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As an example, the median probeset signal estimates in hESCs and hCNS-SCns of the FIP1L1 gene (gene identifiers BC011543, AL136910) had a Pearson correlation coefficient of 0.38, and the distribution of points was not amenable to robust regression (Figure 4A).
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CellFinder
To avoid inappropriate application of REAP and generating false predictions, we empirically determined that a gene had to have a Pearson correlation coefficient cutoff of 0.6 before being amenable to REAP analysis.
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CellFinder
Next, we managed two additional sources of FPs, namely “high-leverage” and “high-influence” points, which we were able to identify by computing the following metrics.
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CellFinder
For every point, we computed (i) the studentized residual (as described above), (ii) the influence, and (iii) the leverage (see Materials and Methods for more details).
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CellFinder
Leverage assessed how far away a value of the independent variable was from the mean value; the farther away the observation the more leverage it had.
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CellFinder
The influence of a point was related to its covariance ratio: a covariance ratio larger (or smaller) than 1 implied that the point was closer (or farther) than was typical to the regression line, so removing it would hurt (or help) the accuracy of the line and would increase (or decrease) the error term variance.
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CellFinder
Influence was computed as the absolute difference between the covariance ratio and unity.
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CellFinder
To illustrate further, a point was classified as an “outlier” if it had a large studentized residual (p < 0.01) and low leverage (boxed point “a”); as a “high-leverage” point if it had a low studentized residual and high leverage (boxed point “b”); and as a “high-influence” point if it had a high studentized residual, high leverage, and high influence (boxed point “c”; Figure 4B).
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CellFinder
Points that resembled boxed point “a” were designated as potential AS events.
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CellFinder
For example, four of the five boxed points in Figure 3C were “outliers,” and RT-PCR validation indicated that the exon represented by the probeset was indeed skipped in hCNS-SCns (EHBP1, Figure 7B).
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CellFinder
Points that were “high-leverage,” such as the five points in the CLCN2 gene, were experimentally verified to be a FP (Figure 4C; unpublished data).
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CellFinder
Points that were “high-influence,” such as the four of five boxed points in the ABCA3 gene were also experimentally verified to be a FP (Figure 4D; unpublished data).
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CellFinder
In conclusion, in order to reduce the FP rate, all points were evaluated according to the metrics described, and points that were significant “outliers” were considered putative AS events.
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CellFinder
Figure 4Sources of False Positives(A) Scatter plot of points for the FIP1L1 gene and the line representing the robust regression estimate.(B) Boxed point “a” represents a significant “outlier” (with a significantly different studentized residual and low leverage).
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CellFinder
Boxed point “b” represents a “high leverage” point (low studentized residual and a high leverage).
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CellFinder
Boxed point “c” represents a “high influence” point (high studentized residual, high leverage, and high influence).(C) Scatter plot of points for the CLCN2 gene.
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CellFinder
Boxed points represent “high leverage” points.(D) Scatter plot of points for the ABCA3 gene.
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CellFinder
Boxed points represent “high influence” points.
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CellFinder
Global Identification and Characterization of REAP[+] ExonsREAP was applied to identify AS events in NPs compared to hESCs: Cyt-NP versus Cyt-ES; HUES6-NP versus HUES6-ES; hCNS-SCns versus Cyt-ES, and hCNS-SCns versus HUES6-ES.
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CellFinder
After removing potential FPs, 11,348 genes containing 158,657 probesets were scored by REAP.As described above, for each pair of cell lines compared, each probset was represented by five points, where each point was defined a significant outlier if it had a high residual (p < 0.01), low influence, and high leverage.
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CellFinder
Points per probeset should be correlated; in other words, if one point was a significant outlier, the other points were expected to be outliers as well.
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CellFinder
To ensure that this was the case, we counted the number of probesets with N significant outliers, where N was varied from 0 to 5.
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CellFinder
Next, the identity of the probesets and points derived from them were exchanged with other probesets, keeping constant the total number of points that were considered significant outliers.
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CellFinder
At N = 0, we observed approximately equal numbers of probesets in the actual versus shuffled controls.
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CellFinder
In contrast, we observed that there were 1.5 times more probesets with N = 2 significant outliers relative to shuffled controls; 12–31 times more probesets with N = 3; and 17–612 times more probesets that had N = 4 significant outliers (Figure 5A; see Table S1).
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CellFinder
For example, in hCNS-SCns compared to Cyt-ES, approximately 0.39% (490 of 124,604) of probesets had three significant outliers and 0.25% (308 probesets) had four significant outliers, relative to 0.02% and 0% of shuffled controls, respectively.
