Heritability of body length and measures of body density and their relationship to backfat thickness and loin muscle area in swine

Genomic Prediction of Growth Traits in Yorkshire Pigs of Different Reference Group Sizes Using Different Estimated Breeding Value Models

The need for sufficient reference population data poses a significant challenge in breeding programs aimed at improving pig farming on a small to medium scale. To overcome this hurdle, investigating the advantages of combing reference populations of varying sizes is crucial for enhancing the accuracy of the genomic estimated breeding value (GEBV). Genomic selection (GS) in populations with limited reference data can be optimized by combining populations of the same breed or related breeds. This study focused on understanding the effect of combing different reference group sizes on the accuracy of GS for determining the growth effectiveness and percentage of lean meat in Yorkshire pigs. Specifically, our study investigated two important traits: the age at 100 kg live weight (AGE100) and the backfat thickness at 100 kg live weight (BF100). This research assessed the efficiency of genomic prediction (GP) using different GEBV models across three Yorkshire populations with varying genetic backgrounds. The GeneSeek 50K GGP porcine high-density array was used for genotyping. A total of 2295 Yorkshire pigs were included, representing three Yorkshire pig populations with different genetic backgrounds-295 from Danish (small) lines from Huaibei City, Anhui Province, 500 from Canadian (medium) lines from Lixin County, Anhui Province, and 1500 from American (large) lines from Shanghai. To evaluate the impact of different population combination scenarios on the GS accuracy, three approaches were explored: (1) combining all three populations for prediction, (2) combining two populations to predict the third, and (3) predicting each population independently. Five GEBV models, including three Bayesian models (BayesA, BayesB, and BayesC), the genomic best linear unbiased prediction (GBLUP) model, and single-step GBLUP (ssGBLUP) were implemented through 20 repetitions of five-fold cross-validation (CV). The results indicate that predicting one target population using the other two populations yielded the highest accuracy, providing a novel approach for improving the genomic selection accuracy in Yorkshire pigs. In this study, it was found that using different populations of the same breed to predict small- and medium-sized herds might be effective in improving the GEBV. This investigation highlights the significance of incorporating population combinations in genetic models for predicting the breeding value, particularly for pig farmers confronted with resource limitations.

Genetic evaluation for production and body size traits using different animal models in purebred-Duroc pigs

Duroc pigs are popular crossbred terminal sires, and accurate assessment of genetic parameters in the population can help to rationalize breeding programmes. The principle aim of this study were to evaluate the genetic parameters of production (birth weight, BW; age at 115 kg, AGE; feed conversion ratio, FCR) and body size (body length, BL; body height, BH; front cannon circumference, FCC) traits of Duroc pigs. The second objective was to analyze the fit of different genetic assessment models. The variance components and correlations of BW (28,348 records), AGE (28,335 records), FCR (11,135 records), BL (31,544 records), BH (21,862 records), and FCC (14,684 records) traits were calculated by using DMU and AIREMLF90 from BLUPF90 package. In the common environment model, the heritability of BW, AGE, FCR, BL, BH, and FCC traits were 0.17 ± 0.014, 0.30 ± 0.019, 0.28 ± 0.024, 0.16 ± 0.013, 0.14 ± 0.017, and 0.081 ± 0.016, with common litter effect values of 0.25, 0.20, 0.18, 0.23, 0.19, and 0.16, respectively. According to the results of the Akaike information criterion (AIC) calculations, models with smaller AIC values have a better fit. We found that the common environment model with litter effects as random effects for estimating genetic parameters had a better fit. In this Model, the estimated genetic correlations between AGE with BW, FCR, BL, BH, and FCC traits were -0.28 (0.040), 0.76 (0.038), -0.71 (0.036), -0.44 (0.060), and -0.60 (0.073), respectively, with phenotypic correlations of -0.17, 0.52, -0.22, -0.13 and -0.24, respectively. In our analysis of genetic trends for six traits in the Duroc population from 2012 to 2021, we observed significant genetic trends for AGE, BL, and BH. Particularly noteworthy is the rapid decline in the genetic trend for AGE, indicating an enhancement in the pig's growth rate through selective breeding. Therefore, we believe that some challenging-to-select traits can benefit from the genetic correlations between traits. By selecting easily measurable traits, they can gain from synergistic selection effects, leading to genetic progress. Conducting population genetic parameter analysis can assist us in devising breeding strategies.

