Whole Genome Association Studies of Residual Feed Intake and Related Traits in the Pig

Analysis of 206 whole-genome resequencing reveals selection signatures associated with breed-specific traits in Hu sheep

As an invaluable Chinese sheep germplasm resource, Hu sheep are renowned for their high fertility and beautiful wavy lambskins. Their distinctive characteristics have evolved over time through a combination of artificial and natural selection. Identifying selection signatures in Hu sheep can provide a straightforward insight into the mechanism of selection and further uncover the candidate genes associated with breed-specific traits subject to selection. Here, we conducted whole-genome resequencing on 206 Hu sheep individuals, each with an approximate 6-fold depth of coverage. And then we employed three complementary approaches, including composite likelihood ratio, integrated haplotype homozygosity score and the detection of runs of homozygosity, to detect selection signatures. In total, 10 candidate genomic regions displaying selection signatures were simultaneously identified by multiple methods, spanning 88.54 Mb. After annotating, these genomic regions harbored collectively 92 unique genes. Interestingly, 32 candidate genes associated with reproduction were distributed in nine genomic regions detected. Out of them, two stood out as star candidates: BMPR1B and GNRH2, both of which have documented associations with fertility, and a HOXA gene cluster (HOXA1-5, HOXA9, HOXA10, HOXA11 and HOXA13) had also been linked to fertility. Additionally, we identified other genes that are related to hair follicle development (LAMTOR3, EEF1A2), ear size (HOXA1, KCNQ2), fat tail formation (HOXA10, HOXA11), growth and development (FAF1, CCNDBP1, GJB2, GJA3), fat deposition (ACOXL, JAZF1, HOXA3, HOXA4, HOXA5, EBF4), immune (UBR1, FASTKD5) and feed intake (DAPP1, RNF17, NPBWR2). Our results offer novel insights into the genetic mechanisms underlying the selection of breed-specific traits in Hu sheep and provide a reference for sheep genetic improvement programs.

Overexpression of GPX2 gene regulates the development of porcine preadipocytes and skeletal muscle cells through MAPK signaling pathway

Glutathione peroxidase 2 (GPX2) is a selenium-dependent enzyme and protects cells against oxidative damage. Recently, GPX2 has been identified as a candidate gene for backfat and feed efficiency in pigs. However, it is unclear whether GPX2 regulates the development of porcine preadipocytes and skeletal muscle cells. In this study, adenoviral gene transfer was used to overexpress GPX2. Our findings suggest that overexpression of GPX2 gene inhibited proliferation of porcine preadipocytes. And the process is accompanied by the reduction of the p-p38. GPX2 inhibited adipogenic differentiation and promoted lipid degradation, while ERK1/2 was reduced and p-p38 was increased. Proliferation of porcine skeletal muscle cells was induced after GPX2 overexpression, was accompanied by activation in JNK, ERK1/2, and p-p38. Overexpression methods confirmed that GPX2 has a promoting function in myoblastic differentiation. ERK1/2 pathway was activated and p38 was suppressed during the process. This study lays a foundation for the functional study of GPX2 and provides theoretical support for promoting subcutaneous fat reduction and muscle growth.

Advances in the discovery of genetic elements underlying longissimus dorsi muscle growth and development in the pig

As a major source of protein in human diets, pig meat plays a crucial role in ensuring global food security. Key determinants of meat production refer to the chemical and physical compositions or characteristics of muscle fibers, such as the number, hypertrophy potential, fiber-type conversion and intramuscular fat deposition. However, the growth and formation of muscle fibers comprises a complex process under spatio-temporal regulation, that is, the intermingled and concomitant proliferation, differentiation, migration and fusion of myoblasts. Recently, with the fast and continuous development of next-generation sequencing technology, the integration of quantitative trait loci mapping with genome-wide association studies (GWAS) has greatly helped animal geneticists to discover and explore thousands of functional or causal genetic elements underlying muscle growth and development. However, owing to the underlying complex molecular mechanisms, challenges to in-depth understanding and utilization remain, and the cost of large-scale sequencing, which requires integrated analyses of high-throughput omics data, is high. In this review, we mainly elaborate on research advances in integrative analyses (e.g. GWAS, omics) for identifying functional genes or genomic elements for longissimus dorsi muscle growth and development for different pig breeds, describing several successful transcriptome analyses and functional genomics cases, in an attempt to provide some perspective on the future functional annotation of genetic elements for muscle growth and development in pigs.

Integrated analysis of genome-wide association studies and 3D epigenomic characteristics reveal the BMP2 gene regulating loin muscle depth in Yorkshire pigs

BACKGROUND

The lack of integrated analysis of genome-wide association studies (GWAS) and 3D epigenomics restricts a deep understanding of the genetic mechanisms of meat-related traits. With the application of techniques as ChIP-seq and Hi-C, the annotations of cis-regulatory elements in the pig genome have been established, which offers a new opportunity to elucidate the genetic mechanisms and identify major genetic variants and candidate genes that are significantly associated with important economic traits. Among these traits, loin muscle depth (LMD) is an important one as it impacts the lean meat content. In this study, we integrated cis-regulatory elements and genome-wide association studies (GWAS) to identify candidate genes and genetic variants regulating LMD.

RESULTS

Five single nucleotide polymorphisms (SNPs) located on porcine chromosome 17 were significantly associated with LMD in Yorkshire pigs. A 10 kb quantitative trait locus (QTL) was identified as a candidate functional genomic region through the integration of linkage disequilibrium and linkage analysis (LDLA) and high-throughput chromosome conformation capture (Hi-C) analysis. The BMP2 gene was identified as a candidate gene for LMD based on the integrated results of GWAS, Hi-C meta-analysis, and cis-regulatory element data. The identified QTL region was further verified through target region sequencing. Furthermore, through using dual-luciferase assays and electrophoretic mobility shift assays (EMSA), two SNPs, including SNP rs321846600, located in the enhancer region, and SNP rs1111440035, located in the promoter region, were identified as candidate SNPs that may be functionally related to the LMD.

CONCLUSIONS

Based on the results of GWAS, Hi-C, and cis-regulatory elements, the BMP2 gene was identified as an important candidate gene regulating variation in LMD. The SNPs rs321846600 and rs1111440035 were identified as candidate SNPs that are functionally related to the LMD of Yorkshire pigs. Our results shed light on the advantages of integrating GWAS with 3D epigenomics in identifying candidate genes for quantitative traits. This study is a pioneering work for the identification of candidate genes and related genetic variants regulating one key production trait (LMD) in pigs by integrating genome-wide association studies and 3D epigenomics.

The SWine IMputation (SWIM) haplotype reference panel enables nucleotide resolution genetic mapping in pigs

Genetic mapping to identify genes and alleles associated with or causing economically important quantitative trait variation in livestock animals such as pigs is a major goal in animal genetic improvement. Despite recent advances in high-throughput genotyping technologies, the resolution of genetic mapping in pigs remains poor due in part to the low density of genotyped variant sites. In this study, we overcame this limitation by developing a reference haplotype panel for pigs based on 2259 whole genome-sequenced animals representing 44 pig breeds. We evaluated software combinations and breed composition to optimize the imputation procedure and achieved an average concordance rate in excess of 96%, a non-reference concordance rate of 88%, and an r² of 0.85. We demonstrated in two case studies that genotype imputation using this resource can dramatically improve the resolution of genetic mapping. A public web server has been developed to allow the pig genetics community to fully utilize this resource. We expect this resource to facilitate genetic mapping and accelerate genetic improvement in pigs.

Polymorphisms in SHISA3 and RFC3 genes and their association with feed conversion ratio in Hu sheep

In animal husbandry, feed efficiency is a crucial economic trait. In this study, the general linear model was used to perform association analysis for various genotypes and feed conversion ratio (FCR)-related traits. Reverse transcription-quantitative PCR (RT-qPCR) was used to detect the expression of SHISA3 and RFC3 mRNA levels in 10 tissues from 6 sheep. The results showed that SNPs in the NC_040257.1:c.625 T > C and NC_040261.1:g.9905 T > C were analyzed whether they were associated to feed efficiency parameters in Hu sheep (body weight, feed intake, average daily growth, and feed conversion ratio). NC_040257.1:c.625 T > C was shown to be significantly associated with body weight at 80, 100, and 120 days as well as feed conversion ratio (P < 0.05), whereas NC_040261.1:g.9905 T > C was found to be significantly associated with average daily weight gain from 80-140 days (ADG80-140) and FCR (P < 0.05). In Hu sheep, the CC genotypes of SHISA3 and RFC3 were the most common genotypes related to feed efficiency traits. Furthermore, the feed conversion ratio of the combined genotypes TT ^SHISA3-CC ^RFC3, TT ^SHISA3-CT ^RFC3, TT ^SHISA3-TT ^RFC3, CT ^SHISA3-CC ^RFC3 and CT ^SHISA3-CT ^RFC3 was significantly better than the FCR of CC ^SHISA3-TT ^RFC3. RT-qPCR results showed that the expression levels of SHISA3 were lower in the lung than in spleen, kidney, muscle and lymph (P < 0.05), and RFC3 was the lung had a highly significant higher expression level than the heart, liver, spleen, and muscle (P < 0.01). In conclusion, SHISA3 and RFC3 polymorphisms can be used as genetic markers for improving feed conversion efficiency in Hu sheep.

