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1.
Background
Conventionally, the first step in analyzing the large and high-dimensional data sets measured by microarrays is visual exploration. Dendrograms of hierarchical clustering, self-organizing maps (SOMs), and multidimensional scaling have been used to visualize similarity relationships of data samples. We address two central properties of the methods: (i) Are the visualizations trustworthy, i.e., if two samples are visualized to be similar, are they really similar? (ii) The metric. The measure of similarity determines the result; we propose using a new learning metrics principle to derive a metric from interrelationships among data sets.Results
The trustworthiness of hierarchical clustering, multidimensional scaling, and the self-organizing map were compared in visualizing similarity relationships among gene expression profiles. The self-organizing map was the best except that hierarchical clustering was the most trustworthy for the most similar profiles. Trustworthiness can be further increased by treating separately those genes for which the visualization is least trustworthy. We then proceed to improve the metric. The distance measure between the expression profiles is adjusted to measure differences relevant to functional classes of the genes. The genes for which the new metric is the most different from the usual correlation metric are listed and visualized with one of the visualization methods, the self-organizing map, computed in the new metric.Conclusions
The conjecture from the methodological results is that the self-organizing map can be recommended to complement the usual hierarchical clustering for visualizing and exploring gene expression data. Discarding the least trustworthy samples and improving the metric still improves it.2.
Background
In recent years the visualization of biomagnetic measurement data by so-called pseudo current density maps or Hosaka-Cohen (HC) transformations became popular.Methods
The physical basis of these intuitive maps is clarified by means of analytically solvable problems.Results
Examples in magnetocardiography, magnetoencephalography and magnetoneurography demonstrate the usefulness of this method.Conclusion
Hardware realizations of the HC-transformation and some similar transformations are discussed which could advantageously support cross-platform comparability of biomagnetic measurements.3.
Background
The present study elucidates the protective potential of bromelain against dichlorvos intoxication in mice brains. Dichlorvos induces the oxidative stress by disproportionating the balance between free radicals generation and their scavenging in neurons which leads to neuronal degeneration.Methods
In this study, mice were divided into four groups-group I (control), group II (dichlorvos treated), group III (bromelain treated) and group IV (exposed to both bromelain and dichlorvos both).Results
Dichlorvos treatment increased the levels of thiobarbituric acid reactive substances (TBARS) and protein carbonyl content (PCC) which indicate the increased oxidative stress. Meanwhile, brain endogenous antioxidants and cholinesterases level was decreased after dichlorvos exposure. Levels of TBARS and PCC decreased whereas cholinesterases level was recorded to be elevated after bromelain exposure.Conclusion
Bromelain offered neuroprotection by decreasing oxidative stress and augmenting cholinesterases in mice brains. This study highlights the invulnerability of bromelain against oxidative and cholinergic deficits in mice brains.4.
Background
Existing clustering approaches for microarray data do not adequately differentiate between subsets of co-expressed genes. We devised a novel approach that integrates expression and sequence data in order to generate functionally coherent and biologically meaningful subclusters of genes. Specifically, the approach clusters co-expressed genes on the basis of similar content and distributions of predicted statistically significant sequence motifs in their upstream regions.Results
We applied our method to several sets of co-expressed genes and were able to define subsets with enrichment in particular biological processes and specific upstream regulatory motifs.Conclusions
These results show the potential of our technique for functional prediction and regulatory motif identification from microarray data.5.
Background
While there are a large number of bioinformatics datasets for clustering, many of them are incomplete, i.e., missing attribute values in some data samples needed by clustering algorithms. A variety of clustering algorithms have been proposed in the past years, but they usually are limited to cluster on the complete dataset. Besides, conventional clustering algorithms cannot obtain a trade-off between accuracy and efficiency of the clustering process since many essential parameters are determined by the human user’s experience.Results
The paper proposes a Multiple Kernel Density Clustering algorithm for Incomplete datasets called MKDCI. The MKDCI algorithm consists of recovering missing attribute values of input data samples, learning an optimally combined kernel for clustering the input dataset, reducing dimensionality with the optimal kernel based on multiple basis kernels, detecting cluster centroids with the Isolation Forests method, assigning clusters with arbitrary shape and visualizing the results.Conclusions
Extensive experiments on several well-known clustering datasets in bioinformatics field demonstrate the effectiveness of the proposed MKDCI algorithm. Compared with existing density clustering algorithms and parameter-free clustering algorithms, the proposed MKDCI algorithm tends to automatically produce clusters of better quality on the incomplete dataset in bioinformatics.6.
