QTL analysis of production traits on SSC3 in a Large White×Meishan pig resource family

In order to locate the genetic regions that are responsible for economically important traits, a resource population was established by crossing Large White boars and Meishan sows. Phenotypic data of a total of 287 F2 offspring were collected from 1998 to 2000 and QTL analysis conducted using nine microsatellites on Sus scrofa chromosome 3 (SSC3). Least square regression interval mapping revealed two significant QTL effects on dressing percentage and moisture in m. longissimus dorsi, respectively. They were located at 136 cM and 22 cM in the genetic linkage map, near the marker Sw349 and Swr1637, respectively. QTL for dressing percentage had an additive effect of -1.035 ± 0.296% and a dominance effect of 1.056 ± 0.481%, and the explained phenotypic variance was 15.9%. The additive and dominance effects of QTL for moisture in m. longissimus dorsi were -0.025 ± 0.076% and 0.365 ± 0.101%, respectively, indicating that this QTL seemed to be significantly dominant in action. The present study confirms previously identified QTL and provides an important step in the search for the actual major genes involved in the traits of economic interest. South African Journal of Animal Science Vol. 36(2) 2006: 122-12

Polymorphism of the pig-implantation protein 3 (preis3) gene and its association with litter size traits

The pre-implantation protein 3 (prei3), which might play a role in pre-implantation embryogenesis, is one of the promising candidate genes for litter size traits in pigs. In this study, a single nucleotide polymorphism (SNP: T802G) in intron 6 of the pig prei3 gene was detected and a genotyping assay for this SNP was developed. An association study for this SNP with litter size was performed in two independent populations. One population consisted of crossbred sows derived from Landrace, Large White, Chinese Tongcheng and/or Chinese Meishan (Line DIV). The other population constituted of crossbred animals derived from Chinese Qingping and Duroc (QD). Statistical analysis demonstrated that, in first parity, 2.65 more piglets were born and 3.82 more piglets were born alive in sows in Line DIV with genotype TT than with genotype GG. For second and subsequent litters, in both the DIV and QD lines there were significant differences in the number of piglets born alive between TG and GG sows, with the TG sows producing more piglets born alive than the GG sows. These results suggest that the prei3 SNP is significantly associated with litter size in the two populations studied, and could be useful in selection for increasing litter size in pigs. Further investigations on more pig populations with large sample sizes are needed to confirm this. South African Journal of Animal Science Vol. 36(3) 2006: 209-21

PRED_PPI: a server for predicting protein-protein interactions based on sequence data with probability assignment

<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions (PPIs) are crucial for almost all cellular processes, including metabolic cycles, DNA transcription and replication, and signaling cascades. Given the importance of PPIs, several methods have been developed to detect them. Since the experimental methods are time-consuming and expensive, developing computational methods for effectively identifying PPIs is of great practical significance.</p> <p>Findings</p> <p>Most previous methods were developed for predicting PPIs in only one species, and do not account for probability estimations. In this work, a relatively comprehensive prediction system was developed, based on a support vector machine (SVM), for predicting PPIs in five organisms, specifically humans, yeast, <it>Drosophila</it>, <it>Escherichia coli</it>, and <it>Caenorhabditis elegans</it>. This PPI predictor includes the probability of its prediction in the output, so it can be used to assess the confidence of each SVM prediction by the probability assignment. Using a probability of 0.5 as the threshold for assigning class labels, the method had an average accuracy for detecting protein interactions of 90.67% for humans, 88.99% for yeast, 90.09% for <it>Drosophila</it>, 92.73% for <it>E. coli</it>, and 97.51% for <it>C. elegans</it>. Moreover, among the correctly predicted pairs, more than 80% were predicted with a high probability of ≥0.8, indicating that this tool could predict novel PPIs with high confidence.</p> <p>Conclusions</p> <p>Based on this work, a web-based system, Pred_PPI, was constructed for predicting PPIs from the five organisms. Users can predict novel PPIs and obtain a probability value about the prediction using this tool. Pred_PPI is freely available at <url>http://cic.scu.edu.cn/bioinformatics/predict_ppi/default.html</url>.</p