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.

Meta-analysis of genome-wide association studies uncovers shared candidate genes across breeds for pig fatness trait

Background

Average backfat thickness (BFT) is a critical complex trait in pig and an important indicator for fat deposition and lean rate. Usually, genome-wide association study (GWAS) was used to discover quantitative trait loci (QTLs) of BFT in a single population. However, the power of GWAS is limited by sample size in a single population. Alternatively, meta-analysis of GWAS (metaGWAS) is an attractive method to increase the statistical power by integrating data from multiple breeds and populations. The aim of this study is to identify shared genetic characterization of BFT across breeds in pigs via metaGWAS. 

Results

In this study, we performed metaGWAS on BFT using 15,353 pigs (5,143 Duroc, 7,275 Yorkshire, and 2,935 Landrace) from 19 populations. We detected 40 genome-wide significant SNPs (Bonferroni corrected P < 0.05) and defined five breed-shared QTLs in across-breed metaGWAS. Markers within the five QTL regions explained 7 ~ 9% additive genetic variance and showed strong heritability enrichment. Furthermore, by integrating information from multiple bioinformatics databases, we annotated 46 candidate genes located in the five QTLs. Among them, three important (MC4R, PPARD, and SLC27A1) and seven suggestive candidate genes (PHLPP1, NUDT3, ILRUN, RELCH, KCNQ5, ITPR3, and U3) were identified.

Conclusion

QTLs and candidate genes underlying BFT across breeds were identified via metaGWAS from multiple populations. Our findings contribute to the understanding of the genetic architecture of BFT and the regulating mechanism underlying fat deposition in pigs.

Integrative Analysis Between Genome-Wide Association Study and Expression Quantitative Trait Loci Reveals Bovine Muscle Gene Expression Regulatory Polymorphisms Associated With Intramuscular Fat and Backfat Thickness

Understanding the architecture of gene expression is fundamental to unravel the molecular mechanisms regulating complex traits in bovine, such as intramuscular fat content (IMF) and backfat thickness (BFT). These traits are economically important for the beef industry since they affect carcass and meat quality. Our main goal was to identify gene expression regulatory polymorphisms within genomic regions (QTL) associated with IMF and BFT in Nellore cattle. For that, we used RNA-Seq data from 193 Nellore steers to perform SNP calling analysis. Then, we combined the RNA-Seq SNP and a high-density SNP panel to obtain a new dataset for further genome-wide association analysis (GWAS), totaling 534,928 SNPs. GWAS was performed using the Bayes B model. Twenty-one relevant QTL were associated with our target traits. The expression quantitative trait loci (eQTL) analysis was performed using Matrix eQTL with the complete SNP dataset and 12,991 genes, revealing a total of 71,033 cis and 36,497 trans-eQTL (FDR &lt; 0.05). Intersecting with QTL for IMF, we found 231 eQTL regulating the expression levels of 117 genes. Within those eQTL, three predicted deleterious SNPs were identified. We also identified 109 eQTL associated with BFT and affecting the expression of 54 genes. This study revealed genomic regions and regulatory SNPs associated with fat deposition in Nellore cattle. We highlight the transcription factors FOXP4, FOXO3, ZSCAN2, and EBF4, involved in lipid metabolism-related pathways. These results helped us to improve our knowledge about the genetic architecture behind important traits in cattle.

Application of Genetic, Genomic and Biological Pathways in Improvement of Swine Feed Efficiency

Despite the significant improvement of feed efficiency (FE) in pigs over the past decades, feed costs remain a major challenge for producers profitability. Improving FE is a top priority for the global swine industry. A deeper understanding of the biology underlying FE is crucial for making progress in genetic improvement of FE traits. This review comprehensively discusses the topics related to the FE in pigs including: measurements, genetics, genomics, biological pathways and the advanced technologies and methods involved in FE improvement. We first provide an update of heritability for different FE indicators and then characterize the correlations of FE traits with other economically important traits. Moreover, we present the quantitative trait loci (QTL) and possible candidate genes associated with FE in pigs and outline the most important biological pathways related to the FE traits in pigs. Finally, we present possible ways to improve FE in swine including the implementation of genomic selection, new technologies for measuring the FE traits, and the potential use of genome editing and omics technologies.

Fine Mapping of a Major Backfat QTL Reveals a Causal Regulatory Variant Affecting the CCND2 Gene

Backfat is an important trait in pork production, and it has been included in the breeding objectives of genetic companies for decades. Although adipose tissue is a good energy storage, excessive fat results in reduced efficiency and economical losses. A large QTL for backfat thickness on chromosome 5 is still segregating in different commercial pig breeds. We fine mapped this QTL region using a genome-wide association analysis (GWAS) with 133,358 genotyped animals from five commercial populations (Landrace, Pietrain, Large White, Synthetic, and Duroc) imputed to the porcine 660K SNP chip. The lead SNP was located at 5:66103958 (G/A) within the third intron of the CCND2 gene, with the G allele associated with more backfat, while the A allele is associated with less backfat. We further phased the QTL region to discover a core haplotype of five SNPs associated with low backfat across three breeds. Linkage disequilibrium analysis using whole-genome sequence data revealed three candidate causal variants within intronic regions and downstream of the CCND2 gene, including the lead SNP. We evaluated the association of the lead SNP with the expression of the genes in the QTL region (including CCND2) in a large cohort of 100 crossbred samples, sequenced in four different tissues (lung, spleen, liver, muscle). Results show that the A allele increases the expression of CCND2 in an additive way in three out of four tissues. Our findings indicate that the causal variant for this QTL region is a regulatory variant within the third intron of the CCND2 gene affecting the expression of CCND2.

Transcriptome Analysis of Breast Muscle Reveals Pathways Related to Protein Deposition in High Feed Efficiency of Native Turkeys

Feed efficiency is important due to the high cost of food, which accounts for about 70% of the total cost of a turkey breeding system. Native poultry are an important genetic resource in poultry breeding programs. This study aimed to conduct a global transcriptome analysis of native male turkeys which have been phenotyped for high and low feed efficiency. Feed efficiency traits were recorded during the experimental period. After slaughter, the three most efficient and three least efficient male turkeys were selected for RNA-Seq analysis. A total of 365 genes with different expressions in muscle tissue were identified between turkeys with a high feed efficiency compared to turkeys with a low feed efficiency. In the pathway analysis of up-regulated genes, major pathways included the "metabolism of glycine, serine, and threonine"; the "adipocytokine signaling pathway" and the "biosynthesis of amino acids". In the pathway analysis of down-regulated genes, the major pathways included "dorso-ventral axis formation" and "actin cytoskeleton regulation". In addition, gene set enrichment analyses were performed, which showed that high feed efficiency birds exhibit an increased expression of genes related to the biosynthesis of amino acids and low feed efficiency birds an increased expression of genes related to the immune response. Furthermore, functional analysis and protein network interaction analysis revealed that genes including GATM, PSAT1, PSPH, PHGDH, VCAM1, CD44, KRAS, SRC, CAV3, NEDD9, and PTPRQ were key genes for feed efficiency. These key genes may be good potential candidates for biomarkers of feed efficiency in genetic selection in turkeys.

New insights into genetics underlying of plumage color

Plumage color can be considered as a social signal in chickens and a breeding identification tool among breeders. The relationship between plumage color and trait groups of immunity, growth and fertility is still a controversial issue. This research aimed to determine the genome-wide additive and epistatic variants affecting plumage color variation in chickens using the chicken Illumina 60k high-density SNP array. Two scenarios of genome-wide additive association studies using all SNPs and independent SNPs were carried out. To perform epistatic association analysis, the LD pruning approach was used to reduce the complexity of the analysis. We detected seven novel significant loci using all of the SNPs in the model and 14 SNPs using the LD pruning approach associated with plumage color. Moreover, 89 significantly associated SNP-SNP interactions (P-value <10^-6 ) distributed in 25 chromosomes were identified, indicating that all of the signals together putatively influence the quantitative variation of plumage color. By annotating genes relevant to top SNPs, we have distinguished 18 potential candidate genes comprising HNF4beta, CKMT1B, TBC1D22A, RPL8, CACNA2D1, FZD4, SGMS1, IRF8, OPTN, LOC420362, TRABD, OvoDA1, DAD1, USP6, RBM12B, MIR1772, MIR1709 and MIR6696 and also 89 putative gene-gene combinations responsible for plumage color variation in chickens. Furthermore, several KEGG pathways including metabolic pathway, cytokine-cytokine receptor interaction, focal adhesion, melanogenesis, glycosaminoglycan biosynthesis-keratan sulfate and sphingolipid metabolism were enriched in the gene-set analysis. The results indicated that plumage color is a highly polygenic trait which, in turn, can be affected by multiple coding genes, regulatory genes and gene-gene epistasis interactions. In addition to genes with additive effects, epistatic genes with tiny individual effect sizes but significant effects in a pair have the potential to control plumage coloration in chickens.

