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Epigenetic mechanisms are important modulators of neurodevelopmental outcomes in the offspring of animals challenged during pregnancy. Pregnant sows living in a confined environment are challenged with stress and lack of stimulation which may result in the expression of stereotypies (repetitive behaviours without an apparent function). Little attention has been devoted to the postnatal effects of maternal stereotypies in the offspring. We investigated how the environment and stereotypies of pregnant sows affected the neuro-epigenome of their piglets. We focused on the amygdala, frontal cortex, and hippocampus, brain regions related to emotionality, learning, memory, and stress response. Differentially methylated regions (DMRs) were investigated in these brain regions of male piglets born from sows kept in an enriched vs a barren environment. Within the latter group of piglets, we compared the brain methylomes of piglets born from sows expressing stereotypies vs sows not expressing stereotypies. DMRs emerged in each comparison. While the epigenome of the hippocampus and frontal cortex of piglets is mainly affected by the maternal environment, the epigenome of the amygdala is mainly affected by maternal stereotypies. The molecular pathways and mechanisms triggered in the brains of piglets by maternal environment or stereotypies are different, which is reflected on the differential gene function associated to the DMRs found in each piglets' brain region . The present study is the first to investigate the neuro-epigenomic effects of maternal enrichment in pigs' offspring and the first to investigate the neuro-epigenomic effects of maternal stereotypies in the offspring of a mammal.

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Epigenetics works as an interface between the individual and its environment to provide phenotypic plasticity to increase individual adaptation capabilities. Recently, a wide variety of epi-genetic findings have indicated evidence for its application in the development of putative epi-biomarkers of stress in farm animals. The purpose of this study was to evaluate previously reported stress epi-biomarkers in swine and encourage researchers to investigate potential paths for the development of a robust molecular tool for animal welfare certification. In this literature review, we report on the scientific concerns in the swine production chain, the management carried out on the farms, and the potential implications of these practices for the animals' welfare and their epigenome. To assess reported epi-biomarkers, we identified, from previous studies, potentially stress-related genes surrounding epi-biomarkers. With those genes, we carried out a functional enrichment analysis of differentially methylated regions (DMRs) of the DNA of swine subjected to different stress-related conditions (e.g., heat stress, intrauterine insult, and sanitary challenges). We identified potential epi-biomarkers for target analysis, which could be added to the current guidelines and certification schemes to guarantee and certify animal welfare on farms. We believe that this technology may have the power to increase consumers' trust in animal welfare.

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Production animals are constantly subjected to early adverse environmental conditions that influence the adult phenotype and produce epigenetic effects. CpG dinucleotide methylation in red blood cells (RBC) could be a useful epigenetic biomarker to identify animals subjected to chronic stress in the production environment. Here we compared a reduced fraction of the RBC methylome of chickens exposed to social isolation to non-exposed. These experiments were performed in two different locations: Brazil and Sweden. The aim was to identify stress-associated DNA methylation profiles in RBC across these populations, in spite of the variable conditions to which birds are exposed in each facility and their different lineages. Birds were increasingly exposed to a social isolation treatment, combined with food and water deprivation, at random periods of the day from weeks 1-4 after hatching. We then collected the RBC DNA from individuals and compared a reduced fraction of their methylome between the experimental groups using two bioinformatic approaches to identify differentially methylated regions (DMRs): one using fixed-size windows and another that preselected differential peaks with MACS2. Three levels of significance were used (P ≤ 0.05, P ≤ 0.005, and P ≤ 0.0005) to identify DMRs between experimental groups, which were then used for different analyses. With both of the approaches more DMRs reached the defined significance thresholds in BR individuals compared to SW. However, more DMRs had higher fold change values in SW compared to BR individuals. Interestingly, ChrZ was enriched above expectancy for the presence of DMRs. Additionally, when analyzing the locations of these DMRs in relation to the transcription starting site (TSS), we found three peaks with high DMR presence: 10 kb upstream, the TSS itself, and 20-40 kb downstream. Interestingly, these peaks had DMRs with a high presence (>50%) of specific transcription factor binding sites. Three overlapping DMRs were found between the BR and SW population using the most relaxed p-value (P ≤ 0.05). With the most stringent p-value (P ≤ 0.0005), we found 7 and 4 DMRs between treatments in the BR and SW populations, respectively. This study is the first approximation to identify epigenetic biomarkers of long-term exposure to stress in different lineages of production animals.

