Assessing population structure and migration patterns of wild boar (Sus scrofa) in Japan.

Geographical wildlife patterns reflect historical range expansion and connectivity and provide insights into wildlife population management. In our large-scale phylogeographic population analysis of wild boars (Sus scrofa leucomystax) in Japan, we identified 15 clusters using 29 microsatellite markers, each structured within a range of approximately 200 km. This suggests that evolution was essentially driven by isolation by distance, and that the range of gene flow was limited. One cluster contained subpopulations located approximately 900 km apart, indicating the occurrence of past anthropogenic introductions. Moreover, we estimated effective migration to visualize the geographic genetic population diversity. This analysis identified six potential barriers, one of which involved large plains and mountainous areas in the Kanto region of eastern Japan. This barrier likely persisted in the two eastern clusters for an extended period, restricting migration to the neighboring areas. Overall, our study sheds light on the demographic history of wild boar in Japan, provides evidence of past anthropogenic introductions from distant areas, and highlights the importance of geographic barriers in shaping genetic diversity and population dynamics. This knowledge will be beneficial for forming informed wildlife management strategies toward the conservation of genetic integrity and ecological balance of wild boar populations in Japan.

Application of linear and machine learning models to genomic prediction of fatty acid composition in Japanese Black cattle.

We collected 3180 records of oleic acid (C18:1) and monounsaturated fatty acid (MUFA) measured using gas chromatography (GC) and 6960 records of C18:1 and MUFA measured using near-infrared spectroscopy (NIRS) in intermuscular fat samples of Japanese Black cattle. We compared genomic prediction performance for four linear models (genomic best linear unbiased prediction [GBLUP], kinship-adjusted multiple loci [KAML], BayesC, and BayesLASSO) and five machine learning models (Gaussian kernel [GK], deep kernel [DK], random forest [RF], extreme gradient boost [XGB], and convolutional neural network [CNN]). For GC-based C18:1 and MUFA, KAML showed the highest accuracies, followed by BayesC, XGB, DK, GK, and BayesLASSO, with more than 6% gain of accuracy by KAML over GBLUP. Meanwhile, DK had the highest prediction accuracy for NIRS-based C18:1 and MUFA, but the difference in accuracies between DK and KAML was slight. For all traits, accuracies of RF and CNN were lower than those of GBLUP. The KAML extends GBLUP methods, of which marker effects are weighted, and involves only additive genetic effects; whereas machine learning methods capture non-additive genetic effects. Thus, KAML is the most suitable method for breeding of fatty acid composition in Japanese Black cattle.

Population structure of Vietnamese pigs using mitochondrial DNA.

The D-loop region on mitochondrial DNA (mtDNA) is frequently used for analyses of maternal lineages within domestic animal species. There are many native pig breeds in Vietnam, but their origins remain unclear. This study investigated maternal lineages using the D-loop region on mtDNA of 260 samples collected from native pigs in 20 provinces across Vietnam. The D-loop region of all samples was amplified and sequenced. We obtained 713 bp sequences of the D-loop region for each sample excluding the repeat region, and variants on this region were used to construct a phylogenetic tree. We detected 50 haplotypes from Vietnamese native pigs, with 27 novel haplotypes. Phylogenetic tree analysis showed two haplotype groups: one for the MTSEA group, frequently found in domestic pigs in the mountainous areas of Cambodia and Laos; and the D2 group, found in pigs originating from Chinese pigs. No European haplotype was found. Haplotypes in northeast Vietnam comprised only haplotypes of the D2 group, whereas in areas from the northwest mountains to the south, we found haplotypes belonging to both the D2 and MTSEA groups. This study suggested that both origins contributed to maternal lineages of current populations of Vietnamese native pigs.

Evaluating the performance of genomic prediction accounting for effects of single nucleotide polymorphism markers in reproductive traits of Japanese Black cattle.

