Is the porcine RN locus a pleiotropic QTL? A Bayesian marker assisted segregation analysis

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Evaluation of suitable reference genes for gene expression studies in porcine alveolar macrophages in response to LPS and LTA

<p>Abstract</p> <p>Background</p> <p>To obtain reliable quantitative real-time PCR data, normalization relative to stable housekeeping genes (HKGs) is required. However, in practice, expression levels of 'typical' housekeeping genes have been found to vary between tissues and under different experimental conditions. To date, validation studies of reference genes in pigs are relatively rare and have never been performed in porcine alveolar macrophages (AMs). In this study, expression stability of putative housekeeping genes were identified in the porcine AMs in response to the stimulation with two pathogen-associated molecular patterns (PAMPs) lipopolysaccharide (LPS) and lipoteichoic acid (LTA). Three different algorithms (geNorm, Normfinder and BestKeeper) were applied to assess the stability of HKGs.</p> <p>Results</p> <p>The mRNA expression stability of nine commonly used reference genes (<it>B2M, BLM, GAPDH, HPRT1, PPIA, RPL4, SDHA, TBP </it>and <it>YWHAZ</it>) was determined by qRT-PCR in AMs that were stimulated by LPS and LTA <it>in vitro</it>. mRNA expression levels of all genes were found to be affected by the type of stimulation and duration of the stimulation (<it>P </it>< 0.0001). geNorm software revealed that <it>SDHA, B2M </it>and <it>RPL4 </it>showed a high expression stability in the irrespective to the stimulation group, while <it>SDHA, YWHAZ </it>and <it>RPL4 </it>showed high stability in non-stimulated control group. In all cases, <it>GAPDH </it>showed the least stability in geNorm. NormFinder revealed that <it>SDHA </it>was the most stable gene in all the groups. Moreover, geNorm software suggested that the geometric mean of the three most stable genes would be the suitable combination for accurate normalization of gene expression study.</p> <p>Conclusions</p> <p>There was discrepancy in the ranking order of reference genes obtained by different analysing algorithms. In conclusion, the geometric mean of the <it>SDHA, YWHAZ </it>and <it>RPL4 </it>seemed to be the most appropriate combination of HKGs for accurate normalization of gene expression data in porcine AMs without knowing the type of bacterial pathogenic status of the animals.</p

Detection of quantitative trait loci affecting serum cholesterol, LDL, HDL, and triglyceride in pigs

<p>Abstract</p> <p>Background</p> <p>Serum lipids are associated with many serious cardiovascular diseases and obesity problems. Many quantitative trait loci (QTL) have been reported in the pig mostly for performance traits but very few for the serum lipid traits. In contrast, remarkable numbers of QTL are mapped for serum lipids in humans and mice. Therefore, the objective of this research was to investigate the chromosomal regions influencing the serum level of the total cholesterol (CT), triglyceride (TG), high density protein cholesterol (HDL) and low density protein cholesterol (LDL) in pigs. For this purpose, a total of 330 animals from a Duroc × Pietrain F2 resource population were phenotyped for serum lipids using ELISA and were genotyped by using 122 microsatellite markers covering all porcine autosomes for QTL study in QTL Express. Blood sampling was performed at approximately 175 days before slaughter of the pig.</p> <p>Results</p> <p>Most of the traits were correlated with each other and were influenced by average daily gain, slaughter date and age. A total of 18 QTL including three QTL with imprinting effect were identified on 11 different porcine autosomes. Most of the QTL reached to 5% chromosome-wide (CW) level significance including a QTL at 5% experiment-wide (GW) and a QTL at 1% GW level significance. Of these QTL four were identified for both the CT and LDL and two QTL were identified for both the TG and LDL. Moreover, three chromosomal regions were detected for the HDL/LDL ratio in this study. One QTL for HDL on SSC2 and two QTL for TG on SSC11 and 17 were detected with imprinting effect. The highly significant QTL (1% GW) was detected for LDL at 82 cM on SSC1, whereas significant QTL (5% GW) was identified for HDL/LDL on SSC1 at 87 cM. Chromosomal regions with pleiotropic effects were detected for correlated traits on SSC1, 7 and 12. Most of the QTL identified for serum lipid traits correspond with the previously reported QTL for similar traits in other mammals. Two novel QTL on SSC16 for HDL and HDL/LDL ratio and an imprinted QTL on SSS17 for TG were detected in the pig for the first time.</p> <p>Conclusion</p> <p>The newly identified QTL are potentially involved in lipid metabolism. The results of this work shed new light on the genetic background of serum lipid concentrations and these findings will be helpful to identify candidate genes in these QTL regions related to lipid metabolism and serum lipid concentrations in pigs.</p

