Data from: Nonsense-mediated decay of alternative pre-mRNA splicing variants is a major determinant of the Arabidopsis steady state transcriptome

Drechsel G, Kahles A, Kesarwani AK, Stauffer E, Behr J, Drewe P, Rätsch G, Wachter A

Date Published: November 1, 2013

DOI: http://dx.doi.org/10.5061/dryad.hb7j1

 

Files in this package

Content in the Dryad Digital Repository is offered "as is." By downloading files, you agree to the Dryad Terms of Service. To the extent possible under law, the authors have waived all copyright and related or neighboring rights to this data. CC0 (opens a new window) Open Data (opens a new window)

Title Supplemental Data Set 1. Read Statistics of RNA-Seq Data and Computational Analysis of Transcriptome-Wide AS and Gene Expression.
Downloaded 81 times
Description (A) Alignment statistics of all RNA-seq reads derived from Illumina sequencing. (B) - (E) Event based alternative splicing analysis based on comparisons of WT vs. lba1 upf3-1 double mutant (B), WT vs. lba1 (C) and WT vs. upf3-1 (D) single mutants, and Mock vs. CHX treatment (E) datasets. For each AS event and comparison, p and Q values from testing AS variant ratio changes in either one (up) or the other (down) direction as well as the minimum (min) values are provided. Furthermore, rankings within each list according to the p values are provided. (F) Combined list of alternative splicing analyses (based on single comparisons displayed in (B) - (E)) allowing comparison of different datasets on a single event basis. Use matrix in columns R-U to analyze differential gene expression (GE) or AS pattern changes (TE) for the indicated comparisons by changing thresholds for FDR or p values. The matrix allows considering single tests as well as combinations, and both maximum (MAX THRESHOLDS) and minimum (MIN THRESHOLDS) cut-off values can be set. Number of significant changes with given settings are displayed under “SIGNIFICANCE COUNTS”. Results for single events can be viewed and sorted using columns A-P, with values “1” and “0” indicating “FALSE” and “TRUE”, respectively, for fulfilling the criteria set in the matrix shown in columns R-U. Note that the logic provided in this spreadsheet only works if sorting in sheets (B) - (E) is unchanged. (G) Splice Index Score (Percent spliced in, PSI) of all tested alternative splicing events in all samples and replicates (R) analyzed. (H) Table for internal lookup to compute differential gene expression data. Sorting of this table must not be changed. For analyzing differential gene expression use sheet (I). (I) Differential gene expression analysis for all genes and samples. Numbers provide p values. Matrix in columns P-AB can be used to enter gene types and cut-off values for the individual samples, displaying the total number of genes (“COUNT”) fulfilling the set criteria. Further information and a detailed description of the computational pipeline are provided in Supplemental Methods.
Download tpc115485SupplementalDS1.xlsx (39.04 Mb)
Details View File Details
Title Supplemental Data Set 2. Analysis of NMD Target Features for All Events.
Downloaded 45 times
Description (A) General information on mapping of all and the significantly changed alternative splicing events. (B) AS event positions relative to the cds of the representative transcript model annotated in TAIR10 for all AS events and those significantly changed in the different samples. Subsets as described in Figure 3B. (C) Analysis of NMD target feature frequencies for the AS events significantly changed in the indicated samples. For each AS event and dependent on the direction of the AS ratio change, one of the two corresponding splicing variants was assigned to the control sample (WT or Mock treatment), whereas the other was assigned to the NMD-impaired sample (“Δ NMD”). This splicing variant assignment then allowed counting how many of those contained classical NMD features, separately analyzing events mapping to the 5’ UTR, cds, and 3’ UTR. NMD feature inspection included upstream open reading frames (uORFs), translation initiation site (TIS) overlapping uORFs, occurrence of PTCs leading to 3’ UTRs > 347 nts, splice junctions more than 50 nts downstream of a stop codon, and PTC-independent, long 3’ UTRs > 347 nts. (D) Frequency patterns of NMD-eliciting features in different datasets. Occurrence of NMD features described in (C) were analyzed considering the following categories: splicing variant assigned to the control, but not to the NMD impairment has NMD feature (1,0), splicing variant assigned to the NMD impairment, but not to the control has NMD feature (0,1), both splicing variants have NMD feature (1,1), and none splicing variant has NMD feature (0,0). (E) 3’ UTR length distribution for transcripts assigned to the control or NMD-impaired samples for the indicated subsets. Assignments of two splicing variants for each event as described in (C). (F) 5’ UTR length distribution for transcripts assigned to the control or NMD-impaired samples for the indicated subsets. Assignments of two splicing variants for each event as described in (C). (G) Numbers of genes containing single or multiple significantly changed AS events for the indicated subsets. For the genes with multiple events, transcripts with all possible combinations were assembled and analyzed for the rescue of a PTC introduced by a single event. Further details on data analysis are provided in Supplemental Methods.
Download tpc115485SupplementalDS2.xlsx (79.92 Kb)
Details View File Details
Title Supplemental Data Set 3. Analysis of NMD Target Features for Genes Containing Single Events.
