Cargando…

A tetrasomic inheritance model and likelihood‐based method for mapping quantitative trait loci in autotetraploid species

Dissecting the genetic architecture of quantitative traits in autotetraploid species is a methodologically challenging task, but a pivotally important goal for breeding globally important food crops, including potato and blueberry, and ornamental species such as rose. Mapping quantitative trait loci...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Jing, Leach, Lindsey, Yang, Jixuan, Zhang, Fengjun, Tao, Qin, Dang, Zhenyu, Chen, Yue, Luo, Zewei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7984458/
https://www.ncbi.nlm.nih.gov/pubmed/31913501
http://dx.doi.org/10.1111/nph.16413
_version_ 1783668068622270464
author Chen, Jing
Leach, Lindsey
Yang, Jixuan
Zhang, Fengjun
Tao, Qin
Dang, Zhenyu
Chen, Yue
Luo, Zewei
author_facet Chen, Jing
Leach, Lindsey
Yang, Jixuan
Zhang, Fengjun
Tao, Qin
Dang, Zhenyu
Chen, Yue
Luo, Zewei
author_sort Chen, Jing
collection PubMed
description Dissecting the genetic architecture of quantitative traits in autotetraploid species is a methodologically challenging task, but a pivotally important goal for breeding globally important food crops, including potato and blueberry, and ornamental species such as rose. Mapping quantitative trait loci (QTLs) is now a routine practice in diploid species but is far less advanced in autotetraploids, largely due to a lack of analytical methods that account for the complexities of tetrasomic inheritance. We present a novel likelihood‐based method for QTL mapping in outbred segregating populations of autotetraploid species. The method accounts properly for sophisticated features of gene segregation and recombination in an autotetraploid meiosis. It may model and analyse molecular marker data with or without allele dosage information, such as that from microarray or sequencing experiments. The method developed outperforms existing bivalent‐based methods, which may fail to model and analyse the full spectrum of experimental data, in the statistical power of QTL detection, and accuracy of QTL location, as demonstrated by an intensive simulation study and analysis of data sets collected from a segregating population of potato (Solanum tuberosum). The study enables QTL mapping analysis to be conducted in autotetraploid species under a rigorous tetrasomic inheritance model.
format Online
Article
Text
id pubmed-7984458
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-79844582021-03-25 A tetrasomic inheritance model and likelihood‐based method for mapping quantitative trait loci in autotetraploid species Chen, Jing Leach, Lindsey Yang, Jixuan Zhang, Fengjun Tao, Qin Dang, Zhenyu Chen, Yue Luo, Zewei New Phytol Research Dissecting the genetic architecture of quantitative traits in autotetraploid species is a methodologically challenging task, but a pivotally important goal for breeding globally important food crops, including potato and blueberry, and ornamental species such as rose. Mapping quantitative trait loci (QTLs) is now a routine practice in diploid species but is far less advanced in autotetraploids, largely due to a lack of analytical methods that account for the complexities of tetrasomic inheritance. We present a novel likelihood‐based method for QTL mapping in outbred segregating populations of autotetraploid species. The method accounts properly for sophisticated features of gene segregation and recombination in an autotetraploid meiosis. It may model and analyse molecular marker data with or without allele dosage information, such as that from microarray or sequencing experiments. The method developed outperforms existing bivalent‐based methods, which may fail to model and analyse the full spectrum of experimental data, in the statistical power of QTL detection, and accuracy of QTL location, as demonstrated by an intensive simulation study and analysis of data sets collected from a segregating population of potato (Solanum tuberosum). The study enables QTL mapping analysis to be conducted in autotetraploid species under a rigorous tetrasomic inheritance model. John Wiley and Sons Inc. 2020-05-16 2021-04 /pmc/articles/PMC7984458/ /pubmed/31913501 http://dx.doi.org/10.1111/nph.16413 Text en © 2020 The Authors. New Phytologist © 2020 New Phytologist Trust This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Chen, Jing
Leach, Lindsey
Yang, Jixuan
Zhang, Fengjun
Tao, Qin
Dang, Zhenyu
Chen, Yue
Luo, Zewei
A tetrasomic inheritance model and likelihood‐based method for mapping quantitative trait loci in autotetraploid species
title A tetrasomic inheritance model and likelihood‐based method for mapping quantitative trait loci in autotetraploid species
title_full A tetrasomic inheritance model and likelihood‐based method for mapping quantitative trait loci in autotetraploid species
title_fullStr A tetrasomic inheritance model and likelihood‐based method for mapping quantitative trait loci in autotetraploid species
title_full_unstemmed A tetrasomic inheritance model and likelihood‐based method for mapping quantitative trait loci in autotetraploid species
title_short A tetrasomic inheritance model and likelihood‐based method for mapping quantitative trait loci in autotetraploid species
title_sort tetrasomic inheritance model and likelihood‐based method for mapping quantitative trait loci in autotetraploid species
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7984458/
https://www.ncbi.nlm.nih.gov/pubmed/31913501
http://dx.doi.org/10.1111/nph.16413
work_keys_str_mv AT chenjing atetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies
AT leachlindsey atetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies
AT yangjixuan atetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies
AT zhangfengjun atetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies
AT taoqin atetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies
AT dangzhenyu atetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies
AT chenyue atetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies
AT luozewei atetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies
AT chenjing tetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies
AT leachlindsey tetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies
AT yangjixuan tetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies
AT zhangfengjun tetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies
AT taoqin tetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies
AT dangzhenyu tetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies
AT chenyue tetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies
AT luozewei tetrasomicinheritancemodelandlikelihoodbasedmethodformappingquantitativetraitlociinautotetraploidspecies