Phenotypic divergence between broiler and layer chicken lines is regulated at the molecular level during development.

BACKGROUND: Understanding the molecular underpinnings of phenotypic variations is critical for enhancing poultry breeding programs. The Brazilian broiler (TT) and laying hen (CC) lines exhibit striking differences in body weight, growth potential, and muscle mass. Our work aimed to compare the global transcriptome of wing and pectoral tissues during the early development (days 2.5 to 3.5) of these chicken lines, unveiling disparities in gene expression and regulation. RESULTS: Different and bona-fide transcriptomic profiles were identified for the compared lines. A similar number of up- and downregulated differentially expressed genes (DEGs) were identified, considering the broiler line as a reference. Upregulated DEGs displayed an enrichment of protease-encoding genes, whereas downregulated DEGs exhibited a prevalence of receptors and ligands. Gene Ontology analysis revealed that upregulated DEGs were mainly associated with hormone response, mitotic cell cycle, and different metabolic and biosynthetic processes. In contrast, downregulated DEGs were primarily linked to communication, signal transduction, cell differentiation, and nervous system development. Regulatory networks were constructed for the mitotic cell cycle and cell differentiation biological processes, as their contrasting roles may impact the development of distinct postnatal traits. Within the mitotic cell cycle network, key upregulated DEGs included CCND1 and HSP90, with central regulators being NF-κB subunits (RELA and REL) and NFATC2. The cell differentiation network comprises numerous DEGs encoding transcription factors (e.g., HOX genes), receptors, ligands, and histones, while the main regulatory hubs are CREB, AR and epigenetic modifiers. Clustering analyses highlighted PIK3CD as a central player within the differentiation network. CONCLUSIONS: Our study revealed distinct developmental transcriptomes between Brazilian broiler and layer lines. The gene expression profile of broiler embryos seems to favour increased cell proliferation and delayed differentiation, which may contribute to the subsequent enlargement of pectoral tissues during foetal and postnatal development. Our findings pave the way for future functional studies and improvement of targeted traits of economic interest in poultry.

Ancestral alleles defined for 70 million cattle variants using a population-based likelihood ratio test.

BACKGROUND: The study of ancestral alleles provides insights into the evolutionary history, selection, and genetic structures of a population. In cattle, ancestral alleles are widely used in genetic analyses, including the detection of signatures of selection, determination of breed ancestry, and identification of admixture. Having a comprehensive list of ancestral alleles is expected to improve the accuracy of these genetic analyses. However, the list of ancestral alleles in cattle, especially at the whole genome sequence level, is far from complete. In fact, the current largest list of ancestral alleles (~ 42 million) represents less than 28% of the total number of detected variants in cattle. To address this issue and develop a genomic resource for evolutionary studies, we determined ancestral alleles in cattle by comparing prior derived whole-genome sequence variants to an out-species group using a population-based likelihood ratio test. RESULTS: Our study determined and makes available the largest list of ancestral alleles in cattle to date (70.1 million) and includes 2.3 million on the X chromosome. There was high concordance (97.6%) of the determined ancestral alleles with those from previous studies when only high-probability ancestral alleles were considered (29.8 million positions) and another 23.5 million high-confidence ancestral alleles were novel, expanding the available reference list to improve the accuracies of genetic analyses involving ancestral alleles. The high concordance of the results with previous studies implies that our approach using genomic sequence variants and a likelihood ratio test to determine ancestral alleles is appropriate. CONCLUSIONS: Considering the high concordance of ancestral alleles across studies, the ancestral alleles determined in this study including those not previously listed, particularly those with high-probability estimates, may be used for further genetic analyses with reasonable accuracy. Our approach that used predetermined variants in species and the likelihood ratio test to determine ancestral alleles is applicable to other species for which sequence level genotypes are available.

An association weight matrix identified biological pathways associated with bull fertility traits in a multi-breed population.

