Features generated for computational splice-site prediction correspond to functional elements

<p>Abstract</p> <p>Background</p> <p>Accurate selection of splice sites during the splicing of precursors to messenger RNA requires both relatively well-characterized signals at the splice sites and auxiliary signals in the adjacent exons and introns. We previously described a feature generation algorithm (FGA) that is capable of achieving high classification accuracy on human 3' splice sites. In this paper, we extend the splice-site prediction to 5' splice sites and explore the generated features for biologically meaningful splicing signals.</p> <p>Results</p> <p>We present examples from the observed features that correspond to known signals, both core signals (including the branch site and pyrimidine tract) and auxiliary signals (including GGG triplets and exon splicing enhancers). We present evidence that features identified by FGA include splicing signals not found by other methods.</p> <p>Conclusion</p> <p>Our generated features capture known biological signals in the expected sequence interval flanking splice sites. The method can be easily applied to other species and to similar classification problems, such as tissue-specific regulatory elements, polyadenylation sites, promoters, etc.</p

Sim4cc: a cross-species spliced alignment program

Advances in sequencing technologies have accelerated the sequencing of new genomes, far outpacing the generation of gene and protein resources needed to annotate them. Direct comparison and alignment of existing cDNA sequences from a related species is an effective and readily available means to determine genes in the new genomes. Current spliced alignment programs are inadequate for comparing sequences between different species, owing to their low sensitivity and splice junction accuracy. A new spliced alignment tool, sim4cc, overcomes problems in the earlier tools by incorporating three new features: universal spaced seeds, to increase sensitivity and allow comparisons between species at various evolutionary distances, and powerful splice signal models and evolutionarily-aware alignment techniques, to improve the accuracy of gene models. When tested on vertebrate comparisons at diverse evolutionary distances, sim4cc had significantly higher sensitivity compared to existing alignment programs, more than 10% higher than the closest competitor for some comparisons, while being comparable in speed to its predecessor, sim4. Sim4cc can be used in one-to-one or one-to-many comparisons of genomic and cDNA sequences, and can also be effectively incorporated into a high-throughput annotation engine, as demonstrated by the mapping of 64 000 Fagus grandifolia 454 ESTs and unigenes to the poplar genome

Features generated for computational splice-site prediction correspond to functional elements-5

<p><b>Copyright information:</b></p><p>Taken from "Features generated for computational splice-site prediction correspond to functional elements"</p><p>http://www.biomedcentral.com/1471-2105/8/410</p><p>BMC Bioinformatics 2007;8():410-410.</p><p>Published online 24 Oct 2007</p><p>PMCID:PMC2241647.</p><p></p> location is marked with the red bars (positions -1 and -2) in Figure 7A. The consensus dinucleotide GT location is marked with the red bars (positions 1 and 2), in Figure 7B. For every occurrence of the feature GAAG in the set 4[-80,80], we draw a bar corresponding in height to its CMLS assigned weight. This feature has a negative weight when it is positioned in the intron region, but a positive weight downstream the splice site. For the donor site, we notice its exceptionally high weight at position -4. One possible reason may be the reflection of the donor-site consensus signal

Features generated for computational splice-site prediction correspond to functional elements-2

<p><b>Copyright information:</b></p><p>Taken from "Features generated for computational splice-site prediction correspond to functional elements"</p><p>http://www.biomedcentral.com/1471-2105/8/410</p><p>BMC Bioinformatics 2007;8():410-410.</p><p>Published online 24 Oct 2007</p><p>PMCID:PMC2241647.</p><p></p>for each feature from the feature set -61 [-20,-1]. The presence of the AG dinucleotide upstream the annotated 3' splice site, in the pyrimidine-tract interval is not preferred. All these features have negative weights

Features generated for computational splice-site prediction correspond to functional elements-1

<p><b>Copyright information:</b></p><p>Taken from "Features generated for computational splice-site prediction correspond to functional elements"</p><p>http://www.biomedcentral.com/1471-2105/8/410</p><p>BMC Bioinformatics 2007;8():410-410.</p><p>Published online 24 Oct 2007</p><p>PMCID:PMC2241647.</p><p></p>idine-tract interval, -51 [-20,-1], (Figure 3a and Figure 3b), compared with frequency distribution of the training acceptor and non-acceptor sequences in the same interval (Figure 3c and Figure 3d). The positive features frequency plot corresponds to the acceptor splice-site consensus, which is also illustrated with the true acceptor sequences frequency plot. The negative features frequency plot reveals an AG-rich element

Features generated for computational splice-site prediction correspond to functional elements-0

<p><b>Copyright information:</b></p><p>Taken from "Features generated for computational splice-site prediction correspond to functional elements"</p><p>http://www.biomedcentral.com/1471-2105/8/410</p><p>BMC Bioinformatics 2007;8():410-410.</p><p>Published online 24 Oct 2007</p><p>PMCID:PMC2241647.</p><p></p>te that the distributions of scores for CTGA and CTAA are similar and sharply focused around the peak that would place the branch A at position -24. Note that the distributions of TTTT and CCTT corresponds to the well-known pyrimidine tract with the additional information that C is preferred to T at positions -15 through -11, where a peak of scores for CCTT coincides with a group of negative values for TTTT. There are no occurrences of these four hexamers in this feature set upstream of the region shown

Features generated for computational splice-site prediction correspond to functional elements-3

<p><b>Copyright information:</b></p><p>Taken from "Features generated for computational splice-site prediction correspond to functional elements"</p><p>http://www.biomedcentral.com/1471-2105/8/410</p><p>BMC Bioinformatics 2007;8():410-410.</p><p>Published online 24 Oct 2007</p><p>PMCID:PMC2241647.</p><p></p>ed from the feature set -31 [-30,-45] (A) and -41 [-30,-45] (B). These features are not preferred upstream the donor site, but they are encouraged on the downstream region

Mechanisms of Estrogen Receptor Alternative Splicing and the Consequences for Aging in the Female Brain

The advances in healthcare and scientific knowledge have resulted in longer life expectancies in women. These advanced ages in women now means that they are experiencing the effects of age-related changes in the body for much longer periods of time, mainly reproductive senescence, resulting in the loss of circulating ovarian hormones. The age at which menopause occurs has not changed, resulting in women now living over a third of their lives in a postmenopausal state. The major circulating estrogen produced by the ovaries, 17β-estradiol (E2), has many homeostatic effects in the body like neuroprotection and cardioprotection. Hormone replacement therapy (HT) was to become the standard in treating women undergoing reproductive senescence in order to abrogate the negative effects associated with the decline in circulating E2, however adverse effects of HT were observed mainly women who were at least 10 years removed from menopause. These findings led to the idea of a therapeutic window in which ET is beneficial, known as the “timing hypothesis”, pointing to age-related adjustments that occur during and after this critical period of declining E2 levels. E2 is known to regulate transcription through an important class of nuclear steroid receptors called estrogen receptors (ERs). ERβ mediate the actions of E2 upon binding through interactions within the promoter region of ER-regulated genes and is subject to alternative splicing. It is through this process that ERβ splice variants arise altering the receptor function and responsiveness to E2 in the brain. These observations led to the hypothesis that aging and diminished E2 levels affect the alternative splicing of ERβ in the aged female brain through altered expression of ER-regulated splicing factors. ERβ alternative splice variants were measured in the brain of young and aged female rats who were subjected to increasingly longer periods of hormone deprivation. In vitro data from brain-derived cell lines also provided mechanistic answers to how ERβ is alternatively spliced in the brain. This dissertation work contributes to our overall understanding of ERβ in the context of its expression and possible function in the aging female brain