Estimation of Breeding Values Using Different Densities of Snp to Inform Kinship in Broiler Chickens

Background: Traditionally, breeding values are estimated based on phenotypic and pedigree information using the numerator relationship (A) matrix. With the availability of genomic information, genome-wide markers can be included in the estimation of breeding values through genomic kinship. However, the density of genomic information used can impact the cost of implementation. The aim of this study was to compare the rank, accuracy, and bias of estimated breeding values (EBV) for organs [heart (HRT), liver (LIV), gizzard (GIZ), lungs (LUN)] and carcass [breast (BRST), drumstick (DRM) and thigh (THG)] weight traits in a broiler population using pedigree-based BLUP (PBLUP) and single-step genomic BLUP (ssGBLUP) methods using various densities of SNP and variants imputed from whole-genome sequence (WGS). Results: For both PBLUP and ssGBLUP, heritability estimates varied from low (LUN) to high (fHRT, LIV, GIZ, BRST, DRM and THG.) Regression coefficients values of EBV on genomic estimated breeding values (GEBV) were similar for both the high density (HD) and WGS sets of SNPs ranging from 0.87 to 0.99 across senarios. Conclusion: Results show no benefit of using WGS data compared to HD array data using an unweighted ssGBLUP. Our results suggest that 10% of the content of the HD array can yield unbiased and accurate EBV

Genome-wide association scan for QTL and their positional candidate genes associated with internal organ traits in chickens

Background: Poultry breeding programs have been focused on improvement of growth and carcass traits, however, this has resulted in correlated changes in internal organ weights and increased incidence of metabolic disorders. These disorders can affect feed efficiency or even cause death. We used a high density SNP array (600 K, Affymetrix) to estimate genomic heritability, perform genome-wide association analysis, and identify genomic regions and positional candidate genes (PCGs) associated with internal organ traits in an F2 chicken population. We integrated knowledge of haplotype blocks, selection signature regions and sequencing data to refine the list of PCGs. Results: Estimated genomic heritability for internal organ traits in chickens ranged from low (LUNGWT, 0.06) to high (GIZZWT, 0.45). A total of 20 unique 1 Mb windows identified on GGA1, 2, 4, 7, 12, 15, 18, 19, 21, 27 and 28 were significantly associated with intestine length, and weights or percentages of liver, gizzard or lungs. Within these windows, 14 PCGs were identified based on their biological functions: TNFSF11, GTF2F2, SPERT, KCTD4, HTR2A, RB1, PCDH7, LCORL, LDB2, NR4A2, GPD2, PTPN11, ITGB4 and SLC6A4. From those genes, two were located within haplotype blocks and three overlapped with selection signature regions. A total of 13,748 annotated sequence SNPs were in the 14 PCGs, including 156 SNPs in coding regions (124 synonymous, 26 non-synonymous, and 6 splice variants). Seven deleterious SNPs were identified in TNFSF11, NR4A2 or ITGB4 genes. Conclusions: The results from this study provide novel insights to understand the genetic architecture of internal organ traits in chickens. The QTL detection performed using a high density SNP array covered the whole genome allowing the discovery of novel QTL associated with organ traits. We identified PCGs within the QTL involved in biological processes that may regulate internal organ growth and development. Potential functional genetic variations were identified generating crucial information that, after validation, might be used in poultry breeding programs to reduce the occurrence of metabolic disorders

