Genetic correlations between lean growth and litter traits in U.S. Yorkshire, Duroc, Hampshire, and Landrace pigs

Genetic parameter estimation for pork production and litter performance traits of Landrace, Large White, and Duroc pigs in Japan

We estimated genetic parameters for two pork production and six litter performance traits of Landrace, Large White, and Duroc pigs reared in Japan. Pork production traits were average daily gain from birth to end of performance testing and backfat thickness at end of testing (46,042 records for Landrace, 40,467 records for Large White, and 42,920 records for Duroc). Litter performance traits were number born alive, litter size at weaning (LSW), number of piglets dead during suckling (ND), survival rate of piglets during suckling (SV), total piglet weight at weaning (TWW), and average piglet weight at weaning (AWW) (27,410, 26,716, and 12,430 records for Landrace, Large White, and Duroc, respectively). ND was calculated as the difference between LSW and litter size at start of suckling (LSS). SV was calculated as LSW/LSS. AWW was calculated as TWW/LSW. Pedigree data for Landrace, Large White, and Duroc breeds contained 50,193, 44,077, and 45,336 pigs, respectively. Trait heritability was estimated via single-trait analysis and genetic correlation between two traits was estimated via two-trait analysis. When considering the linear covariate of LSS in the statistical model for LSW and TWW, for all breeds, the heritability was estimated to be 0.4-0.5 for pork production traits and below 0.2 for litter performance traits. Estimated genetic correlation between average daily gain and backfat thickness was small, ranging from 0.057 to 0.112, and those between pork production traits and litter performance traits were negligible to moderate, ranging from -0.493 to 0.487. A wide range of genetic correlation values among the litter performance traits was estimated, while that between LSW and ND could not be obtained. The results of genetic parameter estimation were affected by whether the linear covariate of LSS was included in the statistical model for LSW and TWW or not. This finding implies the necessity of carefully interpreting the results according to the choice of statistical model. Our results could give fundamental information on simultaneously improving productivity and female reproductivity for pigs.

Identification of circRNAs Associated with Adipogenesis Based on RNA-seq Data in Pigs

Adipocytes or fat cells play a vital role in the storage and release of energy in pigs, and many circular RNAs (circRNAs) have emerged as important regulators in various tissues and cell types in pigs. However, the spatio-temporal expression pattern of circRNAs between different adipose deposition breeds remains elusive. In this study, RNA sequencing (RNA-seq) produced transcriptome profiles of Western Landrace (lean-type) and Chinese Songliao black pigs (obese-type) with different thicknesses of subcutaneous fat tissues and were used to identify circRNAs involved in the regulation of adipogenesis. Gene expression analysis revealed 883 circRNAs, among which 26 and 11 circRNAs were differentially expressed between Landrace vs. Songliao pigs and high- vs. low-thickness groups, respectively. We also analyzed the interaction between circRNAs and microRNAs (miRNAs) and constructed their interaction network in adipogenesis; gene ontology classification and pathway analysis revealed two vital circRNAs, with the majority of their target genes enriched in biological functions such as fatty acids biosynthesis, fatty acid metabolism, and Wnt/TGF-β signaling pathways. These candidate circRNAs can be taken as potential targets for further experimental studies. Our results show that circRNAs are dynamically expressed and provide a valuable basis for understanding the molecular mechanism of circRNAs in pig adipose biology.

Comparison of long non-coding RNAs in adipose and muscle tissues between seven indigenous Chinese and the Yorkshire pig breeds

lncRNAs play crucial roles in fat metabolism in animals. Previously, we have compared the mRNA transcriptome profiles between seven fat-type Chinese pig breeds and one lean-type Western breed (Yorkshire, YY). The associations between differentially expressed (DE) genes and phenotypical traits were investigated. In the present study, to further explore the underlying regulatory mechanisms, lncRNAs were sequenced and compared between YY and Chinese indigenous breeds. The results showed 9114 and 7538 DE lncRNAs between at least one Chinese breed and the YY breed in the adipose and muscle tissue respectively. KEGG enrichment analysis revealed that the target genes of these DE lncRNAs mainly influenced the glucolipid metabolism, which is an important process affecting meat quality. Correlation analyses between the DE lncRNA and DE mRNA genes related to meat quality and growth traits were performed. The results showed that LTCONS_00073280 was associated with intramuscular fat content. Four lncRNAs (LTCONS_00101781, LTCONS_00037879, LTCONS_00088260 and LTCONS-00128343) might mediate backfat thickness. Overall, this study provides candidate lncRNAs that potentially affect meat quality, which might be useful for molecular breeding of pig breeds in future.

