E-GWAS: an ensemble-like GWAS strategy that provides effective control over false positive rates without decreasing true positives.

BACKGROUND: Genome-wide association studies (GWAS) are an effective way to explore genotype-phenotype associations in humans, animals, and plants. Various GWAS methods have been developed based on different genetic or statistical assumptions. However, no single method is optimal for all traits and, for many traits, the putative single nucleotide polymorphisms (SNPs) that are detected by the different methods do not entirely overlap due to the diversity of the genetic architecture of complex traits. Therefore, multi-tool-based GWAS strategies that combine different methods have been increasingly employed. To take this one step further, we propose an ensemble-like GWAS strategy (E-GWAS) that statistically integrates GWAS results from different single GWAS methods. RESULTS: E-GWAS was compared with various single GWAS methods using simulated phenotype traits with different genetic architectures. E-GWAS performed stably across traits with different genetic architectures and effectively controlled the number of false positive genetic variants detected without decreasing the number of true positive variants. In addition, its performance could be further improved by using a bin-merged strategy and the addition of more distinct single GWAS methods. Our results show that the numbers of true and false positive SNPs detected by the E-GWAS strategy slightly increased and decreased, respectively, with increasing bin size and when the number and the diversity of individual GWAS methods that were integrated in E-GWAS increased, the latter being more effective than the bin-merged strategy. The E-GWAS strategy was also applied to a real dataset to study backfat thickness in a pig population, and 10 candidate genes related to this trait and expressed in adipose-associated tissues were identified. CONCLUSIONS: Using both simulated and real datasets, we show that E-GWAS is a reliable and robust strategy that effectively integrates the GWAS results of different methods and reduces the number of false positive SNPs without decreasing that of true positive SNPs.

Endometrial gene expression profiling in pregnant Meishan and Yorkshire pigs on day 12 of gestation.

BACKGROUND: Litter size in pigs is a major factor affecting the profitability in the pig industry. The peri-implantation window in pigs is characterized by the coordinated interactions between the maternal uterine endometrium and the rapidly elongating conceptuses and represents a period of time during which a large percentage of the developing conceptuses are lost. However, the gene expression and regulatory networks in the endometrium contributing to the establishment of the maternal: placental interface remain poorly understood. RESULTS: We characterized the endometrial gene expression profile during the peri-implantation stage of development by comparing two breeds that demonstrate very different reproductive efficiencies. We employed the porcine Affymetrix GeneChip® to assay the transcriptomic profiles of genes expressed in the uterine endometrium obtained from Meishan and Yorkshire gilts (n = 4 for each breed) on day 12 of gestation (M12 and Y12, respectively). Total of 17,076 probesets were identified as "present" in at least two arrays. A mixed model-based statistical analysis predicted a total of 2,656 (q < 0.1) transcripts as differentially expressed between Meishan and Yorkshire pigs. Eighteen differentially expressed transcripts of interest were validated by quantitative real-time PCR. Gene ontology (GO) annotation revealed that the known functions of the differentially expressed genes were involved in a series of important biological processes relevant to early pregnancy establishment in the pig. CONCLUSIONS: The results identified endometrial gene expression profiles of two breeds differing in litter size and identified candidate genes that are related to known physiological pathways related to reproductive prolificacy. These findings provide a deeper understanding of molecular pathways differing between two breeds at the critical peri-implantation stage of pregnancy, which can be utilized to better understand the events contributing to pregnancy establishment in the pig.

Systems infection biology: a compartmentalized immune network of pig spleen challenged with Haemophilus parasuis.

