Genome analysis,phylogeny, and classification

The implications of genome analysis for evolutionary theory and systematics are treated. The precise relationship between the theoretical and operational definitions of chromosome homology is shown to be uncertain. It is pointed out that genera defined by genome analysis may be either monophyletic or non-monophyletic, and that the genus is not a basic unit of evolution. Characters obtained by genome analysis may be useful in a phylogenetic context, provided they are treated as all other characters.     

Blood analysis in newborn donkeys: hematology,biochemistry, and blood gases analysis

The knowledge of reference ranges for hematologic, biochemical, and blood gas parameters in the different species and the influence of breed and age on them is a fundamental tool for the clinician. For this reason, the aim of this study was to evaluate the age-related changes of hematologic and biochemical parameters in Martina Franca donkey foals during the first 3 weeks of life and of blood gases during the first 24 hours of age. Fifteen healthy donkey foals were enrolled; blood samples were collected from each foal at 10 minutes after birth, 1 hour after the first and second suckles, 12 and 24 hours after birth, daily from Day 2 to 7, and at Days 10, 14, and 21 of life. Erythrocytes, leukocytes, and platelets counts were assessed; also metabolic (alanine aminotransferase, aspartate aminotransferase, gamma glutamyl transferase, creatinphospokinase, lactate dehydrogenase, alkaline phosphatase, glucose, blood urea nitrogen, creatinine, total proteins, albumins, cholesterol, and total bilirubin) and electrolytic parameters (Ca, P, Mg, Na, K, and Cl) were evaluated. Finally, blood gases and metabolic parameters (pH, pCO₂, pO₂, sO₂, TCO₂, HCO₃, lactate, and base excess) on venous blood were assessed with a portable analyzer. A statistical analysis to evaluate the influence of age and sex was performed. Several differences were found between sampling times, demonstrating that age influences these parameters. Moreover differences were found compared with data reported in literature for donkey foals of another species, horse foals, and adult donkeys. Although a great interindividual variation for some parameters exists, this study demonstrated that interval references should be addressed not only to different species, but also to specific breeds and to the neonatal period.     

ChIP-chip: data, model, and analysis

ChIP-chip (or ChIP-on-chip) is a technology for isolation and identification of genomic sites occupied by specific DNA-binding proteins in living cells. The ChIP-chip signals can be obtained over the whole genome by tiling arrays, where a peak shape is generally observed around a protein-binding site. In this article, we describe the ChIP-chip process and present a probability model for ChIP-chip data. We then propose a model-based method for recognizing the peak shapes for the purpose of detecting protein-binding sites. We also investigate the issue of bandwidth in nonparametric kernel smoothing method.     

Climatic reconstruction at the Miocene Shanwang basin, China, using leaf margin analysis, CLAMP, coexistence approach, and overlapping distribution analysis

The reconstruction of the climate in the Miocene Shanwang basin is an important link in understanding past climate and environmental changes in East Asia. A recent study showed that the mean annual temperature (MAT) estimates derived from leaf margin analysis (LMA) and the Climate Leaf Analysis Multivariate Program (CLAMP) conflicted with and were remarkably lower than those estimated by the coexistence approach (CA). Overlapping distribution analysis (ODA), a new method introduced here, is used to reconstruct the Shanwang Miocene climate based explicitly on local plant distribution data and associated meteorological stations. The Shanwang flora (17-15.2 Ma) suggests a MAT of 10.9-14.5°C and a mean annual precipitation (MAP) of 1107.3-1880.0 mm. This result is closer to the values derived from CLAMP and LMA than that obtained by CA. This report is the first comprehensive intercomparison of foliar physiognomic and nearest living relative climate proxies in a Chinese context and provides important cross validation of results.     