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CellFinder
Figure 5Correlation between “Outliers”(A) The number of probesets with N significant “outliers” was determined for hCNS-SCns versus Cyt-ES, hCNS-SCns versus HUES6-ES, Cyt-NPs versus Cyt-ES, and HUES6-NPs versus HUES6-ES (N = 0, 1, 2, 3, 4, 5).
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CellFinder
For comparison, points to probeset relationships were randomly permuted, retaining the same number of “outliers.”
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CellFinder
Vertical bars represent the ratio between the number of actual points and the randomly permutated sets.(B) Similar to (A), except points were counted as “outliers” only if they were “outliers” in both hCNS-SCns versus Cyt-ES and hCNS-SCns versus HUES6-ES (combined hCNS-SCns versus hESC; blue bars); in both HUES6-NP versus HUES6-ES and Cyt-NP versus Cyt-ES (combined derived NP versus hESC; red bars); and in all four comparisons (combined NP versus hESC; yellow bar).Next we asked whether the overlap between related comparisons was higher than expected.
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CellFinder
Comparing the significant probesets between hCNS-SCns versus Cyt-ES and hCNS-SCns versus HUES6-ES revealed 672 significant probesets (N ≥ 2), whereas if we shuffled the associations between probeset identity and significant outliers, only four significant probesets (N ≥ 2) were identified—a 168-fold enrichment (Figure 5B, Table S1).
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CellFinder
A total of 236 significant probesets overlapped when we compared the derived NPs to hESCs (Cyt-NP versus Cyt-ES and HUES6-NP versus HUES6-ES), relative to seven significant probesets (34-fold enrichment).At a cutoff of two significant outliers, 1,737 probesets contained in internal exons were defined as positive REAP predictions (hereafter called REAP[+]) exons—candidate AS events that distinguished NP from hESC.
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CellFinder
Surprisingly, we observed that the majority of REAP[+] exons were specific to the pair of hESC and NP that was compared, likely reflecting differences in genetic origins and/or culturing and differentiation conditions of the cell lines: 614 REAP[+] events were unique to hCNS-SCns versus HUE6-ES; 220 were unique to hCNS-SCns versus Cyt-ES; 439 were unique to HUES6-NP versus HUES6-ES; and 250 were unique to Cyt-NP versus Cyt-ES.
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CellFinder
The shared events between pairs of comparisons made up a minority of the total number identified: 102 REAP[+] events were found to be in common between hCNS-SCns versus Cyt-ES and hCNS-SCns versus HUES6-ES; 48 between hCNS-SCns versus HUES6-ES and HUES6-NP versus HUES6-ES; and only 17 between hCNS-SCns versus Cyt-ES and Cyt-NP versus Cyt-ES (Table S2).
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CellFinder
Comparison of REAP to EST-Based Method and ACEScanTraditionally, AS exons were discovered by using EST alignments to genomic loci, and also more recently by computational algorithms that used sequence information extracted from multiple genomes.
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CellFinder
Here, we compared REAP predictions to both approaches.
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CellFinder
In the first comparison, publicly available ESTs and mRNA transcripts were aligned to the human genome sequence.
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CellFinder
13,934 exons with evidence for exon-skipping and/or inclusion (EST-SE for EST-verified skipped exons) were generated, comprising ∼7% of all internal exons.
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CellFinder
First we analyzed Cyt-ES versus hCNS-SCns.
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CellFinder
If we required that none of the points per probeset (exon) was significant, 6% (4,402 of 71,731) of exons (after probeset mapping) had evidence for EST-SE (Figure 6A).
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CellFinder
Shuffling the mapping between these probesets and exons resulted in 8% (5,777 of 71,731) of exons with evidence for EST-SE (Figure 6A).
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CellFinder
These percentages were not significantly different from the 7% of exons with EST evidence for AS observed from using all exons.
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CellFinder
By raising the requirement that probesets had to contain at least one significant point to five significant points, the percentage of EST-SE increased dramatically from 11% (531 of 4,898 exons) to 26% (33 of 126).
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CellFinder
In comparison, the shuffled probesets at the same requirements remained at ∼8%, rising slightly to 11% at five points, due to small sample sizes.
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CellFinder
Similar trends were observed with hCNS-SCns versus HUES6-ES and the derived NPs versus hESCs (Figure 6A).
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CellFinder
Therefore, we concluded that REAP[+] exons were enriched for AS events independently identified by a transcript-based approach.
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CellFinder
Figure 6Comparison of REAP Predictions for hCNS-SCns versus Cyt-hES, hCNS-SCns versus HUES6-ES, Cyt-NP versus Cyt-ES, and HUES6-NPs versus HUES6-ES with Alternative Exons Identified by an EST-Based Method and ACEScan(A) Black-filled squares represented the fraction of exons containing probesets with N significant points that had EST evidence for exon inclusion or exclusion (N = 0, 1, 2, 3, 4 and 5).
