MicroRNA-Integrated and Network-Embedded Gene Selection with Diffusion Distance

Gene network information has been used to improve gene selection in microarray-based studies by selecting marker genes based both on their expression and the coordinate expression of genes within their gene network under a given condition. Here we propose a new network-embedded gene selection model. In this model, we first address the limitations of microarray data. Microarray data, although widely used for gene selection, measures only mRNA abundance, which does not always reflect the ultimate gene phenotype, since it does not account for post-transcriptional effects. To overcome this important (critical in certain cases) but ignored-in-almost-all-existing-studies limitation, we design a new strategy to integrate together microarray data with the information of microRNA, the major post-transcriptional regulatory factor. We also handle the challenges led by gene collaboration mechanism. To incorporate the biological facts that genes without direct interactions may work closely due to signal transduction and that two genes may be functionally connected through multi paths, we adopt the concept of diffusion distance. This concept permits us to simulate biological signal propagation and therefore to estimate the collaboration probability for all gene pairs, directly or indirectly-connected, according to multi paths connecting them. We demonstrate, using type 2 diabetes (DM2) as an example, that the proposed strategies can enhance the identification of functional gene partners, which is the key issue in a network-embedded gene selection model. More importantly, we show that our gene selection model outperforms related ones. Genes selected by our model 1) have improved classification capability; 2) agree with biological evidence of DM2-association; and 3) are involved in many well-known DM2-associated pathways

Premature termination codons do not affect the rate of splicing of neighboring introns

Introduction of a premature termination codon (PTC) into an exon of a gene can lead to nonsense-mediated decay of the mRNA, which is best characterized as a cytoplasmic event. However, increasing evidence has suggested that PTCs may also influence the nuclear processing of an RNA transcript, leading to models of nuclear surveillance perhaps involving translating nuclear ribosomes. We used quantitative RT-PCR to measure the in vivo steady-state levels of every exon-intron junction in wild-type, PTC-containing, and missense-containing precursor mRNAs of both the nonrearranging dihydrofolate reductase (DHFR) and the somatically rearranging Ig-μ genes. We find that each exon-intron junction’s abundance and, therefore, the rate of intron removal, is not significantly affected by the presence of a PTC in a neighboring exon in either the DHFR or Ig-μ pre-mRNA. Similarly, the abundance of the uncleaved Ig-μ polyadenylation sites does not differ between wild-type and PTC-containing Ig-μ pre-mRNAs. Our Ig-μ data were confirmed by RNase protection analyses, and multiple cell isolates were examined to resolve differences with previously published data on steady-state pre-mRNA levels. We conclude that the presence of a PTC affects the rate of neither splicing nor the cleavage step of 3′ end formation during pre-mRNA processing in the nucleus. Our results are discussed with respect to existing evidence for nuclear surveillance mechanisms

Small nuclear RNAs encoded by Herpesvirus saimiri upregulate the expression of genes linked to T cell activation in virally transformed T cells

SummarySeven small nuclear RNAs of the Sm class are encoded by Herpesvirus saimiri (HVS), a γ Herpesvirus that causes aggressive T cell leukemias and lymphomas in New World primates and efficiently transforms T cells in vitro [1–4]. The Herpesvirus saimiri U RNAs (HSURs) are the most abundant viral transcripts in HVS-transformed, latently infected T cells but are not required for viral replication or transformation in vitro [5]. We have compared marmoset T cells transformed with wild-type or a mutant HVS lacking the most highly conserved HSURs, HSURs 1 and 2. Microarray and Northern analyses reveal that HSUR 1 and 2 expression correlates with significant increases in a small number of host mRNAs, including the T cell-receptor β and γ chains, the T cell and natural killer (NK) cell-surface receptors CD52 and DAP10, and intracellular proteins—SKAP55, granulysin, and NKG7—linked to T cell and NK cell activation. Upregulation of three of these transcripts was rescued after transduction of deletion-mutant-HVS-transformed cells with a lentiviral vector carrying HSURs 1 and 2. These changes indicate an unexpected role for the HSURs in regulating a remarkably defined and physiologically relevant set of host targets involved in the activation of virally transformed T cells during latency

Spatial patterning of supermarkets and fast food outlets with respect to neighborhood characteristics

A large body of literature has reported differences in exposure to environments supporting either healthy (e.g. supermarkets) or unhealthy (e.g. fast food outlets) dietary choices by neighborhood characteristics. We explored the associations of both supermarkets and fast food outlets availability with neighborhood characteristics, and clustering of these two outlet types in a largely rural state. Compared to block groups without a supermarket, those with a supermarket had a significantly higher income, higher housing value, larger population with high school education and above, lower minority population and lower population living below poverty even after controlling for urbanicity and population density of census block groups. Surprisingly, a similar relationship was found for block groups with and without fast food outlets. This was due to spatial co-occurrence and clustering of fast food outlets around supermarket locations. Hence, future studies exploring the associations of food environment with diet or diet-related health outcome should concurrently examine all aspects of food environment (healthy and unhealthy)