Association weight matrix for the genetic dissection of puberty in beef cattle

Advances in our understanding of the estrous cycle and applications for improving targeted reproductive management in livestock

The scientific discipline of endocrinology has been invaluable to our understanding of the estrous cycle. In the second half of the twentieth century the development of immunoassay technologies provided a rapid and sensitive method to quantify circulating concentrations of reproductive hormones and relate them to stage of the estrous cycle and physiological status of the animal. Ovarian ultrasonography provided the ability to track the growth and regression of ovarian structures within the same animal across the estrous cycle in real time and, in combination with hormonal profiling, accurately identify mechanisms regulating the estrous cycle and early pregnancy. Before this, the best technique had been serial collections with each animal being a single endpoint. The availability of continuous data such as daily hormone concentrations and daily follicular measurements within animals led to the improvement of methods to synchronize estrus in each of the species. Unfortunately, the use of radio-immunoassays has been declining for two decades. While enzyme-linked immunosorbent assays have been developed for many endocrine, paracrine, and autocrine factors, their primary market is human medicine and rodent models of human health, leaving those available for livestock species economically infeasible. Automated sensors such as accelerometers apply the knowledge attained through decades of endocrinology and ultrasonography studies to identify females in estrus and measure parameters of the estrous cycle that are related to fertility. The ability of automated sensors to centralize and assimilate large amounts of behavioral and physiological data from numerous animals will enhance targeted reproductive management in livestock production systems.

Genome to phenome Association for Pork Belly Parameters Elucidates Three Regulation Distinctions: Adipogenesis, muscle formation, and their transcription factors

Genome to phenome analysis is necessary in livestock areas because of its various and complex phenotypes. Pork belly is a favorable part of meat worldwide, including East Asia. A previous study has suggested that the three key transcription factors (ZNF444, NFYA and PPARG) affecting pork belly traits include total volume, the volume of total fat and muscle, and component muscles of the corresponding slice. However, other transcription factor genes affecting each slice other than pork belly component traits still needed to be identified. Thus, we aimed to analyze pork belly components at the genome to phenome level for identifying key transcription factor genes and their co-associated networks. The range of node numbers against each component trait via the association weight matrix was from 598 to 3020. Premised on the result, an in silico functional approach was performed. Each co-association network enriched three key transcription factors in adipogenesis and skeletal muscle proliferation, mesoderm development, metabolism, and gene transcription. The three key transcription factors and their related genes may be useful in comprehending their effect of pork belly construction.

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.

Uncovering the architecture of selection in two Bos taurus cattle breeds

Directional selection alters the genome via hard sweeps, soft sweeps, and polygenic selection. However, mapping polygenic selection is difficult because it does not leave clear signatures on the genome like a selective sweep. In populations with temporally stratified genotypes, the Generation Proxy Selection Mapping (GPSM) method identifies variants associated with generation number (or appropriate proxy) and thus variants undergoing directional allele frequency changes. Here, we use GPSM on two large datasets of beef cattle to detect associations between an animal's generation and 11 million imputed SNPs. Using these datasets with high power and dense mapping resolution, GPSM detected a total of 294 unique loci actively under selection in two cattle breeds. We observed that GPSM has a high power to detect selection in the very recent past (<10 years), even when allele frequency changes are small. Variants identified by GPSM reside in genomic regions associated with known breed-specific selection objectives, such as fertility and maternal ability in Red Angus, and carcass merit and coat color in Simmental. Over 60% of the selected loci reside in or near (<50 kb) annotated genes. Using haplotype-based and composite selective sweep statistics, we identify hundreds of putative selective sweeps that likely occurred earlier in the evolution of these breeds; however, these sweeps have little overlap with recent polygenic selection. This makes GPSM a complementary approach to sweep detection methods when temporal genotype data are available. The selected loci that we identify across methods demonstrate the complex architecture of selection in domesticated cattle.

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.

Harnessing Genomics and Transcriptomics Approaches to Improve Female Fertility in Beef Cattle-A Review

Female fertility is the foundation of the cow-calf industry, impacting both efficiency and profitability. Reproductive failure is the primary reason why beef cows are sold in the U.S. and the cause of an estimated annual gross loss of USD 2.8 billion. In this review, we discuss the status of the genomics, transcriptomics, and systems genomics approaches currently applied to female fertility and the tools available to cow-calf producers to maximize genetic progress. We highlight the opportunities and limitations associated with using genomic and transcriptomic approaches to discover genes and regulatory mechanisms related to beef fertility. Considering the complex nature of fertility, significant advances in precision breeding will rely on holistic, multidisciplinary approaches to further advance our ability to understand, predict, and improve reproductive performance. While these technologies have advanced our knowledge, the next step is to translate research findings from bench to on-farm applications.

Functional genomics of reproduction in pigs: Are we there yet?

Reproductive failure is the main reason for culling females in swine herds and is both a financial and sustainability issue. Because reproductive traits are complex and lowly to moderately heritable, genomic selection within populations can achieve substantial genetic gain in reproductive efficiency. A better understanding of the physiological components affecting the expression of these traits will facilitate greater understanding of the genes affecting reproductive traits and is necessary to improve and optimize management strategies to maximize reproductive success of gilts and sows. Large-scale genotyping with single-nucleotide polymorphism (SNP) arrays are used for genome-wide association studies (GWAS) and have facilitated identification of positional candidate genes. Transcriptomic data can be used to weight SNP for GWAS and could lead to previously unidentified candidate genes. Resequencing and fine mapping of candidate genes are necessary to identify putative functional variants and some of these have been incorporated into new genotyping arrays. Sequence imputation and genotype by sequence are newer strategies that could reveal novel functional mutations. In this study, these approaches are discussed. Advantages and limitations are highlighted where additional research is needed.

Multi-breed genomic predictions and functional variants for fertility of tropical bulls

Worldwide, most beef breeding herds are naturally mated. As such, the ability to identify and select fertile bulls is critically important for both productivity and genetic improvement. Here, we collected ten fertility-related phenotypes for 6,063 bulls from six tropically adapted breeds. Phenotypes were comprised of four bull conformation traits and six traits directly related to the quality of the bull's semen. We also generated high-density DNA genotypes for all the animals. In total, 680,758 single nucleotide polymorphism (SNP) genotypes were analyzed. The genomic correlation of the same trait observed in different breeds was positive for scrotal circumference and sheath score on most breed comparisons, but close to zero for the percentage of normal sperm, suggesting a divergent genetic background for this trait. We confirmed the importance of a breed being present in the reference population to the generation of accurate genomic estimated breeding values (GEBV) in an across-breed validation scenario. Average GEBV accuracies varied from 0.19 to 0.44 when the breed was not included in the reference population. The range improved to 0.28 to 0.59 when the breed was in the reference population. Variants associated with the gene HDAC4, six genes from the spermatogenesis-associated (SPATA) family of proteins, and 29 transcription factors were identified as candidate genes. Collectively these results enable very early in-life selection for bull fertility traits, supporting genetic improvement strategies currently taking place within tropical beef production systems. This study also improves our understanding of the molecular basis of male fertility in mammals.

Genome and chromosome wide association studies for growth traits in Simmental and Simbrah cattle

OBJECTIVE

The objective of this study was to perform genome (genome wide association studies [GWAS]) and chromosome (CWAS) wide association analyses to identify single nucleotide polymorphisms (SNPs) associated with growth traits in registered Simmental and Simbrah cattle.

METHODS

The phenotypes were deregressed BLUP EBVs for birth weight, weaning weight direct, weaning weight maternal, and yearling weight. The genotyping was performed with the GGP Bovine 150k chip. After the quality control analysis, 105,129 autosomal SNP from 967 animals (473 Simmental and 494 Simbrah) were used to carry out genotype association tests. The two association analyses were performed per breed and using combined information of the two breeds. The SNP associated with growth traits were mapped to their corresponding genes at 100 kb on either side.