Genome-wide association study of resistance/susceptibility to infectious bovine keratoconjunctivitis in Brazilian Hereford cattle

Genome-wide association studies were conducted to identify the more informative genomic regions and SNPs, as well as to identify candidate genes associated with infectious bovine keratoconjunctivitis (IBK) resistance/susceptibility in Hereford cattle. A Bayes B statistical approach was initially applied in genome-wide association studies by using deregressed estimated breeding values for IBK resistance/susceptibility. To estimate the combined effect of a genomic region that is potentially associated with QTL, 2504 non-overlapping 1-Mb windows that varied in SNP number were defined, with the most informative 24 windows including 427 SNPs and explaining more than 20% of the estimated genetic variance for IBK resistance/susceptibility. These regions were explored with respect to their biological functions through functional analysis to map potential candidate genes. The significant SNPs were mapped on chromosomes 1, 3, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 18, 20, 23, and 28, and candidate genes were detected as related to the IBK. Most informative SNPs in term of genetic variance were located in proximity of genes related to phenotypic expression of lesions and biological processes associated to the IBK. Knowledge about phenotypic and genomic variation generated in the present study can be used to on design selection strategies to improve the resistance to IBK of Hereford cattle herds.

Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds

Background

Backfat thickness is an important carcass composition trait for pork production and is commonly included in swine breeding programmes. In this paper, we report the results of a large genome-wide association study for backfat thickness using data from eight lines of diverse genetic backgrounds.

Methods

Data comprised 275,590 pigs from eight lines with diverse genetic backgrounds (breeds included Large White, Landrace, Pietrain, Hampshire, Duroc, and synthetic lines) genotyped and imputed for 71,324 single-nucleotide polymorphisms (SNPs). For each line, we estimated SNP associations using a univariate linear mixed model that accounted for genomic relationships. SNPs with significant associations were identified using a threshold of p < 10^–6 and used to define genomic regions of interest. The proportion of genetic variance explained by a genomic region was estimated using a ridge regression model.

Results

We found significant associations with backfat thickness for 264 SNPs across 27 genomic regions. Six genomic regions were detected in three or more lines. The average estimate of the SNP-based heritability was 0.48, with estimates by line ranging from 0.30 to 0.58. The genomic regions jointly explained from 3.2 to 19.5% of the additive genetic variance of backfat thickness within a line. Individual genomic regions explained up to 8.0% of the additive genetic variance of backfat thickness within a line. Some of these 27 genomic regions also explained up to 1.6% of the additive genetic variance in lines for which the genomic region was not statistically significant. We identified 64 candidate genes with annotated functions that can be related to fat metabolism, including well-studied genes such as MC4R, IGF2, and LEPR, and more novel candidate genes such as DHCR7, FGF23, MEDAG, DGKI, and PTN.

Conclusions

Our results confirm the polygenic architecture of backfat thickness and the role of genes involved in energy homeostasis, adipogenesis, fatty acid metabolism, and insulin signalling pathways for fat deposition in pigs. The results also suggest that several less well-understood metabolic pathways contribute to backfat development, such as those of phosphate, calcium, and vitamin D homeostasis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00671-w.

A Missense Mutation in the MYBPH Gene Is Associated With Abdominal Fat Traits in Meat-Type Chickens

Chicken is an important source of protein for human nutrition and a model system for growth and developmental biology. Although the genetic architecture of quantitative traits in meat-type chickens has been the subject of ongoing investigation, the identification of mutations associated with carcass traits of economic interest remains challenging. Therefore, our aim was to identify predicted deleterious mutation, which potentially affects protein function, and test if they were associated with carcass traits in chickens. For that, we performed a genome-wide association analysis (GWAS) for breast, thigh and drumstick traits in meat-type chickens and detected 19 unique quantitative trait loci (QTL). We then used: (1) the identified windows; (2) QTL for abdominal fat detected in a previous study with the same population and (3) previously obtained whole genome sequence data, to identify 18 predicted deleterious single nucleotide polymorphisms (SNPs) in those QTL for further association with breast, thigh, drumstick and abdominal fat traits. Using the additive model, a predicted deleterious SNP c.482C > T (SIFT score of 0.4) was associated (p-value < 0.05) with abdominal fat weight and percentage. This SNP is in the second exon of the MYBPH gene, and its allele frequency deviates from Hardy–Weinberg equilibrium. In conclusion, our study provides evidence that the c.482C > T SNP in the MYBPH gene is a putative causal mutation for fat deposition in meat-type chickens.

Identification of genomic regions affecting production traits in pigs divergently selected for feed efficiency

BACKGROUND

Feed efficiency is a major driver of the sustainability of pig production systems. Understanding the biological mechanisms that underlie these agronomic traits is an important issue for environment questions and farms' economy. This study aimed at identifying genomic regions that affect residual feed intake (RFI) and other production traits in two pig lines divergently selected for RFI during nine generations (LRFI, low RFI; HRFI, high RFI).

RESULTS

We built a whole dataset of 570,447 single nucleotide polymorphisms (SNPs) in 2426 pigs with records for 24 production traits after both imputation and prediction of genotypes using pedigree information. Genome-wide association studies (GWAS) were performed including both lines (global-GWAS) or each line independently (LRFI-GWAS and HRFI-GWAS). Forty-five chromosomal regions were detected in the global-GWAS, whereas 28 and 42 regions were detected in the HRFI-GWAS and LRFI-GWAS, respectively. Among these 45 regions, only 13 were shared between at least two analyses, and only one was common between the three GWAS but it affects different traits. Among the five quantitative trait loci (QTL) detected for RFI, two were close to QTL for meat quality traits and two pinpointed novel genomic regions that harbor candidate genes involved in cell proliferation and differentiation processes of gastrointestinal tissues or in lipid metabolism-related signaling pathways. In most cases, different QTL regions were detected between the three designs, which suggests a strong impact of the dataset structure on the detection power and could be due to the changes in allelic frequencies during the establishment of lines.

CONCLUSIONS

In addition to efficiently detecting known and new QTL regions for feed efficiency, the combination of GWAS carried out per line or simultaneously using all individuals highlighted chromosomal regions that affect production traits and presented significant changes in allelic frequencies across generations. Further analyses are needed to estimate whether these regions correspond to traces of selection or result from genetic drift.

Characterization and Comparative Transcriptomic Analysis of Skeletal Muscle in Pekin Duck at Different Growth Stages Using RNA-Seq

Simple Summary

Skeletal muscle is an important tissue and its development is strictly regulated by genes. In this study, in order to understand the muscle-related gene expression in Pekin duck, RNA-seq was performed to analyze and compare skeletal muscle at different growth stages. Alternative splicing, single nucleotide polymorphisms and insertion–deletions were detected, and 299 novel genes were discovered. MYL4, IGF2BP1, CSRP3, SPP1, KLHL31, LAMB2, LAMA2, ITGB1 and OPN played crucial roles in skeletal muscle development. Oxidative phosphorylation, ECM-receptor interaction, focal adhesion, carbon metabolism, and biosynthesis of amino acids participated in the regulation of skeletal muscle development in Pekin duck. This study provides an important reference for revealing the developmental mechanisms of pectoral and leg muscles in duck.

Abstract

Skeletal muscle, accounting for approximately 50% of body weight, is the largest and most important tissue. In this study, the gene expression profiles and pathways in skeletal muscle of Pekin duck were investigated and compared at embryonic day 17, 21, and 27 and postnatally at 6 months of age. An average of 49,555,936 reads in each sample was obtained from the transcriptome libraries. Over 70.0% of alternative splicing (AS) in each sample was mainly alternative 5′ first exon (transcription start site)—the first exon splicing (TSS) and alternative 3′ last exon (transcription terminal site)—the last exon splicing (TTS), indicating that TSS and TTS were the most common AS event in Pekin ducks, and these AS events were closely related to the regulation of muscle development at different growth stages. The results provided a valuable genomic resource for selective breeding and functional studies of genes. A total of 299 novel genes with ≥2 exons were obtained. There were 294 to 2806 differentially expressed genes (DEGs) in each pairwise comparison of Pekin duck. Notably, 90 DEGs in breast muscle and 9 DEGs in leg muscle were co-expressed at all developmental points. DEGs were validated by qPCR analysis, which confirmed the tendency of the expression. DEGs related to muscle development were involved in biological processes such as “endodermal cell differentiation”, “muscle cell cellular homeostasis”, “skeletal muscle tissue growth” and “skeletal muscle cell differentiation”, and were involved in pathways such as oxidative phosphorylation, ECM-receptor (extracellular matrix receptor) interaction, focal adhesion, carbon metabolism, and biosynthesis of amino acids. Some DEGs, including MYL4, IGF2BP1, CSRP3, SPP1 and KLHL31, as well as LAMB2, LAMA2, ITGB1 and OPN, played crucial roles in muscle growth and development. This study provides valuable information about the expression profile of mRNAs and pathways from duck skeletal muscle at different growth stages, and further functional study of these mRNAs and pathways could provide new ideas for studying the molecular networks of growth and development in duck skeletal muscle.

