Whole-transcriptome, high-throughput RNA sequence analysis of the bovine macrophage response to Mycobacterium bovis infection in vitro

BACKGROUND: Mycobacterium bovis, the causative agent of bovine tuberculosis, is an intracellular pathogen that can persist inside host macrophages during infection via a diverse range of mechanisms that subvert the host immune response. In the current study, we have analysed and compared the transcriptomes of M. bovis-infected monocyte-derived macrophages (MDM) purified from six Holstein-Friesian females with the transcriptomes of non-infected control MDM from the same animals over a 24 h period using strand-specific RNA sequencing (RNA-seq). In addition, we compare gene expression profiles generated using RNA-seq with those previously generated by us using the high-density Affymetrix® GeneChip® Bovine Genome Array platform from the same MDM-extracted RNA. RESULTS: A mean of 7.2 million reads from each MDM sample mapped uniquely and unambiguously to single Bos taurus reference genome locations. Analysis of these mapped reads showed 2,584 genes (1,392 upregulated; 1,192 downregulated) and 757 putative natural antisense transcripts (558 upregulated; 119 downregulated) that were differentially expressed based on sense and antisense strand data, respectively (adjusted P-value ≤ 0.05). Of the differentially expressed genes, 694 were common to both the sense and antisense data sets, with the direction of expression (i.e. up- or downregulation) positively correlated for 693 genes and negatively correlated for the remaining gene. Gene ontology analysis of the differentially expressed genes revealed an enrichment of immune, apoptotic and cell signalling genes. Notably, the number of differentially expressed genes identified from RNA-seq sense strand analysis was greater than the number of differentially expressed genes detected from microarray analysis (2,584 genes versus 2,015 genes). Furthermore, our data reveal a greater dynamic range in the detection and quantification of gene transcripts for RNA-seq compared to microarray technology. CONCLUSIONS: This study highlights the value of RNA-seq in identifying novel immunomodulatory mechanisms that underlie host-mycobacterial pathogen interactions during infection, including possible complex post-transcriptional regulation of host gene expression involving antisense RNA

Standard errors and confidence intervals in within-subjects designs: Generalizing Loftus and Masson (1994) and avoiding the biases of alternative accounts

Repeated measures designs are common in experimental psychology. Because of the correlational structure in these designs, the calculation and interpretation of confidence intervals is nontrivial. One solution was provided by Loftus and Masson (Psychonomic Bulletin & Review 1:476–490, 1994). This solution, although widely adopted, has the limitation of implying same-size confidence intervals for all factor levels, and therefore does not allow for the assessment of variance homogeneity assumptions (i.e., the circularity assumption, which is crucial for the repeated measures ANOVA). This limitation and the method’s perceived complexity have sometimes led scientists to use a simplified variant, based on a per-subject normalization of the data (Bakeman & McArthur, Behavior Research Methods, Instruments, & Computers 28:584–589, 1996; Cousineau, Tutorials in Quantitative Methods for Psychology 1:42–45, 2005; Morey, Tutorials in Quantitative Methods for Psychology 4:61–64, 2008; Morrison & Weaver, Behavior Research Methods, Instruments, & Computers 27:52–56, 1995). We show that this normalization method leads to biased results and is uninformative with regard to circularity. Instead, we provide a simple, intuitive generalization of the Loftus and Masson method that allows for assessment of the circularity assumption

Illuminating Choices for Library Prep: A Comparison of Library Preparation Methods for Whole Genome Sequencing of Cryptococcus neoformans Using Illumina HiSeq.

The industry of next-generation sequencing is constantly evolving, with novel library preparation methods and new sequencing machines being released by the major sequencing technology companies annually. The Illumina TruSeq v2 library preparation method was the most widely used kit and the market leader; however, it has now been discontinued, and in 2013 was replaced by the TruSeq Nano and TruSeq PCR-free methods, leaving a gap in knowledge regarding which is the most appropriate library preparation method to use. Here, we used isolates from the pathogenic fungi Cryptococcus neoformans var. grubii and sequenced them using the existing TruSeq DNA v2 kit (Illumina), along with two new kits: the TruSeq Nano DNA kit (Illumina) and the NEBNext Ultra DNA kit (New England Biolabs) to provide a comparison. Compared to the original TruSeq DNA v2 kit, both newer kits gave equivalent or better sequencing data, with increased coverage. When comparing the two newer kits, we found little difference in cost and workflow, with the NEBNext Ultra both slightly cheaper and faster than the TruSeq Nano. However, the quality of data generated using the TruSeq Nano DNA kit was superior due to higher coverage at regions of low GC content, and more SNPs identified. Researchers should therefore evaluate their resources and the type of application (and hence data quality) being considered when ultimately deciding on which library prep method to use

