Joint QTL analysis of three connected F2-crosses in pigs

Allelic to genome wide perspectives of swine genetic variation to litter size and its component traits

Litter size is a complex and sex limited trait that depends on various biological, managemental and environmental factors. Owing to its low heritability it is inefficaciously selected by traditional methods. However, due to higher heritability of ovulation rate and embryo survival, selection based on component traits of litter size is advocated. QTL analysis and candidate gene approach are among the various supplementary/alternate strategies for selection of litter size. QTL analysis is aimed at identifying genomic regions affecting trait of interest significantly. Candidate gene approach necessitates identification of genes potentially affecting the trait. There are various genes that significantly affect litter size and its component traits viz. ESR, LEP, BF, IGFBP, RBP4, PRLR, CTNNAL1, WNT10B, TCF12, DAZ, and RNF4. These genes affect litter size in a complex interacting manner. Lately, genome wide association study (GWAS) have been utilized to unveil the genetic and biological background of litter traits, and elucidate the genes governing litter size. Favorable SNPs in these genes have been identified and offers a scope for inclusion in selection programs thereby increasing breeding efficiency and profit in pigs. The review provides a comprehensive coverage of investigations carried out globally to unravel the genetic variation in litter size and its component traits in pigs, both at allelic and genome wide level. It offers a current perspective on different strategies including the profiling of candidate genes, QTLs, and genome wide association studies as an aid to efficient selection for litter size and its component traits.

Structural variants and tandem repeats in the founder individuals of four F2 pig crosses and implications to F2 GWAS results

BACKGROUND

Structural variants and tandem repeats are relevant sources of genomic variation that are not routinely analyzed in genome wide association studies mainly due to challenging identification and genotyping. Here, we profiled these variants via state-of-the-art strategies in the founder animals of four F2 pig crosses using whole-genome sequence data (20x coverage). The variants were compared at a founder level with the commonly screened SNPs and small indels. At the F2 level, we carried out an association study using imputed structural variants and tandem repeats with four growth and carcass traits followed by a comparison with a previously conducted SNPs and small indels based association study.

RESULTS

A total of 13,201 high confidence structural variants and 103,730 polymorphic tandem repeats (with a repeat length of 2-20 bp) were profiled in the founders. We observed a moderate to high (r from 0.48 to 0.57) level of co-localization between SNPs or small indels and structural variants or tandem repeats. In the association step 56.56% of the significant variants were not in high LD with significantly associated SNPs and small indels identified for the same traits in the earlier study and thus presumably not tagged in case of a standard association study. For the four growth and carcass traits investigated, many of the already proposed candidate genes in our previous studies were confirmed and additional ones were identified. Interestingly, a common pattern on how structural variants or tandem repeats regulate the phenotypic traits emerged. Many of the significant variants were embedded or nearby long non-coding RNAs drawing attention to their functional importance. Through which specific mechanisms the identified long non-coding RNAs and their associated structural variants or tandem repeats contribute to quantitative trait variation will need further investigation.

CONCLUSIONS

The current study provides insights into the characteristics of structural variants and tandem repeats and their role in association studies. A systematic incorporation of these variants into genome wide association studies is advised. While not of immediate interest for genomic prediction purposes, this will be particularly beneficial for elucidating biological mechanisms driving the complex trait variation.

Genetic association of polymorphisms in porcine RGS16 with porcine circovirus viral load in naturally infected Yorkshire pigs

Regulator of G protein signaling 16 (RGS16) is known to be associated with porcine circovirus type 2 (PCV2). PCV2 associated disease (PCVAD) is a serious problem in the swine industry. The representative symptoms of PCVAD are high viral titer proliferation and decreased average daily gain. In this study, we identified single nucleotide polymorphisms (SNPs) in the RGS16 region, including the upstream region. Of the 22 identified SNPs, rs332913874, rs326071195, and rs318298586 were genotyped in 142 Yorkshire pigs. These SNPs were significantly associated with the PCV2 viral load. Moreover, the haplotype combination was also related to the PCV2 viral load. The haplotype and diplotype analysis also had a significant difference with the PCV2 viral load. Taken together, our results suggest that RGS16 SNPs considerably affect the PCV2 viral load.

