Theoretical and Computational Multiple Regression Study of Gastric Electrical Activity Using Dipole Tracing from Magnetic Field Measurements

The biomagnetic inverse problem has captured the interest of both mathematicians and physicists due to its important applications in the medical field. As a result of our experience in analyzing the electrical activity of the gastric smooth muscle, we present here a theoretical model of the magnetic field in the stomach and a computational implementation whereby we demonstrate its realism and usefulness. The computational algorithm developed for this purpose consists of dividing the magnetic field signal input surface into centroid-based grids that allow recursive least-squares approximations to be applied, followed by comparison tests in which the locations of the best-fitting current dipoles are determined. In the second part of the article, we develop a multiple-regression analysis of experimental gastric magnetic data collected using Superconducting QUantum Interference Device (SQUID) magnetometers and successfully processed using our algorithm. As a result of our analysis, we conclude on statistical grounds that it is sufficient to model the electrical activity of the GI tract using only two electric current dipoles in order to account for the magnetic data recorded non-invasively with SQUID magnetometers above the human abdomen.     

Spatial Interpolation of Fine Particulate Matter Concentrations Using the Shortest Wind-Field Path Distance

Effective assessments of air-pollution exposure depend on the ability to accurately predict pollutant concentrations at unmonitored locations, which can be achieved through spatial interpolation. However, most interpolation approaches currently in use are based on the Euclidean distance, which cannot account for the complex nonlinear features displayed by air-pollution distributions in the wind-field. In this study, an interpolation method based on the shortest path distance is developed to characterize the impact of complex urban wind-field on the distribution of the particulate matter concentration. In this method, the wind-field is incorporated by first interpolating the observed wind-field from a meteorological-station network, then using this continuous wind-field to construct a cost surface based on Gaussian dispersion model and calculating the shortest wind-field path distances between locations, and finally replacing the Euclidean distances typically used in Inverse Distance Weighting (IDW) with the shortest wind-field path distances. This proposed methodology is used to generate daily and hourly estimation surfaces for the particulate matter concentration in the urban area of Beijing in May 2013. This study demonstrates that wind-fields can be incorporated into an interpolation framework using the shortest wind-field path distance, which leads to a remarkable improvement in both the prediction accuracy and the visual reproduction of the wind-flow effect, both of which are of great importance for the assessment of the effects of pollutants on human health.     

Cell Lineage Tracing Identifies Hormone-Regulated and Wnt-Responsive Vaginal Epithelial Stem Cells

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A Genome-Wide Association Study of the Maize Hypersensitive Defense Response Identifies Genes That Cluster in Related Pathways

Much remains unknown of molecular events controlling the plant hypersensitive defense response (HR), a rapid localized cell death that limits pathogen spread and is mediated by resistance (R-) genes. Genetic control of the HR is hard to quantify due to its microscopic and rapid nature. Natural modifiers of the ectopic HR phenotype induced by an aberrant auto-active R-gene (Rp1-D21), were mapped in a population of 3,381 recombinant inbred lines from the maize nested association mapping population. Joint linkage analysis was conducted to identify 32 additive but no epistatic quantitative trait loci (QTL) using a linkage map based on more than 7000 single nucleotide polymorphisms (SNPs). Genome-wide association (GWA) analysis of 26.5 million SNPs was conducted after adjusting for background QTL. GWA identified associated SNPs that colocalized with 44 candidate genes. Thirty-six of these genes colocalized within 23 of the 32 QTL identified by joint linkage analysis. The candidate genes included genes predicted to be in involved programmed cell death, defense response, ubiquitination, redox homeostasis, autophagy, calcium signalling, lignin biosynthesis and cell wall modification. Twelve of the candidate genes showed significant differential expression between isogenic lines differing for the presence of Rp1-D21. Low but significant correlations between HR-related traits and several previously-measured disease resistance traits suggested that the genetic control of these traits was substantially, though not entirely, independent. This study provides the first system-wide analysis of natural variation that modulates the HR response in plants.     

