Recursive Algorithms for Modeling Genomic Ancestral Origins in a Fixed Pedigree
The study of gene flow in pedigrees is of strong interest for the development of quantitative trait loci (QTL) mapping methods in multiparental populations. We developed a Markovian framework for modeling ancestral origins along two homologous chromosomes within individuals in fixed pedigrees. A hig...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Oxford University Press
2018-10-01
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| Series: | G3: Genes, Genomes, Genetics |
| Subjects: | |
| Online Access: | http://g3journal.org/lookup/doi/10.1534/g3.118.200340 |
| _version_ | 1818620344826593280 |
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| author | Chaozhi Zheng Martin P. Boer Fred A. van Eeuwijk |
| author_facet | Chaozhi Zheng Martin P. Boer Fred A. van Eeuwijk |
| author_sort | Chaozhi Zheng |
| collection | DOAJ |
| description | The study of gene flow in pedigrees is of strong interest for the development of quantitative trait loci (QTL) mapping methods in multiparental populations. We developed a Markovian framework for modeling ancestral origins along two homologous chromosomes within individuals in fixed pedigrees. A highly beneficial property of our method is that the size of state space depends linearly or quadratically on the number of pedigree founders, whereas this increases exponentially with pedigree size in alternative methods. To calculate the parameter values of the Markov process, we describe two novel recursive algorithms that differ with respect to the pedigree founders being assumed to be exchangeable or not. Our algorithms apply equally to autosomes and sex chromosomes, another desirable feature of our approach. We tested the accuracy of the algorithms by a million simulations on a pedigree. We demonstrated two applications of the recursive algorithms in multiparental populations: design a breeding scheme for maximizing the overall density of recombination breakpoints and thus the QTL mapping resolution, and incorporate pedigree information into hidden Markov models in ancestral inference from genotypic data; the conditional probabilities and the recombination breakpoint data resulting from ancestral inference can facilitate follow-up QTL mapping. The results show that the generality of the recursive algorithms can greatly increase the application range of genetic analysis such as ancestral inference in multiparental populations. |
| first_indexed | 2024-12-16T17:51:54Z |
| format | Article |
| id | doaj.art-3422782df9d14f2ca23d54ce34843e61 |
| institution | Directory Open Access Journal |
| issn | 2160-1836 |
| language | English |
| last_indexed | 2024-12-16T17:51:54Z |
| publishDate | 2018-10-01 |
| publisher | Oxford University Press |
| record_format | Article |
| series | G3: Genes, Genomes, Genetics |
| spelling | doaj.art-3422782df9d14f2ca23d54ce34843e612022-12-21T22:22:17ZengOxford University PressG3: Genes, Genomes, Genetics2160-18362018-10-018103231324510.1534/g3.118.20034010Recursive Algorithms for Modeling Genomic Ancestral Origins in a Fixed PedigreeChaozhi ZhengMartin P. BoerFred A. van EeuwijkThe study of gene flow in pedigrees is of strong interest for the development of quantitative trait loci (QTL) mapping methods in multiparental populations. We developed a Markovian framework for modeling ancestral origins along two homologous chromosomes within individuals in fixed pedigrees. A highly beneficial property of our method is that the size of state space depends linearly or quadratically on the number of pedigree founders, whereas this increases exponentially with pedigree size in alternative methods. To calculate the parameter values of the Markov process, we describe two novel recursive algorithms that differ with respect to the pedigree founders being assumed to be exchangeable or not. Our algorithms apply equally to autosomes and sex chromosomes, another desirable feature of our approach. We tested the accuracy of the algorithms by a million simulations on a pedigree. We demonstrated two applications of the recursive algorithms in multiparental populations: design a breeding scheme for maximizing the overall density of recombination breakpoints and thus the QTL mapping resolution, and incorporate pedigree information into hidden Markov models in ancestral inference from genotypic data; the conditional probabilities and the recombination breakpoint data resulting from ancestral inference can facilitate follow-up QTL mapping. The results show that the generality of the recursive algorithms can greatly increase the application range of genetic analysis such as ancestral inference in multiparental populations.http://g3journal.org/lookup/doi/10.1534/g3.118.200340Junction theoryIdentical by descentAncestral inferenceQTL mapping resolutionCollaborative Cross (CC)Recombinant Inbred Line (RIL)Multiparent Advanced Generation InterCross (MAGIC)multiparental populationsMPP |
| spellingShingle | Chaozhi Zheng Martin P. Boer Fred A. van Eeuwijk Recursive Algorithms for Modeling Genomic Ancestral Origins in a Fixed Pedigree G3: Genes, Genomes, Genetics Junction theory Identical by descent Ancestral inference QTL mapping resolution Collaborative Cross (CC) Recombinant Inbred Line (RIL) Multiparent Advanced Generation InterCross (MAGIC) multiparental populations MPP |
| title | Recursive Algorithms for Modeling Genomic Ancestral Origins in a Fixed Pedigree |
| title_full | Recursive Algorithms for Modeling Genomic Ancestral Origins in a Fixed Pedigree |
| title_fullStr | Recursive Algorithms for Modeling Genomic Ancestral Origins in a Fixed Pedigree |
| title_full_unstemmed | Recursive Algorithms for Modeling Genomic Ancestral Origins in a Fixed Pedigree |
| title_short | Recursive Algorithms for Modeling Genomic Ancestral Origins in a Fixed Pedigree |
| title_sort | recursive algorithms for modeling genomic ancestral origins in a fixed pedigree |
| topic | Junction theory Identical by descent Ancestral inference QTL mapping resolution Collaborative Cross (CC) Recombinant Inbred Line (RIL) Multiparent Advanced Generation InterCross (MAGIC) multiparental populations MPP |
| url | http://g3journal.org/lookup/doi/10.1534/g3.118.200340 |
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