Using seven indicator traits, we investigated the genetic basis of bull fertility and predicted gene interactions from SNP associations. We used percent normal sperm as the key phenotype for the association weight matrix-partial correlation information theory (AWM-PCIT) approach. Beyond a simple list of candidate genes, AWM-PCIT predicts significant gene interactions and associations for the selected traits. These interactions formed a network of 537 genes: 38 genes were transcription cofactors, and 41 genes were transcription factors. The network displayed two distinct clusters, one with 294 genes and another with 243 genes. The network is enriched in fertility-associated pathways: steroid biosynthesis, p53 signalling, and the pentose phosphate pathway. Enrichment analysis also highlighted gene ontology terms associated with 'regulation of neurotransmitter secretion' and 'chromatin formation'. Our network recapitulates some genes previously implicated in another network built with lower-density genotypes. Sequence-level data also highlights additional candidate genes relevant to bull fertility, such as FOXO4, FOXP3, GATA1, CYP27B1, and EBP. A trio of regulatory genes-KDM5C, LRRK2, and PME-was deemed core to the network because of their overarching connections. This trio probably influences bull fertility through their interaction with genes, both known and unknown as to their role in male fertility. Future studies may target the trio and their target genes to enrich our understanding of male fertility further.

Sequence level genome-wide associations for bull production and fertility traits in tropically adapted bulls.

BACKGROUND: The genetics of male fertility is complex and not fully understood. Male subfertility can adversely affect the economics of livestock production. For example, inadvertently mating bulls with poor fertility can result in reduced annual liveweight production and suboptimal husbandry management. Fertility traits, such as scrotal circumference and semen quality are commonly used to select bulls before mating and can be targeted in genomic studies. In this study, we conducted genome-wide association analyses using sequence-level data targeting seven bull production and fertility traits measured in a multi-breed population of 6,422 tropically adapted bulls. The beef bull production and fertility traits included body weight (Weight), body condition score (CS), scrotal circumference (SC), sheath score (Sheath), percentage of normal spermatozoa (PNS), percentage of spermatozoa with mid-piece abnormalities (MP) and percentage of spermatozoa with proximal droplets (PD). RESULTS: After quality control, 13,398,171 polymorphisms were tested for their associations with each trait in a mixed-model approach, fitting a multi-breed genomic relationship matrix. A Bonferroni genome-wide significance threshold of 5 × 10- 8 was imposed. This effort led to identifying genetic variants and candidate genes underpinning bull fertility and production traits. Genetic variants in Bos taurus autosome (BTA) 5 were associated with SC, Sheath, PNS, PD and MP. Whereas chromosome X was significant for SC, PNS, and PD. The traits we studied are highly polygenic and had significant results across the genome (BTA 1, 2, 4, 6, 7, 8, 11, 12, 14, 16, 18, 19, 23, 28, and 29). We also highlighted potential high-impact variants and candidate genes associated with Scrotal Circumference (SC) and Sheath Score (Sheath), which warrants further investigation in future studies. CONCLUSION: The work presented here is a step closer to identifying molecular mechanisms that underpin bull fertility and production. Our work also emphasises the importance of including the X chromosome in genomic analyses. Future research aims to investigate potential causative variants and genes in downstream analyses.

Unravelling the genetic variability of host resilience to endo- and ectoparasites in Nellore commercial herds.

BACKGROUND: Host resilience (HR) to parasites can affect the performance of animals. Therefore, the aim of this study was to present a detailed investigation of the genetic mechanisms of HR to ticks (TICK), gastrointestinal nematodes (GIN), and Eimeria spp. (EIM) in Nellore cattle that were raised under natural infestation and a prophylactic parasite control strategy. In our study, HR was defined as the slope coefficient of body weight (BW) when TICK, GIN, and EIM burdens were used as environmental gradients in random regression models. In total, 1712 animals were evaluated at five measurement events (ME) at an average age of 331, 385, 443, 498, and 555 days, which generated 7307 body weight (BW) records. Of the 1712 animals, 1075 genotyped animals were used in genome-wide association studies to identify genomic regions associated with HR. RESULTS: Posterior means of the heritability estimates for BW ranged from 0.09 to 0.54 across parasites and ME. The single nucleotide polymorphism (SNP)-derived heritability for BW at each ME ranged from a low (0.09 at ME.331) to a moderate value (0.23 at ME.555). Those estimates show that genetic progress can be achieved for BW through selection. Both genetic and genomic associations between BW and HR to TICK, GIN, and EIM confirmed that parasite infestation impacted the performance of animals. Selection for BW under an environment with a controlled parasite burden is an alternative to improve both, BW and HR. There was no impact of age of measurement on the estimates of genetic variance for HR. Five quantitative trait loci (QTL) were associated with HR to EIM but none with HR to TICK and to GIN. These QTL contain genes that were previously shown to be associated with the production of antibody modulators and chemokines that are released in the intestinal epithelium. CONCLUSIONS: Selection for BW under natural infestation and controlled parasite burden, via prophylactic parasite control, contributes to the identification of animals that are resilient to nematodes and Eimeria ssp. Although we verified that sufficient genetic variation existed for HR, we did not find any genes associated with mechanisms that could justify the expression of HR to TICK and GIN.