A Genome-wide Expression Association Analysis Identifies Genes and Pathways Associated with Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with strong genetic components. To identity novel risk variants for ALS, utilizing the latest genome-wide association studies (GWAS) and eQTL study data, we conducted a genome-wide expression association analysis by summary data-based Mendelian randomization (SMR) method. Summary data were derived from a large-scale GWAS of ALS, involving 12577 cases and 23475 controls. The eQTL annotation dataset included 923,021 cis-eQTL for 14,329 genes and 4732 trans-eQTL for 2612 genes. Genome-wide single gene expression association analysis was conducted by SMR software. To identify ALS-associated biological pathways, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). SMR single gene analysis identified one significant and four suggestive genes associated with ALS, including C9ORF72 (P value = 7.08 × 10^?6), NT5C3L (P value = 1.33 × 10^?5), GGNBP2 (P value = 1.81 × 10^?5), ZNHIT3(P value = 2.94 × 10^?5), and KIAA1600(P value = 9.97 × 10^?5). GSEA identified 7 significant biological pathways, such as PEROXISOME (empirical P value = 0.006), GLYCOLYSIS_GLUCONEOGENESIS (empirical P value = 0.043), and ARACHIDONIC_ACID_ METABOLISM (empirical P value = 0.040). Our study provides novel clues for the genetic mechanism studies of ALS.     

Discriminating between Lysine Sumoylation and Lysine Acetylation Using mRMR Feature Selection and Analysis

Post-translational modifications (PTMs) are crucial steps in protein synthesis and are important factors contributing to protein diversity. PTMs play important roles in the regulation of gene expression, protein stability and metabolism. Lysine residues in protein sequences have been found to be targeted for both types of PTMs: sumoylations and acetylations; however, each PTM has a different cellular role. As experimental approaches are often laborious and time consuming, it is challenging to distinguish the two types of PTMs on lysine residues using computational methods. In this study, we developed a method to discriminate between sumoylated lysine residues and acetylated residues. The method incorporated several features: PSSM conservation scores, amino acid factors, secondary structures, solvent accessibilities and disorder scores. By using the mRMR (Maximum Relevance Minimum Redundancy) method and the IFS (Incremental Feature Selection) method, an optimal feature set was selected from all of the incorporated features, with which the classifier achieved 92.14% accuracy with an MCC value of 0.7322. Analysis of the optimal feature set revealed some differences between acetylation and sumoylation. The results from our study also supported the previous finding that there exist different consensus motifs for the two types of PTMs. The results could suggest possible dominant factors governing the acetylation and sumoylation of lysine residues, shedding some light on the modification dynamics and molecular mechanisms of the two types of PTMs, and provide guidelines for experimental validations.     

A Novel Computational Method Identifies Intra- and Inter-Species Recombination Events in Staphylococcus aureus and Streptococcus pneumoniae

Advances in high-throughput DNA sequencing technologies have determined an explosion in the number of sequenced bacterial genomes. Comparative sequence analysis frequently reveals evidences of homologous recombination occurring with different mechanisms and rates in different species, but the large-scale use of computational methods to identify recombination events is hampered by their high computational costs. Here, we propose a new method to identify recombination events in large datasets of whole genome sequences. Using a filtering procedure of the gene conservation profiles of a test genome against a panel of strains, this algorithm identifies sets of contiguous genes acquired by homologous recombination. The locations of the recombination breakpoints are determined using a statistical test that is able to account for the differences in the natural rate of evolution between different genes. The algorithm was tested on a dataset of 75 genomes of Staphylococcus aureus and 50 genomes comprising different streptococcal species, and was able to detect intra-species recombination events in S. aureus and in Streptococcus pneumoniae. Furthermore, we found evidences of an inter-species exchange of genetic material between S. pneumoniae and Streptococcus mitis, a closely related commensal species that colonizes the same ecological niche. The method has been implemented in an R package, Reco, which is freely available from supplementary material, and provides a rapid screening tool to investigate recombination on a genome-wide scale from sequence data.     