Whole-genome resequencing analysis of 20 Micro-pigs

BACKGROUND

Miniature pigs have been increasingly used as mammalian model animals for biomedical research because of their similarity to human beings in terms of their metabolic features and proportional organ sizes. However, despite their importance, there is a severe lack of genome-wide studies on miniature pigs.

OBJECTIVE

In this study, we performed whole-genome sequencing analysis of 20 Micro-pigs obtained from Medi Kinetics to elucidate their genomic characteristics.

RESULTS

Approximately 595 gigabase pairs (Gb) of sequence reads were generated to be mapped to the swine reference genome assembly (Sus scrofa 10.2); on average, the sequence reads covered 99.15% of the reference genome at an average of 9.6-fold coverage. We detected a total of 19,518,548 SNPs, of which 8.7% were found to be novel. With further annotation of all of the SNPs, we retrieved 144,507 nonsynonymous SNPs (nsSNPs); of these, 5968 were found in all 20 individuals used in this study. SIFT prediction for these SNPs identified that 812 nsSNPs in 402 genes were deleterious. Among these 402 genes, we identified some genes that could potentially affect traits of interest in Micro-pigs, such as RHEB and FRAS1. Furthermore, we performed runs of homozygosity analysis to locate potential selection signatures in the genome, detecting several loci that might be involved in phenotypic characteristics in Micro-pigs, such as MSTN, GDF5, and GDF11.

CONCLUSION

In this study, we identified numerous nsSNPs that could be used as candidate genetic markers with involvement in traits of interest. Furthermore, we detected putative selection footprints that might be associated with recent selection applied to miniature pigs.

Duroc boars have lower progeny mortality and lower fertility than Pietrain boars

In pig production, Pietrain and Duroc lines are often used as terminal sire lines to produce crossbred slaughter pigs. The objective of this study was to identify the differences in paternal fertility and mortality during the suckling period of crossbred progeny from Pietrain and Duroc terminal sire lines. In total, 87 purebred Duroc boars and 68 purebred Pietrain boars were used as terminal sires to produce 1,823 crossbred Duroc litters (D-litters) and 1,705 crossbred Pietrain litters (P-litters) in two production herds. The sows were crosses between DanBred Landrace and Yorkshire (F1). All boars were kept at the same artificial insemination (AI) station, and all semen doses were produced in the same laboratory. The experiment was balanced according to herd, boars, and time, with approximately 13 sows from each herd mated to each boar within each breed. The results showed higher fertility expressed as litter size at birth in P-litters compared with D-litters led to 0.5 higher total number born (TNB) for P-litters (P = 0.0076). However, piglet mortality including number of stillborn piglets was lower in D-litters compared with P-litters (P < 0.0001), and 5 d after farrowing, the average litter size in P-litters ranged 0.4 below the litter size in D-litters (P < 0.027). At 21 d after birth, mean litter size in P- and D-litters were 14.5 and 14.9 piglets per litter, respectively (P < 0.015). This indicated that Pietrain progenies were weaker than Duroc progenies, and it was concluded that use of Duroc boars as the terminal sire line led to lower piglet mortality. In the two herds, the mean piglet mortality rate including still born piglets ranged from 19.5% to 23.6% and from 17.6% to 19.1% in P- and D-litters, respectively.

Integrated mRNA and miRNA profile expression in livers of Jinhua and Landrace pigs

Objective

To explore the molecular mechanisms of fat metabolism and deposition in pigs, an experiment was conducted to identify hepatic mRNAs and miRNAs expression and determine the potential interaction of them in two phenotypically extreme pig breeds.

