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Illumina TruSeq Synthetic Long-Reads Empower De Novo Assembly and Resolve Complex, Highly-Repetitive Transposable Elements

Figure 3

Results of generalized linear mixed model describing probability of accurate TE assembly.

Predictor variables include: TE length (, , ), GC content (, , ), divergence (, , ), and number of high-identity (0.01 substitutions per base compared to the canonical sequence) copies within family (, , ). Black lines represent predicted values from the GLMM fit to the binary data (colored points). The upper sets of points represent TEs which were perfectly assembled, while the lower set of points represent TEs which are absent from the assembly or were mis-assembled with respect to the reference. The exact positions of the colored points along the Y-axis should therefore be disregarded. Colors indicate different TE families (122 total). To visualize the interaction between divergence and the number of high-identity copies (, , ), we plotted predicted values for both families with low numbers of high-identity copies (dashed line) as well as families with high numbers of high-identity copies (solid line).

doi: https://doi.org/10.1371/journal.pone.0106689.g003