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

Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations

South Africa boasts a diverse range of pig populations, encompassing intensively raised commercial breeds, as well as indigenous and village pigs reared under low-input production systems. The aim of this study was to investigate how natural and artificial selection have shaped the genomic landscape of South African pig populations sampled from different genetic backgrounds and production systems. For this purpose, the integrated haplotype score (iHS), as well as cross population extended haplotype homozygosity (XP-EHH) and Lewontin and Krakauer's extension of the Fst statistic based on haplotype information (HapFLK) were utilised. Our results revealed several population-specific signatures of selection associated with the different production systems. The importance of natural selection in village populations was highlighted, as the majority of genomic regions under selection were identified in these populations. Regions under natural and artificial selection causing the distinct genetic footprints of these populations also allow for the identification of genes and pathways that may influence production and adaptation. In the context of intensively raised commercial pig breeds (Large White, Kolbroek, and Windsnyer), the identified regions included quantitative loci (QTLs) associated with economically important traits. For example, meat and carcass QTLs were prevalent in all the populations, showing the potential of village and indigenous populations' ability to be managed and improved for such traits. Results of this study therefore increase our understanding of the intricate interplay between selection pressures, genomic adaptations, and desirable traits within South African pig populations.

Modeling microRNA-driven post-transcriptional regulation using exon-intron split analysis in pigs

The contribution of microRNAs (miRNAs) to mRNA post-transcriptional regulation has often been explored by the post hoc selection of downregulated genes and determining whether they harbor binding sites for miRNAs of interest. This approach, however, does not discriminate whether these mRNAs are also downregulated at the transcriptional level. Here, we have characterized the transcriptional and post-transcriptional changes in mRNA expression in two porcine tissues: gluteus medius muscle of fasted and fed Duroc gilts and adipose tissue of lean and obese Duroc-Göttingen minipigs. Exon-intron split analysis of RNA-seq data allowed us to identify downregulated mRNAs with high post-transcriptional signals in fed or obese states, and we assessed whether they harbor binding sites for upregulated miRNAs in any of these two physiological states. We found 26 downregulated mRNAs with high post-transcriptional signals in the muscle of fed gilts and 21 of these were predicted targets of miRNAs upregulated in fed pigs. For adipose tissue, 44 downregulated mRNAs in obese minipigs displayed high post-transcriptional signals, and 25 of these were predicted targets of miRNAs upregulated in the obese state. These results suggest that the contribution of miRNAs to mRNA repression is more prominent in the skeletal muscle system. Finally, we identified several genes that may play relevant roles in the energy homeostasis of the pig skeletal muscle (DKK2 and PDK4) and adipose (SESN3 and ESRRG) tissues. By differentiating transcriptional from post-transcriptional changes in mRNA expression, exon-intron split analysis provides a valuable view of the regulation of gene expression, complementary to canonical differential expression analyses.

Weighted single-step GWAS for body mass index and scans for recent signatures of selection in Yorkshire pigs

Controlling extra fat deposition is economically favorable in modern swine industry. Understanding the genetic architecture of fat deposition traits such as body mass index (BMI) can help in improving genomic selection for such traits. We utilized a weighted single-step genome-wide association study (WssGWAS) to detect genetic regions and candidate genes associated with BMI in a Yorkshire pig population. Three extended haplotype homozygosity (EHH)-related statistics were also incorporated within a de-correlated composite of multiple signals (DCMS) framework to detect recent selection signatures signals. Overall, the full pedigree consisted of 7,016 pigs, of which 5,561 had BMI records and 598 pigs were genotyped with an 80 K single nucleotide polymorphism (SNP) array. Results showed that the most significant windows (top 15) explained 9.35% of BMI genetic variance. Several genes were detected in regions previously associated with pig fat deposition traits and treated as potential candidate genes for BMI in Yorkshire pigs: FTMT, SRFBP1, KHDRBS3, FOXG1, SOD3, LRRC32, TSKU, ACER3, B3GNT6, CCDC201, ADCY1, RAMP3, TBRG4, CCM2. Signature of selection analysis revealed multiple candidate genes previously associated with various economic traits. However, BMI genetic variance explained by regions under selection pressure was minimal (1.31%). In conclusion, candidate genes associated with Yorkshire pigs’ BMI trait were identified using WssGWAS. Gene enrichment analysis indicated that the identified candidate genes were enriched in the insulin secretion pathway. We anticipate that these results further advance our understanding of the genetic architecture of BMI in Yorkshire pigs and provide information for genomic selection for fat deposition in this breed.

