Evidence map›Paper›PMID 40418480›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Detection of De Novo Mutations by Sequencing Reduced Representation Libraries.

Saneyoshi Ueno, Yoichi Hasegawa, Shuri Kato, Kentaro Uchiyama, Shingo Kaneko

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. 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

5 authors.

Saneyoshi UenoDepartment of Forest Molecular Genetics and Biotechnology, Forestry and Forest Products Research Institute, Tsukuba, Japan.
Yoichi HasegawaDepartment of Forest Molecular Genetics and Biotechnology, Forestry and Forest Products Research Institute, Tsukuba, Japan.
Shuri KatoTama Forest Science Garden, Forestry and Forest Products Research Institute, Hachioji, Japan.
Kentaro UchiyamaDepartment of Forest Molecular Genetics and Biotechnology, Forestry and Forest Products Research Institute, Tsukuba, Japan.
Shingo KanekoFaculty of Symbiotic Systems Science, Fukushima University, Fukushima, Japan. skane@sss.fukushima-u.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

De novo mutations (DNMs) are spontaneous genetic alterations not present in parents but occurring in the germline and transmitted to offspring. These mutations play a vital role in understanding evolutionary processes, genetic diversity, and impacts on species' fitness and survival. The identification of DNMs is especially crucial in the context of environmental stresses, such as those induced by nuclear accidents like Fukushima. This chapter describes recent advances in high-throughput sequencing technologies that have enhanced our capacity to detect DNMs within a single generation. Due to challenges associated with whole-genome resequencing in nonmodel organisms with high genetic and environmental heterogeneity, we proposed the use of genetic marker-based methods like Restriction site-Associated DNA Sequencing (RADSeq). RADSeq simplifies the detection of DNMs by using restriction enzymes to cut DNA at specific sites, producing manageable fragments for sequencing that represent the entire genome. This method allows for the targeted analysis of genetic variations across large populations and is particularly effective in detecting DNMs from wide range of populations, providing insight into damages and adaptations required for different biological conditions.

Indexed as

Gene LibraryHigh-Throughput Nucleotide SequencingMutationSequence Analysis, DNAAnimalsHumansGenomic surveyGermline mutationsRADSeq

Identifiers

PMID40418480

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.