RESULTS

A difference in magnitude of posterior probabilities was found across breeds between genome and chromosome wide association analyses. A total of 110, 143, and 302 SNP were associated with GWAS and CWAS for growth traits in the Simmental-, Simbrah-and joint -data analyses, respectively. It stands out from the enrichment analysis of the pathways for RNA polymerase (POLR2G, POLR3E) and GABAergic synapse (GABRR1, GABRR3) for Simmental cattle and p53 signaling pathway (BID, SERPINB5) for Simbrah cattle.

CONCLUSION

Only 6,265% of the markers associated with growth traits were found using CWAS and GWAS. The associated markers using the CWAS analysis, which were not associated using the GWAS, represents information that due to the model and priors was not associated with the traits.

Correlation scan: identifying genomic regions that affect genetic correlations applied to fertility traits

Although the genetic correlations between complex traits have been estimated for more than a century, only recently we have started to map and understand the precise localization of the genomic region(s) that underpin these correlations. Reproductive traits are often genetically correlated. Yet, we don't fully understand the complexities, synergism, or trade-offs between male and female fertility. In this study, we used reproductive traits in two cattle populations (Brahman; BB, Tropical Composite; TC) to develop a novel framework termed correlation scan (CS). This framework was used to identify local regions associated with the genetic correlations between male and female fertility traits. Animals were genotyped with bovine high-density single nucleotide polymorphisms (SNPs) chip assay. The data used consisted of ~1000 individual records measured through frequent ovarian scanning for age at first corpus luteum (AGECL) and a laboratory assay for serum levels of insulin growth hormone (IGF1 measured in bulls, IGF1b, or cows, IGF1c). The methodology developed herein used correlations of 500-SNP effects in a 100-SNPs sliding window in each chromosome to identify local genomic regions that either drive or antagonize the genetic correlations between traits. We used Fisher's Z-statistics through a permutation method to confirm which regions of the genome harboured significant correlations. About 30% of the total genomic regions were identified as driving and antagonizing genetic correlations between male and female fertility traits in the two populations. These regions confirmed the polygenic nature of the traits being studied and pointed to genes of interest. For BB, the most important chromosome in terms of local regions is often located on bovine chromosome (BTA) 14. However, the important regions are spread across few different BTA's in TC. Quantitative trait loci (QTLs) and functional enrichment analysis revealed many significant windows co-localized with known QTLs related to milk production and fertility traits, especially puberty. In general, the enriched reproductive QTLs driving the genetic correlations between male and female fertility are the same for both cattle populations, while the antagonizing regions were population specific. Moreover, most of the antagonizing regions were mapped to chromosome X. These results suggest regions of chromosome X for further investigation into the trade-offs between male and female fertility. We compared the CS with two other recently proposed methods that map local genomic correlations. Some genomic regions were significant across methods. Yet, many significant regions identified with the CS were overlooked by other methods.

Network analysis reveals different hub genes and molecular pathways for pig in vitro fertilized early embryos and parthenogenotes

Maternal-to-zygotic transition (MZT) occurs when maternal transcripts decay and zygotic genome is activated gradually at early stage of embryo development. Previously, single cell RNA-seq (scRNA-seq) has helped us to uncover the MZT-associated mRNA dynamics of in vitro produced pig early embryos. Here, to further investigate functional modules and hub genes associated with MZT process, the weighted gene-coexpression network analysis (WGCNA) was performed on our previously generated 45 scRNA-seq datasets. For the in vitro fertilized embryo (IVF) group, 5 significant modules were identified (midnightblue/black/red and blue/brown modules, positively correlated with 1-cell (IVF1) and 8-cell (IVF8), respectively), containing genes mainly enriched in signaling pathways such as Wnt, regulation of RNA transcription, fatty acid metabolic process, poly(A) RNA binding and lysosome. For the parthenogenetically activated embryo (PA) group, 9 significant modules were identified (black/purple/red, brown/turquoise/yellow, and magenta/blue/green modules, positively correlated with MII oocytes, 1-cell (PA1), and 8-cell (PA8), respectively), mainly enriched in extracellular exosome, poly(A) RNA binding, mitochondrion, transcription factor activity. Moreover, some of identified hub genes within 3 IVF and 9 PA significant modules, including ADCY2, DHX34, KDM4A, GDF10, ABCC10, PAFAH2, HEXIM2, COQ9, DCAF11, SGK1, ESRRB etc., have been reported to play vital roles in different biological processes. Our findings provide information and resources for subsequent in-depth study on the regulation and function of MZT in pig embryos.

Genetic variation in PLAG1 is associated with early fertility in Australian Brahman cattle

Variation in the genome region coding for PLAG1 has well-documented associations with skeletal growth and age at puberty in cattle. However, the influence of PLAG1 on other economically important traits such as cow stayability has not yet been explored. Here we investigate the effect of PLAG1 variation on early and later in life female fertility, as well as size and growth, in a well phenotyped Australian Brahman herd. Yearly pregnancy and productivity records were collected from 2,839 genotyped Brahman cows and used to generate fertility, growth, and weight phenotypes. A variant on chromosome 14 in PLAG1 (NC_037341.1:g.23338890G>T, rs109815800) was previously determined to be a putative causative mutation associated with variation in cattle stature. The imputed PLAG1 genotype at this variant was isolated for each animal and the effect of PLAG1 genotype on each trait was estimated using linear modelling. Regardless of how heifer fertility was measured, there was a significant (P < 0.05) and desirable relationship between the additive effects of PLAG1 genotype and successful heifer fertility. Heifers with two copies of the alternate allele (TT) conceived earlier and had higher pregnancy and calving rates. However, the effects of PLAG1 genotype on fertility began to diminish as cows aged and did not significantly influence stayability at later ages. While there was no effect of genotype on growth, PLAG1 had a negative effect on mature cow weight (P < 0.01), where females with two copies of the alternate allele (TT) were significantly smaller than those with either one or none. Selection emphasis on improved Brahman heifer fertility will likely increase the frequency of the T allele of rs109815800, which may also increase herd profitability and long-term sustainability through improved reproductive efficiency and reduced mature cow size.

Sustainable Intensification of Beef Production in the Tropics: The Role of Genetically Improving Sexual Precocity of Heifers

Simple Summary

Tropical pasture-based beef production systems play a vital role in global food security. The importance of promoting sustainable intensification of such systems has been debated worldwide. Demand for beef is growing together with concerns over the impact of its production on the environment. Implementing sustainable livestock intensification programs relies on animal genetic improvement. In tropical areas, the lack of sexual precocity is a bottleneck for cattle efficiency, directly impacting the sustainability of production systems. In the present review we present and discuss the state of the art of genetic evaluation for sexual precocity in Bos indicus beef cattle, covering the definition of measurable traits, genetic parameter estimates, genomic analyses, and a case study of selection for sexual precocity in Nellore breeding programs.

Abstract

Increasing productivity through continued animal genetic improvement is a crucial part of implementing sustainable livestock intensification programs. In Zebu cattle, the lack of sexual precocity is one of the main obstacles to improving beef production efficiency. Puberty-related traits are complex, but large-scale data sets from different “omics” have provided information on specific genes and biological processes with major effects on the expression of such traits, which can greatly increase animal genetic evaluation. In addition, genetic parameter estimates and genomic predictions involving sexual precocity indicator traits and productive, reproductive, and feed-efficiency related traits highlighted the feasibility and importance of direct selection for anticipating heifer reproductive life. Indeed, the case study of selection for sexual precocity in Nellore breeding programs presented here show that, in 12 years of selection for female early precocity and improved management practices, the phenotypic means of age at first calving showed a strong decreasing trend, changing from nearly 34 to less than 28 months, with a genetic trend of almost −2 days/year. In this period, the percentage of early pregnancy in the herds changed from around 10% to more than 60%, showing that the genetic improvement of heifer’s sexual precocity allows optimizing the productive cycle by reducing the number of unproductive animals in the herd. It has a direct impact on sustainability by better use of resources. Genomic selection breeding programs accounting for genotype by environment interaction represent promising tools for accelerating genetic progress for sexual precocity in tropical beef cattle.

