Read counts in all samples analyzed.

<p>Read counts in all samples analyzed.</p

Spearman correlation for the expression level of detected microRNAs.

<p>While different numbers of miRNAs were quantified between duplicated samples, the majority of these miRNA were commonly observed. The expression level of these commonly observed miRNA were highly correlated for both duplicated samples (r>0.9) and across samples from different subjects (r>0.74).</p

High Throughput Sequencing of Extracellular RNA from Human Plasma

<div><p>The presence and relative stability of extracellular RNAs (exRNAs) in biofluids has led to an emerging recognition of their promise as ‘liquid biopsies’ for diseases. Most prior studies on discovery of exRNAs as disease-specific biomarkers have focused on microRNAs (miRNAs) using technologies such as qRT-PCR and microarrays. The recent application of next-generation sequencing to discovery of exRNA biomarkers has revealed the presence of potential novel miRNAs as well as other RNA species such as tRNAs, snoRNAs, piRNAs and lncRNAs in biofluids. At the same time, the use of RNA sequencing for biofluids poses unique challenges, including low amounts of input RNAs, the presence of exRNAs in different compartments with varying degrees of vulnerability to isolation techniques, and the high abundance of specific RNA species (thereby limiting the sensitivity of detection of less abundant species). Moreover, discovery in human diseases often relies on archival biospecimens of varying age and limiting amounts of samples. In this study, we have tested RNA isolation methods to optimize profiling exRNAs by RNA sequencing in individuals without any known diseases. Our findings are consistent with other recent studies that detect microRNAs and ribosomal RNAs as the major exRNA species in plasma. Similar to other recent studies, we found that the landscape of biofluid microRNA transcriptome is dominated by several abundant microRNAs that appear to comprise conserved extracellular miRNAs. There is reasonable correlation of sets of conserved miRNAs across biological replicates, and even across other data sets obtained at different investigative sites. Conversely, the detection of less abundant miRNAs is far more dependent on the exact methodology of RNA isolation and profiling. This study highlights the challenges in detecting and quantifying less abundant plasma miRNAs in health and disease using RNA sequencing platforms.</p></div

Venn diagram of mature miRNA species detected in each treatment group.

<p>Plasma samples libraries from a single health donor generated using no PK, PK treatment before GITC, PK treatment in GITC show strong concordance of miRNA species detected, with PK treatment in GITC method showing higher sensitivity than others.</p

Top expressing miRNA with target genes and reported dysregulation in human disease.

<p>Top expressing miRNA with target genes and reported dysregulation in human disease.</p

Schematic summarizing plasma sample treatments used in this study.

<p>RNA isolation was performed with or without proteinase K treatment and ribodepletion on fresh or archived samples.</p

Top 20 miRNA by read counts in duplicated control samples.

<p>Top 20 miRNA by read counts in duplicated control samples.</p

Additional file 1: of Evaluation of commercially available small RNASeq library preparation kits using low input RNA

Table S1. Percentage of input reads aligned to the human transcriptome, human rRNA, UniVec contaminant sequences and discarded because they are too short (< 15 nts) and unmapped to the human transcriptome. Table S2. Median (Inter-quartile range) of percentage of input reads aligned to the human transcriptome, human rRNA, UniVec contaminant sequences. Table S3. Percentage of reads aligned to the human transcriptome to each RNA biotype for all samples. Table S4. Median (Inter-quartile range) of percentage of input reads aligned to different RNA biotypes between the three sequencing kits. Table S5. Median (IQR) of percentage of input reads aligned and comparison of input amount of RNA. Table S6. Median (IQR) of percentage of input reads aligned and comparison between the two sites for the two input amounts of RNA. Table S7. Median (IQR) of number of miRNAs greater than 10 counts detected in at least 25% of the samples between the two sites for the two input amounts of RNA. Table S8. Pearson’s and Spearman’s correlation coefficient by tissue, kit and input amount. Table S9. Kit specific miRNAs found in each tissue for each kit. The top 5 miRNAs for each tissue that have expression greater than 10 RPM in one kit, but less than 5 RPM in the other two are presented for each tissue and kit. Table S10. miRNAs included on the custom made FirePlex Panel. The columns denote the number of samples that had above detection-limit expression in each tissue. Table S11. Database of RNA biotypes used. (XLSX 89 kb

Additional file 2: of Evaluation of commercially available small RNASeq library preparation kits using low input RNA

Figure S1. Density plot of read lengths for all three kits and tissues respectively by site. Site2 sequenced to a length of 76 nts, whereas all of Site1 samples were sequenced to <=50 nts. Figure S2. Comparison of percentage of reads assigned to the various RNA biotypes for read length restricted to less than 50 nts versus read length = 76 nts. Site2 sequenced to a length of 76 nts. Figure S3. PCA plot showing that the BiooScientific NEXTFlex samples from Site2 cluster by themselves indicating a batch effect. Also, the figure on the right shows the number of miRNAs detected > 10 counts for the two input amounts 10 ng and 1 μg by Site for the BiooScientific NEXTFlex samples. (PDF 5418 kb

NanoFCM allows identification of beads and liposomes down to 100 nm.

<p>Separation of a mixture containing 200 and 500 nm latex beads by LSRII (A), and NanoView (B) instruments show more distinct separation with the NanoView Instrument. The NanoView is capable of separating a mixture of 100–500 nm beads into distinct populations (C) and can detect 100 nm liposomes (D). The gating strategy for these experiments to determine instrument and background noise are described in the methods section.</p