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Zheng K, Yan J, Deng J, Wu W, Wen Y. Modification of Experimental Design and Statistical Method for Mapping Imprinted QTLs Based on Immortalized F2 Population. Front Genet 2020; 11:589047. [PMID: 33329733 PMCID: PMC7714927 DOI: 10.3389/fgene.2020.589047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 10/29/2020] [Indexed: 11/20/2022] Open
Abstract
Genomic imprinting is an epigenetic phenomenon, which plays important roles in the growth and development of animals and plants. Immortalized F2 (imF2) populations generated by random cross between recombinant inbred (RI) or doubled haploid (DH) lines have been proved to have significant advantages for mapping imprinted quantitative trait loci (iQTLs), and statistical methods for this purpose have been proposed. In this paper, we propose a special type of imF2 population (R-imF2) for iQTL mapping, which is developed by random reciprocal cross between RI/DH lines. We also propose two modified iQTL mapping methods: two-step point mapping (PM-2) and two-step composite point mapping (CPM-2). Simulation studies indicated that: (i) R-imF2 cannot improve the results of iQTL mapping, but the experimental design can probably reduce the workload of population construction; (ii) PM-2 can increase the precision of estimating the position and effects of a single iQTL; and (iii) CPM-2 can precisely map not only iQTLs, but also non-imprinted QTLs. The modified experimental design and statistical methods will facilitate and promote the study of iQTL mapping.
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Affiliation(s)
- Kehui Zheng
- College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China
- College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Jiqiang Yan
- College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Jiacong Deng
- School of Ocean and Biochemical Engineering, Fuqing Branch of Fujian Normal University, Fuzhou, China
| | - Weiren Wu
- Fujian Provincial Key Laboratory of Crop Breeding by Design, Fujian Agriculture and Forestry University, Fuzhou, China
- Key Laboratory of Genetics, Breeding and Multiple Utilization of Crops, Ministry of Education, Fujian Agriculture and Forestry University, Fuzhou, China
- *Correspondence: Weiren Wu,
| | - Yongxian Wen
- College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, China
- Yongxian Wen,
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Abstract
Despite increasing emphasis on the genetic study of quantitative traits, we are still far from being able to chart a clear picture of their genetic architecture, given an inherent complexity involved in trait formation. A competing theory for studying such complex traits has emerged by viewing their phenotypic formation as a "system" in which a high-dimensional group of interconnected components act and interact across different levels of biological organization from molecules through cells to whole organisms. This system is initiated by a machinery of DNA sequences that regulate a cascade of biochemical pathways to synthesize endophenotypes and further assemble these endophenotypes toward the end-point phenotype in virtue of various developmental changes. This review focuses on a conceptual framework for genetic mapping of complex traits by which to delineate the underlying components, interactions and mechanisms that govern the system according to biological principles and understand how these components function synergistically under the control of quantitative trait loci (QTLs) to comprise a unified whole. This framework is built by a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function, and provides a quantitative and testable platform for assessing the multiscale interplay between QTLs and development. The method will enable geneticists to shed light on the genetic complexity of any biological system and predict, alter or engineer its physiological and pathological states.
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Affiliation(s)
- Lidan Sun
- National Engineering Research Center for Floriculture, College of Landscape Architecture, Beijing Forestry University, Beijing 100083, China; Center for Statistical Genetics, Departments of Public Health Sciences and Statistics, The Pennsylvania State University, Hershey, PA 17033, USA
| | - Rongling Wu
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China; Center for Statistical Genetics, Departments of Public Health Sciences and Statistics, The Pennsylvania State University, Hershey, PA 17033, USA.
