Comparison of dimensionality reduction methods to predict genomic breeding values for carcass traits in pigs

A significant contribution of molecular genetics is the direct use of DNA information to identify genetically superior individuals. With this approach, genome-wide selection (GWS) can be used for this purpose. GWS consists of analyzing a large number of single nucleotide polymorphism markers widely distributed in the genome; however, because the number of markers is much larger than the number of genotyped individuals, and such markers are highly correlated, special statistical methods are widely required. Among these methods, independent component regression, principal component regression, partial least squares, and partial principal components stand out. Thus, the aim of this study was to propose an application of the methods of dimensionality reduction to GWS of carcass traits in an F2 (Piau x commercial line) pig population. The results show similarities between the principal and the independent component methods and provided the most accurate genomic breeding estimates for most carcass traits in pigs

Scattering of the halo nucleus 11Be from a lead target at 3.5 times the Coulomb barrier energy

Angular distributions of quasielastic scattering and breakup of the neutron-rich halo nucleus 11Be on a 208Pb target at an incident energy of 140 MeV (about 3.5 times the Coulomb barrier) were measured at HIRFL-RIBLL. A strong suppression of the Coulomb nuclear interference peak is observed in the measured quasielastic scattering angular distribution. The result demonstrates for the first time the persistence of the strong breakup coupling effect reported so far for reaction systems involving neutron-halo nuclei at this relatively high incident energy. The measured quasielastic scattering cross sections are satisfactorily reproduced by continuum discretized coupled channel (CDCC) calculations as well as by the XCDCC calculations where the deformation of the 10Be core is taken into account. The angular and energy distributions of the 10Be fragments could also be well reproduced considering elastic breakup (CDCC and XCDCC) plus nonelastic breakup contributions, with the latter evaluated with the model by Ichimura, Austern and Vincent [1]. The comparison of the 10Be energy distributions with simple kinematical estimates evidence the presence of a significant post-acceleration effect which, in the (X)CDCC frameworks, is accounted for by continuum-continuum couplings.National Key Research and Development Program of China (Grant No. 2018YFA0404403)National Natural Science Foundation of China (Grant No. 11775013, No. 11947203, No. 11575256, and No. U1632138)Youth Innovation Promotion Association CAS (No. 2020411)Ministerio de Ciencia, Innovación y Universidades FIS2017-88410-PEuropean Union’s Horizon 2020 (Grant Agreement No. 654002

Seleção genômica ampla para curvas de crescimento

Foi proposta uma metodologia para avaliação genética de curvas de crescimento considerando-se informações de marcadores SNPs (Single Nucleotide Polymorphisms). Em um primeiro passo foram ajustados modelos de crescimento não lineares (logístico) aos dados de peso-idade de cada animal, e em um segundo passo as estimativas dos parâmetros de tais modelos foram consideradas como fenótipos em um modelo de regressão (LASSO Bayesiano – BL) cujas covariáveis foram os genótipos dos marcadores SNPs. Este enfoque possibilitou estimar os valores genéticos genômicos (GBV) para peso em qualquer tempo da trajetória de crescimento, refletindo na confecção de curvas de crescimento genômicas, as quais permitiram a identificação de grupos de indivíduos geneticamente superiores em relação à eficiência de crescimento. Os dados simulados utilizados neste estudo foram constituídos de 2000 indivíduos (1000 na população de treinamento e 1000 na população de validação) contendo 453 marcadores SNPs distribuídos sobre cinco cromossomos. Os resultados indicaram a alta eficiência do método BL em predizer GBVs da população de validação com base na população de treinamento (coeficientes de correlação variaram entre 0,79 e 0,93), bem como a alta eficiência na detecção de QTLs, uma vez que os marcadores com maiores efeitos estimados encontravam-se em posições dos cromossomos próximas àquelas nas quais se encontravam os verdadeiros QTLs postulados na simulação.A methodology was proposed for the genetic evaluation of growth curves considering SNP (Single Nucleotide Polymorphisms) markers. At the first step, nonlinear regression growth models (Logistic) were fitted to the weight-age of each animal, and on second step the parameter estimates of the Logistic model were used as phenotype in a regression model (Bayesian LASSO - BL) which covariates were given by SNP genotypes. This approach allows the estimation of GBV (Genomic Breeding Values) for weight at either time of growth trajectory, allowing also the production of genomic growth curves, which selected groups of individuals with larger growth efficiency. The simulated data set was constituted of 2,000 individuals (being 1,000 in the training and 1,000 in the validation population) each one with 453 SNP markers distributed along 5 chromosomes. The results indicated high efficiency of the BL method to predict GBV in the validation population using information from the training population (correlation coefficients varying between 0.79 and 0.93). The BL also presented high efficiency to detect QTL, once the most expressive estimated SNP effects were located at positions closed to true QTL position fixed in the simulation