Prevalence and dynamics of ribosomal DNA micro-heterogeneity are linked to population history in two contrasting yeast species

Despite the considerable number and taxonomic breadth of past and current genome sequencing projects, many of which necessarily encompass the ribosomal DNA, detailed information on the prevalence and evolutionary significance of sequence variation in this ubiquitous genomic region are severely lacking. Here, we attempt to address this issue in two closely related yet contrasting yeast species, the baker's yeast Saccharomyces cerevisiae and the wild yeast Saccharomyces paradoxus. By drawing on existing datasets from the Saccharomyces Genome Resequencing Project, we identify a rich seam of ribosomal DNA sequence variation, characterising 1,068 and 970 polymorphisms in 34 S. cerevisiae and 26 S. paradoxus strains respectively. We discover the two species sets exhibit distinct mutational profiles. Furthermore, we show for the first time that unresolved rDNA sequence variation resulting from imperfect concerted evolution of the ribosomal DNA region follows a U-shaped allele frequency distribution in each species, similar to loci that evolve under non-concerted mechanisms but arising through rather different evolutionary processes. Finally, we link differences between the shapes of these allele frequency distributions to the two species' contrasting population histories

Comparative genomics of Escherichia coli isolated from patients with inflammatory bowel disease

<p>Abstract</p> <p>Background</p> <p>Inflammatory bowel disease (IBD) is used to describe a state of idiopathic, chronic inflammation of the gastrointestinal tract. The two main phenotypes of IBD are Crohn's disease (CD) and ulcerative colitis (UC). The major cause of IBD-associated mortality is colorectal cancer. Although both host-genetic and exogenous factors have been found to be involved, the aetiology of IBD is still not well understood. In this study we characterized thirteen <it>Escherichia coli </it>strains from patients with IBD by comparative genomic hybridization employing a microarray based on 31 sequenced <it>E. coli </it>genomes from a wide range of commensal and pathogenic isolates.</p> <p>Results</p> <p>The IBD isolates, obtained from patients with UC and CD, displayed remarkably heterogeneous genomic profiles with little or no evidence of group-specific determinants. No IBD-specific genes were evident when compared with the prototypic CD isolate, LF82, suggesting that the IBD-inducing effect of the strains is multifactorial. Several of the IBD isolates carried a number of extraintestinal pathogenic <it>E. coli </it>(ExPEC)-related virulence determinants such as the <it>pap</it>, <it>sfa</it>, <it>cdt </it>and <it>hly </it>genes. The isolates were also found to carry genes of ExPEC-associated genomic islands.</p> <p>Conclusions</p> <p>Combined, these data suggest that <it>E. coli </it>isolates obtained from UC and CD patients represents a heterogeneous population of strains, with genomic profiles that are indistinguishable to those of ExPEC isolates. Our findings indicate that IBD-induction from <it>E. coli </it>strains is multifactorial and that a range of gene products may be involved in triggering the disease.</p

Effects of Picture Size Reduction and Blurring on Emotional Engagement

The activity of basic motivational systems is reflected in emotional responses to arousing stimuli, such as natural pictures. The manipulation of picture properties such as size or detail allows for investigation into the extent to which separate emotional reactions are similarly modulated by perceptual changes, or, rather, may subserve different functions. Pursuing this line of research, the present study examined the effects of two types of perceptual degradation, namely picture size reduction and blurring, on emotional responses. Both manipulations reduced picture relevance and dampened affective modulation of skin conductance, possibly because of a reduced action preparation in response to degraded or remote pictures. However, the affective modulation of the startle reflex did not vary with picture degradation, suggesting that the identification of these degraded affective cues activated the neural circuits mediating appetitive or defensive motivation