A combined GWAS approach reveals key loci for socially-affected traits in Yorkshire pigs

Socially affected traits in pigs are controlled by direct genetic effects and social genetic effects, which can make elucidation of their genetic architecture challenging. We evaluated the genetic basis of direct genetic effects and social genetic effects by combining single-locus and haplotype-based GWAS on imputed whole-genome sequences. Nineteen SNPs and 25 haplotype loci are identified for direct genetic effects on four traits: average daily feed intake, average daily gain, days to 100 kg and time in feeder per day. Nineteen SNPs and 11 haplotype loci are identified for social genetic effects on average daily feed intake, average daily gain, days to 100 kg and feeding speed. Two significant SNPs from single-locus GWAS (SSC6:18,635,874 and SSC6:18,635,895) are shared by a significant haplotype locus with haplotype alleles 'GGG' for both direct genetic effects and social genetic effects in average daily feed intake. A candidate gene, MT3, which is involved in growth, nervous, and immune processes, is identified. We demonstrate the genetic differences between direct genetic effects and social genetic effects and provide an anchor for investigating the genetic architecture underlying direct genetic effects and social genetic effects on socially affected traits in pigs.

GWAS for Meat and Carcass Traits Using Imputed Sequence Level Genotypes in Pooled F2-Designs in Pigs

In order to gain insight into the genetic architecture of economically important traits in pigs and to derive suitable genetic markers to improve these traits in breeding programs, many studies have been conducted to map quantitative trait loci. Shortcomings of these studies were low mapping resolution, large confidence intervals for quantitative trait loci-positions and large linkage disequilibrium blocks. Here, we overcome these shortcomings by pooling four large F2 designs to produce smaller linkage disequilibrium blocks and by resequencing the founder generation at high coverage and the F1 generation at low coverage for subsequent imputation of the F2 generation to whole genome sequencing marker density. This lead to the discovery of more than 32 million variants, 8 million of which have not been previously reported. The pooling of the four F2 designs enabled us to perform a joint genome-wide association study, which lead to the identification of numerous significantly associated variant clusters on chromosomes 1, 2, 4, 7, 17 and 18 for the growth and carcass traits average daily gain, back fat thickness, meat fat ratio, and carcass length. We could not only confirm previously reported, but also discovered new quantitative trait loci. As a result, several new candidate genes are discussed, among them BMP2 (bone morphogenetic protein 2), which we recently discovered in a related study. Variant effect prediction revealed that 15 high impact variants for the traits back fat thickness, meat fat ratio and carcass length were among the statistically significantly associated variants.

Identification of porcine CTLA4 gene polymorphism and their association with piglet diarrhea and performance traits

The objective of this study was to evaluate the association between the cytotoxic T-lymphocyte-associated antigen 4 (CTLA4) gene and piglet diarrhea. In this study, the mRNA expression of the CTLA4 gene increased significantly in IPEC-J2 cells after Escherichia coli K88 infection. Single nucleotide polymorphisms (SNPs) located in the 5' flanking region (SNPs g.107281989C>T) and 3'-untranslated region (3'-UTR; SNPs g.107288753C>A) were identified, and they were in linkage disequilibrium in both Min pigs and the Landrace population. Association analysis showed that Landrace piglets with a TT or AA genotype had a lower diarrhea index, and AA animals had higher average daily gain when compared to CC pigs, respectively (p < 0.05). However, the relationship between SNPs and diarrhea and performance traits in the Min population was not significant. Haplotype analysis indicated that the TC haplotype had the lowest diarrhea index. The 5' flanking deletion assay suggested that SNP g.107281989C>T was a molecular marker instead of the functional marker. This research demonstrated that genetic variances in the CTLA4 gene had significant effects on Landrace piglet diarrhea resistance.