The identification and validation of target genes of IGFBP3 protein in sheep skeletal muscle cells.

This study aimed to identify the target genes of IGFBP3（insulin growth factor binding protein）protein and to investigate its target genes effects on the proliferation and differentiation of Hu sheep skeletal muscle cells. IGFBP3 was an RNA-binding protein that regulates mRNA stability. Previous studies have reported that IGFBP3 promotes the proliferation of Hu sheep skeletal muscle cells and inhibits differentiation, but the downstream genes that bind to it have not been reported yet. We predicted the target genes of IGFBP3 through RNAct and sequencing data, and verified by qPCR and RIP（RNA Immunoprecipitation）experiments, and demonstrated GNAI2（G protein subunit alpha i2）as one of the target gene of IGFBP3. After interference with siRNA, we carried out qPCR, CCK8, EdU, and immunofluorescence experiments, and found that GNAI2 can promote the proliferation and inhibit differentiation of Hu sheep skeletal muscle cells. This study revealed the effects of GNAI2 and provided one of the regulatory mechanisms of IGFBP3 protein underlying sheep muscle development.

Leveraging transcriptome and epigenome landscapes to infer regulatory networks during the onset of sexual maturation.

BACKGROUND: Despite sexual development being ubiquitous to vertebrates, the molecular mechanisms underpinning this fundamental transition remain largely undocumented in many organisms. We designed a time course experiment that successfully sampled the period when Atlantic salmon commence their trajectory towards sexual maturation. RESULTS: Through deep RNA sequencing, we discovered key genes and pathways associated with maturation in the pituitary-ovarian axis. Analyzing DNA methylomes revealed a bias towards hypermethylation in ovary that implicated maturation-related genes. Co-analysis of DNA methylome and gene expression changes revealed chromatin remodeling genes and key transcription factors were both significantly hypermethylated and upregulated in the ovary during the onset of maturation. We also observed changes in chromatin state landscapes that were strongly correlated with fundamental remodeling of gene expression in liver. Finally, a multiomic integrated analysis revealed regulatory networks and identified hub genes including TRIM25 gene (encoding the estrogen-responsive finger protein) as a putative key regulator in the pituitary that underwent a 60-fold change in connectivity during the transition to maturation. CONCLUSION: The study successfully documented transcriptome and epigenome changes that involved key genes and pathways acting in the pituitary - ovarian axis. Using a Systems Biology approach, we identified hub genes and their associated networks deemed crucial for onset of maturation. The results provide a comprehensive view of the spatiotemporal changes involved in a complex trait and opens the door to future efforts aiming to manipulate puberty in an economically important aquaculture species.

Bias, dispersion, and accuracy of genomic predictions for feedlot and carcase traits in Australian Angus steers.

