The prediction of operons in Mycobacterium tuberculosis (MTB) is a first step toward understanding the regulatory network of this pathogen. Here we apply a statistical model using logistic regression to predict operons in MTB. As predictors, our model incorporates intergenic distance and the correlation of gene expression calculated for adjacent gene pairs from over 474 microarray experiments with MTB RNA. We validate our findings with known examples from the literature and experimentation. From this model, we rank each potential operon pair by the strength of evidence for cotranscription, choose a classification threshold with a true positive rate of over 90% at a false positive rate of 9.1%, and use it to construct an operon map for the MTB genome.

BackgroundPhytophthora root and stem rot (PRR) of soybean, caused by Phytophthora sojae, is controlled by Rps genes. However, little is known regarding the Rps-induced molecular responses to P. sojae and how they actually overlap. We thus sequenced, analyzed, and compared the transcriptomes of 10 near isogenic lines (NILs), each with a unique Rps gene/allele, and the susceptible parent Williams, pre- and post-inoculation with the pathogen.ResultsA total of 4,330 differentially expressed genes (DEGs) were identified in Williams versus 2,014 to 5,499 DEGs in individual NILs upon inoculation with the pathogen. Comparisons of the DEGs between the NILs and Williams identified incompatible interaction genes (IIGs) and compatible interaction genes (CIGs). Hierarchical cluster and heatmap analyses consistently grouped the NILs into three clusters: Cluster I (Rps1-a), Cluster II (Rps1-b, 1-c and 1-k) and Cluster III (Rps3-a, 3-b, 3-c, 4, 5, and 6), suggesting an overlap in Rps-induced defense signaling among certain NILs. Gene ontology (GO) analysis revealed associations between members of the WRKY family and incompatible reactions and between a number of phytohormone signaling pathways and incompatible/compatible interactions. These associations appear to be distinguished according to the NIL clusters.ConclusionsThis study characterized genes and multiple branches of putative regulatory networks associated with resistance to P. sojae in ten soybean NILs, and depicted functional “fingerprints” of individual Rps-mediated resistance responses through comparative transcriptomic analysis. Of particular interest are dramatic variations of detected DEGs, putatively involved in ethylene (ET)-, jasmonic acid (JA)-, (reactive oxygen species) ROS-, and (MAP-kinase) MAPK- signaling, among these soybean NILs, implicating their important roles of these signaling in differentiating molecular defense responses. We hypothesize that different timing and robustness in defense signaling to the same pathogen may be largely responsible for such variations.

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Trisomy 21 in humans causes cognitive impairment, craniofacial dysmorphology, and heart defects collectively referred to as Down syndrome. Yet, the pathophysiology of these phenotypes is not well understood. Craniofacial alterations may lead to complications in breathing, eating, and communication. Ts65Dn mice exhibit craniofacial alterations that model Down syndrome including a small mandible. We show that Ts65Dn embryos at 13.5 days gestation (E13.5) have a smaller mandibular precursor but a normal sized tongue as compared to euploid embryos, suggesting a relative instead of actual macroglossia originates during development. Neurological tissues were also altered in E13.5 trisomic embryos. Our array analysis found 155 differentially expressed non-trisomic genes in the trisomic E13.5 mandible, including 20 genes containing a homeobox DNA binding domain. Additionally, Sox9, important in skeletal formation and cell proliferation, was upregulated in Ts65Dn mandible precursors. Our results suggest trisomy causes altered expression of non-trisomic genes in development leading to structural changes associated with DS. Identification of genetic pathways disrupted by trisomy is an important step in proposing rational therapies at relevant time points to ameliorate craniofacial abnormalities in DS and other congenital disorders.

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R code to perform the RASTA procedures is freely available on the web at www.stat.purdue.edu/∼doerge/.

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