Evidence map›Paper›PMID 37540357›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Genetic Screens for Floral Mutants in Arabidopsis thaliana: Enhancers and Suppressors.

Zhigang Huang, Thanh Theresa Dinh, Elizabeth Luscher, Shaofang Li, Xigang Liu, So Youn Won, Xuemei Chen

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. 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 63% 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

7 authors at 2 institutions in 2 countries.

Zhigang HuangHunan Provincial Key Laboratory of Phytohormones and Growth Development, Hunan Agricultural University, Changsha, China.
Thanh Theresa DinhDepartment of Botany and Plant Sciences, University of California, Riverside, CA, USA.
Elizabeth LuscherDepartment of Botany and Plant Sciences, University of California, Riverside, CA, USA.
Shaofang LiDepartment of Botany and Plant Sciences, University of California, Riverside, CA, USA.
Xigang LiuDepartment of Botany and Plant Sciences, University of California, Riverside, CA, USA.
So Youn WonDepartment of Botany and Plant Sciences, University of California, Riverside, CA, USA.
Xuemei ChenDepartment of Botany and Plant Sciences, University of California, Riverside, CA, USA. xuemei.chen@ucr.edu.
University of California, Riverside · USHunan Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The flower is a hallmark feature that has contributed to the evolutionary success of land plants. Diverse mutagenic agents have been employed as a tool to genetically perturb flower development and identify genes involved in floral patterning and morphogenesis. Since the initial studies to identify genes governing processes such as floral organ specification, mutagenesis in sensitized backgrounds has been used to isolate enhancers and suppressors to further probe the molecular basis of floral development. Here, we first describe two commonly employed methods for mutagenesis (using ethyl methanesulfonate (EMS) or T-DNAs as mutagens), and then describe three methods for identifying a mutation that leads to phenotypic alterations: traditional map-based cloning, modified high-efficiency thermal asymmetric interlaced PCR (mhiTAIL-PCR), and deep sequencing in the plant model Arabidopsis thaliana.

Indexed as

ArabidopsisGenetic TestingMutagenesisMutagensMutationMutagensArabidopsisEMSFloral developmentGenetic screenMap-based cloningmhiTAIL-PCRMutagenesisT-DNA

Identifiers

PMID37540357
OpenAlexW4385563457

What OpenQuestion holds

Textmetadata
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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.