Detection of quantitative trait loci for growth- and fatness-related traits in a large-scale White Duroc × Erhualian intercross pig population

Association analysis of the sorting nexin 29 (SNX29) gene copy number variations with growth traits in Diannan small-ear (DSE) pigs

SNX29 is a potential functional gene associated with meat production traits. Previous studies have shown that SNX29 copy number variation (CNV) could be implicated with phenotype in goats. However, in Diannan small-ear (DSE) pigs, the genetic impact of SNX29 CNV on growth traits remains unclear. Therefore, this study investigated the associations between SNX29 CNVs (CNV10810 and CNV10811) and growth traits in 415 DSE pigs. The results revealed that the CNV10810 mutation was significantly associated with backfat thickness in DSE pigs at 12 and 15 months old (P < 0.05), while the CNV10811 mutation had significant effects on various growth traits at 6 and 12 months old, particularly for body weight, body height, back height and backfat thickness (P < 0.05 or P < 0.001). In conclusion, our results confirm that SNX29 CNV plays a role in regulating growth and development in pigs, thus suggesting its potential application for pig breeding programmes.

Evaluation of genetic differentiation and search for candidate genes for reproductive traits in pigs

OBJECTIVE

The use of molecular genetic methods in pig breeding can significantly increase the efficiency of breeding and breeding work. We applied the Fst (fixsacion index) method, the main focus of the work was on the search for common options related to the number of born piglets and the weight of born piglets, since today the urgent task is to prevent a decrease in the weight of piglets at birth while maintaining high fertility of sows.

METHODS

One approach is to scan the genome, followed by an assessment of Fst and identification of selectively selected regions. We chose Large White sows (n = 237) with the same conditions of keeping and feeding. The data were collected from the sows across three farrowing. For genotyping, we used GeneSeek GGP Porcine HD Genomic Profiler v1, which included 68,516 single nucleotide polymorphisms evenly distributed with an average spacing of 25 kb (Illumina Inc, San Diego, CA, USA).

RESULTS

Based on the results of the Fst analysis, 724 variants representing selection signals for the signs BALWT, BALWT1, NBA, and TNB (weight of piglets born alive, average weight of the 1st piglets born alive, total number born alive, total number born). At the same time, 18 common variants have been identified that are potential markers for both the number of piglets at birth and the weight of piglets at birth, which is extremely important for breeding work to improve reproductive characteristics in sows.

CONCLUSION

Оur work resulted in identification of variants associated with the reproductive characteristics of pigs. Moreover, we identified, variants which are potential markers for both the number of piglets at birth and the weight of piglets at birth, which is extremely important for breeding work to improve reproductive performance in sows.

Livestock species as emerging models for genomic imprinting

Genomic imprinting is an epigenetically-regulated process of central importance in mammalian development and evolution. It involves multiple levels of regulation, with spatio-temporal heterogeneity, leading to the context-dependent and parent-of-origin specific expression of a small fraction of the genome. Genomic imprinting studies have therefore been essential to increase basic knowledge in functional genomics, evolution biology and developmental biology, as well as with regard to potential clinical and agrigenomic perspectives. Here we offer an overview on the contribution of livestock research, which features attractive resources in several respects, for better understanding genomic imprinting and its functional impacts. Given the related broad implications and complexity, we promote the use of such resources for studying genomic imprinting in a holistic and integrative view. We hope this mini-review will draw attention to the relevance of livestock genomic imprinting studies and stimulate research in this area.

Genome-Wide Association Analysis Identifies Genomic Regions and Candidate Genes for Growth and Fatness Traits in Diannan Small-Ear (DSE) Pigs

In the livestock industry, the growth and fatness traits are directly related to production efficiency and economic profits. As for Diannan small-ear (DSE) pigs, a unique indigenous breed, the genetic architecture of growth and fatness traits is still elusive. The aim of this study was to search the genetic loci and candidate genes associated with phenotypic traits in DSE pigs using GWAS based on the Geneseek Porcine 50K SNP Chip data. A total of 22,146 single nucleotide polymorphisms (SNPs) were detected in 265 DSE pigs and used for Genome-wide association studies (GWAS) analysis. Seven SNPs were found to be associated with back height, chest circumference, cannon bone circumference, and backfat thickness at the suggestive significance level. Based on gene annotation results, these seven SNPs were, respectively, mapped to the following candidate genes, VIPR2, SLC10A2, NUCKS1, MCT1, CHCHD3, SMOX, and GPR1, which are mainly involved with adipocyte differentiation, lipid metabolism, skeletal muscle development, and average daily weight gain. Our work offers novel insights into the genetic architecture of economically important traits in swine and may play an important role in breeding using molecular markers in the DSE breed.

Analysis of merged transcriptomic and genomic datasets to identify genes and pathways underlying residual feed intake in growing pigs

Improvement of feed efficiency (FE) in pigs is an important milestone in order to reduce the economic and environmental impact of pig production. The goal of finding biomarkers for FE has persisted for decades. However, due to the complexity of the FE trait, these goals have still not been met. Here, we search for quantitative trait loci (QTL), candidate genes, and biological pathways associated with FE using both genotype and RNA-seq data. We obtained genotype and colon epithelium RNA-seq data for 375 and 96 pigs, respectively. In total, a genome-wide association study (GWAS) and differential expression (DE) analysis led to detection of three QTL on SSC9 and 17 DE-genes associated with FE. Possible intersection points between genes located in QTL and DE-genes were found on levels of transcription factor-target interaction. Moreover, cis-eQTL analysis revealed associations between genotype and expression levels of three DE-genes and three genes located in the GWAS QTLs, which may establish the connection between genotype and phenotype through DE. Finally, single nucleotide polymorphism calling using RNA-seq data for genes located in GWAS QTLs revealed 53 polymorphisms of which eleven were missense variants.