Obesity Animal Models for Acupuncture and Related Therapy Research Studies

Obesity and related diseases are considered as pandemic representing a worldwide threat for health. Animal models are critical to validate the effects and understand the mechanisms related to classical or innovative preventive and therapeutic strategies. It is, therefore, important to identify the best animal models for translational research, using different evaluation criteria such as the face, construct, and predictive validity. Because the pharmacological treatments and surgical interventions currently used for treating obesity often present many undesirable side effects, relatively high relapse probabilities, acupuncture, electroacupuncture (EA), and related therapies have gained more popularity and attention. Many kinds of experimental animal models have been used for obesity research studies, but in the context of acupuncture, most of the studies were performed in rodent obesity models. Though, are these obesity rodent models really the best for acupuncture or related therapies research studies? In this study, we review different obesity animal models that have been used over the past 10 years for acupuncture and EA research studies. We present their respective advantages, disadvantages, and specific constraints. With the development of research on acupuncture and EA and the increasing interest regarding these approaches, proper animal models are critical for preclinical studies aiming at developing future clinical trials in the human. The aim of the present study is to provide researchers with information and guidance related to the preclinical models that are currently available to investigate the outcomes of acupuncture and related therapies.

Identification of three new microsatellites and their effects on body measurement traits in pigs using time of flight-mass spectrometry (TOF-MS)

The body status of livestock affects their physiological function and productive performances. Microsatellites, one of the most used DNA markers, have been found to be associated with pig productive traits. However, their identifications and effects on body measurement traits of the Chinese Qinghai Bamei pig still uncovered. According to our previous sequencing data, in this study, three novel microsatellites were found in this breed. Using time of flight-mass spectrometry (TOF-MS) method, these microsatellites were further identified in a large Bamei pig population. TOF-MS spectra showed that there are three microsatellites loci, named P1, P2 and P3. These microsatellites were linkage equilibrium based on the values of D' and r² tests. Association results demonstrated that P1 locus was associated with the body length, body height and chest width and the beneficial genotype was 150-/150-bp (p < 0.05); and P2 locus was associated with the body height (p < 0.05), and the 145-/145-bp, 145-/147-bp and 145-/149-bp were claimed as favorable genotypes and 145-bp allele was considered as the favorable allele. These findings suggested that P1 and P2 microsatellites might be considered as the candidate genetic markers to select pigs with superior body sizes, especially in local breed.

Unraveling molecular mechanisms involved in the development of leptin resistance using the pig as a model

The increase in obesity worldwide underlines the need for research concerning its metabolic and genetic determinants. One of the most intriguing mechanisms regarding obesity involves leptin and its signaling cascade. Leptin is a key regulator contributing to the fine-tuned crosstalk between nutrient availability and appetite signaling in the central nervous system. Owing to ethical concerns, many human tissues are not readily available and pigs can serve as a good animal model owing to their comparable anatomy, metabolism and genetics. In the present study, we utilized the pig to investigate the possible impact of increased adiposity on the development of alterations within the leptin signaling pathway. Two divergent groups of pigs (High and Low) were defined based on a high and low amount of mesenteric fat. Cortex, cerebellum, hypothalamus, mesenteric, subcutaneous and retroperitoneal fat tissues were used to study changes in expression levels of 94 mRNA transcripts related to the leptin signaling pathway using the qPCR approach. No significant differences were found at the central nervous system, whereas the expression level of STAT1 was reduced in mesenteric fat and leptin (LEP) and interleukin 6 (IL6) were shown to be consistently increased in all analyzed fat compartments from pigs with a high amount of mesenteric fat. These results could imply the onset of leptin and pro-inflammatory cytokine overexpression at early stages of obesity in the analyzed pigs without affecting any key components in the central nervous system. Thus, these pigs showing a unique leptin deregulation in adipose tissues could be a useful translational resource for studies of obesity and leptin resistance phenotypes.

Phenotyping of the Visceral Adipose Tissue Using Dual Energy X-Ray Absorptiometry (DXA) and Magnetic Resonance Imaging (MRI) in Pigs

The objective of this study was to phenotype visceral adipose tissue (VAT) in pigs. In this context, the ability to detect VAT by using the DXA CoreScan mode within the enCORE software, version 17 (GE Healthcare) was evaluated in comparison with MRI measurements (Siemens Magnetom C!) of the same body region. A number of 120 crossbred pigs of the F1 and F2 generation, with the parental breeds Large White, Landrace, Piétrain, and Duroc, were examined at an age of 150 days. A whole-body scan in two different modes ("thick", "standard") was carried out by a GE Lunar iDXA scanner. Very strong relationships (R² = 0.95, RMSE = 175cm³) were found for VAT between the two DXA modes. The comparison of VAT measured by MRI and DXA shows high linear relationships ("thick": R² = 0.76, RMSE = 399.25cm³/"standard": R² = 0.71, RMSE = 443.42cm³), but is biased, according to the Bland-Altman analysis. A variance analysis of VAT shows significant differences for both DXA modes and for MRI between male and female pigs, as well as between F1 and F2. In conclusion, DXA "CoreScan" has the ability to estimate VAT in pigs with a close relationship to MRI but needs bias correction.