BACKGROUND: Improving feedlot performance, carcase weight and quality is a primary goal of the beef industry worldwide. Here, we used data from 3408 Australian Angus steers from seven years of birth (YOB) cohorts (2011-2017) with a minimal level of sire linkage and that were genotyped for 45,152 SNPs. Phenotypic records included two feedlot and five carcase traits, namely average daily gain (ADG), average daily dry matter intake (DMI), carcase weight (CWT), carcase eye muscle area (EMA), carcase Meat Standard Australia marbling score (MBL), carcase ossification score (OSS) and carcase subcutaneous rib fat depth (RIB). Using a 7-way cross-validation based on YOB cohorts, we tested the quality of genomic predictions using the linear regression (LR) method compared to the traditional method (Pearson's correlation between the genomic estimated breeding value (GEBV) and its associated adjusted phenotype divided by the square root of heritability); explored the factors, such as heritability, validation cohort, and phenotype that affect estimates of accuracy, bias, and dispersion calculated with the LR method; and suggested a novel interpretation for translating differences in accuracy into phenotypic differences, based on GEBV quartiles (Q1Q4). RESULTS: Heritability (h2) estimates were generally moderate to high (from 0.29 for ADG to 0.53 for CWT). We found a strong correlation (0.73, P-value < 0.001) between accuracies using the traditional method and those using the LR method, although the LR method was less affected by random variation within and across years and showed a better ability to discriminate between extreme GEBV quartiles. We confirmed that bias of GEBV was not significantly affected by h2, validation cohort or trait. Similarly, validation cohort was not a significant source of variation for any of the GEBV quality metrics. Finally, we observed that the phenotypic differences were larger for higher accuracies. CONCLUSIONS: Our estimates of h2 and GEBV quality metrics suggest a potential for accurate genomic selection of Australian Angus for feedlot performance and carcase traits. In addition, the Q1Q4 measure presented here easily translates into possible gains of genomic selection in terms of phenotypic differences and thus provides a more tangible output for commercial beef cattle producers.

A conserved haplotype in Wagyu cattle contains RAB4A whose encoded protein regulates glucose trafficking in muscle and fat cells.

The Wagyu breed of taurine cattle possess favourable genetics for intramuscular fat (IMF) but genomic loci associated with the trait remain under characterised. Here, we report the identification of a previously unidentified genomic region possessing a particular haplotype structure in Wagyu. Through deployment of a genome-wide haplotype detection analysis that captures regions conserved in a target population but not other populations we screened 100 individual Wagyu and contrasted them with 100 individuals from two independent comparison breeds, Charolais and Angus, using high-density SNPs. An extreme level of Wagyu conservation was assigned to a single genomic window (spanning genomic coordinates BTA28:41 088-300 265 bp). In fact, a five-SNP region spanning 27 096 bp is almost perfectly conserved among the 100 Wagyu individuals assayed and partially overlaps RAB4A. Focussing in, two consecutive SNPs (genomic coordinates 236 949 and 239 950) are apparently fixed within the Wagyu (BB and AA respectively), but at mixed frequencies in the other two breeds. These SNPs are located in the two introns straddling exon 7. In a separate analysis using the 1000 Bulls database, we found that, coincident with exon 7 of RAB4A first allele frequencies were highest in the high IMF Japanese Native (Wagyu) breeds (0.78) and lowest in the low IMF indicine breeds (Nelore and Brahman), with intermediate marbling breeds (Angus and Charolais) assigned intermediate rankings (0.42). RAB4A is known to encode a protein that regulates intracellular trafficking of the insulin-regulated glucose transporter GLUT4. RAB4A can be considered an attractive new positional candidate for IMF development.

Gene expression identifies metabolic and functional differences between intramuscular and subcutaneous adipocytes in cattle.

BACKGROUND: This study used a genome-wide screen of gene expression to better understand the metabolic and functional differences between commercially valuable intramuscular fat (IMF) and commercially wasteful subcutaneous (SC) fat depots in Bos taurus beef cattle. RESULTS: We confirmed many findings previously made at the biochemical level and made new discoveries. The fundamental lipogenic machinery, such as ACACA and FASN encoding the rate limiting Acetyl CoA carboxylase and Fatty Acid synthase were expressed at 1.6-1.8 fold lower levels in IMF, consistent with previous findings. The FA elongation pathway including the rate limiting ELOVL6 was also coordinately downregulated in IMF compared to SC as expected. A 2-fold lower expression in IMF of ACSS2 encoding Acetyl Coenzyme A synthetase is consistent with utilisation of less acetate for lipogenesis in IMF compared to SC as previously determined using radioisotope incorporation. Reduced saturation of fat in the SC depot is reflected by 2.4 fold higher expression of the SCD gene encoding the Δ9 desaturase enzyme. Surprisingly, CH25H encoding the cholesterol 25 hydroxylase enzyme was ~ 36 fold upregulated in IMF compared to SC. Moreover, its expression in whole muscle tissue appears representative of the proportional representation of bovine marbling adipocytes. This suite of observations prompted quantification of a set of oxysterols (oxidised forms of cholesterol) in the plasma of 8 cattle exhibiting varying IMF. Using Liquid Chromatography-Mass Spectrometry (LC-MS) we found the levels of several oxysterols were significantly associated with multiple marbling measurements across the musculature, but (with just one exception) no other carcass phenotypes. CONCLUSIONS: These data build on our molecular understanding of ruminant fat depot biology and suggest oxysterols represent a promising circulating biomarker for cattle marbling.

