of the study was to develop an optimum SNP marker set to be utilized for domestic pork traceability. The study tested 51 SNP markers analyzed for origin of farm to be determined from genotypes of offspring and parents in pigs. With the simulation data through random mating population (PI), half sib mating population (PIhalf-sib) and full sib mating population (PIsibs), probability of identical genotypes were analyzed as 5.63×10 33 , 4.35×10 15 and 1.32×10 15 , respectively. The 51 SNP markers also had 100% accuracy for parental determination. These results suggest that if the pig breeding stock is genotyped with the 51 SNP markers, the genotype information of individual offspring can be checked for farm origins by tracing parental sow and sire. Therefore, these SNP markers will be useful to trace the pork from production to consumption in pigs. (Key words : Pig breeding, SNPs, Pork origin, Parentage analysis)

A Whole Genome Association Study on Meat Quality Traits Using High Density SNP Chips in a Cross between Korean Native Pig and Landrace

A whole genome association (WGA) study was performed to detect significant polymorphisms for meat quality traits in an F2 cross population (N = 478) that were generated with Korean native pig sires and Landrace dams in National Livestock Research Institute, Songwhan, Korea. The animals were genotyped using Illumina porcine 60k SNP beadchips, in which a set of 46,865 SNPs were available for the WGA analyses on ten carcass quality traits; live weight, crude protein, crude lipids, crude ash, water holding capacity, drip loss, shear force, CIE L, CIE a and CIE b. Phenotypes were regressed on additive and dominance effects for each SNP using a simple linear regression model, after adjusting for sex, sire and slaughter stage as fixed effects. With the significant SNPs for each trait (p<0.001), a stepwise regression procedure was applied to determine the best set of SNPs with the additive and/or dominance effects. A total of 106 SNPs, or quantitative trait loci (QTL) were detected, and about 32 to 66% of the total phenotypic variation was explained by the significant SNPs for each trait. The QTL were identified in most porcine chromosomes (SSCs), in which majority of the QTL were detected in SSCs 1, 2, 12, 13, 14 and 16. Several QTL clusters were identified on SSCs 12, 16 and 17, and a cluster of QTL influencing crude protein, crude lipid, drip loss, shear force, CIE a and CIE b were located between 20 and 29 Mb of SSC12. A pleiotropic QTL for drip loss, CIE L and CIE b was also detected on SSC16. These QTL need to be validated in commercial pig populations for genetic improvement in meat quality via marker-assisted selection.

Identification of Single Nucleotide Polymorphisms (SNPs) of the Bovine Growth Hormone (bGH) Gene Associated with Growth and Carcass Traits in Hanwoo.

The purpose of this study was to find any association of the bovine growth hormone (bGH) gene with growth and carcass quality traits in Korean native cattle, Hanwoo. Genomic DNA was extracted from 21 Hanwoo individuals, and the 47 to 2,528 bp region of the bGH 2,856 bp (GenBank accession number M57764) including the promoter and the five exons was sequenced. A total of ten bGH SNPs were confirmed, including four (253 C>T, 303 C>T, 502 C>T, and 559 G>A) in the promoter, one (679 C>T) in exon 1, one (1,692 T>C) in intron 3, and four (2141 C>G, 2258 C>T, 2277 C>T, and 2291 A>C) in exon 5. The ten bGH SNPs were genotyped for a sample of 242 Hanwoo steers and association tests were performed to find any significant SNP that was correlated with growth and carcass quality. Of the SNPs, the 303 C>T SNP in the promoter region was significantly associated with 6-month-old weight, the 559 G>A SNP with longissimus dorsi muscle area, the 2141 C>G SNP in exon 5 with daily weight gain, and the 2258 C>T SNP with daily weight gain and carcass weight (p<0.05). The significant SNPs need to be verified in other Hanwoo populations before considering implementation of marker-assisted selection for genetic improvement of growth and carcass quality in Hanwoo.

