Evidence map›Paper›PMID 38656487›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

Identification of Induced Copy Number Variation from Low Coverage Sequence Data.

Bradley J Till

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. 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, top 87% of its field
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, 0 citations in OpenAlex.

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

1 author at 1 institution in 1 country.

Bradley J TillVeterinary Genetics Laboratory, University of California, Davis, CA, USA. bjtill@ucdavis.edu.ORCID 0000-0002-1300-8285
University of California, Davis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Induced mutations have been an important tool for plant breeding and functional genomics for more than 80 years. Novel mutations can be induced by treating seed or other plant cells with chemical mutagens or ionizing radiation. The majority of released mutant crop varieties were developed using ionizing radiation. This has been shown to create a variety of different DNA lesions including large (e.g., >=10,000 bps) copy number variations (CNV). Detection of induced DNA lesions from whole genome sequence data is useful for choosing a mutagen dosage prior to committing resources to develop a large mutant population for forward or reverse-genetic screening. Here I provide a method for detecting large induced CNV from mutant plants that utilizes a new tool to streamline the process of obtaining read coverage directly from BAM files, comparing non-mutagenized controls and mutagenized samples, and plotting the results for visual evaluation. Example data is provided from low coverage sequence data from gamma-irradiated vegetatively propagated triploid banana.

Indexed as

DNA Copy Number VariationsGenome, PlantHigh-Throughput Nucleotide SequencingMusaMutagensMutationPlant BreedingSequence Analysis, DNAMutagensClonal propagationCNVGamma irradiationLow coverage copy number variationPolyploidy

Identifiers

PMID38656487
OpenAlexW4395078334

What OpenQuestion holds

Textmetadata
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.