Porcine single nucleotide polymorphisms and their functional effect: an update.

OBJECTIVE: To aid in the development of a comprehensive list of functional variants in the swine genome, single nucleotide polymorphisms (SNP) were identified from whole genome sequence of 240 pigs. Interim data from 72 animals in this study was published in 2017. This communication extends our previous work not only by utilizing genomic sequence from additional animals, but also by the use of the newly released Sscrofa 11.1 reference genome. RESULTS: A total of 26,850,263 high confidence SNP were identified, including 19,015,267 reported in our previously published results. Variation was detected in the coding sequence or untranslated regions (UTR) of 78% of the genes in the porcine genome: 1729 loss-of-function variants were predicted in 1162 genes, 12,686 genes contained 64,232 nonsynonymous variants, 250,403 variants were present in UTR of 15,739 genes, and 15,284 genes contained 90,939 synonymous variants. In total, approximately 316,000 SNP were classified as being of high to moderate impact (i.e. loss-of-function, nonsynonymous, or regulatory). These high to moderate impact SNP will be the focus of future genome-wide association studies.

A survey of single nucleotide polymorphisms identified from whole-genome sequencing and their functional effect in the porcine genome.

Genetic variants detected from sequence have been used to successfully identify causal variants and map complex traits in several organisms. High and moderate impact variants, those expected to alter or disrupt the protein coded by a gene and those that regulate protein production, likely have a more significant effect on phenotypic variation than do other types of genetic variants. Hence, a comprehensive list of these functional variants would be of considerable interest in swine genomic studies, particularly those targeting fertility and production traits. Whole-genome sequence was obtained from 72 of the founders of an intensely phenotyped experimental swine herd at the U.S. Meat Animal Research Center (USMARC). These animals included all 24 of the founding boars (12 Duroc and 12 Landrace) and 48 Yorkshire-Landrace composite sows. Sequence reads were mapped to the Sscrofa10.2 genome build, resulting in a mean of 6.1 fold (×) coverage per genome. A total of 22 342 915 high confidence SNPs were identified from the sequenced genomes. These included 21 million previously reported SNPs and 79% of the 62 163 SNPs on the PorcineSNP60 BeadChip assay. Variation was detected in the coding sequence or untranslated regions (UTRs) of 87.8% of the genes in the porcine genome: loss-of-function variants were predicted in 504 genes, 10 202 genes contained nonsynonymous variants, 10 773 had variation in UTRs and 13 010 genes contained synonymous variants. Approximately 139 000 SNPs were classified as loss-of-function, nonsynonymous or regulatory, which suggests that over 99% of the variation detected in our pigs could potentially be ignored, allowing us to focus on a much smaller number of functional SNPs during future analyses.

Litter-of-origin trait effects on gilt development.

The preweaning litter environment of gilts can affect subsequent development. In a recent experiment designed to test the effects of diet on gilt development, litter-of-origin traits including individual birth weights, immunocrits (a measure of colostrum intake), sow parity, number weaned, and individual weaning weights were collected for approximately 1,200 gilts that were progeny of approximately 300 sows. Subsequently, BW, LM area, and backfat were measured at 100 d of age and at 28-d intervals until slaughter (260 d of age). From 160 d of age to slaughter, gilts were observed daily for estrus. At slaughter, the reproductive tract and 1 mammary gland were recovered. The reproductive tract was classified as cyclic or prepubertal; the number of corpora lutea was counted. Uterine horn lengths and ovarian dimensions were measured. Uterus and ovary samples from every 10th gilt were prepared for histological evaluation of uterine gland development and follicle counts, respectively. Mammary gland tissue protein and fat were assayed. Day of the estrous cycle at slaughter was calculated using the first day of the most recent standing estrus (d 0) recorded previous to slaughter. Each gilt development trait was analyzed for association with each litter-of-origin trait, after adjusting for dietary treatment effects. Uterine length, ovarian dimensions, mammary gland protein and fat, and uterine gland development were also adjusted for day of the estrous cycle at slaughter. All litter-of-origin traits were associated ( < 0.05) with growth traits. Top-down (backward elimination) multiple regression analysis indicated that BW and LM accretion in gilts was positively associated with immunocrit ( < 0.01), birth weight ( < 0.01), preweaning growth rate ( < 0.01), and parity ( < 0.01). Backfat accretion was positively associated with preweaning growth rate ( < 0.01), number weaned ( < 0.05), and parity ( < 0.05). Age at puberty was associated with birth weight (positive; < 0.01) and preweaning growth rate (negative; < 0.01). Total uterine length was positively associated with only birth weights ( < 0.05). Mammary gland protein was negatively associated with preweaning growth ( < 0.01). Mammary gland fat was positively associated with birth weight and number of piglets weaned ( > 0.05). These results indicate that colostrum consumption, birth weights, preweaning growth rate, number weaned, and parity are associated with gilt development traits during later life.

