Evidence map›Paper›PMID 34282453›Full record

ArticleGigaScience2021

Accelerated deciphering of the genetic architecture of agricultural economic traits in pigs using a low-coverage whole-genome sequencing strategy.

Ruifei Yang, Xiaoli Guo, Di Zhu, Cheng Tan, Cheng Bian, Jiangli Ren, Zhuolin Huang, Yiqiang Zhao, Gengyuan Cai, Dewu Liu and 4 more

Abstract read
In one paragraph

Article in GigaScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 2 pooled it
–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

55 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  18. Rapid Identification of the SNP Mutation in theAnimals : an open access journal from MDPI · 2025
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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

14 authors.

Ruifei YangState Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China.
Xiaoli GuoState Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China.
Di ZhuState Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China.
Cheng TanNational Engineering Research Center for Breeding Swine Industry, South China Agricultural University, No. 483 Wushan road, Tianhe district, Guangdong 510640, China.
Cheng BianState Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China.
Jiangli RenState Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China.
Zhuolin HuangState Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China.
Yiqiang ZhaoState Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China.
Gengyuan CaiNational Engineering Research Center for Breeding Swine Industry, South China Agricultural University, No. 483 Wushan road, Tianhe district, Guangdong 510640, China.
Dewu LiuNational Engineering Research Center for Breeding Swine Industry, South China Agricultural University, No. 483 Wushan road, Tianhe district, Guangdong 510640, China.
Zhenfang WuNational Engineering Research Center for Breeding Swine Industry, South China Agricultural University, No. 483 Wushan road, Tianhe district, Guangdong 510640, China.
Yuzhe WangState Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China.
Ning LiState Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China.
Xiaoxiang HuState Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, No. 2 Yuanmingyuan west road, Haidian district, Beijing 100193, China.ORCID 0000-0001-7045-0283

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUncovering the genetic architecture of economic traits in pigs is important for agricultural breeding. However, high-density haplotype reference panels are unavailable in most agricultural species, limiting accurate genotype imputation in large populations. Moreover, the infinitesimal model of quantitative traits implies that weak association signals tend to be spread across most of the genome, further complicating the genetic analysis. Hence, there is a need to develop new methods for sequencing large cohorts without large reference panels.

resultsWe describe a Tn5-based highly accurate, cost- and time-efficient, low-coverage sequencing method to obtain 11.3 million whole-genome single-nucleotide polymorphisms in 2,869 Duroc boars at a mean depth of 0.73×. On the basis of these single-nucleotide polymorphisms, a genome-wide association study was performed, resulting in 14 quantitative trait loci (QTLs) for 7 of 21 important agricultural traits in pigs. These QTLs harbour genes, such as ABCD4 for total teat number and HMGA1 for back fat thickness, and provided a starting point for further investigation. The inheritance models of the different traits varied greatly. Most follow the minor-polygene model, but this can be attributed to different reasons, such as the shaping of genetic architecture by artificial selection for this population and sufficiently interconnected minor gene regulatory networks.

conclusionsGenome-wide association study results for 21 important agricultural traits identified 14 QTLs/genes and showed their genetic architectures, providing guidance for genetic improvement harnessing genomic features. The Tn5-based low-coverage sequencing method can be applied to large-scale genome studies for any species without a good reference panel and can be used for agricultural breeding.

Indexed as

Genome-Wide Association StudyQuantitative Trait LociAnimalsGenotypeMalePhenotypePolymorphism, Single NucleotideSwineWhole Genome Sequencingagricultural traitsgenetic architecturegenotypingGWASlow-coverage sequencingpig

Identifiers

PMID34282453
PMCPMC8290195

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LicenceCC BY
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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.