Methods

mRNA and miRNA profiling of liver from 70-day Jinhua (JH) and Landrace (LD) pigs were performed using RNA sequencing. Blood samples were taken to detect results of serum biochemistry. Bioinformatics analysis were applied to construct differentially expressed miRNA-mRNA network.

Results

Serum total triiodothyronine and total thyroxine were significantly lower in Jinhua pigs, but the content of serum total cholesterol (TCH) and low-density lipoprotein cholesterol were strikingly higher. A total of 467 differentially expressed genes (DEGs) and 35 differentially expressed miRNAs (DE miRNAs) were identified between JH and LD groups. Gene ontology analysis suggested that DEGs were involved in oxidation-reduction, lipid biosynthetic and lipid metabolism process. Interaction network of DEGs and DE miRNAs were constructed, according to target prediction results.

Conclusion

We generated transcriptome and miRNAome profiles of liver from JH and LD pig breeds which represent distinguishing phenotypes of growth and metabolism. The potential miRNA-mRNA interaction networks may provide a comprehensive understanding in the mechanism of lipid metabolism. These results serve as a basis for further investigation on biological functions of miRNAs in the porcine liver.

Estimation of the effects of selection on French Large White sow and piglet performance during the suckling period

The effects of 21 yr of selection were estimated for sow and piglet performance during the suckling period in a French Large White (LW) pig population using frozen semen. Two experimental groups (EXP = L77 and L98) were produced by inseminating LW sows with either stored frozen semen from 17 LW boars born in 1977 (EXP = L77) or with fresh semen from 23 LW boars born in 1998 (EXP = L98). Seventy-four L77 and 89 L98 randomly chosen females were mated to 15 L77 and 15 L98, respectively, randomly chosen boars for 6 successive parities. They produced 2,796 L77 progeny (G77) and 3,529 L98 progeny (G98) piglets including stillbirths. To disentangle direct and maternal effects on piglet growth, a 2 × 2 factorial design was set by cross-fostering half-litters across genetic groups the day after farrowing, resulting in mixed G77/G98 litters nursed by either L77 or L98 sows. Piglet traits investigated included individual weight at birth (IWB), at 21 d of age (IW21d), and at weaning at 4 wk of age (IWW) and ADG from birth to 21 d of age (ADG21d) and from birth to weaning (ADGBW) as well as probability of stillbirth, probability of mortality on the first day after farrowing and from d 2 to weaning. Sow traits analyzed included weight before farrowing and at weaning, feed intake, milk production, colostrum, and milk composition. The variability of performance across genetic groups and litters was also investigated. The data were analyzed using generalized (piglet mortality) or linear mixed models (other traits). Results showed an increase in IWB (+240 ± 72 g in 21 yr for IWB adjusted for total number born), and a negative maternal genetic trend was observed on piglet growth during the suckling period (e.g., +33 ± 13 g/d in 21 yr for ADG21d, that is, 14% of the mean), whereas direct genetic effects remained unchanged. Piglets from L98 litters also had a 40% larger probability of being stillborn and a 28% larger probability of dying on d 1 and had a more heterogeneous IWB (358 vs. 336 g; < 0.001) and growth during the suckling period (60 vs. 56 g/d; < 0.001). Sows from L77 and L98 experimental groups did not differ in weight, feed intake, colostrum, and milk composition. These results give evidence of negative correlated effects of selection for piglet traits related to robustness. These adverse effects are at least partly of maternal origin.

Circular RNA expression profiles in the porcine liver of two distinct phenotype pig breeds

Objective

An experiment was conducted to identify and characterize the circular RNA expression and metabolic characteristics in the liver of Jinhua pigs and Landrace pigs.

Methods

Three Jinhua pigs and three Landrace pigs respectively at 70-day were slaughtered to collect the liver tissue samples. Immediately after slaughter, blood samples were taken to detect serum biochemical indicators. Total RNA extracted from liver tissue samples were used to prepare the library and then sequence on HiSeq 2500. Bioinformatic methods were employed to analyze sequence data to identify the circRNAs and predict the potential roles of differentially expressed circRNAs between the two breeds.