Plasma concentrations of acyl-ghrelin are associated with average daily gain and feeding behavior in grow-finish pigs.

The objectives of this study were to determine the effect of sex, sire line, and litter size on concentrations of acyl-ghrelin and total ghrelin in plasma of grow-finish pigs and to understand the relationship of plasma concentrations of ghrelin with feeding behavior, average daily gain (ADG), and back fat in grow-finish swine. Yorkshire-Landrace crossbred dams were inseminated with semen from Yorkshire, Landrace, or Duroc sires. Within 24 h of birth, pigs were cross-fostered into litter sizes of normal (N; >12 pigs/litter) or small (S; ≤ 9 pigs/litter). At 8 wk of age, pigs (n = 240) were blocked by sire breed, sex, and litter size and assigned to pens (n = 6) containing commercial feeders modified with a system to monitor feeding behavior. Total time eating, number of daily meals, and duration of meals were recorded for each individual pig. Body weight was recorded every 4 wk. Back fat and loin eye area were recorded at the conclusion of the 12-wk feeding study. A blood sample was collected at week 7 of the study to quantify concentrations of acyl- and total ghrelin in plasma. Pigs from small litters weighed more (P < 0.05) and tended (P = 0.07) to be fatter than pigs from normal litters. Postnatal litter size did not affect ADG, feeding behavior, or concentrations of ghrelin in plasma during the grow-finish phase. Barrows spent more time eating (P < 0.001) than gilts, but the number of meals and concentrations of ghrelin did not differ with sex of the pig. Pigs from Duroc and Yorkshire sires had lesser (P < 0.0001) concentrations of acyl-ghrelin than pigs from Landrace sires, but plasma concentrations of total ghrelin were not affected by sire breed. Concentrations of acyl-ghrelin were positively correlated with the number of meals and negatively correlated with meal length and ADG (P < 0.05). A larger number of short-duration meals may indicate that pigs with greater concentrations of acyl-ghrelin consumed less total feed, which likely explains why they were leaner and grew more slowly. Acyl-ghrelin is involved in regulating feeding behavior in pigs, and measuring acyl-ghrelin is important when trying to understand the role of this hormone in swine physiology.

Meta-analysis of genome-wide association from genomic prediction models.

Genome-wide association (GWA) studies based on GBLUP models are a common practice in animal breeding. However, effect sizes of GWA tests are small, requiring larger sample sizes to enhance power of detection of rare variants. Because of difficulties in increasing sample size in animal populations, one alternative is to implement a meta-analysis (MA), combining information and results from independent GWA studies. Although this methodology has been used widely in human genetics, implementation in animal breeding has been limited. Thus, we present methods to implement a MA of GWA, describing the proper approach to compute weights derived from multiple genomic evaluations based on animal-centric GBLUP models. Application to real datasets shows that MA increases power of detection of associations in comparison with population-level GWA, allowing for population structure and heterogeneity of variance components across populations to be accounted for. Another advantage of MA is that it does not require access to genotype data that is required for a joint analysis. Scripts related to the implementation of this approach, which consider the strength of association as well as the sign, are distributed and thus account for heterogeneity in association phase between QTL and SNPs. Thus, MA of GWA is an attractive alternative to summarizing results from multiple genomic studies, avoiding restrictions with genotype data sharing, definition of fixed effects and different scales of measurement of evaluated traits.

