Genetic determinants of pig birth weight variability

Genome wide association study of thyroid hormone levels following challenge with porcine reproductive and respiratory syndrome virus

Introduction: Porcine reproductive and respiratory syndrome virus (PRRSV) causes respiratory disease in piglets and reproductive disease in sows. Piglet and fetal serum thyroid hormone (i.e., T3 and T4) levels decrease rapidly in response to Porcine reproductive and respiratory syndrome virus infection. However, the genetic control of T3 and T4 levels during infection is not completely understood. Our objective was to estimate genetic parameters and identify quantitative trait loci (QTL) for absolute T3 and/or T4 levels of piglets and fetuses challenged with Porcine reproductive and respiratory syndrome virus. Methods: Sera from 5-week-old pigs (N = 1792) at 11 days post inoculation (DPI) with Porcine reproductive and respiratory syndrome virus were assayed for T3 levels (piglet_T3). Sera from fetuses (N = 1,267) at 12 or 21 days post maternal inoculation (DPMI) with Porcine reproductive and respiratory syndrome virus of sows (N = 145) in late gestation were assayed for T3 (fetal_T3) and T4 (fetal_T4) levels. Animals were genotyped using 60 K Illumina or 650 K Affymetrix single nucleotide polymorphism (SNP) panels. Heritabilities, phenotypic correlations, and genetic correlations were estimated using ASREML; genome wide association studies were performed for each trait separately using Julia for Whole-genome Analysis Software (JWAS). Results: All three traits were low to moderately heritable (10%-16%). Phenotypic and genetic correlations of piglet_T3 levels with weight gain (0-42 DPI) were 0.26 ± 0.03 and 0.67 ± 0.14, respectively. Nine significant quantitative trait loci were identified for piglet_T3, on Sus scrofa chromosomes (SSC) 3, 4, 5, 6, 7, 14, 15, and 17, and collectively explaining 30% of the genetic variation (GV), with the largest quantitative trait loci identified on SSC5, explaining 15% of the genetic variation. Three significant quantitative trait loci were identified for fetal_T3 on SSC1 and SSC4, which collectively explained 10% of the genetic variation. Five significant quantitative trait loci were identified for fetal_T4 on SSC1, 6, 10, 13, and 15, which collectively explained 14% of the genetic variation. Several putative immune-related candidate genes were identified, including CD247, IRF8, and MAPK8. Discussion: Thyroid hormone levels following Porcine reproductive and respiratory syndrome virus infection were heritable and had positive genetic correlations with growth rate. Multiple quantitative trait loci with moderate effects were identified for T3 and T4 levels during challenge with Porcine reproductive and respiratory syndrome virus and candidate genes were identified, including several immune-related genes. These results advance our understanding of growth effects of both piglet and fetal response to Porcine reproductive and respiratory syndrome virus infection, revealing factors associated with genomic control of host resilience.

Genome-Wide Association Analysis Reveals Novel Loci Related with Visual Score Traits in Nellore Cattle Raised in Pasture-Based Systems

Body conformation traits assessed based on visual scores are widely used in Zebu cattle breeding programs. The aim of this study was to identify genomic regions and biological pathways associated with body conformation (CONF), finishing precocity (PREC), and muscling (MUSC) in Nellore cattle. The measurements based on visual scores were collected in 20,807 animals raised in pasture-based systems in Brazil. In addition, 2775 animals were genotyped using a 35 K SNP chip, which contained 31,737 single nucleotide polymorphisms after quality control. Single-step GWAS was performed using the BLUPF90 software while candidate genes were identified based on the Ensembl Genes 69. PANTHER and REVIGO platforms were used to identify key biological pathways and STRING to create gene networks. Novel candidate genes were revealed associated with CONF, including ALDH9A1, RXRG, RAB2A, and CYP7A1, involved in lipid metabolism. The genes associated with PREC were ELOVL5, PID1, DNER, TRIP12, and PLCB4, which are related to the synthesis of long-chain fatty acids, lipid metabolism, and muscle differentiation. For MUSC, the most important genes associated with muscle development were SEMA6A, TIAM2, UNC5A, and UIMC1. The polymorphisms identified in this study can be incorporated in commercial genotyping panels to improve the accuracy of genomic evaluations for visual scores in beef cattle.