Genetic parameters for automatically-measured vaginal temperature, respiration efficiency, and other thermotolerance indicators measured on lactating sows under heat stress conditions

BACKGROUND

Genetic selection based on direct indicators of heat stress could capture additional mechanisms that are involved in heat stress response and enable more accurate selection for more heat-tolerant individuals. Therefore, the main objectives of this study were to estimate genetic parameters for various heat stress indicators in a commercial population of Landrace × Large White lactating sows measured under heat stress conditions. The main indicators evaluated were: skin surface temperatures (SST), automatically-recorded vaginal temperature (TV), respiration rate (RR), panting score (PS), body condition score (BCS), hair density (HD), body size (BS), ear size, and respiration efficiency (Reff).

RESULTS

Traits based on TV presented moderate heritability estimates, ranging from 0.15 ± 0.02 to 0.29 ± 0.05. Low heritability estimates were found for SST traits (from 0.04 ± 0.01 to 0.06 ± 0.01), RR (0.06 ± 0.01), PS (0.05 0.01), and Reff (0.03 ± 0.01). Moderate to high heritability values were estimated for BCS (0.29 ± 0.04 for caliper measurements and 0.25 ± 0.04 for visual assessments), HD (0.25 ± 0.05), BS (0.33 ± 0.05), ear area (EA; 0.40 ± 0.09), and ear length (EL; 0.32 ± 0.07). High genetic correlations were estimated among SST traits (> 0.78) and among TV traits (> 0.75). Similarly, high genetic correlations were also estimated for RR with PS (0.87 ± 0.02), with BCS measures (0.92 ± 0.04), and with ear measures (0.95 ± 0.03). Low to moderate positive genetic correlations were estimated between SST and TV (from 0.25 ± 0.04 to 0.76 ± 0.07). Low genetic correlations were estimated between TV and BCS (from - 0.01 ± 0.08 to 0.06 ± 0.07). Respiration efficiency was estimated to be positively and moderately correlated with RR (0.36 ± 0.04), PS (0.56 ± 0.03), and BCS (0.56 ± 0.05 for caliper measurements and 0.50 ± 0.05 for the visual assessments). All other trait combinations were lowly genetically correlated.

CONCLUSIONS

A comprehensive landscape of heritabilities and genetic correlations for various thermotolerance indicators in lactating sows were estimated. All traits evaluated are under genetic control and heritable, with different magnitudes, indicating that genetic progress is possible for all of them. The genetic correlation estimates provide evidence for the complex relationships between these traits and confirm the importance of a sub-index of thermotolerance traits to improve heat tolerance in pigs.

Genomic Association Analysis of Growth and Backfat Traits in Large White Pigs

The pig industry is significantly influenced by complex traits such as growth rate and fat deposition, which have substantial implications for economic returns. Over the years, remarkable genetic advancements have been achieved through intense artificial selection to enhance these traits in pigs. In this study, we aimed to investigate the genetic factors that contribute to growth efficiency and lean meat percentages in Large White pigs. Specifically, we focused on analyzing two key traits: age at 100 kg live weight (AGE100) and backfat thickness at 100 kg (BF100), in three distinct Large White pig populations-500 Canadian, 295 Danish, and 1500 American Large White pigs. By employing population genomic techniques, we observed significant population stratification among these pig populations. Utilizing imputed whole-genome sequencing data, we conducted single population genome-wide association studies (GWAS) as well as a combined meta-analysis across the three populations to identify genetic markers associated with the aforementioned traits. Our analyses highlighted several candidate genes, such as CNTN1-which has been linked to weight loss in mice and is potentially influential for AGE100-and MC4R, which is associated with obesity and appetite and may impact both traits. Additionally, we identified other genes-namely, PDZRN4, LIPM, and ANKRD22-which play a partial role in fat growth. Our findings provide valuable insights into the genetic basis of these important traits in Large White pigs, which may inform breeding strategies for improved production efficiency and meat quality.

