Prediction of IBD based on population history for fine gene mapping

Abstract A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDLprobabilities are a function of the increase in linkage diseq...
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Autor*in:	Hernández-Sánchez, Jules [verfasserIn] Haley, Chris S. Woolliams, John A.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2006

Schlagwörter:	QTL fine mapping identity-by-descent

Anmerkung:	© INRA, EDP Sciences 2006

Übergeordnetes Werk:	Enthalten in: Genetics, selection, evolution - London : BioMed Central, 1989, 38(2006), 3 vom: 26. Apr.
Übergeordnetes Werk:	volume:38 ; year:2006 ; number:3 ; day:26 ; month:04

Links:	Volltext

DOI / URN:	10.1186/1297-9686-38-3-231

Katalog-ID:	SPR026803674

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520			\|a Abstract A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDLprobabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBDLare used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM.
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allfields	10.1186/1297-9686-38-3-231 doi (DE-627)SPR026803674 (SPR)1297-9686-38-3-231-e DE-627 ger DE-627 rakwb eng Hernández-Sánchez, Jules verfasserin aut Prediction of IBD based on population history for fine gene mapping 2006 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © INRA, EDP Sciences 2006 Abstract A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDLprobabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBDLare used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM. QTL fine mapping (dpeaa)DE-He213 identity-by-descent (dpeaa)DE-He213 Haley, Chris S. aut Woolliams, John A. aut Enthalten in Genetics, selection, evolution London : BioMed Central, 1989 38(2006), 3 vom: 26. Apr. (DE-627)312849052 (DE-600)2012369-3 1297-9686 nnns volume:38 year:2006 number:3 day:26 month:04 https://dx.doi.org/10.1186/1297-9686-38-3-231 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 38 2006 3 26 04
spelling	10.1186/1297-9686-38-3-231 doi (DE-627)SPR026803674 (SPR)1297-9686-38-3-231-e DE-627 ger DE-627 rakwb eng Hernández-Sánchez, Jules verfasserin aut Prediction of IBD based on population history for fine gene mapping 2006 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © INRA, EDP Sciences 2006 Abstract A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDLprobabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBDLare used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM. QTL fine mapping (dpeaa)DE-He213 identity-by-descent (dpeaa)DE-He213 Haley, Chris S. aut Woolliams, John A. aut Enthalten in Genetics, selection, evolution London : BioMed Central, 1989 38(2006), 3 vom: 26. Apr. (DE-627)312849052 (DE-600)2012369-3 1297-9686 nnns volume:38 year:2006 number:3 day:26 month:04 https://dx.doi.org/10.1186/1297-9686-38-3-231 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 38 2006 3 26 04
allfields_unstemmed	10.1186/1297-9686-38-3-231 doi (DE-627)SPR026803674 (SPR)1297-9686-38-3-231-e DE-627 ger DE-627 rakwb eng Hernández-Sánchez, Jules verfasserin aut Prediction of IBD based on population history for fine gene mapping 2006 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © INRA, EDP Sciences 2006 Abstract A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDLprobabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBDLare used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM. QTL fine mapping (dpeaa)DE-He213 identity-by-descent (dpeaa)DE-He213 Haley, Chris S. aut Woolliams, John A. aut Enthalten in Genetics, selection, evolution London : BioMed Central, 1989 38(2006), 3 vom: 26. Apr. (DE-627)312849052 (DE-600)2012369-3 1297-9686 nnns volume:38 year:2006 number:3 day:26 month:04 https://dx.doi.org/10.1186/1297-9686-38-3-231 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 38 2006 3 26 04
allfieldsGer	10.1186/1297-9686-38-3-231 doi (DE-627)SPR026803674 (SPR)1297-9686-38-3-231-e DE-627 ger DE-627 rakwb eng Hernández-Sánchez, Jules verfasserin aut Prediction of IBD based on population history for fine gene mapping 2006 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © INRA, EDP Sciences 2006 Abstract A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDLprobabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBDLare used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM. QTL fine mapping (dpeaa)DE-He213 identity-by-descent (dpeaa)DE-He213 Haley, Chris S. aut Woolliams, John A. aut Enthalten in Genetics, selection, evolution London : BioMed Central, 1989 38(2006), 3 vom: 26. Apr. (DE-627)312849052 (DE-600)2012369-3 1297-9686 nnns volume:38 year:2006 number:3 day:26 month:04 https://dx.doi.org/10.1186/1297-9686-38-3-231 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 38 2006 3 26 04