"Sex" and body region effects on bone mineralization in male pigs

Lameness in pigs is one of the major reasons for culling and early losses in pigs. This can be linked to osteoporosis due to pathologic alterations in bone mineral density (BMD) or bone mineral content (BMC) and may also be linked to the sex. Dealing with the ban on piglet castration without anaesthesia in Germany 2021, we have three male “sex” types: entire boars (EB), immunocastrated boars (IB), and surgically castrated boars (SB). The hypothesis of the present study is that BMC or BMD varies between different male sex types. If sex has an effect on bone mineralization (BMC or BMD) and if this affects leg health, it could result in more lameness and problems during fattening in the negatively affected sex type. The present study evaluated bone mineralization (in terms of BMD and BMC) and body composition traits using dual-energy X-ray absorptiometry (DXA) three times during growth at 30, 50, and 90 kg live body weight. Nine body regions were analysed for bone mineral traits and compared for different male sex types and the fattening season. Significant differences were found regarding BMD (and BMC) among EB, IB, and SB for whole-body BMD (BMC). Additionally significant differences were found in the front and lower hind limbs, where SB showed a significantly higher BMD compared to EB, with IB in between. Additionally regional differences were detected among the groups. Further studies are needed to evaluate the effect of these differences in bone mineralization on leg health.

Epigenetic and Transcriptomic Characterization of Pure Adipocyte Fractions From Obese Pigs Identifies Candidate Pathways Controlling Metabolism

Reprogramming of adipocyte function in obesity is implicated in metabolic disorders like type 2 diabetes. Here, we used the pig, an animal model sharing many physiological and pathophysiological similarities with humans, to perform in-depth epigenomic and transcriptomic characterization of pure adipocyte fractions. Using a combined DNA methylation capture sequencing and Reduced Representation bisulfite sequencing (RRBS) strategy in 11 lean and 12 obese pigs, we identified in 3529 differentially methylated regions (DMRs) located at close proximity to-, or within genes in the adipocytes. By sequencing of the transcriptome from the same fraction of isolated adipocytes, we identified 276 differentially expressed transcripts with at least one or more DMR. These transcripts were over-represented in gene pathways related to MAPK, metabolic and insulin signaling. Using a candidate gene approach, we further characterized 13 genes potentially regulated by DNA methylation and identified putative transcription factor binding sites that could be affected by the differential methylation in obesity. Our data constitute a valuable resource for further investigations aiming to delineate the epigenetic etiology of metabolic disorders.

High-throughput sequencing reveals biofluid exosomal miRNAs associated with immunity in pigs

Large numbers of miRNAs are found in biofluid exosomes. We isolated ~50-200 nm diameter exosomes from four types of porcine biofluid (urine, plasma, semen, and bile) using serial centrifugation and ultracentrifugation procedures. A total of 42.15 M raw data were generated from four small RNA libraries. This produced 40.17 M map-able sequences, of which we identified 204 conserved miRNAs, and 190 novel candidate miRNAs. Furthermore, we identified 34 miRNAs specifically expressed in only one library, all with well-characterized immune-related functions. A set of five universally abundant miRNAs (miR-148a-3p, miR-21-5p, let-7f-5p, let-7i-5p, and miR-99a-5p) across all four biofluids was also found. Function enrichment analysis revealed that the target genes of the five ubiquitous miRNAs are primarily involved in immune and RNA metabolic processes. In summary, our findings suggest that porcine biofluid exosomes contain a large number of miRNAs, many of which may be crucial regulators of the immune system.

An Epigenome-Wide DNA Methylation Map of Testis in Pigs for Study of Complex Traits

Epigenetic changes are important for understanding complex trait variation and inheritance in pigs that are also a valuable biomedical model for human health research. Testis is the main organ for reproduction and boar taint in pigs; however, there have been no studies to-date on adult pig testis epigenome. The main objective of this study was to establish a genome-wide DNA methylation map of pig testis that would help identify candidate epigenetic biomarkers and methylated genes for complex traits such as male reproduction, fertility or boar taint. Reduced Representation Bisulfite Sequencing (RRBS) was used to study methylation levels of cytosine in nine pig testis samples. The results showed that genome-wide methylation status of nine samples overlapped greatly and their variation among pigs were low. The methylation levels of promoter, exon, intron, cytosine and guanine dinucleotide (CpG) islands and CpG island shores regions were 0.15, 0.47, 0.55, 0.39, and 0.53, respectively. Cytosines binding to CpG islands showed different methylation levels between exon and intron regions. All methylation levels of CpG islands were lower than CpG island shores in different genic features. The distribution of 12,738 differentially methylated cytosines (DMCs) within CpG islands, CpG island shores and other regions was 36.86, 21.65, and 41.49%, respectively, and was 0.33, 1.71, 5.95, and 92.01% in promoter, exon, intron and intergenic regions, respectively. Methylation levels of DMCs in promoter, exon and intron regions were significantly different between CpG islands and CpG island shores (P < 0.05). A total of 898 genes with 2089 DMCs were enriched in 112 Gene Ontology (GO) terms. Fifteen methylated genes from our study were associated with fertility or boar taint traits. Our analysis revealed the methylation patterns in different genic features and CpG island regions of testis in pigs, and summarized several candidate genes associated with DMCs and the involved GO terms. These findings are helpful to understand the relationship between DNA methylation and genic CpG islands, to provide candidate epigenetic regions or biomarkers for pig production and welfare and for translational epigenomic studies that use pigs as an animal model for human research.

