Evidence map›Paper›PMID 38392318›Full record

ArticleBiology2024

PMSeeker: A Scheme Based on the Greedy Algorithm and the Exhaustive Algorithm to Screen Low-Redundancy Marker Sets for Large-Scale Parentage Assignment with Full Parental Genotyping.

Lei Xia, Mijuan Shi, Heng Li, Wanting Zhang, Yingyin Cheng, Xiao-Qin Xia

Open access · goldAbstract read
In one paragraph

Article in Biology, 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
0.6field-weighted citation impact, top 31% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. A prediction model for CORSC advances · 2024
    Article
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

6 authors at 1 institution in 1 country.

Lei XiaState Key Laboratory of Freshwater Ecology and Biotechnology, Hubei Hongshan Laboratory, Key Laboratory of Aquaculture Disease Control, Ministry of Agriculture and Rural Affairs, The Innovation Academy of Seed Design, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China.
Mijuan ShiState Key Laboratory of Freshwater Ecology and Biotechnology, Hubei Hongshan Laboratory, Key Laboratory of Aquaculture Disease Control, Ministry of Agriculture and Rural Affairs, The Innovation Academy of Seed Design, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China.
Heng LiState Key Laboratory of Freshwater Ecology and Biotechnology, Hubei Hongshan Laboratory, Key Laboratory of Aquaculture Disease Control, Ministry of Agriculture and Rural Affairs, The Innovation Academy of Seed Design, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China.
Wanting ZhangState Key Laboratory of Freshwater Ecology and Biotechnology, Hubei Hongshan Laboratory, Key Laboratory of Aquaculture Disease Control, Ministry of Agriculture and Rural Affairs, The Innovation Academy of Seed Design, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China.
Yingyin ChengState Key Laboratory of Freshwater Ecology and Biotechnology, Hubei Hongshan Laboratory, Key Laboratory of Aquaculture Disease Control, Ministry of Agriculture and Rural Affairs, The Innovation Academy of Seed Design, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China.
Xiao-Qin XiaState Key Laboratory of Freshwater Ecology and Biotechnology, Hubei Hongshan Laboratory, Key Laboratory of Aquaculture Disease Control, Ministry of Agriculture and Rural Affairs, The Innovation Academy of Seed Design, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China.ORCID 0000-0002-8034-1096
Chinese Academy of Sciences · CN

Funding

the National Key R&D Program of China 2018YFD0901201the National Key R&D Program of China 2021YFD1200804the National Nature Science Foundation of China 31801055the Strategic Priority Research Program of the Chinese Academy of Sciences XDA24010206
6 · The paper itself

Abstract

Parentage assignment is a genetic test that utilizes genetic characteristics, such as molecular markers, to identify the parental relationships within populations, which, in commercial fish farming, are almost always large and where full information on potential parents is known. To accurately find the true parents, the genotypes of all loci in the parentage marker set (PMS) are required for each individual being tested. With the same accuracy, a PMS containing a smaller number of markers will undoubtedly save experimental costs. Thus, this study established a scheme to screen low-redundancy PMSs using the exhaustive algorithm and greedy algorithm. When screening PMSs, the greedy algorithm selects markers based on the parental dispersity index (PDI), a uniquely defined metric that outperforms the probability of exclusion (PE). With the conjunctive use of the two algorithms, non-redundant PMSs were found for more than 99.7% of solvable cases in three groups of random sample experiments in this study. Then, a low-redundancy PMS can be composed using two or more of these non-redundant PMSs. This scheme effectively reduces the number of markers in PMSs, thus conserving human and experimental resources and laying the groundwork for the widespread implementation of parentage assignment technology in economic species breeding.

Indexed as

fishmixed familiesmolecular markerparentage allocationparentage marker set

Identifiers

PMID38392318
PMCPMC10886308
OpenAlexW4391533981

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.