Genome-wide DNA methylation analysis using next-generation sequencing to reveal candidate genes responsible for boar taint in pigs

Boar taint (BT) is an offensive flavor observed in non-castrated male pigs that reduces the carcass price. Surgical castration effectively avoids the taint but is associated with animal welfare concerns. The functional annotation of farm animal genomes for understanding the biology of complex traits can be used in the selection of breeding animals to achieve favorable phenotypic outcomes. The characterization of pig epigenomes/methylation changes between animals with high and low BT and genome-wide epigenetic markers that can predict BT are lacking. Reduced representation bisulfite sequencing of DNA methylation patterns based on next-generation sequencing is an efficient technology to identify candidate epigenetic biomarkers associated with BT. Three different BT levels were analyzed using reduced representation bisulfite sequencing data to calculate the methylation levels of cytosine and guanine dinucleotide (CpG) sites. The co-analysis of differentially methylated CpG sites identified by this study and differentially expressed genes identified by a previous study found 32 significant co-located genes. The joint analysis of GO terms and pathways revealed that methylation and gene expression of seven candidate genes were associated with BT; in particular, FASN plays a key role in fatty acid biosynthesis, and PEMT might be involved in estrogen regulation and the development of BT. This study is the first to report the genome-wide DNA methylation profiles of BT in pigs using next-generation sequencing and summarize candidate genes associated with epigenetic markers of BT, which could contribute to the understanding of the functional biology of BT traits and selective breeding of pigs against BT based on epigenetic biomarkers.

Transcriptomics-genomics data integration and expression quantitative trait loci analyses in oocyte donors and embryo recipients for improving invitro production of dairy cattle embryos

In this paper we first provide a brief review of main results from our previously published studies on genome-wide gene expression (transcriptomics) in donor and recipient cattle used in invitro production (IVP) of embryos and embryo transfer (ET). Then, we present novel results from applying integrative systems genomics and biological analyses where transcriptomics data are combined with genomic data in both donor and recipient cattle to map expression quantitative trait loci (eQTLs). The eQTLs are genetic markers that can regulate or control the expression of genes in the entire genome, via complex molecular mechanisms, and thus can act as a powerful tool for genomic and gene-assisted selection. We identified significant eQTLs potentially controlling the expression of 13 candidate genes for donor cow quality (IVP parameters; e.g. cyclin B1 (CCNB1), outer dense fiber of sperm tails 2 like (ODF2L)) and 19 candidate genes for recipient cows quality (endometrial receptivity; e.g. ER membrane protein complex subunit 9 (EMC9), mannosidase beta (MANBA), peptidase inhibitor 16 (PI16)). Annotation and colocation of detected eQTLs show that some of the eQTLs are in the same genomic regions previously reported as QTLs for reproduction-related traits. However, eQTLs and the candidate genes identified should be further validated in larger populations before implementation as genetic markers or used in genomic selection for improving IVP and ET performance.

Genomic study and Medical Subject Headings enrichment analysis of early pregnancy rate and antral follicle numbers in Nelore heifers

Zebu animals () are known to take longer to reach puberty compared with taurine animals (), limiting the supply of animals for harvest or breeding and impacting profitability. Genomic information can be a helpful tool to better understand complex traits and improve genetic gains. In this study, we performed a genomewide association study (GWAS) to identify genetic variants associated with reproductive traits in Nelore beef cattle. Heifer pregnancy (HP) was recorded for 1,267 genotyped animals distributed in 12 contemporary groups (CG) with an average pregnancy rate of 0.35 (±0.01). Disregarding one of these CG, the number of antral follicles (NF) was also collected for 937 of these animals, with an average of 11.53 (±4.43). The animals were organized in CG: 12 and 11 for HP and NF, respectively. Genes in linkage disequilibrium (LD) with the associated variants can be considered in a functional enrichment analysis to identify biological mechanisms involved in fertility. Medical Subject Headings (MeSH) were detected using the MESHR package, allowing the extraction of broad meanings from the gene lists provided by the GWAS. The estimated heritability for HP was 0.28 ± 0.07 and for NF was 0.49 ± 0.09, with the genomic correlation being -0.21 ± 0.29. The average LD between adjacent markers was 0.23 ± 0.01, and GWAS identified genomic windows that accounted for >1% of total genetic variance on chromosomes 5, 14, and 18 for HP and on chromosomes 2, 8, 11, 14, 15, 16, and 22 for NF. The MeSH enrichment analyses revealed significant ( < 0.05) terms associated with HP-"Munc18 Proteins," "Fucose," and "Hemoglobins"-and with NF-"Cathepsin B," "Receptors, Neuropeptide," and "Palmitic Acid." This is the first study in Nelore cattle introducing the concept of MeSH analysis. The genomic analyses contributed to a better understanding of the genetic control of the reproductive traits HP and NF and provide new selection strategies to improve beef production.