We examined the prediction accuracies of genomic best linear unbiased prediction (GBLUP), various weighted GBLUP according to the degrees of marker effects (WGBLUP) and machine learning (ML) methods, and compared them with traditional BLUP for age at first calving (AFC), calving difficulty (CD), and gestation length in Japanese Black cattle. For WGBLUP, firstly, BayesC and FarmCPU were used to estimate marker effects. Then, we constructed three weighted genomic relationship matrices from information of estimated marker effects in the first step: absolute value of the estimated marker-effect WGBLUP, estimated marker-variance WGBLUP, and genomic-feature WGBLUP. For ML, we applied Gaussian kernel, random forest, extreme gradient boost, and support vector regression. We collected a total of 2583 animals having both phenotypic records and genotypes with 30,105 markers and 16,406 pedigree records. For AFC, prediction accuracies of WGBLUP methods using FarmCPU exceeded BLUP by 25.7%-39.5%. For CD, estimated marker-variance WGBLUP using BayesC achieved the highest prediction accuracy. Among ML methods, extreme gradient boost, support vector regression, and Gaussian kernel increased prediction accuracies by 28.4%, 19.0%, and 36.4% for AFC, CD, and gestation length compared with BLUP, respectively. Thus, prediction performance could be improved using suitable WGBLUP and ML methods according to target reproductive traits for the population used.

Comparing pedigree and genomic inbreeding coefficients, and inbreeding depression of reproductive traits in Japanese Black cattle.

BACKGROUND: Pedigree-based inbreeding coefficients have been generally included in statistical models for genetic evaluation of Japanese Black cattle. The use of genomic data is expected to provide precise assessment of inbreeding level and depression. Recently, many measures have been used for genome-based inbreeding coefficients; however, with no consensus on which is the most appropriate. Therefore, we compared the pedigree- ([Formula: see text]) and multiple genome-based inbreeding coefficients, which were calculated from the genomic relationship matrix with observed allele frequencies ([Formula: see text]), correlation between uniting gametes ([Formula: see text]), the observed vs expected number of homozygous genotypes ([Formula: see text]), runs of homozygosity (ROH) segments ([Formula: see text]) and heterozygosity by descent segments ([Formula: see text]). We quantified inbreeding depression from estimating regression coefficients of inbreeding coefficients on three reproductive traits: age at first calving (AFC), calving difficulty (CD) and gestation length (GL) in Japanese Black cattle. RESULTS: The highest correlations with [Formula: see text] were for [Formula: see text] (0.86) and [Formula: see text] (0.85) whereas [Formula: see text] and [Formula: see text] provided weak correlations with [Formula: see text], with range 0.33-0.55. Except for [Formula: see text] and [Formula: see text], there were strong correlations among genome-based inbreeding coefficients ([Formula: see text] 0.94). The estimates of regression coefficients of inbreeding depression for [Formula: see text] was 2.1 for AFC, 0.63 for CD and -1.21 for GL, respectively, but [Formula: see text] had no significant effects on all traits. Genome-based inbreeding coefficients provided larger effects on all reproductive traits than [Formula: see text]. In particular, for CD, all estimated regression coefficients for genome-based inbreeding coefficients were significant, and for GL, that for [Formula: see text] had a significant.. Although there were no significant effects when using overall genome-level inbreeding coefficients for AFC and GL, [Formula: see text] provided significant effects at chromosomal level in four chromosomes for AFC, three chromosomes for CD, and two chromosomes for GL. In addition, similar results were obtained for [Formula: see text]. CONCLUSIONS: Genome-based inbreeding coefficients can capture more phenotypic variation than [Formula: see text]. In particular, [Formula: see text] and [Formula: see text] can be considered good estimators for quantifying inbreeding level and identifying inbreeding depression at the chromosome level. These findings might improve the quantification of inbreeding and breeding programs using genome-based inbreeding coefficients.

Performance of the No-U-Turn sampler in multi-trait variance component estimation using genomic data.