Genome-wide association studies uncover genes associated with litter traits in the pig

Litter traits are critical economic variables in the pig industry as they represent a production indicator that can serve to determine sow fertility. In this study, a genome-wide association study on litter traits, including total number born (TNB), number born alive (NBA), litter birth weight (LBW), average birth weight (ABW), and piglet uniformity (PU), was carried out on two pig breeds (Yorkshire and Landrace). A total of 3 637 pigs of both breeds were genotyped using the GeneSeek GGP Porcine 50K SNP BeadChip. A mixed linear model (MLM) and fixed and random model circulating probability unification (FarmCPU) were employed in the genome-wide association studies for litter traits using combined data from the two pig breeds and data from each breed separately. Additionally, the heritability of traits was estimated using three methods-pedigree-based best linear unbiased prediction (PBLUP), genomic best linear unbiased prediction (GBLUP), and single-step best linear unbiased prediction (ssGBLUP)-and was found to lie between 0.065 and 0.1289, 0.0478 and 0.0938, 0.0793 and 0.0935, 0.1862 and 0.2163, and 0.0327 and 0.0419 for TNB, NBA, LBW, ABW, and PU, respectively. We also compared the genomic prediction accuracies and unbiasedness for litter traits of the three BLUP models. Our results indicated that the ssGBLUP method provided higher predictive accuracies and more rational unbiasedness compared with the PBLUP and GBLUP methodologies. Furthermore, based on their possible roles, eight candidate genes (INHBA, LEPR, HDHD2, CTNND2, RNF216, HMX1, PAPPA2, and NTN1) were identified as being linked with litter traits. In the middle of the test, these genes were found to be connected with pig metabolism and ovulation rate. Our results provide the insights into the genetic architecture of litter traits in pigs, and the potential single nucleotide polymorphisms (SNPs) and candidate genes identified may benefit economic profits in pig-breeding industry and contribute to improve litter traits.

Profiling of open chromatin in developing pig (Sus scrofa) muscle to identify regulatory regions

There is very little information about how the genome is regulated in domestic pigs (Sus scrofa). This lack of knowledge hinders efforts to define and predict the effects of genetic variants in pig breeding programs. To address this knowledge gap, we need to identify regulatory sequences in the pig genome starting with regions of open chromatin. We used the "Improved Protocol for the Assay for Transposase-Accessible Chromatin (Omni-ATAC-Seq)" to identify putative regulatory regions in flash-frozen semitendinosus muscle from 24 male piglets. We collected samples from the smallest-, average-, and largest-sized male piglets from each litter through five developmental time points. Of the 4661 ATAC-Seq peaks identified that represent regions of open chromatin, >50% were within 1 kb of known transcription start sites. Differential read count analysis revealed 377 ATAC-Seq defined genomic regions where chromatin accessibility differed significantly across developmental time points. We found regions of open chromatin associated with downregulation of genes involved in muscle development that were present in small-sized fetal piglets but absent in large-sized fetal piglets at day 90 of gestation. The dataset that we have generated provides a resource for studies of genome regulation in pigs and contributes valuable functional annotation information to filter genetic variants for use in genomic selection in pig breeding programs.

Evaluation of the phenotypic and genomic background of variability based on litter size of Large White pigs

BACKGROUND

The genetic background of trait variability has captured the interest of ecologists and animal breeders because the genes that control it could be involved in buffering various environmental effects. Phenotypic variability of a given trait can be assessed by studying the heterogeneity of the residual variance, and the quantitative trait loci (QTL) that are involved in the control of this variability are described as variance QTL (vQTL). This study focuses on litter size (total number born, TNB) and its variability in a Large White pig population. The variability of TNB was evaluated either using a simple method, i.e. analysis of the log-transformed variance of residuals (LnVar), or the more complex double hierarchical generalized linear model (DHGLM). We also performed a single-SNP (single nucleotide polymorphism) genome-wide association study (GWAS). To our knowledge, this is only the second study that reports vQTL for litter size in pigs and the first one that shows GWAS results when using two methods to evaluate variability of TNB: LnVar and DHGLM.

RESULTS

Based on LnVar, three candidate vQTL regions were detected, on Sus scrofa chromosomes (SSC) 1, 7, and 18, which comprised 18 SNPs. Based on the DHGLM, three candidate vQTL regions were detected, i.e. two on SSC7 and one on SSC11, which comprised 32 SNPs. Only one candidate vQTL region overlapped between the two methods, on SSC7, which also contained the most significant SNP. Within this vQTL region, two candidate genes were identified, ADGRF1, which is involved in neurodevelopment of the brain, and ADGRF5, which is involved in the function of the respiratory system and in vascularization. The correlation between estimated breeding values based on the two methods was 0.86. Three-fold cross-validation indicated that DHGLM yielded EBV that were much more accurate and had better prediction of missing observations than LnVar.