A Targeted Gain-of-Function Screen Identifies Genes Affecting Salivary Gland Morphogenesis/Tubulogenesis in Drosophila

During development individual cells in tissues undergo complex cell-shape changes to drive the morphogenetic movements required to form tissues. Cell shape is determined by the cytoskeleton and cell-shape changes critically depend on a tight spatial and temporal control of cytoskeletal behavior. We have used the formation of the salivary glands in the Drosophila embryo, a process of tubulogenesis, as an assay for identifying factors that impinge on cell shape and the cytoskeleton. To this end we have performed a gain-of-function screen in the salivary glands, using a collection of fly lines carrying EP-element insertions that allow the overexpression of downstream-located genes using the UAS-Gal4 system. We used a salivary-gland-specific fork head-Gal4 line to restrict expression to the salivary glands, in combination with reporters of cell shape and the cytoskeleton. We identified a number of genes known to affect salivary gland formation, confirming the effectiveness of the screen. In addition, we found many genes not implicated previously in this process, some having known functions in other tissues. We report the initial characterization of a subset of genes, including chickadee, rhomboid1, egalitarian, bitesize, and capricious, through comparison of gain- and loss-of-function phenotypes.     

A Hybrid Computational Method for the Discovery of Novel Reproduction-Related Genes

Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.     

Genome-Wide Association Study Identifies Loci and Candidate Genes for Body Composition and Meat Quality Traits in Beijing-You Chickens

Body composition and meat quality traits are important economic traits of chickens. The development of high-throughput genotyping platforms and relevant statistical methods have enabled genome-wide association studies in chickens. In order to identify molecular markers and candidate genes associated with body composition and meat quality traits, genome-wide association studies were conducted using the Illumina 60 K SNP Beadchip to genotype 724 Beijing-You chickens. For each bird, a total of 16 traits were measured, including carcass weight (CW), eviscerated weight (EW), dressing percentage, breast muscle weight (BrW) and percentage (BrP), thigh muscle weight and percentage, abdominal fat weight and percentage, dry matter and intramuscular fat contents of breast and thigh muscle, ultimate pH, and shear force of the pectoralis major muscle at 100 d of age. The SNPs that were significantly associated with the phenotypic traits were identified using both simple (GLM) and compressed mixed linear (MLM) models. For nine of ten body composition traits studied, SNPs showing genome wide significance (P<2.59E−6) have been identified. A consistent region on chicken (Gallus gallus) chromosome 4 (GGA4), including seven significant SNPs and four candidate genes (LCORL, LAP3, LDB2, TAPT1), were found to be associated with CW and EW. Another 0.65 Mb region on GGA3 for BrW and BrP was identified. After measuring the mRNA content in beast muscle for five genes located in this region, the changes in GJA1 expression were found to be consistent with that of breast muscle weight across development. It is highly possible that GJA1 is a functional gene for breast muscle development in chickens. For meat quality traits, several SNPs reaching suggestive association were identified and possible candidate genes with their functions were discussed.     

软件预测和MAST技术筛选mRNA反义核酸靶点的比较

基因mRNA的结构靶点筛选是反义核酸药物研发的一个难题 .兔 (Oryctolaguscuniculus) β珠蛋白基因mRNA的结构靶位点通过运用MAST技术筛选获得 ,和计算机软件RNAstructure3 71模拟分析的位点进行了比较 ,也和寡核苷酸微阵列杂交技术筛选获得的靶点结果 (M .Natalie ,1 997)进行了比较 ,显示 :据MAST技术获得的兔 β珠蛋白基因 2个反义核酸结合靶位点 ,和用RNAstructure3 71软件给出的模拟分析的 2个靶位点相同 ,且它们与寡核苷酸微阵列杂交技术的结果完全一致 .运用MAST技术筛选获得绿色荧光蛋白 (GFP)mRNA有 4个结构靶位点 ,体外分析表明这 4个靶位点均有效 ,其中有 3个与RNAstructure3 71软件分析的靶点相同 ,但计算机模拟推荐的结构靶位点较多 ,而且随着基因长度增加确认靶位点的难度增大 ,获得的靶位点还需要实验验证 ,计算机软件模拟分析对实验筛选靶点、设计反义核酸有辅助价值 .MAST方法能筛选各种长度基因mRNA的全部可及位点和准确给定核苷酸的起止位置以供设计反义核酸 ,具有简单快捷的优点 ,将能为反义核酸设计起重要作用 .     