Relationship among MS4A8 expression, its variants, and the immune response in a porcine model of Salmonella

Salmonella colonization often establishes carrier status in infected animals, which decreases their performance. Salmonella-carrying pigs shed large amounts of bacteria in their feces, and thus they have a negative economic impact on the swine industry. The MS4A8 gene (membrane-spanning 4-domains A8) was significantly activated, by up to 119-fold, in peripheral blood after Salmonella inoculation of pigs. The present study analyzed the correlation of peripheral blood expression level and a genetic variant of porcine MS4A8 with Salmonella-infection traits. The result indicated that MS4A8 expression levels correlated significantly with Salmonella shedding counts. Both the expression of MS4A8 and fecal shedding counts correlated with leukocytes, lymphocytes, monocytes, segmented neutrophils, and banded neutrophils. A novel single nucleotide polymorphism of porcine MS4A8 (nonsynonymous, Val > Ala) was associated with Salmonella shedding counts and average daily gain (ADG) of body weight. The TT genotype had higher fecal shedding counts, leukocyte counts, and lymphocyte counts than the TC and CC genotypes. The CC genotype had higher level of ADG than the TC and TT genotype (p < 0.05). Those results indicated that MS4A8 is intriguing and could be used as a prospective genetic marker for Salmonella susceptibility.

Genome-wide association studies and meta-analysis uncovers new candidate genes for growth and carcass traits in pigs

Genome-wide association studies (GWAS) have been widely used in the genetic dissection of complex traits. As more genomic data is being generated within different commercial or resource pig populations, the challenge which arises is how to collectively investigate the data with the purpose to increase sample size and implicitly the statistical power. This study performs an individual population GWAS, a joint population GWAS and a meta-analysis in three pig F2 populations. D1 is derived from European type breeds (Piétrain, Large White and Landrace), D2 is obtained from an Asian breed (Meishan) and Piétrain, and D3 stems from a European Wild Boar and Piétrain, which is the common founder breed. The traits investigated are average daily gain, backfat thickness, meat to fat ratio and carcass length. The joint and the meta-analysis did not identify additional genomic clusters besides the ones discovered via the individual population GWAS. However, the benefit was an increased mapping resolution which pinpointed to narrower clusters harboring causative variants. The joint analysis identified a higher number of clusters as compared to the meta-analysis; nevertheless, the significance levels and the number of significant variants in the meta-analysis were generally higher. Both types of analysis had similar outputs suggesting that the two strategies can complement each other and that the meta-analysis approach can be a valuable tool whenever access to raw datasets is limited. Overall, a total of 20 genomic clusters that predominantly overlapped at various extents, were identified on chromosomes 2, 7 and 17, many confirming previously identified quantitative trait loci. Several new candidate genes are being proposed and, among them, a strong candidate gene to be taken into account for subsequent analysis is BMP2 (bone morphogenetic protein 2).

Linkage disequilibrium pattern and genome-wide association mapping for meat traits in multiple porcine F2 crosses

In the present study, data from four F2 crosses were analysed and used to study the linkage disequilibrium (LD) structure within and across the crosses. Genome-wide association analyses (GWASes) for conductivity and dressing out meat traits were conducted using single-marker and Bayesian multi-marker models using the pooled data from all F2 crosses. Porcine F2 crosses generated from the distantly related founder breeds Wild Boar, Piétrain and Meishan, as well as from a porcine F2 cross from the closely related founder breed Piétrain and an F1 Large White × Landrace cross were pooled. A total of 2572 F2 animals were genotyped using a 62K SNP chip. The positions of the SNPs were based on genome assembly Sscrofa11.1. After post-alignment and genotype filtering, approximately 50K SNPs were usable for LD studies and GWASes. The main findings of the present study are that the breakdown of LD was faster in crosses from closely related founder breeds compared to crosses from distantly related founders. The fastest breakdown of LD was observed by pooling the data. Based on the single-marker results and LD structure, clusters and windows were built for 1-Mb intervals. For conductivity and dressing out, 183 and 191 nominal significant associations respectively and six and five clusters respectively were found. Dominance was important for conductivity, and considering dominance in GWASes improved the mapping signals. Most clear signals were found for conductivity on SSC6, 8 and 15 and for dressing out on SSC2 and 7. Considering dominance might contribute to the accuracy of genomic selection and serve as a guide for choosing mating pairs with good combining abilities. However, further research is needed to investigate if dominance is also important in crossbreed pig breeding schemes.