Genetic parameters for linear conformation, stayability, performance and reproduction traits in German local Swabian-Hall landrace sows

Improvements of longevity in sows are of overriding importance from an animal welfare as well as from an economic perspective, also in the local Swabian-Hall Landrace (SHL) breed. Consequently, the aim of the present study was a detailed assessment of linear conformation traits in the context of early predictions of sow stayability and to infer genetic (co)variance components between conformation traits with reproduction and performance traits. In this regard, we implemented a linear 9-point scoring system for conformation traits reflecting the body morphology and feet and leg characteristics in gilts. Linear conformation trait scoring included body length (BLEN), body height (BHEI), hind leg angularity (HLANG), hind leg pastern (HLPAS), hind cannon bone strength (HCBS), hind leg position (HLPOS), front leg position (FLPOS), claw length (CLEN) and muscling (MUSC) from 6042 SHL gilts before first insemination at the age of 180-200 days. For the same gilts, performance traits included average daily gain (ADG) and back fat thickness (BF) measured via ultrasound, reproduction traits included the number of piglets born alive (NBA) and the number of piglets weaned (NWEAN), and stayability was a binary trait reflecting sow survival after parity 2 (STAY_12), 3 (STAY_13) and 4 (STAY_14). For the estimation of variance components and heritabilities, single-trait linear animal models were defined for conformation, performance and reproduction traits, and single-trait generalized linear mixed models with a logit link function for binary stayability traits. Genetic covariances and correlations were inferred in series of bivariate runs for all combinations of conformation and remaining traits. The distribution of the assigned conformation scores reflected a Gaussian distribution, but a large fraction of records was assigned to the intermediate score classes 4, 5 and 6. Accordingly, the restricted utilization of the 9-point scale might explain the small genetic variances and small heritabilities for feet and leg traits in the range from 0.06 to 0.17. Heritabilities were larger for the linear traits reflecting body morphology, i.e., for BLEN (0.21) and BHEI (0.20). For conformation traits, the common litter environment explained up to 17% of the phenotypic trait variation. Genetic and especially phenotypic correlations between linear conformation traits with the reproduction traits NBA and NWEAN were close to zero. Heritabilities for STAY_12, STAY_13 and STAY_14 were 0.08, 0.07 and 0.05, respectively. Moderate genetic relationships were estimated between STAY_14 with some conformation traits. Especially high scores for BHEI and BLEN (i.e., long and large gilts) implied a decline in STAY_14 genetically (r_g  = -0.24 and -0.53, respectively). Moderate genetic correlations were estimated between HLANG with STAY_14 (0.28), and between HCBS with STAY_12 (0.23). For most of the conformation traits with intermediate optimum, genetic correlations with STAY were close to zero, indicating improved longevity for gilts representing the population average with scores 4, 5 or 6, and suggesting the development of appropriate selection indices in this regard.

Novel Haplotype in the HHEX Gene Promoter Associated with Body Length in Pigs

The screening of important candidate genes and the identification of genetic markers are important for molecular selection in the pig industry. The hematopoietically expressed homeobox (HHEX) gene plays an important role in embryonic development and organogenesis; however, the genetic variation and expression pattern of the porcine HHEX gene remains to be clarified. In this study, semiquantitative RT-PCR and immunohistochemistry results showed the specific expression of the HHEX gene in porcine cartilage tissues. A novel haplotype consisting of two SNPs rs80901185 (T > C) and rs80934526 (A > G) was detected in the promoter region of the HHEX gene. The expression of the HHEX gene was significantly higher in Yorkshire pigs (TA haplotype) than in Wuzhishan pigs (CG haplotype), and a population analysis showed that this haplotype was significantly associated with body length. An analysis subsequently revealed that the -586 to -1 bp region of the HHEX gene promoter showed the highest activity. Furthermore, we found that the activity of the TA haplotype was significantly higher than that of the CG haplotype by changing the potential binding of transcription factors YY1 and HDAC2. In summary, we conclude that the porcine HHEX gene may contribute to the breeding of pigs for body length traits.

Integrating genome-wide association studies and population genomics analysis reveals the genetic architecture of growth and backfat traits in pigs

Growth and fat deposition are complex traits, which can affect economical income in the pig industry. Due to the intensive artificial selection, a significant genetic improvement has been observed for growth and fat deposition in pigs. Here, we first investigated genomic-wide association studies (GWAS) and population genomics (e.g., selection signature) to explore the genetic basis of such complex traits in two Large White pig lines (n = 3,727) with the GeneSeek GGP Porcine HD array (n = 50,915 SNPs). Ten genetic variants were identified to be associated with growth and fatness traits in two Large White pig lines from different genetic backgrounds by performing both within-population GWAS and cross-population GWAS analyses. These ten significant loci represented eight candidate genes, i.e., NRG4, BATF3, IRS2, ANO1, ANO9, RNF152, KCNQ5, and EYA2. One of them, ANO1 gene was simultaneously identified for both two lines in BF100 trait. Compared to single-population GWAS, cross-population GWAS was less effective for identifying SNPs with population-specific effect, but more powerful for detecting SNPs with population-shared effects. We further detected genomic regions specifically selected in each of two populations, but did not observe a significant enrichment for the heritability of growth and backfat traits in such regions. In summary, the candidate genes will provide an insight into the understanding of the genetic architecture of growth-related traits and backfat thickness, and may have a potential use in the genomic breeding programs in pigs.