Genome-wide association study identifying genetic variants associated with carcass backfat thickness, lean percentage and fat percentage in a four-way crossbred pig population using SLAF-seq technology

Background

Carcass backfat thickness (BFT), carcass lean percentage (CLP) and carcass fat percentage (CFP) are important to the commercial pig industry. Nevertheless, the genetic architecture of BFT, CLP and CFP is still elusive. Here, we performed a genome-wide association study (GWAS) based on specific-locus amplified fragment sequencing (SLAF-seq) to analyze seven fatness-related traits, including five BFTs, CLP, and CFP on 223 four-way crossbred pigs.

Results

A total of 227, 921 highly consistent single nucleotide polymorphisms (SNPs) evenly distributed throughout the genome were used to perform GWAS. Using the mixed linear model (MLM), a total of 20 SNP loci significantly related to these traits were identified on ten Sus scrofa chromosomes (SSC), of which 10 SNPs were located in previously reported quantitative trait loci (QTL) regions. On SSC7, two SNPs (SSC7:29,503,670 and rs1112937671) for average backfat thickness (ABFT) exceeded 1% and 10% Bonferroni genome-wide significance levels, respectively. These two SNP loci were located within an intron region of the COL21A1 gene, which was a protein-coding gene that played an important role in the porcine backfat deposition by affecting extracellular matrix (ECM) remodeling. In addition, based on the other three significant SNPs on SSC7, five candidate genes, ZNF184, ZNF391, HMGA1, GRM4 and NUDT3 were proposed to influence BFT. On SSC9, two SNPs for backfat thickness at 6–7 ribs (67RBFT) and one SNP for CLP were in the same locus region (19 kb interval). These three SNPs were located in the PGM2L1 gene, which encoded a protein that played an indispensable role in glycogen metabolism, glycolysis and gluconeogenesis as a key enzyme. Finally, one significant SNP on SSC14 for CLP was located within the PLBD2 gene, which participated in the lipid catabolic process.

Conclusions

A total of two regions on SSC7 and SSC9 and eight potential candidate genes were found for fatness-related traits in pigs. The results of this GWAS based on SLAF-seq will greatly advance our understanding of the genetic architecture of BFT, CLP, and CFP traits. These identified SNP loci and candidate genes might serve as a biological basis for improving the important fatness-related traits of pigs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08827-8.

Mutations in melanocortin-4 receptor: From fish to men

Melanocortin-4 receptor (MC4R), expressed abundantly in the hypothalamus, is a critical regulator of energy homeostasis, including both food intake and energy expenditure. Shortly after the publication in 1997 of the Mc4r knockout phenotypes in mice, including increased food intake and severe obesity, the first mutations in MC4R were reported in humans in 1998. Studies in the subsequent two decades have established MC4R mutation as the most common monogenic form of obesity, especially in early-onset severe obesity. Studies in animals, from fish to mammals, have established the conserved physiological roles of MC4R in all vertebrates in regulating energy balance. Drug targeting MC4R has been recently approved for treating morbid genetic obesity. How the MC4R can be exploited for animal production is highly worthy of active investigation.

The expression pattern, polymorphisms and association analyses of the porcine NREP gene

NREP (neuronal regeneration related protein homolog) plays a role in the transformation of neural, muscle, and fibroblast cells and in smooth muscle myogenesis. The NREP gene was selected for detailed study as an expressional and functional candidate gene on the basis of data from the expression microarray, which detected the differences in gene expression between Czech Large White pigs and wild boars in the longissimus lumborum et thoracis and biceps femoris muscle tissues. Quantitative real-time PCR results confirmed that porcine NREP was expressed in both skeletal muscles and significantly overexpressed in Czech Large White pigs compared with wild boars (14.5- and 11.6-fold; p < .05). We identified 9 polymorphic sites in the genomic DNA of NREP. Six of these polymorphisms were in complete linkage disequilibrium, and therefore, only 4 loci were informative. The associations of the HF571253:g.103G>A, HF571253:g.134G>A, HF571253:g.179T>C and HF571253:g.402_409delT polymorphisms with backfat thickness, lean meat content and average daily gain were assessed in Czech Large White pigs. The GG genotypes HF571253:g.103G>A and HF571253:g.134G>A, the TT genotypes HF571253:g.179T>C and 67 HF571253:g.402_409delT genotypes had favourable effects on the studied traits. Our results indicate the possibility of utilizing the variability of the NREP gene in marker-assisted selection in order to improve meat production in pigs.

An imputed whole-genome sequence-based GWAS approach pinpoints causal mutations for complex traits in a specific swine population

Sequencing-based genome-wide association studies (GWAS) have facilitated the identification of causal associations between genetic variants and traits in diverse species. However, it is cost-prohibitive for the majority of research groups to sequence a large number of samples. Here, we carried out genotype imputation to increase the density of single nucleotide polymorphisms in a large-scale Swine F₂ population using a reference panel including 117 individuals, followed by a series of GWAS analyses. The imputation accuracies reached 0.89 and 0.86 for allelic concordance and correlation, respectively. A quantitative trait nucleotide (QTN) affecting the chest vertebrate was detected directly, while the investigation of another QTN affecting the residual glucose failed due to the presence of similar haplotypes carrying wild-type and mutant allelesin the reference panel used in this study. A high imputation accuracy was confirmed by Sanger sequencing technology for the most significant loci. Two candidate genes, CPNE5 and MYH3, affecting meat-related traits were proposed. Collectively, we illustrated four scenarios in imputation-based GWAS that may be encountered by researchers, and our results will provide an extensive reference for future genotype imputation-based GWAS analyses in the future.