BACKGROUND: Multi-trait genetic parameter estimation is an important topic for target traits with few records and with a low heritability and when the genetic correlation between target and secondary traits is strong. However, estimating correlations between multiple traits is difficult for both Bayesian and non-Bayesian inferences. We extended a Hamiltonian Monte Carlo approach using the No-U-Turn Sampler (NUTS) to a multi-trait animal model and investigated the performance of estimating (co)variance components and breeding values, compared to those for restricted maximum likelihood and Gibbs sampling with a population size of 2314 and 578 in a simulated and real pig dataset, respectively. For real data, we used publicly available data for three traits from the Pig Improvement Company (PIC). For simulation data, we generated two quantitative traits by using the genotypes of the PIC data. For NUTS, two prior distributions were adopted: Lewandowski-Kurowicka-Joe (LKJ) and inverse-Wishart distributions. RESULTS: For the two simulated traits with heritabilities of 0.1 and 0.5, most estimates of the genetic and residual variances for NUTS with the LKJ prior were closer to the true values and had smaller root mean square errors and smaller mean absolute errors, compared to NUTS with inverse-Wishart priors, Gibbs sampling and restricted maximum likelihood. The accuracies of estimated breeding values for lowly heritable traits for NUTS with LKJ and inverse-Wishart priors were 14.8% and 11.1% higher than those for Gibbs sampling and restricted maximum likelihood, respectively, with a population size of 578. For the trivariate animal model with real pig data, the estimates of the genetic correlations for Gibbs sampling and restricted maximum likelihood were strongly affected by population size, compared to NUTS. For both the simulated and pig data, the genetic variances and heritabilities for NUTS with an inverse-Wishart prior were overestimated for low-heritability traits when the population size was 578. CONCLUSIONS: The accuracies of variance components and breeding values estimates for a multi-trait animal model using NUTS with the LKJ prior were equal to or higher than those obtained with restricted maximum likelihood or Gibbs sampling. Therefore, when the population size is small, NUTS with an LKJ prior could be an alternative sampling method for multi-trait analysis in animal breeding.

Detection of non-reference porcine endogenous retrovirus loci in the Vietnamese native pig genome.

The Vietnamese native pig (VnP)-a porcine breed with a small body-has proven suitable as a biomedical animal model. Here, we demonstrate that, compared to other breeds, VnPs have fewer copies of porcine endogenous retroviruses (PERVs), which pose a risk for xenotransplantation of pig organs to humans. More specifically, we sought to characterize non-reference PERVs (nrPERVs) that were previously unidentified in the reference genome. To this end, we used whole-genome sequencing data to identify nrPERV loci with long terminal repeat (LTR) sequences in VnPs. RetroSeq was used to estimate nrPERV loci based on the most current porcine reference genome (Sscrofa11.1). LTRs were detected using de novo sequencing read assembly near the loci containing the target site duplication sequences in the inferred regions. A total of 21 non-reference LTR loci were identified and separated into two subtypes based on phylogenetic analysis. Moreover, PERVs within the detected LTR loci were identified, the presence of which was confirmed using conventional PCR and Sanger sequencing. These novel loci represent previously unknown PERVs as they have not been identified in the porcine reference genome. Thus, our RetroSeq method accurately detects novel PERV loci, and can be applied for development of a useful biomedical model.

An R package VIGoR for joint estimation of multiple linear learners with variational Bayesian inference.

SUMMARY: An R package that can implement multiple linear learners, including penalized regression and regression with spike and slab priors, in a single model has been developed. Solutions are obtained with fast minorize-maximization algorithms in the framework of variational Bayesian inference. This package helps to incorporate multimodal and high-dimensional explanatory variables in a single regression model. AVAILABILITY AND IMPLEMENTATION: The R package VIGoR (Variational Bayesian Inference for Genome-wide Regression) is available at the Comprehensive R Archive Network (CRAN) (https://cran.r-project.org/) and at GitHub (https://github.com/Onogi/VIGoR). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Hamiltonian Monte Carlo method for estimating variance components.

A Hamiltonian Monte Carlo algorithm is a Markov chain Monte Carlo method, and the method has a potential to improve estimating parameters effectively. Hamiltonian Monte Carlo is based on Hamiltonian dynamics, and it follows Hamilton's equations, which are expressed as two differential equations. In the sampling process of Hamiltonian Monte Carlo, a numerical integration method called leapfrog integration is used to approximately solve Hamilton's equations, and the integration is required to set the number of discrete time steps and the integration stepsize. These two parameters require some amount of tuning and calibration for effective sampling. In this study, we applied the Hamiltonian Monte Carlo method to animal breeding data and identified the optimal tunings of leapfrog integration for normal and inverse chi-square distributions. Then, using real pig data, we revealed the properties of the Hamiltonian Monte Carlo method with the optimal tuning by applying models including variance explained by pedigree information or genomic information. Compared with the Gibbs sampling method, the Hamiltonian Monte Carlo method had superior performance in both models. We have provided the source codes of this method written in the Fortran language at https://github.com/A-ARAKAWA/HMC.