Haplotypes on pig chromosome 3 distinguish metabolically healthy from unhealthy obese individuals

We have established a pig resource population specifically designed to elucidate the genetics involved in development of obesity and obesity related co-morbidities by crossing the obesity prone Göttingen Minipig breed with two lean production pig breeds. In this study we have performed genome wide association (GWA) to identify loci with effect on blood lipid levels. The most significantly associated single nucleotide polymorphisms (SNPs) were used for linkage disequilibrium (LD) and haplotype analyses. Three separate haploblocks which influence the ratio between high density lipoprotein cholesterol and total cholesterol (HDL-C/CT), triglycerides (TG) and low density lipoprotein cholesterol (LDL-C) levels respectively were identified on Sus Scrofa chromosome 3 (SSC3). Large additive genetic effects were found for the HDL-C/CT and LDL-C haplotypes. Haplotypes segregating from Göttingen Minipigs were shown to impose a positive effect on blood lipid levels. Thus, the genetic profile of the Göttingen Minipig breed seems to support a phenotype comparable to the metabolic healthy obese (MHO) phenotype in humans.

Identification of protein-damaging mutations in 10 swine taste receptors and 191 appetite-reward genes

Background

Taste receptors (TASRs) are essential for the body’s recognition of chemical compounds. In the tongue, TASRs sense the sweet and umami and the toxin-related bitter taste thus promoting a particular eating behaviour. Moreover, their relevance in other organs is now becoming evident. In the intestine, they regulate nutrient absorption and gut motility. Upon ligand binding, TASRs activate the appetite-reward circuitry to signal the nervous system and keep body homeostasis. With the aim to identify genetic variation in the swine TASRs and in the genes from the appetite and the reward pathways, we have sequenced the exons of 201 TASRs and appetite-reward genes from 304 pigs belonging to ten breeds, wild boars and to two phenotypically extreme groups from a F₂ resource with data on growth and fat deposition.

Results

We identified 2,766 coding variants 395 of which were predicted to have a strong impact on protein sequence and function. 334 variants were present in only one breed and at predicted alternative allele frequency (pAAF) ≥ 0.1. The Asian pigs and the wild boars showed the largest proportion of breed specific variants. We also compared the pAAF of the two F₂ groups and found that variants in TAS2R39 and CD36 display significant differences suggesting that these genes could influence growth and fat deposition. We developed a 128-variant genotyping assay and confirmed 57 of these variants.

Conclusions

We have identified thousands of variants affecting TASRs as well as genes involved in the appetite and the reward mechanisms. Some of these genes have been already associated to taste preferences, appetite or behaviour in humans and mouse. We have also detected indications of a potential relationship of some of these genes with growth and fat deposition, which could have been caused by changes in taste preferences, appetite or reward and ultimately impact on food intake. A genotyping array with 57 variants in 31 of these genes is now available for genotyping and start elucidating the impact of genetic variation in these genes on pig biology and breeding.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2972-z) contains supplementary material, which is available to authorized users.

A GWA study reveals genetic loci for body conformation traits in Chinese Laiwu pigs and its implications for human BMI

Pigs share numerous physiological and phenotypic similarities with human and thus have been considered as a good model in nonrodent mammals for the study of genetic basis of human obesity. Researches on candidate genes for obesity traits have successfully identified some common genes between humans and pigs. However, few studies have assessed how many similarities exist between the genetic architecture of obesity in pigs and humans by large-scale comparative genomics. Here, we performed a genome-wide association study (GWAS) using the porcine 60 K SNP Beadchip for BMI and other four conformation traits at three different ages in a Chinese Laiwu pig population, which shows a large variability in fat deposition. In total, 35 SNPs were found to be significant at Bonferroni-corrected 5 % chromosome-wise level (P = 2.13 × 10^-5) and 88 SNPs had suggestive (P < 10^-4) association with the conformation traits. Some SNPs showed age-dependent association. Intriguingly, out of 32 regions associated with BMI in pigs, 18 were homologous with the loci for BMI in humans. Furthermore, five closest genes to GWAS peaks including HIF1AN, SMYD3, COX10, SLMAP, and GBE1 have been already associated with BMI in humans, which makes them very promising candidates for these QTLs. The result of GO analysis provided strong support to the fact that mitochondria and synapse play important roles in obesity susceptibility, which is consistent with previous findings on human obesity, and it also implicated new gene sets related to chromatin modification and Ig-like C2-type 5 domain. Therefore, these results not only provide new insights into the genetic architecture of BMI in pigs but also highlight that humans and pigs share the significant overlap of obesity-related genes.

