Additional file 8: of Atp8 is in the ground pattern of flatworm mitochondrial genomes

Mitochondrial gene order in macrostomorphans, showing the newly sequenced complete mitochondrial genome of Macrostomum lignano and the partial mitochondrial genome of Microstomum lineare [8]. The gene order between these two members of Macrostomorpha is not conserved. (TIF 133 kb

Additional file 8: Table S4. of The mitochondrial genome of the egg-laying flatworm Aglaiogyrodactylus forficulatus (Platyhelminthes: Monogenoidea)

CREx distance matrix for mitochondrial gene order rearrangements. (DOCX 16 kb

Additional file 5: Table S3. of The mitochondrial genome of the egg-laying flatworm Aglaiogyrodactylus forficulatus (Platyhelminthes: Monogenoidea)

P-distances of concatenated mitochondrial genes. (DOCX 17 kb

Additional file 6: Figure S3. of The mitochondrial genome of the egg-laying flatworm Aglaiogyrodactylus forficulatus (Platyhelminthes: Monogenoidea)

Schematic order of the mitochondrial genes. (PDF 113 kb

Additional file 2: Table S2. of The mitochondrial genome of the egg-laying flatworm Aglaiogyrodactylus forficulatus (Platyhelminthes: Monogenoidea)

Codon usage of the protein coding genes (PCGs). (DOCX 107 kb

Additional file 4: Figure S2. of The mitochondrial genome of the egg-laying flatworm Aglaiogyrodactylus forficulatus (Platyhelminthes: Monogenoidea)

Maximum Likelihood trees after removal of ambiguous sites. (PDF 119 kb

Additional file 1: Table S1. of The mitochondrial genome of the egg-laying flatworm Aglaiogyrodactylus forficulatus (Platyhelminthes: Monogenoidea)

Base composition of the mtDNA. (DOCX 53 kb

Additional file 1: of Identification of non-invasive miRNAs biomarkers for prostate cancer by deep sequencing analysis of urinary exosomes

Materials and methods; Table S1 and S2; Supplementary figures S1, S2, S3, S4, S5, S6, S7, S8. (PDF 457 kb

A comprehensive profile of circulating RNAs in human serum

<p>Non-coding RNA (ncRNA) molecules have fundamental roles in cells and many are also stable in body fluids as extracellular RNAs. In this study, we used RNA sequencing (RNA-seq) to investigate the profile of small non-coding RNA (sncRNA) in human serum. We analyzed 10 billion Illumina reads from 477 serum samples, included in the Norwegian population-based Janus Serum Bank (JSB). We found that the core serum RNA repertoire includes 258 micro RNAs (miRNA), 441 piwi-interacting RNAs (piRNA), 411 transfer RNAs (tRNA), 24 small nucleolar RNAs (snoRNA), 125 small nuclear RNAs (snRNA) and 123 miscellaneous RNAs (misc-RNA). We also investigated biological and technical variation in expression, and the results suggest that many RNA molecules identified in serum contain signs of biological variation. They are therefore unlikely to be random degradation by-products. In addition, the presence of specific fragments of tRNA, snoRNA, Vault RNA and Y_RNA indicates protection from degradation. Our results suggest that many circulating RNAs in serum can be potential biomarkers.</p