Estimating genetics of body dimensions and activity levels in pigs using automated pose estimation

Pig breeding is changing rapidly due to technological progress and socio-ecological factors. New precision livestock farming technologies such as computer vision systems are crucial for automated phenotyping on a large scale for novel traits, as pigs’ robustness and behavior are gaining importance in breeding goals. However, individual identification, data processing and the availability of adequate (open source) software currently pose the main hurdles. The overall goal of this study was to expand pig weighing with automated measurements of body dimensions and activity levels using an automated video-analytic system: DeepLabCut. Furthermore, these data were coupled with pedigree information to estimate genetic parameters for breeding programs. We analyzed 7428 recordings over the fattening period of 1556 finishing pigs (Piétrain sire x crossbred dam) with two-week intervals between recordings on the same pig. We were able to accurately estimate relevant body parts with an average tracking error of 3.3 cm. Body metrics extracted from video images were highly heritable (61–74%) and significantly genetically correlated with average daily gain (r_g = 0.81–0.92). Activity traits were low to moderately heritable (22–35%) and showed low genetic correlations with production traits and physical abnormalities. We demonstrated a simple and cost-efficient method to extract body dimension parameters and activity traits. These traits were estimated to be heritable, and hence, can be selected on. These findings are valuable for (pig) breeding organizations, as they offer a method to automatically phenotype new production and behavioral traits on an individual level.

Genome-Wide Detection of Genetic Loci and Candidate Genes for Body Conformation Traits in Duroc × Landrace × Yorkshire Crossbred Pigs

The Duroc × (Landrace × Yorkshire) hybrid pigs (DLY) are the most popular commercial pigs, providing consumers with the largest source of pork. In order to gain more insights into the genetic architecture of economically important traits in pigs, we performed a genome-wide association study (GWAS) using the GeneSeek Porcine 50 K SNP Chip to map the genetic markers and genes associated with body conformation traits (BCT) in 311 DLY pigs. The quantitative traits analyzed included body weight (BW), carcass length (CL), body length (BL), body height (BH), and body mass index (BMI). BMI was defined as BMI_CL, BMI_BL, and BMI_BH, respectively, based on CL, BL, and BH phenotypic data. We identified 82 SNPs for the seven traits by GEMMA-based and FarmCPU-based GWASs. Both methods detected two quantitative trait loci (QTL) on SSC8 and SSC17 for body conformation traits. Several candidate genes (such as TNFAIP3, KDM4C, HSPG2, BMP2, PLCB4, and GRM5) were found to be associated with body weight and body conformation traits in pigs. Notably, the BMP2 gene had pleiotropic effects on CL, BL, BH, BMI_CL, and BMI_BL and is proposed as a strong candidate gene for body size due to its involvement in growth and bone development. Furthermore, gene set enrichment analysis indicated that most of the pathway terms are associated with regulation of cell growth, negative regulation of cell population proliferation, and chondrocyte differentiation. We anticipate that these results further advance our understanding of the genetic architecture of body conformation traits in the popular commercial DLY pigs and provide new insights into the genetic architecture of BMI in pigs.

Genome-Wide Association Study for Body Length, Body Height, and Total Teat Number in Large White Pigs

