Correlation of sperm parameters with fertility in two commercial pig lines

Background: One of the most important parameters to be considered in the assessment of male fertility or in the evaluation of methods to preserve sperm cells is the study of sperm viability. Considering that semen quality is of great importance for artificial insemination AI) in sows and for the production of an optimal number of piglets, complementary test results can be correlated with the number of piglets born after AI. The present study aimed to characterise the seminal pattern of breeding boars from two commercial lines and to correlate this pattern with the prolificacy of sows.Materials, Methods & Results: The reproductive performance of four boars from two commercial lines (A and B) was determined by evaluating physical and morphological semen parameters and by conducting a complementary analysis of semen. Semen was subjected to the following parameters: total sperm motility, sperm vigor, major sperm defects, minor sperm defects, and total sperm defects, in addition to complementary tests (supravital staining and hypoosmotic swelling tests). The semen was evaluated immediately after collection and every 12 h for up to 72 h of cold storage. A total of 163 breeding sows were inseminated. To evaluate sow prolificacy, the total number of piglets born was recorded. In general, the values obtained for the tests assessing sperm viability (particularly sperm motility and...(AU)

Correlation of sperm parameters with fertility in two commercial pig lines

Background: One of the most important parameters to be considered in the assessment of male fertility or in the evaluation of methods to preserve sperm cells is the study of sperm viability. Considering that semen quality is of great importance for artificial insemination AI) in sows and for the production of an optimal number of piglets, complementary test results can be correlated with the number of piglets born after AI. The present study aimed to characterise the seminal pattern of breeding boars from two commercial lines and to correlate this pattern with the prolificacy of sows.Materials, Methods & Results: The reproductive performance of four boars from two commercial lines (A and B) was determined by evaluating physical and morphological semen parameters and by conducting a complementary analysis of semen. Semen was subjected to the following parameters: total sperm motility, sperm vigor, major sperm defects, minor sperm defects, and total sperm defects, in addition to complementary tests (supravital staining and hypoosmotic swelling tests). The semen was evaluated immediately after collection and every 12 h for up to 72 h of cold storage. A total of 163 breeding sows were inseminated. To evaluate sow prolificacy, the total number of piglets born was recorded. In general, the values obtained for the tests assessing sperm viability (particularly sperm motility and...

Seleção genômica para características relacionadas ao odor da carne e características de carcaça em uma linhagem comercial de suínos / Genomic selection for boar taint and carcass traits in a commercial pig line

A partir do início do século XXI, avanços na genotipagem permitiram o desenvolvimento de novas classes de marcadores, entre os quais se destacam os polimorfismos de nucleotídeos simples (SNPs). Devido à disponibilidade desses marcadores, foi proposta a Seleção Genômica, que consiste em uma análise simultânea de um grande número de marcadores distribuídos ao longo do genoma, cujo sucesso depende do método utilizado de predição de valores genéticos genômicos. O objetivo deste estudo foi comparar os métodos RR-BLUP e LASSO Bayesiano para cálculo dos valores genéticos genômicos estimados (GEBVs) e determinar qual método apresenta resultados mais acurados para a seleção genômica em suínos. Foram genotipados 622 suínos machos não castrados para 2.500 SNPs, e fenotipados para as seguintes características: concentração de androstenona, concentração de skatol, espessura de gordura subcutânea e profundidade de lombo. Os pacotes rrBLUP e BLR do software R foram utilizados respectivamente para a implementação do método RR-BLUP e LASSO Bayesiano. As correlações genéticas entre as característicasforam calculadas por meio da correlação entre os vetores de GEBVs. O método LASSO Bayesiano apresentou valores mais elevados de acurácia em três características: concentração de androstenona (0,65), concentração deskatol (0,58), e profundidade de lombo (0,33), e o RR-BLUP foi mais acurado para espessura de gordura subcutânea (0,61). As correlações genéticas calculadas, mostram que existe uma pequena correlação genética entre espessura de gordura subcutânea e profundidade de lombo (0,03). Entre as concentrações de androstenona e skatol também existe correlação genética (0,24) que é consistente com os resultados de outros estudos. Assim, com relação às estimativas de efeitos de marcadores, para todas as características os picos encontrados estão em regiões onde se encontram QTLs relatados no PIGQTLdatabase e em outros estudos

From the beginning of the century, advances in genotyping enabled the development of new classes of markers, among which stand out single nucleotide polymorphisms (SNPs). Due to the availability of these markers it has been proposed genomic selection, consisting of simultaneous analysis of large number of markers distributed throughout the genome; its success depends on the method used for prediction of genomic breeding values. The objective of this study was to compare the methods RR-BLUP and Bayesian LASSO to calculate estimated genomic breeding values (GEBVs) and also to determine which method provides more accurate results for genomic selection in pigs. A total of 622 boarswere genotyped for 2,500 SNPs, and phenotyped for the following traits: concentration of androstenone, concentration of skatole, backfat thickness and loin depth. The R software packages rrBLUP and BLR were used respectively for the implementation of the RR-BLUP method and Bayesian LASSO method. Genetic correlations between the traits were calculated by the correlation between the vectors of GEBVs. The Bayesian LASSO method reached higher accuracy values in three traits: concentration of androstenone (0.65), concentration of skatole (0.58) and loin depth (0.33), and RR-BLUP was more accurate (0.61) for backfat thickness. Genetic correlations calculated, show that exists a small genetic correlation (0.03) between backfat thickness and loin depth. Between the concentrations of androstenone and skatole also exists a genetic correlation (0.24)that is consistent with results from other studies. Thus, concerning to the estimates of effects of markers, for all traits the found peaks were in regions where are reported QTLs inPIGQTLdatabase and other studies