Practical application of a Bayesian network approach to poultry epigenetics and stress

This work was supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 812777. We also greatly appreciate funding from the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS) grants #2018-01074 and #2017-00946 to CG-B. FP appreciates funding from São Paulo Research Foundation (FAPESP, Brazil) projects #2016/20440-3 and #2018/13600-0.Background: Relationships among genetic or epigenetic features can be explored by learning probabilistic networks and unravelling the dependencies among a set of given genetic/epigenetic features. Bayesian networks (BNs) consist of nodes that represent the variables and arcs that represent the probabilistic relationships between the variables. However, practical guidance on how to make choices among the wide array of possibilities in Bayesian network analysis is limited. Our study aimed to apply a BN approach, while clearly laying out our analysis choices as an example for future researchers, in order to provide further insights into the relationships among epigenetic features and a stressful condition in chickens (Gallus gallus). Results: Chickens raised under control conditions (n = 22) and chickens exposed to a social isolation protocol (n = 24) were used to identify differentially methylated regions (DMRs). A total of 60 DMRs were selected by a threshold, after bioinformatic pre-processing and analysis. The treatment was included as a binary variable (control = 0; stress = 1). Thereafter, a BN approach was applied: initially, a pre-filtering test was used for identifying pairs of features that must not be included in the process of learning the structure of the network; then, the average probability values for each arc of being part of the network were calculated; and finally, the arcs that were part of the consensus network were selected. The structure of the BN consisted of 47 out of 61 features (60 DMRs and the stressful condition), displaying 43 functional relationships. The stress condition was connected to two DMRs, one of them playing a role in tight and adhesive intracellular junctions in organs such as ovary, intestine, and brain. Conclusions: We clearly explain our steps in making each analysis choice, from discrete BN models to final generation of a consensus network from multiple model averaging searches. The epigenetic BN unravelled functional relationships among the DMRs, as well as epigenetic features in close association with the stressful condition the chickens were exposed to. The DMRs interacting with the stress condition could be further explored in future studies as possible biomarkers of stress in poultry species.Publisher PDFPeer reviewe

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

Background: Feed efficiency and growth rate have been targets for selection to improve chicken production. The incorporation of genomic tools may help to accelerate selection. We genotyped 529 individuals using a high-density SNP chip (600 K, Affymetrix®) to estimate genomic heritability of performance traits and to identify genomic regions and their positional candidate genes associated with performance traits in a Brazilian F2 Chicken Resource population. Regions exhibiting selection signatures and a SNP dataset from resequencing were integrated with the genomic regions identified using the chip to refine the list of positional candidate genes and identify potential causative mutations. Results: Feed intake (FI), feed conversion ratio (FC), feed efficiency (FE) and weight gain (WG) exhibited low genomic heritability values (i.e. from 0.0002 to 0.13), while body weight at hatch (BW1), 35 days-of-age (BW35), and 41 days-of-age (BW41) exhibited high genomic heritability values (i.e. from 0.60 to 0.73) in this F2 population. Twenty unique 1-Mb genomic windows were associated with BW1, BW35 or BW41, located on GGA1–4, 6–7, 10, 14, 24, 27 and 28. Thirty-eight positional candidate genes were identified within these windows, and three of them overlapped with selection signature regions. Thirteen predicted deleterious and three high impact sequence SNPs in these QTL regions were annotated in 11 positional candidate genes related to osteogenesis, skeletal muscle development, growth, energy metabolism and lipid metabolism, which may be associated with body weight in chickens. Conclusions: The use of a high-density SNP array to identify QTL which were integrated with whole genome sequence signatures of selection allowed the identification of candidate genes and candidate causal variants. One novel QTL was detected providing additional information to understand the genetic architecture of body weight traits. We identified QTL for body weight traits, which were also associated with fatness in the same population. Our findings form a basis for further functional studies to elucidate the role of specific genes in regulating body weight and fat deposition in chickens, generating useful information for poultry breeding programs

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

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

Large-scale SNP discovery and construction of a high-density genetic map of Colossoma macropomum through genotyping-by-sequencing

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

Identification of Polymorphisms Associated with Performance and Carcass Traits in Chromosome 4 of Chicken (Gallus gallus)

