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

Population structure and accuracy of genomic prediction in poultry populations: a simulation study

Para o desenvolvimento sustentável, a produção de linhagens de aves nativas, seria uma alternativa de aliar a preservação da diversidade e variabilidade genética. Neste contexto, foram desenvolvidos dois estudos. O primeiro estudo objetivou-se entender melhor as estratégias de seleção e acasalamentos utilizados; e compreender se o Ne de rebanhos de aves caipiras nacionais em condições reais está adequado. Foi simulado uma geração histórica que por mil gerações teve um tamanho constante de 2000 indivíduos, ocorrendo um gargalo genético nas gerações subsequentes (1010 a 1020) para 400 animais e expandiu para 1000, 500, 200 e 100 animais de onde surgiram as fases (população recente) dos quatro cenários simulados e para três coeficientes de herdabilidade (0,15; 0,30 e 0,45). Na Fase 1 os indivíduos não passaram por nenhum processo de seleção por quarenta gerações (G_0 a G_40), posteriormente nas Fases 2 e 3, os indivíduos foram selecionados por características fenotípicas por 25 gerações (G_41 a G_65) e pelos valores genéticos preditos (BLUP-EBV) nas ultimas 15 gerações (G_66 a G_80), respectivamente. Os cenários 1, 2, 3 e 4 possuíram tamanhos efetivos da população de 1000, 640 e 640; 500, 320 e 320; 200, 128 e 128; 100, 64 e 64 nas Fases 1, 2 e 3, respectivamente. Foram calculados coeficientes de endogamia, a taxa de homozigose, as tendências genéticas e os ganhos genéticos. Para todos os cenários estudados, a geração zero (G_0) das três fases da população recente (Fase 1, Fase 2 e Fase 3) teve um coeficiente de endogamia igual a zero. Além disso, os valores obtidos para os coeficientes de endogamia aumentaram da primeira para a última geração de cada uma das fases 1, 2 e 3 estudadas, e os maiores coeficientes de endogamia foram obtidos nos cenários com menor Ne, assim como, os valores das taxas de homozigose. Os valores de ganhos genéticos foram maiores para o coeficiente de herdabilidade de 0,45 dos quatro cenários simulados com diferentes tamanhos efetivos da população. Pode-se concluir que o Ne dos rebanhos de linhagens caipiras deve ser aumentado; e as estratégias de seleção devem ser revisadas e aplicadas para a minimização dos níveis de endogamia e homozigose; para que os ganhos genéticos destas populações possam ser maximizados. No segundo objetivou-se compreender os impactos do Ne sobre o desequilíbrio de ligação (LD) e a acurácia de predição genômica. Foi realizado o mesmo processo de simulação do estudo anterior para três cenários e três coeficientes de herdabilidade (0,15; 0,30 e 0,45) simulados. Os cenários 1, 2, 3 possuíram tamanhos efetivos da população de 500, 320 e 320; 200, 128 e 128; 100, 64 e 64 nas Fases 1, 2 e 3, respectivamente. Foram calculados o desequilíbrio de ligação (LD), a acurácia e o viés de predição \"empíricos\". Os valores médios de r2, a distâncias dos marcadores de 0-0,05 Kb, foram inferiores ou próximos a 0,30 nas Fases 1 e 2 dos cenários 1 e 2, enquanto que para o cenário 3 (menor Ne), os valores médios de r2 foram superiores a 0,30 em todas as fases e coeficientes de herdabilidade simulados. Os valores de correlações entre os TBVs e EBVs variaram de 0,69 a 0,81 nos três cenários e herdabilidades simulados. As correlações entre TBVs e GEBVs variaram de 0,45 a 0,90; e foram menores no cenário 3. Os coeficientes de regressão estimados dos fenótipos simulados nos EBVs foram altos e maiores que 1; e as regressões dos fenótipos simulados nos GEBVs apresentaram valores menores que 1. Por isso, com base nos resultados deste estudo de simulação pode-se concluir que o LD das populações de linhagens caipiras da ESALQ pode ser considerado \"útil\" e eficiente para estudos genômicos e para que os valores de acurácia de predição sejam maiores será necessário o aumento do Ne nos rebanhos de linhagens caipira da ESALQ.For sustainable development, the production of native bird lines would be an alternative to combine the preservation of genetic diversity and variability. In this context, two studies were developed. The first study aimed to better understand the selection and mating strategies used and understand whether the Ne of national free-range poultry flocks in real conditions is adequate. A historical generation was simulated, which for a thousand generations had a constant size of 2000 individuals, with a genetic bottleneck occurring in subsequent generations (1010 to 1020) for 400 animals and expanded to 1000, 500, 200 and 100 animals from which the phases emerged (population recent) of the four simulated scenarios and for three coefficients of heritability (0.15; 0.30 and 0.45). In Phase 1, individuals did not undergo any selection process for forty generations (G_0 to G_40), later in Phases 2 and 3, individuals were selected for phenotypic characteristics for 25 generations (G_41 to G_65) and the predicted genetic values (BLUP -EBV) in the last 15 generations (G_66 to G_80), respectively. Scenarios 1, 2, 3 and 4 had effective population sizes of 1000, 640 and 640; 500, 320 and 320; 200, 128 and 128; 100, 64 and 64 in Phases 1, 2 and 3, respectively. Inbreeding coefficients, homozygosity rate, genetic trends, and genetic gains were calculated. For all studied scenarios, the zero generation (G_0) of the three phases of the recent population (Phase 1. Phase 2 and Phase 3) had an inbreeding coefficient equal to zero. In addition, the values obtained for the inbreeding coefficients increased from the first to the last generation of each of the studied phases 1, 2, and 3, and the highest inbreeding coefficients were obtained in the scenarios with the lowest Ne, as well as the values of the homozygosity rates. The values of genetic gains were higher for the heritability coefficient of 0.45 of the four simulated scenarios with different effective population sizes. It can be concluded that the Ne of herds of free-range lineages must be increased; and selection strategies should be reviewed and applied to minimize levels of inbreeding and homozygosity; so that the genetic gains of these populations can be maximized. The second aimed to understand the impacts of Ne on the linkage disequilibrium (LD) and the accuracy of genomic prediction. The same simulation process of the previous study was performed for three scenarios and three coefficients of heritability (0.15; 0.30 and 0.45) simulated. Scenarios 1, 2, 3 had effective population sizes of 500, 320 and 320; 200, 128 and 128; 100, 64 and 64 in Phases 1, 2 and 3, respectively. Linkage disequilibrium (LD), accuracy, and \"empirical\" prediction bias were calculated. The average values of r2, at distance from the markers of 0-0.05 Kb, were lower or close to 0.30 in Phases 1 and 2 of scenarios 1 and 2, while for scenario 3 (lowest Ne), the values mean r2 were greater than 0.30 in all phases and simulated heritability coefficients. The correlation values between TBVs and EBVs varied from 0.69 to 0.81 in the three scenarios and simulated heritabilities. The correlations between TBVs and GEBVs ranged from 0.45 to 0.90 and were lower in scenario 3. The estimated regression coefficients of the simulated phenotypes in the EBVs were high and greater than 1; and the regressions of the simulated phenotypes in the GEBVs showed values less than 1. Therefore, based on the results of this simulation study, it can be concluded that the LD of the populations of ESALQ free-range strains can be considered \"useful\" and efficient for genomic and for the prediction accuracy values to be higher, it will be necessary to increase the Ne in herds of ESALQ free-range strains

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