Implementing meta-analysis from genome-wide association studies for pork quality traits.

Pork quality plays an important role in the meat processing industry. Thus, different methodologies have been implemented to elucidate the genetic architecture of traits affecting meat quality. One of the most common and widely used approaches is to perform genome-wide association (GWA) studies. However, a limitation of many GWA in animal breeding is the limited power due to small sample sizes in animal populations. One alternative is to implement a meta-analysis of GWA (MA-GWA) combining results from independent association studies. The objective of this study was to identify significant genomic regions associated with meat quality traits by performing MA-GWA for 8 different traits in 3 independent pig populations. Results from MA-GWA were used to search for genes possibly associated with the set of evaluated traits. Data from 3 pig data sets (U.S. Meat Animal Research Center, commercial, and Michigan State University Pig Resource Population) were used. A MA was implemented by combining -scores derived for each SNP in every population and then weighting them using the inverse of estimated variance of SNP effects. A search for annotated genes retrieved genes previously reported as candidates for shear force (calpain-1 catalytic subunit [] and calpastatin []), as well as for ultimate pH, purge loss, and cook loss (protein kinase, AMP-activated, γ 3 noncatalytic subunit []). In addition, novel candidate genes were identified for intramuscular fat and cook loss (acyl-CoA synthetase family member 3 mitochondrial []) and for the objective measure of muscle redness, CIE a* (glycogen synthase 1, muscle [] and ferritin, light polypeptide []). Thus, implementation of MA-GWA allowed integration of results for economically relevant traits and identified novel genes to be tested as candidates for meat quality traits in pig populations.

Age at puberty, ovulation rate, and uterine length of developing gilts fed two lysine and three metabolizable energy concentrations from 100 to 260 d of age.

The objective of this study was to determine the effect of ad libitum feeding diets differing in standard ileal digestible (SID) lysine and ME concentrations that bracket those fed to developing gilts in U.S. commercial settings. Average SID lysine and ME concentrations in diets currently fed to developing gilts were obtained from a poll of the U.S. commercial swine industry. Crossbred Large White × Landrace gilts (n = 1,221), housed in groups, were randomly allotted to 6 corn-soybean diets in a 2 × 3 factorial arrangement formulated to provided 2 SID lysine and 3 ME concentrations. Gilts received grower diets formulated to provide 1.02% (control = survey average) or 0.86% (control minus 15%) SID lysine and 2.94, 3.25, or 3.57 (survey average ME ± 10%) Mcal of ME/kg from 100 d of age until approximately 90 kg BW. Then, gilts were fed finisher diet containing 0.85% (control = survey average) or 0.73% (control minus 15%) SID lysine and 2.94, 3.26, or 3.59 (control ± 10%) Mcal of ME/kg until 260 d of age. Gilts were weighed, and backfat thickness and loin muscle area were recorded at the beginning of the trial and then every 28 d. Starting at 160 d of age, gilts were exposed daily to vasectomized boars and observed for behavioral estrus. At approximately 260 d of age, gilts were slaughtered and their reproductive tract was collected. Each reproductive tract was examined to determine whether the gilt was cyclic, the stage of estrus cycle, ovulation rate, and uterine length. Data were evaluated for normality and analyzed using mixed model methods. Average age at puberty was 193 d of age with a range from 160 to 265 d. When all gilts on trial at 160 d of age were included in the analysis, 91.0% reached puberty as determine by observation of standing estrus. Differences between dietary treatments on age at puberty or measurements of the reproductive tract were not detected. Growth rates to 160 d were not limiting for attainment of puberty in response to daily boar stimulation from 160 d.