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CellFinder
White-filled triangles represented similarly computed fractions with permuted probeset to exon mappings.(B) Black-filled squares represented the fraction of exons containing probesets with N significant points that had ACEScan positive scores, indicative of evolutionarily conserved alternative exons.
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CellFinder
White-filled triangles represented similarly computed fractions with permuted probeset to exon mappings.
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CellFinder
Next, we compared REAP predictions to a computational approach of identifying exons with AS conserved in human and mouse, ACEScan [55].
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CellFinder
ACEScan receives as input orthologous human–mouse exon pairs and flanking intronic regions and computes sequence features and integrates the features into a machine-learning algorithm to assign a real-valued score to the exon.
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CellFinder
A positive score indicated a higher likelihood of being AS in both human and mouse.
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CellFinder
ACEScan was updated in the following ways.
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CellFinder
Firstly, instead of relying on orthology information by Ensembl, and then aligning flanking introns in “orthologous” exons, conserved exonic and intronic regions in human and mouse from genome-wide multiple alignments were extracted.
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CellFinder
Secondly, whereas in our previous analysis exons from the longest transcript in Ensembl were utilized, now we collapsed all the transcripts available at the UCSC genome browser and analyzed all exons in the entire gene loci.
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CellFinder
ACEScan was utilized to assign ACEScan scores to all ∼162,000 internal exons in our genes.
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CellFinder
Exons annotated as first or last exons in Refseq mRNAs were excluded from our analysis, resulting in 4,487 positive-scoring exons, 2-fold more exons than originally published.
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CellFinder
Here we repeated our analysis with exons with positive ACEScan scores (ACE[+]) instead of EST-SEs.
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CellFinder
If we required that none of the points per probeset (exon) was significant, 2% (1,645 of 71,731) of exons (after probeset mapping) were ACE[+] (Figure 6B).
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CellFinder
Shuffling the mapping between these probesets and exons resulted in 3% (2,044 of 71,731) of exons being ACE[+] (Figure 6B).
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CellFinder
These percentages were not significantly different from the 2.7% observed from all exons (4,487 of the 162,000 exons that were scored by ACEScan).
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CellFinder
By raising the requirement that probesets had to contain five significant points, the percentage of ACE[+] exons increased from 4% to 11%.
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CellFinder
However, the sample sizes were small.
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CellFinder
In comparison, the shuffled probesets at the same requirements remained at ∼4%.
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CellFinder
Similar overall trends were observed with hCNS-SCns versus HUES6-ES and the derived NPs versus hESCs (Figure 6B).
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CellFinder
In total, 7.5% (131 of 1,737) of REAP [+] exons were designated as ACEScan[+] compared to 2.4% (2,328 of 97,437) of REAP[−] exons.
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CellFinder
This result suggested that a small but significantly enriched fraction of AS events in hESCs versus NPs was likely to be evolutionarily conserved in human and mouse.
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CellFinder
In conclusion, our results suggested that REAP predictions were congruent with predictions from two independent, orthogonal methods.
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CellFinder
Experimental Validation of Alternative ExonsThe sensitivity and specificity of REAP in the identification of REAP[+] exons was tested by RT-PCR.
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CellFinder
To validate REAP[+] alternative exons, RT-PCR primers were designed in the flanking exons to amplify both isoforms.
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CellFinder
To be a positively validated candidate, the PCR products on a gel had to satisfy all of the following criteria: (i) at least one isoform with the expected size must be visible in each cell type; (ii) the relative abundance of the two isoforms must be altered between two cell types and the direction of change have to be consistent with the REAP studentized residuals: in our study positive residuals implied inclusion in hESCs and skipping in NPs, and negative residuals implied inclusion in NP and skipping in hESCs; and (iii) the results were replicable in at least two experiments.
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CellFinder
For simplicity of design, we tested candidates predicted from Cyt-ES versus hCNS-SCns.
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CellFinder
Fifteen REAP[+] exons with at least two significant outliers (out of five) were randomly chosen as predicted alternative events and thirty-five exons with less than two significant outliers were randomly chosen as constitutive events (Table S3).
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CellFinder
Nine of the fifteen exons (60%) were validated as AS events by our criteria.
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CellFinder
The sensitivity and specificity of the algorithm at the cutoff of two is 69% and 77%.
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CellFinder
Increasing the cutoff to three increased the specificity to 85%, with a slight decrease in sensitivity to 67% (Figure 7A).