A further survey of the quantitative trait loci affecting swine body size and carcass traits in five related pig populations

Breeding for good meat quality performance while maintaining large body size and desirable carcass traits has been the major challenge for modern swine selective breeding. To address this goal, in the present work we studied five related populations produced by two commercial breeds (Berkshire and Duroc) and two Chinese breeds (Licha black pig and Lulai black pig). A single-trait GWAS performed on 20 body size and carcass traits using a self-developed China Chip-1 porcine SNP50K BeadChip identified 11 genome-wide significant QTL on nine chromosomes and 22 suggestive QTL on 15 chromosomes. For the 11 genome-wide significant QTL, eight were detected in at least two populations, and the rest were population-specific and only mapped in Shanxia black pig. Most of the genome-wide significant QTL were pleiotropic; for example, the QTL around 75.65 Mb on SSC4 was associated with four traits at genome-wide significance level. After screening the genes within 50 kb of the top SNP for each genome-wide significant QTL, NR6A1 and VRTN were chosen as candidate genes for vertebrae number; PLAG1 and BMP2 were identified as candidate genes for body size; and MC4R was the strong candidate gene for body weight. The four genes have been reported as candidates for thoracic vertebrae number, lumbar vertebrae number, carcass length and body weight respectively in previous studies. The effects of VRTN on thoracic vertebrae number, carcass length and body length have been verified in Shanxia black pig. Therefore, the VRTN genotype could be used in gene-assisted selection, and this could accelerate genetic improvement of body size and carcass traits in Shanxia black pig.

A further look at quantitative trait loci for growth and fatness traits in a White Duroc × Erhualian F3 intercross population

Genetic analysis of porcine growth and fatness traits is beneficial to the swine industry and provides a reference to understand human obesity. Here, we obtained 29 growth and fatness traits for 473 individuals from a White Duroc × Erhualian F₃ intercross population. Basic statistical analyses showed that: (1) Positive correlations between different-stage body weights were detected, the shorter the time interval the stronger the correlation. (2) Strong correlations existed in the paired fatness traits. (3) With the growth of age, the correlation between fatness and body weight was increasing. All pigs were genotyped by Illumina 50 K SNP chips and their whole-genome genotypes were imputed referred to 109 re-sequencing data. We performed common and imputation-based GWASs for these traits. Two genome-wide significant loci on swine chromosome (SSC) 4 and 7 were repeatedly detected. The strongest association (P = 3.24 × 10^-19) was detected at 31.96 Mb on SSC7 for leaf fat weight. On this locus, seven major haplotypes were identified, of which two were novel and had an increasing-fatness effect. In the imputation-based GWAS, three new loci were identified. Our findings provide further insights into and enhance our understanding of genetic mechanism of porcine growth and fat deposition.

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 for backfat thickness at 100 kg and loin muscle thickness in domestic pigs based on genotyping by sequencing

Both backfat thickness at 100 kg (B100) and loin muscle thickness (LMT) are economically important traits in pigs. In this study, a total of 1,200 pigs (600 Landrace and 600 Yorkshire pigs) were examined with genotyping by sequencing. A total of 345,570 single nucleotide polymorphisms (SNPs) were obtained from 1,200 pigs. Then, a single marker regression test was used to conduct a genome-wide association study for B100 and LMT. A total of 8 and 90 significant SNPs were detected for LMT and B100, respectively. Interestingly, two shared significant loci [located at Sus scrofa chromosome (SSC) 6: 149876694 and SSC12: 46226580] were detected in two breeds for B100. Furthermore, three potential candidate genes were found for LMT and B100. The positional candidate gene FAM3C (SSC18: 25573656, P = 2.48 × 10^-9), which controls the survival, growth, and differentiation of tissues and cells, was found for LMT in Landrace pigs. At SSC9: 6.78-6.82 Mb in Landrace pigs, the positional candidate gene, INPPL1, which has a negative regulatory effect on diet-induced obesity and is involved in the regulation of insulin function, was found for B100. The candidate gene, RAB35, which regulates the adipocyte glucose transporter SLC2A4/GLUT4, was identified at approximately SSC14: 40.09-40.13 Mb in Yorkshire pigs. The results of this GWAS will greatly advance our understanding of the genetic architecture of the LMT and B100 traits. However, these identified loci and genes need to be further verified in more pig populations, and their functions also need to be validated by more biological experiments in pigs.

An association study using imputed whole-genome sequence data identifies novel significant loci for growth-related traits in a Duroc × Erhualian F2 population

The average daily gain (ADG) and body weight (BW) are very important traits for breeding programs and for the meat production industry, which have attracted many researchers to delineate the genetic architecture behind these traits. In the present study, single- and multi-trait genome-wide association studies (GWAS) were performed between imputed whole-genome sequence data and the traits of the ADG and BW at different stages in a large-scale White Duroc × Erhualian F₂ population. A bioinformatics annotation analysis was used to assist in the identification of candidate genes that are associated with these traits. Five and seven genome-wide significant quantitative trait loci (QTLs) were identified by single- and multi-trait GWAS, respectively. Furthermore, more than 40 genome-wide suggestive loci were detected. On the basis of the whole-genome sequence association study and the bioinformatics analysis, NDUFAF6, TNS1 and HMGA1 stood out as the strongest candidate genes. The presented single- and multi-trait GWAS analysis using imputed whole-genome sequence data identified several novel QTLs for pig growth-related traits. Integrating the GWAS with bioinformatics analysis can facilitate the more accurate identification of candidate genes. Higher imputation accuracy, time-saving algorithms, improved models and comprehensive databases will accelerate the identification of causal genes or mutations, which will contribute to genomic selection and pig breeding in the future.