Identification of Predictor Genes for Feed Efficiency in Beef Cattle by Applying Machine Learning Methods to Multi-Tissue Transcriptome Data

Machine learning (ML) methods have shown promising results in identifying genes when applied to large transcriptome datasets. However, no attempt has been made to compare the performance of combining different ML methods together in the prediction of high feed efficiency (HFE) and low feed efficiency (LFE) animals. In this study, using RNA sequencing data of five tissues (adrenal gland, hypothalamus, liver, skeletal muscle, and pituitary) from nine HFE and nine LFE Nellore bulls, we evaluated the prediction accuracies of five analytical methods in classifying FE animals. These included two conventional methods for differential gene expression (DGE) analysis (t-test and edgeR) as benchmarks, and three ML methods: Random Forests (RFs), Extreme Gradient Boosting (XGBoost), and combination of both RF and XGBoost (RX). Utility of a subset of candidate genes selected from each method for classification of FE animals was assessed by support vector machine (SVM). Among all methods, the smallest subsets of genes (117) identified by RX outperformed those chosen by t-test, edgeR, RF, or XGBoost in classification accuracy of animals. Gene co-expression network analysis confirmed the interactivity existing among these genes and their relevance within the network related to their prediction ranking based on ML. The results demonstrate a great potential for applying a combination of ML methods to large transcriptome datasets to identify biologically important genes for accurately classifying FE animals.

Identification of QTL regions and candidate genes for growth and feed efficiency in broilers

BACKGROUND

Feed accounts for about 70% of the total cost of poultry meat production. Residual feed intake (RFI) has become the preferred measure of feed efficiency because it is phenotypically independent of growth rate and body weight. In this study, our aim was to estimate genetic parameters and identify quantitative trait loci (QTL) for feed efficiency in 3314 purebred broilers using a genome-wide association study. Broilers were genotyped using a custom 55 K single nucleotide polymorphism (SNP) array.

RESULTS

Estimates of genomic heritability for seven growth and feed efficiency traits, including body weight at 28 days of age (BW28), BW42, average daily feed intake (ADFI), RFI, and RFI adjusted for weight of abdominal fat (RFIa), ranged from 0.12 to 0.26. Eleven genome-wide significant SNPs and 15 suggestively significant SNPs were detected, of which 19 clustered around two genomic regions. A region on chromosome 16 (2.34-2.66 Mb) was associated with both BW28 and BW42, and the most significant SNP in this region, AX_101003762, accounted for 7.6% of the genetic variance of BW28. The other region, on chromosome 1 (91.27-92.43 Mb) was associated with RFI and ADFI, and contains the NSUN3 and EPHA6 as candidate genes. The most significant SNP in this region, AX_172588157, accounted for 4.4% of the genetic variance of RFI. In addition, a genomic region containing the gene AGK on chromosome 1 was found to be associated with RFIa. The NSUN3 and AGK genes were found to be differentially expressed in breast muscle, thigh muscle, and abdominal fat between male broilers with high and low RFI.

CONCLUSIONS

We identified QTL regions for BW28 and BW42 (spanning 0.32 Mb) and RFI (spanning 1.16 Mb). The NSUN3, EPHA6, and AGK were identified as the most likely candidate genes for these QTL. These genes are involved in mitochondrial function and behavioral regulation. These results contribute to the identification of candidate genes and variants for growth and feed efficiency in poultry.

Brain Transcriptome Analysis Reveals Potential Transcription Factors and Biological Pathways Associated with Feed Efficiency in Commercial DLY Pigs

Feed efficiency (FE) is one of the most important economic traits in the porcine industry. In this study, high-throughput RNA sequencing (RNA-seq) was first utilized for brain tissue transcriptome analysis in pigs to indicate the potential genes and biological pathways related to FE in pigs. A total of 8 pigs with either extremely high-FE group (HE-group) or low-FE group (LE-group) were selected from 225 Duroc × (Landrace × Yorkshire) (DLY) pigs for transcriptomic analysis. RNA-seq analysis was performed to determine differentially expressed genes (DEGs) between the HE- and LE-group, and 430 DEGs were identified in brain tissues of pigs (|log₂(FoldChange)| > 1; adjusted p-values <0.05). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the DEGs were mainly enriched in synaptic signaling or transmission, and hormone secretion pathways, in which insulin secretion, and oxytocin signaling pathways were closely associated with FE by regulating feeding behavior and energy metabolism (adjusted p-values <0.05). Further, the transcription factors (TFs) analysis and gene co-expression network analysis indicated three hub differentially expressed TFs (NR2F2, TFAP2D, and HNF1B) that affected FE by mainly regulating feeding behavior, insulin sensitivity, or energy metabolism. Our findings suggest several potential TFs and biological pathways for further investigations of FE in pigs.

Loci Associated With Antibody Response in Feral Swine (Sus scrofa) Infected With Brucella suis

Feral swine (Sus scrofa) are a destructive invasive species widespread throughout the United States that disrupt ecosystems, damage crops, and carry pathogens of concern for the health of domestic stock and humans including Brucella suis-the causative organism for swine brucellosis. In domestic swine, brucellosis results in reproductive failure due to abortions and infertility. Contact with infected feral swine poses spillover risks to domestic pigs as well as humans, companion animals, wildlife, and other livestock. Genetic factors influence the outcome of infectious diseases; therefore, genome wide association studies (GWAS) of differential immune responses among feral swine can provide an understanding of disease dynamics and inform management to prevent the spillover of brucellosis from feral swine to domestic pigs. We sought to identify loci associated with differential antibody responses among feral swine naturally infected with B. suis using a case-control GWAS. Tissue, serum, and genotype data (68,516 bi-allelic single nucleotide polymorphisms) collected from 47 feral swine were analyzed in this study. The 47 feral swine were culture positive for Brucella spp. Of these 47, 16 were antibody positive (cases) whereas 31 were antibody negative (controls). Single-locus GWAS were performed using efficient mixed-model association eXpedited (EMMAX) methodology with three genetic models: additive, dominant, and recessive. Eight loci associated with seroconversion were identified on chromosome 4, 8, 9, 10, 12, and 18. Subsequent bioinformatic analyses revealed nine putative candidate genes related to immune function, most notably phagocytosis and induction of an inflammatory response. Identified loci and putative candidate genes may play an important role in host immune responses to B. suis infection, characterized by a detectable bacterial presence yet a differential antibody response. Given that antibody tests are used to evaluate brucellosis infection in domestic pigs and for disease surveillance in invasive feral swine, additional studies are needed to fully understand the genetic component of the response to B. suis infection and to more effectively translate estimates of Brucella spp. antibody prevalence among feral swine to disease control management action.

Genomic sequencing analysis reveals copy number variations and their associations with economically important traits in beef cattle

Copy number variation (CNV) represents a major source of genetic variation, which may have potentially large effects, including alternating gene regulation and dosage, as well as contributing to gene expression and risk for normal phenotypic variability. We carried out a comprehensive analysis of CNV based on whole genome sequencing in Chinese Simmental beef cattle. Totally, we found 9313 deletion and 234 duplication events, covering 147.5 Mb autosomal regions. Within them, 257 deletion events of high frequency overlapped with 193 known RefGenes. Among these genes, we observed several genes were related to economically important traits, like residual feed intake, immune responding, pregnancy rate and muscle differentiation. Using a locus-based analysis, we identified 11 deletions and 1 duplication, which were significantly associated with three traits including carcass weight, tenderloin and longissimus muscle area. Our sequencing-based study provided important insights into investigating the association of CNVs with important traits in beef cattle.

A Genome-Wide Association Study on Feed Efficiency Related Traits in Landrace Pigs

Feed efficiency (FE) traits in pigs are of utmost economic importance. Genetic improvement of FE related traits in pigs might significantly reduce production cost and energy consumption. Hence, our study aimed at identifying SNPs and candidate genes associated with FE related traits, including feed conversion ratio (FCR), average daily gain (ADG), average daily feed intake (ADFI), and residual feed intake (RFI). A genome-wide association study (GWAS) was performed for the four FE related traits in 296 Landrace pigs genotyped with PorcineSNP50 BeadChip. Two different single-trait methods, single SNP linear model GWAS (LM-GWAS) and single-step GWAS (ssGWAS), were implemented. Our results showed that the two methods showed high consistency with respect to SNP identification. A total of 32 common significant SNPs associated with the four FE related traits were identified. Bioinformatics analysis revealed eight common QTL regions, of which three QTL regions related to ADFI and RFI traits were overlapped. Gene ontology analysis revealed six common candidate genes (PRELID2, GPER1, PDX1, TEX2, PLCL2, ICAM2) relevant for the four FE related traits. These genes are involved in the processes of fat synthesis and decomposition, lipid transport process, insulin metabolism, among others. Our results provide, new insights into the genetic mechanisms and candidate function genes of FE related traits in pigs. However, further investigations to validate these results are warranted.