CONCLUSIONS

The results indicated that the LnVar and DHGLM methods resulted in genetically different traits. Based on their validation, we recommend the use of DHGLM over the simpler method of log-transformed variance of residuals. These conclusions can be useful for future studies on the evaluation of the variability of any trait in any species.

Genome-Wide Association Study of Body Weight Traits in Inner Mongolia Cashmere Goats

Objective: Body weight is an important economic trait for a goat, which greatly affects animal growth and survival. The purpose of this study was to identify genes associated with birth weight (BW), weaning weight (WW), and yearling weight (YW).

Materials and Methods: In this study, a genome-wide association study (GWAS) of BW, WW, and YW was determined using the GGP_Goat_70K single-nucleotide polymorphism (SNP) chip in 1,920 Inner Mongolia cashmere goats.

Results: We discovered that 21 SNPs were significantly associated with BW on the genome-wide levels. These SNPs were located in 10 genes, e.g., Mitogen-Activated Protein Kinase 3 (MAPK3), LIM domain binding 2 (LDB2), and low-density lipoprotein receptor-related protein 1B (LRP1B), which may be related to muscle growth and development in Inner Mongolia Cashmere goats. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that these genes were significantly enriched in the regulation of actin cytoskeleton and phospholipase D signaling pathway etc.

Conclusion: In summary, this study will improve the marker-assisted breeding of Inner Mongolia cashmere goats and the molecular mechanisms of important economic traits.

Whole-genome sequencing association analysis reveals the genetic architecture of meat quality traits in Chinese Qingyu pigs

The Chinese Qingyu pig breed is an invaluable indigenous genetic resource. However, few studies have investigated the genetic architecture of meat quality traits in Qingyu pigs. Here, 30 purebred Qingyu pigs were subjected to whole-genome sequencing. After quality control, 18 436 759 SNPs were retained. Genome-wide association studies (GWAS) were then performed for meat pH and color at three postmortem time points (45 min, 24 h, and 48 h) using single-marker regression analysis. In total, 11 and 69 SNPs were associated with meat pH and color of the longissimus thoracis muscle (LTM), respectively, while 54 and 29 SNPs were associated with meat pH and color of the semimembranosus muscle (SM), respectively. Seven SNPs associated with pork pH were shared by all three postmortem time points. Several candidate genes for meat traits were identified, including four genes (CXXC5, RYR3, BNIP3, and MYCT1) related to skeletal muscle development, regulation of Ca²⁺ release in the muscle, and anaerobic respiration, which are promising candidates for selecting superior meat quality traits in Qingyu pigs. To our knowledge, this is the first study investigating the postmortem genetic architecture of pork pH and color in Qingyu pigs. Our findings further the current understanding of the genetic factors influencing meat quality.

Genome-Wide Association Study and Fine Mapping Reveals Candidate Genes for Birth Weight of Yorkshire and Landrace Pigs

Birth weight of pigs is an important economic factor in the livestock industry. The identification of the genes and variants that underlie birth weight is of great importance. In this study, we integrated two genotyping methods, single nucleotide polymorphism (SNP) chip analysis and restriction site associated DNA sequencing (RAD-seq) to genotype genome-wide SNPs. In total, 45,175 and 139,634 SNPs were detected with the SNP chip and RAD-seq, respectively. The genome-wide association study (GWAS) of the combined SNP panels identified two significant loci located at chr1: 97,745,041 and chr4: 112,031,589, that explained 6.36% and 4.25% of the phenotypic variance respectively. To reduce interval containing causal variants, we imputed sequence-level SNPs in the GWAS identified regions and fine-mapped the causative variants into two narrower genomic intervals: a ∼100 kb interval containing 71 SNPs and a broader ∼870 kb interval with 432 SNPs. This fine-mapping highlighted four promising candidate genes, SKOR2, SMAD2, VAV3, and NTNG1. Additionally, the functional genes, SLC25A24, PRMT6 and STXBP3, are also located near the fine-mapping region. These results suggest that these candidate genes may have contribute substantially to the birth weight of pigs.

Impact of merging commercial breeding lines on the genetic diversity of Landrace pigs

BACKGROUND

The pig breeding industry has undergone a large number of mergers in the past decades. Various commercial lines were merged or discontinued, which is expected to reduce the genetic diversity of the pig species. The objective of the current study was to investigate the genetic diversity of different former Dutch Landrace breeding lines and quantify their relationship with the current Dutch Landrace breed that originated from these lines.