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Oleic acid (OA) and cis-9, trans-11 conjugated linoleic acid (c9t11-CLA) are fatty acids found in beef with beneficial effects in human health. This study investigated differentially abundant proteins (DAPs) in skeletal muscle of bovines with extreme values of OA, and c9t11-CLA. For each one of the fatty acids, twenty muscle samples were divided into two groups (N = 10_High; N = 10_Low) and analyzed by high definition mass spectrometry. We identified 103 and 133 DAPs between the groups for each fatty acid. We found 64 and 45 up-regulated and 39 and 68 down-regulated proteins for OA and c9t11-CLA, respectively. Comparative analysis between proteomic and transcriptomic data revealed eight and ten genes with a consistent between mRNA expression levels and protein abundance for OA and c9t11-CLA, respectively. Unconventional myosin-Id (MYO1D), mineralocorticoid receptor (NR3C2), geranylgeranyl transferase type-2 subunit-alpha (RABGGTA), and uveal autoantigen with coiled-coil domains and ankyrin repeats (UACA) were found as putative candidate proteins for OA content. Fatty acid synthase (FASN), tubulin alpha-4A chain (TUBA4A), vinculin (VCL), NADH dehydrogenase 1 alpha subcomplex 5 (NDUFA5), and prefoldin subunit 6 (PFDN6) for c9t11-CLA. Our findings contribute to a deeper understanding of the molecular mechanisms behind the regulation of the OA and c9t11-CLA content in cattle skeletal muscle. SIGNIFICANCE: Questions about the association between meat intake and disease incidence in humans has driven animal scientist to pursue a better understanding of the biological processes associated with differences in the intramuscular fat composition. The beneficial effects of oleic acid and conjugated linoleic acid in human health have been demonstrated by improving the immune system and preventing atherosclerosis, different types of cancers, hypertension, and diabetes. Previous genome-wide association and gene expression studies identified genomic regions and differentially expressed genes associated with the fatty acid profile in skeletal muscle. In this work, differences were evaluated at the protein level. The use of a label-free quantitative proteomic approach, compared with muscle transcriptome results obtained by RNA-sequencing, allowed us to earn new insights into the variability in fatty acid deposition in skeletal muscle of farm animals. This study opens new avenues to explore the effect of the fatty acids in the skeletal muscle of livestock animals, which is associated with nutritional values of the meat, and perhaps to understand the mechanisms correlated with metabolic diseases in other species.

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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.

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The Indubrasil breed was developed in the Brazilian region called Triângulo Mineiro as a result of a cross between zebu cattle. Initially, it was used as a terminal cross and currently it represents approximately 4.45% of all the Brazilian zebu cattle. Studies were conducted to estimate genetic parameters in the Indubrasil using pedigree information, however, until now, no study has been developed using large-scale genomic markers in this breed. Pedigree information are widely used to investigate population parameters; however, they can neglect some estimates when compared to the use of genomic markers. Therefore, the objective of this study was to investigate the population structure and the genetic diversity of Indubrasil cattle using a high-density Single Nucleotide Polymorphism (SNP) panel (Illumina BovineHD BeadChip 700k). Levels of genomic homozygosity were evaluated using three different approaches: Runs of homozygosity (FROH), % of homozygosis (FSNP), and inbreeding coefficient (Fx). Further, Runs of Homozygosity (ROH) segments conserved among the animals were investigated to identify possible regions associated with the breed characteristics. Our results indicate that even the Indubrasil breed having a small effective population size, the levels of homozygosity (FROH = 0.046) are still small. This was possibly caused by the cross conducted among different breeds for its development. It suggests no immediate risks associated with loss of genetic variation. This information might be used in breeding programs, for the breed conservation and for the expansion of the Indubrasil breed.

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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.

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Colossoma macropomum, or tambaqui, is the largest native Characiform species found in the Amazon and Orinoco river basins, yet few resources for genetic studies and the genetic improvement of tambaqui exist. In this study, we identified a large number of single-nucleotide polymorphisms (SNPs) for tambaqui and constructed a high-resolution genetic linkage map from a full-sib family of 124 individuals and their parents using the genotyping by sequencing method. In all, 68,584 SNPs were initially identified using minimum minor allele frequency (MAF) of 5%. Filtering parameters were used to select high-quality markers for linkage analysis. We selected 7,734 SNPs for linkage mapping, resulting in 27 linkage groups with a minimum logarithm of odds (LOD) of 8 and maximum recombination fraction of 0.35. The final genetic map contains 7,192 successfully mapped markers that span a total of 2,811 cM, with an average marker interval of 0.39 cM. Comparative genomic analysis between tambaqui and zebrafish revealed variable levels of genomic conservation across the 27 linkage groups which allowed for functional SNP annotations. The large-scale SNP discovery obtained here, allowed us to build a high-density linkage map in tambaqui, which will be useful to enhance genetic studies that can be applied in breeding programs.