Genomewide association analysis for average birth interval and stillbirth in swine.

Reproductive efficiency has a great impact on the economic success of pork production. Stillborn pigs and average birth interval contribute to the number of pigs born alive in a litter. To better understand the underlying genetics of these traits, a genomewide association study was undertaken. Samples of DNA were collected and tested using the Illumina Porcine SNP60 BeadChip from 798 females farrowing over a 4-yr period (all first parity). Birth intervals and piglet birth status (stillborn or alive) were determined by videotaping each farrowing event. A total of 41,148 SNP were tested using the Bayes C option of GenSel (version 4.61) and 1-Mb windows. These 1-Mb windows explained proportions of 0.017, 0.002, 0.032, 0.029, and 0.030 of the total variation, respectively, for litter average birth interval after deletion of the last piglet born, last birth interval in the litter, number of stillborn piglets ignoring the last piglet born, number of stillborns in the last birth position, and percent stillborn ignoring the last piglet. Significant 1-Mb nonoverlapping SNP windows were identified by using a conservative approach requiring 1-Mb windows to have a genetic variance ≥1.0% of genomic variance and these were considered to be QTL. Quantitative trait loci were located for number of stillborn piglets ignoring the last piglet born (1 QTL), number of stillborns in the last birth position (1 QTL), and percent stillborn ignoring the last piglet (3 QTL). In addition, 2, 13, 3, and 6 suggestive 1-Mb nonoverlapping SNP windows were identified for litter average birth interval after deletion of the last piglet born, number of stillborn piglets ignoring the last piglet born, number of stillborns in the last birth position, and percent stillborn ignoring the last piglet, respectively. Possible candidate genes affecting both birth interval and stillbirth included () and (). Possible genes affecting only birth interval included (), and (), and those affecting only stillbirth included (), LOC100518697 (a nostrin-like gene), and (). The QTL and the suggestive 1-Mb nonoverlapping SNP windows may lead to genetic markers for marker assisted selection, marker assisted management, or genomic selection applications in commercial pig populations.

Genomewide association and identification of candidate genes for ovulation rate in swine.

Reproductive efficiency has a great impact on the economic success of pork production. Ovulation rate is an early component of reproduction efficiency and contributes to the number of pigs born in a litter. To better understand the underlying genetics of ovulation rate, a genomewide association study was undertaken. Samples of DNA were collected and tested using the Illumina Porcine SNP60 BeadChip from 1,180 females with ovulation measurements ranging from never farrowed to measurements taken after parity 2. A total of 41,848 SNP were tested using the Bayes C option of GenSel. After the Bayes C analysis, SNP were assigned to sliding windows of 5 consecutive SNP by chromosome-position order beginning with the first 5 SNP on SSC1 and ending with the last 5 SNP on SSCX. The 5-SNP windows were analyzed using the Predict option of GenSel. From the Predict analysis, putative QTL were selected having no overlap with other 5-SNP window groups, no overlap across chromosomes, and the highest genetic variation. These putative QTL were submitted to statistical testing using the bootstrap option of GenSel. Of the putative QTL tested, 80 were found to be statistically significant (P < 0.01). Ten QTL were found on SSC1, 12 on SSC2, 4 on SSC3, 8 on SSC4, 3 on SSC5, 3 on SSC6, 3 on SSC7, 4 on SSC8, 2 on SSC9, 4 on SSC10, 1 on SSC12, 4 on SSC13, 2 on SSC14, 4 on SSC15, 4 on SSC16, 6 on SSC17, 4 on SSC18, and 1 on SSCX. Sixteen QTL were found to be statistically significant at the P < 0.001 level. Six additional QTL were significant at the P = 0.001 level. These 22 QTL accounted for 71.10% of the total genetic variance. The most compelling candidate genes in these regions include Estrogen receptor 1, growth differentiation factor 9, and inhibin ßA. These QTL, when combined with information on genes found in the same regions, should provide useful information that could be used for marker assisted selection, marker assisted management, or genomic selection applications in commercial pig populations.

