Additional file 4 of RNA profiles differ between small and large extracellular vesicle subsets isolated from porcine seminal plasma

Additional file 4 (.xlsx). Table S1. Raw data for the RNAs identified in each of 12 samples of small (S) and 12 samples of large (L) extracellular vesicles isolated from porcine seminal plasma. Table S2. The mean percentage of read counts of each of the RNA class identified in each of 12 samples of small (S) and 12 samples of large (L) extracellular vesicles isolated from porcine seminal plasma. Table S3. Data of selected all RNAs, including protein-coding RNAs (mRNAs), transfer RNAs (tRNAs), ribosomal RNAs (rRNAs), small nucleolar RNAs (snoRNAs), spliceosomal U small nuclear RNAs (snRNAs), and other non-coding RNAs (ncRNAs) in each of 12 samples of small (S) and 12 samples of large (L) extracellular vesicles isolated from porcine seminal plasma. Table S4. Data of microRNAs identified in small (S, n = 12) and large (L, n = 12) extracellular vesicles samples isolated from porcine seminal plasma. Those with at least 10 counts in three samples were selected for further analysis. Table S5. Data of PIWI-interacting RNAs identified in small (S, n = 12) and large (L, n = 12) extracellular vesicles samples isolated from porcine seminal plasma. Table S6. Data of all RNAs differentially abundant between small (S, n = 12) and large (L, n = 12) extracellular vesicle samples isolated from porcine seminal plasma. All RNAs includes protein-coding RNAs (mRNAs), transfer RNAs (tRNAs), ribosomal RNAs (rRNAs), small nucleolar RNAs (snoRNAs), spliceosomal U small nuclear RNAs (snRNAs), and other non-coding RNAs (ncRNAs). Table S7. Differentially abundant microRNAs (miRNAs) between samples of small (S, n = 12) and large (L, n = 12) extracellular vesicles isolated from porcine seminal plasma. Table S8. List and sequencing data of putative non-microRNAs after analyzing the nucleotide sequence using the Basic Local Alignment Search Tool (BLAST) software. Table S9. Data of the Network of differentially abundant microRNAs (miRNAs) and overrepresented functional categories. Analysis was performed with ToppCluster software ( https://toppcluster.cchmc.org/ )