Power and precision of QTL mapping in simulated multiple porcine F2 crosses using whole-genome sequence information

Background

During the last two decades, many QTL (quantitative trait locus) mapping experiments in pigs have been conducted using F2 crosses established from two outbred founder breeds. The founder breeds were frequently chosen from the Asian and European type breeds. A combination of next-generation sequencing, SNP (single nucleotide polymorphism) genotyping technology using SNP-chips, and genotype imputation techniques, can be used to infer the sequence information of all F2 individuals in a cost-effective way. The aim of the present simulation study was to analyze the power and precision of genome-wide association studies (GWASs) with whole-genome sequence data in several types of F2 crosses, including pooled crosses.

Methods

Based on a common historical population, three breeds representing two European type breeds (EU1 and EU2) and one Asian type breed (AS) were simulated. Two F2 designs of 500 individuals each were simulated. The cross EU1xEU2 (ASxEU2) was simulated using the phylogenetically closely related breeds EU1 and EU2 (or distantly related breeds AS and EU2) as the founder breeds. The simulated genomes comprised ten chromosomes, each with a length of 1 Morgan and whole-genome sequence information. A polygenic trait with a heritability of 0.5, which was affected by approximately 20 QTL per Morgan, was simulated. GWASs were conducted using single marker mixed linear models, either within the crosses or in their pooled datasets. Additionally, the studies were conducted in the breed EU2, which was a founder breed in both simulated crosses.

Results

The power to map QTL was high (low) in the ASxEU2 (EU1xEU2) cross and was highest when the data of both crosses were analyzed jointly. By contrast, the mapping precision was the highest in the EU1xEU2 cross. Pooling data led to a precision that was in between the precision of the EU1xEU2 cross and the ASxEU2 cross. A higher mapping precision was observed for QTL segregating within a founder breed.

Conclusions

These results suggest that the existing F2 crosses are promising databases for QTL mapping when the founder breeds are closely related or several crosses can be pooled. This conclusion is particularly applicable for QTL that segregate in a founder breed.

Genomic regions associated with host response to porcine reproductive and respiratory syndrome vaccination and co-infection in nursery pigs

BACKGROUND

The WUR1000125 (WUR) single nucleotide polymorphism (SNP) can be used as a genetic marker for host response to porcine reproductive and respiratory syndrome (PRRS), PRRS vaccination, and co-infection with porcine circovirus type 2b (PCV2b). Objectives of this study were to identify genomic regions other than WUR associated with host response to PRRS vaccination and PRRSV/PCV2b co-infection and regions with a different effect on host response to co-infection, depending on previous vaccination for PRRS.

METHODS

Commercial crossbred nursery pigs were pre-selected for WUR genotype (n = 171 AA and 198 AB pigs) where B is the dominant and favorable allele. Half of the pigs were vaccinated for PRRS and 4 weeks later, all pigs were co-infected with PRRS virus and PCV2b. Average daily gain (ADG) and viral load (VL) were quantified post vaccination (Post Vx) and post co-infection (Post Co-X). Single-SNP genome-wide association analyses were then conducted to identify genomic regions associated with response to vaccination and co-infection.

RESULTS

Multiple SNPs near the major histocompatibility complex were significantly associated with PCV2b VL (-log ₁₀ P ≥ 5.5), regardless of prior vaccination for PRRS. Several SNPs were also significantly associated with ADG Post Vx and Post Co-X. SNPs with a different effect on ADG, depending on prior vaccination for PRRS, were identified Post Vx (-log ₁₀ P = 5.6) and Post Co-X (-log ₁₀ P = 5.5). No SNPs were significantly associated with vaccination VL (-log₁₀ P ≤ 4.7) or PRRS VL (-log₁₀ P ≤ 4.3). Genes near SNPs associated with vaccination VL, PRRS VL, and PCV2b VL were enriched (P ≤ 0.01) for immune-related pathways and genes near SNPs associated with ADG were enriched for metabolism pathways (P ≤ 0.04). SNPs associated with vaccination VL, PRRS VL, and PCV2b VL showed overrepresentation of health QTL identified in previous studies and SNPs associated with ADG Post Vx of Non-Vx pigs showed overrepresentation of growth QTL.