A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs

In recent years, the increase in awareness of antimicrobial resistance together with the societal demand of healthier meat products have driven attention to health-related traits in livestock production. Previous studies have reported medium to high heritabilities for these traits and described genomic regions associated with them. Despite its genetic component, health- and immunity-related traits are complex and its study by association analysis with genomic markers may be missing some information. To analyse multiple phenotypes and gene-by-gene interactions, systems biology approaches, such as the association weight matrix (AWM), allows combining genome wide association study results with network inference algorithms. The present study aimed to identify gene networks, key regulators and candidate genes associated to immunocompetence in pigs by integrating multiple health-related traits, enriched for innate immune phenotypes, using the AWM approach. The co-association network analysis unveiled a network comprised of 3,636 nodes (genes) and 451,407 edges (interactions), including a total of 246 regulators. From these, five genes (ARNT2, BRMS1L, MED12L, SUPT3H and TRIM25) were selected as key regulators as they were associated with the maximum number of genes with the minimum overlapping (1,827 genes in total). The five regulators were involved in pathways related to immunity such as lymphocyte differentiation and activation, platelet activation and degranulation, megakaryocyte differentiation, FcγR-mediated phagocytosis and response to nitric oxide, among others, but also in immunometabolism. Furthermore, we identified genes co-associated with the key regulators previously reported as candidate genes (e.g., ANGPT1, CD4, CD36, DOCK1, PDE4B, PRKCE, PTPRC and SH2B3) for immunity traits in humans and pigs, but also new candidate ones (e.g., ACSL3, CXADR, HBB, MMP12, PTPN6, WLS) that were not previously described. The co-association analysis revealed new regulators associated with health-related traits in pigs. This approach also identified gene-by-gene interactions and candidate genes involved in pathways related to cell fate and metabolic and immune functions. Our results shed new light in the regulatory mechanisms involved in pig immunity and reinforce the use of the pig as biomedical model.

A gene co-association network regulating gut microbial communities in a Duroc pig population

BACKGROUND

Analyses of gut microbiome composition in livestock species have shown its potential to contribute to the regulation of complex phenotypes. However, little is known about the host genetic control over the gut microbial communities. In pigs, previous studies are based on classical "single-gene-single-trait" approaches and have evaluated the role of host genome controlling gut prokaryote and eukaryote communities separately.

RESULTS

In order to determine the ability of the host genome to control the diversity and composition of microbial communities in healthy pigs, we undertook genome-wide association studies (GWAS) for 39 microbial phenotypes that included 2 diversity indexes, and the relative abundance of 31 bacterial and six commensal protist genera in 390 pigs genotyped for 70 K SNPs. The GWAS results were processed through a 3-step analytical pipeline comprised of (1) association weight matrix; (2) regulatory impact factor; and (3) partial correlation and information theory. The inferred gene regulatory network comprised 3561 genes (within a 5 kb distance from a relevant SNP-P < 0.05) and 738,913 connections (SNP-to-SNP co-associations). Our findings highlight the complexity and polygenic nature of the pig gut microbial ecosystem. Prominent within the network were 5 regulators, PRDM15, STAT1, ssc-mir-371, SOX9 and RUNX2 which gathered 942, 607, 588, 284 and 273 connections, respectively. PRDM15 modulates the transcription of upstream regulators of WNT and MAPK-ERK signaling to safeguard naive pluripotency and regulates the production of Th1- and Th2-type immune response. The signal transducer STAT1 has long been associated with immune processes and was recently identified as a potential regulator of vaccine response to porcine reproductive and respiratory syndrome. The list of regulators was enriched for immune-related pathways, and the list of predicted targets includes candidate genes previously reported as associated with microbiota profile in pigs, mice and human, such as SLIT3, SLC39A8, NOS1, IL1R2, DAB1, TOX3, SPP1, THSD7B, ELF2, PIANP, A2ML1, and IFNAR1. Moreover, we show the existence of host-genetic variants jointly associated with the relative abundance of butyrate producer bacteria and host performance.

CONCLUSIONS

Taken together, our results identified regulators, candidate genes, and mechanisms linked with microbiome modulation by the host. They further highlight the value of the proposed analytical pipeline to exploit pleiotropy and the crosstalk between bacteria and protists as significant contributors to host-microbiome interactions and identify genetic markers and candidate genes that can be incorporated in breeding program to improve host-performance and microbial traits. Video Abstract.

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.

Analysis of single nucleotide polymorphisms related to heifer fertility in Hanwoo (Korean cattle)

Genome-wide association studies (GWAS) have accelerated the identification of functional trait loci in cattle and identified single nucleotide polymorphisms (SNPs) in candidate genes associated with fertility and production traits in high milk yield dairy cattle. The fertility of Hanwoo (Korean native beef cattle) has declined after the adaptation of a selection program for high quantity and quality meat. However, there are few GWAS studies of fertility in beef cattle. We performed a genome-wide association study of 40 Korean native beef cattle heifers with imputed 770 K genotype and identified 12 significant SNPs within seven regions on three chromosomes (BTA 8, BTA 16 and BTA 24) associated with services per conception (SPC). Five SNPs were located in the ABCA1, BRINP3 and ESRRG genes, which are involved in early embryo development. In addition, 27 proximal genes were identified within 1 Mb of the candidate SNPs, which are involved in muscle cell differentiation and muscle structure development. However, we did not find any previously reported SNPs related to fertility in Holstein cows. Taken together, we identified SNPs associated with SPC and their proximal genes using gene-based analysis and the candidates were different from SNPs associated with subfertility of dairy cattle.

Gene networks for three feed efficiency criteria reveal shared and specific biological processes

Background

French beef producers suffer from the decrease in profitability of their farms mainly because of the continuous increase in feed costs. Selection for feed efficiency in beef cattle represents a relevant solution to face this problem. However, feed efficiency is a complex trait that can be assessed by three major criteria: residual feed intake (RFI), residual gain (RG) and feed efficiency ratio (FE), which involve different genetic determinisms. An analysis that combines phenotype and whole-genome sequence data provides a unique framework for genomic studies. The aim of our study was to identify the gene networks and the biological processes that are responsible for the genetic determinism that is shared between these three feed efficiency criteria.

Results

A population of 1477 French Charolais young bulls was phenotyped for feed intake (FI), average daily gain (ADG) and final weight (FW) to estimate RFI, RG and FE. A subset of 789 young bulls was genotyped on the BovineSNP50 single nucleotide polymorphism (SNP) array and imputed at the sequence level using RUN6 of the 1000 Bull Genomes Project. We conducted a genome-wide association study (GWAS) to estimate the individual effect of 8.5 million SNPs and applied an association weight matrix (AWM) approach to analyse the results, one for each feed efficiency criterion. The results highlighted co-association networks including 626 genes for RFI, 426 for RG and 564 for FE. Enrichment assessment revealed the biological processes that show the strongest association with RFI, RG and FE, i.e. digestive tract (salivary, gastric and mucin secretion) and metabolic processes (cellular and cardiovascular). Energetic functions were more associated with RFI and FE and cardio-vascular and cellular processes with RG. Several hormones such as apelin, glucagon, insulin, aldosterone, the gonadotrophin releasing hormone and the thyroid hormone were also identified, and these should be tested in future studies as candidate biomarkers for feed efficiency.

