Ghost QTL and hotspots in experimental crosses : novel approach for modeling polygenic effects
(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.
(Less)
- author
- Wallin, Jonas LU ; Bogdan, Małgorzata LU ; Szulc, Piotr A. ; Doerge, R. W. and Siegmund, David O.
- organization
- publishing date
- 2021
- 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}}, }