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Yin D, Zhu X, Jiang L, Zhang J, Zeng Y, Wu R. A reciprocal cross design to map the genetic architecture of complex traits in apomictic plants. THE NEW PHYTOLOGIST 2015; 205:1360-1367. [PMID: 25354995 DOI: 10.1111/nph.13128] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2014] [Accepted: 09/11/2014] [Indexed: 06/04/2023]
Abstract
Many higher plants of economic and biological importance undergo apomixis in which the maternal tissue of the ovule forms a seed, without experiencing meiosis and fertilization. This feature of apomixis has made it difficult to perform linkage mapping which relies on meiotic recombination. Here, we describe a computational model for mapping quantitative trait loci (QTLs) that control complex traits in apomictic plants. The model is founded on the mixture model-based likelihood in which maternal genotypes are dissolved into two possible components generated by meiotic and apomictic processes, respectively. The EM algorithm was implemented to discern meiotic and apomictic genotypes and, therefore, allow the marker-QTL linkage relationship to be estimated. By capitalizing on reciprocal crosses, the model is renovated to estimate and test imprinting effects of QTLs, providing a better gateway to characterize the genetic architecture of complex traits. The model was validated through computer simulation and further demonstrated for its usefulness by analyzing a real data for an apomictic woody plant. The model has for the first time provided a unique tool for genetic mapping in apomictic plants.
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Affiliation(s)
- Danni Yin
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, 100083, China
| | - Xuli Zhu
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, 100083, China
| | - Libo Jiang
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, 100083, China
| | - Jian Zhang
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, 100083, China
- Yuanpeng Genome Institute of Jiangsu, Nantong, Jiangsu, 226531, China
| | - Yanru Zeng
- The Nurturing Station for the State Key Laboratory of Subtropical Silviculture, Zhejiang Agricultural and Forestry University, Lin'an, Zhejiang, 311300, China
| | - Rongling Wu
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, 100083, China
- Center for Statistical Genetics, The Pennsylvania State University, Hershey, PA, 17033, USA
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An open-pollinated design for mapping imprinting genes in natural populations. Brief Bioinform 2014; 16:449-60. [DOI: 10.1093/bib/bbu019] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2014] [Accepted: 04/14/2014] [Indexed: 02/04/2023] Open
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Wang C, Wang Z, Prows DR, Wu R. A computational framework for the inheritance pattern of genomic imprinting for complex traits. Brief Bioinform 2012; 13:34-45. [PMID: 21565936 PMCID: PMC3278998 DOI: 10.1093/bib/bbr023] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2011] [Revised: 03/26/2011] [Indexed: 11/13/2022] Open
Abstract
Genetic imprinting, by which the expression of a gene depends on the parental origin of its alleles, may be subjected to reprogramming through each generation. Currently, such reprogramming is limited to qualitative description only, lacking more precise quantitative estimation for its extent, pattern and mechanism. Here, we present a computational framework for analyzing the magnitude of genetic imprinting and its transgenerational inheritance mode. This quantitative model is based on the breeding scheme of reciprocal backcrosses between reciprocal F(1) hybrids and original inbred parents, in which the transmission of genetic imprinting across generations can be tracked. We define a series of quantitative genetic parameters that describe the extent and transmission mode of genetic imprinting and further estimate and test these parameters within a genetic mapping framework using a new powerful computational algorithm. The model and algorithm described will enable geneticists to identify and map imprinted quantitative trait loci and dictate a comprehensive atlas of developmental and epigenetic mechanisms related to genetic imprinting. We illustrate the new discovery of the role of genetic imprinting in regulating hyperoxic acute lung injury survival time using a mouse reciprocal backcross design.