Results

Significant differences in physiological and biochemical traits were observed between growing Jinhua and Landrace pigs. We identified 84,864 circRNA candidates in two breeds and 366 circRNAs were detected as significantly differentially expressed. Their host genes are involved in lipid biosynthetic and metabolic processes according to the gene ontology analysis and associated with metabolic pathways.

Conclusion

Our research represents the first description of circRNA profiles in the porcine liver from two divergent phenotype pigs. The predicted miRNA-circRNA interaction provides important basis for miRNA-circRNA relationships in the porcine liver. These data expand the repertories of porcine circRNA and are conducive to understanding the possible molecular mechanisms involved in miRNA and circRNA. Our study provides basic data for further research of the biological functions of circRNAs in the porcine liver.

Study of failures in a rabbit line selected for growth rate

<p>Selection for growth rate is negatively related with reproductive fitness. The aim of this work was to analyse the causes of fertility failure in rabbit does selected for growth rate and characterised for reproductive deficiencies (line R). In the experiment, 82 does were divided into 2 groups: naturally mated (NM) and artificially inseminated (AI), to relate luteinizing hormone (LH) concentration with ovulation induction and pregnancy rate by laparoscopic determination. Additionally, in 38 of these females ovulation rate and metabolites determination (leptin, NEFA, BOHB and glucose) were analysed and perirenal fat thickness measurement and live body weight (LBW) determined. The results showed that all ovulated does (both NM and AI) presented higher concentrations of LH than non-ovulated females. In addition, non-ovulated females showed high levels of leptin and BOHB, as well as LBW. Females from line R have an inherit reduced fertility due to ovulation failure as a consequence of a reduction in LH release, which could be explained by a heavier body weight and higher leptin concentrations.</p>

Genetic Parameters of Reproductive and Meat Quality Traits in Korean Berkshire Pigs

Genetic parameters of Berkshire pigs for reproduction, carcass and meat quality traits were estimated using the records from a breeding farm in Korea. For reproduction traits, 2,457 records of the total number of piglets born (TNB) and the number of piglets born alive (NBA) from 781 sows and 53 sires were used. For two carcass traits which are carcass weight (CW) and backfat thickness (BF) and for 10 meat quality traits which are pH value after 45 minutes (pH45m), pH value after 24 hours (pH24h), lightness in meat color (LMC), redness in meat color (RMC), yellowness in meat color (YMC), moisture holding capacity (MHC), drip loss (DL), cooking loss (CL), fat content (FC), and shear force value (SH), 1,942 pig records were used to estimate genetic parameters. The genetic parameters for each trait were estimated using VCE program with animal model. Heritability estimates for reproduction traits TNB and NBA were 0.07 and 0.06, respectively, for carcass traits CW and BF were 0.37 and 0.57, respectively and for meat traits pH45m, pH24h, LMC, RMC, YMC, MHC, DL, CL, FC, and SH were 0.48, 0.15, 0.19, 0.36, 0.28, 0.21, 0.33, 0.45, 0.43, and 0.39, respectively. The estimate for genetic correlation coefficient between CW and BF was 0.27. The Genetic correlation between pH24h and meat color traits were in the range of −0.51 to −0.33 and between pH24h and DL and SH were −0.41 and −0.32, respectively. The estimates for genetic correlation coefficients between reproductive and meat quality traits were very low or zero. However, the estimates for genetic correlation coefficients between reproductive traits and drip and cooking loss were in the range of 0.12 to 0.17 and −0.14 to −0.12, respectively. As the estimated heritability of meat quality traits showed medium to high heritability, these traits may be applicable for the genetic improvement by continuous measurement. However, since some of the meat quality traits showed negative genetic correlations with carcass traits, an appropriate breeding scheme is required that carefully considers the complexity of genetic parameters and applicability of data.

