Complex organizational structure of the genome revealed by genome-wide analysis of single and alternative promoters in Drosophila melanogaster

<p>Abstract</p> <p>Background</p> <p>The promoter is a critical necessary transcriptional <it>cis</it>-regulatory element. In addition to its role as an assembly site for the basal transcriptional apparatus, the promoter plays a key part in mediating temporal and spatial aspects of gene expression through differential binding of transcription factors and selective interaction with distal enhancers. Although many genes have multiple promoters, little attention has been focused on how these relate to one another; nor has much study been directed at relationships between promoters of adjacent genes.</p> <p>Results</p> <p>We have undertaken a systematic investigation of <it>Drosophila </it>promoters. We divided promoters into three groups: unique promoters, first alternative promoters (the most 5' of a gene's multiple promoters), and downstream alternative promoters (the remaining alternative promoters 3' to the first). We observed distinct nucleotide distribution and sequence motif preferences among these three classes. We also investigated the promoters of neighboring genes and found that a greater than expected number of adjacent genes have similar sequence motif profiles, which may allow the genes to be regulated in a coordinated fashion. Consistent with this, there is a positive correlation between similar promoter motifs and related gene expression profiles for these genes.</p> <p>Conclusions</p> <p>Our results suggest that different regulatory mechanisms may apply to each of the three promoter classes, and provide a mechanism for "gene expression neighborhoods," local clusters of co-expressed genes. As a whole, our data reveal an unexpected complexity of genomic organization at the promoter level with respect to both alternative and neighboring promoters.</p

Computational discovery of cis-regulatory modules in Drosophila without prior knowledge of motifs

Prediction of cis-regulatory modules ab initio, without any input of relevant motifs, is achieved with two novel methods

Syphilis and parvovirus B19 co-infection imitating a lupus nephropathy: A case report.

Syphilis can share clinical features with autoimmune diseases, such as cutaneous Lupus or rheumatoid arthritis. Moreover, secondary syphilis can have visceral involvement, thus affecting the kidney. Syphilitic nephropathy causes nephrotic syndrome with a classic membranous pattern. We present a unique presentation of a co-infection by syphilis and parvovirus B19 sharing all the biological and histological features of proliferative lupus nephritis (LN). We present a case of a 71-year-old Caucasian male returning from a trip to Asia presenting with nephrotic syndrome with antinuclear antibodies (ANA) positivity. Because of nephrotic syndrome a kidney biopsy was performed. It demonstrated a membranous nephropathy with extracapillary proliferation and a full house pattern (presence of IgA, IgG, IgM and C1Q deposits) on immunofluorescence (IF), highly suggestive of LN class III and V. However, several atypical clinical features notably the age, sex of the patient and the history of travel prompt us to search for another cause of nephropathy. A serology was positive for syphilis and a PCR in the renal biopsy was also positive for parvovirus B19. Thus, a co-infection by syphilis and parvovirus B19 was funded to be the cause of the renal lesions. The proteinuria improved; a course of antibiotic was administrated because of neurologic syphilitic involvement (presence of headache with positive syphilis serology in the CSF). A co-infection by syphilis and parvovirus B19 can share all the biological and histological features of proliferative LN and must be recognized as a cause of pseudo-lupus nephritis

HHV-8-negative multicentric Castleman disease presenting as a crescentic immune complexes membranoproliferative glomerulonephritis.

Multicentric Castleman disease is a rare polyclonal lymphoproliferative disorder mainly associated with two renal manifestations: thrombotic microangiopathy and amyloidosis. Nevertheless, we report here a case of human herpes virus-8 negative multicentric Castleman disease with membranous proliferative glomerulonephritis and extracapillary proliferation. A patient was successfully treated with corticosteroids, anti-CD20 and cyclophosphamide therapy

Large-scale analysis of transcriptional cis-regulatory modules reveals both common features and distinct subclasses

Analysis of 280 experimentally-verified cis-regulatory modules from Drosophila reveal features both common to all and unique to distinct subclasses of modules

Preferred analysis methods for Affymetrix GeneChips revealed by a wholly defined control dataset

BACKGROUND: As more methods are developed to analyze RNA-profiling data, assessing their performance using control datasets becomes increasingly important. RESULTS: We present a 'spike-in' experiment for Affymetrix GeneChips that provides a defined dataset of 3,860 RNA species, which we use to evaluate analysis options for identifying differentially expressed genes. The experimental design incorporates two novel features. First, to obtain accurate estimates of false-positive and false-negative rates, 100-200 RNAs are spiked in at each fold-change level of interest, ranging from 1.2 to 4-fold. Second, instead of using an uncharacterized background RNA sample, a set of 2,551 RNA species is used as the constant (1x) set, allowing us to know whether any given probe set is truly present or absent. Application of a large number of analysis methods to this dataset reveals clear variation in their ability to identify differentially expressed genes. False-negative and false-positive rates are minimized when the following options are chosen: subtracting nonspecific signal from the PM probe intensities; performing an intensity-dependent normalization at the probe set level; and incorporating a signal intensity-dependent standard deviation in the test statistic. CONCLUSIONS: A best-route combination of analysis methods is presented that allows detection of approximately 70% of true positives before reaching a 10% false-discovery rate. We highlight areas in need of improvement, including better estimate of false-discovery rates and decreased false-negative rates