Evaluating the association between feed efficiency and the fecal microbiota of early-life Duroc pigs using 16S rRNA sequencing

Improving the predication efficiency of porcine production performance at early stage will contribute to reducing the breeding and production costs. The intestinal microbiota had received plenty of attention in recent years due to their influence on host health and performance. The purpose of this study was to investigate the relationship between the fecal microbiota at early growth period and porcine feed efficiency (FE) under a commercial feeding environment. Ninety-one pigs were reordered according to the residual feed intake (RFI) values between day 90 on test and day 160 off test, 9 lowest RFI pigs and 9 highest RFI pigs were selected as the LRFI group and the HRFI group, respectively. Fecal samples from pigs in the early grower phase (day 80) were performed for microbial diversity, composition, and predicted functionality by using 16S rRNA sequencing. The results showed that no significant differences in microbial alpha diversity were observed between two RFI groups, whereas, some RFI-associated compositional differences were revealed. In particular, the microbiota of the LRFI group (more feed-efficient) had significantly higher levels of some members of Clostridiales and Bacteroidales (e.g., g_1_68 and g_norank_f_p_2534_18B5), which may promoted FE through protecting gut barrier function, compared with those of the HRFI pigs. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis found that the LRFI pigs were likely have microbiota with higher levels of amino acid metabolism. Moreover, redundancy analysis (RDA) showed that litter size, parity, and date of birth had significant effects on the bacterial community structure. These results improved our knowledge of the porcine early-life fecal microbiota and its potential link underlying RFI, which would be useful for future development of microbial biomarkers for predicting and improving porcine FE as well as investigation of targets for dietary strategies.

A Transcriptome Analysis Reveals that Hepatic Glycolysis and Lipid Synthesis Are Negatively Associated with Feed Efficiency in DLY Pigs

Feed efficiency (FE) is an important trait in the porcine industry. Therefore, understanding the molecular mechanisms of FE is vital for the improvement of this trait. In this study, 6 extreme high-FE and 6 low-FE pigs were selected from 225 Duroc × (Landrace × Yorkshire) (DLY) pigs for transcriptomic analysis. RNA-seq analysis was performed to determine differentially expressed genes (DEGs) in the liver tissues of the 12 individuals, and 507 DEGs were identified between high-FE pigs (HE- group) and low-FE pigs (LE- group). A gene ontology (GO) enrichment and pathway enrichment analysis were performed and revealed that glycolytic metabolism and lipid synthesis-related pathways were significantly enriched within DEGs; all of these DEGs were downregulated in the HE- group. Moreover, Weighted gene co-expression analysis (WGCNA) revealed that oxidative phosphorylation, thermogenesis, and energy metabolism-related pathways were negatively related to HE- group, which might result in lower energy consumption in higher efficiency pigs. These results implied that the higher FE in the HE- group may be attributed to a lower glycolytic, energy consumption and lipid synthesizing potential in the liver. Furthermore, our findings suggested that the inhibition of lipid synthesis and glucose metabolic activity in the liver may be strategies for improving the FE of DLY pigs.

Metabolite Genome-Wide Association Study (mGWAS) and Gene-Metabolite Interaction Network Analysis Reveal Potential Biomarkers for Feed Efficiency in Pigs

Metabolites represent the ultimate response of biological systems, so metabolomics is considered the link between genotypes and phenotypes. Feed efficiency is one of the most important phenotypes in sustainable pig production and is the main breeding goal trait. We utilized metabolic and genomic datasets from a total of 108 pigs from our own previously published studies that involved 59 Duroc and 49 Landrace pigs with data on feed efficiency (residual feed intake (RFI)), genotype (PorcineSNP80 BeadChip) data, and metabolomic data (45 final metabolite datasets derived from LC-MS system). Utilizing these datasets, our main aim was to identify genetic variants (single-nucleotide polymorphisms (SNPs)) that affect 45 different metabolite concentrations in plasma collected at the start and end of the performance testing of pigs categorized as high or low in their feed efficiency (based on RFI values). Genome-wide significant genetic variants could be then used as potential genetic or biomarkers in breeding programs for feed efficiency. The other objective was to reveal the biochemical mechanisms underlying genetic variation for pigs' feed efficiency. In order to achieve these objectives, we firstly conducted a metabolite genome-wide association study (mGWAS) based on mixed linear models and found 152 genome-wide significant SNPs (p-value < 1.06 × 10-6) in association with 17 metabolites that included 90 significant SNPs annotated to 52 genes. On chromosome one alone, 51 significant SNPs associated with isovalerylcarnitine and propionylcarnitine were found to be in strong linkage disequilibrium (LD). SNPs in strong LD annotated to FBXL4, and CCNC consisted of two haplotype blocks where three SNPs (ALGA0004000, ALGA0004041, and ALGA0004042) were in the intron regions of FBXL4 and CCNC. The interaction network revealed that CCNC and FBXL4 were linked by the hub gene N6AMT1 that was associated with isovalerylcarnitine and propionylcarnitine. Moreover, three metabolites (i.e., isovalerylcarnitine, propionylcarnitine, and pyruvic acid) were clustered in one group based on the low-high RFI pigs. This study performed a comprehensive metabolite-based genome-wide association study (GWAS) analysis for pigs with differences in feed efficiency and provided significant metabolites for which there is significant genetic variation as well as biological interaction networks. The identified metabolite genetic variants, genes, and networks in high versus low feed efficient pigs could be considered as potential genetic or biomarkers for feed efficiency.

Transcriptome Analysis of Skeletal Muscle in Pigs with Divergent Residual Feed Intake Phenotypes

Residual feed intake (RFI) is defined as the difference between the observed and expected feed intake for maintenance and growth requirements. In this study, the expression profiles of mRNAs and long noncoding RNAs (lncRNAs) from skeletal muscle in Duroc pigs with divergent RFI phenotypes were investigated by Illumina sequencing. Finally, a total of 2195 annotated lncRNAs and 1976 novel lncRNAs were obtained. About 210 mRNAs and 43 lncRNAs were differentially expressed among high and low RFI pigs. The differentially expressed mRNAs were potentially involved in the biological processes of lipid metabolism, extracellular matrix organization, cell proliferation, and cell adhesion. The lipolysis in skeletal muscle was increased in high RFI pigs, suggesting that high RFI pigs might need more energy than low RFI pigs. However, skeletal muscle development was increased in low RFI pigs. These results suggested that low RFI pigs might be more efficient in energy utilization during skeletal muscle growth. The function of lncRNA was also analyzed by target prediction. Nine lncRNAs might be candidate lncRNAs for the determination of RFI phenotype, by the regulation of the biological processes of lipid metabolism, cell proliferation, and cell adhesion. This study should facilitate a further understanding of the molecular mechanism for the determination of RFI phenotype in pigs.

Combining information from genome-wide association and multi-tissue gene expression studies to elucidate factors underlying genetic variation for residual feed intake in Australian Angus cattle

BACKGROUND

Genome-wide association studies (GWAS) are extensively used to identify single nucleotide polymorphisms (SNP) underlying the genetic variation of complex traits. However, much uncertainly often still exists about the causal variants and genes at quantitative trait loci (QTL). The aim of this study was to identify QTL associated with residual feed intake (RFI) and genes in these regions whose expression is also associated with this trait. Angus cattle (2190 steers) with RFI records were genotyped and imputed to high density arrays (770 K) and used for a GWAS approach to identify QTL associated with RFI. RNA sequences from 126 Angus divergently selected for RFI were analyzed to identify the genes whose expression was significantly associated this trait with special attention to those genes residing in the QTL regions.

RESULTS

The heritability for RFI estimated for this Angus population was 0.3. In a GWAS, we identified 78 SNPs associated with RFI on six QTL (on BTA1, BTA6, BTA14, BTA17, BTA20 and BTA26). The most significant SNP was found on chromosome BTA20 (rs42662073) and explained 4% of the genetic variance. The minor allele frequencies of significant SNPs ranged from 0.05 to 0.49. All regions, except on BTA17, showed a significant dominance effect. In 1 Mb windows surrounding the six significant QTL, we found 149 genes from which OAS2, STC2, SHOX, XKR4, and SGMS1 were the closest to the most significant QTL on BTA17, BTA20, BTA1, BTA14, and BTA26, respectively. In a 2 Mb windows around the six significant QTL, we identified 15 genes whose expression was significantly associated with RFI: BTA20) NEURL1B and CPEB4; BTA17) RITA1, CCDC42B, OAS2, RPL6, and ERP29; BTA26) A1CF, SGMS1, PAPSS2, and PTEN; BTA1) MFSD1 and RARRES1; BTA14) ATP6V1H and MRPL15.

CONCLUSIONS

Our results showed six QTL regions associated with RFI in a beef Angus population where five of these QTL contained genes that have expression associated with this trait. Therefore, here we show that integrating information from gene expression and GWAS studies can help to better understand the genetic mechanisms that determine variation in complex traits.

Unraveling genomic associations with feed efficiency and body weight traits in chickens through an integrative approach

BACKGROUND

Feed efficiency and growth rate have been targets for selection to improve chicken production. The incorporation of genomic tools may help to accelerate selection. We genotyped 529 individuals using a high-density SNP chip (600 K, Affymetrix®) to estimate genomic heritability of performance traits and to identify genomic regions and their positional candidate genes associated with performance traits in a Brazilian F2 Chicken Resource population. Regions exhibiting selection signatures and a SNP dataset from resequencing were integrated with the genomic regions identified using the chip to refine the list of positional candidate genes and identify potential causative mutations.