Altered Methylation Profile of Lymphocytes Is Concordant with Perturbation of Lipids Metabolism and Inflammatory Response in Obesity

Obesity is associated with immunological perturbations that contribute to insulin resistance. Epigenetic mechanisms can control immune functions and have been linked to metabolic complications, although their contribution to insulin resistance still remains unclear. In this study, we investigated the link between metabolic dysfunction and immune alterations with the epigenetic signature in leukocytes in a porcine model of obesity. Global DNA methylation of circulating leukocytes, adipose tissue leukocyte trafficking, and macrophage polarisation were established by flow cytometry. Adipose tissue inflammation and metabolic function were further characterised by quantification of metabolites and expression levels of genes associated with obesity and inflammation. Here we show that obese pigs showed bigger visceral fat pads, higher levels of circulating LDL cholesterol, and impaired glucose tolerance. These changes coincided with impaired metabolism, sustained macrophages infiltration, and increased inflammation in the adipose tissue. Those immune alterations were linked to global DNA hypermethylation in both B-cells and T-cells. Our results provide novel insight into the possible contribution of immune cell epigenetics into the immunological disturbances observed in obesity. The dramatic changes in the transcriptomic and epigenetic signature of circulating lymphocytes reinforce the concept that epigenetic processes participate in the increased immune cell activation and impaired metabolic functions in obesity.

An integrative systems genetics approach reveals potential causal genes and pathways related to obesity

Background

Obesity is a multi-factorial health problem in which genetic factors play an important role. Limited results have been obtained in single-gene studies using either genomic or transcriptomic data. RNA sequencing technology has shown its potential in gaining accurate knowledge about the transcriptome, and may reveal novel genes affecting complex diseases. Integration of genomic and transcriptomic variation (expression quantitative trait loci [eQTL] mapping) has identified causal variants that affect complex diseases. We integrated transcriptomic data from adipose tissue and genomic data from a porcine model to investigate the mechanisms involved in obesity using a systems genetics approach.

Methods

Using a selective gene expression profiling approach, we selected 36 animals based on a previously created genomic Obesity Index for RNA sequencing of subcutaneous adipose tissue. Differential expression analysis was performed using the Obesity Index as a continuous variable in a linear model. eQTL mapping was then performed to integrate 60 K porcine SNP chip data with the RNA sequencing data. Results were restricted based on genome-wide significant single nucleotide polymorphisms, detected differentially expressed genes, and previously detected co-expressed gene modules. Further data integration was performed by detecting co-expression patterns among eQTLs and integration with protein data.

Results

Differential expression analysis of RNA sequencing data revealed 458 differentially expressed genes. The eQTL mapping resulted in 987 cis-eQTLs and 73 trans-eQTLs (false discovery rate < 0.05), of which the cis-eQTLs were associated with metabolic pathways. We reduced the eQTL search space by focusing on differentially expressed and co-expressed genes and disease-associated single nucleotide polymorphisms to detect obesity-related genes and pathways. Building a co-expression network using eQTLs resulted in the detection of a module strongly associated with lipid pathways. Furthermore, we detected several obesity candidate genes, for example, ENPP1, CTSL, and ABHD12B.

Conclusions

To our knowledge, this is the first study to perform an integrated genomics and transcriptomics (eQTL) study using, and modeling, genomic and subcutaneous adipose tissue RNA sequencing data on obesity in a porcine model. We detected several pathways and potential causal genes for obesity. Further validation and investigation may reveal their exact function and association with obesity.

Electronic supplementary material

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Comparative Analyses of QTLs Influencing Obesity and Metabolic Phenotypes in Pigs and Humans

The pig is a well-known animal model used to investigate genetic and mechanistic aspects of human disease biology. They are particularly useful in the context of obesity and metabolic diseases because other widely used models (e.g. mice) do not completely recapitulate key pathophysiological features associated with these diseases in humans. Therefore, we established a F2 pig resource population (n = 564) designed to elucidate the genetics underlying obesity and metabolic phenotypes. Segregation of obesity traits was ensured by using breeds highly divergent with respect to obesity traits in the parental generation. Several obesity and metabolic phenotypes were recorded (n = 35) from birth to slaughter (242 ± 48 days), including body composition determined at about two months of age (63 ± 10 days) via dual-energy x-ray absorptiometry (DXA) scanning. All pigs were genotyped using Illumina Porcine 60k SNP Beadchip and a combined linkage disequilibrium-linkage analysis was used to identify genome-wide significant associations for collected phenotypes. We identified 229 QTLs which associated with adiposity- and metabolic phenotypes at genome-wide significant levels. Subsequently comparative analyses were performed to identify the extent of overlap between previously identified QTLs in both humans and pigs. The combined analysis of a large number of obesity phenotypes has provided insight in the genetic architecture of the molecular mechanisms underlying these traits indicating that QTLs underlying similar phenotypes are clustered in the genome. Our analyses have further confirmed that genetic heterogeneity is an inherent characteristic of obesity traits most likely caused by segregation or fixation of different variants of the individual components belonging to cellular pathways in different populations. Several important genes previously associated to obesity in human studies, along with novel genes were identified. Altogether, this study provides novel insight that may further the current understanding of the molecular mechanisms underlying human obesity.