Effect of a genetic polymorphism in SREBP1 on fatty acid composition and related gene expression in subcutaneous fat tissue of beef cattle breeds.

Sterol regulatory element-binding factor 1 (SREBP1) plays an important role in the lipogenesis which affects fatty acid (FA) composition in backfat and consequently influences beef nutritional quality. This study analyzed the association of 84 bp-indel, both short (S) and long (L) alleles in intron 5 of SREBP1, with FA composition and gene expression of SREBP1 in backfat of northern Spanish beef breeds (Pirenaica, Salers and Holstein-Friesian). Phylogenetic analysis suggests that 84 bp-indel of ruminants is a highly conserved region compared with those in the full-length sequence of intron 5 or mRNA of SREBP1 among species. Overall, higher content of polyunsaturated FAs was observed in SL genotype compared to LL genotype of 84 bp-Indel (p < .05). In particular, in Pirenaica, SL genotype was associated with a higher content of stearic (18:0), α-linolenic (18:3n-3) acid, and total n-3 content (p < .05). However, the gene expression of SREBP1 did not differ among genotypes of 84 bp-Indel (p > .05).

Genetic Characterization of the Local Pirenaica Cattle for Parentage and Traceability Purposes.

Pirenaica is the most important autochthonous cattle breed within the Protected Geographic Indication (PGI) beef quality label in the Basque region, in northern Spain. The short tandem repeats (STRs) are powerful markers to elucidate forensic cases and traceability across the agri-food sector. The main objective of the present work was to study the phylogenetic relationships of Pirenaica cattle and other breeds typically raised in the region and provide the minimum number of STR markers for parentage and traceability purposes. The 30-STR panel recommended by the International Society of Animal Genetics-Food and Agriculture Organization of the United Nations (ISAG-FAO) was compared against other commercial STR panels. The 30-STR panel showed a combined matching probability of 1.89 × 10-25 and a power of exclusion for duos of 0.99998. However, commercial STR panels showed a limited efficiency for a reliable parentage analysis in Pirenaica, and at least a 21-STR panel is needed to reach a power of exclusion of 0.9999. Machine-learning analysis also demonstrated a 95% accuracy in assignments selecting the markers with the highest FST in Pirenaica individuals. Overall, the present study shows the genetic characterization of Pirenaica and its phylogeny compared with other breeds typically raised in the Basque region. Finally, a 21-STR panel with the highest FST markers is proposed for a confident parentage analysis and high traceability.

Differential Metabolomics Profiles Identified by CE-TOFMS between High and Low Intramuscular Fat Amount in Fattening Pigs.

The amount of intramuscular fat (IMF) present in the loin eye area is one of the most important characteristics of high-quality pork. IMF measurements are currently impractical without a labor-intensive process. Metabolomic profiling could be used as an IMF indicator to avoid this process; however, no studies have investigated their use during the fattening period of pigs. This study examined the metabolite profiles in the plasma of two groups of pigs derived from the same Duroc genetic line and fed the same diet. Five plasma samples were collected from each individual the day before slaughter. Capillary electrophoresis-time of flight mass spectrometry (CE-TOFMS) was used to analyze the purified plasma from each sample. Principle component analysis (PCA) and partial least squares (PLS) were used to find the semi-quantitative values of the compounds. The results indicate that branched-chain amino acids are significantly associated with high IMF content, while amino acids are associated with low IMF content. These differences were validated using the quantification analyses by high-performance liquid chromatograph, which supported our results. These results suggest that the concentration of branched-chain amino acids in plasma could be an indicative biomarker for the IMF content in the loin eye area.

The phenotypic characteristics and relational database for Vietnamese native pig populations.