CONCLUSIONS

Multiple genomic regions were associated with PCV2b VL and ADG Post Vx and Post Co-X. Different SNPs were associated with ADG, depending on previous vaccination for PRRS. Results of functional annotation analyses and novel approaches of using previously-reported QTL support the identified regions.

Invited review: Genome-wide association analysis for quantitative traits in livestock – a selective review of statistical models and experimental designs

Abstract. Quantitative or complex traits are controlled by many genes and environmental factors. Most traits in livestock breeding are quantitative traits. Mapping genes and causative mutations generating the genetic variance of these traits is still a very active area of research in livestock genetics. Since genome-wide and dense SNP panels are available for most livestock species, genome-wide association studies (GWASs) have become the method of choice in mapping experiments. Different statistical models are used for GWASs. We will review the frequently used single-marker models and additionally describe Bayesian multi-marker models. The importance of nonadditive genetic and genotype-by-environment effects along with GWAS methods to detect them will be briefly discussed. Different mapping populations are used and will also be reviewed. Whenever possible, our own real-data examples are included to illustrate the reviewed methods and designs. Future research directions including post-GWAS strategies are outlined.

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.

Conservation of imprinting of MKRN3 and NAP1L5 in rabbits

Maternally imprinted genes of makorin ring finger protein 3 (MKRN3) and nucleosome assembly protein 1-like 5 (NAP1L5) have been identified in many species but have not yet been investigated in rabbits. In this study, a polymorphism-based approach and bisulfite-sequencing PCR (BSP) were used to determine the imprinting status of MKRN3 and NAP1L5 in rabbits. The single nucleotide polymorphism (SNP)-based sequencing results demonstrated that MKRN3 and NAP1L5 were expressed preferentially from the paternal allele. Furthermore, the BSP results showed the gamete-specific methylation patterns and hemimethylation in brain and full methylation in liver were observed in MKRN3 and NAP1L5 respectively. Thus, we provide the first evidence that MKRN3 and NAP1L5 are paternally expressed genes and that the CpG islands located in the promoter region may be the putative differentially methylated region of these two genes in rabbits.

Multiple-Line Inference of Selection on Quantitative Traits

Trait differences between species may be attributable to natural selection. However, quantifying the strength of evidence for selection acting on a particular trait is a difficult task. Here we develop a population genetics test for selection acting on a quantitative trait that is based on multiple-line crosses. We show that using multiple lines increases both the power and the scope of selection inferences. First, a test based on three or more lines detects selection with strongly increased statistical significance, and we show explicitly how the sensitivity of the test depends on the number of lines. Second, a multiple-line test can distinguish between different lineage-specific selection scenarios. Our analytical results are complemented by extensive numerical simulations. We then apply the multiple-line test to QTL data on floral character traits in plant species of the Mimulus genus and on photoperiodic traits in different maize strains, where we find a signature of lineage-specific selection not seen in two-line tests.

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.

Feed intake, average daily gain, feed efficiency, and real-time ultrasound traits in Duroc pigs: II. Genomewide association

Efficient use of feed resources has become a clear challenge for the U.S. pork industry as feed costs continue to be the largest variable expense. The availability of the Illumina Porcine60K BeadChip has greatly facilitated whole-genome association studies to identify chromosomal regions harboring genes influencing those traits. The current study aimed at identifying genomic regions associated with variation in feed efficiency and several production traits in a Duroc terminal sire population, including ADFI, ADG, feed conversion ratio, residual feed intake (RFI), real-time ultrasound back fat thickness (BF), ultrasound muscle depth, intramuscular fat content (IMF), birth weight (BW at birth), and weaning weight (BW at weaning). Single trait association analyses were performed using Bayes B models with 35,140 SNP on 18 autosomes after quality control. Significance of nonoverlapping 1-Mb length windows (n = 2,380) were tested across 3 QTL inference methods: posterior distribution of windows variances from Monte Carlo Markov Chain, naive Bayes factor, and nonparametric bootstrapping. Genes within the informative QTL regions for the traits were annotated. A region ranging from166 to 140 Mb (4-Mb length) on SSC 1, approximately 8 Mb upstream of the MC4R gene, was significantly associated with ADFI, ADG, and BF, where SOCS6 and DOK6 are proposed as the most likely candidate genes. Another region affecting BW at weaning was identified on SSC 4 (84-85 Mb), harboring genes previously found to influence both human and cattle height: PLAG1, CHCHD7, RDHE2 (or SDR16C5), MOS, RPS20, LYN, and PENK. No QTL were identified for RFI, IMF, and BW at birth. In conclusion, we have identified several genomic regions associated with traits affecting nutrient utilization that could be considered for future genomic prediction to improve feed utilization.