BACKGROUND: Network biology (systems biology) approaches are useful tools for elucidating the host infection processes that often accompany complex immune networks. Although many studies have recently focused on Haemophilus parasuis, a model of Gram-negative bacterium, little attention has been paid to the host's immune response to infection. In this article, we use network biology to investigate infection with Haemophilus parasuis in an in vivo pig model. RESULTS: By targeting the spleen immunogenome, we established an expression signature indicative of H. parasuis infection using a PCA/GSEA combined method. We reconstructed the immune network and estimated the network topology parameters that characterize the immunogene expressions in response to H. parasuis infection. The results showed that the immune network of H. parasuis infection is compartmentalized (not globally linked). Statistical analysis revealed that the reconstructed network is scale-free but not small-world. Based on the quantitative topological prioritization, we inferred that the C1R-centered clique might play a vital role in responding to H. parasuis infection. CONCLUSIONS: Here, we provide the first report of reconstruction of the immune network in H. parasuis-infected porcine spleen. The distinguishing feature of our work is the focus on utilizing the immunogenome for a network biology-oriented analysis. Our findings complement and extend the frontiers of knowledge of host infection biology for H. parasuis and also provide a new clue for systems infection biology of Gram-negative bacilli in mammals.

Molecular characterization of caveolin-1 in pigs infected with Haemophilus parasuis.

Caveolin-1 (Cav1) plays a critical role in the invasion of pathogenic microbes into host cells, yet little is known about porcine Cav1. In this study, we provide the molecular characterization of Cav1 in pigs following stimulation with LPS/polyinosinic-polycytidylic acid as well as during infection with Haemophilus parasuis. The porcine Cav1 gene is 35 kb long and is located at SSC18q21; two isoforms (Cav1-α and Cav1-ß) are produced by alternative splicing. Three point mutations were identified in the coding region of the gene, two of which were significantly associated with nine immunological parameters in Landrace pigs, including the Ab response against porcine reproductive and respiratory syndrome virus and lymphocyte counts. Promoter analysis indicated that NF-κB activates both Cav1 transcripts, but the forkhead gene family specifically regulates Cav1-ß in the pig. Porcine Cav1 is expressed ubiquitously, with Cav1-α more abundantly expressed than Cav1-ß in all tissues investigated. Basal expression levels of Cav1 in PBMCs are relatively similar across different pig breeds. LPS and polyinosinic-polycytidylic acid markedly induced the expression of Cav1 in porcine kidney-15 cells in vitro, likely through NF-κB activation. Pigs infected with H. parasuis exhibited decreased expression of Cav1, particularly in seriously impaired organs such as the brain. This study provides new evidence that supports the use of Cav1 as a potential diagnostic and genetic marker for disease resistance in animal breeding. In addition, our results suggest that Cav1 may be implicated in the pathogenesis of Glasser's disease, which is caused by H. parasuis.

Digital candidate gene approach (DigiCGA) for identification of cancer genes.

The candidate gene approach is one of the most commonly used methods for identifying genes underlying disease traits. Advances in genomics have greatly contributed to the development of this approach in the past decade. More recently, with the explosion of genomic resources accessible via the public Web, digital candidate gene approach (DigiCGA) has emerged as a new development in this field. DigiCGA, an approach still in its infancy, has already achieved some primary success in cancer gene discovery. However, a detailed discussion concerning the applications of DigiCGA in cancer gene identification has not been addressed. This chapter will focus on discussing DigiCGA in a generalized sense and its applications to the identification of cancer genes, including the cancer gene resources, application status, platform and tools, challenges, and prospects.

Molecular characterization and association analysis with production traits of the porcine INPP5F gene.

Inositol polyphosphate-5-phosphatase F (INPP5F) is one of the largest families of phosphoinositide phosphatases, 5-phosphatase. It contains a Sac domain whose amino acids are essential for inositol polyphosphate phosphatase activities. Here, we assigned the porcine INPP5F to SSC14q29 by using SCHP and IMpRH. Sequencing of PCR products from different breeds identified an A/G polymorphism in the last exon. The allele frequencies of this SNP showed that the Yorkshire and Duroc pigs have high G allele frequency, whereas the local pigs have high A allele frequency. Association analysis of the genotypes with growth and carcass traits found that different genotypes of INPP5F have significant differences in average daily gain (ADG) (P < 0.05) in Yorkshire pigs.

Discovery of porcine microRNAs and profiling from skeletal muscle tissues during development.