RESULTS

Principal component analysis clearly divided the former Landrace lines into two main clusters, which are represented by Norwegian/Finnish Landrace lines and Dutch Landrace lines. Structure analysis revealed that each of the lines that are present in the Dutch Gene bank has a unique genetic identity. The current Dutch Landrace breed shows a high level of admixture and is closely related to the six former lines. The Dumeco N-line, which is conserved in the Dutch Gene bank, is poorly represented in the current Dutch Landrace. All seven lines (the six former and the current line) contribute almost equally to the genetic diversity of the Dutch Landrace breed. As expected, the current Dutch Landrace breed comprises only a small proportion of unique genetic diversity that was not present in the other lines. The genetic diversity level, as measured by Eding's core set method, was equal to 0.89 for the current Dutch Landrace breed, whereas total genetic diversity across the seven lines, measured by the same method, was equal to 0.99.

CONCLUSIONS

The current Dutch Landrace breed shows a high level of admixture and is closely related to the six former Dutch Landrace lines. Merging of commercial Landrace lines has reduced the genetic diversity of the Landrace population in the Netherlands, although a large proportion of the original variation is maintained. Thus, our recommendation is to conserve breeding lines in a gene bank before they are merged.

First Genome-wide Association Analysis for Growth Traits in the Largest Coral Reef-Dwelling Bony Fishes, the Giant Grouper (Epinephelus lanceolatus)

The giant grouper, Epinephelus lanceolatus, is the largest coral reef-dwelling bony fish species. However, despite extremely fast growth performance and the considerable economic importance in this species, its genetic regulation of growth remains unknown. Here, we performed the first genome-wide association study (GWAS) for five growth traits in 289 giant groupers using 42,323 single nucleotide polymorphisms (SNPs) obtained by genotyping-by-sequencing (GBS). We identified a total of 36 growth-related SNPs, of which 11 SNPs reached a genome-wide significance level. The phenotypic variance explained by these SNPs varied from 7.09% for body height to 18.42% for body length. Moreover, 22 quantitative trait loci (QTLs) for growth traits, including nine significant QTLs and 13 suggestive QTLs, were found on multiple chromosomes. Interestingly, the QTL (LG17: 6934451) was shared between body weight and body height, while two significant QTLs (LG7: 22596399 and LG15: 11877836) for body length were consistent with the associated regions of total length at the genome-wide suggestive level. Eight potential candidate genes close to the associated SNPs were selected for expression analysis, of which four genes (phosphatidylinositol transfer protein cytoplasmic 1, protein tyrosine phosphatase receptor type E, alpha/beta hydrolase domain-containing protein 17C, and vascular endothelial growth factor A-A) were differentially expressed and involved in metabolism, development, response stress, etc. This study improves our understanding of the complex genetic architecture of growth in the giant grouper. The results contribute to the selective breeding of grouper species and the conservation of coral reef fishes.

Genomic analysis reveals genes affecting distinct phenotypes among different Chinese and western pig breeds

The differences in artificial and natural selection have been some of the factors contributing to phenotypic diversity between Chinese and western pigs. Here, 830 individuals from western and Chinese pig breeds were genotyped using the reduced-representation genotyping method. First, we identified the selection signatures for different pig breeds. By comparing Chinese pigs and western pigs along the first principal component, the growth gene IGF1R; the immune genes IL1R1, IL1RL1, DUSP10, RAC3 and SWAP70; the meat quality-related gene SNORA50 and the olfactory gene OR1F1 were identified as candidate differentiated targets. Further, along a principal component separating Pudong White pigs from others, a potential causal gene for coat colour (EDNRB) was discovered. In addition, the divergent signatures evaluated by F_st within Chinese pig breeds found genes associated with the phenotypic features of coat colour, meat quality and feed efficiency among these indigenous pigs. Second, admixture and genomic introgression analysis were performed. Shan pigs have introgressed genes from Berkshire, Yorkshire and Hongdenglong pigs. The results of introgression mapping showed that this introgression conferred adaption to the local environment and coat colour of Chinese pigs and the superior productivity of western pigs.