Yuki Kobayashi Go Sato Nobuyuki Mochizuki Shinji Hirano Takuya Itou Adolorata AB Carvalho Avelino Albas Hamilton P Santos Fumio H Ito Takeo Sakai 《BMC veterinary research》2008,4(1):44
Background
Vampire bats are important rabies virus vectors, causing critical problems in both the livestock industry and public health sector in Latin America. In order to assess the epidemiological characteristics of vampire bat-transmitted rabies, the authors conducted phylogenetic and geographical analyses using sequence data of a large number of cattle rabies isolates collected from a wide geographical area in Brazil.Methods
Partial nucleoprotein genes of rabies viruses isolated from 666 cattle and 18 vampire bats between 1987 and 2006 were sequenced and used for phylogenetic analysis. The genetic variants were plotted on topographical maps of Brazil.Results
In this study, 593 samples consisting of 24 genetic variants were analyzed. Regional localization of variants was observed, with the distribution of several variants found to be delimited by mountain ranges which served as geographic boundaries. The geographical distributions of vampire-bat and cattle isolates that were classified as the identical phylogenetic group were found to overlap with high certainty. Most of the samples analyzed in this study were isolated from adjacent areas linked by rivers.Conclusion
This study revealed the existence of several dozen regional variants associated with vampire bats in Brazil, with the distribution patterns of these variants found to be affected by mountain ranges and rivers. These results suggest that epidemiological characteristics of vampire bat-related rabies appear to be associated with the topographical and geographical characteristics of areas where cattle are maintained, and the factors affecting vampire bat ecology.8.
Background
The feasibility of effectively analyzing high-density single nucleotide polymorphism (SNP) maps in whole genome scans of complex traits is not known. The purpose of this study was to compare variance components linkage results using different density marker maps in data from the Collaborative Study on the Genetics of Alcoholism (COGA). Marker maps having an average spacing of 10 cM (microsatellite), 0.78 cM (SNP1), and 0.31 cM (SNP2) were used to identify quantitative trait loci (QTLs) affecting maximum number of alcoholic drinks consumed in a 24-hour period (lnmaxalc).Results
Heritability of lnmaxalc was estimated to be 15%. Multipoint variance components linkage analysis revealed similar linkage patterns among the three marker panels, with the SNP maps consistently yielding higher LOD scores. Robust LOD scores > 1.0 were observed on chromosomes 1 and 13 for all three marker maps. Additional LODs > 1.0 were observed on chromosome 4 with both SNP maps and on chromosomes 18 and 21 with the SNP2 map. Peak LOD scores for lnmaxalc were observed on chromosome 1, although none reached genome-wide statistical significance. Quantile-quantile plots revealed that the multipoint distribution of SNP results appeared to fit the asymptotic null distribution better than the twopoint results.Conclusion
In conclusion, variance-components linkage analysis using high-density SNP maps provided higher LOD scores compared with the standard microsatellite map, similar to studies using nonparametric linkage methods. Widespread application of SNP maps will depend on further improvements in the computational methods implemented in current software packages.9.
Yonghua Xu Xiangmin Wang Surong Jiang Chen Men Di Xu Yan Guo Jun Wu 《Cellular & molecular biology letters》2018,23(1):50
Background
Microcystins are waterborne environmental toxins that induce oxidative stress and cause injuries in the heart. On the other hand, many physiological processes, including antioxidant defense, are under precise control by the mammalian circadian clock.Results
In the present study, we evaluated the effect of microcystin-LR (MC-LR) on the rhythmic expression patterns of circadian and antioxidant genes in rat cardiomyocytes using the serum shock technique. We found that a non-toxic dose (10 μm) of MC-LR decreased the amplitudes of rhythmic patterns of clock genes, while it increased the expression levels of antioxidant genes.Conclusions
Our results indicate an influence of MC-LR on the circadian clock system and clock-controlled antioxidant genes, which will shed some light on the explanation of heart toxicity induced by MC-LR from the viewpoint of chronobiology.10.
