Evidence map›Paper›PMID 38656486›Full record

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

Identification of Novel Induced Mutations in Seed and Vegetatively Propagated Plants from Reduced Representation or Whole Genome Sequencing Data.

Bradley J Till, José P Jiménez-Madrigal, Andrés Gatica-Arias

Abstract read
PubMed Publisher
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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Advances in mutant characterization for detecting causal mutations in crop plants.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    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

3 authors.

Bradley J TillVeterinary Genetics Laboratory, University of California, Davis, CA, USA. bjtill@ucdavis.edu.ORCID 0000-0002-1300-8285
José P Jiménez-MadrigalInstituto Tecnológico de Costa Rica, Escuela de Ciencias Naturales y Exactas, Alajuela, Costa Rica.ORCID 0000-0002-0345-8899
Andrés Gatica-AriasEscuela de Biología, Universidad de Costa Rica, San José, Costa Rica.ORCID 0000-0002-3841-0238

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Treatment of plants with chemical mutagens results primarily in the production of novel single nucleotide variants. Mutagenesis is a mostly random process and as such plants derived from mutagenesis of different seeds or in vitro material are expected to accumulate different mutations. An important step in the creation of a mutant population for forward or reverse genetics is the choice of treatment conditions (e.g., dosage) such that sufficient mutations accumulate while not adversely affecting propagation of the plant. DNA sequencing provides a quick method to evaluate the effect of different treatment conditions and their effect on the density and spectrum of accumulated mutations. Whole genome sequencing or reduced representation sequencing is carried out followed by mapping to a reference genome and production of a Variant Call Format (VCF) file. We provide here a method for generating a multi-sample VCF from mutagenized plants and describe a new tool to streamline the process of recovering unique induced mutations and determining their possible effect on gene function.

Indexed as

Genome, PlantMutagenesisMutationSeedsWhole Genome SequencingHigh-Throughput Nucleotide SequencingMutagensPlantsMutagensChemical mutagenesisddRADseqInduced mutationTILLINGWhole genome sequencing

Identifiers

PMID38656486

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.