allfieldsSound	10.1186/1297-9686-38-3-231 doi (DE-627)SPR026803674 (SPR)1297-9686-38-3-231-e DE-627 ger DE-627 rakwb eng Hernández-Sánchez, Jules verfasserin aut Prediction of IBD based on population history for fine gene mapping 2006 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © INRA, EDP Sciences 2006 Abstract A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDLprobabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBDLare used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM. QTL fine mapping (dpeaa)DE-He213 identity-by-descent (dpeaa)DE-He213 Haley, Chris S. aut Woolliams, John A. aut Enthalten in Genetics, selection, evolution London : BioMed Central, 1989 38(2006), 3 vom: 26. Apr. (DE-627)312849052 (DE-600)2012369-3 1297-9686 nnns volume:38 year:2006 number:3 day:26 month:04 https://dx.doi.org/10.1186/1297-9686-38-3-231 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 38 2006 3 26 04
language	English
source	Enthalten in Genetics, selection, evolution 38(2006), 3 vom: 26. Apr. volume:38 year:2006 number:3 day:26 month:04
sourceStr	Enthalten in Genetics, selection, evolution 38(2006), 3 vom: 26. Apr. volume:38 year:2006 number:3 day:26 month:04
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	QTL fine mapping identity-by-descent
isfreeaccess_bool	true
container_title	Genetics, selection, evolution
authorswithroles_txt_mv	Hernández-Sánchez, Jules @@aut@@ Haley, Chris S. @@aut@@ Woolliams, John A. @@aut@@
publishDateDaySort_date	2006-04-26T00:00:00Z
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author	Hernández-Sánchez, Jules
spellingShingle	Hernández-Sánchez, Jules misc QTL fine mapping misc identity-by-descent Prediction of IBD based on population history for fine gene mapping
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topic_title	Prediction of IBD based on population history for fine gene mapping QTL fine mapping (dpeaa)DE-He213 identity-by-descent (dpeaa)DE-He213
topic	misc QTL fine mapping misc identity-by-descent
topic_unstemmed	misc QTL fine mapping misc identity-by-descent
topic_browse	misc QTL fine mapping misc identity-by-descent
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
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title	Prediction of IBD based on population history for fine gene mapping
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title_full	Prediction of IBD based on population history for fine gene mapping
author_sort	Hernández-Sánchez, Jules
journal	Genetics, selection, evolution
journalStr	Genetics, selection, evolution
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author_browse	Hernández-Sánchez, Jules Haley, Chris S. Woolliams, John A.
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author-letter	Hernández-Sánchez, Jules
doi_str_mv	10.1186/1297-9686-38-3-231
title_sort	prediction of ibd based on population history for fine gene mapping
title_auth	Prediction of IBD based on population history for fine gene mapping
abstract	Abstract A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDLprobabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBDLare used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM. © INRA, EDP Sciences 2006
abstractGer	Abstract A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDLprobabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBDLare used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM. © INRA, EDP Sciences 2006
abstract_unstemmed	Abstract A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDLprobabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBDLare used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM. © INRA, EDP Sciences 2006
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title_short	Prediction of IBD based on population history for fine gene mapping
url	https://dx.doi.org/10.1186/1297-9686-38-3-231
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author2	Haley, Chris S. Woolliams, John A.
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up_date	2024-07-03T22:49:10.406Z
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