Body length, body height, and total teat number are economically important traits in pig breeding, as these traits are usually associated with the growth, reproductivity, and longevity potential of piglets. Here, we report a genetic analysis of these traits using a population comprising 2,068 Large White pigs. A genotyping-by-sequencing (GBS) approach was used to provide high-density genome-wide SNP discovery and genotyping. Univariate and bivariate animal models were used to estimate heritability and genetic correlations. The results showed that heritability estimates for body length, body height, and total teat number were 0.25 ± 0.04, 0.11 ± 0.03, and 0.22 ± 0.04, respectively. The genetic correlation between body length and body height exhibited a strongly positive correlation (0.63 ± 0.15), while a positive but low genetic correlation was observed between total teat number and body length. Furthermore, we used two different genome-wide association study (GWAS) approaches: single-locus GWAS and weighted single-step GWAS (WssGWAS), to identify candidate genes for these traits. Single-locus GWAS detected 76, 13, and 29 significant single-nucleotide polymorphisms (SNPs) associated with body length, body height, and total teat number. Notably, the most significant SNP (S17_15781294), which is located 20 kb downstream of the BMP2 gene, explained 9.09% of the genetic variance for body length traits, and it also explained 9.57% of the genetic variance for body height traits. In addition, another significant SNP (S7_97595973), which is located in the ABCD4 gene, explained 8.92% of the genetic variance for total teat number traits. GWAS results for these traits identified some candidate genomic regions, such as SSC6: 14.96–15.02 Mb, SSC7: 97.18–98.18 Mb, SSC14: 128.29–131.15 Mb, SSC17: 15.39–17.27 Mb, and SSC17: 22.04–24.15 Mb, providing a starting point for further inheritance research. Most quantitative trait loci were detected by single-locus GWAS and WssGWAS. These findings reveal the complexity of the genetic mechanism of the three traits and provide guidance for subsequent genetic improvement through genome selection.

Genome-wide association study for growth and fatness traits in Chinese Sujiang pigs

Growth and fatness traits are complex and economically important traits in the pig industry. The molecular basis underlying porcine growth and fatness traits remains largely unknown. To uncover genetic loci and candidate genes for these traits, we explored the GeneSeek GGP Porcine 80K SNP chip to perform a GWAS for seven growth and fatness traits in 365 individuals from the Sujiang pig, a recently developed breed in China. We identified two, 17, one and 11 SNPs surpassing the suggestively significant threshold (P < 1.86 × 10^-5 ) for body weight, chest circumference, chest width and backfat thickness respectively. Of these SNPs, 20 represent novel genetic loci, and five and four SNPs were respectively associated with chest circumference and backfat thickness at a genome-wide significant threshold (P < 9.31 × 10^-7 ). Eight SNPs had a pleiotropic effect on both chest circumference and backfat thickness. The most remarkable locus resided in a region between 72.95 and 76.27 Mb on pig chromosome 4, harboring a number of previously reported quantitative trait loci related to backfat deposition. In addition to two reported genes (PLAG1 and TAS2R38), we identified four genes including GABRB3, ZNF106, XKR4 and MGAM as novel candidates for body weight and backfat thickness at the mapped loci. Our findings provide insights into the genetic architecture of porcine growth and fatness traits and potential markers for selective breeding of Chinese Sujiang pigs.

Genome-wide association study identifies 22 new loci for body dimension and body weight traits in a White Duroc×Erhualian F2 intercross population

Objective

Growth-related traits are important economic traits in the swine industry. However, the genetic mechanism of growth-related traits is little known. The aim of this study was to screen the candidate genes and molecular markers associated with body dimension and body weight traits in pigs.

Methods

A genome-wide association study (GWAS) on body dimension and body weight traits was performed in a White Duroc×Erhualian F₂ intercross by the illumina PorcineSNP60K Beadchip. A mixed linear model was used to assess the association between single nucleotide polymorphisms (SNPs) and the phenotypes.

Results

In total, 611 and 79 SNPs were identified significantly associated with body dimension traits and body weight respectively. All SNPs but 62 were located into 23 genomic regions (quantitative trait loci, QTLs) on 14 autosomal and X chromosomes in Sus scrofa Build 10.2 assembly. Out of the 23 QTLs with the suggestive significance level (5×10⁻⁴), three QTLs exceeded the genome-wide significance threshold (1.15×10⁻⁶). Except the one on Sus scrofa chromosome (SSC) 7 which was reported previously all the QTLs are novel. In addition, we identified 5 promising candidate genes, including cell division cycle 7 for abdominal circumference, pleiomorphic adenoma gene 1 and neuropeptides B/W receptor 1 for both body weight and cannon bone circumference on SSC4, phosphoenolpyruvate carboxykinase 1, and bone morphogenetic protein 7 for hip circumference on SSC17.

Conclusion

The results have not only demonstrated a number of potential genes/loci associated with the growth-related traits in pigs, but also laid a foundation for studying the genes’ role and further identifying causative variants underlying these loci.

