Short-lived AUF1 p42-binding mRNAs of RANKL and BCL6 have two distinct instability elements each.

Regulation of mRNA stability by RNA-protein interactions contributes significantly to quantitative aspects of gene expression. We have identified potential mRNA targets of the AU-rich element binding protein AUF1. Myc-tagged AUF1 p42 was induced in mouse NIH/3T3 cells and RNA-protein complexes isolated using anti-myc tag antibody beads. Bound mRNAs were analyzed with Affymetrix microarrays. We have identified 508 potential target mRNAs that were at least 3-fold enriched compared to control cells without myc-AUF1. 22.3% of the enriched mRNAs had an AU-rich cluster in the ARED Organism database, against 16.3% of non-enriched control mRNAs. The enrichment towards AU-rich elements was also visible by AREScore with an average value of 5.2 in the enriched mRNAs versus 4.2 in the control group. Yet, numerous mRNAs were enriched without a high ARE score. The enrichment of tetrameric and pentameric sequences suggests a broad AUF1 p42-binding spectrum at short U-rich sequences flanked by A or G. Still, some enriched mRNAs were highly unstable, as those of TNFSF11 (known as RANKL), KLF10, HES1, CCNT2, SMAD6, and BCL6. We have mapped some of the instability determinants. HES1 mRNA appeared to have a coding region determinant. Detailed analysis of the RANKL and BCL6 3'UTR revealed for both that full instability required two elements, which are conserved in evolution. In RANKL mRNA both elements are AU-rich and separated by 30 bases, while in BCL6 mRNA one is AU-rich and 60 bases from a non AU-rich element that potentially forms a stem-loop structure.

Concordance among digital gene expression, microarrays, and qPCR when measuring differential expression of microRNAs.

Profiling microRNA (miRNA) expression is of widespread interest given the critical role of miRNAs in many cellular functions. Profiling can be achieved via hybridization-based (microarrays), sequencing-based, or amplification-based (quantitative reverse transcription-PCR, qPCR) technologies. Among these, microarrays face the significant challenge of accurately distinguishing between mature and immature miRNA forms, and different vendors have developed different methods to meet this challenge. Here we measure differential miRNA expression using the Affymetrix, Agilent, and Illumina microarray platforms, as well as qPCR (Applied Biosystems) and ultra high-throughput sequencing (Illumina). We show that the differential expression measurements are more divergent when the three types of microarrays are compared than when the Agilent microarray, qPCR, and sequencing technology measurements are compared, which exhibit a good overall concordance.

Affymetrix Whole-Transcript Human Gene 1.0 ST array is highly concordant with standard 3' expression arrays.

The recently released Affymetrix Human Gene 1.0 ST array has two major differences compared with standard 3' based arrays: (i) it interrogates the entire mRNA transcript, and (ii) it uses DNA targets. To assess the impact of these differences on array performance, we performed a series of comparative hybridizations between the Human Gene 1.0 ST and the Affymetrix HG-U133 Plus 2.0 and the Illumina HumanRef-8 BeadChip arrays. Additionally, both RNA and DNA targets were hybridized on HG-U133 Plus 2.0 arrays. The results show that the overall reproducibility of the Gene 1.0 ST array is best. When looking only at the high intensity probes, the reproducibility of the Gene 1.0 ST array and the Illumina BeadChip array is equally good. Concordance of array results was assessed using different inter-platform mappings. Agreements are best between the two labeling protocols using HG-U133 Plus 2.0 array. The Gene 1.0 ST array is most concordant with the HG-U133 array hybridized with cDNA targets. This may reflect the impact of the target type. Overall, the high degree of correspondence provides strong evidence for the reliability of the Gene 1.0 ST array.

Host and invader impact of transfer of the clc genomic island into Pseudomonas aeruginosa PAO1.

Genomic islands, large potentially mobile regions of bacterial chromosomes, are a major contributor to bacteria evolution. Here, we investigated the fitness cost and phenotypic differences between the bacterium Pseudomonas aeruginosa PAO1 and a derivative carrying one integrated copy of the clc element, a 103-kb genomic island [and integrative and conjugative element (ICE)] originating in Pseudomonas sp. strain B13 and a close relative of genomic islands found in clinical and environmental isolates of P. aeruginosa. By using a combination of whole genome transcriptome profiling, phenotypic arrays, competition experiments, and biofilm formation studies, only few differences became apparent, such as reduced biofilm growth and fourfold stationary phase repression of genes involved in acetoin metabolism in PAO1 containing the clc element. In contrast, PAO1 carrying the clc element acquired the capacity to grow on 3-chlorobenzoate and 2-aminophenol as sole carbon and energy substrates. No fitness loss >1% was detectable in competition experiments between PAO1 and PAO1 carrying the clc element. The genes from the clc element were not silent in PAO1, and excision was observed, although transfer of clc from PAO1 to other recipient bacteria was reduced by two orders of magnitude. Our results indicate that newly acquired mobile DNA not necessarily invoke an important fitness cost on their host. Absence of immediate detriment to the host may have contributed to the wide distribution of genomic islands like clc in bacterial genomes.

Homer1a is a core brain molecular correlate of sleep loss.

Sleep is regulated by a homeostatic process that determines its need and by a circadian process that determines its timing. By using sleep deprivation and transcriptome profiling in inbred mouse strains, we show that genetic background affects susceptibility to sleep loss at the transcriptional level in a tissue-dependent manner. In the brain, Homer1a expression best reflects the response to sleep loss. Time-course gene expression analysis suggests that 2,032 brain transcripts are under circadian control. However, only 391 remain rhythmic when mice are sleep-deprived at four time points around the clock, suggesting that most diurnal changes in gene transcription are, in fact, sleep-wake-dependent. By generating a transgenic mouse line, we show that in Homer1-expressing cells specifically, apart from Homer1a, three other activity-induced genes (Ptgs2, Jph3, and Nptx2) are overexpressed after sleep loss. All four genes play a role in recovery from glutamate-induced neuronal hyperactivity. The consistent activation of Homer1a suggests a role for sleep in intracellular calcium homeostasis for protecting and recovering from the neuronal activation imposed by wakefulness.

An amylase/Cre transgene marks the whole endoderm but the primordia of liver and ventral pancreas.

Mice bearing a Cre-encoding transgene driven by a compound [SV40 small t antigen/mousealpha-amylase-2] promoter expressed the recombinase at early developmental stages broadly in the embryonic endoderm before the pancreas and lungs begin to outgrow, but not in other germ layers, as determined indirectly by beta-galactosidase and YFP reporter activity, indicating that the transgene is in fact an endodermic marker. Interestingly, the liver and ventral pancreas were excluded from this expression pattern, denoting that the chimerical alpha-amylase-2 promoter was not active in the anterior leading edge of the endoderm (the presumptive region from which liver and ventral pancreas form). These transgenics thus confirm, among other findings, that dorsal and ventral pancreatic primordia have different intrinsic transcriptional capabilities. In conclusion, we have generated a new transgenic mouse that should be useful to target endoderm at early stages, without affecting the liver or ventral pancreas before embryonic day E12.5.