Identifying genetic loci controlling neonatal passive transfer of immunity using a hybrid genotyping strategy.

Colostrum intake is critical to a piglet's survival and can be measured by precipitating out the γ-immunoglobulins from serum with ammonium sulfate (immunocrit). Genetic analysis of immunocrits on 5312 piglets indicated that the heritabilities (se) for direct and maternal effects were 0.13 (0.06) and 0.53 (0.08) respectively. To identify QTL for direct genetic effects, piglets with the highest and lowest immunocrits from 470 litters were selected. Six sets of DNA pools were created based on sire of the litter. These 12 DNA pools were applied to Illumina Porcine SNP60 BeadChips. Normalized X and Y values were analyzed. Three different SNP selection methods were used: deviation of the mean from high vs. low pools, the deviation adjusted for variance based on binomial theory and ANOVA. The 25 highest ranking SNPs were selected from each evaluation for further study along with 12 regions selected based on a five-SNP window approach. Selected SNPs were individually genotyped in the 988 piglets included in pools as well as in 524 piglets that had intermediate immunocrits. Association analyses were conducted fitting an animal model using the estimated genetic parameters. Nineteen SNPs were nominally associated (P < 0.01) with immunocrit values, of which nine remained significant (P < 0.05) after Bonferroni correction, located in 16 genomic regions on 13 chromosomes. In conclusion, the pooling strategy reduced the cost to scan the genome by more than 80% and identified genomic regions associated with a piglet's ability to acquire γ-immunoglobulin from colostrum. Each method to rank SNPs from the pooled analyses contributed unique validated markers, suggesting that multiple analyses will reveal more QTL than a single analysis.

Genome-wide association of meat quality traits and tenderness in swine.

Pork quality has a large impact on consumer preference and perception of eating quality. A genome-wide association was performed for pork quality traits [intramuscular fat (IMF)], slice shear force (SSF), color attributes, purge, cooking loss, and pH] from 531 to 1,237 records on barrows and gilts of a Landrace-Duroc-Yorkshire population using the Illumina PorcineSNP60 BeadChip. Associations were detected using MTDFREML for all traits. Intramuscular fat had the greatest number of SNP associations, followed by pH, purge, cooking loss, shear force, and color. Two regions contained associations for multiple traits; one on SSC1 at 255 Mb near calcineurin subunit B (PPP3R2) was associated with SSF, moisture loss, and pH, and one on SSC6 from 28 to 29.5 Mb for purge and IMF containing the candidate genes glucose-6-phosphate isomerase (GPI) and KCTD15. Some of the other compelling candidate genes in regions associated with meat quality include CEBPA, SNAI1, and FAM132A for IMF, CAPN1 for SSF, GLUL for pH, and PRKAG3 and ITGB1 with cooking loss.

Association of single nucleotide polymorphism (SNP) markers in candidate genes and QTL regions with pork quality traits in commercial pigs.

Numerous reports have described genetic markers or genomic regions (QTL) associated with pork quality and/or palatability but few validation studies have been reported. Therefore, 156 SNP markers from 45 candidate genes and eight QTL regions were analyzed for association with pork quality and palatability traits from 888 pork loins. Loins were collected at three slaughter facilities and selected to represent a wide range of pork color, pH and marbling. Phenotypic data recorded included objective and subjective measures of color and marbling, purge loss, shear force, and cooking loss. Data were analyzed with SAS PROC MIXED where loin was fit as a random effect. Results indicated some of the markers tested should be useful in industry, while others are not segregating in all populations or linkage disequilibrium between markers and causative genetic variation fluctuates among populations limiting their universal utility. Genes with the largest effects on pork quality were MC4R, IGF2, CAST and PRKAG3.

Genome-wide association study of swine farrowing traits. Part I: genetic and genomic parameter estimates.