Mitophagy: mechanisms, pathophysiological roles, and analysis

Abstract Mitochondria are essential organelles that regulate cellular energy homeostasis and cell death. The removal of damaged mitochondria through autophagy, a process called mitophagy, is thus critical for maintaining proper cellular functions. Indeed, mitophagy has been recently proposed to play critical roles in terminal differentiation of red blood cells, paternal mitochondrial degradation, neurodegenerative diseases, and ischemia or drug-induced tissue injury. Removal of damaged mitochondria through autophagy requires two steps: induction of general autophagy and priming of damaged mitochondria for selective autophagic recognition. Recent progress in mitophagy studies reveals that mitochondrial priming is mediated either by the Pink1-Parkin signaling pathway or the mitophagic receptors Nix and Bnip3. In this review, we summarize our current knowledge on the mechanisms of mitophagy. We also discuss the pathophysiological roles of mitophagy and current assays used to monitor mitophagy.     

Cocaine: analysis, pharmacokinetics, and metabolic disposition

The ability to measure concentrations of cocaine in body fluids can contribute substantially to any investigation of cocaine's pharmacological effects. Design of research which involves the administration of cocaine must take into account current knowledge regarding the drug's pharmacokinetics. Cocaine's very rapid elimination from the body should be considered in attempting to understand patterns of cocaine abuse, and such phenomena as bingeing and acute tolerance. Accurate analysis of cocaine and/or its metabolites is essential to the diagnosis and evaluation of cocaine use whether for medical or forensic purposes. Appropriate selection of methods for analysis of cocaine depends upon the intended purpose of the assay, and correct interpretation of the data obtained upon knowledge of cocaine's kinetics and metabolic disposition.     

Family-based approaches: design,imputation, analysis,and beyond

Participants in the family-based analysis group at Genetic Analysis Workshop 19 addressed diverse topics, all of which used the family data. Topics addressed included questions of study design and data quality control (QC), genotype imputation to augment available sequence data, and linkage and/or association analyses. Results show that pedigree-based tests that are sensitive to genotype error may be useful for QC. Imputation quality improved with inclusion of small amounts of pedigree information used to phase the data in evaluation of 5 commonly used approaches for imputation in samples of (typically) unrelated subjects. It improved still further when pedigree-based imputation using larger pedigrees was also added. An important distinction was made between methods that do versus do not make use of Mendelian transmission in pedigrees, because this serves as a key difference between underlying models and assumptions. Methods that model relatedness generally had higher power in association testing than did analyses that carry out testing in the presence of a transmission model, but this may reflect details of implementation and/or ability of more general methods to jointly include data from larger pedigrees. In either case, for single nucleotide polymorphism–set approaches, weights that incorporate information on functional effects may be more useful than those that are based only on allele frequencies. The overall results demonstrate that family data continue to provide important information in the search for trait loci.     

Release cells, breath analysis and in-mouth analysis in flavour research

The flavour of a food or beverage is not perceived in a single event, but rather as a series of events experienced as the food is consumed. Recent methods in flavour research have taken account of this, and techniques have been developed to study flavour release in model systems (release cells or simulated mouths) and from the mouth or nose of assessors, while consuming foods. However, while there is agreement on the need in some cases for hydration or artificial saliva in simulated mouths, other parameters must be optimised on a case-by-case basis. Individual variability may still be a problem in breath analysis, and further work is required to determine the extent to which there are real differences in volatile profiles. The techniques of release cells and breath analysis must now be applied to provide data, which will allow flavour release to be modelled.     