Conclusions

The combination of network and pathway analyses at the sequence level led to the identification of both common and specific mechanisms that are involved in RFI, RG and FE, and to a better understanding of the genetic determinism underlying these three criteria. The effects of the genes involved in each of the identified processes need to be tested in genomic evaluations to confirm the potential gain in reliability of using functional variants to select animals for feed efficiency.

Physiological and genomic insight into neuroendocrine regulation of puberty in gilts

The timing of pubertal attainment in gilts is a critical factor for pork production and is an early indicator of future reproductive potential. Puberty, defined as age at first standing estrus in the presence of a boar, is brought about by an escape from estrogen inhibition of the GnRH pulse generator, which allows for increasing LH pulses leading to the onset of cyclicity. The biological mechanisms that control the timing of these events is related to decreasing inhibitory signals with a concomitant increase in stimulatory signals within the hypothalamus. The roles of gamma-aminobutyric acid, endogenous opioid peptides, and gonadotropin-inhibitory hormone in negatively regulating gonadotropin secretion in gilts is explored. Developmental changes in stimulatory mechanisms of glutamatergic and kisspeptin neurons are important for increased LH pulsatility required for the occurrence of puberty in pigs. Age at first estrus of gilts is metabolically gated, and numerous metabolites, metabolic hormones, and appetite-regulating neurotransmitters have been implicated in the nutritional regulation of gonadotropin secretion. Leptin is an important metabolic signal linking body energy reserves with age at puberty in gilts. Leptin acting through neuropeptide Y and proopiomelanocortin neurons in the hypothalamus has important impacts on the function of the reproductive neurosecretory axis of gilts. Age at puberty in swine is heritable, and genomic analyses reveal it to be a polygenic trait. Genome-wide association studies for pubertal age in gilts have revealed several genomic regions in common with those identified for age at menarche in humans. Candidate genes have been identified that have important functions in growth and adiposity. Numerous genes regulating hypothalamic neuronal function, gonadotropes in the adenohypophysis, and ovarian follicular development have been identified and illustrate the complex maturational changes occurring in the hypothalamic-pituitary-ovarian axis during puberty in gilts.

Identification and Functional Annotation of Genes Related to Horses' Performance: From GWAS to Post-GWAS

Simple Summary

It is assumed that the athletic performance of horses is influenced by a large number of genes; however, to date, not many genomic studies have been performed to identify candidate genes. In this study we performed a systematic review of genome-wide association studies followed by functional analyses aiming to identify the most candidate genes for horse performance. We were successful in identifying 669 candidate genes, from which we built biological process networks. Regulatory elements (transcription factors, TFs) of these genes were identified and used to build a gene–TF network. Genes and TFs presented in this study are suggested to play a role in the studied traits through biological processes related with exercise performance, for example, positive regulation of glucose metabolism, regulation of vascular endothelial growth factor production, skeletal system development, cellular response to fatty acids and cellular response to lipids. In general, this study may provide insights into the genetic architecture underlying horse performance in different breeds around the world.

Abstract

Integration of genomic data with gene network analysis can be a relevant strategy for unraveling genetic mechanisms. It can be used to explore shared biological processes between genes, as well as highlighting transcription factors (TFs) related to phenotypes of interest. Unlike other species, gene–TF network analyses have not yet been well applied to horse traits. We aimed to (1) identify candidate genes associated with horse performance via systematic review, and (2) build biological processes and gene–TF networks from the identified genes aiming to highlight the most candidate genes for horse performance. Our systematic review considered peer-reviewed articles using 20 combinations of keywords. Nine articles were selected and placed into groups for functional analysis via gene networks. A total of 669 candidate genes were identified. From that, gene networks of biological processes from each group were constructed, highlighting processes associated with horse performance (e.g., regulation of systemic arterial blood pressure by vasopressin and regulation of actin polymerization and depolymerization). Transcription factors associated with candidate genes were also identified. Based on their biological processes and evidence from the literature, we identified the main TFs related to horse performance traits, which allowed us to construct a gene–TF network highlighting TFs and the most candidate genes for horse performance.

Common Gene Modules Identified for Chicken Adiposity by Network Construction and Comparison

Excessive fat deposition can cause chicken health problem, and affect production efficiency by causing great economic losses to the industry. However, the molecular underpinnings of the complex adiposity trait remain elusive. In the current study, we constructed and compared the gene co-expression networks on four transcriptome profiling datasets, from two chicken lines under divergent selection for abdominal fat contents, in an attempt to dissect network compositions underlying adipose tissue growth and development. After functional enrichment analysis, nine network modules important to adipogenesis were discovered to be involved in lipid metabolism, PPAR and insulin signaling pathways, and contained hub genes related to adipogenesis, cell cycle, inflammation, and protein synthesis. Moreover, after additional functional annotation and network module comparisons, common sub-modules of similar functionality for chicken fat deposition were identified for different chicken lines, apart from modules specific to each chicken line. We further validated the lysosome pathway, and found TFEB and its downstream target genes showed similar expression patterns along with chicken preadipocyte differentiation. Our findings could provide novel insights into the genetic basis of complex adiposity traits, as well as human obesity and related metabolic diseases.

Dynamics of genomic architecture during composite breed development in cattle

Some livestock breeds face the challenge of reduced genetic variation, increased inbreeding depression owing to genetic drift and selection. Hybridization can reverse these processes and increase levels of productivity and adaptation to various environmental stressors. Samples from American Brangus were used to evaluate the indicine/taurine composition through nine generations (~45 years) after the hybridization process was completed. The purpose was to determine how hybridization alters allelic combinations of a breed over time when genetic factors such as selection and drift are operating. Furthermore, we explored genomic regions with deviations from the expected composition from the progenitor breeds and related these regions to traits under selection. The Brangus composition deviated from the theoretical expectation, defined by the breed association, of 62.5% taurine, showing taurine composition to be 70.4 ± 0.6%. Taurine and indicine proportion were not consistent across chromosomes. Furthermore, these non‐uniform areas were found to be associated with traits that were probably under selection such as intermuscular fat and average daily gain. Interestingly, the sex chromosomes were predominantly taurine, which could be due to the composite being formed particularly in the final cross that resulted in progeny designated as purebred Brangus. This work demonstrated the process of new breed formation on a genomic level. It suggests that factors like genetic drift, selection and complementarity shift the genetic architecture into a uniquely different population. These findings are important to better understand how hybridization and crossbreeding systems shape the genetic architecture of composite populations.

Genome-wide scans identify known and novel regions associated with prolificacy and reproduction traits in a sub-Saharan African indigenous sheep (Ovis aries)

Maximizing the number of offspring born per female is a key functionality trait in commercial- and/or subsistence-oriented livestock enterprises. Although the number of offspring born is closely associated with female fertility and reproductive success, the genetic control of these traits remains poorly understood in sub-Saharan Africa livestock. Using selection signature analysis performed on Ovine HD BeadChip data from the prolific Bonga sheep in Ethiopia, 41 candidate regions under selection were identified. The analysis revealed one strong selection signature on a candidate region on chromosome X spanning BMP15, suggesting this to be the primary candidate prolificacy gene in the breed. The analysis also identified several candidate regions spanning genes not reported before in prolific sheep but underlying fertility and reproduction in other species. The genes associated with female reproduction traits included SPOCK1 (age at first oestrus), GPR173 (mediator of ovarian cyclicity), HB-EGF (signalling early pregnancy success) and SMARCAL1 and HMGN3a (regulate gene expression during embryogenesis). The genes involved in male reproduction were FOXJ1 (sperm function and successful fertilization) and NME5 (spermatogenesis). We also observed genes such as PKD2L2, MAGED1 and KDM3B, which have been associated with diverse fertility traits in both sexes of other species. The results confirm the complexity of the genetic mechanisms underlying reproduction while suggesting that prolificacy in the Bonga sheep, and possibly African indigenous sheep is partly under the control of BMP15 while other genes that enhance male and female fertility are essential for reproductive fitness.