Recent developments in cattle, pig, sheep and horse breeding - a review

The aim of this review was to summarize new genetic approaches and techniques in the breeding of cattle, pigs, sheep and horses. Often production and reproductive traits are treated separately in genetic evaluations, but advantages may accrue to their joint evaluation. A good example is the system in pig breeding. Simplified breeding objectives are generally no longer appropriate and consequently becoming increasingly complex. The goal of selection for improved animal performance is to increase the profit of the production system; therefore, economic selection indices are now used in most livestock breeding programmes. Recent developments in dairy cattle breeding have focused on the incorporation of molecular information into genetic evaluations and on increasing the importance of longevity and health in breeding objectives to maximize the change in profit. For a genetic evaluation of meat yield (beef, pig, sheep), several types of information can be used, including data from performance test stations, records from progeny tests and measurements taken at slaughter. The standard genetic evaluation method of evaluation of growth or milk production has been the multi-trait animal model, but a test-day model with random regression is becoming the new standard, in sheep as well. Reviews of molecular genetics and pedigree analyses for performance traits in horses are described. Genome – wide selection is becoming a world standard for dairy cattle, and for other farm animals it is under development.

Analysis of 28 generations of selection for reproduction, growth, and carcass traits in swine

Selection (28 generations, G) in a Large White-Landrace composite population for traits aimed at increasing live pigs born per litter (BA), with additional selection for increased 180-d weight (WT180) and longissimus muscle area (LMA) and decreased back fat (BF10) in the last 8 generations, was practiced. Objectives herein were to estimate genetic and phenotypic responses and genetic parameters (n = 1,883 to 54,174) and to investigate whether a plateau in response for BA occurred. Line 2 (L2) was selected for an index of ovulation rate and embryo survival (G0 to G11), fully formed pigs (FF) per litter (G12 to 14), and BA and pig birth weight (PBW, G15 to G19), and its control line (LC1) was selected randomly (G0 to G21). Line 4 (L4), derived from L2, and line 5 (L5), derived from LC1, at G8 were selected in 2 stages for ovulation rate and FF (G9 to G16) and BA and PBW (G17 to G19), and their control (LC6) was selected randomly. At G20, L4 and L5 were crossed to form L45, and L4 and L2 were crossed to continue L2; L2 and L45 were subsequently selected for BA, WT180, LMA, and BF10 (G21 to G28). At G21, LC1 and LC6 were reciprocally crossed to form LC16, control for L2, and LC61, control for L45. Selection in L2 and L45 was first for BA and then for other traits among pigs selected for BA. Line sizes were 40 to 60 litters by 15 to 20 sires/G. Cumulative selection differentials (CSD) were calculated. MTDFREML was used to estimate variance components, EBV, and responses. Genetic changes at G28 in L2 were 4.63 FF and 3.66 BA, with 72% (FF) and 86% (BA) of the change occurring after G11. Two-stage selection produced similar responses (P < 0.01) in FF in L4 and L5 (0.27 and 0.29 pigs/G) but a greater response in BA in L5 (0.19 vs. 0.28 pigs/G). Genetic change in L45 from G20 to G28 was 0.17 pigs/G for both FF and BA (P < 0.01). Genetic changes at G28 in L45 were 4.16 FF and 3.68 BA. Genetic correlations of reproductive and growth traits were near zero, ranging from -0.43 (stillborn pigs/litter with BF10) to 0.21 (mummies/litter with LMA). Selection for growth traits along with litter size selection during G19 to G28 resulted in responses consistent with the selection applied and the heritability of the trait. No evidence for a selection plateau existed; selection differentials and variances of FF and BA in selection lines during G20 to G28 were similar to those in earlier generations. Over all generations, heritability of BA was 0.20 ± 0.03 and remained at approximately 0.17 in selection lines in later generations.

Optimising a crossbreeding production system using three specialised imported swine breeds in south-western China

Crossbreeding is an effective method for improving the efficiency and profit of production in pig commercial operations. It exploits available heterosis and combines breed differences for specific characteristics. Before application of a crossbreeding system, commercial swine producers should evaluate available crossbreeding systems using existing swine breeds, and choose one that is most beneficial for their own environment, resources, and management. In this study, the latest biological and economic data were collected from commercial producers in south-western China. Three imported swine breeds (Duroc, Landrace and Yorkshire) were evaluated with three simulated crossbreeding systems. System 1 used a three-breed terminal cross with Duroc × (Landrace × Yorkshire). System 2 was based on a three-breed rotational cross of Duroc, Landrace and Yorkshire. System 3 was a combined cross system with Duroc × (Landrace, Yorkshire) three-breed rotaterminal. System 1 was predicted to be the most beneficial system (￥3895.15/sow), followed by system 3 (￥3749.02/sow), and then system 2 (￥3317.33/sow). Results of this study suggested that three-breed terminal cross or rotaterminal cross should maximise effective use of heterosis and breed complementarity of three imported breeds in south-western China. Also, the relative economic values of objective traits for these systems were updated using the most up-to-date biological and economic parameters.