Anatoly V. Zhigunov Pavel S. Ulianich Marina V. Lebedeva Peter L. Chang Sergey V. Nuzhdin Elena K. Potokina 《BMC plant biology》2017,17(1):180
Background
Restriction-site associated DNA sequencing (RADseq) technology was recently employed to identify a large number of single nucleotide polymorphisms (SNP) for linkage mapping of a North American and Eastern Asian Populus species. However, there is also the need for high-density genetic linkage maps for the European aspen (P. tremula) as a tool for further mapping of quantitative trait loci (QTLs) and marker-assisted selection of the Populus species native to Europe.Results
We established a hybrid F1 population from the cross of two aspen parental genotypes diverged in their phenological and morphological traits. We performed RADseq of 122 F1 progenies and two parents yielding 15,732 high-quality SNPs that were successfully identified using the reference genome of P. trichocarpa. 2055 SNPs were employed for the construction of maternal and paternal linkage maps. The maternal linkage map was assembled with 1000 SNPs, containing 19 linkage groups and spanning 3054.9 cM of the genome, with an average distance of 3.05 cM between adjacent markers. The paternal map consisted of 1055 SNPs and the same number of linkage groups with a total length of 3090.56 cM and average interval distance of 2.93 cM. The linkage maps were employed for QTL mapping of one-year-old seedlings height variation. The most significant QTL (LOD = 5.73) was localized to LG5 (96.94 cM) of the male linkage map, explaining 18% of the phenotypic variation.Conclusions
The set of 15,732 SNPs polymorphic in aspen and high-density genetic linkage maps constructed for the P. tremula intra-specific cross will provide a valuable source for QTL mapping and identification of candidate genes facilitating marker-assisted selection in European aspen.11.
Jamie V. de Seymour Stephanie Tu Xiaoling He Hua Zhang Ting-Li Han Philip N. Baker Karolina Sulek 《Metabolomics : Official journal of the Metabolomic Society》2018,14(6):79
Introduction
Intrahepatic cholestasis of pregnancy (ICP) is a common maternal liver disease; development can result in devastating consequences, including sudden fetal death and stillbirth. Currently, recognition of ICP only occurs following onset of clinical symptoms.Objective
Investigate the maternal hair metabolome for predictive biomarkers of ICP.Methods
The maternal hair metabolome (gestational age of sampling between 17 and 41 weeks) of 38 Chinese women with ICP and 46 pregnant controls was analysed using gas chromatography–mass spectrometry.Results
Of 105 metabolites detected in hair, none were significantly associated with ICP.Conclusion
Hair samples represent accumulative environmental exposure over time. Samples collected at the onset of ICP did not reveal any metabolic shifts, suggesting rapid development of the disease.12.
Background
Microarray technology is often used to identify the genes that are differentially expressed between two biological conditions. On the other hand, since microarray datasets contain a small number of samples and a large number of genes, it is usually desirable to identify small gene subsets with distinct pattern between sample classes. Such gene subsets are highly discriminative in phenotype classification because of their tightly coupling features. Unfortunately, such identified classifiers usually tend to have poor generalization properties on the test samples due to overfitting problem.Results
We propose a novel approach combining both supervised learning with unsupervised learning techniques to generate increasingly discriminative gene clusters in an iterative manner. Our experiments on both simulated and real datasets show that our method can produce a series of robust gene clusters with good classification performance compared with existing approaches.Conclusion
This backward approach for refining a series of highly discriminative gene clusters for classification purpose proves to be very consistent and stable when applied to various types of training samples.13.
