Evidence map›Paper›PMID 30588329›Full record

ArticleNPJ genomic medicine2018

TAC-seq: targeted DNA and RNA sequencing for precise biomarker molecule counting.

Hindrek Teder, Mariann Koel, Priit Paluoja, Tatjana Jatsenko, Kadri Rekker, Triin Laisk-Podar, Viktorija Kukuškina, Agne Velthut-Meikas, Olga Fjodorova, Maire Peters and 4 more

Abstract read
In one paragraph

Article in NPJ genomic medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Review
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  7. Single-Nucleus RNA-Seq: Open the Era of Great Navigation for FFPE Tissue.International journal of molecular sciences · 2023
    Review
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  14. Observational
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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

14 authors.

Hindrek Teder *1Competence Centre on Health Technologies, Tartu, Estonia.ORCID 0000-0001-6608-7979
Mariann Koel *1Competence Centre on Health Technologies, Tartu, Estonia.
Priit Paluoja *1Competence Centre on Health Technologies, Tartu, Estonia.ORCID 0000-0002-2016-661X
Tatjana Jatsenko1Competence Centre on Health Technologies, Tartu, Estonia.
Kadri Rekker1Competence Centre on Health Technologies, Tartu, Estonia.
Triin Laisk-Podar1Competence Centre on Health Technologies, Tartu, Estonia.
Viktorija Kukuškina6Estonian Genome Center, University of Tartu, Tartu, Estonia.
Agne Velthut-Meikas1Competence Centre on Health Technologies, Tartu, Estonia.
Olga Fjodorova3Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia.
Maire Peters1Competence Centre on Health Technologies, Tartu, Estonia.
Juha Kere8Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden.
Andres Salumets1Competence Centre on Health Technologies, Tartu, Estonia.
Priit Palta6Estonian Genome Center, University of Tartu, Tartu, Estonia.
Kaarel Krjutškov1Competence Centre on Health Technologies, Tartu, Estonia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Targeted next-generation sequencing (NGS) methods have become essential in medical research and diagnostics. In addition to NGS sensitivity and high-throughput capacity, precise biomolecule counting based on unique molecular identifier (UMI) has potential to increase biomolecule detection accuracy. Although UMIs are widely used in basic research its introduction to clinical assays is still in progress. Here, we present a robust and cost-effective TAC-seq (Targeted Allele Counting by sequencing) method that uses UMIs to estimate the original molecule counts of mRNAs, microRNAs, and cell-free DNA. We applied TAC-seq in three different clinical applications and compared the results with standard NGS. RNA samples extracted from human endometrial biopsies were analyzed using previously described 57 mRNA-based receptivity biomarkers and 49 selected microRNAs at different expression levels. Cell-free DNA aneuploidy testing was based on cell line (47,XX, +21) genomic DNA. TAC-seq mRNA profiling showed identical clustering results to transcriptome RNA sequencing, and microRNA detection demonstrated significant reduction in amplification bias, allowing to determine minor expression changes between different samples that remained undetermined by standard NGS. The mimicking experiment for cell-free DNA fetal aneuploidy analysis showed that TAC-seq can be applied to count highly fragmented DNA, detecting significant (

Identifiers

PMID30588329
PMCPMC6299075

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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.