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    A Multi-Locus Association Model Framework for Nested Association Mapping With Discriminating QTL Effects in Various Subpopulations
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    Abstract:
    Nested association mapping (NAM) has been an invaluable approach for plant genetics community and can dissect the genetic architecture of complex traits. As the most popular NAM analysis strategy, joint multifamily mapping can combine all information from diverse genetic backgrounds and increase population size. However, it is influenced by the genetic heterogeneity of quantitative trait locus (QTL) across various subpopulations. Multi-locus association mapping has been proven to be powerful in many cases of QTL mapping and genome-wide association studies. Therefore, we developed a multi-locus association model of multiple families in the NAM population, which could discriminate the effects of QTLs in all subpopulations. A series of simulations with a real maize NAM genomic data were implemented. The results demonstrated that the new method improves the statistical power in QTL detection and the accuracy in QTL effect estimation. The new approach, along with single-family linkage mapping, was used to identify QTLs for three flowering time traits in the maize NAM population. As a result, most QTLs detected in single family linkage mapping were identified by the new method. In addition, the new method also mapped some new QTLs with small effects, although their functions need to be identified in the future.
    Keywords:
    Family-based QTL mapping
    Association mapping
    Genetic Association
    Genetic architecture
    Genome-wide Association Study
    Genetic linkage
    Both modern molecular biology technique and new statistical methods greatly promoted the analysis of plant quantitative trait loci(QTL).Linkage mapping(LM)and association mapping(AM) are two important methods for QTL analysis.Both them have obvious complementarity in the accuracy and breadth of QTL mapping,the provided information,and the statistical analysis method.Linkage mapping can preliminary locate the target trait gene,while association mapping can quickly achieve the verification and fine mapping of target gene;moreover,it can also verify the candidate gene function according to a lot of information provided for a specific candidate gene.In this paper,the new advances were reviewed from the linkage mapping and association mapping of cotton quantitative traits.The research prospects of cotton QTL were analyzed by combining the two methods.
    Family-based QTL mapping
    Association mapping
    Linkage (software)
    Genetic linkage
    Candidate gene
    Trait
    Genetic Association
    Citations (0)
    Family-based QTL mapping
    Association mapping
    Linkage (software)
    Trait
    Identification
    Genetic linkage
    Citations (18)
    Dissecting the genetic architecture of complex traits is an ongoing challenge for geneticists. Two complementary approaches for genetic mapping, linkage mapping and association mapping have led to successful dissection of complex traits in many crop species. Both of these methods detect quantitative trait loci (QTL) by identifying marker–trait associations, and the only fundamental difference between them is that between mapping populations, which directly determine mapping resolution and power. Based on this difference, we first summarize in this review the advances and limitations of family-based mapping and natural population-based mapping instead of linkage mapping and association mapping. We then describe statistical methods used for improving detection power and computational speed and outline emerging areas such as large-scale meta-analysis for genetic mapping in crops. In the era of next-generation sequencing, there has arisen an urgent need for proper population design, advanced statistical strategies, and precision phenotyping to fully exploit high-throughput genotyping.
    Family-based QTL mapping
    Association mapping
    Genetic architecture
    Linkage (software)
    Trait
    Genetic Association
    Citations (200)
    Understanding and estimating the structure and parameters associated with the genetic architecture of quantitative traits is a major research focus in quantitative genetics. With the availability of a well-saturated genetic map of molecular markers, it is possible to identify a major part of the structure of the genetic architecture of quantitative traits and to estimate the associated parameters. Multiple interval mapping, which was recently proposed for simultaneously mapping multiple quantitative trait loci (QTL), is well suited to the identification and estimation of the genetic architecture parameters, including the number, genomic positions, effects and interactions of significant QTL and their contribution to the genetic variance. With multiple traits and multiple environments involved in a QTL mapping experiment, pleiotropic effects and QTL by environment interactions can also be estimated. We review the method and discuss issues associated with multiple interval mapping, such as likelihood analysis, model selection, stopping rules and parameter estimation. The potential power and advantages of the method for mapping multiple QTL and estimating the genetic architecture are discussed. We also point out potential problems and difficulties in resolving the details of the genetic architecture as well as other areas that require further investigation. One application of the analysis is to improve genome-wide marker-assisted selection, particularly when the information about epistasis is used for selection with mating.
    Genetic architecture
    Epistasis
    Family-based QTL mapping
    Association mapping
    Quantitative Genetics
    genetic model
    Citations (336)
    QTL mapping is an important step in gene fine mapping,map-based cloning,and the efficient use of gene information in molecular breeding.Questions are frequently met and asked in the application of QTL mapping in practical genetic populations.Questions related to statistical method of QTL mapping are:what does LOD score mean? What is the relationship between the reliability of detected QTL and the LOD threshold? How to evaluate different QTL mapping methods? How to improve the QTL detection power? Questions related to genetic parameter estimation are:how to calculate the phenotypic variance explained by each detected QTL? How to determine the source of favorable alleles at detected QTL? How efficient is the selective genotyping? Can composite traits be used in QTL mapping? Questions related to linkage map and mapping populations are:does the phenotype of a trait in interest have to follow a normal distribution? Does the increase in marker density greatly improve QTL mapping power? What effects will missing markers have in QTL mapping? What effects will segregation distortion have in QTL mapping? Our objective in this paper was to give an analysis and answer to each of the 12 frequently asked questions,based on our studies in past several years.
    Family-based QTL mapping
    Association mapping
    Positional cloning
    Trait
    Genetic linkage
    Citations (0)
    Family-based QTL mapping
    Association mapping
    Linkage (software)
    Linkage Disequilibrium
    Trait
    Traditionally, QTL mapping has been used as methodology to understand the genetic control of polygenic traits and has been useful for identifying QTL in different species, however QTL mapping presents limitations, such as the difficulty to build segregating populations in some species, the presence of only one meiotic generation and the reduced genetically diversity derived of just two parental. Recently, association genetics studies are becoming an important methodology to identify quantitative trait loci and to find diagnostic molecular markers associated with complex traits. This methodology overcomes some barriers of QTL mapping and it is an alternative to apply in plant breeding in direct way. However, it is necessary to considerer important aspects in this methodology to avoid false associations between trait-markers. Association genetics employs as parameter linkage disequilibrium to find these associations. Here we present methods to analyze and establish population structure, factors that affect linkage disequilibrium and how to measure it and methods to perform association mapping.
    Linkage Disequilibrium
    Family-based QTL mapping
    Association mapping
    Genetic Association
    Trait
    Linkage (software)
    Citations (12)
    Association mapping, a high-resolution method for mapping quantitative trait loci based on linkage disequilibrium, holds great promise for the dissection of complex genetic traits. General understanding of association mapping has increased significantly since its debut in plants. We have seen a more concerted effort in assembling various association-mapping populations and initiating experiments through either candidate-gene or genome-wide approaches in different plant species. In this review, we describe the current status of association mapping in plants, Relation between LD and Association Mapping, QTL Mapping and Association Mapping, Types of Association mapping, Steps in Association Mapping and Benefits and limitations of association mapping.
    Association mapping
    Family-based QTL mapping
    Linkage Disequilibrium
    Association (psychology)
    Genetic Association
    Genome-wide Association Study
    Linkage (software)
    Family-based QTL mapping
    Triticeae
    Genetic linkage
    Association mapping
    Linkage (software)
    Positional cloning
    Citations (10)