Table 1.
Optimization process of total RNA extraction.
Figure 1.
Small RNA Series II Bioanalyzer assay as checkpoint for RNA quantity after extraction procedure.
Intensity of bands in the gel images ([A–D]) depicts the quantity of eluted RNAs with different isolation systems and varying plasma input volumes (0.3–9.0 ml). The first signal at 4 nts is the marker that is included in each run. Image [E] shows an overlay of representative electropherograms to illustrate size proportions. The fluorescence unit (FU) represents the signal intensity of small RNAs.
Figure 2.
High Sensitivity DNA Bioanalyzer assay as checkpoint for correct size selection during library preparation.
All nine samples showed adaptor/RNA/adaptor-constructs in appropriate sizes. One electropherogram is shown as representative example. The lengths of adaptor-ligated constructs from all nine samples were reported as indicated in the column peak size [bp]. The initial peak at 35 bp and the final peak at 10.380 bp are marker peaks that are system inherent included in all runs.
Figure 3.
Sequence length distribution pattern analyzed by FastQC software.
Calculating the average number of sequences with a certain length for all nine plasma samples, the profile displayed a bimodal pattern. The first peak includes sequences with a length between 20 nts and 24 nts reflecting miRNAs. The second peak indicates the piRNA fraction with sequences of 29 nts to 33 nts in size.
Figure 4.
Percentage of mapped and annotated miRNA/piRNA reads compared to the total number of sequences.
Figure 5.
The proportions of trimmed, annotated and non-annotated reads.
The total number of sequenced reads (100%) is divided into reads that failed trimming and reads that passed trimming and were mapped to Rfam database. Reads that were not mapped to Rfam database, were mapped to miRBase. Reads separated into annotated reads in miRBase and in reads that failed miRNA annotation. Image [A] displays miRNA results from mapping to human reference indexes. Image [B] presents miRNA results from mapping to bovine references. Regarding piRNAs (Image [C]), reads that could not be mapped to miRBase were aligned to piRNA database. They separate into annotated piRNAs and unmapped piRNAs.
Table 2.
miRNA data analysis shows the composition of evaluated reads from nine animals generated by computer data analysis pipeline using free software tools.
Table 3.
piRNA data analysis shows the composition of evaluated reads from nine animals generated by computer data analysis pipeline using free software tools.
Figure 6.
Sequence motif analysis to evaluate piRNA 5′-T-bias.
Image [A] shows the piRNA reference that was used for alignment and Image [B] represents the nucleotide composition of mapped piRNAs pointing out the T-bias at 5′.