RNA-Seq transcriptomics and pathway analyses reveal potential regulatory genes and molecular mechanisms in high- and low-residual feed intake in Nordic dairy cattle

Background

The selective breeding of cattle with high-feed efficiencies (FE) is an important goal of beef and dairy cattle producers. Global gene expression patterns in relevant tissues can be used to study the functions of genes that are potentially involved in regulating FE. In the present study, high-throughput RNA sequencing data of liver biopsies from 19 dairy cows were used to identify differentially expressed genes (DEGs) between high- and low-FE groups of cows (based on Residual Feed Intake or RFI). Subsequently, a profile of the pathways connecting the DEGs to FE was generated, and a list of candidate genes and biomarkers was derived for their potential inclusion in breeding programmes to improve FE.

Results

The bovine RNA-Seq gene expression data from the liver was analysed to identify DEGs and, subsequently, identify the molecular mechanisms, pathways and possible candidate biomarkers of feed efficiency. On average, 57 million reads (short reads or short mRNA sequences < ~200 bases) were sequenced, 52 million reads were mapped, and 24,616 known transcripts were quantified according to the bovine reference genome. A comparison of the high- and low-RFI groups revealed 70 and 19 significantly DEGs in Holstein and Jersey cows, respectively. The interaction analysis (high vs. low RFI x control vs. high concentrate diet) showed no interaction effects in the Holstein cows, while two genes showed interaction effects in the Jersey cows. The analyses showed that DEGs act through certain pathways to affect or regulate FE, including steroid hormone biosynthesis, retinol metabolism, starch and sucrose metabolism, ether lipid metabolism, arachidonic acid metabolism and drug metabolism cytochrome P450.

Conclusion

We used RNA-Seq-based liver transcriptomic profiling of high- and low-RFI dairy cows in two breeds and identified significantly DEGs, their molecular mechanisms, their interactions with other genes and functional enrichments of different molecular pathways. The DEGs that were identified were the CYP’s and GIMAP genes for the Holstein and Jersey cows, respectively, which are related to the primary immunodeficiency pathway and play a major role in feed utilization and the metabolism of lipids, sugars and proteins.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3622-9) contains supplementary material, which is available to authorized users.

Systems genetics analysis of pharmacogenomics variation during antidepressant treatment

Selective serotonin reuptake inhibitors (SSRIs) are the most widely used antidepressants, but the efficacy of the treatment varies significantly among individuals. It is believed that complex genetic mechanisms play a part in this variation. We have used a network based approach to unravel the involved genetic components. Moreover, we investigated the potential difference in the genetic interaction networks underlying SSRI treatment response over time. We found four hub genes (ASCC3, PPARGC1B, SCHIP1 and TMTC2) with different connectivity in the initial SSRI treatment period (baseline to week 4) compared with the subsequent period (4-8 weeks after initiation), suggesting that different genetic networks are important at different times during SSRI treatment. The strongest interactions in the initial SSRI treatment period involved genes encoding transcriptional factors, and in the subsequent period genes involved in calcium homeostasis. In conclusion, we suggest a difference in genetic interaction networks between initial and subsequent SSRI response.

Systems genetics and genome-wide association approaches for analysis of feed intake, feed efficiency, and performance in beef cattle

Feed intake, feed efficiency, and weight gain are important economic traits of beef cattle in feedlots. In the present study, we investigated the physiological processes underlying such traits from the point of view of systems genetics. Firstly, using data from 1334 Nellore (Bos indicus) cattle and 943,577 single nucleotide polymorphisms (SNPs), a genome-wide association analysis was performed for dry matter intake, average daily weight gain, feed conversion ratio, and residual feed intake with a Bayesian Lasso procedure. Genes within 50-kb SNPs, most relevant for explaining the genomic variance, were annotated and the biological processes underlying the traits were inferred from Database for Annotation, Visualization and Integrated Discovery (DAVID) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Our results indicated several putative genomic regions associated with the target phenotypes and showed that almost all genomic variances were in the SNPs located in the intergenic and intronic regions. We further identified five main metabolic pathways related to ion transport, body composition, and feed intake control, which influenced the four phenotypes simultaneously. The systems genetics approach used in this study revealed novel pathways related to feed efficiency traits in beef cattle.

SNP annotation-based whole genomic prediction and selection: an application to feed efficiency and its component traits in pigs

The study investigated genetic architecture and predictive ability using genomic annotation of residual feed intake (RFI) and its component traits (daily feed intake [DFI], ADG, and back fat [BF]). A total of 1,272 Duroc pigs had both genotypic and phenotypic records, and the records were split into a training (968 pigs) and a validation dataset (304 pigs) by assigning records as before and after January 1, 2012, respectively. SNP were annotated by 14 different classes using Ensembl variant effect prediction. Predictive accuracy and prediction bias were calculated using Bayesian Power LASSO, Bayesian A, B, and Cπ, and genomic BLUP (GBLUP) methods. Predictive accuracy ranged from 0.508 to 0.531, 0.506 to 0.532, 0.276 to 0.357, and 0.308 to 0.362 for DFI, RFI, ADG, and BF, respectively. BayesCπ100.1 increased accuracy slightly compared to the GBLUP model and other methods. The contribution per SNP to total genomic variance was similar among annotated classes across different traits. Predictive performance of SNP classes did not significantly differ from randomized SNP groups. Genomic prediction has accuracy comparable to observed phenotype, and use of genomic prediction can be cost effective by replacing feed intake measurement. Genomic annotation had less impact on predictive accuracy traits considered here but may be different for other traits. It is the first study to provide useful insights into biological classes of SNP driving the whole genomic prediction for complex traits in pigs.