A Thirteen-Gene Expression Signature Predicts Survival of Patients with Pancreatic Cancer and Identifies New Genes of Interest

Background

Currently, prognostication for pancreatic ductal adenocarcinoma (PDAC) is based upon a coarse clinical staging system. Thus, more accurate prognostic tests are needed for PDAC patients to aid treatment decisions.

Methods and Findings

Affymetrix gene expression profiling was carried out on 15 human PDAC tumors and from the data we identified a 13-gene expression signature (risk score) that correlated with patient survival. The gene expression risk score was then independently validated using published gene expression data and survival data for an additional 101 patients with pancreatic cancer. Patients with high-risk scores had significantly higher risk of death compared to patients with low-risk scores (HR 2.27, p = 0.002). When the 13-gene score was combined with lymph node status the risk-score further discriminated the length of patient survival time (p<0.001). Patients with a high-risk score had poor survival independent of nodal status; however, nodal status increased predictability for survival in patients with a low-risk gene signature score (low-risk N1 vs. low-risk N0: HR = 2.0, p = 0.002). While AJCC stage correlated with patient survival (p = 0.03), the 13-gene score was superior at predicting survival. Of the 13 genes comprising the predictive model, four have been shown to be important in PDAC, six are unreported in PDAC but important in other cancers, and three are unreported in any cancer.

Conclusions

We identified a 13-gene expression signature that predicts survival of PDAC patients and could prove useful for making treatment decisions. This risk score should be evaluated prospectively in clinical trials for prognostication and for predicting response to chemotherapy. Investigation of new genes identified in our model may lead to novel therapeutic targets.     

Bac-to-Bac系统在杆状病毒功能基因研究上的应用

利用Bac-to-Bac系统,在大肠细菌中复制增殖杆状病毒质粒bacmid,并通过RecA介导法、ET-recombination法在bacmid DNA上缺失或插入功能基因,构建功能基因缺陷型或补回型的杆状病毒质粒.该质粒转染到昆虫细胞中产生重组病毒,进而在细胞甚至虫体水平上研究基因的功能,极大改善了传统上用空斑实验筛选重组病毒的不足.     

A Genome-Wide Over-Expression Screen Identifies Genes Involved in Phagocytosis in the Human Protozoan Parasite, Entamoeba histolytica

Functional genomics and forward genetics seek to assign function to all known genes in a genome. Entamoeba histolytica is a protozoan parasite for which forward genetics approaches have not been extensively applied. It is the causative agent of amoebic dysentery and liver abscess, and infection is prevalent in developing countries that cannot prevent its fecal-oral spread. It is responsible for considerable global morbidity and mortality. Given that the E. histolytica genome has been sequenced, it should be possible to apply genomic approaches to discover gene function. We used a genome-wide over-expression screen to uncover genes regulating an important virulence function of E. histolytica, namely phagocytosis. We developed an episomal E. histolytica cDNA over-expression library, transfected the collection of plasmids into trophozoites, and applied a high-throughput screen to identify phagocytosis mutants in the population of over-expressing cells. The screen was based on the phagocytic uptake of human red blood cells loaded with the metabolic toxin, tubercidin. Expression plasmids were isolated from trophozoites that survived exposure to tubercidin-charged erythrocytes (phagocytosis mutants), and the cDNAs were sequenced. We isolated the gene encoding profilin, a well-characterized cytoskeleton-regulating protein with a known role in phagocytosis. This supports the validity of our approach. Furthermore, we assigned a phagocytic role to several genes not previously known to function in this manner. To our knowledge, this is the first genome-wide forward genetics screen to be applied to this pathogen. The study demonstrates the power of forward genetics in revealing genes regulating virulence in E. histolytica. In addition, the study validates an E. histolytica cDNA over-expression library as a valuable tool for functional genomics.