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An alternate approach to analysis of developmental traits is discussed with information about a study of time-to-flowering in brown midrib mutants of maize. he The related mutations of maize affect lignin biosynthesis. Survival analysis, an accessible technique to improve inferences in cases where distributions are skewed or data missing/incomplete, was used to describe the distribution of times to flowering and compare differences between genotypic classes.

Many biomarkers have been shown to be associated not only with chronological age but also with functional measures of biological age. In human populations, it is difficult to show whether variation in biological age is truly predictive of life expectancy, as such research would require longitudinal studies over many years, or even decades. We followed adult cohorts of 20 Drosophila Genetic Reference Panel (DGRP) strains chosen to represent the breadth of lifespan variation, obtain estimates of lifespan, baseline mortality, and rate of aging, and associate these parameters with age-specific functional traits including fecundity and climbing activity and with age-specific targeted metabolomic profiles. We show that activity levels and metabolome-wide profiles are strongly associated with age, that numerous individual metabolites show a strong association with lifespan, and that the metabolome provides a biological clock that predicts not only sample age but also future mortality rates and lifespan. This study with 20 genotypes and 87 metabolites, while relatively small in scope, establishes strong proof of principle for the fly as a powerful experimental model to test hypotheses about biomarkers and aging and provides further evidence for the potential value of metabolomic profiles as biomarkers of aging. [ABSTRACT FROM AUTHOR]

Estimation of allelic and genotypic distributions for continuous data using kernel density estimation is discussed and illustrated for some variable number of tandem repeat data. These kernel density estimates provide a useful representation of data when only some of the many variants at a locus are present in a sample. Two Hardy-Weinberg test procedures are introduced for continuous data: a continuous chi-square test with test statistic [T.sub.CCS] and a test based on Hellinger's distance with test statistic [T.sub.HD]. Simulations are used to compare the powers of these tests to each other and to the powers of a test of intraclass correlation [T.sub.IC], as well as to the power of Fisher's exact test [T.sub.FET] applied to discretized data. Results indicate that the power of [T.sub.CCS] is better than that of [T.sub.HD], but neither is as powerful as [T.sub.FET]. The intraclass correlation test does not perform as well as the other tests examined in this article.

Background To understand the clinical, bacterial, and host characteristics associated with recurrent Staphylococcus aureus bacteremia (R-SAB), patients with R-SAB were compared to contemporaneous patients with a single episode of SAB (S-SAB). Methods All SAB isolates underwent spa genotyping. All isolates from R-SAB patients underwent pulsed-field gel electrophoresis (PFGE). PFGE-indistinguishable pairs from 40 patients underwent whole genome sequencing (WGS). Acute phase plasma from R-SAB and S-SAB patients was matched 1:1 for age, race, sex, and bacterial genotype, and underwent cytokine quantification using 25-analyte multiplex bead array. Results R-SAB occurred in 69 (9.1%) of the 756 study patients. Of the 69 patients, 30 experienced relapse (43.5%) and 39 reinfection (56.5%). Age, race, hemodialysis dependence, presence of foreign body, methicillin-resistant Staphyloccus aureus , and persistent bacteremia were individually associated with likelihood of recurrence. Multivariate risk modeling revealed that black hemodialysis patients were nearly 2 times more likely (odds ratio [OR] = 9.652 [95% confidence interval [CI], 5.402–17.418]) than white hemodialysis patients (OR = 4.53 [95% CI, 1.696–10.879]) to experience R-SAB. WGS confirmed PFGE interpretations in all cases. Median RANTES (regulated on activation, normal T cell expressed and secreted) levels in acute phase plasma from the initial episode of SAB were higher in R-SAB than in matched S-SAB controls (P  = .0053, false discovery rate < 0.10). Conclusion This study identified several risk factors for R-SAB. The largest risk for R-SAB is among black hemodialysis patients. Higher RANTES levels in R-SAB compared to matched controls warrants further study. [ABSTRACT FROM AUTHOR]