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CellFinder
The patterns of AS in hESCs were similar in both Cyt-ES and HUES6-ES for all AS events validated, but the NPs (Cyt-NP, HUES6-NP, and hCNS-SCns) had more varied AS.
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CellFinder
The pattern of AS in the REAP[+] exons in the SLK (serine/threonine kinase 2) and POT1 (protection of telomeres 1) genes showed remarkable agreement within derived NPs and hCNS-SCns (Figure 7B).
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CellFinder
The AS exon in SLK was observed to be included in hESCs and completely excluded in NPs; the AS exon in the POT1 gene was included more in hESCs and a smaller isoform persisted in NPs.
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CellFinder
The AS patterns of the other verified REAP[+] exons were consistently similar in hESCs but were more varied in the NP.
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CellFinder
Interestingly, the patterns of AS in the derived NPs (Cyt-NP and HUES6-NP) were not always identical to those of hCNS-SCns.
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CellFinder
For example, the AS exon in the EHBP1 (EH domain binding protein 1) gene was included in hESCs but skipped in hCNS-SCns, and both isoforms were present in the derived NPs (Figure 7B).
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CellFinder
As another example, the AS exon in the SORBS1 (sorbin and SH3 domain containing 1) gene was skipped in hESCs and included in hCNS-SCns, but exhibited an intermediate pattern in the derived NPs.
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CellFinder
However, in some cases, the AS patterns in the derived NPs were different from both hESCs and hCNS-SCns (such as in the AS exon in UNC84A, SIRT1, and MLLT10).Figure 7RT-PCR Validation of REAP-Predicted Alternative Exons(A) Probesets (exons) were considered REAP[+] candidates if they contained at least N = 2 (white bars), 3 (gray bars), or 4 (black bars) significant outliers.
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CellFinder
True positive (TP), true negative (TN), false positive (FP), and false negative (FN) rates were calculated from RT-PCR-validated REAP[+] exons at the different cutoffs (N = 2, 3, 4).(B) Nine RT-PCR validated REAP[+] AS events in hESCs (Cyt-ES and HUES6-ES), derived NPs (Cyt-NP and HUES6-NP), and hCNS-SCns.
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CellFinder
Arrows indicate the larger (exon-included) isoforms and smaller (exon-skipped) isoforms.(C) RT-PCR of REAP[+] alternative exons from EHBP1, SLK, and RAI14 across a panel of human tissues.
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Arrows indicate the larger (exon-included) isoforms and smaller (exon-skipped) isoforms.
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First, given three independent samples each from two conditions, we concluded that REAP was able to identify AS events with high specificity but with moderate sensitivity.
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Second, AS events in hESCs were more similar, whereas the AS events in derived NPs were consistent with or intermediate to the benchmark hCNS-SCns, likely reflecting differences in the cell lines and/or differentiation protocols.
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In addition, we tested the AS patterns of REAP[+] exons from EHBP1, SLK, and RAI14 in a panel of differentiated human tissues (Figure 7C).
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The REAP[+] alternative exon in the RAI14 (retinoic acid induced 14) gene was observed to have the same AS pattern in NPs as in frontal and temporal cortex and in several other, non-brain adult tissues, such as heart and spleen.
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CellFinder
The AS pattern of the REAP[+] exon in the SLK gene in NPs was similar to most differentiated tissues; however, the relatively strong inclusion of the exon in hESCs was unique.
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CellFinder
Even in esophagus, kidney, liver, and prostate, both isoforms were present.
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The relative ratio of the exon-included to exon-skipped isoforms in SLK likely represents an ESC-specific AS signature.
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The alternative exon in the EHBP1 gene was unusual.
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The exon was included in hESCs but also in frontal cortex and temporal cortex, a finding that was unexpected given the exclusion of the exon in hCNS-SCns (Figure 7C).
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CellFinder
The AS pattern in hCNS-SCns may represent a transient, early neuronal molecular change.
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CellFinder
Functional and Expression Characteristics of REAP[+] GenesIn total, 1,500 genes were identified that contained 1,737 REAP[+] exons, 68% of which lacked prior transcript (EST/cDNA) evidence for AS.
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To determine whether genes that contained REAP[+] exons, which we refer to as REAP[+] genes, are biased toward particular biological activities, REAP[+] genes were compared to a set of REAP analyzed genes not found to have REAP[+] exons (REAP[−] genes).
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A Gene Ontology analysis revealed that REAP[+] genes are enriched for GO molecular function categories “ATP binding,” “helicase activity,” “protein serine/theronine kinase activity,” “small GTPase regulatory/interacting protein activity,” and “thyroid hormone receptor binding” (Table 1).
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In terms of GO biological process categories, REAP[+] genes were more frequently involved in “ubiquitin cycle.”
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CellFinder