New normal linear modeling strategies are presented for analyzing read counts from RNA-seq experiments. The voom method estimates the mean-variance relationship of the log-counts, generates a precision weight for each observation and enters these into the limma empirical Bayes analysis pipeline. This opens access for RNA-seq analysts to a large body of methodology developed for microarrays. Simulation studies show that voom performs as well or better than count-based RNA-seq methods even when the data are generated according to the assumptions of the earlier methods. Two case studies illustrate the use of linear modeling and gene set testing methods.

/pdf/voom-precision-weights-unlock-linear-model-analysis-tools-5bgw8lj2b8.pdf

voom: precision weights unlock linear model analysis tools for RNA-seq read counts

Transcriptomics studies often rely on partial reference transcriptomes that fail to capture the full catalog of transcripts and their variations. Recent advances in sequencing technologies and assembly algorithms have facilitated the reconstruction of the entire transcriptome by deep RNA sequencing (RNA-seq), even without a reference genome. However, transcriptome assembly from billions of RNA-seq reads, which are often very short, poses a significant informatics challenge. This Review summarizes the recent developments in transcriptome assembly approaches - reference-based, de novo and combined strategies-along with some perspectives on transcriptome assembly in the near future.

/pdf/next-generation-transcriptome-assembly-ns6cyvpfx6.pdf

Next-generation transcriptome assembly

Species delimitation is the act of identifying species-level biological diversity. In recent years, the field has witnessed a dramatic increase in the number of methods available for delimiting species. However, most recent investigations only utilize a handful (i.e. 2–3) of the available methods, often for unstated reasons. Because the parameter space that is potentially relevant to species delimitation far exceeds the parameterization of any existing method, a given method necessarily makes a number of simplifying assumptions, any one of which could be violated in a particular system. We suggest that researchers should apply a wide range of species delimitation analyses to their data and place their trust in delimitations that are congruent across methods. Incongruence across the results from different methods is evidence of either a difference in the power to detect cryptic lineages across one or more of the approaches used to delimit species and could indicate that assumptions of one or more of the methods have been violated. In either case, the inferences drawn from species delimitation studies should be conservative, for in most contexts it is better to fail to delimit species than it is to falsely delimit entities that do not represent actual evolutionary lineages.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/mec.12413

How to fail at species delimitation.

Summary: The epidemiology of Clostridium difficile infection (CDI) has changed dramatically during this millennium. Infection rates have increased markedly in most countries with detailed surveillance data. There have been clear changes in the clinical presentation, response to treatment, and outcome of CDI. These changes have been driven to a major degree by the emergence and epidemic spread of a novel strain, known as PCR ribotype 027 (sometimes referred to as BI/NAP1/027). We review the evidence for the changing epidemiology, clinical virulence and outcome of treatment of CDI, and the similarities and differences between data from various countries and continents. Community-acquired CDI has also emerged, although the evidence for this as a distinct new entity is less clear. There are new data on the etiology of and potential risk factors for CDI; controversial issues include specific antimicrobial agents, gastric acid suppressants, potential animal and food sources of C. difficile, and the effect of the use of alcohol-based hand hygiene agents.

The Changing Epidemiology of Clostridium difficile Infections

The regulatory mechanisms by which hydrogen peroxide (H2O2) modulates the activity of transcription factors in bacteria (OxyR and PerR), lower eukaryotes (Yap1, Maf1, Hsf1 and Msn2/4) and mammalian cells (AP-1, NRF2, CREB, HSF1, HIF-1, TP53, NF-κB, NOTCH, SP1 and SCREB-1) are reviewed The complexity of regulatory networks increases throughout the phylogenetic tree, reaching a high level of complexity in mammalians Multiple H2O2 sensors and pathways are triggered converging in the regulation of transcription factors at several levels: (1) synthesis of the transcription factor by upregulating transcription or increasing both mRNA stability and translation; (ii) stability of the transcription factor by decreasing its association with the ubiquitin E3 ligase complex or by inhibiting this complex; (iii) cytoplasm–nuclear traffic by exposing/masking nuclear localization signals, or by releasing the transcription factor from partners or from membrane anchors; and (iv) DNA binding and nuclear transactivation by modulating transcription factor affinity towards DNA, co-activators or repressors, and by targeting specific regions of chromatin to activate individual genes We also discuss how H2O2 biological specificity results from diverse thiol protein sensors, with different reactivity of their sulfhydryl groups towards H2O2, being activated by different concentrations and times of exposure to H2O2 The specific regulation of local H2O2 concentrations is also crucial and results from H2O2 localized production and removal controlled by signals Finally, we formulate equations to extract from typical experiments quantitative data concerning H2O2 reactivity with sensor molecules Rate constants of 140 M−1 s−1 and ≥13 × 103 M−1 s−1 were estimated, respectively, for the reaction of H2O2 with KEAP1 and with an unknown target that mediates NRF2 protein synthesis In conclusion, the multitude of H2O2 targets and mechanisms provides an opportunity for highly specific effects on gene regulation that depend on the cell type and on signals received from the cellular microenvironment

https://repositorio.ipl.pt/bitstream/10400.21/3303/1/Hydrogen%20peroxide%20sensing,%20signaling%20and%20regulation%20of%20transcription%20factors.pdf

Hydrogen peroxide sensing, signaling and regulation of transcription factors

Background: The continued rise of Clostridium difficile infections worldwide has been accompanied by the rapid emergence of a highly virulent clone designated PCR-ribotype 027. To understand more about the evolution of this virulent clone, we made a three-way genomic and phenotypic comparison of an 'historic' non-epidemic 027 C. difficile (CD196), a recent epidemic and hypervirulent 027 (R20291) and a previously sequenced PCR-ribotype 012 strain (630).

/pdf/comparative-genome-and-phenotypic-analysis-of-clostridium-5elhl364ak.pdf

Comparative genome and phenotypic analysis of Clostridium difficile 027 strains provides insight into the evolution of a hypervirulent bacterium

High-density, strand-specific cDNA sequencing (ssRNA–seq) was used to analyze the transcriptome of Salmonella enterica serovar Typhi (S. Typhi). By mapping sequence data to the entire S. Typhi genome, we analyzed the transcriptome in a strand-specific manner and further defined transcribed regions encoded within prophages, pseudogenes, previously un-annotated, and 3′- or 5′-untranslated regions (UTR). An additional 40 novel candidate non-coding RNAs were identified beyond those previously annotated. Proteomic analysis was combined with transcriptome data to confirm and refine the annotation of a number of hpothetical genes. ssRNA–seq was also combined with microarray and proteome analysis to further define the S. Typhi OmpR regulon and identify novel OmpR regulated transcripts. Thus, ssRNA–seq provides a novel and powerful approach to the characterization of the bacterial transcriptome.

/pdf/a-strand-specific-rna-seq-analysis-of-the-transcriptome-of-2nj19p7ucs.pdf

Miao-Xia He

Papers

Comparative genome and phenotypic analysis of Clostridium difficile 027 strains provides insight into the evolution of a hypervirulent bacterium

A Strand-Specific RNA–Seq Analysis of the Transcriptome of the Typhoid Bacillus Salmonella Typhi