Although there are a number of Vietnamese native pig (VnP) populations, some are on the verge of extinction, and therefore adequate management and conservation are necessary. In this study, we conducted a field survey of VnP populations and analyzed interrelationships among their characteristics. We also established a relational database for management of field data on these populations. For data collection, we conducted interviews with farmers and visual inspection of 32 VnP populations in 22 provinces of Vietnam, as well as taking photographs of individual animals. Data on the characteristics of VnP populations were subjected to multiple correspondence analysis (MCA). For establishment of the database, normalization and table partitioning were performed to eliminate redundancy and ensure consistency of the collected data items. Passport data, characteristics data, and image data were collected from a total of 1,918 VnPs and entered as a normalized table. Upon MCA, most of the populations were not separated from each other, but the Mong Cai, O Lam, and Chu Prong populations were separated from the other populations. Thus, we have constructed a relational database from comprehensive information on the characteristics of VnP populations.

Characteristic features of porcine endogenous retroviruses in Vietnamese native pigs.

We aimed to clarify the genomic characteristics of porcine endogenous retroviruses (PERVs) in Vietnamese native pig (VnP) breeds. First, we investigated genetic polymorphisms in ß- and γ-like PERVs, and we then measured the copy numbers of infectious γ-like PERVs (PERV-A, B, and C). We purified genomic DNA from 15 VnP breeds from 12 regions all over the country and three Western pig breeds as controls, and investigated genetic polymorphisms in all known PERVs, including the beta (ß)1-4 and gamma (γ)1-5 groups. PERVs of ß1, ß2, ß3, and γ4 were highly polymorphic with VnP-specific haplotypes. We did not identify genetic polymorphisms in ß4, γ1, or γ2 PERVs. We then applied a real-time polymerase chain reaction-based method to estimate copy numbers of the gag, pol, and env genes of γ1 PERVs (defined as A, B, and C). VnP breeds showed significantly lower copy number of the PERV genes compared with the Western pig breeds (on average, 16.2 and 35.7 copies, respectively, p < .05). Two VnP breeds showed significantly higher copy number compared with the other VnPs (p < .05). Our results elucidated that VnPs have specific haplotypes and a low copy number of PERV genes.

Evaluation of genetic richness among Vietnamese native pig breeds using microsatellite markers.

We have elucidated genetic relationships of Vietnamese native pigs (VNP) using preliminarily collected samples by a single-nucleotide polymorphism (SNP) array. In order to confirm our previous results and compare with the results of a previous study using microsatellite (MS) markers, we aimed to characterize genetic diversity and population structure in wider varieties (24 breeds from 21 Provinces) of VNP across the country using 20 polymorphic MS markers recommended by ISAG/FAO (International Society for Animal Genetics/Food and Agriculture Organization) for diversity study. In this study, we collected 1,136 DNA samples of the VNPs and three exotic breeds. Our results revealed that the average number of alleles and allelic richness across the loci in VNPs were 10.0 and 7.6, which were higher than those of exotic breeds. Genomic components among VNPs were subjected to the sampling locations. Interestingly, Co Binh Thuan showed remarkable genetic feature compared to the other VNPs, because the habitation of Co Binh Thuan was relatively far from the other breeds. The results of this study provided useful information for exploitation, conservation, and development trends of the VNP breeds. More recently, African swine fever caused significant damage to most of the VNP populations. Therefore, our findings will help a reconstruction scheme of the VNP genetic resources.

Evaluation of the genetic structure of indigenous Okinawa Agu pigs using microsatellite markers.