Downloaded 51 times
Description (A) AS event positions relative to the cds of the representative transcript model annotated in TAIR10 for all AS events and those significantly changed in the different samples. Subsets as described in Figure 3B. (B) Analysis of NMD target feature frequencies for the AS events significantly changed in the indicated samples. For each AS event and dependent on the direction of the AS ratio change, one of the two corresponding splicing variants was assigned to the control sample (WT or Mock treatment), whereas the other was assigned to the NMD-impaired sample (“Δ NMD”). This splicing variant assignment then allowed counting how many of those contained classical NMD features, separately analyzing events mapping to the 5’ UTR, cds, and 3’ UTR. NMD feature inspection included upstream open reading frames (uORFs), translation initiation site (TIS) overlapping uORFs, occurrence of PTCs leading to 3’ UTRs > 347 nts, splice junctions more than 50 nts downstream of a stop codon, and PTC-independent, long 3’ UTRs > 347 nts. (C) Frequency patterns of NMD-eliciting features in different datasets. Occurrence of NMD features described in (B) were analyzed considering the following categories: splicing variant assigned to the control, but not to the NMD impairment has NMD feature (1,0), splicing variant assigned to the NMD impairment, but not to the control has NMD feature (0,1), both splicing variants have NMD feature (1,1), and none splicing variant has NMD feature (0,0). (D) 3’ UTR length distribution for transcripts assigned to the control or NMD-impaired samples for the indicated subsets. Assignments of two splicing variants for each event as described in (B). (E) 5’ UTR length distribution for transcripts assigned to the control or NMD-impaired samples for the indicated subsets. Assignments of two splicing variants for each event as described in (B). Further details on data analysis are provided in Supplemental Methods.
Download tpc115485SupplementalDS3.xlsx (62.44 Kb)
Details View File Details
Title Supplemental Data Set 4. Categorization of NMD-Regulated and Reference Gene Sets into Functional Subgroups.
Downloaded 52 times
Description (A) Functional categorization of genes derived from the different subsets described in Figure 3B as well as all annotated genes based on the TAIR10 release and all genes displaying AS evidence based on our data (“all AS”). Furthermore, indicated subsets of cassette exon (CE)-containing genes were analyzed. Category bin and names and corresponding counts are listed. (B) Combination of MapMan based functional classifications into different functional subgroups as shown in table on the left side. Numbers of genes falling into these combined categories for the indicated subsets are shown. Below each set, data are also displayed in pie charts. Hypergeometrical test for differential representation of the combined categories are provided for the individual subsets. (C) Differential gene expression data for annotated splicing factors in NMD-impaired samples versus their respective controls based on the analysis described in Supplemental Dataset 1I. Furthermore, expression of the annotated, representative isoforms was analyzed in WT and lba1 upf3-1 using rQuant as described in Supplemental Methods.
Download tpc115485SupplementalDS4.xlsx (323.4 Kb)
Details View File Details
Title Supplemental Data Set 5. Expressed Intergenic Regions and NMD Impairment-Responsive ncRNAs and Pseudogenes.
Downloaded 51 times
Description (A) Differential gene expression data for all annotated ncRNAs based on the analysis described in Supplemental Dataset 1I. Separate display of ncRNAs differentially expressed (either up- or downregulated) in the indicated samples. (B) Differential gene expression of annotated pseudogenic transcripts based on the analysis described in Supplemental Dataset 1I. The matrix provides counts for genes and pseudogenes differentially expressed (p < 0.01) in the indicated NMD-impaired samples relative to their corresponding controls. (C) Expression of identified intergenic regions; listed are total read counts for the indicated subsets and regions. Significantly expressed intergenic regions are marked by an asterisk, colored in green are the regions analyzed in Figure 7D. Furthermore, information on the numbers of intergenic regions, which are more than twofold up- or downregulated in the indicated types of NMD impairments versus their corresponding controls, is indicated below the table. For more detailed information on data analysis see Supplemental Methods.
Download tpc115485SupplementalDS5.xlsx (51.26 Kb)
Details View File Details

When using this data, please cite the original publication:

Drechsel G, Kahles A, Kesarwani AK, Stauffer E, Behr J, Drewe P, Rätsch G, Wachter A (2013) Nonsense-mediated decay of alternative pre-mRNA splicing variants is a major determinant of the Arabidopsis steady state transcriptome. The Plant Cell 25(10): 3726-3742. http://dx.doi.org/10.1105/tpc.113.115485

Additionally, please cite the Dryad data package:

Drechsel G, Kahles A, Kesarwani AK, Stauffer E, Behr J, Drewe P, Rätsch G, Wachter A (2013) Data from: Nonsense-mediated decay of alternative pre-mRNA splicing variants is a major determinant of the Arabidopsis steady state transcriptome. Dryad Digital Repository. http://dx.doi.org/10.5061/dryad.hb7j1
Cite | Share
Download the data package citation in the following formats:
   RIS (compatible with EndNote, Reference Manager, ProCite, RefWorks)
   BibTex (compatible with BibDesk, LaTeX)

Search for data

Be part of Dryad

We encourage organizations to: