Header

UZH-Logo

Maintenance Infos

Neighbor GWAS: incorporating neighbor genotypic identity into genome-wide association studies of field herbivory


Sato, Yasuhiro; Yamamoto, Eiji; Shimizu, Kentaro K; Nagano, Atsushi J (2021). Neighbor GWAS: incorporating neighbor genotypic identity into genome-wide association studies of field herbivory. Heredity:Epub ahead of print.

Abstract

An increasing number of field studies have shown that the phenotype of an individual plant depends not only on its genotype but also on those of neighboring plants; however, this fact is not taken into consideration in genome-wide association studies (GWAS). Based on the Ising model of ferromagnetism, we incorporated neighbor genotypic identity into a regression model, named "Neighbor GWAS". Our simulations showed that the effective range of neighbor effects could be estimated using an observed phenotype when the proportion of phenotypic variation explained (PVE) by neighbor effects peaked. The spatial scale of the first nearest neighbors gave the maximum power to detect the causal variants responsible for neighbor effects, unless their effective range was too broad. However, if the effective range of the neighbor effects was broad and minor allele frequencies were low, there was collinearity between the self and neighbor effects. To suppress the false positive detection of neighbor effects, the fixed effect and variance components involved in the neighbor effects should be tested in comparison with a standard GWAS model. We applied neighbor GWAS to field herbivory data from 199 accessions of Arabidopsis thaliana and found that neighbor effects explained 8% more of the PVE of the observed damage than standard GWAS. The neighbor GWAS method provides a novel tool that could facilitate the analysis of complex traits in spatially structured environments and is available as an R package at CRAN ( https://cran.rproject.org/package=rNeighborGWAS ).

Abstract

An increasing number of field studies have shown that the phenotype of an individual plant depends not only on its genotype but also on those of neighboring plants; however, this fact is not taken into consideration in genome-wide association studies (GWAS). Based on the Ising model of ferromagnetism, we incorporated neighbor genotypic identity into a regression model, named "Neighbor GWAS". Our simulations showed that the effective range of neighbor effects could be estimated using an observed phenotype when the proportion of phenotypic variation explained (PVE) by neighbor effects peaked. The spatial scale of the first nearest neighbors gave the maximum power to detect the causal variants responsible for neighbor effects, unless their effective range was too broad. However, if the effective range of the neighbor effects was broad and minor allele frequencies were low, there was collinearity between the self and neighbor effects. To suppress the false positive detection of neighbor effects, the fixed effect and variance components involved in the neighbor effects should be tested in comparison with a standard GWAS model. We applied neighbor GWAS to field herbivory data from 199 accessions of Arabidopsis thaliana and found that neighbor effects explained 8% more of the PVE of the observed damage than standard GWAS. The neighbor GWAS method provides a novel tool that could facilitate the analysis of complex traits in spatially structured environments and is available as an R package at CRAN ( https://cran.rproject.org/package=rNeighborGWAS ).

Statistics

Citations

Altmetrics

Downloads

5 downloads since deposited on 02 Feb 2021
5 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Evolutionary Biology and Environmental Studies
08 Research Priority Programs > Global Change and Biodiversity
Dewey Decimal Classification:570 Life sciences; biology
590 Animals (Zoology)
Uncontrolled Keywords:Genetics(clinical), Genetics
Language:English
Date:29 January 2021
Deposited On:02 Feb 2021 10:58
Last Modified:28 Feb 2021 08:54
Publisher:Nature Publishing Group
ISSN:0018-067X
OA Status:Hybrid
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1038/s41437-020-00401-w
PubMed ID:33514929
Project Information:
  • : FunderSNSF
  • : Grant ID31003A_182318
  • : Project TitleEvolutionary functional genomics of selfing and polyploid speciation
  • : FunderJapan Science and Technology Agency (JST)
  • : Grant IDJPMJCR16O3/MEXT
  • : Project Title
  • : FunderJapan Science and Technology Agency (JST)
  • : Grant IDJPMJPR17Q4/MEXT
  • : Project Title
  • : FunderJapan Science and Technology Agency (JST)
  • : Grant IDJPMJPR16Q9/MEXT
  • : Project Title
  • : FunderJapan Science and Technology Agency (JST)
  • : Grant IDJPMJCR16O3/MEXT
  • : Project Title
  • : FunderJapan Society for the Promotion of Science (JSPS)
  • : Grant ID16J30005/MEXT
  • : Project Title
  • : FunderJapan Society for the Promotion of Science (JSPS)
  • : Grant ID18H04785/MEXT
  • : Project Title

Download

Hybrid Open Access

Download PDF  'Neighbor GWAS: incorporating neighbor genotypic identity into genome-wide association studies of field herbivory'.
Preview
Content: Published Version
Language: English
Filetype: PDF
Size: 2MB
View at publisher
Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)