Cross talk between mineral metabolism and meat quality: a systems biology overview

Meat quality has an inherent complexity because of the multiple interrelated causative factors and layers of feedback regulation. Understanding the key factors and their interactions has been challenging, despite the availability of remarkable high-throughput tools and techniques that have provided insights on muscle metabolism and the genetic basis of meat quality. Likewise, we have deepened our knowledge about mineral metabolism and its role in cell functioning. Regardless of these facts, complex traits like mineral content and meat quality have been studied under reductionist approaches. However, as these phenotypes arise from complex interactions among different biological layers (genome, transcriptome, proteome, epigenome, etc.), along with environmental effects, a holistic view and systemic-level understanding of the genetic basis of complex phenotypes are in demand. Based on the state of the art, we addressed some of the questions regarding the interdependence of meat quality traits and mineral content. Furthermore, we sought to highlight potential regulatory mechanisms arising from the genes, miRNAs, and mineral interactions, as well as the pathways modulated by this interplay affecting muscle, mineral metabolism, and meat quality. By answering these questions, we did not intend to give an exhaustive review but to identify the key biological points, the challenges, and benefits of integrative genomic approaches.

Integrating genome-wide co-association and gene expression to identify putative regulators and predictors of feed efficiency in pigs

BACKGROUND

Feed efficiency (FE) has a major impact on the economic sustainability of pig production. We used a systems-based approach that integrates single nucleotide polymorphism (SNP) co-association and gene-expression data to identify candidate genes, biological pathways, and potential predictors of FE in a Duroc pig population.

RESULTS

We applied an association weight matrix (AWM) approach to analyse the results from genome-wide association studies (GWAS) for nine FE associated and production traits using 31K SNPs by defining residual feed intake (RFI) as the target phenotype. The resulting co-association network was formed by 829 SNPs. Additive effects of this SNP panel explained 61% of the phenotypic variance of RFI, and the resulting phenotype prediction accuracy estimated by cross-validation was 0.65 (vs. 0.20 using pedigree-based best linear unbiased prediction and 0.12 using the 31K SNPs). Sixty-eight transcription factor (TF) genes were identified in the co-association network; based on the lossless approach, the putative main regulators were COPS5, GTF2H5, RUNX1, HDAC4, ESR1, USP16, SMARCA2 and GTF2F2. Furthermore, gene expression data of the gluteus medius muscle was explored through differential expression and multivariate analyses. A list of candidate genes showing functional and/or structural associations with FE was elaborated based on results from both AWM and gene expression analyses, and included the aforementioned TF genes and other ones that have key roles in metabolism, e.g. ESRRG, RXRG, PPARGC1A, TCF7L2, LHX4, MAML2, NFATC3, NFKBIZ, TCEA1, CDCA7L, LZTFL1 or CBFB. The most enriched biological pathways in this list were associated with behaviour, immunity, nervous system, and neurotransmitters, including melatonin, glutamate receptor, and gustation pathways. Finally, an expression GWAS allowed identifying 269 SNPs associated with the candidate genes' expression (eSNPs). Addition of these eSNPs to the AWM panel of 829 SNPs did not improve the accuracy of genomic predictions.

CONCLUSIONS

Candidate genes that have a direct or indirect effect on FE-related traits belong to various biological processes that are mainly related to immunity, behaviour, energy metabolism, and the nervous system. The pituitary gland, hypothalamus and thyroid axis, and estrogen signalling play fundamental roles in the regulation of FE in pigs. The 829 selected SNPs explained 61% of the phenotypic variance of RFI, which constitutes a promising perspective for applying genetic selection on FE relying on molecular-based prediction.

Sequence-based GWAS, network and pathway analyses reveal genes co-associated with milk cheese-making properties and milk composition in Montbéliarde cows

BACKGROUND

Milk quality in dairy cattle is routinely assessed via analysis of mid-infrared (MIR) spectra; this approach can also be used to predict the milk's cheese-making properties (CMP) and composition. When this method of high-throughput phenotyping is combined with efficient imputations of whole-genome sequence data from cows' genotyping data, it provides a unique and powerful framework with which to carry out genomic analyses. The goal of this study was to use this approach to identify genes and gene networks associated with milk CMP and composition in the Montbéliarde breed.

RESULTS

Milk cheese yields, coagulation traits, milk pH and contents of proteins, fatty acids, minerals, citrate, and lactose were predicted from MIR spectra. Thirty-six phenotypes from primiparous Montbéliarde cows (1,442,371 test-day records from 189,817 cows) were adjusted for non-genetic effects and averaged per cow. 50 K genotypes, which were available for a subset of 19,586 cows, were imputed at the sequence level using Run6 of the 1000 Bull Genomes Project (comprising 2333 animals). The individual effects of 8.5 million variants were evaluated in a genome-wide association study (GWAS) which led to the detection of 59 QTL regions, most of which had highly significant effects on CMP and milk composition. The results of the GWAS were further subjected to an association weight matrix and the partial correlation and information theory approach and we identified a set of 736 co-associated genes. Among these, the well-known caseins, PAEP and DGAT1, together with dozens of other genes such as SLC37A1, ALPL, MGST1, SEL1L3, GPT, BRI3BP, SCD, GPAT4, FASN, and ANKH, explained from 12 to 30% of the phenotypic variance of CMP traits. We were further able to identify metabolic pathways (e.g., phosphate and phospholipid metabolism and inorganic anion transport) and key regulator genes, such as PPARA, ASXL3, and bta-mir-200c that are functionally linked to milk composition.

CONCLUSIONS

By using an approach that integrated GWAS with network and pathway analyses at the whole-genome sequence level, we propose candidate variants that explain a substantial proportion of the phenotypic variance of CMP traits and could thus be included in genomic evaluation models to improve milk CMP in Montbéliarde cows.

Genome-wide association study reveals candidate genes associated with body measurement traits in Chinese Wagyu beef cattle

We performed a genome-wide association study to identify candidate genes for body measurement traits in 463 Wagyu beef cattle typed with the Illumina Bovine HD 770K SNP array. At the genome-wide level, we detected 18, five and one SNPs associated with hip height, body height and body length respectively. In total, these SNPs are within or near 11 genes, six of which (PENK, XKR4, IMPAD1, PLAG1, CCND2 and SNTG1) have been reported previously and five of which (CSMD3, LAP3, SYN3, FAM19A5 and TIMP3) are novel candidate genes that we found to be associated with body measurement traits. Further exploration of these candidate genes will facilitate genetic improvement in Chinese Wagyu beef cattle.

Selection signatures in candidate genes and QTL for reproductive traits in Nellore heifers

The identification of selection signature genes may help to detect genomic regions that underwent artificial selection and contributed to phenotypic diversity. The aim of this study, therefore, was to detect selection signatures in candidate genes and quantitative trait locus (QTL) for reproductive traits in a Nellore population being selected for sexual precocity. A total of 2035 Nellore heifers, sourced from breeding programs focused on sexual precocity, were used. Candidate genes and some specific QTL related to reproductive traits were chosen based on published literature and Animal QTL databases, respectively, for investigation whether these regions were affected by selection. Selection signature DNA sequences were detected in the selected regions using the extended haplotype homozygosity (EHH) and relative extended haplotype homozygosity (REHH) methods. From 22,241 single nucleotide polymorphisms (SNPs) located in the candidate genes and QTL, 17,312 SNPs generated 2756 haplotype blocks. A total of 7518 EHH tests were analyzed using haplotypes with a frequency of more than 25%, for which there were 39 tests that were significant for REHH (P<0.01). Selection signature DNA sequences were detected that contained several QTLs for important reproductive traits in cattle, suggesting that reproductive traits may have been affected by selection for sexual precocity in this population. Forty-six genes were located in the selection signature regions, whereas 24 genes participated in important biological processes or pathways that may underlie sexual precocity. These results indicate there are possible molecular mechanisms related to sexual precocity in the Nellore breed.

