Prediction of non-canonical polyadenylation signals in human genomic sequences based on a novel algorithm using a fuzzy membership function.

Computational prediction of polyadenylation signals (PASes) is essential for analysis of alternative polyadenylation that plays crucial roles in gene regulations by generating heterogeneity of 3'-UTR of mRNAs. To date, several algorithms that are mostly based on machine learning methods have been developed to predict PASes. Accuracies of predictions by those algorithms have improved significantly for the last decade. However, they are designed primarily for prediction of the most canonical AAUAAA and its common variant AUUAAA whereas other variants have been ignored in their predictions despite recent studies indicating that non-canonical variants of AAUAAA are more important in the polyadenylation process than commonly recognized. Here we present a new algorithm "PolyF" employing fuzzy logic to confer an advance in computational PAS prediction--enable prediction of the non-canonical variants, and improve the accuracies for the canonical A(A/U)UAAA prediction. PolyF is a simple computational algorithm that is composed of membership functions defining sequence features of downstream sequence element (DSE) and upstream sequence element (USE), together with an inference engine. As a result, PolyF successfully identified the 10 single-nucleotide variants with approximately the same or higher accuracies compared to those for A(A/U)UAAA. PolyF also achieved higher accuracies for A(A/U)UAAA prediction than those by commonly known PAS finder programs, Polyadq and Erpin. Incorporating the USE into the PolyF algorithm was found to enhance prediction accuracies for all the 12 PAS hexamers compared to those using only the DSE, suggesting an important contribution of the USE in the polyadenylation process.

Identification and characterization of polyadenylation signal (PAS) variants in human genomic sequences based on modified EST clustering.

A large-scale analysis of human polyadenylation signals was carried out in silico. The most canonical AAUAAA hexamer and its 11 single-nucleotide variants that are most frequent in human genes were used to search for polyadenylation signals in the terminal sequences. Out of 18,277 poly(A) sites that were identified from 26,414 human genes, 82.5% of the sites were found to contain at least one of these 12 hexamers as a polyadenylation signal within 40 nucleotides upstream of the poly(A) site. The rest (17.5%) did not contain any of these hexamers, which suggests the existence of yet unknown signals. A total of 20,347 terminal sequences in close proximity to 12 polyadenylation signals were collected using modified EST clustering technique to establish a large-scale database of polyadenylation signals. To characterize the 12 hexamers, the locations of polyadenylation signals that were identified as "authentic" and the uracil contents of the downstream region of the signal were examined. Based on this analysis, the 11 variants of the canonical AAUAAA were identified as possibly forming "functional" signals as AAUAAA. Moreover, the observed frequency of 41.9% for AAUAAA was significantly lower than those of other reports, suggesting that the non-canonical variants are more important in the polyadenylation process than frequently recognized. Since the poly(A) sites processed by those non-canonical variants have not been generally annotated in major gene databases, it is important to determine whether the variant hexamers could work as polyadenylation signals that may be responsible for generating heterogeneity of mRNAs by alternative polyadenylation.

Ultrastructural localization of connexins (Cx36, Cx43, Cx45), glutamate receptors and aquaporin-4 in rodent olfactory mucosa, olfactory nerve and olfactory bulb.

Odorant/receptor binding and initial olfactory information processing occurs in olfactory receptor neurons (ORNs) within the olfactory epithelium. Subsequent information coding involves high-frequency spike synchronization of paired mitral/tufted cell dendrites within olfactory bulb (OB) glomeruli via positive feedback between glutamate receptors and closely-associated gap junctions. With mRNA for connexins Cx36, Cx43 and Cx45 detected within ORN somata and Cx36 and Cx43 proteins reported in ORN somata and axons, abundant gap junctions were proposed to couple ORNs. We used freeze-fracture replica immunogold labeling (FRIL) and confocal immunofluorescence microscopy to examine Cx36, Cx43 and Cx45 protein in gap junctions in olfactory mucosa, olfactory nerve and OB in adult rats and mice and early postnatal rats. In olfactory mucosa, Cx43 was detected in gap junctions between virtually all intrinsic cell types except ORNs and basal cells; whereas Cx45 was restricted to gap junctions in sustentacular cells. ORN axons contained neither gap junctions nor any of the three connexins. In OB, Cx43 was detected in homologous gap junctions between almost all cell types except neurons and oligodendrocytes. Cx36 and, less abundantly, Cx45 were present in neuronal gap junctions, primarily at "mixed" glutamatergic/electrical synapses between presumptive mitral/tufted cell dendrites. Genomic analysis revealed multiple miRNA (micro interfering RNA) binding sequences in 3'-untranslated regions of Cx36, Cx43 and Cx45 genes, consistent with cell-type-specific post-transcriptional regulation of connexin synthesis. Our data confirm absence of gap junctions between ORNs, and support Cx36- and Cx45-containing gap junctions at glutamatergic mixed synapses between mitral/tufted cells as contributing to higher-order information coding within OB glomeruli.