New Assembly, Reannotation and Analysis of the Entamoeba histolytica Genome Reveal New Genomic Features and Protein Content Information

Entamoeba histolytica is an anaerobic parasitic protozoan that causes amoebic dysentery. The parasites colonize the large intestine, but under some circumstances may invade the intestinal mucosa, enter the bloodstream and lead to the formation of abscesses such amoebic liver abscesses. The draft genome of E. histolytica, published in 2005, provided the scientific community with the first comprehensive view of the gene set for this parasite and important tools for elucidating the genetic basis of Entamoeba pathogenicity. Because complete genetic knowledge is critical for drug discovery and potential vaccine development for amoebiases, we have re-examined the original draft genome for E. histolytica. We have corrected the sequence assembly, improved the gene predictions and refreshed the functional gene assignments. As a result, this effort has led to a more accurate gene annotation, and the discovery of novel features, such as the presence of genome segmental duplications and the close association of some gene families with transposable elements. We believe that continuing efforts to improve genomic data will undoubtedly help to identify and characterize potential targets for amoebiasis control, as well as to contribute to a better understanding of genome evolution and pathogenesis for this parasite

On the interpretation of removable interactions: A survey of the field 33 years after Loftus

In a classic 1978 Memory &Cognition article, Geoff Loftus explained why noncrossover interactions are removable. These removable interactions are tied to the scale of measurement for the dependent variable and therefore do not allow unambiguous conclusions about latent psychological processes. In the present article, we present concrete examples of how this insight helps prevent experimental psychologists from drawing incorrect conclusions about the effects of forgetting and aging. In addition, we extend the Loftus classification scheme for interactions to include those on the cusp between removable and nonremovable. Finally, we use various methods (i.e., a study of citation histories, a questionnaire for psychology students and faculty members, an analysis of statistical textbooks, and a review of articles published in the 2008 issue of Psychology andAging) to show that experimental psychologists have remained generally unaware of the concept of removable interactions. We conclude that there is more to interactions in a 2 × 2 design than meets the eye

CodingQuarry: Highly accurate hidden Markov model gene prediction in fungal genomes using RNA-seq transcripts

Background: The impact of gene annotation quality on functional and comparative genomics makes gene prediction an important process, particularly in non-model species, including many fungi. Sets of homologous protein sequences are rarely complete with respect to the fungal species of interest and are often small or unreliable, especially when closely related species have not been sequenced or annotated in detail. In these cases, protein homology-based evidence fails to correctly annotate many genes, or significantly improve ab initio predictions. Generalised hidden Markov models (GHMM) have proven to be invaluable tools in gene annotation and, recently, RNA-seq has emerged as a cost-effective means to significantly improve the quality of automated gene annotation. As these methods do not require sets of homologous proteins, improving gene prediction from these resources is of benefit to fungal researchers. While many pipelines now incorporate RNA-seq data in training GHMMs, there has been relatively little investigation into additionally combining RNA-seq data at the point of prediction, and room for improvement in this area motivates this study. Results: CodingQuarry is a highly accurate, self-training GHMM fungal gene predictor designed to work with assembled, aligned RNA-seq transcripts. RNA-seq data informs annotations both during gene-model training and in prediction. Our approach capitalises on the high quality of fungal transcript assemblies by incorporating predictions made directly from transcript sequences. Correct predictions are made despite transcript assembly problems, including those caused by overlap between the transcripts of adjacent gene loci. Stringent benchmarking against high-confidence annotation subsets showed CodingQuarry predicted 91.3% of Schizosaccharomyces pombe genes and 90.4% of Saccharomyces cerevisiae genes perfectly. These results are 4-5% better than those of AUGUSTUS, the next best performing RNA-seq driven gene predictor tested. Comparisons against whole genome Sc. pombe and S. cerevisiae annotations further substantiate a 4-5% improvement in the number of correctly predicted genes. Conclusions: We demonstrate the success of a novel method of incorporating RNA-seq data into GHMM fungal gene prediction. This shows that a high quality annotation can be achieved without relying on protein homology or a training set of genes. CodingQuarry is freely available (https://sourceforge.net/projects/codingquarry/), and suitable for incorporation into genome annotation pipelines