OBJECTIVE: Agu pigs are indigenous to the Okinawa prefecture, which is the southernmost region of Japan. Agu pigs were exposed to a genetic bottleneck during the 20th century, due to the introduction of European pig breeds. The objective of this study was to elucidate the genetic structure of Agu pigs and to determine their relationships with those of five European breeds, two Chinese breeds and Ryukyu wild boar using microsatellite markers. METHODS: A total of 203 DNA samples consist of 8 pig breeds were used in this study. Genotyping was performed using 21 microsatellite markers distributed across 17 chromosomes. RESULTS: Numbers of effective alleles in Agu pigs were fewer than in European breeds and Ryukyu wild boar. Among domestic pigs, Agu pigs had the lowest heterozygosity (0.423) and highest inbreeding coefficient (FIS = 0.202), indicating a severe loss of heterozygosity in Agu pigs possibly due to inbreeding. Neighbor-joining tree analysis was performed based on Reynolds' genetic distances, which clustered Agu pigs with Duroc pigs. However, principal component analysis revealed a unique genetic position of the Agu pig, and the second principal component separated Agu pigs from all other breeds. Structure analysis with the optimal assumption of seven groups (K = 7) indicated that Agu pigs form an independent cluster from the other breeds. In addition, high and significant FST values (0.235-0.413) were identified between Agu pigs and the other breeds. CONCLUSION: This study revealed a substantial loss of genetic diversity among Agu pigs due to inbreeding. Our data also suggest that Agu pigs have a distinctive genetic structure, although gene flows from European breeds were observed.

Performance of Hamiltonian Monte Carlo and No-U-Turn Sampler for estimating genetic parameters and breeding values.

BACKGROUND: Hamiltonian Monte Carlo is one of the algorithms of the Markov chain Monte Carlo method that uses Hamiltonian dynamics to propose samples that follow a target distribution. The method can avoid the random walk behavior to achieve a more effective and consistent exploration of the probability space and sensitivity to correlated parameters, which are shortcomings that plague many Markov chain Monte Carlo methods. However, the performance of Hamiltonian Monte Carlo is highly sensitive to two hyperparameters. The No-U-Turn Sampler, an extension of Hamiltonian Monte Carlo, was recently introduced to automate the tuning of these hyperparameters. Thus, this study compared the performances of Gibbs sampling, Hamiltonian Monte Carlo, and the No-U-Turn Sampler for estimating genetic parameters and breeding values as well as sampling qualities in both simulated and real pig data. For all datasets, we used a pedigree-based univariate linear mixed model. RESULTS: For all datasets, the No-U-Turn Sampler and Gibbs sampling performed comparably regarding the estimation of heritabilities and accuracies of breeding values. Compared with Gibbs sampling, the estimates of effective sample sizes for simulated and pig data with the No-U-Turn Sampler were 3.2 to 22.6 and 3.5 to 5.9 times larger, respectively. Autocorrelations decreased more quickly with the No-U-Turn Sampler than with Gibbs sampling. When true heritability was low in the simulated data, the skewness of the marginal posterior distributions with the No-U-Turn Sampler was smaller than that with Gibbs sampling. The performance of Hamiltonian Monte Carlo for sampling quality was inferior to that of No-U-Turn Sampler in the simulated data. Moreover, Hamiltonian Monte Carlo could not estimate genetic parameters because of difficulties with the hyperparameter settings with pig data. CONCLUSIONS: The No-U-Turn Sampler is a promising sampling method for animal breeding because of its good sampling qualities: large effective sample sizes, low autocorrelations, and low skewness of marginal posterior distributions, particularly when heritability is low. Meanwhile, Hamiltonian Monte Carlo failed to converge with a simple univariate model for pig data. Thus, it might be difficult to use Hamiltonian Monte Carlo for usual complex models in animal breeding.

Maternal lineage of Okinawa indigenous Agu pig inferred from mitochondrial DNA control region.

OBJECTIVE: The Agu is the only native pig breed in Japan, which is reared in Okinawa prefecture, the southernmost region in Japan. Its origins are considered to be of Asian lineage; however, the genetic background of the Agu is still unclear. The objective of this study was to elucidate the maternal lineage of the Okinawa indigenous Agu pig with the use of the mitochondrial DNA (mtDNA) control region. METHODS: The mtDNA control regions of Agu pigs were sequenced and the phylogenetic relationship among Agu, East Asian and European pigs was investigated with the use of 78 Agu individuals. RESULTS: Twenty-seven polymorphic sites and five different haplotypes (type 1 to type 5) were identified within the Agu population. Phylogenetic analysis indicated that types 1 and 2 were included in East Asian lineages; however, the remaining types 3, 4, and 5 were of European lineages, which showed a gene flow from European pigs in the 20th century. Sixty-seven out of 78 Agu individuals (85.9%) possessed mtDNA haplotypes 1 and 2 of the East Asian lineage, which were identical to two haplotypes of ancient mtDNA (7,200 to 1,700 years before the present) excavated at archaeological sites in Okinawa. CONCLUSION: This study confirmed that the East Asian lineage is dominant in the maternal genetic background of the Agu population, supporting the hypothesis that the ancestors of the Agu pig were introduced from the Asian continent.