Abstract Background Many analyses of gene expression data involve hypothesis tests of an interaction term between two fixed effects, typically tested using a residual variance. In expression studies, the issue of variance heteroscedasticity has received much attention, and previous work has focused on either between-gene or within-gene heteroscedasticity. However, in a single experiment, heteroscedasticity may exist both within and between genes. Here we develop flexible shrinkage error estimators considering both between-gene and within-gene heteroscedasticity and use them to construct F-like test statistics for testing interactions, with cutoff values obtained by permutation. These permutation tests are complicated, and several permutation tests are investigated here. Results Our proposed test statistics are compared with other existing shrinkage-type test statistics through extensive simulation studies and a real data example. The results show that the choice of permutation procedures has dramatically more influence on detection power than the choice of F or F-like test statistics. When both types of gene heteroscedasticity exist, our proposed test statistics can control preselected type-I errors and are more powerful. Raw data permutation is not valid in this setting. Whether unrestricted or restricted residual permutation should be used depends on the specific type of test statistic. Conclusions The F-like test statistic that uses the proposed flexible shrinkage error estimator considering both types of gene heteroscedasticity and unrestricted residual permutation can provide a statistically valid and powerful test. Therefore, we recommended that it should always applied in the analysis of real gene expression data analysis to test an interaction term.

Abstract Background RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences among samples are beginning to surface. Biological variation has been reported to be larger than technical variation. In addition, technical variation has been reported to be in line with expectations due to random sampling. However, strategies for dealing with technical variation will differ depending on the magnitude. The size of technical variance, and the role of sampling are examined in this manuscript. Results In this study three independent Solexa/Illumina experiments containing technical replicates are analyzed. When coverage is low, large disagreements between technical replicates are apparent. Exon detection between technical replicates is highly variable when the coverage is less than 5 reads per nucleotide and estimates of gene expression are more likely to disagree when coverage is low. Although large disagreements in the estimates of expression are observed at all levels of coverage. Conclusions Technical variability is too high to ignore. Technical variability results in inconsistent detection of exons at low levels of coverage. Further, the estimate of the relative abundance of a transcript can substantially disagree, even when coverage levels are high. This may be due to the low sampling fraction and if so, it will persist as an issue needing to be addressed in experimental design even as the next wave of technology produces larger numbers of reads. We provide practical recommendations for dealing with the technical variability, without dramatic cost increases.

Abstract Background Vibrio vulnificus is the leading cause of reported death from consumption of seafood in the United States. Despite several decades of research on molecular pathogenesis, much remains to be learned about the mechanisms of virulence of this opportunistic bacterial pathogen. The two complete and annotated genomic DNA sequences of V. vulnificus belong to strains of clade 2, which is the predominant clade among clinical strains. Clade 2 strains generally possess higher virulence potential in animal models of disease compared with clade 1, which predominates among environmental strains. SOLiD sequencing of four V. vulnificus strains representing different clades (1 and 2) and biotypes (1 and 2) was used for comparative genomic analysis. Results Greater than 4,100,000 bases were sequenced of each strain, yielding approximately 100-fold coverage for each of the four genomes. Although the read lengths of SOLiD genomic sequencing were only 35 nt, we were able to make significant conclusions about the unique and shared sequences among the genomes, including identification of single nucleotide polymorphisms. Comparative analysis of the newly sequenced genomes to the existing reference genomes enabled the identification of 3,459 core V. vulnificus genes shared among all six strains and 80 clade 2-specific genes. We identified 523,161 SNPs among the six genomes. Conclusions We were able to glean much information about the genomic content of each strain using next generation sequencing. Flp pili, GGDEF proteins, and genomic island XII were identified as possible virulence factors because of their presence in virulent sequenced strains. Genomic comparisons also point toward the involvement of sialic acid catabolism in pathogenesis.

