Evidence map›Paper›PMID 30783180›Full record

ArticleScientific reports2019

High-throughput, Efficient, and Unbiased Capture of Small RNAs from Low-input Samples for Sequencing.

Cassandra D Belair, Tianyi Hu, Brandon Chu, Jacob W Freimer, Matthew R Cooperberg, Robert H Blelloch

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Review
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  3. Article
  4. Review
  5. Article
  6. Article
  7. Global MicroRNA Profiling of Vascular Endothelial Cells.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  8. Mechanosensitive miR-100 coordinates TGFβ and Wnt signaling in osteocytes during fluid shear stress.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2021
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Cassandra D BelairThe Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, 94143, USA.
Tianyi HuThe Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, 94143, USA.
Brandon ChuThe Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, 94143, USA.
Jacob W FreimerThe Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, 94143, USA.
Matthew R CooperbergDepartment of Urology, University of California, San Francisco, CA, 94143, USA.
Robert H BlellochThe Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, 94143, USA. Robert.Blelloch@ucsf.edu.

Funding

PREDOCTORAL TRAINING IN DEVELOPMENTAL BIOLOGYT32HD007470 · NICHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Todd Nystul · 1994 to 2026
$7.7M
Transcellular epigenetic regulation by ex-small RNA in C. elegantU19CA179512 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BLELLOCH, ROBERT · 2013 to 2017
$7.4M
Improving Prostate Cancer Outcome Prediction Through Noninvasive exRNA AssessmentR01CA198145 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI COOPERBERG, MATTHEW R · 2016 to 2020
$3.1M
Determining the mechanisms of selective miRNA packaging for extracellular miRNA secretion in prostate cancerF31CA200163 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HU, TIANYI · 2015 to 2018
$106k
NCI NIH HHS F31 CA200163NCI NIH HHS R01 CA198145NCI NIH HHS U19 CA179512NICHD NIH HHS T32 HD007470U.S. Department of Health & Human Services | National Institutes of Health (NIH) U19CA179512U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) 5F31CA200163
6 · The paper itself

Abstract

MicroRNAs hold great promise as biomarkers of disease. However, there are few efficient and robust methods for measuring microRNAs from low input samples. Here, we develop a high-throughput sequencing protocol that efficiently captures small RNAs while minimizing inherent biases associated with library production. The protocol is based on early barcoding such that all downstream manipulations can be performed on a pool of many samples thereby reducing reagent usage and workload. We show that the optimization of adapter concentrations along with the addition of nucleotide modifications and random nucleotides increases the efficiency of small RNA capture. We further show, using unique molecular identifiers, that stochastic capture of low input RNA rather than PCR amplification influences the biased quantitation of intermediately and lowly expressed microRNAs. Our improved method allows the processing of tens to hundreds of samples simultaneously while retaining high efficiency quantitation of microRNAs in low input samples from tissues or bodily fluids.

Indexed as

High-Throughput Nucleotide SequencingMicroRNAsReverse Transcriptase Polymerase Chain ReactionSequence Analysis, RNASpecimen HandlingHumansMicroRNAs

Identifiers

PMID30783180
PMCPMC6381177

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.