New insight into kinetics behavor of the structural formation process in Agar gelation

A time-resolved experimental study on the kinetics and relaxation of the structural formation process in gelling Agar-water solutions was carried out using our custom-built torsion resonator. The study was based on measurements of three naturally cooled solutions with agar concentrations of 0.75%, 1.0% and 2.0% w/w. It was found that the natural-cooling agar gelation process could be divided into three stages, sol stage (Stage I), gelation zone (Stage II) and gel stage (Stage III), based on the time/temperature evolutions of the structural development rate (SDR). An interesting fluctuant decaying behavior of SDR was observed in Stage II and III, indicative of a sum of multiple relaxation processes and well described by a multiple-order Gaussisn-like equation: . More interestingly, the temperature dependences of the fitted values of Wn in Stage II and Stage III were found to follow the different Arrhenius laws, with different activation energies of EaII= 39-74 KJ/mol and EaIII~7.0 KJ/mol. The two different Arrhenius-like behaviors respectively suggest that dispersions in Stage II be attributed to the relaxation of the self-assembly of agar molecules or the growth of junction zones en route to gelation, in which the formation or fission of hydrogen bonding interactions plays an important role; and that dispersions in Stage III be attributed to the relaxation dynamics of water released from various size domains close to the domain of the viscous flow of water during the syneresis process.Comment: 24 pages, 4 figures, 1 tabl

Common Variants in a Novel Gene, FONG on Chromosome 2q33.1 Confer Risk of Osteoporosis in Japanese

Osteoporosis is a common disease characterized by low bone mass, decreased bone quality and increased predisposition to fracture. Genetic factors have been implicated in its etiology; however, the specific genes related to susceptibility to osteoporosis are not entirely known. To detect susceptibility genes for osteoporosis, we conducted a genome-wide association study in Japanese using ∼270,000 SNPs in 1,747 subjects (190 cases and 1,557 controls) followed by multiple levels of replication of the association using a total of ∼5,000 subjects (2,092 cases and 3,114 controls). Through these staged association studies followed by resequencing and linkage disequilibrium mapping, we identified a single nucleotide polymorphism (SNP), rs7605378 associated with osteoporosis. (combined P = 1.51×10−8, odds ratio = 1.25). This SNP is in a previously unknown gene on chromosome 2q33.1, FONG. FONG is predicted to encode a 147 amino-acid protein with a formiminotransferase domain in its N-terminal (FTCD_N domain) and is ubiquitously expressed in various tissues including bone. Our findings would give a new insight into osteoporosis etiology and pathogenesis

Phosphorus removal from eutrophic waters with an aluminium hybrid nanocomposite

An excess of phosphorus (P) is the most common cause of eutrophication of freshwater bodies. Thus, it is imperative to reduce the concentration of P to prevent harmful algal blooms. Moreover, recovery of P has been gaining importance because its natural source will be exhausted in the near future. Therefore, the present work investigated the removal and recovery of phosphate from water using a newly developed hybrid nanocomposite containing aluminium nanoparticles (HPN). The HPN-Pr removes 0.80 ± 0.01 mg P/g in a pH interval between 2.0 and 6.5. The adsorption mechanism was described by a Freundlich adsorption model. The material presented good selectivity for phosphate and can be regenerated using an HCl dilute solution. The factors that contribute most to the attractiveness of HPN-Pr as a phosphate sorbent are its moderate removal capacity, feasible production at industrial scale, reuse after regeneration and recovery of phosphate.The authors acknowledge the Foundation for Science and Technology (FCT) Project SFRH/BD/39085/2007 for the financial support

QTL Mapping of Combining Ability and Heterosis of Agronomic Traits in Rice Backcross Recombinant Inbred Lines and Hybrid Crosses