Abstract Background Allele-specific expression (ASE) assays can be used to identify cis, trans, and cis-by-trans regulatory variation. Understanding the source of expression variation has important implications for disease susceptibility, phenotypic diversity, and adaptation. While ASE is commonly measured via relative fluorescence at a SNP, next generation sequencing provides an opportunity to measure ASE in an accurate and high-throughput manner using read counts. Results We introduce a Solexa-based method to perform large numbers of ASE assays using only a single lane of a Solexa flowcell. In brief, transcripts of interest, which contain a known SNP, are PCR enriched and barcoded to enable multiplexing. Then high-throughput sequencing is used to estimate allele-specific expression using sequencing counts. To validate this method, we measured the allelic bias in a dilution series and found high correlations between measured and expected values (r>0.9, p < 0.001). We applied this method to a set of 5 genes in a Drosophila simulans parental mix, F1 and introgression and found that for these genes the majority of expression divergence can be explained by cis-regulatory variation. Conclusion We present a new method with the capacity to measure ASE for large numbers of assays using as little as one lane of a Solexa flowcell. This will be a valuable technique for molecular and population genetic studies, as well as for verification of genome-wide data sets.

Abstract Background A molecular process based genotype-to-phenotype map will ultimately enable us to predict how genetic variation among individuals results in phenotypic alterations. Building such a map is, however, far from straightforward. It requires understanding how molecular variation re-shapes developmental and metabolic networks, and how the functional state of these networks modifies phenotypes in genotype specific way. We focus on the latter problem by describing genetic variation in transcript levels of genes in the InR/TOR pathway among 72 Drosophila melanogaster genotypes. Results We observe tight co-variance in transcript levels of genes not known to influence each other through direct transcriptional control. We summarize transcriptome variation with factor analyses, and observe strong co-variance of gene expression within the dFOXO-branch and within the TOR-branch of the pathway. Finally, we investigate whether major axes of transcriptome variation shape phenotypes expected to be influenced through the InR/TOR pathway. We find limited evidence that transcript levels of individual upstream genes in the InR/TOR pathway predict fly phenotypes in expected ways. However, there is no evidence that these effects are mediated through the major axes of downstream transcriptome variation. Conclusion In summary, our results question the assertion of the 'sparse' nature of genetic networks, while validating and extending candidate gene approaches in the analyses of complex traits.

Abstract Background Beta-adrenergic receptor agonists (BA) induce skeletal muscle hypertrophy, yet specific mechanisms that lead to this effect are not well understood. The objective of this research was to identify novel genes and physiological pathways that potentially facilitate BA induced skeletal muscle growth. The Affymetrix platform was utilized to identify gene expression changes in mouse skeletal muscle 24 hours and 10 days after administration of the BA clenbuterol. Results Administration of clenbuterol stimulated anabolic activity, as indicated by decreased blood urea nitrogen (BUN; P < 0.01) and increased body weight gain (P < 0.05) 24 hours or 10 days, respectively, after initiation of clenbuterol treatment. A total of 22,605 probesets were evaluated with 52 probesets defined as differentially expressed based on a false discovery rate of 10%. Differential mRNA abundance of four of these genes was validated in an independent experiment by quantitative PCR. Functional characterization of differentially expressed genes revealed several categories that participate in biological processes important to skeletal muscle growth, including regulators of transcription and translation, mediators of cell-signalling pathways, and genes involved in polyamine metabolism. Conclusion Global evaluation of gene expression after administration of clenbuterol identified changes in gene expression and overrepresented functional categories of genes that may regulate BA-induced muscle hypertrophy. Changes in mRNA abundance of multiple genes associated with myogenic differentiation may indicate an important effect of BA on proliferation, differentiation, and/or recruitment of satellite cells into muscle fibers to promote muscle hypertrophy. Increased mRNA abundance of genes involved in the initiation of translation suggests that increased levels of protein synthesis often associated with BA administration may result from a general up-regulation of translational initiators. Additionally, numerous other genes and physiological pathways were identified that will be important targets for further investigations of the hypertrophic effect of BA on skeletal muscle.