Correlative responses for carcass and meat quality traits to selection for ovulation rate or prenatal survival in French Large White pigs

Correlated effects of selection for components of litter size on carcass and meat quality traits were estimated using data from 3 lines of pigs derived from the same Large White base population. Two lines were selected for 6 generations on high ovulation rate at puberty (OR) or high prenatal survival corrected for ovulation rate in the first 2 parities (PS). The third line was an unselected control (CON). The 3 lines were kept for a 7th generation, but without any selection. Carcass and meat quality traits were recorded on the 5th to 7th generation of the experiment. Carcass traits included dressing percentage, carcass length (LGTH), average backfat thickness (ABT), estimated lean meat content, and 8 carcass joint weight traits. Meat quality traits included pH recorded 24 h after slaughter (pH24) of LM, gluteus superficialis (GS), biceps femoris (BF), and adductor femoris (AD) muscles, as well as reflectance and water-holding capacity (WHC) of GS and BF muscles. Heritabilities of carcass and meat quality traits and their genetic correlations with OR and PS were estimated using REML methodology applied to a multiple trait animal model. Correlated responses to selection were then estimated by computing differences between OR or PS and CON lines at generations 5 to 7 using least squares and mixed model methodology. Heritability (h(2)) estimates were 0.08 +/- 0.04, 0.58 +/- 0.10, 0.70 +/- 0.10, and 0.74 +/- 0.10 for dressing percentage, LGTH, ABT, and lean meat content, respectively, ranged from 0.28 to 0.72 for carcass joint traits, from 0.28 to 0.45 for pH24 and reflectance measurements, and from 0.03 to 0.11 for WHC measurements. Both OR and PS had weak genetic correlations with carcass (r(G) = -0.09 to 0.17) and most meat quality traits. Selection for OR did not affect any carcass composition or meat quality trait. Correlated responses to selection for PS were also limited, with the exception of a decrease in pH24 of GS and BF muscles (-0.12 to -0.14 after 6 generations; P < 0.05), in WHC of GS muscle (-18.9 s after 6 generations; P < 0.05) and a tendency toward an increase in loin weight (0.44 kg after 6 generations; P < 0.10) .

Correlated responses of pre- and postweaning growth and backfat thickness to six generations of selection for ovulation rate or prenatal survival in French Large White pigs

Correlated effects of selection for components of litter size on growth and backfat thickness were estimated using data from 3 pig lines derived from the same base population of Large White. Two lines were selected for 6 generations on either high ovulation rate at puberty (OR) or high prenatal survival corrected for ovulation rate in the first 2 parities (PS). The third line was an unselected control (C). Genetic parameters for individual piglet BW at birth (IWB); at 3 wk of age (IW3W); and at weaning (IWW); ADG from birth to weaning (ADGBW), from weaning to 10 wk of age (ADGPW), and from 25 to 90 kg of BW (ADGT); and age (AGET) and average backfat thickness (ABT) at 90 kg of BW were estimated using REML methodology applied to a multivariate animal model. In addition to fixed effects, the model included the common environment of birth litter, as well as direct and maternal additive genetic effects as random effects. Genetic trends were estimated by computing differences between OR or PS and C lines at each generation using both least squares (LS) and mixed model (MM) methodology. Average genetic trends for direct and maternal effects were computed by regressing line differences on generation number. Estimates of direct and maternal heritabilities were, respectively, 0.10, 0.12, 0.20, 0.24, and 0.41, and 0.17, 0.33, 0.32, 0.41, and 0.21 (SE = 0.03 to 0.04) for IWB, IW3W, IWW, ADGBW, and ADGPW. Genetic correlations between direct and maternal effects were moderately negative for IWB (-0.21 +/- 0.18), but larger for the 4 other traits (-0.59 to -0.74). Maternal effects were nonsignificant and were removed from the final analyses of ADGT, AGET, and ABT. Direct heritability estimates were 0.34, 0.46, and 0.21 (SE = 0.03 to 0.05) for ADGT, AGET, and ABT, respectively. Direct and maternal genetic correlations of OR with performance traits were nonsignificant, with the exception of maternal correlations with IWB (-0.28 +/- 0.13) and ADGPW (0.23 +/- 0.11) and direct correlation with AGET (-0.23 +/- 0.09). Prenatal survival also had low direct but moderate to strong maternal genetic correlations (-0.34 to -0.65) with performance traits. The only significant genetic trends were a negative maternal trend for IBW in the OR line and favorable direct trends for postweaning growth (ADGT and AGET) in both lines. Selection for components of litter size has limited effects on growth and backfat thickness, although it slightly reduces birth weight and improves postweaning growth.