The primary objective of this study was to determine genetic and genomic parameters among swine (Sus scrofa) farrowing traits. Genetic parameters were obtained using MTDFREML. Genomic parameters were obtained using GENSEL. Genetic and residual variances obtained from MTDFREML were used as priors for the Bayes C analysis of GENSEL. Farrowing traits included total number born (TNB), number born alive (NBA), number born dead (NBD), number stillborn (NSB), number of mummies (MUM), litter birth weight (LBW), and average piglet birth weight (ABW). Statistically significant heritabilities included TNB (0.09, P = 0.048), NBA (0.09, P = 0.041), LBW (0.20, P = 0.002), and ABW (0.26, P < 0.0001). Statistically significant genetic correlations included TNB-NBA (0.97, P < 0.0001), TNB-LBW (0.74, P < 0.0001), NBA-LBW (0.56, P < 0.0017), NSB-LBW (0.87, P < 0.0395), and LBW-ABW (0.63, P < 0.0002). Genetic parameters are similar to others found in the literature. The proportion of phenotypic variance explained by genomic markers (GP) generated by GENSEL was TNB (0.04), NBA (0.06), NBD (0.00), NSB (0.01), MUM (0.00), LBW (0.11), and ABW (0.31). Limited information is available in the literature about genomic parameters. Only the GP estimate for NSB is significantly lower than what has been published. The GP estimate for ABW is greater than the estimate for heritability found in this study. Other traits with significant heritability had GP estimates half the value of heritability. This research indicates that significant genetic markers will be found for TNB, NBA, LBW, and ABW that will have either immediate use in industry or provide a roadmap to further research with fine mapping or sequencing of areas of significance. Furthermore, these results indicate that genomic selection implemented at an early age would have similar annual progress as traditional selection, and could be incorporated along with traditional selection procedures to improve genetic progress of litter traits.

Genome-wide association study of swine farrowing traits. Part II: Bayesian analysis of marker data.

Reproductive efficiency has a great impact on the economic success of pork (sus scrofa) production. Number born alive (NBA) and average piglet birth weight (ABW) contribute greatly to reproductive efficiency. To better understand the underlying genetics of birth traits, a genome-wide association study (GWAS) was undertaken. Samples of DNA were collected and tested using the Illumina PorcineSNP60 BeadChip from 1,152 first parity gilts. Traits included total number born (TNB), NBA, number born dead (NBD), number stillborn (NSB), number of mummies (MUM), total litter birth weight (LBW), and ABW. A total of 41,151 SNP were tested using a Bayesian approach. Beginning with the first 5 SNP on SSC1 and ending with the last 5 SNP on the SSCX, SNP were assigned to groups of 5 consecutive SNP by chromosome-position order and analyzed again using a Bayesian approach. From that analysis, 5-SNP groups were selected having no overlap with another 5-SNP groups and no overlap across chromosomes. These selected 5-SNP non-overlapping groups were defined as QTL. Of the available 8,814 QTL, 124 were found to be statistically significant (P < 0.01). Multiple testing was considered using the probability of false positives. Eleven QTL were found for TNB, 3 on SSC1, 3 on SSC4, 1 on SSC13, 1 on SSC14, 2 on SSC15, and 1 on SSC17. Statistical testing for NBA identified 14 QTL, 4 on SSC1, 1 on SSC4, 1 on SSC6, 1 on SSC10, 1on SSC13, 3 on SSC15, and 3 on SSC17. A single NBD QTL was found on SSC11. No QTL were identified for NSB or MUM. Thirty-three QTL were found for LBW, 3 on SSC1, 1 on SSC2, 1 on SSC3, 5 on SSC4, 2 on SSC5, 5 on SSC6, 3 on SSC7, 2 on SSC9, 1 on SSC10, 2 on SSC14, 6 on SSC15, and 2 on SSC17. A total of 65 QTL were found for ABW, 9 on SSC1, 3 on SSC2, 9 on SSC5, 5 on SSC6, 1 on SSC7, 2 on SSC8, 2 on SSC9, 3 on SSC10, 1 on SSC11, 3 on SSC12, 2 on SSC13, 8 on SSC14, 8 on SSC15, 1 on SSC17, and 8 on SSC18. Several candidate genes have been identified that overlap QTL locations among TNB, NBA, NBD, and ABW. These QTL when combined with information on genes found in the same regions should provide useful information that could be used for marker assisted selection, marker assisted management, or genomic selection applications in commercial pig populations.