Late gestation under- and overnutrition have differential impacts when combined with a post-natal obesogenic diet on glucose-lactate-insulin adaptations during metabolic challenges in adolescent sheep

AIM

To determine whether late gestation under- and overnutrition programme metabolic plasticity in a similar way, and whether metabolic responses to an obesogenic diet in early post-natal life depend on the foetal nutrition history.

METHODS

In a 3 × 2 factorial design, twin-pregnant ewes were for the last 6 weeks of gestation (term = 147 days) assigned to HIGH (N = 13; 150 and 110% of energy and protein requirements, respectively), NORM (N = 9; 100% of requirements) or LOW (N = 14; 50% of requirements) diets. The twin offspring were raised on high-carbohydrate-high-fat (HCHF; N = 35) or conventional (CONV; N = 35) diets from 3 days to 6 months of age (around puberty). Then intravenous glucose (GTT; overnight fasted), insulin (ITT; fed) and propionate (gluconeogenetic precursor; PTT; both fed and fasted) tolerance tests were conducted to evaluate (hepatic) metabolic plasticity.

RESULTS

Prenatal malnutrition differentially impacted adaptations of particularly plasma lactate followed by glucose, cholesterol and insulin. This was most clearly expressed during PTT in fasted lambs and much less during ITT and GTT. In fasted lambs, propionate induced more dramatic increases in lactate than glucose, and HIGH lambs became more hyperglycaemic, hyperlactataemic and secreted less insulin compared to the hypercholesterolaemic LOW lambs. Propionate-induced insulin secretion was virtually abolished in fasted HCHF lambs, but upregulated in fasted compared to fed CONV lambs. HCHF lambs had the greatest glucose-induced insulin secretory responses.

CONCLUSION

Prenatal malnutrition differentially programmed glucose-lactate metabolic pathways and cholesterol homeostasis. Prenatal overnutrition predisposed for hyperglycaemia and hyperlactataemia, whereas undernutrition predisposed for hypercholesterolaemia upon exposure to an obesogenic diet. Prenatal overnutrition (not undernutrition) interfered with pancreatic insulin secretion by non-glucose-dependent mechanisms.

Expression studies of six human obesity-related genes in seven tissues from divergent pig breeds

Obesity has reached epidemic proportions globally and has become the cause of several major health risks worldwide. Presently, more than 100 loci have been related to obesity and metabolic traits in humans by genome-wide association studies. The complex genetic architecture behind obesity has triggered a need for the development of better animal models than rodents. The pig has emerged as a very promising biomedical model to study human obesity traits. In this study, we have characterized the expression patterns of six obesity-related genes, leptin (LEP), leptin receptor (LEPR), melanocortin 4 receptor (MC4R), fat mass and obesity associated (FTO), neuronal growth regulator 1 (NEGR)1 and adiponectin (ADIPOQ), in seven obesity-relevant tissues (liver; muscle; pancreas; hypothalamus; and retroperitoneal, subcutaneous and mesenteric adipose tissues) in two pig breeds (production pigs and Göttingen minipigs) that deviate phenotypically and genetically from each other with respect to obesity traits. We observe significant differential expression for LEP, LEPR and ADIPOQ in muscle and in all three adipose tissues. Interestingly, in pancreas, LEP expression is only detected in the fat minipigs. FTO shows significant differential expression in all tissues analyzed, and NEGR1 shows significant differential expression in muscle, pancreas, hypothalamus and subcutaneous adipose tissue. The MC4R transcript can be detected only in hypothalamus. In general, the expression profiles of the investigated genes are in accordance with those observed in human studies. Our study shows that both the differences between the investigated breeds and the phenotypic state with respect to obesity/leanness play a large role for differential expression of the obesity-related genes.