Gender and Obesity Specific MicroRNA Expression in Adipose Tissue from Lean and Obese Pigs

Obesity is a complex condition that increases the risk of life threatening diseases such as cardiovascular disease and diabetes. Studying the gene regulation of obesity is important for understanding the molecular mechanisms behind the obesity derived diseases and may lead to better intervention and treatment plans. MicroRNAs (miRNAs) are short non-coding RNAs regulating target mRNA by binding to their 3'UTR. They are involved in numerous biological processes and diseases, including obesity. In this study we use a mixed breed pig model designed for obesity studies to investigate differentially expressed miRNAs in subcutaneous adipose tissue by RNA sequencing (RNAseq). Both male and female pigs are included to explore gender differences. The RNAseq study shows that the most highly expressed miRNAs are in accordance with comparable studies in pigs and humans. A total of six miRNAs are differentially expressed in subcutaneous adipose tissue between the lean and obese group of pigs, and in addition gender specific significant differential expression is observed for a number of miRNAs. The differentially expressed miRNAs have been verified using qPCR. The results of these studies in general confirm the trends found by RNAseq. Mir-9 and mir-124a are significantly differentially expressed with large fold changes in subcutaneous adipose tissue between lean and obese pigs. Mir-9 is more highly expressed in the obese pigs with a fold change of 10 and a p-value < 0.001. Mir-124a is more highly expressed in the obese pigs with a fold change of 114 and a p-value < 0.001. In addition, mir-124a is significantly higher expressed in abdominal adipose tissue in male pigs with a fold change of 119 and a p-value < 0.05. Both miRNAs are also significantly higher expressed in the liver of obese male pigs where mir-124a has a fold change of 12 and mir-9 has a fold change of 1.6, both with p-values < 0.05.

Non-invasive methods for the determination of body and carcass composition in livestock: dual-energy X-ray absorptiometry, computed tomography, magnetic resonance imaging and ultrasound: invited review

The ability to accurately measure body or carcass composition is important for performance testing, grading and finally selection or payment of meat-producing animals. Advances especially in non-invasive techniques are mainly based on the development of electronic and computer-driven methods in order to provide objective phenotypic data. The preference for a specific technique depends on the target animal species or carcass, combined with technical and practical aspects such as accuracy, reliability, cost, portability, speed, ease of use, safety and for in vivo measurements the need for fixation or sedation. The techniques rely on specific device-driven signals, which interact with tissues in the body or carcass at the atomic or molecular level, resulting in secondary or attenuated signals detected by the instruments and analyzed quantitatively. The electromagnetic signal produced by the instrument may originate from mechanical energy such as sound waves (ultrasound - US), 'photon' radiation (X-ray-computed tomography - CT, dual-energy X-ray absorptiometry - DXA) or radio frequency waves (magnetic resonance imaging - MRI). The signals detected by the corresponding instruments are processed to measure, for example, tissue depths, areas, volumes or distributions of fat, muscle (water, protein) and partly bone or bone mineral. Among the above techniques, CT is the most accurate one followed by MRI and DXA, whereas US can be used for all sizes of farm animal species even under field conditions. CT, MRI and US can provide volume data, whereas only DXA delivers immediate whole-body composition results without (2D) image manipulation. A combination of simple US and more expensive CT, MRI or DXA might be applied for farm animal selection programs in a stepwise approach.

Genome-wide QTL mapping of nine body composition and bone mineral density traits in pigs

Background

Since the pig is one of the most important livestock animals worldwide, mapping loci that are associated with economically important traits and/or traits that influence animal welfare is extremely relevant for efficient future pig breeding. Therefore, the purpose of this study was a genome-wide mapping of quantitative trait loci (QTL) associated with nine body composition and bone mineral traits: absolute (Fat, Lean) and percentage (FatPC, LeanPC) fat and lean mass, live weight (Weight), soft tissue X-ray attenuation coefficient (R), absolute (BMC) and percentage (BMCPC) bone mineral content and bone mineral density (BMD).

Methods

Data on the nine traits investigated were obtained by Dual-energy X-ray absorptiometry for 551 pigs that were between 160 and 200 days old. In addition, all pigs were genotyped using Illumina’s PorcineSNP60 Genotyping BeadChip. Based on these data, a genome-wide combined linkage and linkage disequilibrium analysis was conducted. Thus, we used 44 611 sliding windows that each consisted of 20 adjacent single nucleotide polymorphisms (SNPs). For the middle of each sliding window a variance component analysis was carried out using ASReml. The underlying mixed linear model included random QTL and polygenic effects, with fixed effects of sex, housing, season and age.

Results

Using a Bonferroni-corrected genome-wide significance threshold of P < 0.001, significant peaks were identified for all traits except BMCPC. Overall, we identified 72 QTL on 16 chromosomes, of which 24 were significantly associated with one trait only and the remaining with more than one trait. For example, a QTL on chromosome 2 included the highest peak across the genome for four traits (Fat, FatPC, LeanPC and R). The nearby gene, ZNF608, is known to be associated with body mass index in humans and involved in starvation in Drosophila, which makes it an extremely good candidate gene for this QTL.

Conclusions

Our QTL mapping approach identified 72 QTL, some of which confirmed results of previous studies in pigs. However, we also detected significant associations that have not been published before and were able to identify a number of new and promising candidate genes, such as ZNF608.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-014-0068-2) contains supplementary material, which is available to authorized users.