Genetic correlations between reproduction and production traits in swine

Genetic correlations between reproduction and production traits were estimated in swine. Reproduction traits investigated were age at first service (AFS), number of live-born piglets in the first litter (NBA1), interval from weaning to first service after first litter (WTS1), number of live-born piglets in the second litter (NBA2), and interval from weaning to first service after the second litter (WTS2). Females generating the data were Norwegian Landrace born in nucleus herds between 1990 and 2000, and the number of records ranged from 13,792 to 56,932. Genetic correlations were estimated among the main production traits in the breeding goal: adjusted age at 100 kg live weight (A100), percentage of lean meat content (LMC), individual feed consumption from 25 to 100 kg (FC), and bacon side quality (BSQ). Average adjusted backfat thickness (BF) was included as a production trait. The A100 and BF traits were recorded on gilts on-farm with 190,454 records, whereas LMC, BSQ, and FC were recorded on-station with the number of records ranging from 12,487 to 12,992. Analyses were carried out with a multivariate animal model using average information restricted maximum likelihood procedures by first running each reproduction trait with A100 and BF, followed by each reproduction trait with LMC, BSQ, and FC. Average heritabilities for reproduction traits were as follows: AFS (0.38), NBA1 (0.11), WTS1 (0.06), NBA2 (0.12), and WTS2 (0.03); and for production traits: A100 (0.30), BF (0.44), FC (0.22), LMC (0.58), and BSQ (0.23). The highest genetic correlation was estimated between A100 and AFS (r(g)= 0.68), also resulting in a positive genetic correlation between FC and AFS. Growth (A100) was negatively (i.e., unfavorably) genetically correlated to NBA1 and NBA2 (r(g) = 0.60 and rg = 0.42 respectively), and so the genetic correlation to FC also became unfavorable (r(g)= 0.23 and r(g) = 0.20). Single-trait selection for enhanced LMC would also affect NBA1 and NBA2 unfavorably (r(g)= -0.12 and r(g)= -0.24). Correlations between BF at 100 kg live weight and reproduction traits were close to zero; however, a low genetic correlation between BF and WTS1 was obtained (r(g)= -0.12), indicating that selection toward reduced BF at 100 kg live weight may have an unfavorable impact on WTS1.

Relationships between quantitative and reproductive fitness traits in animals

The relationships between quantitative and reproductive fitness traits in animals are of general biological importance for the development of population genetic models and our understanding of evolution, and of great direct economical importance in the breeding of farm animals. Two well investigated quantitative traits--body weight (BW) and litter size (LS)--were chosen as the focus of our review. The genetic relationships between them are reviewed in fishes and several mammalian species. We have focused especially on mice where data are most abundant. In mice, many individual genes influencing these traits have been identified, and numerous quantitative trait loci (QTL) located. The extensive data on both unselected and selected mouse populations, with some characterized for more than 100 generations, allow a thorough investigation of the dynamics of this relationship during the process of selection. Although there is a substantial positive genetic correlation between both traits in unselected populations, caused mainly by the high correlation between BW and ovulation rate, that correlation apparently declines during selection and therefore does not restrict a relatively independent development of both traits. The importance of these findings for overall reproductive fitness and its change during selection is discussed.

Threshold-linear estimation of genetic parameters for farrowing mortality, litter size, and test performance of Large White sows

Up to 109,447 records of 49,656 Large White sows were used to evaluate the genetic relationship between number of pigs born dead (BD) and number born alive (BA) in first and later parities. Performance data (n = 30,832) for ultrasound backfat (BF) at the end of the test and days to reach 113.5 kg (AD) were used to estimate their relationships with BD and BA at first parity in a four-trait threshold-linear analysis (TL). Effects were year-farm, contemporary group (CG: farm-farrowing year-farrowing month) and animal additive genetic. At first parity, estimates of heritability were 0.09, 0.09, 0.37, and 0.31 for BA, BD, AD, and BF, respectively. The estimate of genetic correlation between BD and litter size was -0.04 (BD-BA). Corresponding values with test traits were both -0.14 (BD-AD, BD-BF). Estimates of genetic correlation between BA and performance traits were 0.08 (BA-AD) and 0.05 (BA-BF). The two test traits were moderately negatively correlated (-0.22). For later parities, a six-trait (BD, BA in three parities) TL model was implemented. The estimates of additive genetic variances and heritability increased with parity for BD and BA. Estimates of heritabilities were: 0.09, 0.10, and 0.11 for BD, and 0.09, 0.12, and 0.12 for BA in parities one to three, respectively. Estimates of genetic correlations between different parities were high (0.91 to 0.96) for BD, and slightly lower (0.74 to 0.95) for BA. Genetic correlations between BD and BA were low and positive (0.02 to 0.17) for BA in Parities 1 and 2, but negative (-0.04 to -0.10) for BA in Parity 3. Selection for increased litter size should have little effect on farrowing piglet mortality. Intense selection for faster growth and increased leanness should increase farrowing piglet mortality of first-parity sows. A repeatability model with a simple correction for the heterogeneity of variances over parities could be implemented to select against farrowing mortality. The genetic components of perinatal piglet mortality are independent of the ones for litter size in the first parity, and they show an undesirable, but not strong, genetic association in second parity.

Genetic associations of prolificacy with performance, carcass, meat quality, and leg conformation traits in the Finnish Landrace and Large White pig populations

The objective of this study was to estimate genetic associations of prolificacy traits with other traits under selection in the Finnish Landrace and Large White populations. The prolificacy traits evaluated were total number of piglets born, number of stillborn piglets, piglet mortality during suckling, age at first farrowing, and first farrowing interval. Genetic correlations were estimated with two performance traits (ADG and feed:gain ratio), with two carcass traits (lean percent and fat percent), with four meat quality traits (pH and L* values in longissimus dorsi and semimembranosus muscles), and with two leg conformation traits (overall leg action and buck-kneed forelegs). The data contained prolificacy information on 12,525 and 10,511 sows in the Finnish litter recording scheme and station testing records on 10,372 and 9,838 pigs in Landrace and Large White breeds, respectively. The genetic correlations were estimated by the restricted maximum likelihood method. The most substantial correlations were found between age at first farrowing and lean percent (0.19 in Landrace and 0.27 in Large White), and fat percent (-0.26 in Landrace and -0.18 in Large White), and between number of stillborn piglets and ADG (-0.38 in Landrace and -0.25 in Large White) and feed:gain (0.27 in Landrace and 0.12 in Large White). The correlations are indicative of the benefits of superior growth for piglets already at birth. Similarly, the correlations indicate that age at first farrowing is increasing owing to selection for carcass lean content. There was also clear favorable correlation between performance traits and piglet mortality from birth to weaning in Large White (r(g) was -0.43 between piglet mortality and ADG, and 0.42 between piglet mortality and feed:gain), but not in Landrace (corresponding correlations were 0.26 and -0.22). There was a general tendency that prolificacy traits were favorably correlated with performance traits, and unfavorably with carcass lean and fat percents, whereas there were no clear associations between prolificacy and meat quality or leg conformation. In conclusion, accuracy of estimated breeding values may be improved by accounting for genetic associations between prolificacy, carcass, and performance traits in a multitrait analysis.