A systems biology framework integrating GWAS and RNA-seq to shed light on the molecular basis of sperm quality in swine.

BACKGROUND: Genetic pressure in animal breeding is sparking the interest of breeders for selecting elite boars with higher sperm quality to optimize ejaculate doses and fertility rates. However, the molecular basis of sperm quality is not yet fully understood. Our aim was to identify candidate genes, pathways and DNA variants associated to sperm quality in swine by analysing 25 sperm-related phenotypes and integrating genome-wide association studies (GWAS) and RNA-seq under a systems biology framework. RESULTS: By GWAS, we identified 12 quantitative trait loci (QTL) associated to the percentage of head and neck abnormalities, abnormal acrosomes and motile spermatozoa. Candidate genes included CHD2, KATNAL2, SLC14A2 and ABCA1. By RNA-seq, we identified a wide repertoire of mRNAs (e.g. PRM1, OAZ3, DNAJB8, TPPP2 and TNP1) and miRNAs (e.g. ssc-miR-30d, ssc-miR-34c, ssc-miR-30c-5p, ssc-miR-191, members of the let-7 family and ssc-miR-425-5p) with functions related to sperm biology. We detected 6128 significant correlations (P-value ≤ 0.05) between sperm traits and mRNA abundances. By expression (e)GWAS, we identified three trans-expression QTL involving the genes IQCJ, ACTR2 and HARS. Using the GWAS and RNA-seq data, we built a gene interaction network. We considered that the genes and interactions that were present in both the GWAS and RNA-seq networks had a higher probability of being actually involved in sperm quality and used them to build a robust gene interaction network. In addition, in the final network we included genes with RNA abundances correlated with more than four semen traits and miRNAs interacting with the genes on the network. The final network was enriched for genes involved in gamete generation and development, meiotic cell cycle, DNA repair or embryo implantation. Finally, we designed a panel of 73 SNPs based on the GWAS, eGWAS and final network data, that explains between 5% (for sperm cell concentration) and 36% (for percentage of neck abnormalities) of the phenotypic variance of the sperm traits. CONCLUSIONS: By applying a systems biology approach, we identified genes that potentially affect sperm quality and constructed a SNP panel that explains a substantial part of the phenotypic variance for semen quality in our study and that should be tested in other swine populations to evaluate its relevance for the pig breeding sector.

Selection signatures in tropical cattle are enriched for promoter and coding regions and reveal missense mutations in the damage response gene HELB.

BACKGROUND: Distinct domestication events, adaptation to different climatic zones, and divergent selection in productive traits have shaped the genomic differences between taurine and indicine cattle. In this study, we assessed the impact of artificial selection and environmental adaptation by comparing whole-genome sequences from European taurine and Asian indicine breeds and from African cattle. Next, we studied the impact of divergent selection by exploiting predicted and experimental functional annotation of the bovine genome. RESULTS: We identified selective sweeps in beef cattle taurine and indicine populations, including a 430-kb selective sweep on indicine cattle chromosome 5 that is located between 47,670,001 and 48,100,000 bp and spans five genes, i.e. HELB, IRAK3, ENSBTAG00000026993, GRIP1 and part of HMGA2. Regions under selection in indicine cattle display significant enrichment for promoters and coding genes. At the nucleotide level, sites that show a strong divergence in allele frequency between European taurine and Asian indicine are enriched for the same functional categories. We identified nine single nucleotide polymorphisms (SNPs) in coding regions that are fixed for different alleles between subspecies, eight of which were located within the DNA helicase B (HELB) gene. By mining information from the 1000 Bull Genomes Project, we found that HELB carries mutations that are specific to indicine cattle but also found in taurine cattle, which are known to have been subject to indicine introgression from breeds, such as N'Dama, Anatolian Red, Marchigiana, Chianina, and Piedmontese. Based on in-house genome sequences, we proved that mutations in HELB segregate independently of the copy number variation HMGA2-CNV, which is located in the same region. CONCLUSIONS: Major genomic sequence differences between Bos taurus and Bos indicus are enriched for promoter and coding regions. We identified a 430-kb selective sweep in Asian indicine cattle located on chromosome 5, which carries SNPs that are fixed in indicine populations and located in the coding sequences of the HELB gene. HELB is involved in the response to DNA damage including exposure to ultra-violet light and is associated with reproductive traits and yearling weight in tropical cattle. Thus, HELB likely contributed to the adaptation of tropical cattle to their harsh environment.

