Evidence map›Paper›PMID 28828506›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2017

An innovative procedure of genome-wide association analysis fits studies on germplasm population and plant breeding.

Jianbo He, Shan Meng, Tuanjie Zhao, Guangnan Xing, Shouping Yang, Yan Li, Rongzhan Guan, Jiangjie Lu, Yufeng Wang, Qiuju Xia and 2 more

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Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.

0numbers the graph read from it
0cells of the map it votes in
68citing papers in PubMed
15.2field-weighted citation impact, top 1% 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

68 citing papers in PubMed, 117 citations in OpenAlex.

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  8. Genome-wide association analyses for revealing QTN, QTN-by-environment and QTN-by-QTN interactions in soybean phenology.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
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  13. Genome-Wide Genetic Architecture for Common Scab (International journal of molecular sciences · 2025
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  19. Fine-mapping of a major locus for Fusarium wilt resistance in flax (Linum usitatissimum L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article
  20. Efficient identification of QTL for agronomic traits in foxtail millet (Setaria italica) using RTM- and MLM-GWAS.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article

8 more citing papers are in PubMed but not listed here.

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

12 authors at 1 institution in 1 country.

Jianbo HeSoybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, China.
Shan MengSoybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, China.
Tuanjie ZhaoNational Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095, China.
Guangnan XingNational Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095, China.
Shouping YangKey Laboratory of Biology and Genetic Improvement of Soybean (General), Ministry of Agriculture, Nanjing, 210095, China.
Yan LiKey Laboratory of Biology and Genetic Improvement of Soybean (General), Ministry of Agriculture, Nanjing, 210095, China.
Rongzhan GuanState Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China.
Jiangjie LuSoybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, China.
Yufeng WangSoybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, China.
Qiuju XiaState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Bing YangState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Junyi GaiSoybean Research Institute, Nanjing Agricultural University, Nanjing, 210095, China. sri@njau.edu.cn.
Nanjing Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

key messageThe innovative RTM-GWAS procedure provides a relatively thorough detection of QTL and their multiple alleles for germplasm population characterization, gene network identification, and genomic selection strategy innovation in plant breeding. The previous genome-wide association studies (GWAS) have been concentrated on finding a handful of major quantitative trait loci (QTL), but plant breeders are interested in revealing the whole-genome QTL-allele constitution in breeding materials/germplasm (in which tremendous historical allelic variation has been accumulated) for genome-wide improvement. To match this requirement, two innovations were suggested for GWAS: first grouping tightly linked sequential SNPs into linkage disequilibrium blocks (SNPLDBs) to form markers with multi-allelic haplotypes, and second utilizing two-stage association analysis for QTL identification, where the markers were preselected by single-locus model followed by multi-locus multi-allele model stepwise regression. Our proposed GWAS procedure is characterized as a novel restricted two-stage multi-locus multi-allele GWAS (RTM-GWAS, https://github.com/njau-sri/rtm-gwas ). The Chinese soybean germplasm population (CSGP) composed of 1024 accessions with 36,952 SNPLDBs (generated from 145,558 SNPs, with reduced linkage disequilibrium decay distance) was used to demonstrate the power and efficiency of RTM-GWAS. Using the CSGP marker information, simulation studies demonstrated that RTM-GWAS achieved the highest QTL detection power and efficiency compared with the previous procedures, especially under large sample size and high trait heritability conditions. A relatively thorough detection of QTL with their multiple alleles was achieved by RTM-GWAS compared with the linear mixed model method on 100-seed weight in CSGP. A QTL-allele matrix (402 alleles of 139 QTL × 1024 accessions) was established as a compact form of the population genetic constitution. The 100-seed weight QTL-allele matrix was used for genetic characterization, candidate gene prediction, and genomic selection for optimal crosses in the germplasm population.

Indexed as

Genetics, PopulationPlant BreedingAllelesComputer SimulationGenetic Association StudiesGenetic MarkersGlycine maxHaplotypesLinkage DisequilibriumModels, GeneticPhenotypePolymorphism, Single NucleotideQuantitative Trait LociSeedsSelection, GeneticGenetic Markers

Identifiers

PMID28828506
OpenAlexW2749951460

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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.