Genetic parameters for male fertility and its relationship to skatole and androstenone in Danish Landrace boars

Concerns have been raised regarding selection against the boar taint compounds, androstenone and skatole, due to potential unfavorable genetic correlations with important male fertility traits (i.e., selection of boars with low levels of these boar taint compounds might also reduce male fertility). Hence, the objective of this investigation was to study the genetic association between direct measures of male fertility and the boar taint compounds in Danish Landrace pigs. Concentrations of skatole and androstenone in the back fat were available for approximately 6,000 and 1,000 Landrace boars, respectively. The litter size traits, such as total number born, live piglets at d 5, and piglet survival until d 5 on relatives of the slaughter boars, were extracted from the Danish Landrace breeding program, yielding 35,715 records. Semen volume, sperm concentration, subjective sperm quality score, and total number of sperm were available from 95,267 ejaculates. These ejaculates were collected between 2005 and 2012 and originated from 3,145 Landrace boars from 12 AI stations in Denmark. The traits were analyzed using single and multitrait animal models including univariate random regression models. Skatole and androstenone concentrations were moderate to highly heritable (i.e., 0.33 and 0.59, respectively). The genetic correlation between the two compounds was moderate (0.40). Genetic variance of sperm production per ejaculate increased during the productive life of the boar, resulting in heritability estimates increasing from 0.18 to 0.31. Genetic correlations between sperm production per ejaculate at different ages were high and generally larger than 0.8, indicating that later genetic merit can be predicted from records at an early age. The heritability (based on service-sire genetic component) of both total number of piglets born and survival to d 5 were 0.02, and the correlation between these effects and the additive genetic effect on boar taint ranged from 0.05 to -0.40 (none of these correlations were significantly different from zero). Most importantly, the genetic correlations between skatole and androstenone and the different semen traits tended to be more favorable with increase in age of the boars. In conclusion, these data suggest that concentrations of skatole and androstenone can be reduced through genetic selection without negatively affecting important male fertility traits in Danish Landrace pigs.

Genetic parameters for different measures of feed efficiency and related traits in boars of three pig breeds

Residual feed intake (RFI) is commonly used as a measure of feed efficiency at a given level of production. A total of 16,872 pigs with their pedigree traced back as far as possible was used to estimate genetic parameters for RFI, growth performance, food conversion ratio (FCR), body conformation, and feeding behavior traits in 3 Danish breeds [Duroc (DD), Landrace (LL), and Yorkshire (YY)]. Two measures of RFI were considered: residual feed intake 1 (RFI1) was calculated based on regression of daily feed intake (DFI) from 30 to 100 kg on initial test weight and ADG from 30 to 100 kg (ADG2). Residual feed intake 2 (RFI2) was as RFI1, except it was also regressed with respect to backfat (BF). The estimated heritabilities for RFI1 and RFI2 were 0.34 and 0.38 in DD, 0.34 and 0.36 in LL, and 0.39 and 0.40 in YY, respectively. The heritabilities ranged from 0.32 (DD) to 0.54 (LL) for ADG2, from 0.54 (DD) to 0.67 (LL) for BF, and from 0.13 (DD) to 0.19 (YY) for body conformation. Feeding behavior traits including DFI, number of visits to feeder per day (NVD), total time spent eating per day (TPD), feed intake rate (FR), feed intake per visit (FPV), and time spent eating per visit (TPV) were moderately to highly heritable. Residual feed intake 2 was genetically independent of ADG2 and BF in all breeds, except it had low genetic correlation to ADG2 in YY (0.2). Residual feed intake 1 was also genetically independent of ADG2 in DD and LL. Both RFI traits had strong genetic correlations with DFI (0.85 to 0.96) and FCR (0.76 to 0.99). They had low or no genetic correlations with feeding behavior traits. Unfavorable genetic correlations were found between ADG2 and both BF and DFI. Among feeding behavior traits, DFI had low genetic correlations to other traits in all breeds. High and negative genetic correlations were also found between TPD with FR (-0.79 in YY to -0.88 in DD), NVD, and TPD (-0.91 in DD to -0.94 in YY) and between NVD and FPV (-0.83 in DD to -0.91 in YY) in all breeds. The genetic trend for feed efficiency was favorable in all breeds regardless of the definition of feed efficiency used. In summary, RFI1 and RFI2 were heritable and selection for reduced RFI2 can be performed without adversely affecting ADG and BF and could replace FCR in the selection index for the Danish pig breeds. Selection could also be based on RFI1 for breeds with fewer concerns about a negative effect of BF or for breeds that do not have BF records.

Genetic parameters for androstenone and skatole as indicators of boar taint and their relationship to production and litter size traits in Danish Landrace

Boar taint is an offensive odor that affects the smell and taste of cooked pork, resulting mainly from the accumulation of skatole and androstenone in the back fat of intact males. The aim of the study was to estimate genetic parameters for skatole and androstenone and their genetic relationship to production and litter size traits. Concentrations of skatole and androstenone in the back fat were available for approximately 6,000 and 1,000 Landrace boars, respectively. The concentrations were log-transformed to align phenotypic measures to a normal distribution. Heritability estimates for Log(skatole) and Log(androstenone) were 0.33 and 0.59, respectively. The genetic correlation between the 2 measures of boar taint was 0.37, suggesting that genetic selection against boar taint based on only 1 of the chemical compounds could be insufficient. The boar taint compounds had low and mostly favorable genetic correlations with the production traits. Most noticeable, a favorable genetic correlation of -0.20 between meat percentage and Log(skatole) was estimated and hence continued selection for lean pigs can also slowly reduce the level of boar taint if the desired carcass weight is kept constant. The relationship between litter size traits (measured on sows related to boars) and boar taint compounds was low and not significantly different from 0. In conclusion, skatole and androstenone can be reduced through selection without affecting important economical production and litter size traits. Therefore, animal breeding offers an effective and sustainable solution to surgical castration of male piglets.