Bayes Factor-Based Regulatory Gene Network Analysis of Genome-Wide Association Study of Economic Traits in a Purebred Swine Population

Early stage prediction of economic trait performance is important and directly linked to profitability of farm pig production. Genome-wide association study (GWAS) has been applied to find causative genomic regions of traits. This study established a regulatory gene network using GWAS for critical economic pig characteristics, centered on easily measurable body fat thickness in live animals. We genotyped 2,681 pigs using Illumina Porcine SNP60, followed by GWAS to calculate Bayes factors for 47,697 single nucleotide polymorphisms (SNPs) of seven traits. Using this information, SNPs were annotated with specific genes near genome locations to establish the association weight matrix. The entire network consisted of 226 nodes and 6,921 significant edges. For in silico validation of their interactions, we conducted regulatory sequence analysis of predicted target genes of transcription factors (TFs). Three key regulatory TFs were identified to guarantee maximum coverage: AT-rich interaction domain 3B (ARID3B), glial cell missing homolog 1 (GCM1), and GLI family zinc finger 2 (GLI2). We identified numerous genes targeted by ARID3B, associated with cellular processes. GCM1 and GLI2 were involved in developmental processes, and their shared target genes regulated multicellular organismal process. This system biology-based function analysis might contribute to enhancing understanding of economic pig traits.

An intersection network based on combining SNP coassociation and RNA coexpression networks for feed utilization traits in Japanese Black cattle

Genome-wide association studies (GWAS) of quantitative traits have detected numerous genetic associations, but they encounter difficulties in pinpointing prominent candidate genes and inferring gene networks. The present study used a systems genetics approach integrating GWAS results with external RNA-expression data to detect candidate gene networks in feed utilization and growth traits of Japanese Black cattle, which are matters of concern. A SNP coassociation network was derived from significant correlations between SNPs with effects estimated by GWAS across 7 phenotypic traits. The resulting network genes contained significant numbers of annotations related to the traits. Using bovine transcriptome data from a public database, an RNA coexpression network was inferred based on the similarity of expression patterns across different tissues. An intersection network was then generated by superimposing the SNP and RNA networks and extracting shared interactions. This intersection network contained 4 tissue-specific modules: nervous system, reproductive system, muscular system, and glands. To characterize the structure (topographical properties) of the 3 networks, their scale-free properties were evaluated, which revealed that the intersection network was the most scale-free. In the subnetwork containing the most connected transcription factors (URI1, ROCK2, and ETV6), most genes were widely expressed across tissues, and genes previously shown to be involved in the traits were found. Results indicated that the current approach might be used to construct a gene network that better reflects biological information, providing encouragement for the genetic dissection of economically important quantitative traits.

Combining multi-OMICs information to identify key-regulator genes for pleiotropic effect on fertility and production traits in beef cattle

The identification of biological processes related to the regulation of complex traits is a difficult task. Commonly, complex traits are regulated through a multitude of genes contributing each to a small part of the total genetic variance. Additionally, some loci can simultaneously regulate several complex traits, a phenomenon defined as pleiotropy. The lack of understanding on the biological processes responsible for the regulation of these traits results in the decrease of selection efficiency and the selection of undesirable hitchhiking effects. The identification of pleiotropic key-regulator genes can assist in developing important tools for investigating biological processes underlying complex traits. A multi-breed and multi-OMICs approach was applied to study the pleiotropic effects of key-regulator genes using three independent beef cattle populations evaluated for fertility traits. A pleiotropic map for 32 traits related to growth, feed efficiency, carcass and meat quality, and reproduction was used to identify genes shared among the different populations and breeds in pleiotropic regions. Furthermore, data-mining analyses were performed using the Cattle QTL database (CattleQTLdb) to identify the QTL category annotated in the regions around the genes shared among breeds. This approach allowed the identification of a main gene network (composed of 38 genes) shared among breeds. This gene network was significantly associated with thyroid activity, among other biological processes, and displayed a high regulatory potential. In addition, it was possible to identify genes with pleiotropic effects related to crucial biological processes that regulate economically relevant traits associated with fertility, production and health, such as MYC, PPARG, GSK3B, TG and IYD genes. These genes will be further investigated to better understand the biological processes involved in the expression of complex traits and assist in the identification of functional variants associated with undesirable phenotypes, such as decreased fertility, poor feed efficiency and negative energetic balance.

A comprehensive manually-curated compendium of bovine transcription factors

Transcription factors (TFs) are pivotal regulatory proteins that control gene expression in a context-dependent and tissue-specific manner. In contrast to human, where comprehensive curated TF collections exist, bovine TFs are only rudimentary recorded and characterized. In this article, we present a manually-curated compendium of 865 sequence-specific DNA-binding bovines TFs, which we analyzed for domain family distribution, evolutionary conservation, and tissue-specific expression. In addition, we provide a list of putative transcription cofactors derived from known interactions with the identified TFs. Since there is a general lack of knowledge concerning the regulation of gene expression in cattle, the curated list of TF should provide a basis for an improved comprehension of regulatory mechanisms that are specific to the species.

Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle

Background

Improving resistance to mastitis, one of the costliest diseases in dairy production, has become an important objective in dairy cattle breeding. However, mastitis resistance is influenced by many genes involved in multiple processes, including the response to infection, inflammation, and post-infection healing. Low genetic heritability, environmental variations, and farm management differences further complicate the identification of links between genetic variants and mastitis resistance. Consequently, studies of the genetics of variation in mastitis resistance in dairy cattle lack agreement about the responsible genes.

Results

We associated 15,552,968 imputed whole-genome sequencing markers for 5147 Nordic Holstein cattle with mastitis resistance in a genome-wide association study (GWAS). Next, we augmented P-values for markers in genes in the associated regions using Gene Ontology terms, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and mammalian phenotype database. To confirm results of gene-based analyses, we used gene expression data from E. coli-challenged cow udders. We identified 22 independent quantitative trait loci (QTL) that collectively explained 14% of the variance in breeding values for resistance to clinical mastitis (CM). Using association test statistics with multiple pieces of independent information on gene function and differential expression during bacterial infection, we suggested putative causal genes with biological relevance for 12 QTL affecting resistance to CM in dairy cattle.

Conclusion

Combining information on the nearest positional genes, gene-based analyses, and differential gene expression data from RNA-seq, we identified putative causal genes (candidate genes with biological evidence) in QTL for mastitis resistance in Nordic Holstein cattle. The same strategy can be applied for other traits.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5050-x) contains supplementary material, which is available to authorized users.

Genome-wide association study using haplotype alleles for the evaluation of reproductive traits in Nelore cattle

Zebu cattle (Bos taurus indicus) are highly adapted to tropical regions. However, females reach puberty after taurine heifers, which affects the economic efficiency of beef cattle breeding in the tropical regions. The aims of this study were to establish associations between the haplotype alleles of the bovine genome and age at first calving (AFC) in the Nelore cattle, and to identify the genes and quantitative trait loci (QTL) related to this phenotype. A total of 2,273 Nelore cattle (995 males and 1,278 females) genotyped using the Illumina BovineHD BeadChip were used in the current study. The association analysis included females with valid first calving records as well as open heifers. Linkage disequilibrium (LD) analysis among the markers was performed using blocks of 5, 10, and 15 markers, which were determined by sliding windows shifting one marker at a time. Then, the haplotype block size to be used in the association study was chosen based on the highest r² average among the SNPs in the block. The five HapAlleles most strongly associated with the trait (top five) were considered as significant associations. The results of the analysis revealed four genomic regions related to AFC, which overlapped with 20 QTL of the reproductive traits reported previously. Furthermore, there were 19 genes related to reproduction in those regions. In conclusion, the use of haplotypes allowed the detection of chromosomal regions associated with AFC in Nelore cattle, and provided the basis for elucidating the mechanisms underlying this trait.