RESULTS

Feed intake (FI), feed conversion ratio (FC), feed efficiency (FE) and weight gain (WG) exhibited low genomic heritability values (i.e. from 0.0002 to 0.13), while body weight at hatch (BW1), 35 days-of-age (BW35), and 41 days-of-age (BW41) exhibited high genomic heritability values (i.e. from 0.60 to 0.73) in this F2 population. Twenty unique 1-Mb genomic windows were associated with BW1, BW35 or BW41, located on GGA1-4, 6-7, 10, 14, 24, 27 and 28. Thirty-eight positional candidate genes were identified within these windows, and three of them overlapped with selection signature regions. Thirteen predicted deleterious and three high impact sequence SNPs in these QTL regions were annotated in 11 positional candidate genes related to osteogenesis, skeletal muscle development, growth, energy metabolism and lipid metabolism, which may be associated with body weight in chickens.

CONCLUSIONS

The use of a high-density SNP array to identify QTL which were integrated with whole genome sequence signatures of selection allowed the identification of candidate genes and candidate causal variants. One novel QTL was detected providing additional information to understand the genetic architecture of body weight traits. We identified QTL for body weight traits, which were also associated with fatness in the same population. Our findings form a basis for further functional studies to elucidate the role of specific genes in regulating body weight and fat deposition in chickens, generating useful information for poultry breeding programs.

A genome-wide association study for feed efficiency-related traits in a crossbred pig population

Feed efficiency (FE) is one of the most important traits in pig production. However, it is difficult and costly to measure it, limiting the collection of large amount of data for an accurate selection for better FE. Therefore, the identification of single-nucleotide polymorphisms (SNPs) associated with FE-related traits to be used in the genetic evaluation is of great interest of pig breeding programs for increasing the prediction accuracy and the genetic progress of these traits. The objective of this study was to identify SNPs significantly associated with FE-related traits: average daily gain (ADG), average daily feed intake (ADFI) and feed conversion ratio (FCR). We also aimed to identify potential candidate genes for these traits. Phenotypic information recorded on a population of 2386 three-way crossbreed pigs that were genotyped for 51 468 SNPs was used. We identified three loci of quantitative trait (QTL) regions associated with ADG and three QTL regions associated with ADFI; however, no significant association was found for FCR. A false discovery rate (FDR) ≤ 0.005 was used as the threshold for declaring an association as significant. The QTL regions associated with ADG on Sus scrofa chromosome (SSC) 1 were located between 177.01 and 185.47 Mb, which overlaps with the QTL regions for ADFI on SSC1 (173.26 and 185.47 Mb). The other QTL region for ADG was located on SSC12 (2.87 and 3.22 Mb). The most significant SNPs in these QTL regions explained up to 3.26% of the phenotypic variance of these traits. The non-identification of genomic regions associated with FCR can be explained by the complexity of this trait, which is a ratio between ADG and ADFI. Finally, the genes CDH19, CDH7, RNF152, MC4R, PMAIP1, FEM1B and GAA were the candidate genes found in the 1 Mb window around the QTL regions identified in this study. Among them, the MC4R gene (SSC1) has a well-known function related to ADG and ADFI. In this study, we identified three QTL regions for ADG (SSC1 and SSC12) and three for ADFI (SSC1). These regions were previously described in purebred pig populations; however, to our knowledge, this is the first study to confirm the relevance of these QTL regions in a crossbred pig population. The potential use of the SNPs and genes identified in this study in prediction models that combine genomic selection and marker-assisted selection should be evaluated for increasing the prediction accuracy of these traits in this population.

A genomewide association study in divergently selected lines in rabbits reveals novel genomic regions associated with litter size traits

Uterine capacity (UC), defined as the total number of kits from unilaterally ovariectomized does at birth, has a high genetic correlation with litter size. The aim of our research was to identify genomic regions associated with litter size traits through a genomewide association study using rabbits from a divergent selection experiment for UC. A high-density SNP array (200K) was used to genotype 181 does from a control population, high and low UC lines. Traits included total number born (TNB), number born alive (NBA), number born dead, ovulation rate (OR), implanted embryos (IE) and embryo, foetal and prenatal survivals at second parity. We implemented the Bayes B method and the associations were tested by Bayes factors and the percentage of genomic variance (GV) explained by windows. Different genomic regions associated with TNB, NBA, IE and OR were found. These regions explained 7.36%, 1.27%, 15.87% and 3.95% of GV, respectively. Two consecutive windows on chromosome 17 were associated with TNB, NBA and IE. This genomic region accounted for 6.32% of GV of TNB. In this region, we found the BMP4, PTDGR, PTGER2, STYX and CDKN3 candidate genes which presented functional annotations linked to some reproductive processes. Our findings suggest that a genomic region on chromosome 17 has an important effect on litter size traits. However, further analyses are needed to validate this region in other maternal rabbit lines.

Acute systemic inflammatory response to lipopolysaccharide stimulation in pigs divergently selected for residual feed intake

Background

It is unclear whether improving feed efficiency by selection for low residual feed intake (RFI) compromises pigs’ immunocompetence. Here, we aimed at investigating whether pig lines divergently selected for RFI had different inflammatory responses to lipopolysaccharide (LPS) exposure, regarding to clinical presentations and transcriptomic changes in peripheral blood cells.

Results

LPS injection induced acute systemic inflammation in both the low-RFI and high-RFI line (n = 8 per line). At 4 h post injection (hpi), the low-RFI line had a significantly lower (p = 0.0075) mean rectal temperature compared to the high-RFI line. However, no significant differences in complete blood count or levels of several plasma cytokines were detected between the two lines. Profiling blood transcriptomes at 0, 2, 6, and 24 hpi by RNA-sequencing revealed that LPS induced dramatic transcriptional changes, with 6296 genes differentially expressed at at least one time point post injection relative to baseline in at least one line (n = 4 per line) (|log₂(fold change)| ≥ log₂(1.2); q < 0.05). Furthermore, applying the same cutoffs, we detected 334 genes differentially expressed between the two lines at at least one time point, including 33 genes differentially expressed between the two lines at baseline. But no significant line-by-time interaction effects were detected. Genes involved in protein translation, defense response, immune response, and signaling were enriched in different co-expression clusters of genes responsive to LPS stimulation. The two lines were largely similar in their peripheral blood transcriptomic responses to LPS stimulation at the pathway level, although the low-RFI line had a slightly lower level of inflammatory response than the high-RFI line from 2 to 6 hpi and a slightly higher level of inflammatory response than the high-RFI line at 24 hpi.

Conclusions

The pig lines divergently selected for RFI had a largely similar response to LPS stimulation. However, the low-RFI line had a relatively lower-level, but longer-lasting, inflammatory response compared to the high-RFI line. Our results suggest selection for feed efficient pigs does not significantly compromise a pig’s acute systemic inflammatory response to LPS, although slight differences in intensity and duration may occur.

A Transcriptome Analysis Identifies Biological Pathways and Candidate Genes for Feed Efficiency in DLY Pigs

Feed cost accounts for approximately 65–75% of overall commercial pork production costs. Therefore, improving the feed efficiency of pig production is important. In this study, 12 individuals with either extremely high (HE) or low (LE) feed efficiency were selected from 225 Duroc × (Landrace × Yorkshire) (DLY) pigs. After the pigs were slaughtered, we collected small intestine mucosal tissue. Next, RNA sequencing (RNA-seq) analysis was used to reveal the presence and quantity of genes expressed between these extremely HE- and LE-groups. We found 433 significantly differentially expressed genes (DEGs) between the HE- and LE-groups. Of these, 389 and 44 DEGs were upregulated and downregulated in the HE-group, respectively. An enrichment analysis showed that the DEGs were mainly enriched in functions related to apical plasma membrane composition, transporter activity, transport process and hormone regulation of digestion and absorption. Protein network interaction and gene function analyses revealed that SLC2A2 was an important candidate gene for FE in pigs, which may give us a deeper understanding of the mechanism of feed efficiency. Furthermore, some significant DEGs identified in the current study could be incorporated into artificial selection programs for increased feeding efficiency in pigs.

Genome-wide association scan for QTL and their positional candidate genes associated with internal organ traits in chickens

BACKGROUND

Poultry breeding programs have been focused on improvement of growth and carcass traits, however, this has resulted in correlated changes in internal organ weights and increased incidence of metabolic disorders. These disorders can affect feed efficiency or even cause death. We used a high density SNP array (600 K, Affymetrix) to estimate genomic heritability, perform genome-wide association analysis, and identify genomic regions and positional candidate genes (PCGs) associated with internal organ traits in an F2 chicken population. We integrated knowledge of haplotype blocks, selection signature regions and sequencing data to refine the list of PCGs.