Julia B. Honneffer Jörg M. Steiner Jonathan A. Lidbury Jan S. Suchodolski 《Metabolomics : Official journal of the Metabolomic Society》2017,13(3):26
Introduction
The fecal microbiota are relevant to the health and disease of many species. The importance of the fecal metabolome has more recently been appreciated, but our knowledge of the microbiota and metabolome at other sites along the gastrointestinal tract remains deficient.Objective
To analyze the gastrointestinal microbiota and metabolome of healthy domestic dogs at four anatomical sites.Methods
Samples of the duodenal, ileal, colonic, and rectal contents were collected from six adult dogs after humane euthanasia for an unrelated study. The microbiota were characterized using Illumina sequencing of 16S rRNA genes. The metabolome was characterized by mass spectrometry-based methods.Results
Prevalent phyla throughout the samples were Proteobacteria, Firmicutes, Fusobacteria, and Bacteroidetes, consistent with previous findings in dogs and other species. A total of 530 unique metabolites were detected; 199 of these were identified as previously named compounds, but 141 of them had at least one significantly different site-pair comparison. Noteworthy examples include relative concentrations of amino acids, which decreased from the small to large intestine; pyruvate, which peaked in the ileum; and several phenol-containing carboxylic acid compounds that increased in the large intestine.Conclusion
The microbiota and metabolome vary significantly at different sites along the canine gastrointestinal tract.14.
Background
Bacterial genomes develop new mechanisms to tide them over the imposing conditions they encounter during the course of their evolution. Acquisition of new genes by lateral gene transfer may be one of the dominant ways of adaptation in bacterial genome evolution. Lateral gene transfer provides the bacterial genome with a new set of genes that help it to explore and adapt to new ecological niches.Methods
A maximum likelihood analysis was done on the five sequenced corynebacterial genomes to model the rates of gene insertions/deletions at various depths of the phylogeny.Results
The study shows that most of the laterally acquired genes are transient and the inferred rates of gene movement are higher on the external branches of the phylogeny and decrease as the phylogenetic depth increases. The newly acquired genes are under relaxed selection and evolve faster than their older counterparts. Analysis of some of the functionally characterised LGTs in each species has indicated that they may have a possible adaptive role.Conclusion
The five Corynebacterial genomes sequenced to date have evolved by acquiring between 8 – 14% of their genomes by LGT and some of these genes may have a role in adaptation.15.
16.
Huange Wang Fred A. van Eeuwijk Johannes Jansen 《TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik》2017,130(2):433-444
Key message
Probabilistic graphical models show great potential for robust and reliable construction of linkage maps. We show how to use probabilistic graphical models to construct high-quality linkage maps in the face of data perturbations caused by genotyping errors and reciprocal translocations.Abstract
It has been shown that linkage map construction can be hampered by the presence of genotyping errors and chromosomal rearrangements such as inversions and translocations. Here, we report a novel method for linkage map construction using probabilistic graphical models. The method is proven, both theoretically and practically, to be effective in filtering out markers that contain genotyping errors. In particular, it carries out marker filtering and ordering simultaneously, and is therefore superior to the standard post hoc filtering using nearest-neighbour stress. Furthermore, we demonstrate empirically that the proposed method offers a promising solution to linkage map construction in the case of a reciprocal translocation.17.
Background
Microbial communities are influenced by environmental factors including host genetics. We investigated the relationship between host bitter taste receptor genotype hTAS2R38 and oral microbiota, together with the influence of geographical location.Methods
hTAS2R38 polymorphisms and 16S bacterial gene sequencing from oral samples were analyzed from a total of 45 healthy volunteers from different geographical locations.Results
Genetic variation in the bitter taste receptor TAS2R38 reflected in the microbial composition of oral mucosa in Finnish and Spanish subjects. Multivariate analysis showed significant differences in the microbial composition between country and also dependent on taste genotype. Oral microbiota was shown to be more stable to the geographical location impact among AVI-homozygotes than PAV-homozygotes or heterozygotes (PAV/AVI).Conclusion
Geographical location and genetic variation in the hTAS2R38 taste receptor impact oral mucosa microbial composition. These findings provide an advance in the knowledge regarding the interactions between taste receptor genes and oral microbiota. This study suggests the role of host-microbiota interactions on the food taste perception in food choices, nutrition, and eating behavior.18.
19.
Rachel A. Spicer Christoph Steinbeck 《Metabolomics : Official journal of the Metabolomic Society》2018,14(1):16
Introduction
Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.Objectives
(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.Methods
A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.Results
Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.Conclusion
Further efforts are required to improve data sharing in metabolomics.20.
Antonio Murgia Christine Hinz Sonia Liggi Jùlìa Denes Zoe Hall James West Maria Laura Santoru Cristina Piras Cristina Manis Paolo Usai Luigi Atzori Julian L. Griffin Pierluigi Caboni 《Metabolomics : Official journal of the Metabolomic Society》2018,14(10):140