Genomic regions underlying uniformity of yearling weight in Nellore cattle evaluated under different response variables

BACKGROUND

In livestock, residual variance has been studied because of the interest to improve uniformity of production. Several studies have provided evidence that residual variance is partially under genetic control; however, few investigations have elucidated genes that control it. The aim of this study was to identify genomic regions associated with within-family residual variance of yearling weight (YW; N = 423) in Nellore bulls with high density SNP data, using different response variables. For this, solutions from double hierarchical generalized linear models (DHGLM) were used to provide the response variables, as follows: a DGHLM assuming non-null genetic correlation between mean and residual variance (rmv ≠ 0) to obtain deregressed EBV for mean (dEBVm) and residual variance (dEBVv); and a DHGLM assuming rmv = 0 to obtain two alternative response variables for residual variance, dEBVv_r0 and log-transformed variance of estimated residuals (ln_[Formula: see text]).

RESULTS

The dEBVm and dEBVv were highly correlated, resulting in common regions associated with mean and residual variance of YW. However, higher effects on variance than the mean showed that these regions had effects on the variance beyond scale effects. More independent association results between mean and residual variance were obtained when null rmv was assumed. While 13 and 4 single nucleotide polymorphisms (SNPs) showed a strong association (Bayes Factor > 20) with dEBVv and ln_[Formula: see text], respectively, only suggestive signals were found for dEBVv_r0. All overlapping 1-Mb windows among top 20 between dEBVm and dEBVv were previously associated with growth traits. The potential candidate genes for uniformity are involved in metabolism, stress, inflammatory and immune responses, mineralization, neuronal activity and bone formation.

CONCLUSIONS

It is necessary to use a strategy like assuming null rmv to obtain genomic regions associated with uniformity that are not associated with the mean. Genes involved not only in metabolism, but also stress, inflammatory and immune responses, mineralization, neuronal activity and bone formation were the most promising biological candidates for uniformity of YW. Although no clear evidence of using a specific response variable was found, we recommend consider different response variables to study uniformity to increase evidence on candidate regions and biological mechanisms behind it.

Identification of novel genes significantly affecting growth in catfish through GWAS analysis

Growth is the most important economic trait in aquaculture. Improvements in growth-related traits can enhance production, reduce costs and time to produce market-size fish. Catfish is the major aquaculture species in the United States, accounting for 65% of the US finfish production. However, the genes underlying growth traits in catfish were not well studied. Currently, the majority of the US catfish industry uses hybrid catfish derived from channel catfish female mated with blue catfish male. Interestingly, channel catfish and blue catfish exhibit differences in growth-related traits, and therefore the backcross progenies provide an efficient system for QTL analysis. In this study, we conducted a genome-wide association study for catfish body weight using the 250 K SNP array with 556 backcross progenies generated from backcross of male F1 hybrid (female channel catfish × male blue catfish) with female channel catfish. A genomic region of approximately 1 Mb on linkage group 5 was found to be significantly associated with body weight. In addition, four suggestively associated QTL regions were identified on linkage groups 1, 2, 23 and 24. Most candidate genes in the associated regions are known to be involved in muscle growth and bone development, some of which were reported to be associated with obesity in humans and pigs, suggesting that the functions of these genes may be evolutionarily conserved in controlling growth. Additional fine mapping or functional studies should allow identification of the causal genes for fast growth in catfish, and elucidation of molecular mechanisms of regulation of growth in fish.

Genome-Wide Association Study of Piglet Uniformity and Farrowing Interval

Piglet uniformity (PU) and farrowing interval (FI) are important reproductive traits related to production and economic profits in the pig industry. However, the genetic architecture of the longitudinal trends of reproductive traits still remains elusive. Herein, we performed a genome-wide association study (GWAS) to detect potential genetic variation and candidate genes underlying the phenotypic records at different parities for PU and FI in a population of 884 Large White pigs. In total, 12 significant SNPs were detected on SSC1, 3, 4, 9, and 14, which collectively explained 1–1.79% of the phenotypic variance for PU from parity 1 to 4, and 2.58–4.11% for FI at different stages. Of these, seven SNPs were located within 16 QTL regions related to swine reproductive traits. One QTL region was associated with birth body weight (related to PU) and contained the peak SNP MARC0040730, and another was associated with plasma FSH concentration (related to FI) and contained the SNP MARC0031325. Finally, some positional candidate genes for PU and FI were identified because of their roles in prenatal skeletal muscle development, fetal energy substrate, pre-implantation, and the expression of mammary gland epithelium. Identification of novel variants and candidate genes will greatly advance our understanding of the genetic mechanisms of PU and FI, and suggest a specific opportunity for improving marker assisted selection or genomic selection in pigs.