Revisiting the Pig IGHC Gene Locus in Different Breeds Uncovers Nine Distinct IGHG Genes.

IgG subclass diversification is common in placental mammals. It has been well documented in humans and mice that different IgG subclasses, with diversified functions, synergistically regulate humoral immunity. However, our knowledge on the genomic and functional diversification of IgG subclasses in the pig, a mammalian species with high agricultural and biomedical importance, is incomplete. Using bacterial artificial chromosome sequencing and newly assembled genomes generated by the PacBio sequencing approach, we characterized and mapped the IgH C region gene locus in three indigenous Chinese breeds (Erhualian, Xiang, and Luchuan) and compared them to that of Duroc. Our data revealed that IGHG genes in Chinese pigs differ from the Duroc, whereas the IGHM, IGHD, IGHA, and IGHE genes were all single copy and highly conserved in the pig breeds examined. Most striking were differences in numbers of IGHG genes: there are seven genes in Erhualian pigs, six in the Duroc, but only five in Xiang pigs. Phylogenetic analysis suggested that all reported porcine IGHG genes could be classified into nine subclasses: IGHG1, IGHG2a, IGHG2b, IGHG2c, IGHG3, IGHG4, IGHG5a, IGHG5b, and IGHG5c. Using sequence information, we developed a mouse mAb specific for IgG3. This study offers a starting point to investigate the structure-function relationship of IgG subclasses in pigs.

Model parameters of molecular evolution explain genomic correlations.

One long-standing research focus in evolutionary genomics is trying to resolve how biological variables (expression, essentiality, protein-protein interaction, structural stability, etc.) determine the rate of protein evolution. While these studies have considerably deepened our understanding of molecular evolution, many issues remain unsolved. In this opinion article, after having a brief survey of literatures, we establish relationships between model parameters of molecular evolution and genomic variables, based on which, most-observed genomic correlations and confounds can be explained by model parameter combinations under different conditions, which include the strength of stabilizing selection, mutational variance, expression sufficiency, gene pleiotropy, as well as the effective population size. We suggest that the problem to discern biological variable(s) that may determine the rate of protein evolution can be tackled at two levels. The first level, as discussed here, is to demonstrate how the model of molecular evolution can predict potential genomic correlations under various conditions. And the second level is to estimate genome-wide variations of model parameters (or combinations) that help to identify canonical biological variables that may underlie the rate variation among genes that ranges up to at least three magnitudes.

Use of NTRIP for optimizing the decoding algorithm for real-time data streams.

As a network transmission protocol, Networked Transport of RTCM via Internet Protocol (NTRIP) is widely used in GPS and Global Orbiting Navigational Satellite System (GLONASS) Augmentation systems, such as Continuous Operational Reference System (CORS), Wide Area Augmentation System (WAAS) and Satellite Based Augmentation Systems (SBAS). With the deployment of BeiDou Navigation Satellite system(BDS) to serve the Asia-Pacific region, there are increasing needs for ground monitoring of the BeiDou Navigation Satellite system and the development of the high-precision real-time BeiDou products. This paper aims to optimize the decoding algorithm of NTRIP Client data streams and the user authentication strategies of the NTRIP Caster based on NTRIP. The proposed method greatly enhances the handling efficiency and significantly reduces the data transmission delay compared with the Federal Agency for Cartography and Geodesy (BKG) NTRIP. Meanwhile, a transcoding method is proposed to facilitate the data transformation from the BINary EXchange (BINEX) format to the RTCM format. The transformation scheme thus solves the problem of handing real-time data streams from Trimble receivers in the BeiDou Navigation Satellite System indigenously developed by China.

A high-throughput screen for genes essential for PRRSV infection using a piggyBac-based system.

In this study, using a dual-functional, piggyBac transposon-based system, we developed a method to systematically decipher the host genes that may be associated with porcine reproductive and respiratory syndrome virus (PRRSV) infection. A Marc145 cell library, which was randomly mutated by transfecting piggyBac plasmids, was challenged with PRRSV. The surviving cell clones were subjected to inverse PCR and high-throughput sequencing to map the integration sites of the transposon. Detailed annotation of the genes flanking the integration sites allowed us to generate a ranked list of candidate genes. Among the predicted genes with a high priority, four genes, CDK17, RNF168, BCL2L15, and TRIM33, were strongly correlated with PRRSV infection in both Marc145 cells and porcine primary alveolar macrophages. This study not only assists in identifying the genes essential for PRRSV infection but also confirms the possibility of using the piggyBac system to study other virus-host genetic interactions in a high-throughput manner.