There is a need for genetic markers or biomarkers that can predict resistance towards a wide range of infectious diseases, especially within a health environment typical of commercial farms. Such markers also need to be heritable under these conditions and ideally correlate with commercial performance traits. In this study, we estimated the heritabilities of a wide range of immune traits, as potential biomarkers, and measured their relationship with performance within both specific pathogen-free (SPF) and non-SPF environments. Immune traits were measured in 674 SPF pigs and 606 non-SPF pigs, which were subsets of the populations for which we had performance measurements (average daily gain), viz. 1549 SPF pigs and 1093 non-SPF pigs. Immune traits measured included total and differential white blood cell counts, peripheral blood mononuclear leucocyte (PBML) subsets (CD4+ cells, total CD8α+ cells, classical CD8αβ+ cells, CD11R1+ cells (CD8α+ and CD8α-), B cells, monocytes and CD16+ cells) and acute phase proteins (alpha-1 acid glycoprotein (AGP), haptoglobin, C-reactive protein (CRP) and transthyretin). Nearly all traits tested were heritable regardless of health status, although the heritability estimate for average daily gain was lower under non-SPF conditions. There were also negative genetic correlations between performance and the following immune traits: CD11R1+ cells, monocytes and the acute phase protein AGP. The strength of the association between performance and AGP was not affected by health status. However, negative genetic correlations were only apparent between performance and monocytes under SPF conditions and between performance and CD11R1+ cells under non-SPF conditions. Although we cannot infer causality in these relationships, these results suggest a role for using some immune traits, particularly CD11R1+ cells or AGP concentrations, as predictors of pig performance under the lower health status conditions associated with commercial farms.
Differential display PCR (ddPCR) and complementary DNA microarray analyses were used to evaluate gene expression differences in porcine ovarian follicles between a line of pigs selected for an index of ovulation rate and embryo survival (Line I) and its randomly selected control line (Line C). Follicles (4.0 to 7.0 mm) were dissected from ovaries of multiparous sows (n = 27) at either 2 or 4 d following PGF 2α analog injection on d 12 to 14 of the estrous cycle. Using ddPCR, differentially expressed bands (n = 282) were excised from gels and 107 were sequenced, yielding 84 unique porcine follicle expressed sequence tags. Northern hybridization confirmed differential expression (between lines, days, or follicle sizes) for messenger RNA representing the calpain I light subunit, cytochrome C oxidase subunit III, cytochrome P450 aromatase, and cytochrome P450 side chain cleavage genes. For microarray analysis, two mRNA pools representing follicles (d 2; 4.50 to 4.75 mm) from Line I and Line C sows were hybridized to the Incyte UniGEM V1.0 human chip (approximately 7,000 gene probes). A second analysis
Ankyrin 1 (ANK1) is a positional and functional candidate gene for both bovine and porcine meat quality. The objectives of this study were: (1) to determine if the gene expression levels of ANK1 are associated with pig meat quality traits; (2) to examine polymorphisms in the promoter region of the porcine ANK1 gene for association with meat quality in diverse breeds; and (3) to search for putative transcription factor binding sites predicted to be altered by such polymorphisms. ANK1 gene expression was positively correlated with drip loss (%) in the Large White breed. Twelve novel SNPs were discovered in a 761 bp region of the ANK1 promoter in three phenotypically diverse F1 cross populations. Five were subsequently selected for association analysis with meat quality traits and genotyped in three pure pig breeds (Pietrain n = 98, Duroc n = 99 and Large White n = 98). Two of these five SNPs were associated with meat quality traits at the Bonferroni significance threshold: g.-606G>A with drip loss % in the Pietrain breed and g.-272G>A with intramuscular fat (IMF) in the LTL and SM. Following haplotype construction from SNP genotypes, Haplotype 3 was found to be associated with drip loss % at the Bonferroni level of significance in the Pietrain breed and Haplotype 5 was associated at the Bonferroni level with IMF in two muscles in the Large White breed. Further associations were observed at the nominal significance threshold. Our conclusion from this study is that SNPs in the ANK1 gene promoter could potentially contribute to genome-assisted selection SNP panels to improve IMF and water holding capacity on a breed basis.
ABSTRACT:The objective of this study was to identify differentially expressed genes in the anterior pituitary (AP) of sows selected for enhanced reproductive phenotypes. Selection in the Index (I) line was based on an index of ovulation rate and embryo survival, whereas random selection was used in the Control (C) line. Average numbers of fully formed piglets at birth were 12.5 ± 1.5 and 9.9 ± 2.0 for Line I and C sows used in this study, respectively. In order to induce luteolysis and synchronize follicle development, sows were injected (i.m.) with 2 mL of prostaglandin F 2α analog between d 12 and 14 of the estrous cycle. Tissue was harvested 2 d (d2) or 4 d (d4) after injection, resulting in four experimental groups: Cd2 (n = 6), Cd4 (n = 4), Id2 (n = 6), and Id4 (n = 7). Differential display PCR (ddPCR)
Health is one of the most important contributors to animal welfare, productivity and profitability in pig production today. For the past 30 years, pig breeders have focused on genetic improvement of lean growth, feed efficiency, meat quality and reproduction. However, in recent years, selection objectives have been broadened to include livability, robustness and disease resistance. A DNA marker for selection of resistance to F18+ E. coli has been available for several years. This marker decreases mortality and improves growth on farms experiencing post-weaning scours and/or oedema disease. However, for most diseases affecting intensive production systems such as porcine reproductive and respiratory syndrome (PRRS), porcine circovirus type 2-associated diseases (PCVAD), Haemophilus parasuis, and swine influenza virus, resistance is a complex and polygenic trait. Selection for improved resistance to these diseases will be incremental and require use of multiple markers in complex breeding schemes. Novel technologies such as pig gene microarrays, single nucleotide polymorphism (SNP) panels and advanced bioinformatics are being used to identify new health candidate genes for these economically important diseases. Lagging behind, however, is availability of large DNAdatasets from pedigreed populations with accurately measured health phenotypes that are needed to identify associations between SNPs and health traits. Increased focus on datasets with health traits will be the key to finding useable discoveries with new genomics technologies. Currently, the industry uses dozens of SNP markers to increase the accuracy of selection for complex breeding objectives, including disease resistance. As the pig genome is sequenced and barriers to genotyping thousand of markers are eliminated, genomic selection for health traits will receive increasing attention from commercial breeders.
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