Heritability for milk production and composition traits in Holstein dairy cattle

Todos os textos, informa??es e resultados apresentados s?o de inteira responsabilidade dos autores.O Brasil se encontra entre os seis maiores produtores de leite do mundo. A produ??o deste alimento depende do potencial gen?tico do animal e do ambiente, tendo o melhoramento animal um papel fundamental nesta atividade. Com o objetivo de estimar a herdabilidade para as caracter?sticas produ??o de leite, teor de lactose, gordura e prote?na, um banco de dados composto de mais de 13 mil amostras de leite oriundas tr?s fazendas no Estado de S?o Paulo foi analisado. Os resultados obtidos para a estimativa de herdabilidade para caracter?stica de produ??o e composi??o do leite, teor de lactose, gordurae prote?na foram de0,51 ? 0,01, 0,48 ? 0,01, 0,22 ? 0,01 e 0,43 ? 0,01. A produ??o de leite, teor de lactose, gordura e prote?na, s?o caracter?sticas que podem ser utilizadas como crit?rio de sele??o dentro dos rebanhos estudados, quando o objetivo for aumentar a produ??o e a qualidade do leite.Brazil is one of the six largest producers of milk in the world. The milk production depends on the genetic potential of the animal and the environment, and animal breeding plays a key role in this activity. In order to estimate the heritability for the milk production and quality traits, lactose, fat, and protein, a database consisting of more than 13 thousand milk samples from three different farms in the state of S?o Paulo were analyzed. The heritability estimates milk production, lactose, fat, and protein were 0.51 ? 0,01, 0.48 ? 0,01, 0.22 ? 0,01, and 0.43 ? 0,01. Milk production, lactose, fat, and protein may be used as selection criteria in the population analyzed, when the objective is the increase of milk production and quality

Heat stress on breeding value prediction for production traits and milk quality of Holstein cows

A raça Holandesa apresenta alto rendimento na produção de leite, por isto, diversos países têm optado pela importação de sêmen para substituir as raças leiteiras locais. Esta estratégia seria eficaz se o sêmen importado fosse utilizado nas mesmas circunstâncias em que foram selecionados. Caso exista interação genótipo ambiente significativa, é esperada uma nova classificação dos touros, porém se o efeito da interação genótipo ambiente não é levada em consideração, os valores genéticos preditos (EBVs) podem ser tendenciosos, reduzindo a resposta de seleção. Diante disso, os objetivos deste trabalho foram comparar modelos de diferentes ordens de ajuste por meio de funções polinomiais de Legendre, utilizando modelos de regressão aleatória e estimar os coeficientes de herdabilidade para os teores de gordura, proteína, ácido graxo saturado, ácido graxo insaturado, e produção de leite. Além de estimar o valor genético dos animais, sob a interferência do estresse térmico. Foram utilizadas informações fenotípicas coletadas mensalmente ao longo da lactação e modelos com polinômios ortogonais de Legendre de primeira a sexta ordem, para verificar a interferência de estresse térmico, foram utilizadas informações de temperatura e umidade do dia de coleta. Os modelos que melhor se ajustaram foram os de primeira e segunda ordem. As estimativas de herdabilidade variaram de 0,02 a 0,52 para teor de gordura; de 0,03 a 0,63 para teor de proteína; de 0,05 a 0,63 para ácido graxo saturado; de 0,019 a 0,364 para ácido graxo insaturado e de 0,133 a 0,390 para produção de leite nos diferentes modelos estudados. As estimativas de valores genéticos variaram de -0,5 a 0,5 em ambiente sem estresse térmico e de -0,2 a 0,2 em ambiente com estresse térmico para o teor de gordura; de -0,4 a 0,4 para ambiente sem estresse térmico e de -0,2 a 0,2 em ambiente com estresse térmico para o teor de proteína; de -0,3 a 0,3 em ambiente sem estresse térmico e de -0,2 a 0,2 em ambiente com estresse térmico para ácido graxo saturado; de -0,1 a 0,1 em ambiente sem estresse térmico e de -0,1 a 0,1 em ambiente com estresse térmico para ácido graxo insaturado e de - 6 a 6 em ambiente sem estresse térmico e de -2 e 2 em ambiente com estresse térmico para produção de leite. De acordo com os resultados, as herdabilidades indicam que o teor de gordura, proteína, ácido graxo saturado produção de leite podem ser utilizados como critério de seleção. Com o uso de informações de temperatura e umidade do ar, foi possível verificar a presença de interação genótipo ambiente para teor de gordura, proteína, ácido graxo saturado e produção de leite aos 205 dias em lactação.Due to the high milk production of Holstein cattle, many countries have chosen to import semen to replace local dairy breeds. This strategy would be effective if these semen was used in the same circumstances in which they were selected. However, if there is significant genotype environment interaction, it is expected a new bulls ranking, but if the effect of genotype environment interaction is not considered, the estimated breeding values (EBVs) may be tendentious, reducing the selection response. The objectives of this study were estimate breeding value under heat stress and heritability coefficients, and also to compare models of different adjustment orders through Legendre polynomials, using random regression models for fat, protein, saturated fatty acid, unsaturated fatty acid and milk production. There were used phenotypic information collected monthly through the lactation period and Legendre orthogonal polynomials models from the first to sixth order. To verify the interference of heat stress, there was used temperature and humidity information on the day of the evaluation was performed. The first and second order models were the ones that better fitted. Heritability estimates were from 0.02 to 0.52 for fat; 0.03 to 0.63 for protein; 0.05 to 0.63 for saturated fatty acid; 0.019 to 0.364 for unsaturated fatty acid and 0.133 to 0.390 for milk production on the different models tested. Estimates of the genetic value were from -0.5 to 0.5 on environment without heat stress and -0.2 to 0.2 on environment with heat stress for fat; -0.4 to 0.4 on environment without heat stress and -0.2 to 0.2 on environment with heat stress for protein; -0.3 to 0.3 on environment without heat stress and -0.2 to 0.2 on environment with heat stress for saturated fatty acid; -0.1 to 0.1 on environment without heat stress and of -0.8 to 0.8 on environment with heat stress for unsaturated fatty acid; -6 to 6 on environment without heat stress and -2 to 2 on environment with heat stress for milk production. The heritability indicates that the fat, protein, saturated fatty acid and milk production can be used as selection criteria. With the use of temperature and humidity information, it was possible to verify the presence of genotype environment interaction for fat, protein, saturated fatty acid and milk production at 205 days in milk