Reconstitution of UCP1 using CRISPR/Cas9 in the white adipose tissue of pigs decreases fat deposition and improves thermogenic capacity

Uncoupling protein 1 (UCP1) is localized on the inner mitochondrial membrane and generates heat by uncoupling ATP synthesis from proton transit across the inner membrane. UCP1 is a key element of nonshivering thermogenesis and is most likely important in the regulation of body adiposity. Pigs (Artiodactyl family Suidae) lack a functional UCP1 gene, resulting in poor thermoregulation and susceptibility to cold, which is an economic and pig welfare issue owing to neonatal mortality. Pigs also have a tendency toward fat accumulation, which may be linked to their lack of UCP1, and thus influences the efficiency of pig production. Here, we report application of a CRISPR/Cas9-mediated, homologous recombination (HR)-independent approach to efficiently insert mouse adiponectin-UCP1 into the porcine endogenous UCP1 locus. The resultant UCP1 knock-in (KI) pigs showed an improved ability to maintain body temperature during acute cold exposure, but they did not have alterations in physical activity levels or total daily energy expenditure (DEE). Furthermore, ectopic UCP1 expression in white adipose tissue (WAT) dramatically decreased fat deposition by 4.89% (P < 0.01), consequently increasing carcass lean percentage (CLP; P < 0.05). Mechanism studies indicated that the loss of fat upon UCP1 activation in WAT was linked to elevated lipolysis. UCP1 KI pigs are a potentially valuable resource for agricultural production through their combination of cold adaptation, which improves pig welfare and reduces economic losses, with reduced fat deposition and increased lean meat production.

Genomewide association analysis of sow lactation performance traits in lines of Yorkshire pigs divergently selected for residual feed intake during grow-finish phase

Lactation is an economically and biologically important phase in the life cycle of sows. Short generation intervals in nucleus herds and low heritability of traits associated with lactation along with challenges associated with collecting accurate lactation performance phenotypes emphasize the importance of using genomic tools to examine the underlying genetics of these traits. We report the first genomewide association study (GWAS) on traits associated with lactation and efficiency in 2 lines of Yorkshire pigs that were divergently selected for residual feed intake during grow-finish phase. A total of 862 farrowing records from 2 parities were analyzed using a Bayesian whole genome variable selection model (Bayes B) to locate 1-Mb regions that were most strongly associated with each trait. The GWAS was conducted separately for parity 1 and 2 records. Marker-based heritabilities ranged from 0.03 to 0.39 for parity 1 traits and from 0.06 to 0.40 for parity 2 traits. For all traits studied, around 90% of genetic variance came from a large number of genomic regions with small effects, whereas genomic regions with large effects were found to be different for the same trait measured in parity 1 and 2. The highest percentage of genetic variance explained by a 1-Mb window for each trait ranged from 0.4% for feed intake during lactation to 4.2% for back fat measured at farrowing in parity 1 sows and from 0.2% for lactation feed intake to 5.4% for protein mass loss during lactation in parity 2 sows. A total of thirteen 1-Mb nonoverlapping windows were found to explain more than 1.5% of genetic variance for either a single trait or across multiple traits. These 1-Mb windows were on chromosomes 2, 3, 6, 7, 8, 11, 14, 15, 17, and 18. The major positional candidate genes within 1 Mb upstream and downstream of these windows were , (SSC2), (SSC6) (SSC7), (SSC8), (SSC11), (SSC14), (SSC17). Further validation studies on larger populations are required to validate these findings and to improve our understanding of the biology and complex genetic architecture of traits associated with sow lactation performance.

Genomewide association of piglet responses to infection with one of two porcine reproductive and respiratory syndrome virus isolates

Porcine reproductive and respiratory syndrome (PRRS) is a devastating disease in the swine industry. Identification of host genetic factors that enable selection for improved performance during PRRS virus (PRRSV) infection would reduce the impact of this disease on animal welfare and production efficiency. We conducted genomewide association study (GWAS) analyses of data from 13 trials of approximately 200 commercial crossbred nursery-age piglets that were experimentally infected with 1 of 2 type 2 isolates of PRRSV (NVSL 97-7985 [NVSL] and KS2006-72109 [KS06]). Phenotypes analyzed were viral load (VL) in blood during the first 21 d after infection (dpi) and weight gain (WG) from 0 to 42 dpi. We accounted for the previously identified QTL in the region on SSC4 in our models to increase power to identify additional regions. Many regions identified by single-SNP analyses were not identified using Bayes-B, but both analyses identified the same regions on SSC3 and SSC5 to be associated with VL in the KS06 trials and on SSC6 in the NVSL trials ( < 5 × 10); for WG, regions on SSC5 and SSC17 were associated in the NVSL trials ( < 3 × 10). No regions were identified with either method for WG in the KS06 trials. Except for the region on SSC4, which was associated with VL for both isolates (but only with WG for NVSL), identified regions did not overlap between the 2 PRRSV isolate data sets, despite high estimates of the genetic correlation between isolates for traits based on these data. We also identified genomic regions whose associations with VL or WG interacted with either PRRSV isolate or with genotype at the SSC4 QTL. Gene ontology (GO) annotation terms for genes located near moderately associated SNP ( < 0.003) were enriched for multiple immunologically (VL) and metabolism- (WG) related GO terms. The biological relevance of these regions suggests that, although it may increase the number of false positives, the use of single-SNP analyses and a relaxed threshold also increased the identification of true positives. In conclusion, although only the SSC4 QTL was associated with response to both PRRSV isolates, genes near associated SNP were enriched for the same GO terms across PRRSV isolates, suggesting that host responses to these 2 isolates are affected by the actions of many genes that function together in similar biological processes.