RESULTS

Estimated genomic heritability for internal organ traits in chickens ranged from low (LUNGWT, 0.06) to high (GIZZWT, 0.45). A total of 20 unique 1 Mb windows identified on GGA1, 2, 4, 7, 12, 15, 18, 19, 21, 27 and 28 were significantly associated with intestine length, and weights or percentages of liver, gizzard or lungs. Within these windows, 14 PCGs were identified based on their biological functions: TNFSF11, GTF2F2, SPERT, KCTD4, HTR2A, RB1, PCDH7, LCORL, LDB2, NR4A2, GPD2, PTPN11, ITGB4 and SLC6A4. From those genes, two were located within haplotype blocks and three overlapped with selection signature regions. A total of 13,748 annotated sequence SNPs were in the 14 PCGs, including 156 SNPs in coding regions (124 synonymous, 26 non-synonymous, and 6 splice variants). Seven deleterious SNPs were identified in TNFSF11, NR4A2 or ITGB4 genes.

CONCLUSIONS

The results from this study provide novel insights to understand the genetic architecture of internal organ traits in chickens. The QTL detection performed using a high density SNP array covered the whole genome allowing the discovery of novel QTL associated with organ traits. We identified PCGs within the QTL involved in biological processes that may regulate internal organ growth and development. Potential functional genetic variations were identified generating crucial information that, after validation, might be used in poultry breeding programs to reduce the occurrence of metabolic disorders.

Responsiveness of swine divergently selected for feed efficiency to exogenous adrenocorticotropic hormone and glucose challenges

Increasing the feed efficiency of lean tissue gains is an important goal for improving sustainable pork production and profitability for swine producers. To study feed efficiency, genetic selection based on residual feed intake (RFI) was used to create two divergent lines. Low-RFI pigs consume less feed for equal weight gain compared with their less-efficient, high-RFI counterparts. As cortisol and insulin are important energy control and growth regulators, our objective was to evaluate the role of the adrenocorticotropic hormone (ACTH)-cortisol and the glucose-insulin axes in pigs divergently selected for RFI. Adrenocorticotropic hormone (0.2 IU/kg BW)-stimulated cortisol and non-esterified fatty acids (NEFA) concentrations and intravenous glucose tolerance test (IVGTT; 0.25 g/kg BW)-stimulated glucose, insulin, and NEFA concentrations were assessed in six low-RFI and six high-RFI gilts (68 ± 5.2 kg). Before the ACTH challenge, low-RFI gilts tended to have less baseline plasma cortisol (P = 0.08) but no difference in NEFA concentrations (P = 0.63) compared with high-RFI gilts. After the ACTH challenge, low-RFI gilts had less cortisol (P = 0.04) and NEFA concentrations (P = 0.05) compared with high-RFI gilts. Glucose, insulin, and NEFA concentrations did not differ between genetic lines before the IVGTT. After glucose infusion, low-RFI gilts had greater insulin concentrations (P = 0.003) but did not differ in glucose or NEFA concentrations compared with high-RFI gilts. These results indicate that genetic selection for reduced RFI (improved feed efficiency) resulted in less stress responsiveness and an increase in insulin after glucose infusion. These data have implications for identifying and selecting more feed efficient pigs and for understanding the physiological mechanisms underlying feed efficiency.

A comparative analysis of the transcriptome profiles of liver and muscle tissue in pigs divergent for feed efficiency

BACKGROUND

The improvement of feed efficiency is a key economic goal within the pig production industry. The objective of this study was to examine transcriptomic differences in both the liver and muscle of pigs divergent for feed efficiency, thus improving our understanding of the molecular mechanisms influencing feed efficiency and enabling the identification of candidate biomarkers. Residual feed intake (RFI) was calculated for two populations of pigs from two different farms of origin/genotype. The 6 most efficient (LRFI) and 6 least efficient (HRFI) animals from each population were selected for further analysis of Longissimus Dorsi muscle (n = 22) and liver (n = 23). Transcriptomic data were generated from liver and muscle collected post-slaughter.

RESULTS

The transcriptomic data segregated based on the RFI value of the pig rather than genotype/farm of origin. A total of 6463 genes were identified as being differentially expressed (DE) in muscle, while 964 genes were identified as being DE in liver. Genes that were commonly DE between muscle and liver (n = 526) were used for the multi-tissue analysis. These 526 genes were associated with protein targeting to membrane, extracellular matrix organisation and immune function. In the muscle-only analysis, genes associated with RNA processing, protein synthesis and energy metabolism were down regulated in the LRFI animals while in the liver-only analysis, genes associated with cell signalling and lipid homeostasis were up regulated in the LRFI animals.

CONCLUSIONS

Differences in the transcriptome segregated on pig RFI value rather than the genotype/farm of origin. Multi-tissue analysis identified that genes associated with GO terms protein targeting to membrane, extracellular matrix organisation and a range of terms relating to immune function were over represented in the differentially expressed genes of both liver and muscle.

Genome-Wide Association Study Reveals Candidate Genes for Growth Relevant Traits in Pigs

Improvement of the growth rate is a challenge in the pig industry, the Average Daily Gain (ADG) and Days (AGE) to 100 kg are directly related to growth performance. We performed genome-wide association study (GWAS) and genetic parameters estimation for ADG and AGE using the genomic and phonemic from four breed (Duroc, Yorkshire, Landrace, and Pietrain) populations. All analyses were performed by a multi-loci GWAS model, FarmCPU. The GWAS results of all four breeds indicate that five genome-wide significant SNPs were associated with ADG, and the nearby genomic regions explained 4.08% of the genetic variance and 1.90% of the phenotypic variance, respectively. For AGE, six genome-wide significant SNPs were detected, and the nearby genomic regions explained 8.09% of the genetic variance and 3.52% of phenotypic variance, respectively. In total, nine candidate genes were identified to be associated with growth and metabolism. Among them, TRIB3 was reported to associate with pig growth, GRP, TTR, CNR1, GLP1R, BRD2, HCRTR2, SEC11C, and ssc-mir-122 were reported to associate with growth traits in human and mouse. The newly detected candidate genes will advance the understanding of growth related traits and the identification of the novel variants will suggest a potential use in pig genomic breeding programs.

Associations of sex hormone-binding globulin and testosterone with genome-wide DNA methylation

Background

Levels of sex hormone-binding globulin (SHBG) and the androgen testosterone have been associated with risk of diseases throughout the lifecourse. Although both SHBG and testosterone have been shown to be highly heritable, only a fraction of that heritability has been explained by genetic studies. Epigenetic modifications such as DNA methylation may explain some of the missing heritability and could potentially inform biological knowledge of endocrine disease mechanisms involved in development of later life disease. Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC), we explored cross-sectional associations of SHBG, total testosterone and bioavailable testosterone in childhood (males only) and adolescence (both males and females) with genome-wide DNA methylation. We also report associations of a SHBG polymorphism (rs12150660) with DNA methylation, which leads to differential levels of SHBG in carriers, as a genetic proxy of circulating SHBG levels.

Results

We identified several novel sites and genomic regions where levels of SHBG, total testosterone, and bioavailable testosterone were associated with DNA methylation, including one region associated with total testosterone in males (annotated to the KLHL31 gene) in both childhood and adolescence and a second region associated with bioavailable testosterone (annotated to the CMYA5 gene) at both time-points. We also identified one region where both SHBG and bioavailable testosterone in males in childhood (annotated to the ZNF718 gene) was associated with DNA methylation.

Conclusion

Our findings have important implications in the understanding of the biological processes of SHBG and testosterone, with the potential for future work to determine the molecular mechanisms that could underpin these associations.

Electronic supplementary material

The online version of this article (10.1186/s12863-018-0703-y) contains supplementary material, which is available to authorized users.

Integration of genome wide association studies and whole genome sequencing provides novel insights into fat deposition in chicken

Excessive fat deposition is a negative factor for poultry production because it reduces feed efficiency, increases the cost of meat production and is a health concern for consumers. We genotyped 497 birds from a Brazilian F₂ Chicken Resource Population, using a high-density SNP array (600 K), to estimate the genomic heritability of fat deposition related traits and to identify genomic regions and positional candidate genes (PCGs) associated with these traits. Selection signature regions, haplotype blocks and SNP data from a previous whole genome sequencing study in the founders of this chicken F2 population were used to refine the list of PCGs and to identify potential causative SNPs. We obtained high genomic heritabilities (0.43-0.56) and identified 22 unique QTLs for abdominal fat and carcass fat content traits. These QTLs harbored 26 PCGs involved in biological processes such as fat cell differentiation, insulin and triglyceride levels, and lipid biosynthetic process. Three of these 26 PCGs were located within haplotype blocks there were associated with fat traits, five overlapped with selection signature regions, and 12 contained predicted deleterious variants. The identified QTLs, PCGs and potentially causative SNPs provide new insights into the genetic control of fat deposition and can lead to improved accuracy of selection to reduce excessive fat deposition in chickens.

Genome wide association study on feed conversion ratio using imputed sequence data in chickens

Objective

Feed consumption contributes a large percentage for total production costs in the poultry industry. Detecting genes associated with feeding traits will be of benefit to improve our understanding of the molecular determinants for feed efficiency. The objective of this study was to identify candidate genes associated with feed conversion ratio (FCR) via genome-wide association study (GWAS) using sequence data imputed from single nucleotide polymorphism (SNP) panel in a Chinese indigenous chicken population.