Enriquecimento de painéis de genotipagem para a seleção genômica de características especiais em frango de corte

Traditional animal breeding programs have considerably modified chicken production in Brazil. However, the intensive selection process over the years brought negative consequences in poultry production, such as increased of the abdominal fat deposition, resulting in difficulties in the industrial processing and depreciation of the final product. In recent years, technological advances in molecular genetics and bioinformatics fields have made genomic selection (GS), using molecular markers (Single Nucleotide Polymorphisms - SNP), and more recently the whole-genome sequencing (WGS), an important tool to increase the genetic gain in animal breeding, especially for complex traits and traits which are difficult to measure. The aims of this work were to estimate the genetic values and compare the genomic predictions using a high-density SNP panel (HD - 600K) and whole-genome sequencing (WGS) dataset through different marker densities. Organs (heart, liver, gizzard and lungs) and carcass (breast, thigh, drumstick) information of 2,000 animals derived from a TT broiler line belonging to the Animal Breeding Program from Embrapa Swine and Poultry were used in further analysis. Subsequently, genomic predictions were performed using pedigree- based BLUP (PBLUP), single-step genomic BLUP (ssGBLUP) and BayesC models using various densities of SNP and variants imputed from whole-genome sequence. Genomic predictions were better when the genomic information was added in the analyses. However, our results showed no benefit of using WGS data compared to HD array data when ssGBLUP or BayesC approaches were applied. Besides that, the use of array data with lower densities (~74.000 SNPs can provide significant results at a low cost.O melhoramento genético modificou consideravelmente a produção de frango no Brasil e no mundo. No entanto, o intensivo processo de seleção ao longo dos anos trouxe consequências negativas em aves, como por exemplo, o aumento na deposição de gordura abdominal nos animais, resultando em dificuldades de processamento e depreciação do produto final. Nos últimos anos, os avanços tecnológicos nas áreas de genética molecular e bioinformática fizeram com que a seleção genômica (SG) com o uso de marcadores moleculares (Single Nucleotide Polymorphisms - SNP), e mais recentemente o sequenciamento completo do genoma (Whole-Genomic Sequencing- WGS), se tornasse uma importante ferramenta para aumentar o ganho genético no melhoramento animal, especialmente para características complexas e de difícil mensuração. Os objetivos deste trabalho foram estimar os valores genéticos e comparar as predições genômicas utilizando provenientes de um painel de SNP de alta densidade (HD - 600K) e de dados do sequenciamento completo do genoma (WGS), por meio de diferentes densidades de marcadores. Foram utilizadas informações de órgãos (coração, fígado, moela e pulmões) e carcaça (peito, coxa, sobrecoxa) de 2.000 aves provenientes da população referência TT pertencente ao Programa de Melhoramento Genético de Aves da EMBRAPA Suínos e Aves. Posteriormente, as predições genômicas foram realizadas utilizando os modelos PBLUP (Pedigree-Based BLUP), ssGBLUP (single-step Genomic BLUP) e BayesC em várias densidades de SNP e variantes imputadas a partir da sequência do genoma completo. As predições genômicas foram melhores quando as informações genômicas foram adicionadas nas análises. No entanto, nossos resultados não mostraram nenhum benefício no uso de dados WGS em comparação aos dados do HD quando as abordagens ssGBLUP ou BayesC foram aplicadas. Além disso, o uso de um painel de baixa densidade (~74.000 SNPs) pode fornecer resultados significativos a um baixo custo