MiRNAs (microRNAs) play critical roles in many important biological processes such as growth and development in mammals. In this study, we identified hundreds of porcine miRNA candidates through in silico prediction and analyzed their expression in developing skeletal muscle using microarray. Microarray screening using RNA samples prepared from a 33-day whole embryo and an extra embryo membrane validated 296 of the predicted candidates. Comparative expression profiling across samples of longissimus muscle collected from 33-day and 65-day post-gestation fetuses, as well as adult pigs, identified 140 differentially expressed miRNAs amongst the age groups investigated. The differentially expressed miRNAs showed seven distinctive types of expression patterns, suggesting possible involvement in certain biological processes. Five of the differentially expressed miRNAs were validated using real-time PCR. In silico analysis of the miRNA-mRNA interaction sites suggested that the potential mRNA targets of the differentially expressed miRNAs may play important roles in muscle growth and development.

[Progress in porky genes and transcriptome and discussion of relative issues].

To date, research on molecular base of porky molecular development was mainly involved in muscle growth and meat quality. Some functional genes including Hal gene and RN gene and some QTLs controlling or associated with porky growth and quality were detected through candidate gene approach and genome-wide scanning. Genic transcriptome pertinent to porcine muscle and adipose also came into study. At the same time, these researches have befallen some shortcomings to some extent. Research from molecular quantitative genetics showed shortcomings that single gene was devilishly emphasized and co-expression pattern of multi-genes was ignored. Research applying transcriptome analysis tool also met two of limitations, one was the singleness of type of molecular experimental techniques, and another was that genes of muscle and adipose were artificially divided into unattached two parts. Thus, porky genes were explored by parallel genetics based on systemic views and techniques to specially reveal the interactional mechanism of porky genes respectively controlling muscle and adipose, which would be important issues of genes and genome researches on porky development in the near future.

[Characterization of novel alleles and new mutation sites of porcine MHC class II DQA].

The primers, DQAp161 and DQAp443, were designed based on the homologous region of SLA-DQA cDNA sequences and HLA-DQA genomic sequences. The 731 bp fragment of SLA-DQA including completed intron 2, the near completed exon 2 and partial exon 3 was obtained by PCR. The nucleotide sequences of the fragment of SLA-DQA were obtained with cloning and direct sequencing. Both nucleotide sequences of exon 2 and amino acid sequences of alpha 1 domain were analyzed in a pedigree. The sequence data were compared with all sequences of SLA-DQA exon 2 in GenBank. Two novel alleles, DQA-SLT 26 and DQA-TC 21-1, were found according to the above analyses. Four amino acid changes were observed among SLA-DQA haplotype c, d and DQA-SLT 26. They were Val-->Ala(60), Lys-->Glu(65), Asp-->Gly(81) and Lys-->Ile(93). Comparing the amino acids sequence of the all SLA-DQA sequences with DQA-TC 21-1 revealed that the His (94) was changed into Tyr.

Genetic relationships among twelve Chinese indigenous goat populations based on microsatellite analysis.

Twelve Chinese indigenous goat populations were genotyped for twenty-six microsatellite markers recommended by the EU Sheep and Goat Biodiversity Project. A total of 452 goats were tested. Seventeen of the 26 microsatellite markers used in this analysis had four or more alleles. The mean expected heterozygosity and the mean observed heterozygosity for the population varied from 0.611 to 0.784 and 0.602 to 0.783 respectively. The mean FST (0.105) demonstrated that about 89.5% of the total genetic variation was due to the genetic differentiation within each population. A phylogenetic tree based on the Nei (1978) standard genetic distance displayed a remarkable degree of consistency with their different geographical origins and their presumed migration throughout China. The correspondence analysis did not only distinguish population groups, but also confirmed the above results, classifying the important populations contributing to diversity. Additionally, some specific alleles were shown to be important in the construction of the population structure. The study analyzed the recent origins of these populations and contributed to the knowledge and genetic characterization of Chinese indigenous goat populations. In addition, the seventeen microsatellites recommended by the EU Sheep and Goat Biodiversity Project proved to be useful for the biodiversity studies in goat breeds.