Differences in gene expression profiles for subcutaneous adipose, liver, and skeletal muscle tissues between Meishan and Landrace pigs with different backfat thicknesses.

Backfat thickness is one of the most important traits of commercially raised pigs. Meishan pigs are renowned for having thicker backfat than Landrace pigs. To examine the genetic factors responsible for the differences, we first produced female crossbred pig lines by mating Landrace (L) × Large White (W) × Duroc (D) females (LWD) with Landrace (L) or Meishan (M) boars (i.e., LWD × L = LWDL for Landrace offspring and LWD × M = LWDM for the Meishan offspring). We confirmed that LWDM pigs indeed had a thicker backfat than LWDL pigs. Next, we performed gene expression microarray analysis in both genetic lines to examine differentially expressed genes (DEGs) in energy metabolism-related tissues, subcutaneous adipose (fat), liver, and longissimus dorsi muscle tissues. We analyzed the annotation of DEGs (2-fold cutoff) to functionally categorize them by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. The number of DEGs in muscle tissues of both lines was much less than that in fat and liver tissues, indicating that DEGs in muscle tissues may not contribute much to differences in backfat thickness. In contrast, several genes related to muscle (in fat tissue) and lipid metabolism (in liver tissue) were more upregulated in LWDM pigs than LWDL pigs, indicating that those DEGs might be responsible for differences in backfat thickness. The different genome-wide gene expression profiles in the fat, liver, and muscle tissues between genetic lines can provide useful information for pig breeders.

Distinct correlations between lipogenic gene expression and fatty acid composition of subcutaneous fat among cattle breeds.

BACKGROUND: The fatty acid (FA) composition of adipose tissue influences the nutritional quality of meat products. The unsaturation level of FAs is determined by fatty acid desaturases such as stearoyl-CoA desaturases (SCDs), which are under control of the transcription factor sterol regulatory element-binding protein (SREBP). Differences in SCD genotype may thus confer variations in lipid metabolism and FA content among cattle breeds. This study investigated correlations between FA composition and lipogenic gene expression levels in the subcutaneous adipose tissue of beef cattle breeds of different gender from the Basque region of northern Spain. Pirenaica is the most important beef cattle breed in northern Spain, while Salers cattle and Holstein-Friesian cull cows are also an integral part of the regional beef supply. RESULTS: Pirenaica heifers showed higher monounsaturated FA (MUFA) and conjugated linoleic acid (CLA) contents in subcutaneous adipose tissue than other breeds (P < 0.001). Alternatively, Salers bulls produced the highest oleic acid content, followed by Pirenaica heifers (P < 0.001). There was substantial variability in SCD gene expression among breeds, consistent with these differences in MUFA and CLA content. Correlations between SCD1 expression and most FA desaturation indexes (DIs) were positive in Salers (P < 0.05) and Pirenaica bulls, while, in general, SCD5 expression showed few significant correlations with DIs. There was a significant linear correlation between SCD1 and SRBEP1 in all breeds, suggesting strong regulation of SCD1 expression by SRBEP1. Pirenaica heifers showed a stronger correlation between SCD1 and SREBP1 than Pirenaica bulls. We also observed a opposite relationship between SCD1 and SCD5 expression levels and opposite associations of isoform expression levels with the ∆9 desaturation indexes. CONCLUSIONS: These results suggest that the relationships between FA composition and lipogenic gene expression are influenced by breed and sex. The opposite relationship between SCD isoforms suggests a compensatory regulation of total SCD activity, while opposite relationships between SCD isoforms and desaturation indexes, specially 9c-14:1 DI, previously reported as an indicator of SCD activity, may reflect distinct activities of SCD1 and SCD5 in regulation of FA content. These findings may be useful for beef/dairy breeding and feeding programs to supply nutritionally favorable products.