Genome-wide Association Study to Identify Quantitative Trait Loci for Meat and Carcass Quality Traits in Berkshire

Meat and carcass quality attributes are of crucial importance influencing consumer preference and profitability in the pork industry. A set of 400 Berkshire pigs were collected from Dasan breeding farm, Namwon, Chonbuk province, Korea that were born between 2012 and 2013. To perform genome wide association studies (GWAS), eleven meat and carcass quality traits were considered, including carcass weight, backfat thickness, pH value after 24 hours (pH24), Commission Internationale de l’Eclairage lightness in meat color (CIE L), redness in meat color (CIE a), yellowness in meat color (CIE b), filtering, drip loss, heat loss, shear force and marbling score. All of the 400 animals were genotyped with the Porcine 62K SNP BeadChips (Illumina Inc., USA). A SAS general linear model procedure (SAS version 9.2) was used to pre-adjust the animal phenotypes before GWAS with sire and sex effects as fixed effects and slaughter age as a covariate. After fitting the fixed and covariate factors in the model, the residuals of the phenotype regressed on additive effects of each single nucleotide polymorphism (SNP) under a linear regression model (PLINK version 1.07). The significant SNPs after permutation testing at a chromosome-wise level were subjected to stepwise regression analysis to determine the best set of SNP markers. A total of 55 significant (p<0.05) SNPs or quantitative trait loci (QTL) were detected on various chromosomes. The QTLs explained from 5.06% to 8.28% of the total phenotypic variation of the traits. Some QTLs with pleiotropic effect were also identified. A pair of significant QTL for pH24 was also found to affect both CIE L and drip loss percentage. The significant QTL after characterization of the functional candidate genes on the QTL or around the QTL region may be effectively and efficiently used in marker assisted selection to achieve enhanced genetic improvement of the trait considered.

Evaluation of Genome Based Estimated Breeding Values for Meat Quality in a Berkshire Population Using High Density Single Nucleotide Polymorphism Chips

The accuracy of genomic estimated breeding values (GEBV) was evaluated for sixteen meat quality traits in a Berkshire population (n = 1,191) that was collected from Dasan breeding farm, Namwon, Korea. The animals were genotyped with the Illumina porcine 62 K single nucleotide polymorphism (SNP) bead chips, in which a set of 36,605 SNPs were available after quality control tests. Two methods were applied to evaluate GEBV accuracies, i.e. genome based linear unbiased prediction method (GBLUP) and Bayes B, using ASREML 3.0 and Gensel 4.0 software, respectively. The traits composed different sets of training (both genotypes and phenotypes) and testing (genotypes only) data. Under the GBLUP model, the GEBV accuracies for the training data ranged from 0.42±0.08 for collagen to 0.75±0.02 for water holding capacity with an average of 0.65±0.04 across all the traits. Under the Bayes B model, the GEBV accuracy ranged from 0.10±0.14 for National Pork Producers Council (NPCC) marbling score to 0.76±0.04 for drip loss, with an average of 0.49±0.10. For the testing samples, the GEBV accuracy had an average of 0.46±0.10 under the GBLUP model, ranging from 0.20±0.18 for protein to 0.65±0.06 for drip loss. Under the Bayes B model, the GEBV accuracy ranged from 0.04±0.09 for NPCC marbling score to 0.72±0.05 for drip loss with an average of 0.38±0.13. The GEBV accuracy increased with the size of the training data and heritability. In general, the GEBV accuracies under the Bayes B model were lower than under the GBLUP model, especially when the training sample size was small. Our results suggest that a much greater training sample size is needed to get better GEBV accuracies for the testing samples.