Investigations on the pattern of linkage disequilibrium and selection signatures in the genomes of German Piétrain pigs

The aim of this study was to study the population structure, to characterize the LD structure and to define core regions based on low recombination rates among SNP pairs in the genome of Piétrain pigs using data from the PorcineSNP60 BeadChip. This breed is a European sire line and was strongly selected for lean meat content during the last decades. The data were used to map signatures of selection using the REHH test. In the first step, selection signatures were searched genome-wide using only core haplotypes having a frequency above 0.25. In the second step, the results from the selection signature analysis were matched with the results from the recently conducted genome-wide association study for economical relevant traits to investigate putative overlaps of chromosomal regions. A small subdivision of the population with regard to the geographical origin of the individuals was observed. The extent of LD was determined genome-wide using r(2) values for SNP pairs with a distance ≤5 Mb and was on average 0.34. This comparable low r(2) value indicates a high genetic diversity in the Piétrain population. Six REHH values having a p-value < 0.001 were genome-wide detected. These were located on SSC1, 2, 6 and 17. Three positional candidate genes with potential biological roles were suggested, called LOC100626459, LOC100626014 and MIR1. The results imply that for genome-wide analysis especially in this population, a higher marker density and higher sample sizes are required. For a number of nine SNPs, which were successfully annotated to core regions, the REHH test was applied. However, no selection signatures were found for those regions (p-value < 0.1).

Genome-wide association and systems genetic analyses of residual feed intake, daily feed consumption, backfat and weight gain in pigs

Background

Feed efficiency is one of the major components determining costs of animal production. Residual feed intake (RFI) is defined as the difference between the observed and the expected feed intake given a certain production. Residual feed intake 1 (RFI1) was calculated based on regression of individual daily feed intake (DFI) on initial test weight and average daily gain. Residual feed intake 2 (RFI2) was as RFI1 except it was also regressed with respect to backfat (BF). It has been shown to be a sensitive and accurate measure for feed efficiency in livestock but knowledge of the genomic regions and mechanisms affecting RFI in pigs is lacking. The study aimed to identify genetic markers and candidate genes for RFI and its component traits as well as pathways associated with RFI in Danish Duroc boars by genome-wide associations and systems genetic analyses.

Results

Phenotypic and genotypic records (using the Illumina Porcine SNP60 BeadChip) were available on 1,272 boars. Fifteen and 12 loci were significantly associated (p < 1.52 × 10^-6) with RFI1 and RFI2, respectively. Among them, 10 SNPs were significantly associated with both RFI1 and RFI2 implying the existence of common mechanisms controlling the two RFI measures. Significant QTL regions for component traits of RFI (DFI and BF) were detected on pig chromosome (SSC) 1 (for DFI) and 2 for (BF). The SNPs within MAP3K5 and PEX7 on SSC 1, ENSSSCG00000022338 on SSC 9, and DSCAM on SSC 13 might be interesting markers for both RFI measures. Functional annotation of genes in 0.5 Mb size flanking significant SNPs indicated regulation of protein and lipid metabolic process, gap junction, inositol phosphate metabolism and insulin signaling pathway are significant biological processes and pathways for RFI, respectively.

Conclusions

The study detected novel genetic variants and QTLs on SSC 1, 8, 9, 13 and 18 for RFI and indicated significant biological processes and metabolic pathways involved in RFI. The study also detected novel QTLs for component traits of RFI. These results improve our knowledge of the genetic architecture and potential biological pathways underlying RFI; which would be useful for further investigations of key candidate genes for RFI and for development of biomarkers.