Transient treatment of pregnant Merino ewes with modulators of cortisol biosynthesis coinciding with primary wool follicle initiation alters lifetime wool growth

The economically important characteristics of the adult fleece of Merino sheep, such as increases in clean fleece weight, fibre length, fibre diameter and crimp characteristics are determined during critical phases of fetal development of the skin and its appendages. Genetics plays a major role in the development of traits, but the maternal uterine environment could also influence development. Treatment of pregnant ewes with cortisol and its analogues has previously been shown to produce changes in wool follicle morphology. The aim of this study was to determine the effect of transient manipulation of maternal cortisol status during critical phases of wool follicle initiation and development in utero. From Days 55–65 post-conception, singleton-bearing Merino ewes were treated with metyrapone (cortisol inhibitor) or betamethasone (cortisol analogue). Lambs exposed to metyrapone in utero were born with hairier birthcoats than the control or betamethasone treatment groups (P < 0.05), displayed a 10% increase in staple length and a reduction in crimp frequency for the first three shearings (P < 0.05). Co-expression network analysis of microarray data revealed up-regulation of members of the transforming growth factor-β and chemokine receptor superfamilies, gene families known to influence hair and skin development. These experiments demonstrate that presumptive transient manipulation of maternal cortisol status coinciding with the initiation of fetal wool follicle development results in long-term alteration in fleece characteristics, namely fibre length and fibre crimp frequency. These results indicate it is possible to alter the lifetime wool production of Merino sheep with therapeutics targeted to gene expression during key windows of development in utero.

Polymorphisms of the SLC11A1 gene and resistance to bovine tuberculosis in African Zebu cattle

Bovine tuberculosis (BTB) is a considerable health threat to livestock keepers and general communities in many developing countries. Information on genetic resistance or susceptibility because of polymorphisms of candidate genes could be used in making selection decisions for breeding disease tolerant/resistant animals. Here, we investigated associations between polymorphisms at the solute carrier family 11 (proton-coupled divalent metal ion transporters), member 1 gene (SLC11A1, previously known as natural resistant associated macrophage protein 1, NRAMP1), with BTB phenotypes in Chadian cattle. Phenotypes were (i) single intradermal comparative cervical tuberculin test (SICCT) outcome, (ii) presence of gross visible lung lesions, (iii) a bacteriological culture test outcome and (iv) a predicted true BTB infection status using a Bayesian model. All traits were recorded as binary (presence or absence) traits. A total of 211 cattle were genotyped for a microsatellite within the SLC11A1 candidate gene. Standard linear and threshold-liability models regressing BTB traits on copy number of SLC11A1 alleles revealed statistically significant effects of SLC11A1 alleles (P < 0.001) on most BTB traits. Polymorphisms (alleles 211, 215 and 217) are significantly related to lower incidence of BTB traits in Chadian cattle. This is the first study to report the association of SLC11A1 gene polymorphisms with BTB traits in Chadian or any other African cattle breeds.

Genetical systems biology in livestock: application to gonadotrophin releasing hormone and reproduction

Genetical systems biology or systems genetics treats the genome as the central reference point for all omics variations and is an emerging new branch of systems biology. Quantitative genetic principles were developed for high-throughput genomic, transcriptomic and metabolomic data observed in large populations. New statistical genetic models were developed for expression quantitative trait loci (eQTL), namely, marker regression eQTL mapping and marker-expression co-factor mapping. Evaluations of power to detect eQTL showed that sample size requirements are higher for detecting trans-acting genes than cis-acting genes. Power is higher for eQTL with high heritability than for eQTL with low heritability. These results will be valuable for systems genetic investigations. Gonadotrophin releasing hormone (GnRH) and its receptor gene (GnRH-R) are crucial for mammalian reproduction. Whole genome scan of eQTLs for GnRH-R gene expression in mouse showed three possible trans-eQTL regions on chr 13 and 19, harbouring regulatory genes. Applications of genetical genomics in systems biology were identified as: (1) detection and validation of causal gene for complex traits; (2) development of genetic interaction networks; (3) prediction of transcription factor binding sites and (4) in data-driven systems biology. These applications were illustrated using data on eQTL, protein network and signalling pathways for GnRH. Gpr54 (G protein-coupled receptor kinase 54), Prl (prolactin), Ins1 (insulin) and Fos (viral oncogenes) were found to be major regulators of GnRH and GnRH-R; thus validating their important role in reproduction, mammary gland development and sexual (im)maturity. These results will be useful for further study of mammalian reproductive biology.

