Evidence map›Paper›PMID 25211220›Full record

ArticlePLoS genetics2014

Genome wide association studies using a new nonparametric model reveal the genetic architecture of 17 agronomic traits in an enlarged maize association panel.

Ning Yang, Yanli Lu, Xiaohong Yang, Juan Huang, Yang Zhou, Farhan Ali, Weiwei Wen, Jie Liu, Jiansheng Li, Jianbing Yan

Abstract read
In one paragraph

Article in PLoS genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 205 papers.

0numbers the graph read from it
0cells of the map it votes in
205citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

205 citing papers in PubMed.

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  17. The chromatin accessibility landscape during early maize seed development.The Plant journal : for cell and molecular biology · 2025
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145 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

10 authors.

Ning YangNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Yanli LuNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China; Maize Research Institute, Sichuan Agricultural University, Wenjiang, Sichuan, China.
Xiaohong YangNational Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, China.
Juan HuangNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Yang ZhouNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Farhan AliNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Weiwei WenNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Jie LiuNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Jiansheng LiNational Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, China.
Jianbing YanNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Association mapping is a powerful approach for dissecting the genetic architecture of complex quantitative traits using high-density SNP markers in maize. Here, we expanded our association panel size from 368 to 513 inbred lines with 0.5 million high quality SNPs using a two-step data-imputation method which combines identity by descent (IBD) based projection and k-nearest neighbor (KNN) algorithm. Genome-wide association studies (GWAS) were carried out for 17 agronomic traits with a panel of 513 inbred lines applying both mixed linear model (MLM) and a new method, the Anderson-Darling (A-D) test. Ten loci for five traits were identified using the MLM method at the Bonferroni-corrected threshold -log10 (P) >5.74 (α=1). Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold -log10 (P) >7.05 (α=0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test, a few of which were also detected in independent linkage analysis. This study indicates that combining IBD based projection and KNN algorithm is an efficient imputation method for inferring large missing genotype segments. In addition, we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power. The candidate SNPs and associated genes also provide a rich resource for maize genetics and breeding.

Indexed as

BreedingGenome, PlantGenome-Wide Association StudyGenotypeLinkage DisequilibriumPhenotypePolymorphism, Single NucleotideQuantitative Trait LociZea mays

Identifiers

PMID25211220
PMCPMC4161304

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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.