Fig 1.
Diagramatic overview of how reference based transcripts are removed by TVscript.
Steps (i) to (viii) indicate actions taken. Reference transcripts (green circles) are showen for diagramtic purposes in order to highlight how read counts (grey circles) across replicates are treated for each transcript independently. Read counts are grouped into individual files (gray rectangles) in accordance to replicate. These files are grouped into one of two conditions (blue and brown boxes). Remaining keys are indicated at the bottom.
Fig 2.
Over expressed transcripts pre- and post-filtering using simulated data.
The number of transcripts identified by DESeq2 as being over expressed both prior to (light gray) and post (dark gray) filtering of count datasets within each of the one hundred iterations performed at each level of introduced random intra-condition count variation. Each iteration involved initially simulating ten count datasets divided into conditions A and B following which DESeq2 was run to attempt to identify the one hundred transcripts selected for over representation as described in the methods. Following this the ten simulated datasets were filtered using TVscript with a 95th percentile threshold to generate corresponding filtered datasets (divided into corresponding conditions A’ and B’) on which DESeq2 was re-run.
Fig 3.
Characterization of intra-condition variation.
Percentile range of intra-condition variation scores (x-axis) observed prior to filtering, across both case studies, a) wolves (orange) and dogs (red); b) tame (dark blue) and aggressive (light blue) foxes. PCA plots based on normalized non-filtered count data of the individual datasets comparing c) wolf and dog, and d) tame and aggressive fox. In the latter only individual samples that were positioned within a distant cluster are labelled with the sample ID.
Fig 4.
Removal of transcripts above specified levels of intra-condition variation.
Percentile range of combined intra-condition variation scores (x-axis) present in each case study, a) wolves and dogs; b) tame and aggressive foxes. The number of transcripts removed in the top five percentiles (from the 95th to the 99th) are presented in each panel.
Fig 5.
Effects of removing transcripts above specified levels of intra-condition variation on differential expression analysis.
a) Number of differentially expressed transcripts (DETs) identified using non-filtered (NF) and filtered datasets, based on the top 10 percentiles (99th to the 90th), for both case studies. Up and down regulated transcripts are represented by red and blue dots respectively. Gray arrows identify the selected thresholds for which the results of subsequent corresponding differential expression analysis were used for the identification of candidate transcript associated with tameness within each case study. b) Number of transcripts identified as differentially expressed within the non-filtered datasets that were associated the highest levels of intra-condition variation (99th to 90th) within both case studies, wolves and dogs (orange dots), and tame and aggressive foxes (blue dots).
Fig 6.
Distribution of dispersion estimates.
Plots of final dispersion estimates for both case studies, a) wolves and dogs; b) tame and aggressive foxes, calculated using DESeq2 for the non-filtered (NF; orange) and 10% filtered datasets (90th; blue). Each black dot represents a single transcript, and red dots represent outliers. The number of outliers and correlation index (r2) are displayed in the top right corner of each panel. Both x and y-axis are transformed into a logarithm scale. The line in each graph corresponds to the regression analysis between the mean of normalized counts and dispersion estimates.
Fig 7.
Differentially expressed transcripts overlapping between non-filtered and filtered datasets.
Venn diagrams representing the number of overlapping differential expressed transcripts found following differential expression analysis using non-filtered datasets and filtered datasets (97th, 95th and 90th percentiles), within each case studies. The inset table provides information about the number of differential expressed transcripts lost/added following each filter step in relation to the non-filtered dataset as well as the the percentage of total discordance.
Table 1.
Shared genes and gene families (Up regulation).
List of the gene families, and shared genes, that were commonly up regulated in dogs and tame foxes. The number, and name, of the genes within each gene family are provided, with the corresponding log2fold-change values in brackets for each species. Within each family, single genes were charecterized as shared between dogs and tame foxes (bold), or as exclusively to each of the two groups. When more than one transcript for a specific gene was present, all the log2FC values are reported.
Table 2.
Shared genes and gene families (Down regulation).
List of the gene families, and shared genes, that were commonly down regulated in dogs and tame foxes. The number, and name, of the genes within each gene family are provided, with the corresponding log2fold-change values in brackets for each species. Within each family, single genes were characterized as shared between dogs and tame foxes, or as exclusively to each of the two groups. When more than one transcript for a specific gene was present, all the log2FC values are reported.