Genetic parameters and crossbreeding effects of fat deposition and fatty acid profiles in Iberian pig lines

The aim of this study was to estimate the genetic and environmental parameters and crossbreeding effects on fatty acid and fat traits in the Iberian pig. Our final goal is to explore target selection traits and define crossbreeding strategies. The phenotypes were obtained under intensive management from 470 animals in a diallelic experiment involving Retinto, Torbiscal, and Entrepelado lines. The data set was composed of backfat thickness at the fourth rib (BFT), intramuscular fat (IMF) in the longissimus thoracis (LT), and the fatty acid profile for IMF and subcutaneous fat (SCF) traits. Data were analyzed through a Bayesian bivariate animal model by using a reparameterization of Dickerson's model. The results obtained showed an important genetic determinism for all traits analyzed with heritability ranging from 0.09 to 0.67. The common environment litter effect also had an important effect on IMF (0.34) and its fatty acid composition (0.06-0.53) at slaughter. The additive genetic correlation between BFT and IMF (additive genetic correlation [] = 0.31) suggested that it would be possible to improve lean growth independent of the IMF with an appropriate selection index. Furthermore, the high additive genetic correlation ( = 0.68) found between MUFA tissues would seem to indicate that either the LT or SCF could be used as the reference tissue for MUFA selection. The relevance of the crossbreeding parameters varied according to the traits analyzed. Backfat thickness at the fourth rib and the fatty acid profile of the IMF showed relevant differences between crosses, mostly due to line additive genetic effects associated with the Retinto line. On the contrary, those for IMF crosses were probably mainly attributable to heterosis effects. Particularly, heterosis effects were relevant for the Retinto and Entrepelado crosses (approximately 16% of the trait), which could be valuable for a crossbreeding system involving these lines.

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.

Genome-wide association studies identify the loci for 5 exterior traits in a Large White × Minzhu pig population

As one of the main breeding selection criteria, external appearance has special economic importance in the hog industry. In this study, an Illumina Porcine SNP60 BeadChip was used to conduct a genome-wide association study (GWAS) in 605 pigs of the F₂ generation derived from a Large White × Minzhu intercross. Traits under study were abdominal circumference (AC), body height (BH), body length (BL), cannon bone circumference (CBC), chest depth (CD), chest width (CW), rump circumference (RC), rump width (RW), scapula width (SW), and waist width (WW). A total of 138 SNPs (the most significant being MARC0033464) on chromosome 7 were found to be associated with BH, BL, CBC, and RC (P-value  = 4.15E-6). One SNP on chromosome 1 was found to be associated with CD at genome-wide significance levels. The percentage phenotypic variance of these significant SNPs ranged from 0.1–25.48%. Moreover, a conditional analysis revealed that the significant SNPs were derived from a single quantitative trait locus (QTL) and indicated additional chromosome-wide significant association for 25 SNPs on SSC4 (BL, CBC) and 9 SNPs on SSC7 (RC). Linkage analysis revealed two complete linkage disequilibrium haplotype blocks that contained seven and four SNPs, respectively. In block 1, the most significant SNP, MARC0033464, was present. Annotations from pig reference genome suggested six genes (GRM4, HMGA1, NUDT3, RPS10, SPDEF and PACSIN1) in block 1 (495 kb), and one gene (SCUBE3) in block 3 (124 kb). Functional analysis indicated that HMGA1 and SCUBE3 genes are the potential genes controlling BH, BL, and RC in pigs, with an application in breeding programs. We screened several candidate intervals and genes based on SNP location and gene function, and predicted their function using bioinformatics analyses.

An f2 pig resource population as a model for genetic studies of obesity and obesity-related diseases in humans: design and genetic parameters

Obesity is a rising worldwide public health problem. Difficulties to precisely measure various obesity traits and the genetic heterogeneity in human have been major impediments to completely disentangle genetic factors causing obesity. The pig is a relevant model for studying human obesity and obesity-related (OOR) traits. Using founder breeds divergent with respect to obesity traits we have created an F2 pig resource population (454 pigs), which has been intensively phenotyped for 36 OOR traits. The main rationale for our study is to characterize the genetic architecture of OOR traits in the F2 pig design, by estimating heritabilities, genetic, and phenotypic correlations using mixed- and multi-trait BLUP animal models. Our analyses revealed high coefficients of variation (15–42%) and moderate to high heritabilities (0.22–0.81) in fatness traits, showing large phenotypic and genetic variation in the F2 population, respectively. This fulfills the purpose of creating a resource population divergent for OOR traits. Strong genetic correlations were found between weight and lean mass at dual-energy x-ray absorptiometry scanning (0.56–0.97). Weight and conformation also showed strong genetic correlations with slaughter traits (e.g., r_g between abdominal circumference and leaf fat at slaughtering: 0.66). Genetic correlations between fat-related traits and the glucose level vary between 0.35 and 0.74 and show a strong correlation between adipose tissue and impaired glucose metabolism. Our power calculations showed a minimum of 80% power for QTL detection for all phenotypes. We revealed genetic correlations at population level, for the first time, for several difficult to measure and novel OOR traits and diseases. The results underpin the potential of the established F2 pig resource population for further genomic, systems genetics, and functional investigations to unravel the genetic background of OOR traits.

