Reassessing the atmospheric oxidation mechanism of toluene

Photochemical oxidation of aromatic hydrocarbons leads to tropospheric ozone and secondary organic aerosol (SOA) formation, with profound implications for air quality, human health, and climate. Toluene is the most abundant aromatic compound under urban environments, but its detailed chemical oxidation mechanism remains uncertain. From combined laboratory experiments and quantum chemical calculations, we show a toluene oxidation mechanism that is different from the one adopted in current atmospheric models. Our experimental work indicates a larger-than-expected branching ratio for cresols, but a negligible formation of ring-opening products (e.g., methylglyoxal). Quantum chemical calculations also demonstrate that cresols are much more stable than their corresponding peroxy radicals, and, for the most favorable OH (ortho) addition, the pathway of H extraction by O_2 to form the cresol proceeds with a smaller barrier than O_2 addition to form the peroxy radical. Our results reveal that phenolic (rather than peroxy radical) formation represents the dominant pathway for toluene oxidation, highlighting the necessity to reassess its role in ozone and SOA formation in the atmosphere

Functional prediction of genetic variation within and between two chicken lines selected for body-weight

Identifying genetic variation influencing complex traits is often a big challenge. Paul Siegel at the Virginia Polytechnic Institute and State University (USA) initiated a breeding experiment in the 1950s, where White Plymouth Rock (WPR) chicken lines were bi-directionally selected for body-weight at 56 days of age. After more than 50 generations of selection, the High Weight Selected (HWS) line is more than 10-fold bigger than the Low Weight Selected (LWS) line. These HWS and LWS lines have become a good model to investigate the genetic mechanisms underlying the body weight changes under long-term selection. Moreover, as a result of the recently rapid development of next generation sequencing technologies, with high throughput, a large number of genetics polymorphisms have been identified and can be used to explore the genetic factors underlying complex traits. In this thesis, we used NGS resequencing data and several leading databases to search for genes and mutations within previously mapped epistasic QTL regions, which could explain the differences in growth-related traits between the HWS and LWS lines. In consequence, a number of genetic factors have been detected and provide a good basis for further experimental investigation in relation to the observed effects on growth and other metabolic traits. Additionally, we also developed three softwares, which can be useful in the process of identifying genes and variations with phenotypic effects. One of these softwares were also applied within genetic studies in this thesis. Our softwares could be widely applied in many species and are likely to benefit many other research projects

Identification of candidate genes and mutations in QTL regions for chicken growth using bioinformatic analysis of NGS and SNP-chip data

Mapping of chromosomal regions harboring genetic polymorphisms that regulate complex traits is usually followed by a search for the causative mutations underlying the observed effects. This is often a challenging task even after fine mapping, as millions of base pairs including many genes will typically need to be investigated. Thus to trace the causative mutation(s) there is a great need for efficient bioinformatic strategies. Here, we searched for genes and mutations regulating growth in the Virginia chicken lines – an experimental population comprising two lines that have been divergently selected for body weight at 56 days for more than 50 generations. Several quantitative trait loci (QTL) have been mapped in an F2 intercross between the lines, and the regions have subsequently been replicated and fine mapped using an Advanced Intercross Line. We have further analyzed the QTL regions where the largest genetic divergence between the High-Weight selected (HWS) and Low-Weight selected (LWS) lines was observed. Such regions, covering about 37% of the actual QTL regions, were identified by comparing the allele frequencies of the HWS and LWS lines using both individual 60K SNP chip genotyping of birds and analysis of read proportions from genome resequencing of DNA pools. Based on a combination of criteria including significance of the QTL, allele frequency difference of identified mutations between the selected lines, gene information on relevance for growth, and the predicted functional effects of identified mutations we propose here a subset of candidate mutations of highest priority for further evaluation in functional studies. The candidate mutations were identified within the GCG, IGFBP2, GRB14, CRIM1, FGF16, VEGFR-2, ALG11, EDN1, SNX6, and BIRC7 genes. We believe that the proposed method of combining different types of genomic information increases the probability that the genes underlying the observed QTL effects are represented among the candidate mutations identified

miR-142-5p as a CXCR4-Targeted MicroRNA Attenuates SDF-1-Induced Chondrocyte Apoptosis and Cartilage Degradation via Inactivating MAPK Signaling Pathway

