Understanding Haemophilus parasuis infection in porcine spleen through a transcriptomics approach

<p>Abstract</p> <p>Background</p> <p><it>Haemophilus parasuis </it>(HPS) is an important swine pathogen that causes Glässer's disease, which is characterized by fibrinous polyserositis, meningitis and arthritis. The molecular mechanisms that underlie the pathogenesis of the disease remain poorly understood, particularly the resistance of porcine immune system to HPS invasion. In this study, we investigated the global changes in gene expression in the spleen following HPS infection using the Affymetrix Porcine Genechip™.</p> <p>Results</p> <p>A total of 931 differentially expressed (DE) transcripts were identified in the porcine spleen 7 days after HPS infection; of these, 92 unique genes showed differential expression patterns based on analysis using BLASTX and Gene Ontology. The DE genes involved in the immune response included genes for inflammasomes (<it>RETN</it>, <it>S100A8</it>, <it>S100A9</it>, <it>S100A12</it>), adhesion molecules (<it>CLDN3</it>, <it>CSPG2</it>, <it>CD44</it>, <it>LGALS8</it>), transcription factors (<it>ZBTB16</it>, <it>SLC39A14</it>, <it>CEBPD</it>, <it>CEBPB</it>), acute-phase proteins and complement (<it>SAA1</it>, <it>LTF</it>, <it>HP</it>, <it>C3</it>), differentiation genes for epithelial cells and keratinocytes (<it>TGM1</it>, <it>MS4A8B</it>, <it>CSTA</it>), and genes related to antigen processing and presentation (<it>HLA-B</it>, <it>HLA-DRB1</it>). Further immunostimulation analyses indicated that mRNA levels of <it>S100A8</it>, <it>S100A9</it>, and <it>S100A12 </it>in porcine PK-15 cells increased within 48 h and were sustained after administration of lipopolysaccharide (LPS) and Poly(I:C) respectively. In addition, mapping of DE genes to porcine health traits QTL regions showed that 70 genes were distributed in 7 different known porcine QTL regions. Finally, 10 DE genes were validated by quantitative PCR.</p> <p>Conclusion</p> <p>Our findings demonstrate previously unrecognized changes in gene transcription that are associated with HPS infection <it>in vivo</it>, and many potential cascades identified in the study clearly merit further investigation. Our data provide new clues to the nature of the immune response in mammals, and we have identified candidate genes that are related to resistance to HPS.</p

LongSAGE analysis of skeletal muscle at three prenatal stages in Tongcheng and Landrace pigs

Transcriptional profiling of Tongcheng and Landrace pigs using long serial analysis of gene expression provides insight into the molecular mechanism underlying differences in muscle growth

Genome-Wide Association Study Reveals Candidate Genes for Growth Relevant Traits in Pigs

Improvement of the growth rate is a challenge in the pig industry, the Average Daily Gain (ADG) and Days (AGE) to 100 kg are directly related to growth performance. We performed genome-wide association study (GWAS) and genetic parameters estimation for ADG and AGE using the genomic and phonemic from four breed (Duroc, Yorkshire, Landrace, and Pietrain) populations. All analyses were performed by a multi-loci GWAS model, FarmCPU. The GWAS results of all four breeds indicate that five genome-wide significant SNPs were associated with ADG, and the nearby genomic regions explained 4.08% of the genetic variance and 1.90% of the phenotypic variance, respectively. For AGE, six genome-wide significant SNPs were detected, and the nearby genomic regions explained 8.09% of the genetic variance and 3.52% of phenotypic variance, respectively. In total, nine candidate genes were identified to be associated with growth and metabolism. Among them, TRIB3 was reported to associate with pig growth, GRP, TTR, CNR1, GLP1R, BRD2, HCRTR2, SEC11C, and ssc-mir-122 were reported to associate with growth traits in human and mouse. The newly detected candidate genes will advance the understanding of growth related traits and the identification of the novel variants will suggest a potential use in pig genomic breeding programs

Importance of interfaces in hybrid perovskite solar cells

Photovoltaic devices based on hybrid organic-inorganic perovskite absorbers have reached outstanding performance over the past few years, surpassing power conversion efficiency of over 22%. In this talk we discuss the role of the interface in optimizing device performance as measured by both power conversion efficiency and stability. We present an examination of different perovskite active layers and interfacial electronic structure of these remarkable materials with functional oxide and organic contact layers. Interface formation of the active layer with different carrier transport materials has direct implications for performance of the resulting devices. We present interface studies, which permit identification of charge transfer mechanisms across the interface with chemical specificity and insight into the requirements for realizing high performance devices. Our findings from surface science approaches are combined with time resolved spectroscopy, structural studies and device level studies to validate impacts on carrier dynamics and demonstrate their technological relevance of interfacial insights

Electron and hole drift mobility measurements on methylammonium lead iodide perovskite solar cells

We report nanosecond domain time-of-flight measurements of electron and hole photocarriers in methylammonium lead iodide perovskite solar cells. The mobilities ranged from 0.06 to 1.4 cm2/Vs at room temperature, but there is little systematic difference between the two carriers. We also find that the drift mobilities are dispersive (time-dependent). The dispersion parameters are in the range of 0.4–0.7, and they imply that terahertz domain mobilities will be much larger than nanosecond domain mobilities. The temperature-dependences of the dispersion parameters are consistent with confinement of electron and hole transport to fractal-like spatial networks within nanoseconds of their photogeneration

Candidate Gene Identification Approach: Progress and Challenges

Although it has been widely applied in identification of genes responsible for biomedically, economically, or even evolutionarily important complex and quantitative traits, traditional candidate gene approach is largely limited by its reliance on the priori knowledge about the physiological, biochemical or functional aspects of possible candidates. Such limitation results in a fatal information bottleneck, which has apparently become an obstacle for further applications of traditional candidate gene approach on many occasions. While the identification of candidate genes involved in genetic traits of specific interest remains a challenge, significant progress in this subject has been achieved in the last few years. Several strategies have been developed, or being developed, to break the barrier of information bottleneck. Recently, being a new developing method of candidate gene approach, digital candidate gene approach (DigiCGA) has emerged and been primarily applied to identify potential candidate genes in some studies. This review summarizes the progress, application software, online tools, and challenges related to this approach.</p

Understanding Quantitative Genetics in the Systems Biology Era

Biology is now entering the new era of systems biology and exerting a growing influence on the future development of various disciplines within life sciences. In early classical and molecular periods of Biology, the theoretical frames of classical and molecular quantitative genetics have been systematically established, respectively. With the new advent of systems biology, there is occurring a paradigm shift in the field of quantitative genetics. Where and how the quantitative genetics would develop after having undergone its classical and molecular periods? This is a difficult question to answer exactly. In this perspective article, the major effort was made to discuss the possible development of quantitative genetics in the systems biology era, and for which there is a high potentiality to develop towards &#34;systems quantitative genetics&#34;. In our opinion, the systems quantitative genetics can be defined as a new discipline to address the generalized genetic laws of bioalleles controlling the heritable phenotypes of complex traits following a new dynamic network model. Other issues from quantitative genetic perspective relating to the genetical genomics, the updates of network model, and the future research prospects were also discussed.</p