Pathway enrichment and protein interaction network analysis for milk yield, fat yield and age at first calving in a Thai multibreed dairy population

Objective

This research aimed to determine biological pathways and protein-protein interaction (PPI) networks for 305-d milk yield (MY), 305-d fat yield (FY), and age at first calving (AFC) in the Thai multibreed dairy population.

Methods

Genotypic information contained 75,776 imputed and actual single nucleotide polymorphisms (SNP) from 2,661 animals. Single-step genomic best linear unbiased predictions were utilized to estimate SNP genetic variances for MY, FY, and AFC. Fixed effects included herd-year-season, breed regression and heterosis regression effects. Random effects were animal additive genetic and residual. Individual SNP explaining at least 0.001% of the genetic variance for each trait were used to identify nearby genes in the National Center for Biotechnology Information database. Pathway enrichment analysis was performed. The PPI of genes were identified and visualized of the PPI network.

Results

Identified genes were involved in 16 enriched pathways related to MY, FY, and AFC. Most genes had two or more connections with other genes in the PPI network. Genes associated with MY, FY, and AFC based on the biological pathways and PPI were primarily involved in cellular processes. The percent of the genetic variance explained by genes in enriched pathways (303) was 2.63% for MY, 2.59% for FY, and 2.49% for AFC. Genes in the PPI network (265) explained 2.28% of the genetic variance for MY, 2.26% for FY, and 2.12% for AFC.

Conclusion

These sets of SNP associated with genes in the set enriched pathways and the PPI network could be used as genomic selection targets in the Thai multibreed dairy population. This study should be continued both in this and other populations subject to a variety of environmental conditions because predicted SNP values will likely differ across populations subject to different environmental conditions and changes over time.

A system-based analysis of the genetic determinism of udder conformation and health phenotypes across three French dairy cattle breeds

Using GWAS to identify candidate genes associated with cattle morphology traits at a functional level is challenging. The main difficulty of identifying candidate genes and gene interactions associated with such complex traits is the long-range linkage disequilibrium (LD) phenomenon reported widely in dairy cattle. Systems biology approaches, such as combining the Association Weight Matrix (AWM) with a Partial Correlation in an Information Theory (PCIT) algorithm, can assist in overcoming this LD. Used in a multi-breed and multi-phenotype context, the AWM-PCIT could aid in identifying udder traits candidate genes and gene networks with regulatory and functional significance. This study aims to use the AWM-PCIT algorithm as a post-GWAS analysis tool with the goal of identifying candidate genes underlying udder morphology. We used data from 78,440 dairy cows from three breeds and with own phenotypes for five udder morphology traits, five production traits, somatic cell score and clinical mastitis. Cows were genotyped with medium (50k) or low-density (7 to 10k) chips and imputed to 50k. We performed a within breed and trait GWAS. The GWAS showed 9,830 significant SNP across the genome (p < 0.05). Five thousand and ten SNP did not map a gene, and 4,820 SNP were within 10-kb of a gene. After accounting for 1SNP:1gene, 3,651 SNP were within 10-kb of a gene (set1), and 2,673 significant SNP were further than 10-kb of a gene (set2). The two SNP sets formed 6,324 SNP matrix, which was fitted in an AWM-PCIT considering udder depth/ development as the key trait resulting in 1,013 genes associated with udder morphology, mastitis and production phenotypes. The AWM-PCIT detected ten potential candidate genes for udder related traits: ESR1, FGF2, FGFR2, GLI2, IQGAP3, PGR, PRLR, RREB1, BTRC, and TGFBR2.

Comparative Analysis of V-Akt Murine Thymoma Viral Oncogene Homolog 3 (AKT3) Gene between Cow and Buffalo Reveals Substantial Differences for Mastitis

AKT3 gene is a constituent of the serine/threonine protein kinase family and plays a crucial role in synthesis of milk fats and cholesterol by regulating activity of the sterol regulatory element binding protein (SREBP). AKT3 is highly conserved in mammals and its expression levels during the lactation periods of cattle are markedly increased. AKT3 is highly expressed in the intestine followed by mammary gland and it is also expressed in immune cells. It is involved in the TLR pathways as effectively as proinflammatory cytokines. The aims of this study were to investigate the sequences differences between buffalo and cow. Our results showed that there were substantial differences between buffalo and cow in some exons and noteworthy differences of the gene size in different regions. We also identified the important consensus sequence motifs, variation in 2000 upstream of ATG, substantial difference in the "3'UTR" region, and miRNA association in the buffalo sequences compared with the cow. In addition, genetic analyses, such as gene structure, phylogenetic tree, position of different motifs, and functional domains, were performed to establish their correlation with other species. This may indicate that a buffalo breed has potential resistance to disease, environment changes, and airborne microorganisms and some good production and reproductive traits.

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.

Including gene networks to predict calving difficulty in Holstein, Brown Swiss and Jersey cattle

Background

Calving difficulty or dystocia has a great economic impact in the US dairy industry. Reported risk factors associated with calving difficulty are feto-pelvic disproportion, gestation length and conformation. Different dairy cattle breeds have different incidence of calving difficulty, with Holstein having the highest dystocia rates and Jersey the lowest. Genomic selection becomes important especially for complex traits with low heritability, where the accuracy of conventional selection is lower. However, for complex traits where a large number of genes influence the phenotype, genome-wide association studies showed limitations. Biological networks could overcome some of these limitations and better capture the genetic architecture of complex traits. In this paper, we characterize Holstein, Brown Swiss and Jersey breed-specific dystocia networks and employ them in genomic predictions.

Results

Marker association analysis identified single nucleotide polymorphisms explaining the largest average proportion of genetic variance on BTA18 in Holstein, BTA25 in Brown Swiss, and BTA15 in Jersey. Gene networks derived from the genome-wide association included 1272 genes in Holstein, 1454 genes in Brown Swiss, and 1455 genes in Jersey. Furthermore, 256 genes in Holstein network, 275 genes in the Brown Swiss network, and 253 genes in the Jersey network were within previously reported dystocia quantitative trait loci. The across-breed network included 80 genes, with 9 genes being within previously reported dystocia quantitative trait loci. The gene-gene interactions in this network differed in the different breeds. Gene ontology enrichment analysis of genes in the networks showed Regulation of ARF GTPase was very significant (FDR ≤ 0.0098) on Holstein. Neuron morphogenesis and differentiation was the term most enriched (FDR ≤ 0.0539) on the across-breed network. Genomic prediction models enriched with network-derived relationship matrices did not outperform regular GBLUP models.

Conclusions

Regions identified in the genome were in the proximity of previously described quantitative trait loci that would most likely affect calving difficulty by altering the feto-pelvic proportion. Inclusion of identified networks did not increase prediction accuracy. The approach used in this paper could be extended to any instance with asymmetric distribution of phenotypes, for example, resistance to disease data.

Electronic supplementary material

The online version of this article (10.1186/s12863-018-0606-y) contains supplementary material, which is available to authorized users.

STAT6, PBX2, and PBRM1 Emerge as Predicted Regulators of 452 Differentially Expressed Genes Associated With Puberty in Brahman Heifers

The liver plays a central role in metabolism and produces important hormones. Hepatic estrogen receptors and the release of insulin-like growth factor 1 (IGF1) are critical links between liver function and the reproductive system. However, the role of liver in pubertal development is not fully understood. To explore this question, we applied transcriptomic analyses to liver samples of pre- and post-pubertal Brahman heifers and identified differentially expressed (DE) genes and genes encoding transcription factors (TFs). Differential expression of genes suggests potential biological mechanisms and pathways linking liver function to puberty. The analyses identified 452 DE genes and 82 TF with significant contribution to differential gene expression by using a regulatory impact factor metric. Brain-derived neurotrophic factor was observed as the most down-regulated gene (P = 0.003) in post-pubertal heifers and we propose this gene influences pubertal development in Brahman heifers. Additionally, co-expression network analysis provided evidence for three TF as key regulators of liver function during pubertal development: the signal transducer and activator of transcription 6, PBX homeobox 2, and polybromo 1. Pathway enrichment analysis identified transforming growth factor-beta and Wnt signaling pathways as significant annotation terms for the list of DE genes and TF in the co-expression network. Molecular information regarding genes and pathways described in this work are important to further our understanding of puberty onset in Brahman heifers.

