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A conceptual framework for mapping quantitative trait Loci regulating ontogenetic allometry
Although ontogenetic changes in body shape and its associated allometry has been studied for over a century, essentially nothing is known about their underlying genetic and developmental mechanisms. One of the reasons for this ignorance is the unavailability of a conceptual framework to formulate th...
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Published in: | PloS one 2007-11, Vol.2 (11), p.e1245-e1245 |
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description | Although ontogenetic changes in body shape and its associated allometry has been studied for over a century, essentially nothing is known about their underlying genetic and developmental mechanisms. One of the reasons for this ignorance is the unavailability of a conceptual framework to formulate the experimental design for data collection and statistical models for data analyses. We developed a framework model for unraveling the genetic machinery for ontogenetic changes of allometry. The model incorporates the mathematical aspects of ontogenetic growth and allometry into a maximum likelihood framework for quantitative trait locus (QTL) mapping. As a quantitative platform, the model allows for the testing of a number of biologically meaningful hypotheses to explore the pleiotropic basis of the QTL that regulate ontogeny and allometry. Simulation studies and real data analysis of a live example in soybean have been performed to investigate the statistical behavior of the model and validate its practical utilization. The statistical model proposed will help to study the genetic architecture of complex phenotypes and, therefore, gain better insights into the mechanistic regulation for developmental patterns and processes in organisms. |
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One of the reasons for this ignorance is the unavailability of a conceptual framework to formulate the experimental design for data collection and statistical models for data analyses. We developed a framework model for unraveling the genetic machinery for ontogenetic changes of allometry. The model incorporates the mathematical aspects of ontogenetic growth and allometry into a maximum likelihood framework for quantitative trait locus (QTL) mapping. As a quantitative platform, the model allows for the testing of a number of biologically meaningful hypotheses to explore the pleiotropic basis of the QTL that regulate ontogeny and allometry. Simulation studies and real data analysis of a live example in soybean have been performed to investigate the statistical behavior of the model and validate its practical utilization. The statistical model proposed will help to study the genetic architecture of complex phenotypes and, therefore, gain better insights into the mechanistic regulation for developmental patterns and processes in organisms.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0001245</identifier><identifier>PMID: 18043752</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Allometry ; Analysis ; Animal behavior ; Biomass ; Computer Simulation ; Data analysis ; Data collection ; Data processing ; Dimensional analysis ; Experimental design ; Gene loci ; Gene mapping ; Genetics ; Genetics and Genomics/Complex Traits ; Genomes ; Genotype & phenotype ; Gerridae ; Glycine max ; Information management ; Likelihood Functions ; Loci ; Machinery ; Machinery and equipment ; Mapping ; Mathematical models ; Mathematics/Statistics ; Metabolism ; Models, Genetic ; Ontogeny ; Parameter estimation ; Plant Biology ; Power ; Quantitative genetics ; Quantitative Trait Loci ; Simulation ; Soybeans ; Statistical analysis ; Statistical models ; Studies ; Trends</subject><ispartof>PloS one, 2007-11, Vol.2 (11), p.e1245-e1245</ispartof><rights>COPYRIGHT 2007 Public Library of Science</rights><rights>2007 Li et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Li et al. 2007</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c644t-603bbc1039d64b77c9d823302af123aac48df82cd8fe4d654ccf6a864f9bd7bd3</citedby><cites>FETCH-LOGICAL-c644t-603bbc1039d64b77c9d823302af123aac48df82cd8fe4d654ccf6a864f9bd7bd3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1289138396/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1289138396?