Genome-wide detection of genetic markers associated with growth and fatness in four pig populations using four approaches

BACKGROUND

Genome-wide association studies (GWAS) have been extensively used to identify genomic regions associated with a variety of phenotypic traits in pigs. Until now, most GWAS have explored single-trait association models. Here, we conducted both single- and multi-trait GWAS and a meta-analysis for nine fatness and growth traits on 2004 pigs from four diverse populations, including a White Duroc × Erhualian F₂ intercross population and Chinese Sutai, Laiwu and Erhualian populations.

RESULTS

We identified 44 chromosomal regions that were associated with the nine traits, including four genome-wide significant single nucleotide polymorphisms (SNPs) on SSC2 (SSC for Sus scrofa chromosome), 4, 7 and X. Compared to the single-population GWAS, the meta-analysis was less powerful for the identification of SNPs with population-specific effects but more powerful for the detection of SNPs with population-shared effects. Multiple-trait analysis reduced the power to detect trait-specific SNPs but significantly enhanced the power to identify common SNPs across traits. The SNP on SSC7 had pleiotropic effects on the nine traits in the F₂ and Erhualian populations. Another pleiotropic SNP was observed on SSCX for these traits in the F₂ and Sutai populations. Both population-specific and shared SNPs were identified in this study, thus reflecting the complex genetic architecture of pig growth and fatness traits.

CONCLUSIONS

We demonstrate that the multi-trait method and the meta-analysis on multiple populations can be used to increase the power of GWAS. The two significant SNPs on SSC7 and X had pleiotropic effects in the F₂, Erhualian and Sutai populations.

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.

Consequences of Epistasis on Growth in an Erhualian × White Duroc Pig Cross

Epistasis describes an interaction between the effects of loci. We included epistasis in quantitative trait locus (QTL) mapping of growth at a series of ages in a cross of a Chinese pig breed, Erhualian, with a commercial line, White Duroc. Erhualian pigs have much lower growth rates than White Duroc. We improved a method for genomewide testing of epistasis and present a clear analysis workflow. We also suggest a new approach for interpreting epistasis results where significant additive and dominance effects of a locus in specific backgrounds are determined. In total, seventeen QTL were found and eleven showed epistasis. Loci on chromosomes 2, 3, 4 and 7 were highlighted as affecting growth at more than one age or forming an interaction network. Epistasis resulted in both the QTL on chromosomes 3 and 7 having effects in opposite directions. We believe it is the first time for the chromosome 7 locus that an allele from a Chinese breed has been found to decrease growth. The consequences of epistasis were diverse. Results were impacted by using growth rather than body weight as the phenotype and by correcting for an effect of mother. Epistasis made a considerable contribution to growth in this population and modelling epistasis was important for accurately determining QTL effects.

Evaluating the Contribution of Gut Microbiota to the Variation of Porcine Fatness with the Cecum and Fecal Samples

Microbial community in gastrointestinal tract participates in the development of the obesity as well as quite a few metabolic diseases in human. However, there are few studies about the relationship between gut microbiota and porcine fatness. Here, we used high-throughput sequencing to perform 16S rRNA gene analysis in 256 cecum luminal samples from Erhualian pigs and 244 stools from Bamaxiang pigs, and adopted a two-part model statistical method to evaluate the association of gut microbes with porcine fatness. As the results, we identified a total of 6 and 108 operational taxonomic units (OTUs), and 9 and 10 bacterial taxa which showed significant associations with fatness traits in the stool and cecum samples, respectively. Cross-validation analysis indicated that gut microbiome showed the largest effect on abdominal adipose by explaining 2.73% phenotypic variance of abdominal fat weight. Significantly more fatness-associated OTUs were identified in the cecum samples than that in the stools, suggesting that cecum luminal samples were better used for identification of fatness-associated microbes than stools. The fatness-associated OTUs were mainly annotated to Lachnospiraceae, Ruminococcaceae, Prevotella, Treponema, and Bacteroides. These microbes have been reported to produce short-chain fatty acids by fermenting dietary indigested polysaccharide and pectin. The short-chain fatty acids can regulate host body energy homeostasis, protect host from inflammation and inhibit fat mass development. Our findings suggested that the gut microbiome may be an important factor modulating fatness in pigs.

Genetics of Adiposity in Large Animal Models for Human Obesity-Studies on Pigs and Dogs

The role of domestic mammals in the development of human biomedical sciences has been widely documented. Among these model species the pig and dog are of special importance. Both are useful for studies on the etiology of human obesity. Genome sequences of both species are known and advanced genetic tools [eg, microarray SNP for genome wide association studies (GWAS), next generation sequencing (NGS), etc.] are commonly used in such studies. In the domestic pig the accumulation of adipose tissue is an important trait, which influences meat quality and fattening efficiency. Numerous quantitative trait loci (QTLs) for pig fatness traits were identified, while gene polymorphisms associated with these traits were also described. The situation is different in dog population. Generally, excessive accumulation of adipose tissue is considered, similar to humans, as a complex disease. However, research on the genetic background of canine obesity is still in its infancy. Between-breed differences in terms of adipose tissue accumulation are well known in both animal species. In this review we show recent advances of studies on adipose tissue accumulation in pigs and dogs, and their potential importance for studies on human obesity.