Atomic force microscope,molecular imaging,and analysis

Image visibility is a central issue in analyzing all kinds of microscopic images. An increase of intensity contrast helps to raise the image visibility, thereby to reveal fine image features. Accordingly, a proper evaluation of results with current imaging parameters can be used for feedback on future imaging experiments. In this work, we have applied the Laplacian function of image intensity as either an additive component (Laplacian mask) or a multiplying factor (Laplacian weight) for enhancing image contrast of high‐resolution AFM images of two molecular systems, an unknown protein imaged in air, provided by AFM COST Action TD1002 ( http://www.afm4nanomedbio.eu /), and tobacco mosaic virus (TMV) particles imaged in liquid. Based on both visual inspection and quantitative representation of contrast measurements, we found that the Laplacian weight is more effective than the Laplacian mask for the unknown protein, whereas for the TMV system the strengthened Laplacian mask is superior to the Laplacian weight. The present results indicate that a mathematical function, as exemplified by the Laplacian function, may yield varied processing effects with different operations. To interpret the diversity of molecular structure and topology in images, an explicit expression for processing procedures should be included in scientific reports alongside instrumental setups. Copyright © 2015 John Wiley & Sons, Ltd.     

GeneMerge--post-genomic analysis,data mining,and hypothesis testing

SUMMARY: GeneMerge is a web-based and standalone program written in PERL that returns a range of functional and genomic data for a given set of study genes and provides statistical rank scores for over-representation of particular functions or categories in the data set. Functional or categorical data of all kinds can be analyzed with GeneMerge, facilitating regulatory and metabolic pathway analysis, tests of population genetic hypotheses, cross-experiment comparisons, and tests of chromosomal clustering, among others. GeneMerge can perform analyses on a wide variety of genomic data quickly and easily and facilitates both data mining and hypothesis testing. AVAILABILITY: GeneMerge is available free of charge for academic use over the web and for download from: http://www.oeb.harvard.edu/hartl/lab/publications/GeneMerge.html.     

RAG: RNA-As-Graphs database--concepts, analysis, and features

MOTIVATION: Understanding RNA's structural diversity is vital for identifying novel RNA structures and pursuing RNA genomics initiatives. By classifying RNA secondary motifs based on correlations between conserved RNA secondary structures and functional properties, we offer an avenue for predicting novel motifs. Although several RNA databases exist, no comprehensive schemes are available for cataloguing the range and diversity of RNA's structural repertoire. RESULTS: Our RNA-As-Graphs (RAG) database describes and ranks all mathematically possible (including existing and candidate) RNA secondary motifs on the basis of graphical enumeration techniques. We represent RNA secondary structures as two-dimensional graphs (networks), specifying the connectivity between RNA secondary structural elements, such as loops, bulges, stems and junctions. We archive RNA tree motifs as 'tree graphs' and other RNAs, including pseudoknots, as general 'dual graphs'. All RNA motifs are catalogued by graph vertex number (a measure of sequence length) and ranked by topological complexity. The RAG inventory immediately suggests candidates for novel RNA motifs, either naturally occurring or synthetic, and thereby might stimulate the prediction and design of novel RNA motifs. AVAILABILITY: The database is accessible on the web at http://monod.biomath.nyu.edu/rna     

Epigenetics,heritability and longitudinal analysis

Background

Longitudinal data and repeated measurements in epigenome-wide association studies (EWAS) provide a rich resource for understanding epigenetics. We summarize 7 analytical approaches to the GAW20 data sets that addressed challenges and potential applications of phenotypic and epigenetic data. All contributions used the GAW20 real data set and employed either linear mixed effect (LME) models or marginal models through generalized estimating equations (GEE). These contributions were subdivided into 3 categories: (a) quality control (QC) methods for DNA methylation data; (b) heritability estimates pretreatment and posttreatment with fenofibrate; and (c) impact of drug response pretreatment and posttreatment with fenofibrate on DNA methylation and blood lipids.

Results

Two contributions addressed QC and identified large statistical differences with pretreatment and posttreatment DNA methylation, possibly a result of batch effects. Two contributions compared epigenome-wide heritability estimates pretreatment and posttreatment, with one employing a Bayesian LME and the other using a variance-component LME. Density curves comparing these studies indicated these heritability estimates were similar. Another contribution used a variance-component LME to depict the proportion of heritability resulting from a genetic and shared environment. By including environmental exposures as random effects, the authors found heritability estimates became more stable but not significantly different. Two contributions investigated treatment response. One estimated drug-associated methylation effects on triglyceride levels as the response, and identified 11 significant cytosine-phosphate-guanine (CpG) sites with or without adjusting for high-density lipoprotein. The second contribution performed weighted gene coexpression network analysis and identified 6 significant modules of at least 30 CpG sites, including 3 modules with topological differences pretreatment and posttreatment.