Dentre o setor agropecuário, a avicultura é a que mais tem demonstrado índices de evolução nos últimos anos. Esses avanços são obtidos principalmente por meio da nutrição, manejo dos animais e seleção genética. A biotecnologia tem ganhado papel de destaque com o uso de marcadores moleculares como ferramenta para acrescentar informações genômicas aos processos de melhoramento convencional. Estudos anteriores em uma população F2 originada do cruzamento de frangos de corte e postura permitiram a identificação de um SNP no gene FGFBP1 (Proteína de ligação do fator de crescimento do fibroblasto 1) (g. 2014 G> A) no cromossomo 4 de Gallus gallus (GGA4). Este gene está em uma região de QTLs associado com rendimentos de coxa e sobrecoxa, peso vivo aos 35 e 41 dias de idade. O objetivo deste trabalho foi investigar um QTL previamente descrito para identificação de polimorfismos adicionais e suas associações com características de importância econômica utilizando testes de associação de um ou mais marcadores. Três genes candidatos posicionais foram identificados nesta região de QTL: KLF3(Krüeppel-like factor 3), SLIT2 (Slit homolog 2) e PPARG (Peroxisome proliferator-activated receptor gamma, coactivator 1alpha). O sequenciamento destes genes em onze (n=11) animais F1 permitiu a identificação de um polimorfismo em cada gene: g.6763 C> T (KLF3), g.187737 C> A (SLIT2) e g.76638826 -/TTTCT (PPARGC1A). Essas mutações foram genotipadas em uma população segregante F2 (n=276) e em uma linhagem pura de corte TT (n=840) da Embrapa Suínos e Aves. A frequência dos alelos para o gene KLF3 na população F2 foi de C=50% T=50% e na pura TT de C=98% T=2%, para o gene SLIT2 na população F2 foi de A=25% C=75% e na pura TT de A=30% C=70%, para o gene PPARGC1A na população F2 foi de Del=43% In=57% e na pura TT Del=33% C=67%, representando que estes polimorfismos estão segregando nas duas populações. Associações destes polimorfismos foram observadas (P T (KLF3) e pesos das asas, cabeça, carcaça, dorso, coxas, peito, fígado e gordura abdominal com g.76638826 -/TTTCT (PPARGC1A) indicando que esta região de QTL é importante para características de produção e desempenho em frangos de corte.Within the livestock sector, the broiler industry has showed fastest growing rates in past decades. Those advances were achieved mainly because a better understanding of the nutrition requirements, animal management and animal genetics. Biotechnology has gained a prominent role with the use of molecular markers as a tool for adding genomic information to conventional breeding processes. Previous studies using an F2 population developed from a broiler x layer cross led to the identification of a SNP on the Fibroblast growth factor binding protein 1 (FGFBP1) (g. 2014G> A) on Gallus gallus chromosome 4 (GGA4). This gene is part of a QTL associated with thigh & drumstick yields, weight gain at 35 and 41 days. This paper investigates the previously identified QTL for the identification of additional polymorphisms and their associations with important economic traits using a single and multiple markers tests. Three positional candidate genes were identified on the QTL region: KLF3 (Krüeppel-like factor 3), SLIT2 (Slit homolog 2) and PPARG (Peroxisome proliferator-activated receptor gamma, coactivator 1alpha). Sequencing of those genes was conducted in eleven (n=11) F1 animals and one polymorphism was identified in each gene g.6763 C> T (KLF3), g.187737 C> A (SLIT2) and g.76638826 -/TTTCT (PPARGC1A). These mutations were genotyped in an F2 (n=276) and a pure broiler line (n=840) from Embrapa. The frequency of the genes alleles were: KLF3 gene in F2 population C = 50% T = 50% and pure TT population C = 98% T = 2%; SLIT2 gene in F2 population A = 25% C = 75% and pure TT population A = 30% C = 70%; PPARGC1A gene in F2 population Del =43% and In = 57% and pure TT population Del = 33% C = 67% indicating that those polymorphisms are still segregating in both populations. Association was identified (P T (KLF3) and wings, had, carcass, back, drumstick, breast and liver and abdominal fat weights with g.76638826 -/TTTCT (PPARGC1A) indicating that this QTL region is important for production and performance traits of broiler

Desvendando associações genéticas importantes e perfis de metilação diferenciais utilizando sequenciamento reduzido do genoma da galinha