Evaluating the Contribution of Gut Microbiota to the Variation of Porcine Fatness with the Cecum and Fecal Samples

Microbial community in gastrointestinal tract participates in the development of the obesity as well as quite a few metabolic diseases in human. However, there are few studies about the relationship between gut microbiota and porcine fatness. Here, we used high-throughput sequencing to perform 16S rRNA gene analysis in 256 cecum luminal samples from Erhualian pigs and 244 stools from Bamaxiang pigs, and adopted a two-part model statistical method to evaluate the association of gut microbes with porcine fatness. As the results, we identified a total of 6 and 108 operational taxonomic units (OTUs), and 9 and 10 bacterial taxa which showed significant associations with fatness traits in the stool and cecum samples, respectively. Cross-validation analysis indicated that gut microbiome showed the largest effect on abdominal adipose by explaining 2.73% phenotypic variance of abdominal fat weight. Significantly more fatness-associated OTUs were identified in the cecum samples than that in the stools, suggesting that cecum luminal samples were better used for identification of fatness-associated microbes than stools. The fatness-associated OTUs were mainly annotated to Lachnospiraceae, Ruminococcaceae, Prevotella, Treponema, and Bacteroides. These microbes have been reported to produce short-chain fatty acids by fermenting dietary indigested polysaccharide and pectin. The short-chain fatty acids can regulate host body energy homeostasis, protect host from inflammation and inhibit fat mass development. Our findings suggested that the gut microbiome may be an important factor modulating fatness in pigs.

Genome-wide association study reveals novel loci for litter size and its variability in a Large White pig population

Background

In many traits, not only individual trait levels are under genetic control, but also the variation around that level. In other words, genotypes do not only differ in mean, but also in (residual) variation around the genotypic mean. New statistical methods facilitate gaining knowledge on the genetic architecture of complex traits such as phenotypic variability. Here we study litter size (total number born) and its variation in a Large White pig population using a Double Hierarchical Generalized Linear model, and perform a genome-wide association study using a Bayesian method.

Results

In total, 10 significant single nucleotide polymorphisms (SNPs) were detected for total number born (TNB) and 9 SNPs for variability of TNB (varTNB). Those SNPs explained 0.83 % of genetic variance in TNB and 1.44 % in varTNB. The most significant SNP for TNB was detected on Sus scrofa chromosome (SSC) 11. A possible candidate gene for TNB is ENOX1, which is involved in cell growth and survival. On SSC7, two possible candidate genes for varTNB are located. The first gene is coding a swine heat shock protein 90 (HSPCB = Hsp90), which is a well-studied gene stabilizing morphological traits in Drosophila and Arabidopsis. The second gene is VEGFA, which is activated in angiogenesis and vasculogenesis in the fetus. Furthermore, the genetic correlation between additive genetic effects on TNB and on its variation was 0.49. This indicates that the current selection to increase TNB will also increase the varTNB.

Conclusions

To the best of our knowledge, this is the first study reporting SNPs associated with variation of a trait in pigs. Detected genomic regions associated with varTNB can be used in genomic selection to decrease varTNB, which is highly desirable to avoid very small or very large litters in pigs. However, the percentage of variance explained by those regions was small. The SNPs detected in this study can be used as indication for regions in the Sus scrofa genome involved in maintaining low variability of litter size, but further studies are needed to identify the causative loci.

The Functional SNPs in the 5' Regulatory Region of the Porcine PPARD Gene Have Significant Association with Fat Deposition Traits

Peroxisome proliferator-activated receptor delta (PPARD) is a key regulator of lipid metabolism, insulin sensitivity, cell proliferation and differentiation. In this study, we identified two Single Nucleotide Polymorphisms (SNPs, g.1015 A>G and g.1018 T>C) constituting four haplotypes (GT, GC, AC and AT) in the 5’ regulatory region of porcine PPARD gene. Functional analysis of the four haplotypes showed that the transcriptional activity of the PPARD promoter fragment carrying haplotype AC was significantly lower than that of the other haplotypes in 3T3-L1, C2C12 and PK-15 cells, and haplotype AC had the lowest binding capacities to the nuclear extracts. Transcription factor 7-like 2 (TCF7L2) enhanced the transcription activities of promoter fragments of PPARD gene carrying haplotypes GT, GC and AT in C2C12 and 3T3-L1 cells, and increased the protein expression of PPARD gene in C2C12 myoblasts. TCF7L2 differentially bound to the four haplotypes, and the binding capacity of TCF7L2 to haplotype AC was the lowest. There were significant associations between -655A/G and fat deposition traits in three pig populations including the Large White × Meishan F₂ pigs, France and American Large White pigs. Pigs with genotype GG had significantly higher expression of PPARD at both mRNA and protein level than those with genotype AG. These results strongly suggested that the SNPs in 5’ regulatory region of PPARD genes had significant impact on pig fat deposition traits.

Multi-breed genome-wide association study reveals novel loci associated with the weight of internal organs

Background

Recently, many genome-wide association studies (GWAS) have been conducted to understand the genetic architecture of economic important traits in farm animals. Pig is widely used as a biomedical animal model for its similarity with humans in terms of organ formation and disease mechanisms. Moreover, understanding the mechanisms that underlie the development of internal organs will impact the productive potential of pigs. Our aim was to uncover new single nucleotide polymorphisms (SNPs) associated with the weight of internal organs and carcass and also potential candidate genes.

Methods

We performed GWAS for the weight of heart, liver, spleen, kidney and carcass on five pig populations (White Duroc × Erhualian F₂ intercross, Sutai population, Laiwu population, Erhualian population and commercial population, for a total of 2650 individuals). Genotype data was produced using the PorcineSNP60 Beadchip array. After quality control, the data was used for association tests under a general linear mixed model. Population stratification was adjusted by including a random polygenic effect based on a matrix of genotypic relationships. A meta-analysis of our GWAS datasets was conducted by summing up the Chi square values across breeds, with the degrees of freedom of the Chi square distribution equal to the effective number of breeds.