X chromosome variants are associated with male fertility traits in two bovine populations.

BACKGROUND: Twenty-five phenotypes were measured as indicators of bull fertility (1099 Brahman and 1719 Tropical Composite bulls). Measurements included sperm morphology, scrotal circumference, and sperm chromatin phenotypes such as DNA fragmentation and protamine deficiency. We estimated the heritability of these phenotypes and carried out genome-wide association studies (GWAS) within breed, using the bovine high-density chip, to detect quantitative trait loci (QTL). RESULTS: Our analyses suggested that both sperm DNA fragmentation and sperm protamine deficiency are heritable (h2 from 0.10 to 0.22). To confirm these first estimates of heritability, further studies on sperm chromatin traits, with larger datasets are necessary. Our GWAS identified 12 QTL for bull fertility traits, based on at least five polymorphisms (P < 10-8) for each QTL. Five QTL were identified in Brahman and another seven in Tropical Composite bulls. Most of the significant polymorphisms detected in both breeds and nine of the 12 QTL were on chromosome X. The QTL were breed-specific, but for some traits, a closer inspection of the GWAS results revealed suggestive single nucleotide polymorphism (SNP) associations (P < 10-7) in both breeds. For example, the QTL for inhibin level in Braham could be relevant to Tropical Composites too (many polymorphisms reached P < 10-7 in the same region). The QTL for sperm midpiece morphological abnormalities on chromosome X (QTL peak at 4.92 Mb, P < 10-17) is an example of a breed-specific QTL, supported by 143 significant SNPs (P < 10-8) in Brahman, but absent in Tropical Composites. Our GWAS results add evidence to the mammalian specialization of the X chromosome, which during evolution has accumulated genes linked to spermatogenesis. Some of the polymorphisms on chromosome X were associated to more than one genetically correlated trait (correlations ranged from 0.33 to 0.51). Correlations and shared polymorphism associations support the hypothesis that these phenotypes share the same underlying cause, i.e. defective spermatogenesis. CONCLUSIONS: Genetic improvement for bull fertility is possible through genomic selection, which is likely more accurate if the QTL on chromosome X are considered in the predictions. Polymorphisms associated with male fertility accumulate on this chromosome in cattle, as in humans and mice, suggesting its specialization.

Networks of inbreeding coefficients in a selected population of rabbits.

The correlation between pedigree and genomic-based inbreeding coefficients is usually discussed in the literature. However, some of these correlations could be spurious. Using partial correlations and information theory, it is possible to distinguish a significant association between two variables which is independent from associations with a third variable. The objective of this study is to implement partial correlations and information theory to assess the relationship between different inbreeding coefficients using a selected population of rabbits. Data from pedigree and genomic information from a 200K SNP chip were available. After applying filtering criteria, the data set comprised 437 animals genotyped for 114,604 autosomal SNP. Fifteen pedigree- and genome-based inbreeding coefficients were estimated and used to build a network. Recent inbreeding coefficient based on runs of homozygosity had 9 edges linking it with different inbreeding coefficients. Partial correlations and information theory approach allowed to infer meaningful associations between inbreeding coefficients and highlighted the importance of the recent inbreeding based on runs of homozygosity, but a good proxy of it could be those pedigree-based definitions reflecting recent inbreeding.

Identification and Annotation of Potential Function of Regulatory Antisense Long Non-Coding RNAs Related to Feed Efficiency in Bos taurus Bulls.