Chickens are ideal model organism to improve understanding of several research areas as phylogenetic, embryology, biomedicine, livestock, and have recently been suggested as a promising model for epigenetic studies. In the livestock area, chickens are source of protein to humans and had been selected to achieve a high production standards based on genetic breeding by the traditional selection. We are now in the genomics and epigenomics era and it is time be concern about the use of new tools to improve selection not only thinking about production, but also in the health and welfare of animals. The use of molecular approaches, have been a fundamental tool to understand biological models and improve selection strategies based on genomic information in breeding programs. Molecular approaches have also contributed to understanding of the evolutionary history of these models and the genetics and epigenetics mechanisms involved in evolution process and genetic diversification of chickens. In this context, many technologies have emerged to produce high-throughput data using Next-generation sequencing (NGS) approaches. NGS provided a large amount of information for diverse purposes such as to detect single nucleotide polymorphisms (SNPs), and methylated DNA profiles in chickens. In addition, NGS has allowed the development of pre-designed SNP arrays for genome-wide association studies (GWAS) with specific phenotypes of interest. Moreover, although NGS has enough power to detect informative polymorphisms, its high cost makes it impractical to be used in GWAS and Methylated DNA immunoprecipitation sequencing (MeDIPseq) studies. The demand for an economical, efficient, simple-step and reliable genome-wide method of SNPs discovery, validation and characterization, was the reason for the development of this study. We applied reduced representation sequence by restriction enzyme (RE) cleavage of target chicken genome to be applied in GWAS. Thereafter, to combine the reduced representation of the genome with MeDIPseq method, we developed a novel approach to perform differential methylation studies using reduced libraries. These works allowed us to identify SNPs associated with performance traits and differential methylation windows related to different stress conditions in chickens.A galinha é um organismo modelo ideal para melhorar o entendimento de diversas áreas da pesquisa como: filogenética, embriologia, biomedicina, pecuária, e tem sido recentemente sugerida como um modelo promissor para estudos em epigenética. Na pecuária, as galinhas são fonte de proteína para os seres humanos e tem sido alvo de seleção para alcançar um alto padrão de produção com base no melhoramento genético tradicional. Mas agora, estamos na era genômica e epigenômica e as atenções devem ser voltadas para o uso de novas ferramentas para melhorar a seleção não só pensando em produção, mas também na saúde e bem-estar dos animais. O uso de abordagens moleculares, tem sido uma ferramenta fundamental para compreender modelos biológicos e melhorar as estratégias de seleção baseadas na informação genômica em programas de melhoramento. Abordagens moleculares, também tem contribuído para a compreensão da história evolutiva desses modelos e os mecanismos genéticos e epigenéticos envolvidos no processo de evolução e diversificação genética das galinhas. Neste contexto, tecnologias evoluíram para produção de dados de sequenciamento de alto rendimento por sequenciamento de próxima geração (NGS). NGS forneceu uma grande quantidade de informação a ser utilizado para diversos fins, como para detectar polimorfismos de nucleotídeo único (SNPs) e perfis de metilação diferencial do DNA em galinhas. NGS tem permitido também o desenvolvimento de painéis de SNP para testes de associações genômica ampla (GWAS) com fenótipos específicos de interesse. Embora NGS tem poder suficiente para detectar polimorfismos informativos, o seu elevado custo o torna impraticável para ser utilizado em GWAS ou estudos de metilação diferencial por sequenciamento de DNA metilado por imunoprecipitação (MeDIPseq). A procura de um método de genotipagem eficiente, simples, econômico e confiável para descoberta, caracterização e validação de SNPs, foi a razão para o desenvolvimento deste estudo. Utilizamos sequenciamento do genoma reduzido por enzima de restrição (RE) que cliva o genoma alvo para identificação de SNPs nestas bibliotecas reduzidas e aplicação deste método em GWAS. Em seguida, para combinar a representação reduzida do genoma com o método MeDIPS, desenvolvemos uma nova abordagem para a realização de estudos de metilação diferencial utilizando as bibliotecas reduzidas. Estes trabalhos permitiram a identificação de SNPs associados com características de desempenho e janelas de metilação diferencial relacionados a diferentes condições de manejo em galinhas

How Epigenetics Can Enhance Pig Welfare?

