Next generation sequencing technology provides a powerful tool for measuring gene expression (mRNA) levels in the form of RNA-sequence data. Method development for identifying differentially expressed (DE) genes from RNA-seq data, which frequently includes many low-count integers and can exhibit severe overdispersion relative to Poisson or binomial 1

Some strains of the foliar pathogen Pseudomonas syringae are adapted for growth and survival on leaf surfaces and in the leaf interior. Global transcriptome profiling was used to evaluate if these two habitats offer distinct environments for bacteria and thus present distinct driving forces for adaptation. The transcript profiles of Pseudomonas syringae pv. syringae B728a support a model in which leaf surface, or epiphytic, sites specifically favor flagellar motility, swarming motility based on 3-(3-hydroxyalkanoyloxy)alkanoic acid surfactant production, chemosensing, and chemotaxis, indicating active relocation primarily on the leaf surface. Epiphytic sites also promote high transcript levels for phenylalanine degradation, which may help counteract phenylpropanoidbased defenses before leaf entry. In contrast, intercellular, or apoplastic, sites favor the high-level expression of genes for GABA metabolism (degradation of these genes would attenuate GABA repression of virulence) and the synthesis of phytotoxins, two additional secondary metabolites, and syringolin A. These findings support roles for these compounds in virulence, including a role for syringolin A in suppressing defense responses beyond stomatal closure. A comparison of the transcriptomes from in planta cells and from cells exposed to osmotic stress, oxidative stress, and iron and nitrogen limitation indicated that water availability, in particular, was limited in both leaf habitats but was more severely limited in the apoplast than on the leaf surface under the conditions tested. These findings contribute to a coherent model of the adaptations of this widespread bacterial phytopathogen to distinct habitats within its host.endophyte | epiphyte | phyllosphere

Typically, F 1 -hybrids are more vigorous than their homozygous, genetically distinct parents, a phenomenon known as heterosis. In the present study, the transcriptomes of the reciprocal maize (Zea mays L.) hybrids B733Mo17 and Mo173B73 and their parental inbred lines B73 and Mo17 were surveyed in primary roots, early in the developmental manifestation of heterotic root traits. The application of statistical methods and a suitable experimental design established that 34,233 (i.e., 86%) of all high-confidence maize genes were expressed in at least one genotype. Nearly 70% of all expressed genes were differentially expressed between the two parents and 42%-55% of expressed genes were differentially expressed between one of the parents and one of the hybrids. In both hybrids,~10% of expressed genes exhibited nonadditive gene expression. Consistent with the dominance model (i.e., complementation) for heterosis, 1124 genes that were expressed in the hybrids were expressed in only one of the two parents. For 65 genes, it could be shown that this was a consequence of complementation of genomic presence/absence variation. For dozens of other genes, alleles from the inactive inbred were activated in the hybrid, presumably via interactions with regulatory factors from the active inbred. As a consequence of these types of complementation, both hybrids expressed more genes than did either parental inbred. Finally, in hybrids,~14% of expressed genes exhibited allele-specific expression (ASE) levels that differed significantly from the parental-inbred expression ratios, providing further evidence for interactions of regulatory factors

Innovations in sequencing technologies have allowed biologists to make incredible advances in understanding biological systems. As experience grows, researchers increasingly recognize that analyzing the wealth of data provided by these new sequencing platforms requires careful attention to detail for robust results. Thus far, much of the scientific Communit’s focus for use in bacterial genomics has been on evaluating genome assembly algorithms and rigorously validating assembly program performance. Missing, however, is a focus on critical evaluation of variant callers for these genomes. Variant calling is essential for comparative genomics as it yields insights into nucleotide-level organismal differences. Variant calling is a multistep process with a host of potential error sources that may lead to incorrect variant calls. Identifying and resolving these incorrect calls is critical for bacterial genomics to advance. The goal of this review is to provide guidance on validating algorithms and pipelines used in variant calling for bacterial genomics. First, we will provide an overview of the variant calling procedures and the potential sources of error associated with the methods. We will then identify appropriate datasets for use in evaluating algorithms and describe statistical methods for evaluating algorithm performance. As variant calling moves from basic research to the applied setting, standardized methods for performance evaluation and reporting are required; it is our hope that this review provides the groundwork for the development of these standards.

The plant pathogen Pseudomonas syringae pv. syringae B728a grows and survives on leaf surfaces and in the leaf apoplast of its host, bean (Phaseolus vulgaris). To understand the contribution of distinct regulators to B728a fitness and pathogenicity, we performed a transcriptome analysis of strain B728a and nine regulatory mutants recovered from the surfaces and interior of leaves and exposed to environmental stresses in culture. The quorum-sensing regulators AhlR and AefR influenced few genes in planta or in vitro. In contrast, GacS and a downstream regulator, SalA, formed a large regulatory network that included a branch that regulated diverse traits and was independent of plant-specific environmental signals and a plant signal-dependent branch that positively regulated secondary metabolite genes and negatively regulated the type III secretion system. SalA functioned as a central regulator of iron status based on its reciprocal regulation of pyoverdine and achromobactin genes and also sulfur uptake, suggesting a role in the iron-sulfur balance. RetS functioned almost exclusively to repress secondary metabolite genes when the cells were not on leaves. Among the sigma factors examined, AlgU influenced many more genes than RpoS, and most AlgU-regulated genes depended on RpoN. RpoN differentially impacted many AlgU- and GacS-activated genes in cells recovered from apoplastic versus epiphytic sites, suggesting differences in environmental signals or bacterial stress status in these two habitats. Collectively, our findings illustrate a central role for GacS, SalA, RpoN, and AlgU in global regulation in B728a in planta and a high level of plasticity in these regulators’ responses to distinct environmental signals.