Long non-coding RNAs (lncRNAs) can influence transcriptional and translational processes in mammalian cells and are associated with various developmental, physiological and phenotypic conditions. However, they remain poorly understood and annotated in livestock species. We combined phenotypic, metabolomics and liver transcriptomic data of bulls divergent for residual feed intake (RFI) and fat accretion. Based on a project-specific transcriptome annotation for the bovine reference genome ARS-UCD.1.2 and multiple-tissue total RNA sequencing data, we predicted 3590 loci to be lncRNAs. To identify lncRNAs with potential regulatory influence on phenotype and gene expression, we applied the regulatory impact factor algorithm on a functionally prioritized set of loci (n = 4666). Applying the algorithm of partial correlation and information theory, significant and independent pairwise correlations were calculated and co-expression networks were established, including plasma metabolites correlated with lncRNAs. The network hub lncRNAs were assessed for potential cis-actions and subjected to biological pathway enrichment analyses. Our results reveal a prevalence of antisense lncRNAs positively correlated with adjacent protein-coding genes and suggest their participation in mitochondrial function, acute phase response signalling, TCA-cycle, fatty acid ß-oxidation and presumably gluconeogenesis. These antisense lncRNAs indicate a stabilizing function for their cis-correlated genes and a putative regulatory role in gene expression.

Correction to: Semi-parametric estimates of population accuracy and bias of predictions of breeding values and future phenotypes using the LR method.

After publication of original article [1], the authors noticed that there was an error.

Across-sex genomic-assisted genetic correlations for sex-influenced traits in Brahman cattle.

BACKGROUND: This study aimed at estimating genetic parameters of sex-influenced production traits, evaluating the impact of genotype-by-sex interaction, and identifying the selection criteria that could be included in multiple-trait genetic evaluation to increase the rate of genetic improvement in both sexes. To achieve this goal, we used 10 male and 10 female phenotypes, which were measured in a population of 2111 Australian Brahman cattle genotyped at high-density. RESULTS: Heritability estimates ranged from very low (0.03 ± 0.03 for cows' days to calving at first calving opportunity, DC1), to moderate (0.33 ± 0.08 for cows' adult body weight, AWTc), and to high (0.95 ± 0.07 for cows' hip height, HHc). Genetic correlation (rg) estimates between male and female homologous traits were favorable and ranged from moderate to high values, which indicate that selection for any of the traits in one sex would lead to a correlated response with the equivalent phenotype in the other sex. However, the estimated direct response was greater than the indirect response. Moreover, Pearson correlations between estimated breeding values obtained from each sex separately and from female and male homologous traits combined into a single trait in univariate analysis ranged from 0.74 to 0.99, which indicate that small ranking variation might appear if male and female traits are included as single or separate phenotypes. Genetic correlations between male growth and female reproductive traits were not significant, ranging from - 0.07 ± 0.13 to 0.45 ± 0.65. However, selection to improve HHc and AWTc in cows may reduce the percentage of normal sperm at 24 months of age (PNS24), possibly due to correlated effects in the same traits in males, which are related to late maturing animals. CONCLUSIONS: Hip height in cows and PNS24, as well as blood insulin-like growth factor 1 (IGF1) concentration in bulls at 6 months of age are efficient selection criteria to improve male growth and female reproductive traits, simultaneously. In the presence of genotype-by-sex interactions, selection for traits in each sex results in high rates of genetic improvement, however, for the identification of animals with the highest breeding value, data for males and females may be considered a single trait.

Neuropeptidome of the Hypothalamus and Pituitary Gland of Indicine × Taurine Heifers: Evidence of Differential Neuropeptide Processing in the Pituitary Gland before and after Puberty.