Genetic correlations between body condition scores and fertility in dairy cattle using bivariate random regression models

Genetic correlations between body condition score (BCS) and fertility traits in dairy cattle were estimated using bivariate random regression models. BCS was recorded by the Swiss Holstein Association on 22,075 lactating heifers (primiparous cows) from 856 sires. Fertility data during first lactation were extracted for 40,736 cows. The fertility traits were days to first service (DFS), days between first and last insemination (DFLI), calving interval (CI), number of services per conception (NSPC) and conception rate to first insemination (CRFI). A bivariate model was used to estimate genetic correlations between BCS as a longitudinal trait by random regression components, and daughter's fertility at the sire level as a single lactation measurement. Heritability of BCS was 0.17, and heritabilities for fertility traits were low (0.01-0.08). Genetic correlations between BCS and fertility over the lactation varied from: -0.45 to -0.14 for DFS; -0.75 to 0.03 for DFLI; from -0.59 to -0.02 for CI; from -0.47 to 0.33 for NSPC and from 0.08 to 0.82 for CRFI. These results show (genetic) interactions between fat reserves and reproduction along the lactation trajectory of modern dairy cows, which can be useful in genetic selection as well as in management. Maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in mid lactation when the genetic variance for BCS is largest, and the genetic correlations between BCS and fertility is strongest.

Genetic and phenotypic parameters for conformation and yield traits in three Swiss dairy cattle breeds

This study presents genetic parameters for conformation traits and their genetic and phenotypic correlations with milk production traits and somatic cell score (SCS) in three Swiss dairy cattle breeds. Data on first lactations from Holstein (67,839), Brown Swiss (173,372) and Red & White breeds (53,784) were available. Analysed conformation traits were stature and heart girth (both in cm), and linear scores of body depth, rump width, dairy character or muscularity, and body condition score (only in Holstein). A sire model, with relationships among sires, was used for all breeds and traits and variance components were estimated using AS-REML. Heritabilities for stature were high (0.6-0.8), and for the linear type traits ranged from 0.3 to 0.5, for all breeds. Genetic correlations with production traits (milk, fat and protein yield) and SCS differed between the dairy breeds. Most markedly, stronger correlations were found between SCS and some conformation traits in Brown Swiss and Red & White, indicating that a focus on a larger and more 'dairy' type in these breeds would lead to increased SCS. Another marked difference was that rump width correlated positively with milk yield traits in Holstein and Red & White, but negative in Brown Swiss. Results indicate that conformation traits generally can be used as predictors for various purposes in dairy cattle breeding, but may require specific adaptation for each breed.

Combined genetic, genomic and transcriptomic methods in the analysis of animal traits

Abstract

This paper reviews advances and current status in genetic, genomic and transcriptomic investigations of quantitative traits in livestock species and proposes possible strategies for integrating the vast amounts of information (outputs/datasets) arising from all three investigations into a systems genetics approach. This systems genetics approach is characterized by investigations of the genetic basis of -omic variations and gene regulatory/co-regulatory networks. This review is structured as follows. Genetics/genomics, transcriptomics, combined transcriptomics-genomics and, finally, systems genetics/biology. In the genetics or genomics part, we discuss current status and advances in quantitative trait loci (QTLs) mapping to fine-map multiple causative/candidate genes. We discuss the potential of single nucleotide polymorphism (SNP) genotyping arrays (e.g. Affymetrix GeneChip arrays) to identify SNP-trait associations and fine-map QTLs to less than 0.1 cM. We provide references and resources for SNP analytical methods and tools. In the transcriptomics part, we formulate common biological questions relevant to livestock microarray gene expression profiling (MGEP) experiments to detect differentially expressed (DE) genes. In the combined transcriptomics-genomics (known as genetical genomics), we discuss detection and mapping of expression QTL (eQTL) that harbour regulatory genes for normal trait QTLs or candidate genes detected under 'genetics' and 'genomics' approaches. Illustrations from our own recent genetical genomic investigations in mouse and pigs are provided. One of the current challenges in genetical genomics is to have a coherent approach to design an experiment with due considerations for sample size and controlling false discovery rates (FDRs), while maintaining statistical power to detect eQTLs. Here we provide some concepts for the design of genetical genomics experiments with factors affecting FDR and power. This is followed by a systems biology/genetics section where we focus on combining research outputs from four different sources, namely: genetics or genomics (e.g. SNP, QTL and eQTLs), transcriptomics (e.g. DE genes, gene networks, and heritability of gene transcripts) and phenomics (e.g. phenotypes and pedigree). As a proof of principle, we provide results from systems biology/genetics approach anchored to a gene network for myogenin (MYOG), a muscle-specific transcription factor essential for the development of skeletal muscle. Using bovine expression datasets and in silico approaches, we built a gene network for MYOG that represents 35 significant connections between genes in this network. In conclusion, this paper provides strategies and tools to integrate data from genetics and -omics experiments in animals and highlighted the value of such 'systems genetics' strategy in understanding the genetics of complex traits.