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Performance traits are economically important and are targets for selection in breeding programs, especially in the poultry industry. To identify regions on the chicken genome associated with performance traits, different genomic approaches have been applied in the last years. The aim of this study was the application of CornellGBS approach (134,528 SNPs generated from a PstI restriction enzyme) on Genome-Wide Association Studies (GWAS) in an outbred F2 chicken population. We have validated 91.7% of these 134,528 SNPs after imputation of missed genotypes. Out of those, 20 SNPs were associated with feed conversion, one was associated with body weight at 35 days of age (P < 7.86E-07) and 93 were suggestively associated with a variety of performance traits (P < 1.57E-05). The majority of these SNPs (86.2%) overlapped with previously mapped QTL for the same performance traits and some of the SNPs also showed novel potential QTL regions. The results obtained in this study suggests future searches for candidate genes and QTL refinements as well as potential use of the SNPs described here in breeding programs.

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Brazil is one of the largest beef producers and exporters in the world with the Nelore breed representing the vast majority of Brazilian cattle (Bos taurus indicus). Despite the great adaptability of the Nelore breed to tropical climate, meat tenderness (MT) remains to be improved. Several factors including genetic composition can influence MT. In this article, we report a genome-wide analysis of copy number variation (CNV) inferred from Illumina® High Density SNP-chip data for a Nelore population of 723 males. We detected >2,600 CNV regions (CNVRs) representing ≈6.5% of the genome. Comparing our results with previous studies revealed an overlap in ≈1400 CNVRs (>50%). A total of 1,155 CNVRs (43.6%) overlapped 2,750 genes. They were enriched for processes involving guanosine triphosphate (GTP), previously reported to influence skeletal muscle physiology and morphology. Nelore CNVRs also overlapped QTLs for MT reported in other breeds (8.9%, 236 CNVRs) and from a previous study with this population (4.1%, 109 CNVRs). Two CNVRs were also proximal to glutathione metabolism genes that were previously associated with MT. Genome-wide association study of CN state with estimated breeding values derived from meat shear force identified 6 regions, including a region on BTA3 that contains genes of the cAMP and cGMP pathway. Ten CNVRs that overlapped regions associated with MT were successfully validated by qPCR. Our results represent the first comprehensive CNV study in Bos taurus indicus cattle and identify regions in which copy number changes are potentially of importance for the MT phenotype.

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Chicken genotyping is becoming common practice in conventional animal breeding improvement. Despite the power of high-throughput methods for genotyping, their high cost limits large scale use in animal breeding and selection. In the present paper we optimized the CornellGBS, an efficient and cost-effective genotyping by sequence approach developed in plants, for its application in chickens. Here we describe the successful genotyping of a large number of chickens (462) using CornellGBS approach. Genomic DNA was cleaved with the PstI enzyme, ligated to adapters with barcodes identifying individual animals, and then sequenced on Illumina platform. After filtering parameters were applied, 134,528 SNPs were identified in our experimental population of chickens. Of these SNPs, 67,096 had a minimum taxon call rate of 90% and were considered 'unique tags'. Interestingly, 20.7% of these unique tags have not been previously reported in the dbSNP. Moreover, 92.6% of these SNPs were concordant with a previous Whole Chicken-genome re-sequencing dataset used for validation purposes. The application of CornellGBS in chickens showed high performance to infer SNPs, particularly in exonic regions and microchromosomes. This approach represents a cost-effective (~US$50/sample) and powerful alternative to current genotyping methods, which has the potential to improve whole-genome selection (WGS), and genome-wide association studies (GWAS) in chicken production.

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Repeated measures from the same individual have been analyzed by using repeatability and finite dimension models under univariate or multivariate analyses. However, in the last decade, the use of random regression models for genetic studies with longitudinal data have become more common. Thus, the aim of this research was to estimate genetic parameters for body weight of four experimental chicken lines by using univariate random regression models. Body weight data from hatching to 84 days of age (n = 34,730) from four experimental free-range chicken lines (7P, Caipirão da ESALQ, Caipirinha da ESALQ and Carijó Barbado) were used. The analysis model included the fixed effects of contemporary group (gender and rearing system), fixed regression coefficients for age at measurement, and random regression coefficients for permanent environmental effects and additive genetic effects. Heterogeneous variances for residual effects were considered, and one residual variance was assigned for each of six subclasses of age at measurement. Random regression curves were modeled by using Legendre polynomials of the second and third orders, with the best model chosen based on the Akaike Information Criterion, Bayesian Information Criterion, and restricted maximum likelihood. Multivariate analyses under the same animal mixed model were also performed for the validation of the random regression models. The Legendre polynomials of second order were better for describing the growth curves of the lines studied. Moderate to high heritabilities (h(2) = 0.15 to 0.98) were estimated for body weight between one and 84 days of age, suggesting that selection for body weight at all ages can be used as a selection criteria. Genetic correlations among body weight records obtained through multivariate analyses ranged from 0.18 to 0.96, 0.12 to 0.89, 0.06 to 0.96, and 0.28 to 0.96 in 7P, Caipirão da ESALQ, Caipirinha da ESALQ, and Carijó Barbado chicken lines, respectively. Results indicate that genetic gain for body weight can be achieved by selection. Also, selection for body weight at 42 days of age can be maintained as a selection criterion.

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