A hierarchical statistical model for estimating population properties of quantitative genes.
Identifieur interne : 004633 ( Main/Exploration ); précédent : 004632; suivant : 004634A hierarchical statistical model for estimating population properties of quantitative genes.
Auteurs : Samuel S. Wu [États-Unis] ; Chang-Xing Ma ; Rongling Wu ; George CasellaSource :
- BMC genetics [ 1471-2156 ] ; 2002.
Descripteurs français
- KwdFr :
- MESH :
- croissance et développement : Populus.
- génétique : Gènes de plante, Populus, Reproduction.
- Algorithmes, Allèles, Génotype, Locus de caractère quantitatif, Modèles statistiques, Phénotype.
English descriptors
- KwdEn :
- MESH :
- genetics : Genes, Plant, Populus, Reproduction.
- growth & development : Populus.
- Algorithms, Alleles, Genotype, Models, Statistical, Phenotype, Quantitative Trait Loci.
Abstract
BACKGROUND
Earlier methods for detecting major genes responsible for a quantitative trait rely critically upon a well-structured pedigree in which the segregation pattern of genes exactly follow Mendelian inheritance laws. However, for many outcrossing species, such pedigrees are not available and genes also display population properties.
RESULTS
In this paper, a hierarchical statistical model is proposed to monitor the existence of a major gene based on its segregation and transmission across two successive generations. The model is implemented with an EM algorithm to provide maximum likelihood estimates for genetic parameters of the major locus. This new method is successfully applied to identify an additive gene having a large effect on stem height growth of aspen trees. The estimates of population genetic parameters for this major gene can be generalized to the original breeding population from which the parents were sampled. A simulation study is presented to evaluate finite sample properties of the model.
CONCLUSIONS
A hierarchical model was derived for detecting major genes affecting a quantitative trait based on progeny tests of outcrossing species. The new model takes into account the population genetic properties of genes and is expected to enhance the accuracy, precision and power of gene detection.
DOI: 10.1186/1471-2156-3-10
PubMed: 12097145
PubMed Central: PMC117225
Affiliations:
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Wu</name><affiliation wicri:level="2"><nlm:affiliation>Department of Statistics, University of Florida, Gainesville, FL 32611, USA. samwu@stat.ufl.edu</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Statistics, University of Florida, Gainesville, FL 32611</wicri:regionArea><placeName><region type="state">Floride</region></placeName></affiliation></author><author><name sortKey="Ma, Chang Xing" sort="Ma, Chang Xing" uniqKey="Ma C" first="Chang-Xing" last="Ma">Chang-Xing Ma</name></author><author><name sortKey="Wu, Rongling" sort="Wu, Rongling" uniqKey="Wu R" first="Rongling" last="Wu">Rongling Wu</name></author><author><name sortKey="Casella, George" sort="Casella, George" uniqKey="Casella G" first="George" last="Casella">George Casella</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2002">2002</date><idno type="RBID">pubmed:12097145</idno><idno type="pmid">12097145</idno><idno type="pmc">PMC117225</idno><idno type="doi">10.1186/1471-2156-3-10</idno><idno type="wicri:Area/Main/Corpus">004624</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">004624</idno><idno type="wicri:Area/Main/Curation">004624</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">004624</idno><idno type="wicri:Area/Main/Exploration">004624</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">A hierarchical statistical model for estimating population properties of quantitative genes.</title><author><name sortKey="Wu, Samuel S" sort="Wu, Samuel S" uniqKey="Wu S" first="Samuel S" last="Wu">Samuel S. 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However, for many outcrossing species, such pedigrees are not available and genes also display population properties.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>In this paper, a hierarchical statistical model is proposed to monitor the existence of a major gene based on its segregation and transmission across two successive generations. The model is implemented with an EM algorithm to provide maximum likelihood estimates for genetic parameters of the major locus. This new method is successfully applied to identify an additive gene having a large effect on stem height growth of aspen trees. The estimates of population genetic parameters for this major gene can be generalized to the original breeding population from which the parents were sampled. A simulation study is presented to evaluate finite sample properties of the model.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b></p><p>A hierarchical model was derived for detecting major genes affecting a quantitative trait based on progeny tests of outcrossing species. The new model takes into account the population genetic properties of genes and is expected to enhance the accuracy, precision and power of gene detection.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">12097145</PMID><DateCompleted><Year>2002</Year><Month>12</Month><Day>18</Day></DateCompleted><DateRevised><Year>2019</Year><Month>11</Month><Day>06</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1471-2156</ISSN><JournalIssue CitedMedium="Internet"><Volume>3</Volume><PubDate><Year>2002</Year><Month>Jun</Month><Day>12</Day></PubDate></JournalIssue><Title>BMC genetics</Title><ISOAbbreviation>BMC Genet</ISOAbbreviation></Journal><ArticleTitle>A hierarchical statistical model for estimating population properties of quantitative genes.</ArticleTitle><Pagination><MedlinePgn>10</MedlinePgn></Pagination><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Earlier methods for detecting major genes responsible for a quantitative trait rely critically upon a well-structured pedigree in which the segregation pattern of genes exactly follow Mendelian inheritance laws. However, for many outcrossing species, such pedigrees are not available and genes also display population properties.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">In this paper, a hierarchical statistical model is proposed to monitor the existence of a major gene based on its segregation and transmission across two successive generations. The model is implemented with an EM algorithm to provide maximum likelihood estimates for genetic parameters of the major locus. This new method is successfully applied to identify an additive gene having a large effect on stem height growth of aspen trees. The estimates of population genetic parameters for this major gene can be generalized to the original breeding population from which the parents were sampled. A simulation study is presented to evaluate finite sample properties of the model.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">A hierarchical model was derived for detecting major genes affecting a quantitative trait based on progeny tests of outcrossing species. 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IdType="pubmed">24232121</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed><affiliations><list><country><li>États-Unis</li></country><region><li>Floride</li></region></list><tree><noCountry><name sortKey="Casella, George" sort="Casella, George" uniqKey="Casella G" first="George" last="Casella">George Casella</name><name sortKey="Ma, Chang Xing" sort="Ma, Chang Xing" uniqKey="Ma C" first="Chang-Xing" last="Ma">Chang-Xing Ma</name><name sortKey="Wu, Rongling" sort="Wu, Rongling" uniqKey="Wu R" first="Rongling" last="Wu">Rongling Wu</name></noCountry><country name="États-Unis"><region name="Floride"><name sortKey="Wu, Samuel S" sort="Wu, Samuel S" uniqKey="Wu S" first="Samuel S" last="Wu">Samuel S. 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