A Whole Genome Association Study on Meat Palatability in Hanwoo

A whole genome association (WGA) study was carried out to find quantitative trait loci (QTL) for sensory evaluation traits in Hanwoo. Carcass samples of 250 Hanwoo steers were collected from National Agricultural Cooperative Livestock Research Institute, Ansung, Gyeonggi province, Korea, between 2011 and 2012 and genotyped with the Affymetrix Bovine Axiom Array 640K single nucleotide polymorphism (SNP) chip. Among the SNPs in the chip, a total of 322,160 SNPs were chosen after quality control tests. After adjusting for the effects of age, slaughter-year-season, and polygenic effects using genome relationship matrix, the corrected phenotypes for the sensory evaluation measurements were regressed on each SNP using a simple linear regression additive based model. A total of 1,631 SNPs were detected for color, aroma, tenderness, juiciness and palatability at 0.1% comparison-wise level. Among the significant SNPs, the best set of 52 SNP markers were chosen using a forward regression procedure at 0.05 level, among which the sets of 8, 14, 11, 10, and 9 SNPs were determined for the respectively sensory evaluation traits. The sets of significant SNPs explained 18% to 31% of phenotypic variance. Three SNPs were pleiotropic, i.e. AX-26703353 and AX-26742891 that were located at 101 and 110 Mb of BTA6, respectively, influencing tenderness, juiciness and palatability, while AX-18624743 at 3 Mb of BTA10 affected tenderness and palatability. Our results suggest that some QTL for sensory measures are segregating in a Hanwoo steer population. Additional WGA studies on fatty acid and nutritional components as well as the sensory panels are in process to characterize genetic architecture of meat quality and palatability in Hanwoo.

Quantitative assessment of CD44 genetic variants and cancer susceptibility in Asians: a meta-analysis.

CD44 is a well-established cancer stem cell marker playing a crucial role in tumor metastasis, recurrence and chemo-resistance. Genetic variants of CD44 have been shown to be associated with susceptibility to various cancers; however, the results are confounding. Hence, we performed a meta-analysis to clarify these associations more accurately. Overall, rs13347 (T vs. C: OR=1.30, p=<0.004, pcorr=0.032; CT vs. CC: OR=1.29, p=0.015, pcorr=0.047; TT vs. CC: OR=1.77, p=<0.000, pcorr=0.018; CT+TT vs. CC: OR=1.34, p=<0.009, pcorr=0.041) and rs187115 (GG vs. AA: OR=2.34, p=<0.000, pcorr=0.025; AG vs. AA: OR=1.59, p=<0.000, pcorr=0.038; G vs. A allele OR=1.56, p=0.000, pcorr=0.05; AG+GG vs. AA: OR=1.63, p=<0.000, pcorr=0.013) polymorphisms were found to significantly increase the cancer risk in Asians. On the other hand, rs11821102 was found to confer low risk (A vs. G: OR=0.87, p=<0.027, pcorr=0.04; AG vs. GG: OR=0.85, p=<0.017, pcorr=0.01; AG+AA vs. GG: OR=0.86, p=<0.020, pcorr=0.02). Based on our analysis, we suggest significant role of CD44 variants (rs13347, rs187115 and rs11821102) in modulating individuals cancer susceptibility in Asians. Therefore, these variants may be used as predictive genetic biomarkers for cancer predisposition in Asian populations. However, more comprehensive studies involving other cancers and/or populations, haplotypes, gene-gene and gene-environment interactions are necessary to delineate the role of these variants in conferring cancer risk.

Alpha (1,2)-Fucosyltransferase M307A Polymorphism Improves Piglet Survival

To confirm the beneficial effects of alpha (1,2)-fucosyltransferase (FUT1) M307 A on piglet survival on commercial farms, we performed PCR-RFLP analysis of FUT1 M307 in successfully marketed (n = 245) and disease affected/deceased pigs during weaning (n = 252) at a commercial farm. We also evaluated the FUT1 genotypes of 190 healthy pigs from three different genetic backgrounds. The distribution of genotypes differed between the successfully marketed and disease affected/deceased pig groups. The frequency of the A allele, associated with resistance to edema and post-weaning diarrhea, was higher in the post-weaning survival group (0.21) than in the non-survival group (0.16, P < 0.05). The odds ratio for piglet survival between AA and GG genotypes was 1.98; thus, piglet survival for individuals with the AA genotype was almost two-fold greater than for GG individuals. The FUT1 gene polymorphism can be used as an effective marker for selection programs to improve post-weaning piglet survival.