Simple Summary In the pig industry, new market trends and consumer demands have emerged over the past decades, which includes increased concerns about how animals are raised on farms. As a consequence of consumers concerns, technologies capable of predicting animal welfare on farms have been explored. One of the technologies that are permeating the frontier of knowledge in this area are epigenetic biomarkers. Epigenetic biomarkers are biochemical markers surrounding the genome, which may be able to predict the exposures that individuals had during their lifetime. These markers represent an advance in the molecular level accuracy to support the current welfare indicators. In this literature review focused on pigs, we show some studies already carried out, we performed an integrative analysis of the already reported genes surrounding epi-biomarkers, and we highlight the benefits of investing efforts in this research field to enhance animal welfare and consumers trust. Epigenetics works as an interface between the individual and its environment to provide phenotypic plasticity to increase individual adaptation capabilities. Recently, a wide variety of epi-genetic findings have indicated evidence for its application in the development of putative epi-biomarkers of stress in farm animals. The purpose of this study was to evaluate previously reported stress epi-biomarkers in swine and encourage researchers to investigate potential paths for the development of a robust molecular tool for animal welfare certification. In this literature review, we report on the scientific concerns in the swine production chain, the management carried out on the farms, and the potential implications of these practices for the animals welfare and their epigenome. To assess reported epi-biomarkers, we identified, from previous studies, potentially stress-related genes surrounding epi-biomarkers. With those genes, we carried out a functional enrichment analysis of differentially methylated regions (DMRs) of the DNA of swine subjected to different stress-related conditions (e.g., heat stress, intrauterine insult, and sanitary challenges). We identified potential epi-biomarkers for target analysis, which could be added to the current guidelines and certification schemes to guarantee and certify animal welfare on farms. We believe that this technology may have the power to increase consumers trust in animal welfare.Funding Agencies|Sao Paulo Research Foundation (FAPESP)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [2018/01082-04]; Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior-Brasil (CAPES)Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES) [88887.509167/2020-00]; Department of Biomedical and Clinical Sciences (BKV) from University of Linkoeping, Campus US; [2016/20440-3]; [2018/13600-0]; [2018-01074]</p

DNA methylation variation in the brain of laying hens in relation to differential behavioral patterns

Domesticated animals are unique to investigate the contribution of genetic and non-genetic factors to specific phenotypes. Among non-genetic factors involved in phenotype formation are epigenetic mechanisms. Here we aimed to identify whether relative DNA methylation differences in the nidopallium between groups of individuals are among the non-genetic factors involved in the emergence of differential behavioral patterns in hens. The nidopallium was selected due to its important role in complex cognitive function (i.e., decision making) in birds. Behavioral patterns that spontaneously emerge in hens living in a highly controlled environment were identified with a unique tracking system that recorded their transitions between pen zones. Behavioral activity patterns were characterized through three classification schemes: (i) daily specific features of behavioral routines (Entropy), (ii) daily spatio-temporal activity patterns (Dynamic Time Warping), and (iii) social leading behavior (Leading Index). Unique differentially methylated regions (DMRs) were identified between behavioral patterns emerging within classification schemes, with entropy having the higher number. Functionally, DTW had double the proportion of affected promoters and half of the distal intergenic regions. Pathway enrichment analysis of DMR-associated genes revealed that Entropy relates mainly to cell cycle checkpoints, Leading Index to mitochondrial function, and DTW to gene expression regulation. Our study suggests that different biological functions within neurons (particularly in the nidopallium) could be responsible for the emergence of distinct behavior patterns and that epigenetic variation within brain tissues would be an important factor to explain behavioral variation

DNA methylation in canine brains is related to domestication and dog-breed formation

Epigenetic factors such as DNA methylation act as mediators in the interaction between genome and environment. Variation in the epigenome can both affect phenotype and be inherited, and epigenetics has been suggested to be an important factor in the evolutionary process. During domestication, dogs have evolved an unprecedented between-breed variation in morphology and behavior in an evolutionary short period. In the present study, we explore DNA methylation differences in brain, the most relevant tissue with respect to behavior, between wolf and dog breeds. We optimized a combined method of genotype-by-sequencing (GBS) and methylated DNA immunoprecipitation (MeDIP) for its application in canines. Genomic DNA from the frontal cortex of 38 dogs of 8 breeds and three wolves was used. GBS and GBS-MeDIP libraries were prepared and sequenced on Illuma HiSeq2500 platform. The reduced sample represented 1.18 ± 0.4% of the total dog genome (2,4 billion BP), while the GBS-MeDIP covered 11,250,788 ± 4,042,106 unique base pairs. We find substantial DNA methylation differences between wolf and dog and between the dog breeds. The methylation profiles of the different groups imply that epigenetic factors may have been important in the speciation from dog to wolf, but also in the divergence of different dog breeds. Specifically, we highlight methylation differences in genes related to behavior and morphology. We hypothesize that these differences are involved in the phenotypic variation found among dogs, whereas future studies will have to find the specific mechanisms. Our results not only add an intriguing new dimension to dog breeding but are also useful to further understanding of epigenetic involvement