Results

Thirty-nine quantitative trait loci (QTL) located on 15 chromosomes were identified by the single-population GWAS at the suggestive level. Among these, nine QTL surpassed the 5 % genome-wide significance threshold, including four for heart weight on SSC (Sus scrofa chromosome) 2, 4, 7 and 10, two for liver weight on SSC7, two for spleen weight on SSC5 and SSC7 and one for carcass weight on SSC11. The QTL on SSC7 showed pleiotropic effects for heart, liver and spleen weights in the F₂ population. In addition, two QTL were detected in several populations, including one on SSC2 for heart weight in the F₂ and Sutai populations and one on SSC7 for liver weight in the F₂ and Laiwu populations. The meta-analysis detected four novel QTL on SSC1, 3, 8 and 16 for carcass weight.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0168-7) contains supplementary material, which is available to authorized users.

Polymorphisms and expression analysis of SOX-6 in relation to porcine growth, carcass, and meat quality traits

The aim of the study was to investigate single nucleotide polymorphisms (SNPs) and expression of SOX-6 to support its candidacy for growth, carcass, and meat quality traits in pigs. The first SNP, rs81358375, was associated with pH 45 min post mortem in loin (pH1L), the thickness of backfat and side fat, and carcass length in Pietrain (Pi) population, and related with backfat thickness and daily gain in Duroc × Pietrain F2 (DuPi) population. The other SNP, rs321666676, was associated with meat colour in Pi population. In DuPi population, the protein, not mRNA, level of SOX-6 in high pH1L pigs was significantly less abundant compared with low pH1L pigs, where microRNAs targeting SOX-6 were also differently regulated. This paper shows that SOX-6 could be a potential candidate gene for porcine growth, carcass, and meat quality traits based on genetic association and gene expression.

Identification of quantitative trait transcripts for growth traits in the large scales of liver and muscle samples

Growth-related traits are economically important traits to the pig industry. Identification of causative gene and mutation responsible for growth-related QTL will facilitate the improvement of pig growth through marker-assisted selection. In this study, we applied whole genome gene expression and quantitative trait transcript (QTT) analyses in 497 liver and 586 longissimus dorsi muscle samples to identify candidate genes and dissect the genetic basis of pig growth in a white Duroc × Erhualian F2 resource population. A total of 20,108 transcripts in liver and 23,728 transcripts in muscle with expression values were used for association analysis between gene expression level and phenotypic value. At the significance threshold of P < 0.0005, we identified a total of 169 and 168 QTTs for nine growth-related traits in liver and muscle, respectively. We also found that some QTTs were correlated to more than one trait. The QTTs identified here showed high tissue specificity. We did not identify any QTTs that were associated with one trait in both liver and muscle. Through an integrative genomic approach, we identified SDR16C5 as the important candidate gene in pig growth trait. These findings contribute to further identification of the causative genes for porcine growth traits and facilitate improvement of pig breeding.

Genome-wide association analyses reveal significant loci and strong candidate genes for growth and fatness traits in two pig populations

BACKGROUND

Recently, genome-wide association studies (GWAS) have been reported on various pig traits. We performed a GWAS to analyze 22 traits related to growth and fatness on two pig populations: a White Duroc × Erhualian F2 intercross population and a Chinese Sutai half-sib population.

RESULTS

We identified 14 and 39 loci that displayed significant associations with growth and fatness traits at the genome-wide level and chromosome-wide level, respectively. The strongest association was between a 750 kb region on SSC7 (SSC for Sus scrofa) and backfat thickness at the first rib. This region had pleiotropic effects on both fatness and growth traits in F2 animals and contained a promising candidate gene HMGA1 (high mobility group AT-hook 1). Unexpectedly, population genetic analysis revealed that the allele at this locus that reduces fatness and increases growth is derived from Chinese indigenous pigs and segregates in multiple Chinese breeds. The second strongest association was between the region around 82.85 Mb on SSC4 and average backfat thickness. PLAG1 (pleiomorphic adenoma gene 1), a gene under strong selection in European domestic pigs, is proximal to the top SNP and stands out as a strong candidate gene. On SSC2, a locus that significantly affects fatness traits mapped to the region around the IGF2 (insulin-like growth factor 2) gene but its non-imprinting inheritance excluded IGF2 as a candidate gene. A significant locus was also detected within a recombination cold spot that spans more than 30 Mb on SSCX, which hampered the identification of plausible candidate genes. Notably, no genome-wide significant locus was shared by the two experimental populations; different loci were observed that had both constant and time-specific effects on growth traits at different stages, which illustrates the complex genetic architecture of these traits.

CONCLUSIONS

We confirm several previously reported QTL and provide a list of novel loci for porcine growth and fatness traits in two experimental populations with Chinese Taihu and Western pigs as common founders. We showed that distinct loci exist for these traits in the two populations and identified HMGA1 and PLAG1 as strong candidate genes on SSC7 and SSC4, respectively.

A systems genetics study of swine illustrates mechanisms underlying human phenotypic traits

Background

The pig, which shares greater similarities with human than with mouse, is important for agriculture and for studying human diseases. However, similarities in the genetic architecture and molecular regulations underlying phenotypic variations in humans and swine have not been systematically assessed.

Results

We systematically surveyed ~500 F2 pigs genetically and phenotypically. By comparing candidates for anemia traits identified in swine genome-wide SNP association and human genome-wide association studies (GWAS), we showed that both sets of candidates are related to the biological process “cellular lipid metabolism” in liver. Human height is a complex heritable trait; by integrating genome-wide SNP data and human adipose Bayesian causal network, which closely represents bone transcriptional regulations, we identified PLAG1 as a causal gene for limb bone length. This finding is consistent with GWAS findings for human height and supports the common genetic architecture between swine and humans. By leveraging a human protein-protein interaction network, we identified two putative candidate causal genes TGFB3 and DAB2IP and the known regulators MESP1 and MESP2 as responsible for the variation in rib number and identified the potential underlying molecular mechanisms. In mice, knockout of Tgfb3 and Tgfb2 together decreases rib number.