BACKGROUND: Combining ability effects are very effective genetic parameters in deciding the next phase of breeding programs. Although some breeding strategies on the basis of evaluating combining ability have been utilized extensively in hybrid breeding, little is known about the genetic basis of combining ability. Combining ability is a complex trait that is controlled by polygenes. With the advent and development of molecular markers, it is feasible to evaluate the genetic bases of combining ability and heterosis of elite rice hybrids through QTL analysis. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we first developed a QTL-mapping method for dissecting combining ability and heterosis of agronomic traits. With three testcross populations and a BCRIL population in rice, biometric and QTL analyses were conducted for ten agronomic traits. The significance of general combining ability and special combining ability for most of the traits indicated the importance of both additive and non-additive effects on expression levels. A large number of additive effect QTLs associated with performance per se of BCRIL and general combining ability, and dominant effect QTLs associated with special combining ability and heterosis were identified for the ten traits. CONCLUSIONS/SIGNIFICANCE: The combining ability of agronomic traits could be analyzed by the QTL mapping method. The characteristics revealed by the QTLs for combining ability of agronomic traits were similar with those by multitudinous QTLs for agronomic traits with performance per se of BCRIL. Several QTLs (1-6 in this study) were identified for each trait for combining ability. It demonstrated that some of the QTLs were pleiotropic or linked tightly with each other. The identification of QTLs responsible for combining ability and heterosis in the present study provides valuable information for dissecting genetic basis of combining ability

Analysis of MicroRNA Expression in Embryonic Developmental Toxicity Induced by MC-RR

As cynobacterial blooms frequently occur in fresh waters throughout the world, microcystins (MCs) have caused serious damage to both wildlife and human health. MCs are known to have developmental toxicity, however, the possible molecular mechanism is largely unknown. This is the first toxicological study to integrate post-transcriptomic, proteomic and bioinformatics analysis to explore molecular mechanisms for developmental toxicity of MCs in zebrafish. After being microinjected directly into embryos, MC-RR dose-dependently decreased survival rates and increased malformation rates of embryos, causing various embryo abnormalities including loss of vascular integrity and hemorrhage. Expressions of 31 microRNAs (miRNAs) and 78 proteins were significantly affected at 72 hours post-fertilisation (hpf). Expressions of miR-430 and miR-125 families were also significantly changed. The altered expressions of miR-31 and miR-126 were likely responsible for the loss of vascular integrity. MC-RR significantly reduced the expressions of a number of proteins involved in energy metabolism, cell division, protein synthesis, cytoskeleton maintenance, response to stress and DNA replication. Bioinformatics analysis shows that several aberrantly expressed miRNAs and proteins (involved in various molecular pathways) were predicted to be potential MC-responsive miRNA-target pairs, and that their aberrant expressions should be the possible molecular mechanisms for the various developmental defects caused by MC-RR

Analyses and Comparison of Imputation-Based Association Methods

Genotype imputation methods have become increasingly popular for recovering untyped genotype data. An important application with imputed genotypes is to test genetic association for diseases. Imputation-based association test can provide additional insight beyond what is provided by testing on typed tagging SNPs only. A variety of effective imputation-based association tests have been proposed. However, their performances are affected by a variety of genetic factors, which have not been well studied. In this study, using both simulated and real data sets, we investigated the effects of LD, MAF of untyped causal SNP and imputation accuracy rate on the performances of seven popular imputation-based association methods, including MACH2qtl/dat, SNPTEST, ProbABEL, Beagle, Plink, BIMBAM and SNPMStat. We also aimed to provide a comprehensive comparison among methods. Results show that: 1). imputation-based association tests can boost signals and improve power under medium and high LD levels, with the power improvement increasing with strengthening LD level; 2) the power increases with higher MAF of untyped causal SNPs under medium to high LD level; 3). under low LD level, a high imputation accuracy rate cannot guarantee an improvement of power; 4). among methods, MACH2qtl/dat, ProbABEL and SNPTEST perform similarly and they consistently outperform other methods. Our results are helpful in guiding the choice of imputation-based association test in practical application