Identification of co-expression gene networks, regulatory genes and pathways for obesity based on adipose tissue RNA Sequencing in a porcine model

BACKGROUND

Obesity is a complex metabolic condition in strong association with various diseases, like type 2 diabetes, resulting in major public health and economic implications. Obesity is the result of environmental and genetic factors and their interactions, including genome-wide genetic interactions. Identification of co-expressed and regulatory genes in RNA extracted from relevant tissues representing lean and obese individuals provides an entry point for the identification of genes and pathways of importance to the development of obesity. The pig, an omnivorous animal, is an excellent model for human obesity, offering the possibility to study in-depth organ-level transcriptomic regulations of obesity, unfeasible in humans. Our aim was to reveal adipose tissue co-expression networks, pathways and transcriptional regulations of obesity using RNA Sequencing based systems biology approaches in a porcine model.

METHODS

We selected 36 animals for RNA Sequencing from a previously created F2 pig population representing three extreme groups based on their predicted genetic risks for obesity. We applied Weighted Gene Co-expression Network Analysis (WGCNA) to detect clusters of highly co-expressed genes (modules). Additionally, regulator genes were detected using Lemon-Tree algorithms.

RESULTS

WGCNA revealed five modules which were strongly correlated with at least one obesity-related phenotype (correlations ranging from -0.54 to 0.72, P < 0.001). Functional annotation identified pathways enlightening the association between obesity and other diseases, like osteoporosis (osteoclast differentiation, P = 1.4E-7), and immune-related complications (e.g. Natural killer cell mediated cytotoxity, P = 3.8E-5; B cell receptor signaling pathway, P = 7.2E-5). Lemon-Tree identified three potential regulator genes, using confident scores, for the WGCNA module which was associated with osteoclast differentiation: CCR1, MSR1 and SI1 (probability scores respectively 95.30, 62.28, and 34.58). Moreover, detection of differentially connected genes identified various genes previously identified to be associated with obesity in humans and rodents, e.g. CSF1R and MARC2.

CONCLUSIONS

To our knowledge, this is the first study to apply systems biology approaches using porcine adipose tissue RNA-Sequencing data in a genetically characterized porcine model for obesity. We revealed complex networks, pathways, candidate and regulatory genes related to obesity, confirming the complexity of obesity and its association with immune-related disorders and osteoporosis.

Systems genetics of obesity in an F2 pig model by genome-wide association, genetic network, and pathway analyses

Obesity is a complex condition with world-wide exponentially rising prevalence rates, linked with severe diseases like Type 2 Diabetes. Economic and welfare consequences have led to a raised interest in a better understanding of the biological and genetic background. To date, whole genome investigations focusing on single genetic variants have achieved limited success, and the importance of including genetic interactions is becoming evident. Here, the aim was to perform an integrative genomic analysis in an F2 pig resource population that was constructed with an aim to maximize genetic variation of obesity-related phenotypes and genotyped using the 60K SNP chip. Firstly, Genome Wide Association (GWA) analysis was performed on the Obesity Index to locate candidate genomic regions that were further validated using combined Linkage Disequilibrium Linkage Analysis and investigated by evaluation of haplotype blocks. We built Weighted Interaction SNP Hub (WISH) and differentially wired (DW) networks using genotypic correlations amongst obesity-associated SNPs resulting from GWA analysis. GWA results and SNP modules detected by WISH and DW analyses were further investigated by functional enrichment analyses. The functional annotation of SNPs revealed several genes associated with obesity, e.g., NPC2 and OR4D10. Moreover, gene enrichment analyses identified several significantly associated pathways, over and above the GWA study results, that may influence obesity and obesity related diseases, e.g., metabolic processes. WISH networks based on genotypic correlations allowed further identification of various gene ontology terms and pathways related to obesity and related traits, which were not identified by the GWA study. In conclusion, this is the first study to develop a (genetic) obesity index and employ systems genetics in a porcine model to provide important insights into the complex genetic architecture associated with obesity and many biological pathways that underlie it.

Weighted Interaction SNP Hub (WISH) network method for building genetic networks for complex diseases and traits using whole genome genotype data

Background

High-throughput genotype (HTG) data has been used primarily in genome-wide association (GWA) studies; however, GWA results explain only a limited part of the complete genetic variation of traits. In systems genetics, network approaches have been shown to be able to identify pathways and their underlying causal genes to unravel the biological and genetic background of complex diseases and traits, e.g., the Weighted Gene Co-expression Network Analysis (WGCNA) method based on microarray gene expression data. The main objective of this study was to develop a scale-free weighted genetic interaction network method using whole genome HTG data in order to detect biologically relevant pathways and potential genetic biomarkers for complex diseases and traits.

Results

We developed the Weighted Interaction SNP Hub (WISH) network method that uses HTG data to detect genome-wide interactions between single nucleotide polymorphism (SNPs) and its relationship with complex traits. Data dimensionality reduction was achieved by selecting SNPs based on its: 1) degree of genome-wide significance and 2) degree of genetic variation in a population. Network construction was based on pairwise Pearson's correlation between SNP genotypes or the epistatic interaction effect between SNP pairs. To identify modules the Topological Overlap Measure (TOM) was calculated, reflecting the degree of overlap in shared neighbours between SNP pairs. Modules, clusters of highly interconnected SNPs, were defined using a tree-cutting algorithm on the SNP dendrogram created from the dissimilarity TOM (1-TOM). Modules were selected for functional annotation based on their association with the trait of interest, defined by the Genome-wide Module Association Test (GMAT). We successfully tested the established WISH network method using simulated and real SNP interaction data and GWA study results for carcass weight in a pig resource population; this resulted in detecting modules and key functional and biological pathways related to carcass weight.