Osteoarthritis (OA) is a chronic joint function disorder with characteristics of chondrocytes reduction and extracellular matrix (ECM) components destruction. MicroRNAs (miRNAs) and the SDF-1/CXCR4 axis are essential factors of chondrocyte apoptosis and ECM degeneration. However, very few studies have investigated the correlation between miRNAs and the SDF-1/CXCR4 axis in osteoarthritis so far. Here, through miRNAs microarray and bioinformatics analyses, we identified miR-142-5p as a CXCR4-targeted and dramatically downregulated miRNA in cartilage from OA patients, as well as in SDF-1-induced OA chondrocytes in vitro. In SDF-1-treated primary human OA chondrocytes that were transfected with a miR-142-5p mimic or inhibitor, the expression of CXCR4 was found to be inversely correlated with the expression of miR-142-5p. The dual luciferase reporter assay further verified the target relationship between miR-142-5p and CXCR4. Overexpression of miR-142-5p alleviated OA pathology by suppressing chondrocyte apoptosis, even in CXCR4 overexpressed OA chondrocytes. This was associated with decreased cartilage matrix degradation, reduced cartilage inflammation, and inactivated MAPK signaling pathway. Our study suggests that upregulated expression of CXCR4-targeted miR-142-5p can inhibit apoptosis, inflammation, and matrix catabolism and inactivate the MAPK signaling pathway in OA chondrocytes. Our work provides important insight into targeting miR-142-5p and the SDF-1/CXCR4 axis in OA therapy

PASE: a novel method for functional prediction of amino acid substitutions based on physicochemical properties

Background: Non-synonymous single-nucleotide polymorphisms (nsSNPs) within the coding regions of genes causing amino acid substitutions (AASs) may have a large impact on protein function. The possibilities to identify nsSNPs across genomes have increased notably with the advent of next-generation sequencing technologies. Thus, there is a strong need for efficient bioinformatics tools to predict the functional effect of AASs. Such tools can be used to identify the most promising candidate mutations for further experimental validation. Results: Here we present prediction of AAS effects (PASE), a novel method that predicts the effect of an AASs based on physicochemical property changes. Evaluation of PASE, using a few AASs of known phenotypic effects and 3338 human AASs, for which functional effects have previously been scored with the widely used SIFT and PolyPhen tools, show that PASE is a useful method for functional prediction of AASs. We also show that the predictions can be further improved by combining PASE with information about evolutionary conservation. Conclusion: PASE is a novel algorithm for predicting functional effects of AASs, which can be used for pinpointing the most interesting candidate mutations. PASE predictions are based on changes in seven physicochemical properties and can improve predictions from many other available tools, which are based on evolutionary conservation. Using available experimental data and predictions from the already existing tools, we demonstrate that PASE is a useful method for predicting functional effects of AASs, even when a limited number of query sequence homologs/orthologs are available

Effects of fermentative and non-fermentative additives on silage quality and anaerobic digestion performance of Pennisetum purpureum

The effect of additives on the silage quality, microbial community, and anaerobic digestion performance of Pennisetum purpureum with high moisture content was studied. The sample treated with a mixed additive had best silage quality with the lowest pH and highest lactic acid/acetic acid ratio. Different additives influenced the dominant desirable bacteria. Correspondingly, Enterobacter was the dominant bacterial genus for sample with non-fermentative additives, whereas for the samples with fermentative or mixed additives, both Enterobacter and Lactobacillus had high relative abundance. The parameters of NH3-N, hemicellulose and lactic acid were positively correlated with the specific methane yield, while the lignin content was inversely correlated with the specific methane yield. The higher specific methane yield of 293.81 +/- 0.15-334.69 +/- 22.75 mL/g VS was obtained for samples treated with fermentative additive. Therefore, the mixed additive and fermentative additive are recommended for the silage of material with high-moisture content to improve the silage quality and methane yield