Combined analysis of data from two granddaughter designs: A simple strategy for QTL confirmation and increasing experimental power in dairy cattle

A joint analysis of five paternal half-sib Holstein families that were part of two different granddaughter designs (ADR- or Inra-design) was carried out for five milk production traits and somatic cell score in order to conduct a QTL confirmation study and to increase the experimental power. Data were exchanged in a coded and standardised form. The combined data set (JOINT-design) consisted of on average 231 sires per grandsire. Genetic maps were calculated for 133 markers distributed over nine chromosomes. QTL analyses were performed separately for each design and each trait. The results revealed QTL for milk production on chromosome 14, for milk yield on chromosome 5, and for fat content on chromosome 19 in both the ADR- and the Inra-design (confirmed within this study). Some QTL could only be mapped in either the ADR- or in the Inra-design (not confirmed within this study). Additional QTL previously undetected in the single designs were mapped in the JOINT-design for fat yield (chromosome 19 and 26), protein yield (chromosome 26), protein content (chromosome 5), and somatic cell score (chromosome 2 and 19) with genomewide significance. This study demonstrated the potential benefits of a combined analysis of data from different granddaughter designs

A high-density linkage map of the RN region in pigs

The porcine RN locus affects muscle glycogen content and meat quality. We previously mapped the RN locus to chromosome 15. This study describes the identification of polymorphisms for four class I and four class II markers located in the RN region. Resource families were genotyped with F-SSCP markers (fluorescent single strand conformation polymorphism) and microsatellite markers. Subsequent multipoint linkage analysis revealed the order FN1-IGFBP5-S1000-S1001-IL8RB-VIL1-RN-Sw936-Sw906. The gene order is identical to the previously reported porcine RH map of the same region. The described map will facilitate positional cloning of the RN gene

Age-related changes in relative expression stability of commonly used housekeeping genes in selected porcine tissues

<p>Abstract</p> <p>Background</p> <p>Gene expression analysis using real-time RT-PCR (qRT-PCR) is increasingly important in biological research due to the high-throughput and accuracy of qRT-PCR. For accurate and reliable gene expression analysis, normalization of gene expression data against housekeeping genes or internal control genes is required. The stability of reference genes has a tremendous effect on the results of relative quantification of gene expression by qRT-PCR. The expression stability of reference genes could vary according to tissues, age of individuals and experimental conditions. In the pig however, very little information is available on the expression stability of reference genes. The aim of this research was therefore to develop a new set of reference genes which can be used for normalization of mRNA expression data of genes expressed in varieties of porcine tissues at different ages.</p> <p>Results</p> <p>The mRNA expression stability of nine commonly used reference genes (<it>B2M, BLM, GAPDH, HPRT1, PPIA, RPL4, SDHA, TBP </it>and <it>YWHAZ</it>) was determined in varieties of tissues collected from newborn, young and adult pigs. geNorm, NormFinder and BestKeeper software were used to rank the genes according to their stability. geNorm software revealed that <it>RPL4, PPIA </it>and <it>YWHAZ </it>showed high stability in newborn and adult pigs, while <it>B2M, YWHAZ </it>and <it>SDHA </it>showed high stability in young pigs. In all cases, <it>GAPDH </it>showed the least stability in geNorm. NormFinder revealed that <it>TBP </it>was the most stable gene in newborn and young pigs, while <it>PPIA </it>was most stable in adult pigs. Moreover, geNorm software suggested that the geometric mean of three most stable gene would be the suitable combination for accurate normalization of gene expression study.</p> <p>Conclusions</p> <p>Although, there was discrepancy in the ranking order of reference genes obtained by different analysing software methods, the geometric mean of the <it>RPL4, PPIA </it>and <it>YWHAZ </it>seems to be the most appropriate combination of housekeeping genes for accurate normalization of gene expression data in different porcine tissues at different ages.</p