Meta - and combined - QTL analysis of different experiments on immune traits in chickens

Meta and/or combined QTL analysis from multiple studies can improve quantitative trait loci (QTL) position estimates compared to the individual experiments. Hereby we present results of a meta-analysis of QTL on chicken chromosome 9, 14 and 18 using data from three separate experiments and joint QTL analysis for chromosome 14 and 18. Meta QTL analysis uses information from multiple QTLs studies. Joint QTL analysis is based on combining raw data from different QTL experimental populations. QTLs under the study were related to specific antibody response to keyhole lymphet hemocyanin (KLH), and natural antibodies to environmental antigens, lipopolisaccharide (LPS) and lipoteichoic acid (LTA). Meta QTL analysis resulted in narrowing down the confidence interval for two QTLs on GGA14. The first one for natural antibodies against LTA and the second one for specific antibody response toward KLH. Also, a confidence interval of a QTL for natural antibodies against LPS located on GGA18 was narrowed down. Combined QTL analysis was successful for two QTLs: for specific antibody response toward KLH on GGA14, and for natural antibodies against LPS on GGA18. The greatest statistical power for QTL detection in joint analysis was achieved when raw data from segregating half–sib families from different populations under the study was used.

A two-step approach to map quantitative trait loci for meat quality in connected porcine F(2) crosses considering main and epistatic effects

The aim of this study was to map QTL for meat quality traits in three connected porcine F(2) crosses comprising around 1000 individuals. The three crosses were derived from the founder breeds Chinese Meishan, European Wild Boar and Pietrain. The animals were genotyped genomewide for approximately 250 genetic markers, mostly microsatellites. They were phenotyped for seven meat quality traits (pH at 45 min and 24 h after slaughter, conductivity at 45 min and 24 h after slaughter, meat colour, drip loss and rigour). QTL mapping was conducted using a two-step procedure. In the first step, the QTL were mapped using a multi-QTL multi-allele model that was tailored to analyse multiple connected F(2) crosses. It considered additive, dominance and imprinting effects. The major gene RYR1:g.1843C>T affecting the meat quality on SSC6 was included as a cofactor in the model. The mapped QTL were tested for pairwise epistatic effects in the second step. All possible epistatic effects between additive, dominant and imprinting effects were considered, leading to nine orthogonal forms of epistasis. Numerous QTL were found. The most interesting chromosome was SSC6. Not all genetic variance of meat quality was explained by RYR1:g.1843C>T. A small confidence interval was obtained, which facilitated the identification of candidate genes underlying the QTL. Epistasis was significant for the pairwise QTL on SSC12 and SSC14 for pH24 and for the QTL on SSC2 and SSC5 for rigour. Some evidence for additional pairwise epistatic effects was found, although not significant. Imprinting was involved in epistasis.

Mapping quantitative trait loci for metabolic and cytological fatness traits of connected F2 crosses in pigs

In the present study 3 connected F(2) crosses were used to map QTL for classical fat traits as well as fat-related metabolic and cytological traits in pigs. The founder breeds were Chinese Meishan, European Wild Boar, and Pietrain with to some extent the same founder animals in the different crosses. The different selection history of the breeds for fatness traits as well as the connectedness of the crosses led to a high statistical power. The total number of F(2) animals varied between 694 and 966, depending on the trait. The animals were genotyped for around 250 genetic markers, mostly microsatellites. The statistical model was a multi-allele, multi-QTL model that accounted for imprinting. The model was previously introduced from plant breeding experiments. The traits investigated were backfat depth and fat area as well as relative number of fat cells with different sizes and 2 metabolic traits (i.e., soluble protein content as an indicator for the level of metabolic turnover and NADP-malate dehydrogenase as an indicator for enzyme activity). The results revealed in total 37 significant QTL on chromosomes 1, 2, 4, 5, 6, 7, 8, 9, 14, 17, and 18, with often an overlap of confidence intervals of several traits. These confidence intervals were in some cases remarkably small, which is due to the high statistical power of the design. In total, 18 QTL showed significant imprinting effects. The small and overlapping confidence intervals for the classical fatness traits as well as for the cytological and metabolic traits enabled positional and functional candidate gene identification for several mapped QTL.