Miniaturized Workflow for Transcriptomic Profiling of Urinary Extracellular RNA during Pregnancy
Srimeenakshi SrinivasaniD, Peter L De HoffiD, Amber L. MoreyiD, Aishwarya VuppalaiD, Marina Mochizuki, Robert E. MoreyiD, Morgan MeadsiD, Erika DugganiD, Derek E. WildmaniD, John P. NolaniD, Priyadarshini PanthamiD
Abstract
Urine contains extracellular RNA (exRNA) carried by extracellular vesicles (EVs) and other biomolecular complexes. There is currently a need for studies focused on female cohorts to develop new methods for non-invasive analysis of biofluids to create reference profiles and for identification of biomarkers of reproductive and pregnancy disorders. The objective of this study was therefore to identify optimal methods for transcriptomic profiling of urine by testing different exRNA isolation and scalable library preparation methods that enable detection of biomarkers that reflect pregnancy-associated changes in the placenta and maternal tissues. RNA was extracted from pooled and individual urine samples obtained from normal non-pregnant and pregnant females, as well as males, using input volumes of either 0.6 mL, 1 mL, or 4 mL. Samples were extracted using methods that focused either on isolating vesicular (EV-associated) or total (EV-associated and non EV-associated) exRNA. Small RNA libraries (n=208) were prepared using the NEBNext Small RNA Library Prep kit and long RNA libraries (n=97) were prepared using the SMART-Seq v4 Ultra Low Input RNA or the SMARTer Stranded Total RNA-Seq Kit v2 Pico Input kits (Takara). Principal component analysis showed that the greatest source of variance amongst technical replicates of small RNA libraries (n=176 which passed quality control) was exRNA isolation method, and amongst long RNA libraries (n=97 which passed quality control) was library preparation method. Long RNA libraries prepared from exRNA extracted using miRCURY showed that the SMART-Seq v4 method yielded significantly more uniquely mapped reads compared to the Pico v2 method (p<0.05). We have established a scalable pipeline for small and long RNA-Seq profiling of exRNA in urine in a reproducible manner, which we used to identify differentially expressed urinary exRNAs in pregnancy, and will enable transcriptomic profiling of urinary exRNA in disorders of pregnancy, including preeclampsia.
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