Conclusion

Our findings show that integrative network analyses reveal causal regulators underlying the genetic association of complex traits in swine and that these causal regulators have similar effects in humans. Thus, swine are a potentially good animal model for studying some complex human traits that are not under intense selection.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1240-y) contains supplementary material, which is available to authorized users.

Fine mapping of fatness QTL on porcine chromosome X and analyses of three positional candidate genes

BACKGROUND

Porcine chromosome X harbors four QTL strongly affecting backfat thickness (BFT), ham weight (HW), intramuscular fat content (IMF) and loin eye area (LEA). The confidence intervals (CI) of these QTL overlap and span more than 30 cM, or approximately 80 Mb. This study therefore attempts to fine map these QTL by joint analysis of two large-scale F₂ populations (Large White × Meishan and White Duroc × Erhualian constructed by INRA and JXAU respectively) and furthermore, to determine whether these QTL are caused by mutations in three positional candidate genes (ACSL4, SERPINA7 and IRS4) involved in lipid biosynthesis.

RESULTS

A female-specific linkage map with an average distance of 2 cM between markers in the initial QTL interval (SW2456-SW1943) was created and used here. The CI of QTL for BFT, HW and LEA were narrowed down to 6-7 cM, resulting from the joint analysis. For IMF, two linked QTL were revealed in the INRA population but not in the JXAU population, causing a wider CI (13 cM) for IMF QTL. Linkage analyses using two subsets of INRA F₁ dam families demonstrate that the BFT and HW QTL were segregating in the Meishan pigs. Moreover, haplotype comparisons between these dams suggest that within the refined QTL region, the recombination coldspot (~34 Mb) flanked by markers MCSE3F14 and UMNP1218 is unlikely to contain QTL genes. Two SNPs in the ACSL4 gene were identified and showed significant association with BFT and HW, but they and the known polymorphisms in the other two genes are unlikely to be causal mutations.

CONCLUSION

The candidate QTL regions have been greatly reduced and the QTL are most likely located downstream of the recombination coldspot. The segregation of SSCX QTL for BFT and HW within Meishan breed provides an opportunity for us to make effective use of Meishan chromosome X in crossbreeding. Further studies should attempt to identify the impact of additional DNA sequence (e.g. CNV) and expression variation in the three genes or their surrounding genes on these traits.

A comprehensive survey of copy number variation in 18 diverse pig populations and identification of candidate copy number variable genes associated with complex traits

Background

Copy number variation (CNV) is a major source of structural variants and has been commonly identified in mammalian genome. It is associated with gene expression and may present a major genetic component of phenotypic diversity. Unlike many other mammalian genomes where CNVs have been well annotated, studies of porcine CNV in diverse breeds are still limited.

Result

Here we used Porcine SNP60 BeadChip and PennCNV algorithm to identify 1,315 putative CNVs belonging to 565 CNV regions (CNVRs) in 1,693 pigs from 18 diverse populations. Total 538 out of 683 CNVs identified in a White Duroc × Erhualian F₂ population fit Mendelian transmission and 6 out of 7 randomly selected CNVRs were confirmed by quantitative real time PCR. CNVRs were non-randomly distributed in the pig genome. Several CNV hotspots were found on pig chromosomes 6, 11, 13, 14 and 17. CNV numbers differ greatly among different pig populations. The Duroc pigs were identified to have the most number of CNVs per individual. Among 1,765 transcripts located within the CNVRs, 634 genes have been reported to be copy number variable genes in the human genome. By integrating analysis of QTL mapping, CNVRs and the description of phenotypes in knockout mice, we identified 7 copy number variable genes as candidate genes for phenotypes related to carcass length, backfat thickness, abdominal fat weight, length of scapular, intermuscle fat content of logissimus muscle, body weight at 240 day, glycolytic potential of logissimus muscle, mean corpuscular hemoglobin, mean corpuscular volume and humerus diameter.

Conclusion

We revealed the distribution of the unprecedented number of 565 CNVRs in pig genome and investigated copy number variable genes as the possible candidate genes for phenotypic traits. These findings give novel insights into porcine CNVs and provide resources to facilitate the identification of trait-related CNVs.

Localization of association signal from risk and protective variants in sequencing studies

Aggregating information across multiple variants in a gene or region can improve power for rare variant association testing. Power is maximized when the aggregation region contains many causal variants and few neutral variants. In this paper, we present a method for the localization of the association signal in a region using a sliding-window based approach to rare variant association testing in a region. We first introduce a novel method for analysis of rare variants, the Difference in Minor Allele Frequency test (DMAF), which allows combined analysis of common and rare variants, and makes no assumptions about the direction of effects. In whole-region analyses of simulated data with risk and protective variants, DMAF and other methods which pool data across individuals were found to outperform methods which pool data across variants. We then implement a sliding-window version of DMAF, using a step-down permutation approach to control type I error with the testing of multiple windows. In simulations, the sliding-window DMAF improved power to detect a causal sub-region, compared to applying DMAF to the whole region. Sliding-window DMAF was also effective in localizing the causal sub-region. We also applied the DMAF sliding-window approach to test for an association between response to the drug gemcitabine and variants in the gene FKBP5 sequenced in 91 lymphoblastoid cell lines derived from white non-Hispanic individuals. The application of the sliding-window test procedure detected an association in a sub-region spanning an exon and two introns, when rare and common variants were analyzed together.