Effect of melphalan in vitro on induction of murine suppressor T cells by ConA

Summary The effect of treatment with melphalan in vitro on the activity of spleen cells from BALB/c mice was investigated. Incubation of spleen cells with 1.5–5 g melphalan/1×10⁷ inhibited subsequent mitogenic stimulation by ConA or PHA and the allogeneic response of BALB/c spleen cells against C57B1 target spleen cells. Incubation of spleen cells with ConA led to induction of suppressor T cells which when added to fresh cultures inhibited the allogeneic response. Preincubation of spleen cells with melphalan even at low concentrations (0.15–0.5 g 1×10⁷ cells) which do not directly affect mitogenic stimulation or allogeneic response partially inhibited the generation of suppressor T cells by ConA. Treatment with melphalan had no effect on already induced suppressor T cells as shown by incubation of spleen cells with melphalan (0.15–5 g/1×10⁷ cells) after incubation with ConA. Addition of cells treated with melphalan alone (without ConA) to fresh cultures led to an increase in the allogeneic response.     

Combining bulk segregation analysis and microarrays for mapping of the pH trait in melon

The availability of sequence information for many plants has opened the way to advanced genetic analysis in many non-model plants. Nevertheless, exploration of genetic variation on a large scale and its use as a tool for the identification of traits of interest are still rare. In this study, we combined a bulk segregation approach with our own-designed microarrays to map the pH locus that influences fruit pH in melon. Using these technologies, we identified a set of markers that are genetically linked to the pH trait. Further analysis using a set of melon cultivars demonstrated that some of these markers are tightly linked to the pH trait throughout our germplasm collection. These results validate the utility of combining microarray technology with a bulk segregation approach in mapping traits of interest in non-model plants.     

Systematic Dissection of the Sequence Determinants of Gene 3’ End Mediated Expression Control

The 3’end genomic region encodes a wide range of regulatory process including mRNA stability, 3’ end processing and translation. Here, we systematically investigate the sequence determinants of 3’ end mediated expression control by measuring the effect of 13,000 designed 3’ end sequence variants on constitutive expression levels in yeast. By including a high resolution scanning mutagenesis of more than 200 native 3’ end sequences in this designed set, we found that most mutations had only a mild effect on expression, and that the vast majority (~90%) of strongly effecting mutations localized to a single positive TA-rich element, similar to a previously described 3’ end processing efficiency element, and resulted in up to ten-fold decrease in expression. Measurements of 3’ UTR lengths revealed that these mutations result in mRNAs with aberrantly long 3’UTRs, confirming the role for this element in 3’ end processing. Interestingly, we found that other sequence elements that were previously described in the literature to be part of the polyadenylation signal had a minor effect on expression. We further characterize the sequence specificities of the TA-rich element using additional synthetic 3’ end sequences and show that its activity is sensitive to single base pair mutations and strongly depends on the A/T content of the surrounding sequences. Finally, using a computational model, we show that the strength of this element in native 3’ end sequences can explain some of their measured expression variability (R = 0.41). Together, our results emphasize the importance of efficient 3’ end processing for endogenous protein levels and contribute to an improved understanding of the sequence elements involved in this process.     

Regulation of tooth number by fine-tuning levels of receptor-tyrosine kinase signaling

Much of our knowledge about mammalian evolution comes from examination of dental fossils, because the highly calcified enamel that covers teeth causes them to be among the best-preserved organs. As mammals entered new ecological niches, many changes in tooth number occurred, presumably as adaptations to new diets. For example, in contrast to humans, who have two incisors in each dental quadrant, rodents only have one incisor per quadrant. The rodent incisor, because of its unusual morphogenesis and remarkable stem cell-based continuous growth, presents a quandary for evolutionary biologists, as its origin in the fossil record is difficult to trace, and the genetic regulation of incisor number remains a largely open question. Here, we studied a series of mice carrying mutations in sprouty genes, the protein products of which are antagonists of receptor-tyrosine kinase signaling. In sprouty loss-of-function mutants, splitting of gene expression domains and reduced apoptosis was associated with subdivision of the incisor primordium and a multiplication of its stem cell-containing regions. Interestingly, changes in sprouty gene dosage led to a graded change in incisor number, with progressive decreases in sprouty dosage leading to increasing numbers of teeth. Moreover, the independent development of two incisors in mutants with large decreases in sprouty dosage mimicked the likely condition of rodent ancestors. Together, our findings indicate that altering genetic dosage of an antagonist can recapitulate ancestral dental characters, and that tooth number can be progressively regulated by changing levels of activity of a single signal transduction pathway.     

Genome-wide midrange transcription profiles reveal expression level relationships in human tissue specification

MOTIVATION: Genes are often characterized dichotomously as either housekeeping or single-tissue specific. We conjectured that crucial functional information resides in genes with midrange profiles of expression. RESULTS: To obtain such novel information genome-wide, we have determined the mRNA expression levels for one of the largest hitherto analyzed set of 62 839 probesets in 12 representative normal human tissues. Indeed, when using a newly defined graded tissue specificity index tau, valued between 0 for housekeeping genes and 1 for tissue-specific genes, genes with midrange profiles having 0.15< tau<0.85 were found to constitute >50% of all expression patterns. We developed a binary classification, indicating for every gene the I(B) tissues in which it is overly expressed, and the 12-I(B) tissues in which it shows low expression. The 85 dominant midrange patterns with I(B)=2-11 were found to be bimodally distributed, and to contribute most significantly to the definition of tissue specification dendrograms. Our analyses provide a novel route to infer expression profiles for presumed ancestral nodes in the tissue dendrogram. Such definition has uncovered an unsuspected correlation, whereby de novo enhancement and diminution of gene expression go hand in hand. These findings highlight the importance of gene suppression events, with implications to the course of tissue specification in ontogeny and phylogeny. AVAILABILITY: All data and analyses are publically available at the GeneNote website, http://genecards.weizmann.ac.il/genenote/ and, GEO accession GSE803. CONTACT: doron.lancet@weizmann.ac.il SUPPLEMENTARY INFORMATION: Four tables available at the above site.     

Metaphor Identification in Large Texts Corpora

Identifying metaphorical language-use (e.g., sweet child) is one of the challenges facing natural language processing. This paper describes three novel algorithms for automatic metaphor identification. The algorithms are variations of the same core algorithm. We evaluate the algorithms on two corpora of Reuters and the New York Times articles. The paper presents the most comprehensive study of metaphor identification in terms of scope of metaphorical phrases and annotated corpora size. Algorithms’ performance in identifying linguistic phrases as metaphorical or literal has been compared to human judgment. Overall, the algorithms outperform the state-of-the-art algorithm with 71% precision and 27% averaged improvement in prediction over the base-rate of metaphors in the corpus.