Four genes located on a SSC2 meat quality QTL region are associated with different meat quality traits in Landrace × Chinese-European crossbred population.

Several quantitative trait loci (QTL) for different meat quality traits have been localized on the q arm of porcine chromosome 2 at position 55-78 cM. Association analyses were performed in a commercial Landrace × Chinese-European (LCE) crossbred population (n = 446) slaughtered at approximately 127 kg and an average age of 198 days with records for performance (growth, fat and meat accretion) and meat quality [intramuscular fat (IMF), Minolta L*, Minolta a*, Minolta b* and pH at 45 m]. Polymorphisms within positional candidate genes cloned from homologous regions on human chromosome 19, ubiquitin-like 5 (UBL5- AM950288:g.566G>A), resistin (RETN- AM157180:g.1473A>G causing substitution p.Ala36Thr), insulin receptor (INSR- AM950289:g.589T>C) and complement factor D (adipsin) (CFD- AM950287:g. 306C>T) were located at positions 62.1, 64.0, 68.0 and 70.7 cM respectively on the current USDA USMARC map of porcine chromosome 2 and had the following allele frequencies in the LCE: UBL5 566G - 0.57; RETN 1473G - 0.84; INSR 589C - 0.70; and CFD 306C - 0.73. The effects of alleles within the candidate genes on the recorded traits were estimated using an animal model. Significant effects (P < 0.05) were found for pH(45) in m. semimembranosus (m. sm.) (UBL5), IMF (RETN) and Minolta L* (RETN, CFD). Differences between phenotypic means of homozygotes at UBL5, RETN and either RETN or CFD explained 0.34 SD for pH(45) in m. sm., 0.47 SD for IMF and 0.68 SD for Minolta L* respectively. Suggestive effects (P < 0.10) on IMF (UBL5, CFD), Minolta a* (INSR, CFD) and Minolta b* (INSR) were also observed. Our results support the localization of further QTL for meat quality traits in this region and suggest that there are several genes affecting different meat quality traits.

Validation and fine mapping of a QTL for ovulation rate on swine chromosome 3.

Ovulation rate (OR) is an important component of litter size, but mutation(s) in gene(s) underlying OR QTL have yet to be identified in pigs. Markers within an OR QTL on SSC3 were genotyped in three white composite lines selected for ten generations for increased OR or uterine capacity (UC), with one line being an unselected control. Numbers of corpora lutea (CL) and UC (number of fully formed fetuses) were collected at approximately 105 days of gestation, as well as ovary weight (OW), uterine length (UL) and uterine weight (UW) measurements at 160 d of age in generation 12 and 13 females from all three lines. Six microsatellites and ten single nucleotide polymorphisms (SNPs; 0-42 cM) were genotyped in pigs from all lines of generations 11 through 13. The allele frequencies of 24269.1, SW2429, 7907.2 and 7637.2 were different (P < 0.01) in the OR line compared to the control line. A significant (P < 0.05) association of CL with 24269.1 (additive effect 0.65 ± 0.32) was detected, and additive genotypic effects approached significance for markers at 28 through 35 cM (16963.2, 27514.1 and SWR1637). Haplotyping of 7637.2 and 16963.2 (31 through 32 cM) identified a significant additive association of haplotype 1 with CL (-0.62 ± 0.30). These markers were also associated with OW (24296.1 and SWR1637), UL (16963.2, 27514.1 and haplotypes of 7637.2/16963.2) and UW (haplotypes of 7637.2/16963.2). This study verifies an OR QTL on SSC3. However, based on the data, it was concluded that there may be two genes, at 13 through 18 cM and 28 through 35 cM, controlling OR on SSC3p.