Methods

A total of 435 Chinese indigenous chickens were phenotyped for FCR and were genotyped using a 600K SNP genotyping array. Twenty-four birds were selected for sequencing, and the 600K SNP panel data were imputed to whole sequence data with the 24 birds as the reference. The GWAS were performed with GEMMA software.

Results

After quality control, 8,626,020 SNPs were used for sequence based GWAS, in which ten significant genomic regions were detected to be associated with FCR. Ten candidate genes, ubiquitin specific peptidase 44, leukotriene A4 hydrolase, ETS transcription factor, R-spondin 2, inhibitor of apoptosis protein 3, sosondowah ankyrin repeat domain family member D, calmodulin regulated spectrin associated protein family member 2, zinc finger and BTB domain containing 41, potassium sodium-activated channel subfamily T member 2, and member of RAS oncogene family were annotated. Several of them were within or near the reported FCR quantitative trait loci, and others were newly reported.

Conclusion

Results from this study provide valuable prior information on chicken genomic breeding programs, and potentially improve our understanding of the molecular mechanism for feeding traits.

Effects of alleles in crossbred pigs estimated for genomic prediction depend on their breed-of-origin

BACKGROUND

This study investigated if the allele effect of a given single nucleotide polymorphism (SNP) for crossbred performance in pigs estimated in a genomic prediction model differs depending on its breed-of-origin, and how these are related to estimated effects for purebred performance.

RESULTS

SNP-allele substitution effects were estimated for a commonly used SNP panel using a genomic best linear unbiased prediction model with breed-specific partial relationship matrices. Estimated breeding values for purebred and crossbred performance were converted to SNP-allele effects by breed-of-origin. Differences between purebred and crossbred, and between breeds-of-origin were evaluated by comparing percentage of variance explained by genomic regions for back fat thickness (BF), average daily gain (ADG), and residual feed intake (RFI). From ten regions explaining most additive genetic variance for crossbred performance, 1 to 5 regions also appeared in the top ten for purebred performance. The proportion of genetic variance explained by a genomic region and the estimated effect of a haplotype in such a region were different depending upon the breed-of-origin. To illustrate underlying mechanisms, we evaluated the estimated effects across breeds-of-origin for haplotypes associated to the melanocortin 4 receptor (MC4R) gene, and for the MC4Rsnp itself which is a missense mutation with a known effect on BF and ADG. Although estimated allele substitution effects of the MC4Rsnp mutation were very similar across breeds, explained genetic variance of haplotypes associated to the MC4R gene using a SNP panel that does not include the mutation, was considerably lower in one of the breeds where the allele frequency of the mutation was the lowest.

CONCLUSIONS

Similar regions explaining similar additive genetic variance were observed across purebred and crossbred performance. Moreover, there was some overlap across breeds-of-origin between regions that explained relatively large proportions of genetic variance for crossbred performance; albeit that the actual proportion of variance deviated across breeds-of-origin. Results based on a missense mutation in MC4R confirmed that even if a causal locus has similar effects across breeds-of-origin, estimated effects and explained variance in its region using a commonly used SNP panel can strongly depend on the allele frequency of the underlying causal mutation.

A genome scan for selection signatures in Taihu pig breeds using next-generation sequencing

Taihu pig breeds are the most prolific breeds of swine in the world, and they also have superior economic traits, including high resistance to disease, superior meat quality, high resistance to crude feed and a docile temperament. The formation of these phenotypic characteristics is largely a result of long-term artificial or natural selection. Therefore, exploring selection signatures in the genomes of the Taihu pigs will help us to identify porcine genes related to productivity traits, disease and behaviour. In this study, we used both intra-population (Relative Extend Haplotype Homozygosity Test (REHH)) and inter-population (the Cross-Population Extend Haplotype Homozygosity Test (XPEHH); F-STATISTICS, F ST ) methods to detect genomic regions that might be under selection process in Taihu pig breeds. As a result, we found 282 (REHH) and 112 (XPEHH) selection signature candidate regions corresponding to 159.78 Mb (6.15%) and 62.29 Mb (2.40%) genomic regions, respectively. Further investigations of the selection candidate regions revealed that many genes under these genomic regions were related to reproductive traits (such as the TLR9 gene), coat colour (such as the KIT gene) and fat metabolism (such as the CPT1A and MAML3 genes). Furthermore, gene enrichment analyses showed that genes under the selection candidate regions were significantly over-represented in pathways related to diseases, such as autoimmune thyroid and asthma diseases. In conclusion, several candidate genes potentially under positive selection were involved in characteristics of Taihu pig. These results will further allow us to better understand the mechanisms of selection in pig breeding.

A genome-wide association study reveals novel genomic regions and positional candidate genes for fat deposition in broiler chickens

Background

Excess fat content in chickens has a negative impact on poultry production. The discovery of QTL associated with fat deposition in the carcass allows the identification of positional candidate genes (PCGs) that might regulate fat deposition and be useful for selection against excess fat content in chicken’s carcass. This study aimed to estimate genomic heritability coefficients and to identify QTLs and PCGs for abdominal fat (ABF) and skin (SKIN) traits in a broiler chicken population, originated from the White Plymouth Rock and White Cornish breeds.

Results

ABF and SKIN are moderately heritable traits in our broiler population with estimates ranging from 0.23 to 0.33. Using a high density SNP panel (355,027 informative SNPs), we detected nine unique QTLs that were associated with these fat traits. Among these, four QTL were novel, while five have been previously reported in the literature. Thirteen PCGs were identified that might regulate fat deposition in these QTL regions: JDP2, PLCG1, HNF4A, FITM2, ADIPOR1, PTPN11, MVK, APOA1, APOA4, APOA5, ENSGALG00000000477, ENSGALG00000000483, and ENSGALG00000005043. We used sequence information from founder animals to detect 4843 SNPs in the 13 PCGs. Among those, two were classified as potentially deleterious and two as high impact SNPs.

Conclusions

This study generated novel results that can contribute to a better understanding of fat deposition in chickens. The use of high density array of SNPs increases genome coverage and improves QTL resolution than would have been achieved with low density. The identified PCGs were involved in many biological processes that regulate lipid storage. The SNPs identified in the PCGs, especially those predicted as potentially deleterious and high impact, may affect fat deposition. Validation should be undertaken before using these SNPs for selection against carcass fat accumulation and to improve feed efficiency in broiler chicken production.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4779-6) contains supplementary material, which is available to authorized users.

The effect of QTL-rich region polymorphisms identified by targeted DNA-seq on pig production traits

The aim of the present study was to analyse the effect of PLCD4, PECR, FN1 and PNKD mutations on pig productive traits and tested the usefulness of targeted enrichment DNA sequencing method as tool for preselection of genetic markers. The potential genetic markers for pig productive traits were identified by using targeted enrichment DNA sequencing of chromosome 15 region that is QTL-rich. The selected mutations were genotyped by using HRM, Sanger sequencing and PCR-ACRS methods. The association study was performed by using GLM model in SAS program and included over 500 pigs of 5 populations maintained in Poland. The variation (C/T) of PLCD4 gene affected feed conversion, intramuscular fat and water exudation. The PNKD mutations were associated with texture parameters measured after cooking. In turn, the variation rs792423408 (C/T) in the FN1 gene influenced toughness measured in semimembranosus muscle and growth traits that was observed particularly in Duroc breed. Summarizing, the investigated gene variants delivered valuable information that could be used during developing SNP microarray for genomic estimated breeding value procedure in pigs. Moreover, the study showed that the TEDNA-seq method could be used to preselect the molecular markers associated with pig traits. However, the further association study that included large number animal populations is necessary.

Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed

One of the major limitation for the application of QTL results in pig breeding and QTN identification has been the limited number of QTL effects validated in different animal material. The aim of the current work was to validate QTL regions through joint and specific genome wide association and haplotype analyses for growth, fatness and premier cut weights in three different genetic backgrounds, backcrosses based on Iberian pigs, which has a major role in the analysis due to its high productive relevance. The results revealed nine common QTL regions, three segregating in all three backcrosses on SSC1, 0–3 Mb, for body weight, on SSC2, 3–9 Mb, for loin bone-in weight, and on SSC7, 3 Mb, for shoulder weight, and six segregating in two of the three backcrosses, on SSC2, SSC4, SSC6 and SSC10 for backfat thickness, shoulder and ham weights. Besides, 18 QTL regions were specifically identified in one of the three backcrosses, five identified only in BC_LD, seven in BC_DU and six in BC_PI. Beyond identifying and validating QTL, candidate genes and gene variants within the most interesting regions have been explored using functional annotation, gene expression data and SNP identification from RNA-Seq data. The results allowed us to propose a promising list of candidate mutations, those identified in PDE10A, DHCR7, MFN2 and CCNY genes located within the common QTL regions and those identified near ssc-mir-103-1 considered PANK3 regulators to be further analysed.