Conclusions

We developed the WISH network method which is a novel 'systems genetics' approach to study genetic networks underlying complex trait variation. The WISH network method reduces data dimensionality and statistical complexity in associating genotypes with phenotypes in GWA studies and enables researchers to identify biologically relevant pathways and potential genetic biomarkers for any complex trait of interest.

Identification of genes regulating growth and fatness traits in pig through hypothalamic transcriptome analysis

Previous studies on Iberian × Landrace (IBMAP) pig intercrosses have enabled the identification of several quantitative trait locus (QTL) regions related to growth and fatness traits; however, the genetic variation underlying those QTLs are still unknown. These traits are not only relevant because of their impact on economically important production traits, but also because pig constitutes a widely studied animal model for human obesity and obesity-related diseases. The hypothalamus is the main gland regulating growth, food intake, and fat accumulation. Therefore, the aim of this work was to identify genes and/or gene transcripts involved in the determination of growth and fatness in pig by a comparison of the whole hypothalamic transcriptome (RNA-Seq) in two groups of phenotypically divergent IBMAP pigs. Around 16,000 of the ∼25.010 annotated genes were expressed in these hypothalamic samples, with most of them showing intermediate expression levels. Functional analyses supported the key role of the hypothalamus in the regulation of growth, fat accumulation, and energy expenditure. Moreover, 58,927 potentially new isoforms were detected. More than 250 differentially expressed genes and novel transcript isoforms were identified between the two groups of pigs. Twenty-one DE genes/transcripts that colocalized in previously identified QTL regions and/or whose biological functions are related to the traits of interest were explored in more detail. Additionally, the transcription factors potentially regulating these genes and the subjacent networks and pathways were also analyzed. This study allows us to propose strong candidate genes for growth and fatness based on expression patterns, genomic location, and network interactions.

Highly efficient method for isolation of total RNA from adipose tissue

Background

RNA extraction is a crucial step for monitoring gene expression. Poor RNA quality (including degradation and remaining impurities) can result in misleading results. Isolation of RNA from animal tissues with high lipid content can be challenging. Especially, it is not trivial to isolate high quality RNA with a reasonable yield from adipose tissue. The aim of this study was to provide an optimized protocol for isolating total RNA from adipose tissue. This was achieved by combining the advantages of the two routinely used methods, TRI Reagent® and miRNeasy.

Findings

The miRNeasy method results in cleaner samples but more prone to degradation while the TRI Reagent® method results in samples contaminated with salts and solvents but more intact. The new protocol combines the best of both methods resulting in RNA of high quality and suitable for downstream experiments like RT-qPCR, microarrays and high-throughput sequencing.

Conclusions

The current protocol for total RNA isolation from adipose tissue yields sufficient amount of high quality total RNA free of contaminants.

Genome-wide association study reveals genetic architecture of eating behavior in pigs and its implications for humans obesity by comparative mapping

This study was aimed at identifying genomic regions controlling feeding behavior in Danish Duroc boars and its potential implications for eating behavior in humans. Data regarding individual daily feed intake (DFI), total daily time spent in feeder (TPD), number of daily visits to feeder (NVD), average duration of each visit (TPV), mean feed intake per visit (FPV) and mean feed intake rate (FR) were available for 1130 boars. All boars were genotyped using the Illumina Porcine SNP60 BeadChip. The association analyses were performed using the GenABEL package in the R program. Sixteen SNPs were found to have moderate genome-wide significance (p<5E-05) and 76 SNPs had suggestive (p<5E-04) association with feeding behavior traits. MSI2 gene on chromosome (SSC) 14 was very strongly associated with NVD. Thirty-six SNPs were located in genome regions where QTLs have previously been reported for behavior and/or feed intake traits in pigs. The regions: 64–65 Mb on SSC 1, 124–130 Mb on SSC 8, 63–68 Mb on SSC 11, 32–39 Mb and 59–60 Mb on SSC 12 harbored several signifcant SNPs. Synapse genes (GABRR2, PPP1R9B, SYT1, GABRR1, CADPS2, DLGAP2 and GOPC), dephosphorylation genes (PPM1E, DAPP1, PTPN18, PTPRZ1, PTPN4, MTMR4 and RNGTT) and positive regulation of peptide secretion genes (GHRH, NNAT and TCF7L2) were highly significantly associated with feeding behavior traits. This is the first GWAS to identify genetic variants and biological mechanisms for eating behavior in pigs and these results are important for genetic improvement of pig feed efficiency. We have also conducted pig-human comparative gene mapping to reveal key genomic regions and/or genes on the human genome that may influence eating behavior in human beings and consequently affect the development of obesity and metabolic syndrome. This is the first translational genomics study of its kind to report potential candidate genes for eating behavior in humans.