Despite significant advances in invertebrate phylogenomics over the past decade, the higher-level phylogeny of Pycnogonida (sea spiders) remains elusive. Due to the inaccessibility of some small-bodied lineages, few phylogenetic studies have sampled all sea spider families. Previous efforts based on a handful of genes have yielded unstable tree topologies. Here, we inferred the relationships of 89 sea spider species using targeted capture of the mitochondrial genome, 56 conserved exons, 101 ultraconserved elements, and 3 nuclear ribosomal genes. We inferred molecular divergence times by integrating morphological data for fossil species to calibrate 15 nodes in the arthropod tree of life. This integration of data classes resolved the basal topology of sea spiders with high support. The enigmatic family Austrodecidae was resolved as the sister group to the remaining Pycnogonida and the small-bodied family Rhynchothoracidae as the sister group of the robust-bodied family Pycnogonidae. Molecular divergence time estimation recovered a basal divergence of crown group sea spiders in the Ordovician. Comparison of diversification dynamics with other marine invertebrate taxa that originated in the Paleozoic suggests that sea spiders and some crustacean groups exhibit resilience to mass extinction episodes, relative to mollusk and echinoderm lineages. [ABSTRACT FROM AUTHOR]

Abstract Background It has been reported in the quantitative trait locus (QTL) literature that when testing for QTL location and effect, the statistical power supporting methodologies based on two markers and their estimated genetic map is higher than for the genetic map independent methodologies known as single marker analyses. Close examination of these reports reveals that the two marker approaches are more powerful than single marker analyses only in certain cases. Simulation studies are a commonly used tool to determine the behavior of test statistics under known conditions. We conducted a simulation study to assess the general behavior of an intersection test and a two marker test under a variety of conditions. The study was designed to reveal whether two marker tests are always more powerful than intersection tests, or whether there are cases when an intersection test may outperform the two marker approach. We present a reanalysis of a data set from a QTL study of ovariole number in Drosophila melanogaster. Results Our simulation study results show that there are situations where the single marker intersection test equals or outperforms the two marker test. The intersection test and the two marker test identify overlapping regions in the reanalysis of the Drosophila melanogaster data. The region identified is consistent with a regression based interval mapping analysis. Conclusion We find that the intersection test is appropriate for analysis of QTL data. This approach has the advantage of simplicity and for certain situations supplies equivalent or more powerful results than a comparable two marker test.

Abstract Background Factors that affect flowering vary among different plant species, and in the grasses in particular the exact mechanism behind this transition is not fully understood. The brown midrib (bm) mutants of maize (Zea mays L.), which have altered cell wall composition, have different flowering dynamics compared to their wild-type counterparts. This is indicative of a link between cell wall biogenesis and flowering. In order to test whether this relationship also exists in other grasses, the flowering dynamics in sorghum (Sorghum bicolor (L.) Moench) were investigated. Sorghum is evolutionarily closely related to maize, and a set of brown midrib (bmr) mutants similar to the maize bm mutants is available, making sorghum a suitable choice for study in this context. Results We compared the flowering time (time to half-bloom) of several different bmr sorghum lines and their wild-type counterparts. This revealed that the relationship between cell wall composition and flowering was conserved in sorghum. Specifically, the mutant bmr7 flowered significantly earlier than the corresponding wild-type control, whereas the mutants bmr2, bmr4, bmr6, bmr12, and bmr19 flowered later than their wild-type controls. Conclusion The change in flowering dynamics in several of the brown midrib sorghum lines provides evidence for an evolutionarily conserved mechanism that links cell wall biosynthesis to flowering dynamics. The availability of the sorghum bmr mutants expands the germplasm available to investigate this relationship in further detail.