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18043752$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Shiu, Shin-Han</contributor><creatorcontrib>Li, Hongying</creatorcontrib><creatorcontrib>Huang, Zhongwen</creatorcontrib><creatorcontrib>Gai, Junyi</creatorcontrib><creatorcontrib>Wu, Song</creatorcontrib><creatorcontrib>Zeng, Yanru</creatorcontrib><creatorcontrib>Li, Qin</creatorcontrib><creatorcontrib>Wu, Rongling</creatorcontrib><title>A conceptual framework for mapping quantitative trait Loci regulating ontogenetic allometry</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Although ontogenetic changes in body shape and its associated allometry has been studied for over a century, essentially nothing is known about their underlying genetic and developmental mechanisms. One of the reasons for this ignorance is the unavailability of a conceptual framework to formulate the experimental design for data collection and statistical models for data analyses. We developed a framework model for unraveling the genetic machinery for ontogenetic changes of allometry. The model incorporates the mathematical aspects of ontogenetic growth and allometry into a maximum likelihood framework for quantitative trait locus (QTL) mapping. As a quantitative platform, the model allows for the testing of a number of biologically meaningful hypotheses to explore the pleiotropic basis of the QTL that regulate ontogeny and allometry. Simulation studies and real data analysis of a live example in soybean have been performed to investigate the statistical behavior of the model and validate its practical utilization. The statistical model proposed will help to study the genetic architecture of complex phenotypes and, therefore, gain better insights into the mechanistic regulation for developmental patterns and processes in organisms.</description><subject>Algorithms</subject><subject>Allometry</subject><subject>Analysis</subject><subject>Animal behavior</subject><subject>Biomass</subject><subject>Computer Simulation</subject><subject>Data analysis</subject><subject>Data collection</subject><subject>Data processing</subject><subject>Dimensional analysis</subject><subject>Experimental design</subject><subject>Gene loci</subject><subject>Gene mapping</subject><subject>Genetics</subject><subject>Genetics and Genomics/Complex Traits</subject><subject>Genomes</subject><subject>Genotype & phenotype</subject><subject>Gerridae</subject><subject>Glycine max</subject><subject>Information management</subject><subject>Likelihood Functions</subject><subject>Loci</subject><subject>Machinery</subject><subject>Machinery and equipment</subject><subject>Mapping</subject><subject>Mathematical models</subject><subject>Mathematics/Statistics</subject><subject>Metabolism</subject><subject>Models, Genetic</subject><subject>Ontogeny</subject><subject>Parameter estimation</subject><subject>Plant Biology</subject><subject>Power</subject><subject>Quantitative genetics</subject><subject>Quantitative Trait Loci</subject><subject>Simulation</subject><subject>Soybeans</subject><subject>Statistical analysis</subject><subject>Statistical 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Yanru</au><au>Li, Qin</au><au>Wu, Rongling</au><au>Shiu, Shin-Han</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A conceptual framework for mapping quantitative trait Loci regulating ontogenetic allometry</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2007-11-28</date><risdate>2007</risdate><volume>2</volume><issue>11</issue><spage>e1245</spage><epage>e1245</epage><pages>e1245-e1245</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Although ontogenetic changes in body shape and its associated allometry has been studied for over a century, essentially nothing is known about their underlying genetic and developmental mechanisms. One of the reasons for this ignorance is the unavailability of a conceptual framework to formulate the experimental design for data collection and statistical models for data analyses. We developed a framework model for unraveling the genetic machinery for ontogenetic changes of allometry. The model incorporates the mathematical aspects of ontogenetic growth and allometry into a maximum likelihood framework for quantitative trait locus (QTL) mapping. As a quantitative platform, the model allows for the testing of a number of biologically meaningful hypotheses to explore the pleiotropic basis of the QTL that regulate ontogeny and allometry. Simulation studies and real data analysis of a live example in soybean have been performed to investigate the statistical behavior of the model and validate its practical utilization. The statistical model proposed will help to study the genetic architecture of complex phenotypes and, therefore, gain better insights into the mechanistic regulation for developmental patterns and processes in organisms.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>18043752</pmid><doi>10.1371/journal.pone.0001245</doi><tpages>e1245</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Allometry Analysis Animal behavior Biomass Computer Simulation Data analysis Data collection Data processing Dimensional analysis Experimental design Gene loci Gene mapping Genetics Genetics and Genomics/Complex Traits Genomes Genotype & phenotype Gerridae Glycine max Information management Likelihood Functions Loci Machinery Machinery and equipment Mapping Mathematical models Mathematics/Statistics Metabolism Models, Genetic Ontogeny Parameter estimation Plant Biology Power Quantitative genetics Quantitative Trait Loci Simulation Soybeans Statistical analysis Statistical models Studies Trends |
title | A conceptual framework for mapping quantitative trait Loci regulating ontogenetic allometry |
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