Genetics of osteochondral disease and its relationship with meat quality and quantity, growth, and feed conversion traits in pigs

The main objective of this research was to estimate heritabilities of seven osteochondrosis (OC) lesions in station-tested pigs and their genetic and phenotypic correlations with four meat quality (MQ) traits, the percentage of premium cuts (PPC), daily weight gain (DWG), and feed conversion ratio (FCR). Observed OC lesions were on the head of humerus (HK), condylus medialis humeri (CMH), condylus lateralis humeri (CLH), radius and ulna proximal (RUP), distal epiphyseal cartilage of ulna (DEU), head of femur (FK), and condylus medialis femoris (CMF). Meat quality traits were i.m. fat (IMF), muscle pH at 1 h after slaughter (pH1), muscle pH at 30 h after slaughter (pH30), and light reflectance on muscle (H30). The data set comprised 2,710 animals, of which 1,291 animals had OC records. All traits were analyzed by multiple-trait linear mixed model, with the animal's genetic and common litter effects as random. Fixed effects in the model varied between traits. Each OC lesion was further analyzed by a univariate generalized linear mixed model or, equivalently, "threshold models," assuming logistic, probit (normal), and Poisson distributions of the underlying "liability" to the disease. For OC lesions, estimates of heritability were low on the original "incidence" scale (0.06 for HK to 0.16 for CLH) and moderate to high on the liability scale (0.08 to 0.42). Genetic correlations (r(g)) between OC lesions and most MQ traits and PPC were generally unfavorable. Significant r(g) were -0.44 for DWG-CMH, 0.31 for DWG-CMF, 0.40 for FCR-HK, 0.21 for PPC-CLH, 0.32 for PPC-RUP, 0.30 for PPC-CMF, -0.54 for pH1-CLH, 0.47 for pH1-DEU, -0.34 for pH30-CMH, 0.58 for pH30-DEU, -0.50 for H30-HK, -0.31 for H30-DEU, and 0.31 for H30-CMF. Genetic susceptibilities to some OC lesions within the front leg were positively related to each other (r(g) range = 0.57 to 0.69), but r(g) between front and hind leg OC lesions were mostly negative (range = -0.21 to -0.40). Estimated h2 was 0.60 for PPC, and ranged from 0.12 to 0.66 for MQ traits, 0.28 for DWG, and 0.42 for FCR. Genetic correlations among meat quality and quantity traits ranged from -0.66 to 0.37. This is the first study to report genetic and phenotypic correlations between OC lesions and several meat quality and quantity traits in pigs. These findings will be useful to pig industry, especially in designing breeding programs for robust pigs.

Genetic parameters for functional traits in dairy cattle from daily random regression models

The objective of the research was to estimate genetic parameters, such as heritabilities and genetic correlations, using daily test day data for milk yield (MY), milking speed (MS), dry matter intake (DMI), and body weight (BW) using random regression methodology. Data were from first lactation dairy cows (n = 320) from the Chamau research farm of the Swiss Federal Institute of Technology, Switzerland over the period from April 1994 to 2004. All traits were recorded daily using automated machines. Estimated heritabilities (h(2)) varied from 0.18 to 0.30 (mean h(2) = 0.24) for MY, 0.003 to 0.098 (mean h(2) = 0.03) for MS, 0.22 to 0.53 (mean h(2) = 0.43) for BW, and 0.12 to 0.34 (mean h(2) = 0.23) for DMI. A permanent environmental effect was included in both the univariate and bivariate models, but was assumed constant in estimating some genetic correlations because of convergence problems. Estimated genetic correlations varied from 0.31 to 0.41 between MY and MS, from -0.47 to 0.29 between MY and DMI, from -0.60 to 0.54 between MY and BW, from 0.17 to 0.26 between MS and DMI, from -0.18 to 0.25 between MS and BW, and from -0.89 to 0.29 between DMI and BW. Genetic correlations for MY, MS, DMI, and BW from calving to midlactation decreased similarly to 0.40, 0.36, 0.14, and 0.36 and, at the end of the lactation, decreased to -0.06, 0.23, -0.07, and 0.09, respectively. Daily genetic variance-covariance of many functional traits are reported for the first time and will be useful when constructing selection indexes for more than one trait based on longitudinal genetic parameters.

Genetics of parity-dependant production increase and its relationship with health, fertility, longevity, and conformation in swiss holsteins