Puberty in cattle is regulated by an endocrine axis, which includes a complex milieu of neuropeptides in the hypothalamus and pituitary gland. The neuropeptidome of hypothalamic-pituitary gland tissue of pre- (PRE) and postpubertal (POST) Bos indicus-influenced heifers was characterized, followed by quantitative analysis of 51 fertility-related neuropeptides in these tissues. Comparison of peptide abundances with gene expression levels allowed assessment of post-transcriptional peptide processing. On the basis of classical cleavage, 124 mature neuropeptides from 35 precursor proteins were detected in hypothalamus and pituitary gland tissues of three PRE and three POST Brangus heifers. An additional 19 peptides (cerebellins, PEN peptides) previously reported as neuropeptides that did not follow classical cleavage were also identified. In the pre-pubertal hypothalamus, a greater diversity of neuropeptides (25.8%) was identified relative to post-pubertal heifers, while in the pituitary gland, 38.6% more neuropeptides were detected in the post-pubertal heifers. Neuro-tissues of PRE and POST heifers revealed abundance differences ( p < 0.05) in peptides from protein precursors involved in packaging and processing (e.g., the granin family and ProSAAS) or neuron stimulation (PENK, CART, POMC, cerebellins). On their own, the transcriptome data of the precursor genes could not predict the neuropeptide profile in the exact same tissues in several cases. This provides further evidence of the importance of differential processing of the neuropeptide precursors in the pituitary before and after puberty.

Semi-parametric estimates of population accuracy and bias of predictions of breeding values and future phenotypes using the LR method.

BACKGROUND: Cross-validation tools are used increasingly to validate and compare genetic evaluation methods but analytical properties of cross-validation methods are rarely described. There is also a lack of cross-validation tools for complex problems such as prediction of indirect effects (e.g. maternal effects) or for breeding schemes with small progeny group sizes. RESULTS: We derive the expected value of several quadratic forms by comparing genetic evaluations including "partial" and "whole" data. We propose statistics that compare genetic evaluations including "partial" and "whole" data based on differences in means, covariance, and correlation, and term the use of these statistics "method LR" (from linear regression). Contrary to common belief, the regression of true on estimated breeding values is (on expectation) lower than 1 for small or related validation sets, due to family structures. For validation sets that are sufficiently large, we show that these statistics yield estimators of bias, slope or dispersion, and population accuracy for estimated breeding values. Similar results hold for prediction of future phenotypes although we show that estimates of bias, slope or dispersion using prediction of future phenotypes are sensitive to incorrect heritabilities or precorrection for fixed effects. We present an example for a set of 2111 Brahman beef cattle for which, in repeated partitioning of the data into training and validation sets, there is very good agreement of statistics of method LR with prediction of future phenotypes. CONCLUSIONS: Analytical properties of cross-validation measures are presented. We present a new method named LR for cross-validation that is automatic, easy to use, and which yields the quantities of interest. The method compares predictions based on partial and whole data, which results in estimates of accuracy and biases. Prediction of observed records may yield biased results due to precorrection or use of incorrect heritabilities.

Dominance and epistatic genetic variances for litter size in pigs using genomic models.

BACKGROUND: Epistatic genomic relationship matrices for interactions of any-order can be constructed using the Hadamard products of orthogonal additive and dominance genomic relationship matrices and standardization based on the trace of the resulting matrices. Variance components for litter size in pigs were estimated by Bayesian methods for five nested models with additive, dominance, and pairwise epistatic effects in a pig dataset, and including genomic inbreeding as a covariate. RESULTS: Estimates of additive and non-additive (dominance and epistatic) variance components were obtained for litter size. The variance component estimates were empirically orthogonal, i.e. they did not change when fitting increasingly complex models. Most of the genetic variance was captured by non-epistatic effects, as expected. In the full model, estimates of dominance and total epistatic variances (additive-by-additive plus additive-by-dominance plus dominance-by-dominance), expressed as a proportion of the total phenotypic variance, were equal to 0.02 and 0.04, respectively. The estimate of broad-sense heritability for litter size (0.15) was almost twice that of the narrow-sense heritability (0.09). Ignoring inbreeding depression yielded upward biased estimates of dominance variance, while estimates of epistatic variances were only slightly affected. CONCLUSIONS: Epistatic variance components can be easily computed using genomic relationship matrices. Correct orthogonal definition of the relationship matrices resulted in orthogonal partition of genetic variance into additive, dominance, and epistatic components, but obtaining accurate variance component estimates remains an issue. Genomic models that include non-additive effects must also consider inbreeding depression in order to avoid upward bias of estimates of dominance variance. Inclusion of epistasis did not improve the accuracy of prediction of breeding values.