There is a critical need for standard approaches to assess, report and compare the technical performance of genome-scale differential gene expression experiments. Here we assess technical performance with a proposed standard 'dashboard' of metrics derived from analysis of external spike-in RNA control ratio mixtures. These control ratio mixtures with defined abundance ratios enable assessment of diagnostic performance of differentially expressed transcript lists, limit of detection of ratio (LODR) estimates and expression ratio variability and measurement bias. The performance metrics suite is applicable to analysis of a typical experiment, and here we also apply these metrics to evaluate technical performance among laboratories. An interlaboratory study using identical samples shared among 12 laboratories with three different measurement processes demonstrates generally consistent diagnostic power across 11 laboratories. Ratio measurement variability and bias are also comparable among laboratories for the same measurement process. We observe different biases for measurement processes using different mRNA-enrichment protocols.

The nematode Caenorhabditis elegans is used extensively in molecular, toxicological and genetics research. However, standardized methods for counting nematodes in liquid culture do not exist despite the wide use of nematodes and need for accurate measurements. Herein, we provide a simple and affordable counting protocol developed to maximize count accuracy and minimize variability in liquid nematode culture. Sources of variability in the counting process were identified and tested in 14 separate experiments. Three variables resulted in significant effects on nematode count: shaking of the culture, priming of pipette tips, and sampling location within a microcentrifuge tube. Between-operator variability did not have a statistically significant effect on counts, even among differently-skilled operators. The protocol was used to assess population growth rates of nematodes in two different but common liquid growth media: axenic modified Caenorhabditis elegans Habitation and Reproduction medium (mCeHR) and S-basal complete. In mCeHR, nematode populations doubled daily for 10 d. S-basal complete populations initially doubled every 12 h, but slowed within 7 d. We also detected a statistically significant difference between embryo-to-hatchling incubation period of 5 d in mCeHR compared to 4 d in S-basal complete. The developed counting method for Caenorhabditis elegans reduces variability and allows for rigorous and reliable experimentation.

The forensic science community has increasingly sought quantitative methods for conveying the weight of evidence. Experts from many forensic laboratories summarize their fndings in terms of a likelihood ratio. Several proponents of this approach have argued that Bayesian reasoning proves it to be normative. We fnd this likelihood ratio paradigm to be unsupported by arguments of Bayesian decision theory, which applies only to personal decision making and not to the transfer of information from an expert to a separate decision maker. We further argue that decision theory does not exempt the presentation of a likelihood ratio from uncertainty characterization, which is required to assess the ftness for purpose of any transferred quantity. We propose the concept of a lattice of assumptions leading to an uncertainty pyramid as a framework for assessing the uncertainty in an evaluation of a likelihood ratio. We demonstrate the use of these concepts with illustrative examples regarding the refractive index of glass and automated comparison scores for fngerprints.Key words: assumptions lattice; Bayes' factor; Bayes' rule; Bayesian decision theory; subjective probability; uncertainty; uncertainty pyramid. Executive SummaryIn response to calls from the broader scientifc community [1,2] and concerns of the general public, experts in many disciplines of forensic science have increasingly sought to develop and use objective or quantitative methods to convey the meaning of evidence to others, such as an attorney or members of a jury. Support is growing, especially in Europe [3,4], for a recommendation that forensic experts communicate their fndings using a "likelihood ratio" (see Appendix A for an introduction to likelihood ratios). Proponents of this approach [5 11] appear to believe that it is supported by Bayesian reasoning, a paradigm often viewed as normative (i.e., the right way; what someone should use) for making decisions when uncertainty exists [12 14].Individuals following Bayesian reasoning may establish their personal degrees of belief regarding the truth of a claim in the form of odds (i.e., ratio of their probability that the claim is true to their probability that the claim is false), taking into account all information currently available to them. Upon encountering new evidence, individuals quantify their "weight of evidence" as a personal likelihood ratio. Following Bayes' rule, individuals multiply their previous (or prior) odds by their respective likelihood ratios to obtain their updated (or posterior) odds, refecting their revised degrees of belief regarding the claim in question. Because the likelihood ratio is subjective and personal, we fnd that the proposed framework in which a forensic expert provides a likelihood ratio for others to use in Bayes' equation is unsupported by Bayesian Journal of Research of National Institute of Standards and Technology decision theory, which applies only to personal decision making and not to the transfer of information from an expert to a separate decision maker, s...