Long-term consequences of feed restriction during late pregnancy in goats on feeding behavior and emotional reactivity of female offspring

Feed restriction during pregnancy can have detrimental effects on offspring development both during the juvenile period and during adult life. Long-term effects of maternal feed restriction during the last third of pregnancy on growth, metabolism and behavior of female kids, with a focus on feeding behavior and emotional reactivity, were studied in goats. Female kids born to control (CONT, n=17) or born to feed restricted goats (REST, n=15) were artificially reared and monitored from birth to 24 months of age. Maternal feeding restriction globally reduced live weight (P<0.001) and body condition score (P=0.02) of REST compared to CONT offspring. Females from the REST group had a higher daily feed intake (P=0.05) and tended to eat more rapidly (P=0.09) than females from the CONT group at 12 months of age. One year later, REST goats still ate more than CONT goats (P=0.05). Glucose metabolism did not appear to be modified as no differences were observed in glucose or insulin responses to an intravenous glucose tolerance test. No differences in time budget were found at 12 months of age. However, the HPA axis response to an ACTH injection was greater in REST than in CONT goats: higher peak cortisol concentration (P=0.02) and a greater area under the curve were found (P=0.01) at 14 months of age. In conclusion, maternal feed restriction during late pregnancy modified both feeding behavior and the stress physiology of female offspring for up to 2 years of age. However, the changes observed were small.

High throughput analyses of epistasis for swine body dimensions and organ weights

High throughput analyses were performed to detect epistatic QTL in 17 body dimension and organ weight traits from a large F(2) pig population derived from a White Duroc and Erhualian intercross. The analyses used a nested test framework to handle multiple tests and a combined search algorithm to map epistatic QTL with empirical genome-wide thresholds derived via prior permutation. Alternative statistical models (e.g. including vs. excluding carcass weight as a covariate) were tested to develop an in-depth understanding of the role of epistasis in these kinds of traits. Epistasis signals were detected in only two or three traits under each statistical model studied. The interaction component of each pair of epistatic QTL explained a small proportion (0.7 to 2.1%) of the phenotypic variance in general. About half of the detected epistatic QTL pairs involved one of the two major QTL on porcine chromosomes 7 and 4. In those traits, the Erhualian allele consistently increased the phenotypes for the chromosome 7 QTL but decreased them for the chromosome 4 QTL. Models including carcass weight as covariate detected epistasis in body dimension traits whereas those excluding carcass weight found epistasis in organ weight traits. In addition, the epistasis results suggested that a QTL on chromosome 14 could be important for a number of organ weight traits. Using the high-throughput analysis tool to examine different statistical models was essential for the generation of a complete picture of epistasis in a whole category of traits.

Quantitative trait loci for fatness at growing and reproductive stages in Iberian × Meishan F(2) sows

A considerable number of fatness QTL have been identified in growing pigs, but there is a lack of knowledge about the genetic architecture of this trait in gilts and sows. We have performed a genome scan, in 255 Iberian × Meishan F(2) sows, for backfat thickness (BF) at 150 (BF(150) ) and 210 (BF(210)) days of age, 30 days after conception (BF(30)) and 7-10 days before farrowing (BF(bf)). We have found one BF150 QTL in SSC6 (120 cM) that was highly significant (P < 0.001) at the chromosome-wide level and suggestive at the genome-wide level (P < 0.1). Ten additional chromosome-wide significant QTL were found for sow BF(150) (SSC1, SSC13), BF(210) (SSC6, SSC8, SSC15), BF(30) (SSC5, SSC6) and BF(bf) (SSC1, SSC6, SSC13). The location of several of the BF QTL varied depending on the growing and reproductive status of the sow, suggesting that part of these genetic effects may have a temporal pattern of phenotypic expression.