Conclusions

Four conclusions from this GAW20 working group are: (a) QC measures are an important consideration for EWAS studies that are investigating multiple time points or repeated measurements; (b) application of heritability estimates between time points for individual CpG sites is a useful QC measure for DNA methylation studies; (c) drug intervention demonstrated strong epigenome-wide DNA methylation patterns across the 2 time points; and (d) new statistical methods are required to account for the environmental contributions of DNA methylation across time. These contributions demonstrate numerous opportunities exist for the analysis of longitudinal data in future epigenetic studies.

     

Ginkgo,a multivariate analysis package

Abstract. The Ginkgo software is a subset of the VegAna (for Vegetation edition and Analysis) package that contains three programs named Quercus, Fagus and Yucca. Ginkgo is a multivariate analysis tool; it is oriented mainly towards ordination and classification of ecological data. Quercus is a relevé table editor; it handles community data to perform a phytosociological analysis. Fagus is a floristic citation editor; it can handle data coming from field surveys, bibliographic sources or collections. Yucca is a cartographic tool; it allows plotting distributions of taxa or syntaxa. VegAna is produced by the Department of Vegetal Biology, University of Barcelona. The general project is directed by Xavier Font I Castell, the Ginkgo module by Francesc Oliva I Cuyàs. Programmers are Miquel De Cáceres and Richard Garcia. This review deals primarily with Ginkgo.     

Epigenetics,heritability and longitudinal analysis

Background

Longitudinal data and repeated measurements in epigenome-wide association studies (EWAS) provide a rich resource for understanding epigenetics. We summarize 7 analytical approaches to the GAW20 data sets that addressed challenges and potential applications of phenotypic and epigenetic data. All contributions used the GAW20 real data set and employed either linear mixed effect (LME) models or marginal models through generalized estimating equations (GEE). These contributions were subdivided into 3 categories: (a) quality control (QC) methods for DNA methylation data; (b) heritability estimates pretreatment and posttreatment with fenofibrate; and (c) impact of drug response pretreatment and posttreatment with fenofibrate on DNA methylation and blood lipids.

Results

Two contributions addressed QC and identified large statistical differences with pretreatment and posttreatment DNA methylation, possibly a result of batch effects. Two contributions compared epigenome-wide heritability estimates pretreatment and posttreatment, with one employing a Bayesian LME and the other using a variance-component LME. Density curves comparing these studies indicated these heritability estimates were similar. Another contribution used a variance-component LME to depict the proportion of heritability resulting from a genetic and shared environment. By including environmental exposures as random effects, the authors found heritability estimates became more stable but not significantly different. Two contributions investigated treatment response. One estimated drug-associated methylation effects on triglyceride levels as the response, and identified 11 significant cytosine-phosphate-guanine (CpG) sites with or without adjusting for high-density lipoprotein. The second contribution performed weighted gene coexpression network analysis and identified 6 significant modules of at least 30 CpG sites, including 3 modules with topological differences pretreatment and posttreatment.

Conclusions

Four conclusions from this GAW20 working group are: (a) QC measures are an important consideration for EWAS studies that are investigating multiple time points or repeated measurements; (b) application of heritability estimates between time points for individual CpG sites is a useful QC measure for DNA methylation studies; (c) drug intervention demonstrated strong epigenome-wide DNA methylation patterns across the 2 time points; and (d) new statistical methods are required to account for the environmental contributions of DNA methylation across time. These contributions demonstrate numerous opportunities exist for the analysis of longitudinal data in future epigenetic studies.