Genome‑wide selection and association in animal breeding using ssGBLUP

O objetivo deste trabalho foi avaliar a eficiência do método ssGBLUP quanto à seleção e à associação genômica ampla, com atribuição de pesos a marcadores genéticos e uso de informações de genótipos e fenótipos, com ou sem informações de pedigree, com diferentes coeficientes de herdabilidade. A população estudada foi obtida por simulação de dados com 8.150 animais, 5.850 dos quais eram genotipados. Utilizou-se o método ssGBLUP para a análise dos dados, com duas matrizes de relacionamento – com ou sem informações de pedigree –, e pesos para os marcadores genéticos obtidos em cada iteração. O aumento do coeficiente de herdabilidade melhorou os resultados de seleção e associação genômica. O melhor desempenho quanto à habilidade preditiva foi obtido quando não se utilizaram informações de pedigree. O tipo de matriz de relacionamento utilizada não influenciou a identificação de regiões associadas a características de interesse. O método ssGBLUP é eficiente tanto para a seleção quanto para a identificação de regiões associadas às características estudadas.The objective of this work was to evaluate the efficiency of the ssGBLUP method for genome‑wide selection and association, attributing weights to genetic markers and using genotype and phenotype information, with or without pedigree information, considering different coefficients of heritability. The studied population was obtained by data simulation with 8,150 animals, 5,850 of which were genotyped. The ssGBLUP method was used for data analysis, with two relationship matrices – with or without pedigree information –, and weights for the genetic markers obtained in each iteration. Increasing heritability coefficients improved the results of genomic selection and association. The best performance for predictive ability was obtained without pedigree information. The type of relationship matrix used did not affect the identification of regions associated with traits of interest. The ssGBLUP method is efficient both for selection and identification of regions associated with the studied traits

Seleção e associação genômica ampla para o melhoramento genético animal com uso do método ssGBLUP

O objetivo deste trabalho foi avaliar a eficiência do método ssGBLUP quanto à seleção e à associação genômica ampla, com atribuição de pesos a marcadores genéticos e uso de informações de genótipos e fenótipos, com ou sem informações de pedigree, com diferentes coeficientes de herdabilidade. A população estudada foi obtida por simulação de dados com 8.150 animais, 5.850 dos quais eram genotipados. Utilizou-se o método ssGBLUP para a análise dos dados, com duas matrizes de relacionamento – com ou sem informações de pedigree –, e pesos para os marcadores genéticos obtidos em cada iteração. O aumento do coeficiente de herdabilidade melhorou os resultados de seleção e associação genômica. O melhor desempenho quanto à habilidade preditiva foi obtido quando não se utilizaram informações de pedigree. O tipo de matriz de relacionamento utilizada não influenciou a identificação de regiões associadas a características de interesse. O método ssGBLUP é eficiente tanto para a seleção quanto para a identificação de regiões associadas às características estudadas.The objective of this work was to evaluate the efficiency of the ssGBLUP method for genome‐wide selection and association, attributing weights to genetic markers and using genotype and phenotype information, with or without pedigree information, considering different coefficients of heritability. The studied population was obtained by data simulation with 8,150 animals, 5,850 of which were genotyped. The ssGBLUP method was used for data analysis, with two relationship matrices – with or without pedigree information –, and weights for the genetic markers obtained in each iteration. Increasing heritability coefficients improved the results of genomic selection and association. The best performance for predictive ability was obtained without pedigree information. The type of relationship matrix used did not affect the identification of regions associated with traits of interest. The ssGBLUP method is efficient both for selection and identification of regions associated with the studied traits