Genetic analysis of production increase (ProdI), defined as an increase in production from early to later lactations, was conducted using data from the Holstein Association of Switzerland. This production increase describes the maturity rate of the cow. The data set contained 42,807 cows with a ProdI value. All cows had completed the first 3 lactations. Different formulas were derived for the computation of ProdI using 1) milk yields or energy-corrected milk yields and 2) yields from all 3 lactations or only 2 of them (first and second, first and third, second and third). Heritabilities of ProdI and genetic and phenotypic correlations of ProdI with somatic cell score, days to first service, nonreturn rate, longevity, and 27 conformation traits were estimated by univariate and bivariate sire models that included relationship among sires. Heritabilities for ProdI were low (0.06 to 0.08), but genetic variation among sires existed. For nonreturn rate and longevity, regressions on the sire estimated breeding values were estimated. Additive genetic correlations of ProdI were moderately favorable with somatic cell score (-0.22 to -0.33) and chest width (0.21 to 0.30), i.e., with traits often associated with long-lasting cows. Unfavorable correlations were found with angularity (-0.18 to -0.26). Regression coefficients from regressing ProdI on sire estimated breeding values for longevity tend to show favorable relationships between these 2 traits (0.10 to 0.20). Results show that animals can be selected for ProdI, as there is good genetic variation between bulls. ProdI is a potential trait to be included in selection indices, as it has favorable genetic relationships with economically important functional traits such as health, conformation, and longevity.

Bayesian inference on major loci in related multigeneration selection lines of laying hens

A mixed inheritance model, postulating a polygenic effect and differences between the 3 genotypes of a biallelic locus, was fitted separately to the data of 2 multigeneration selection lines and a control evolving from a common base population. Inferences about the model were drawn from the application of the Gibbs sampler. Body weight at 20 and 40 wk (BW20, BW40) and average egg weight to 40 wk (EW40) were included in the analyses. Significance of differences between posterior means of parameters was established by comparing their 95% highest probability density regions. Significant (P < 0.05) additive and dominance effects due to the genotypes at the major locus were found for all traits. The allele causing a lower trait value was the (partial) dominant one in all traits, leading to a negative dominance effect. The additive variance due to the major locus was also significant, i.e., greater than zero (P < 0.05) in all traits, whereas the dominance variance was only important for EW40. With the exception of the residual variances of one selection and the control line, no (P > 0.05) differences of posterior means of any parameter could be observed between lines. No significant genotypic or polygenic selection response was found for BW40. On the contrary, both genetic responses were found significant for EW40 in the selected lines, but not in the control. No differences (P > 0.05) between lines could be observed for the derived frequencies of the allele causing the higher trait value and the frequencies of one homozygote and the heterozygote genotypes at the major locus. The detection of a major locus with relatively modest effect confirmed that this type of analysis with data from selected lines was indeed powerful.

Genetic Parameters for Body Condition Score and its Relationship with Type and Production Traits in Swiss Holsteins

The objectives of this study were to estimate the genetic and environmental parameters between body condition score (BCS) and 27 conformation and 3 production traits in Swiss Holstein cattle. The dataset consisted of 31,500 first-lactation cows, which were daughters of 545 sires in 1867 herds. Bivariate sire models with relationships among sires were used to estimate parameters. Least squares means for BCS by lactation stage show that cows lose BCS up to 5 mo after calving and gain BCS prior to the next calving. Regression models showed that an increase in age and percentage of Holstein genes results in an increase and decrease in BCS, respectively. Heritability (h2) was 0.24 for BCS score, which indicates good potential for selection. Sire estimated breeding values for BCS ranged from -0.46 to +0.51 units. Heritabilities ranged from 0.08 (heel depth) to 0.46 (rump width) for type traits and 0.23 to 0.29 for yield traits. Genetic correlations of BCS with 8 conformation traits were significant; stature (0.28), heart girth (0.21), strength (0.17), loin (-0.39), body capacity (0.19), dairy character (-0.35), udder quality (-0.42), and teat position rear (-0.33). Milk production and body condition have an unfavorable genetic correlation (-0.12 to -0.17). These results show that selection for good body condition, body conformation, and optimal milk production is possible and their genetic associations reported here will be useful for designing Swiss breeding goals.

Power of quantitative trait locus mapping for polygenic binary traits using generalized and regression interval mapping in multi-family half-sib designs

A generalized interval mapping (GIM) method to map quantitative trait loci (QTL) for binary polygenic traits in a multi-family half-sib design is developed based on threshold theory and implemented using a Newton-Raphson algorithm. Statistical power and bias of QTL mapping for binary traits by GIM is compared with linear regression interval mapping (RIM) using simulation. Data on 20 paternal half-sib families were simulated with two genetic markers that bracketed an additive QTL. Data simulated and analysed were: (1) data on the underlying normally distributed liability (NDL) scale, (2) binary data created by truncating NDL data based on three thresholds yielding data sets with three different incidences, and (3) NDL data with polygenic and QTL effects reduced by a proportion equal to the ratio of the heritabilities on the binary versus NDL scale (reduced-NDL). Binary data were simulated with and without systematic environmental (herd) effects in an unbalanced design. GIM and RIM gave similar power to detect the QTL and similar estimates of QTL location, effects and variances. Presence of fixed effects caused differences in bias between RIM and GIM, where GIM showed smaller bias which was affected less by incidence. The original NDL data had higher power and lower bias in QTL parameter estimates than binary and reduced-NDL data. RIM for reduced-NDL and binary data gave similar power and estimates of QTL parameters, indicating that the impact of the binary nature of data on QTL analysis is equivalent to its impact on heritability.