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Ghost QTL and hotspots in experimental crosses : novel approach for modeling polygenic effects

Wallin, Jonas LU ; Bogdan, Małgorzata LU ; Szulc, Piotr A. ; Doerge, R. W. and Siegmund, David O. (2021) In Genetics 217(3).
Abstract

Ghost quantitative trait loci (QTL) are the false discoveries in QTL mapping, that arise due to the "accumulation" of the polygenic effects, uniformly distributed over the genome. The locations on the chromosome that are strongly correlated with the total of the polygenic effects depend on a specific sample correlation structure determined by the genotypes at all loci. The problem is particularly severe when the same genotypes are used to study multiple QTL, e.g. using recombinant inbred lines or studying the expression QTL. In this case, the ghost QTL phenomenon can lead to false hotspots, where multiple QTL show apparent linkage to the same locus. We illustrate the problem using the classic backcross design and suggest that it can be... (More)

Ghost quantitative trait loci (QTL) are the false discoveries in QTL mapping, that arise due to the "accumulation" of the polygenic effects, uniformly distributed over the genome. The locations on the chromosome that are strongly correlated with the total of the polygenic effects depend on a specific sample correlation structure determined by the genotypes at all loci. The problem is particularly severe when the same genotypes are used to study multiple QTL, e.g. using recombinant inbred lines or studying the expression QTL. In this case, the ghost QTL phenomenon can lead to false hotspots, where multiple QTL show apparent linkage to the same locus. We illustrate the problem using the classic backcross design and suggest that it can be solved by the application of the extended mixed effect model, where the random effects are allowed to have a nonzero mean. We provide formulas for estimating the thresholds for the corresponding t-test statistics and use them in the stepwise selection strategy, which allows for a simultaneous detection of several QTL. Extensive simulation studies illustrate that our approach eliminates ghost QTL/false hotspots, while preserving a high power of true QTL detection.

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author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
expression quantitative trait loci (e-QTL) mapping, ghost QTL, hotspots, mixed effect model, polygenes, QTL mapping
in
Genetics
volume
217
issue
3
publisher
Genetics Society of America
external identifiers
  • scopus:85103746174
  • pmid:33789342
ISSN
0016-6731
DOI
10.1093/genetics/iyaa041
language
English
LU publication?
yes
id
7ed2e6fe-9923-4a71-b56f-b68d45d3f423
date added to LUP
2021-04-19 09:26:19
date last changed
2024-06-15 10:01:29
@article{7ed2e6fe-9923-4a71-b56f-b68d45d3f423,
  abstract     = {{<p>Ghost quantitative trait loci (QTL) are the false discoveries in QTL mapping, that arise due to the "accumulation" of the polygenic effects, uniformly distributed over the genome. The locations on the chromosome that are strongly correlated with the total of the polygenic effects depend on a specific sample correlation structure determined by the genotypes at all loci. The problem is particularly severe when the same genotypes are used to study multiple QTL, e.g. using recombinant inbred lines or studying the expression QTL. In this case, the ghost QTL phenomenon can lead to false hotspots, where multiple QTL show apparent linkage to the same locus. We illustrate the problem using the classic backcross design and suggest that it can be solved by the application of the extended mixed effect model, where the random effects are allowed to have a nonzero mean. We provide formulas for estimating the thresholds for the corresponding t-test statistics and use them in the stepwise selection strategy, which allows for a simultaneous detection of several QTL. Extensive simulation studies illustrate that our approach eliminates ghost QTL/false hotspots, while preserving a high power of true QTL detection.</p>}},
  author       = {{Wallin, Jonas and Bogdan, Małgorzata and Szulc, Piotr A. and Doerge, R. W. and Siegmund, David O.}},
  issn         = {{0016-6731}},
  keywords     = {{expression quantitative trait loci (e-QTL) mapping; ghost QTL; hotspots; mixed effect model; polygenes; QTL mapping}},
  language     = {{eng}},
  number       = {{3}},
  publisher    = {{Genetics Society of America}},
  series       = {{Genetics}},
  title        = {{Ghost QTL and hotspots in experimental crosses : novel approach for modeling polygenic effects}},
  url          = {{http://dx.doi.org/10.1093/genetics/iyaa041}},
  doi          = {{10.1093/genetics/iyaa041}},
  volume       = {{217}},
  year         = {{2021}},
}