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Affiliation(s)
- Chenguang Wang
- Office of Surveillance and Biometrics, Center for Devices and Radiological Health, Food and Drug Administration, USA
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Zhao X, Tong C, Pang X, Wang Z, Guo Y, Du F, Wu R. Functional mapping of ontogeny in flowering plants. Brief Bioinform 2011; 13:317-28. [DOI: 10.1093/bib/bbr054] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Li Y, Guo Y, Wang J, Hou W, Chang MN, Liao D, Wu R. A statistical design for testing transgenerational genomic imprinting in natural human populations. PLoS One 2011; 6:e16858. [PMID: 21364891 PMCID: PMC3045439 DOI: 10.1371/journal.pone.0016858] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2010] [Accepted: 12/31/2010] [Indexed: 12/27/2022] Open
Abstract
Genomic imprinting is a phenomenon in which the same allele is expressed differently, depending on its parental origin. Such a phenomenon, also called the parent-of-origin effect, has been recognized to play a pivotal role in embryological development and pathogenesis in many species. Here we propose a statistical design for detecting imprinted loci that control quantitative traits based on a random set of three-generation families from a natural population in humans. This design provides a pathway for characterizing the effects of imprinted genes on a complex trait or disease at different generations and testing transgenerational changes of imprinted effects. The design is integrated with population and cytogenetic principles of gene segregation and transmission from a previous generation to next. The implementation of the EM algorithm within the design framework leads to the estimation of genetic parameters that define imprinted effects. A simulation study is used to investigate the statistical properties of the model and validate its utilization. This new design, coupled with increasingly used genome-wide association studies, should have an immediate implication for studying the genetic architecture of complex traits in humans.
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Affiliation(s)
- Yao Li
- Center for Computational Biology, Beijing Forestry University, Beijing, People's Republic of China
- Department of Statistics, West Virginia University, Morgantown, West Virginia, United States of America
| | - Yunqian Guo
- Center for Computational Biology, Beijing Forestry University, Beijing, People's Republic of China
| | - Jianxin Wang
- Center for Computational Biology, Beijing Forestry University, Beijing, People's Republic of China
| | - Wei Hou
- Department of Biostatistics, University of Florida, Gainesville, Florida, United States of America
| | - Myron N. Chang
- Department of Biostatistics, University of Florida, Gainesville, Florida, United States of America
| | - Duanping Liao
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania, United States of America
| | - Rongling Wu
- Center for Computational Biology, Beijing Forestry University, Beijing, People's Republic of China
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania, United States of America
- * E-mail:
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A model for transgenerational imprinting variation in complex traits. PLoS One 2010; 5:e11396. [PMID: 20644725 PMCID: PMC2904369 DOI: 10.1371/journal.pone.0011396] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2010] [Accepted: 05/06/2010] [Indexed: 12/15/2022] Open
Abstract
Despite the fact that genetic imprinting, i.e., differential expression of the same allele due to its different parental origins, plays a pivotal role in controlling complex traits or diseases, the origin, action and transmission mode of imprinted genes have still remained largely unexplored. We present a new strategy for studying these properties of genetic imprinting with a two-stage reciprocal F mating design, initiated with two contrasting inbred lines. This strategy maps quantitative trait loci that are imprinted (i.e., iQTLs) based on their segregation and transmission across different generations. By incorporating the allelic configuration of an iQTL genotype into a mixture model framework, this strategy provides a path to trace the parental origin of alleles from previous generations. The imprinting effects of iQTLs and their interactions with other traditionally defined genetic effects, expressed in different generations, are estimated and tested by implementing the EM algorithm. The strategy was used to map iQTLs responsible for survival time with four reciprocal F populations and test whether and how the detected iQTLs inherit their imprinting effects into the next generation. The new strategy will provide a tool for quantifying the role of imprinting effects in the creation and maintenance of phenotypic diversity and elucidating a comprehensive picture of the genetic architecture of complex traits and diseases.