Plenary contribution to International Conference on Boar Semen Preservation 2011. Genetic selection for freezability and its controversy with selection for performance.

Little data are available in the literature regarding freezability of boar sperm or its relationship with other traits. Existing data suggest the trait would respond favourably to selection, and information is available from other species suggesting components that might have changed. Genetic parameters are estimated for boar sperm freezability including heritability and correlations with other production traits. Sperm freezability is an ideal candidate for marker assisted-selection or selection for favourable alleles.

Genetic parameter estimates among scale activity score and farrowing disposition with reproductive traits in swine.

The primary objective of this study was to determine if certain behavior traits were genetically correlated with reproduction. If 1 or both of the behavior traits were found to be correlated, a secondary objective was to determine if the behavior traits could be useful in selecting for more productive females. A scale activity score taken at 5 mo of age and a farrowing disposition score taken at farrowing were selected as the behavioral traits. Scale activity score ranged from 1 to 5 and farrowing disposition ranged from 1 to 3. Reproductive traits included age at puberty, number born alive, number born dead, litter birth weight, average piglet birth weight, number weaned, litter weaning weight, average weaning weight, wean-to-estrus interval, ovulation rate including gilts, and postweaning ovulation rate. Genetic correlations between scale activity score and reproduction ranged from -0.79 to 0.61. Three of the correlations, number born alive (P < 0.01), average piglet birth weight (P < 0.001), and wean-to-estrus interval (P = 0.014), were statistically significant but included both favorable and antagonistic correlations. In contrast, all but 1 of the farrowing disposition correlations was favorable and ranged from -0.66 to 0.67. Although only the correlation with litter birth weight was significant (P = 0.018), the consistent favorable direction of all farrowing disposition correlations, except average weaning weight, shows a potential for inclusion of farrowing disposition into a selection program.

Predictive markers in calpastatin for tenderness in commercial pig populations.

The identification of predictive DNA markers for pork quality would allow US pork producers and breeders to select genetically superior animals more quickly and efficiently for the production of consistent, high-quality meat. Genome scans have identified QTL for tenderness on SSC 2, which have been fine-mapped to the calpastatin locus. The objectives of this study were to identify the sequence variation in calpastatin that likely affects tenderness in commercial-level pig populations and to develop definitive DNA markers that are predictive of pork tenderness for use in marker-assisted selection programs. We resequenced the calpastatin regulatory and transcribed regions in pigs with divergently extreme shear force values to identify possible mutations that could affect tenderness. A total of 194 SNP were identified in this sequence, and 31 SNP were found in predicted transcription factor binding sites. We tested 131 polymorphisms in our research population and a subset (40) of these in samples of industry pigs for their association with objective measures of tenderness. We identified 4 SNP that were consistently associated with pork tenderness in all the populations studied, representing 2,826 pigs from 4 distinct populations. Gel shift assays were designed for these SNP and 12 other polymorphic sites. Six sites demonstrated a gel shift when probes were incubated with nuclear extract from muscle, heart, or testis. Four of these sites, a specificity protein 1 (Sp1) site around nucleotides 12978 and 12979, a potential thyrotroph embryonic factor (Tef) site at nucleotide 25587, an unknown site at nucleotide 48699, and myocyte enhancer factor-2 (Mef-2)/TATA sites with SNP at positions 49223 and 49228 were allele specific in binding nuclear proteins. The allele frequencies for the tender alleles were similar (0.11 to 0.36) in the 4 different commercial populations. These 4 SNP were not in complete linkage disequilibrium with each other and may independently affect calpastatin expression, tenderness, or both. These markers should be predictive of pork tenderness in industry populations.