Integration of GWAS, pathway and network analyses reveals novel mechanistic insights into the synthesis of milk proteins in dairy cows

The quantities and proportions of protein fractions have notable effects on the nutritional and technological value of milk. Although much is known about the effects of genetic variants on milk proteins, the complex relationships among the set of genes and pathways regulating the different protein fractions synthesis and secretion into milk in dairy cows are still not completely understood. We conducted genome-wide association studies (GWAS) for milk nitrogen fractions in a cohort of 1,011 Brown Swiss cows, which uncovered 170 significant single nucleotide polymorphism (SNPs), mostly located on BTA6 and BTA11. Gene-set analysis and the network-based Associated Weight Matrix approach revealed that the milk proteins associated genes were involved in several biological functions, particularly ion and cation transmembrane transporter activity and neuronal and hormone signalling, according to the structure and function of casein micelles. Deeper analysis of the transcription factors and their predicted target genes within the network revealed that GFI1B, ZNF407 and NR5A1 might act as master regulators of milk protein synthesis and secretion. The information acquired provides novel insight into the regulatory mechanisms controlling milk protein synthesis and secretion in bovine mammary gland and may be useful in breeding programmes aimed at improving milk nutritional and/or technological properties.

Genomic association for sexual precocity in beef heifers using pre-selection of genes and haplotype reconstruction

Reproductive traits are of the utmost importance for any livestock farming, but are difficult to measure and to interpret since they are influenced by various factors. The objective of this study was to detect associations between known polymorphisms in candidate genes related to sexual precocity in Nellore heifers, which could be used in breeding programs. Records of 1,689 precocious and non-precocious heifers from farms participating in the Conexão Delta G breeding program were analyzed. A subset of single nucleotide polymorphisms (SNP) located in the region of the candidate genes at a distance of up to 5 kb from the boundaries of each gene, were selected from the panel of 777,000 SNPs of the High-Density Bovine SNP BeadChip. Linear mixed models were used for statistical analysis of early heifer pregnancy, relating the trait with isolated SNPs or with haplotype groups. The model included the contemporary group (year and month of birth) as fixed effect and parent of the animal (sire effect) as random effect. The fastPHASE® and GenomeStudio® were used for reconstruction of the haplotypes and for analysis of linkage disequilibrium based on r² statistics. A total of 125 candidate genes and 2,024 SNPs forming haplotypes were analyzed. Statistical analysis after Bonferroni correction showed that nine haplotypes exerted a significant effect (p<0.05) on sexual precocity. Four of these haplotypes were located in the Pregnancy-associated plasma protein-A2 gene (PAPP-A2), two in the Estrogen-related receptor gamma gene (ESRRG), and one each in the Pregnancy-associated plasma protein-A gene (PAPP-A), Kell blood group complex subunit-related family (XKR4) and mannose-binding lectin genes (MBL-1) genes. Although the present results indicate that the PAPP-A2, PAPP-A, XKR4, MBL-1 and ESRRG genes influence sexual precocity in Nellore heifers, further studies are needed to evaluate their possible use in breeding programs.

Genome-wide association studies, meta-analyses and derived gene network for meat quality and carcass traits in pigs

A large number of quantitative trait loci (QTL) for meat quality and carcass traits has been reported in pigs over the past 20 years. However, few QTL have been validated and the biological meaning of the genes associated to these QTL has been underexploited. In this context, a meta-analysis was performed to compare the significant markers with meta-QTL previously reported in literature. Genome association studies were performed for 12 traits, from which 144 SNPs were found out to be significant (P < 0.05). They were validated in the meta-analysis and used to build the Association Weight Matrix, a matrix framework employed to investigate co-association of pairwise SNP across phenotypes enabling to derive a gene network. A total of 45 genes were selected from the Association Weight Matrix analysis, from which 25 significant transcription factors were identified and used to construct the networks associated to meat quality and carcass traits. These networks allowed the identification of key transcription factors, such as SOX5 and NKX2–5, gene–gene interactions (e.g. ATP5A1, JPH1, DPT and NEDD4) and pathways related to the regulation of adipose tissue metabolism and skeletal muscle development. Validated SNPs and knowledge of key genes driving these important industry traits might assist future strategies in pig breeding.

SNP co-association and network analyses identify E2F3, KDM5A and BACH2 as key regulators of the bovine milk fatty acid profile

The fatty acid (FA) profile has a considerable impact on the nutritional and technological quality of milk and dairy products. The molecular mechanism underlying the regulation of fat metabolism in bovine mammary gland have been not completely elucidated. We conducted genome-wide association studies (GWAS) across 65 milk FAs and fat percentage in 1,152 Brown Swiss cows. In total, we identified 175 significant single nucleotide polymorphism (SNPs) spanning all chromosomes. Pathway analyses revealed that 12:0 was associated with the greatest number of overrepresented categories/pathways (e.g. mitogen-activated protein kinase (MAPK) activity and protein phosphorylation), suggesting that it might play an important biological role in controlling milk fat composition. An Associated Weight Matrix approach based on SNP co-associations predicted a network of 791 genes related to the milk FA profile, which were involved in several connected molecular pathways (e.g., MAPK, lipid metabolism and hormone signalling) and undetectable through standard GWAS. Analysis of transcription factors and their putative target genes within the network identified BACH2, E2F3 and KDM5A as key regulators of milk FA metabolism. These findings contribute to increasing knowledge of FA metabolism and mammary gland functionality in dairy cows and may be useful in developing targeted breeding practices to improve milk quality.

Network Analysis Reveals Putative Genes Affecting Meat Quality in Angus Cattle

Improvements in eating satisfaction will benefit consumers and should increase beef demand which is of interest to the beef industry. Tenderness, juiciness, and flavor are major determinants of the palatability of beef and are often used to reflect eating satisfaction. Carcass qualities are used as indicator traits for meat quality, with higher quality grade carcasses expected to relate to more tender and palatable meat. However, meat quality is a complex concept determined by many component traits making interpretation of genome-wide association studies (GWAS) on any one component challenging to interpret. Recent approaches combining traditional GWAS with gene network interactions theory could be more efficient in dissecting the genetic architecture of complex traits. Phenotypic measures of 23 traits reflecting carcass characteristics, components of meat quality, along with mineral and peptide concentrations were used along with Illumina 54k bovine SNP genotypes to derive an annotated gene network associated with meat quality in 2,110 Angus beef cattle. The efficient mixed model association (EMMAX) approach in combination with a genomic relationship matrix was used to directly estimate the associations between 54k SNP genotypes and each of the 23 component traits. Genomic correlated regions were identified by partial correlations which were further used along with an information theory algorithm to derive gene network clusters. Correlated SNP across 23 component traits were subjected to network scoring and visualization software to identify significant SNP. Significant pathways implicated in the meat quality complex through GO term enrichment analysis included angiogenesis, inflammation, transmembrane transporter activity, and receptor activity. These results suggest that network analysis using partial correlations and annotation of significant SNP can reveal the genetic architecture of complex traits and provide novel information regarding biological mechanisms and genes that lead to complex phenotypes, like meat quality, and the nutritional and healthfulness value of beef. Improvements in genome annotation and knowledge of gene function will contribute to more comprehensive analyses that will advance our ability to dissect the complex architecture of complex traits.