Comparison of Marker Effects and Breeding Values at Two Levels at THI for Milk Yield and Quality Traits in Brazilian Holstein Cows

Genomic tools can help in the selection of animals genetically resistant to heat stress, especially the genome-wide association studies (GWAS). The objective of this study was to compare the variance explained by SNPs and direct genomic breeding values (DGVs) at two levels of a temperature and humidity index (THI). Records of milk yield (MY), somatic cell score (SCS), and percentages of casein (CAS), saturated fatty acids (SFA), and unsaturated fatty acids (UFA) in milk from 1157 Holstein cows were used. Traditional breeding values (EBV) were determined in a previous study and used as pseudo-phenotypes. Two levels of THI (heat comfort zone and heat stress zone) were used as environments and were treated as “traits” in a bi-trait model. The GWAS was performed using the genomic best linear unbiased prediction (GBLUP) method. Considering the top 50 SNPs, a total of 36 SNPs were not common between environments, eight of which were located in gene regions related to the evaluated traits. Even for those SNPs that had differences in their explained variances between the two environments, the differences were very small. The animals showed virtually no rank order, with rank correlation values of 0.90, 0.88, 1.00, 0.88, and 0.97 for MY, CAS, SCS, SFA, and UFA, respectively. The small difference between the environments studied can be attributed to the small difference in the pseudo-phenotypes used between the environments, on-farm acclimation, the polygenic nature of the traits, and the THI values studied near the threshold between comfort and heat stress. It is recommended that future studies be conducted with a larger number of animals and at more extreme THI levels

Genome-wide association scan for QTL and their positional candidate genes associated with internal organ traits in chickens

Background: Poultry breeding programs have been focused on improvement of growth and carcass traits, however, this has resulted in correlated changes in internal organ weights and increased incidence of metabolic disorders. These disorders can affect feed efficiency or even cause death. We used a high density SNP array (600 K, Affymetrix) to estimate genomic heritability, perform genome-wide association analysis, and identify genomic regions and positional candidate genes (PCGs) associated with internal organ traits in an F2 chicken population. We integrated knowledge of haplotype blocks, selection signature regions and sequencing data to refine the list of PCGs. Results: Estimated genomic heritability for internal organ traits in chickens ranged from low (LUNGWT, 0.06) to high (GIZZWT, 0.45). A total of 20 unique 1 Mb windows identified on GGA1, 2, 4, 7, 12, 15, 18, 19, 21, 27 and 28 were significantly associated with intestine length, and weights or percentages of liver, gizzard or lungs. Within these windows, 14 PCGs were identified based on their biological functions: TNFSF11, GTF2F2, SPERT, KCTD4, HTR2A, RB1, PCDH7, LCORL, LDB2, NR4A2, GPD2, PTPN11, ITGB4 and SLC6A4. From those genes, two were located within haplotype blocks and three overlapped with selection signature regions. A total of 13,748 annotated sequence SNPs were in the 14 PCGs, including 156 SNPs in coding regions (124 synonymous, 26 non-synonymous, and 6 splice variants). Seven deleterious SNPs were identified in TNFSF11, NR4A2 or ITGB4 genes. Conclusions: The results from this study provide novel insights to understand the genetic architecture of internal organ traits in chickens. The QTL detection performed using a high density SNP array covered the whole genome allowing the discovery of novel QTL associated with organ traits. We identified PCGs within the QTL involved in biological processes that may regulate internal organ growth and development. Potential functional genetic variations were identified generating crucial information that, after validation, might be used in poultry breeding programs to reduce the occurrence of metabolic disorders.This article is published as Moreira, Gabriel Costa Monteiro, Mayara Salvian, Clarissa Boschiero, Aline Silva Mello Cesar, James M. Reecy, Thaís Fernanda Godoy, Mônica Corrêa Ledur, Dorian Garrick, Gerson Barreto Mourão, and Luiz L. Coutinho. "Genome-wide association scan for QTL and their positional candidate genes associated with internal organ traits in chickens." BMC Genomics 20 (2019): 669. doi: 10.1186/s12864-019-6040-3.</p