Evidence map›Paper›PMID 26153459›Full record

ArticleBMC genomics2015

Read count-based method for high-throughput allelic genotyping of transposable elements and structural variants.

Alexandre Kuhn, Yao Min Ong, Stephen R Quake, William F Burkholder

Abstract read
In one paragraph

Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Alexandre KuhnMicrofluidics Systems Biology Lab, Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Proteos Building, Room #03-04, 61 Biopolis Drive, Singapore, 138673, Singapore. alexandre.m.kuhn@gmail.com.
Yao Min OngMicrofluidics Systems Biology Lab, Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Proteos Building, Room #03-04, 61 Biopolis Drive, Singapore, 138673, Singapore. yaomin81@gmail.com.
Stephen R QuakeDepts. of Bioengineering and Applied Physics and Howard Hughes Medical Institute, Stanford University, Clark Center, Room E300, 318 Campus Drive, Stanford, CA, 94305, USA. quake@stanford.edu.
William F BurkholderMicrofluidics Systems Biology Lab, Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Proteos Building, Room #03-04, 61 Biopolis Drive, Singapore, 138673, Singapore. wfburkholder@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLike other structural variants, transposable element insertions can be highly polymorphic across individuals. Their functional impact, however, remains poorly understood. Current genome-wide approaches for genotyping insertion-site polymorphisms based on targeted or whole-genome sequencing remain very expensive and can lack accuracy, hence new large-scale genotyping methods are needed.

resultsWe describe a high-throughput method for genotyping transposable element insertions and other types of structural variants that can be assayed by breakpoint PCR. The method relies on next-generation sequencing of multiplex, site-specific PCR amplification products and read count-based genotype calls. We show that this method is flexible, efficient (it does not require rounds of optimization), cost-effective and highly accurate.

conclusionsThis method can benefit a wide range of applications from the routine genotyping of animal and plant populations to the functional study of structural variants in humans.

Indexed as

AllelesDNA Transposable ElementsGenotypeGenotyping TechniquesHigh-Throughput Nucleotide SequencingHumansPolymorphism, GeneticSequence Analysis, DNADNA Transposable Elements

Identifiers

PMID26153459
PMCPMC4494700

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.