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Maternal-zygotic epistasis and the evolution of genetic diseases. J Biomed Biotechnol 2010; 2010:478732. [PMID: 20467476 PMCID: PMC2867001 DOI: 10.1155/2010/478732] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2009] [Revised: 11/25/2009] [Accepted: 02/19/2010] [Indexed: 01/08/2023] Open
Abstract
Many birth defects and genetic diseases are expressed in individuals that do not carry the disease causing alleles. Genetic diseases observed in offspring can be caused by gene expression in mothers and by interactions between gene expression in mothers and offspring. It is not clear whether the underlying pattern of gene expression (maternal versus offspring) affects the incidence of genetic disease. Here we develop a 2-locus population genetic model with epistatic interactions between a maternal gene and a zygotic gene to address this question. We show that maternal effect genes that affect disease susceptibility in offspring persist longer and at higher frequencies in a population than offspring genes with the same effects. We find that specific forms of maternal-zygotic epistasis can maintain disease causing alleles at high frequencies over a range of plausible values. Our findings suggest that the strength and form of epistasis and the underlying pattern of gene expression may greatly influence the prevalence of human genetic diseases.
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Berger F, Chaudhury A. Parental memories shape seeds. TRENDS IN PLANT SCIENCE 2009; 14:550-6. [PMID: 19748816 DOI: 10.1016/j.tplants.2009.08.003] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2009] [Revised: 07/31/2009] [Accepted: 08/04/2009] [Indexed: 05/05/2023]
Abstract
It is ten years since imprinting was first demonstrated in Arabidopsis, following the realization, five years earlier, that some genetic controls of seed development did not conform to Mendelian inheritance. Sixteen imprinted genes have since been identified in maize and Arabidopsis and these are expressed primarily in the endosperm, which nurtures embryo development. Imprinting results from the regulation of transcriptional silencing by DNA methylation or by Polycomb Group complex-mediated histone methylation. Here we review recent studies suggesting that imprinting results from global epigenetic changes that occur during female gametogenesis. We also discuss why imprinting has evolved and what its biological functions might be.
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Affiliation(s)
- Fred Berger
- Temasek Lifesciences Laboratory, 117604 Singapore.
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Wang X, Xu C, Wu R, Larkins BA. Genetic dissection of complex endosperm traits. TRENDS IN PLANT SCIENCE 2009; 14:391-398. [PMID: 19546022 DOI: 10.1016/j.tplants.2009.04.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2009] [Revised: 04/23/2009] [Accepted: 04/23/2009] [Indexed: 05/28/2023]
Abstract
The endosperm of plants is a major source of food, feed and industrial raw materials. The genetic analysis of endosperm traits poses numerous challenges due to the endosperm's complex genetic composition and unique physical and developmental properties. Modern molecular techniques and statistical methods have greatly improved the mapping of quantitative trait loci underlying endosperm traits and have led to revolutionary insights regarding epistatic and epigenetic effects. This article describes the current state of the methodologies used in the genetic dissection of endosperm traits and highlights practical issues and statistical concepts and procedures.
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Affiliation(s)
- Xuefeng Wang
- Jiangsu Provincial Key Laboratory of Crop Genetics and Physiology; Key Laboratory of Plant Functional Genomics of the Ministry of Education, Yangzhou University, Yangzhou, China
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A Statistical Variance Components Framework for Mapping Imprinted Quantitative Trait Locus in Experimental Crosses. JOURNAL OF PROBABILITY AND STATISTICS 2009. [DOI: 10.1155/2009/689489] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Current methods for mapping imprinted quantitative trait locus (iQTL) with inbred line crosses assume fixed QTL effects. When an iQTL segregates in experimental line crosses, combining different line crosses with similar genetic background can improve the accuracy of iQTLs inference. In this article, we develop a general interval-based statistical variance components framework to map iQTLs underlying complex traits by combining different backcross line crosses. We propose a new iQTL variance partition method based on the nature of marker alleles shared identical-by-decent (IBD) in inbred lines. Maternal effect is adjusted when testing imprinting. Efficient estimation methods with the maximum likelihood and the restricted maximum likelihood are derived and compared. Statistical properties of the proposed mapping strategy are evaluated through extensive simulations under different sampling designs. An extension to multiple QTL analysis is given. The proposed method will greatly facilitate genetic dissection of imprinted complex traits in inbred line crosses.
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