Evidence map›Paper›PMID 41298594›Full record

ArticleScientific reports2025

Multi-marker GWAS and variant-specific genomic prediction for growth traits in Pacific white shrimp.

Tianzan Lv, Yan Xia, Jian Tan, Qiang Fu, Kun Luo, Xianhong Meng, Baolong Chen, Meijia Chen, Juan Sui, Ping Dai and 9 more

Abstract read
In one paragraph

Article in Scientific reports, 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

19 authors.

Tianzan LvState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Yan XiaState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Jian TanState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Qiang FuState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Kun LuoState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Xianhong MengState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Baolong ChenState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Meijia ChenState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Juan SuiState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Ping DaiState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Xupeng LiState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Junyu LiuState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Mianyu LiuState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Jiawang CaoState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Qun XingBLUP Aquabreed Co., Ltd., Weifang, 261311, China.
Guangfeng QiangState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Jie KongState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China.
Hao ZhouState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China. zhouhao@ysfri.ac.cn.
Sheng LuanState Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, 266071, China. luansheng@ysfri.ac.cn.

Funding

National Natural Science Foundation of China 32273129Natural Science Foundation of Shandong Province ZR2024QC192Shandong Provincial Postdoctoral Innovative Talents Support Program SDBX202302022
6 · The paper itself

Abstract

The genome of Penaeus vannamei is rich in short tandem repeats (STRs), occupying 18.96% of the genome, with 68.6% of loci showing high polymorphic information content, highlighting their potential as molecular markers. Accordingly, we performed an integrative GWAS leveraging STR, SNP, and InDel markers to identify 78 growth-associated loci, including 17 additional STRs compared with single-marker GWAS and six high-linkage regions containing metabolic, molting, and other growth-related genes. Four markers were validated in an independent population. In genomic prediction, STRs outperformed SNPs under the GBLUP model at low marker densities (20-50 loci), with accuracy gains up to 183%. GWAS-informed marker selection improved cross-population prediction performance, with STR-Top sets enhancing accuracy by 0.6%-3.0% under the GBLUP model, while SNP-Top sets achieved greater and more consistent gains under the KRR model. These results demonstrate the utility of STRs and support multi-marker integration for trait dissection and breeding in aquatic animals.

Indexed as

Genome-Wide Association StudyPenaeidaeAnimalsGenetic MarkersGenomeGenomicsINDEL MutationMicrosatellite RepeatsPolymorphism, Single NucleotideQuantitative Trait LociGenetic MarkersAquaculture breedingGenomic predictionGWASPenaeus vannameiSTR

Identifiers

PMID41298594
PMCPMC12658181

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.