Evidence map›Paper›PMID 29230585›Full record

ArticleMolecular genetics and genomics : MGG2018

Identification of novel genes significantly affecting growth in catfish through GWAS analysis.

Ning Li, Tao Zhou, Xin Geng, Yulin Jin, Xiaozhu Wang, Shikai Liu, Xiaoyan Xu, Dongya Gao, Qi Li, Zhanjiang Liu

Abstract read
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In one paragraph

Article in Molecular genetics and genomics : MGG, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
6.6field-weighted citation impact, top 3% 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

38 citing papers in PubMed, 99 citations in OpenAlex.

  1. Identification of Candidate Genes Associated with Growth Traits inInternational journal of molecular sciences · 2026
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  3. Genetic Architecture of Growth Traits in Turbot (International journal of molecular sciences · 2026
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  6. Identification of Genes Related to Rapid Growth of Giant Grouper (Animals : an open access journal from MDPI · 2025
    Article
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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

10 authors at 4 institutions in 2 countries.

Ning LiThe Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA.
Tao ZhouThe Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA.
Xin GengThe Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA.
Yulin JinThe Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA.
Xiaozhu WangThe Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA.
Shikai LiuThe Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA.
Xiaoyan XuThe Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA.
Dongya GaoThe Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA.
Qi LiThe Shellfish Genetics and Breeding Laboratory, Fisheries College, Ocean University of China, Qingdao, 266003, Shandong, China.
Zhanjiang LiuDepartment of Biology, Syracuse University, Syracuse, NY, 13244, USA. johnliu@syr.edu.
Auburn University · USOcean University of China · CNShanghai Ocean University · CNSyracuse University · US

Funding

USDA 2015-67015-22907
6 · The paper itself

Abstract

Growth is the most important economic trait in aquaculture. Improvements in growth-related traits can enhance production, reduce costs and time to produce market-size fish. Catfish is the major aquaculture species in the United States, accounting for 65% of the US finfish production. However, the genes underlying growth traits in catfish were not well studied. Currently, the majority of the US catfish industry uses hybrid catfish derived from channel catfish female mated with blue catfish male. Interestingly, channel catfish and blue catfish exhibit differences in growth-related traits, and therefore the backcross progenies provide an efficient system for QTL analysis. In this study, we conducted a genome-wide association study for catfish body weight using the 250 K SNP array with 556 backcross progenies generated from backcross of male F1 hybrid (female channel catfish × male blue catfish) with female channel catfish. A genomic region of approximately 1 Mb on linkage group 5 was found to be significantly associated with body weight. In addition, four suggestively associated QTL regions were identified on linkage groups 1, 2, 23 and 24. Most candidate genes in the associated regions are known to be involved in muscle growth and bone development, some of which were reported to be associated with obesity in humans and pigs, suggesting that the functions of these genes may be evolutionarily conserved in controlling growth. Additional fine mapping or functional studies should allow identification of the causal genes for fast growth in catfish, and elucidation of molecular mechanisms of regulation of growth in fish.

Indexed as

Quantitative Trait LociAnimalsBody WeightCatfishesChromosome MappingFemaleFish ProteinsGenetic LinkageGenome-Wide Association StudyInbreedingMaleFish ProteinsFishGrowthGWASHybridQTL

Identifiers

PMID29230585
OpenAlexW2773999050

What OpenQuestion holds

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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.