Investigation of Obesity Candidate Genes On Porcine Fat Deposition Quantitative Trait Loci Regions
Kwan‐Suk KimHauke ThomsenJ.W.M. BastiaansenNguyet Thu NguyenJack C. M. DekkersGraham PlastowMax F. Rothschild
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Abstract Objectives : To investigate possible obesity candidate genes in regions of porcine quantitative trait loci (QTL) for fat deposition and obesity‐related phenotypes. Research Methods and Procedures : Chromosome mapping and QTL analyses of obesity candidate genes were performed using DNA panels from a reference pig family. Statistical association analyses of these genes were performed for fat deposition phenotypes in several other commercial pig populations. Results : Eight candidate genes were mapped to QTL regions of pig chromosomes in this study. These candidate genes also served as anchor loci to determine homologous human chromosomal locations of pig fat deposition QTL. Preliminary analyses of relationships among polymorphisms of individual candidate genes and a variety of phenotypic measurements in a large number of pigs were performed. On the basis of available data, gene‐gene interactions were also studied. Discussion : Comparative analysis of obesity‐related genes in the pig is not only important for development of marker‐assisted selection on growth and fat deposition traits in the pig but also provides for an understanding of their genetic roles in the development of human obesity.Keywords:
Candidate gene
Family-based QTL mapping
Polygene
Most of the important agronomic traits of rice are quantitative in nature, which are controlled by polygenes. In conventional quantitative genetics, QTL analysis was only executed as a whole. In recent years, the construction of highly dense molecular linkage map and the development of effective biostatistical methods have revolutionized the genetic studies of quantitative traits. The joint analysis of molecular marker genotype and phenotype values of individuals or lines in different populations enabled the detection and location of quantitative trait loci (QTL). In the present paper, the principles and methods of QTL mapping were introduced, recent progresses in the studies of QTL analysis in rice were reviewed, including QTL numbers and effects, epistasis effect, interaction between QTL and environment, QTLs of related characters, developmental QTL and so on. The rice genome sequencing project has been finished, therefore in this paper, the strategy for fine mapping and cloning of QTLs in the genome era was also discussed. Application prospect of QTL analysis in rice breeding was forecasted.
Family-based QTL mapping
Polygene
Epistasis
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Abstract Objectives : To investigate possible obesity candidate genes in regions of porcine quantitative trait loci (QTL) for fat deposition and obesity‐related phenotypes. Research Methods and Procedures : Chromosome mapping and QTL analyses of obesity candidate genes were performed using DNA panels from a reference pig family. Statistical association analyses of these genes were performed for fat deposition phenotypes in several other commercial pig populations. Results : Eight candidate genes were mapped to QTL regions of pig chromosomes in this study. These candidate genes also served as anchor loci to determine homologous human chromosomal locations of pig fat deposition QTL. Preliminary analyses of relationships among polymorphisms of individual candidate genes and a variety of phenotypic measurements in a large number of pigs were performed. On the basis of available data, gene‐gene interactions were also studied. Discussion : Comparative analysis of obesity‐related genes in the pig is not only important for development of marker‐assisted selection on growth and fat deposition traits in the pig but also provides for an understanding of their genetic roles in the development of human obesity.
Candidate gene
Family-based QTL mapping
Polygene
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Almost all crops have been studied on QTL(quantitative trait loci) mapping with many QTL mapping methods,such as IM(interval mapping),CIM(composite interval mapping),MCIM(mixed-model based composite interval mapping) and Bayesian QTL mapping having been developed.However,these methods have had shortcomings,namey,the genomic region of the QTL detected,within which there were probably hundreds of candidate genes was still too large.In this paper,a better understanding of the molecular functions of QTLs was obtained by first briefly reviewing methods of analyzing the candidate gene within QTL intervals based on bioinformatics.Then,in order to provide a new analytical method for better use of QTLs in the future,the genetics,genome organization,gene expression and function of candidate genes located on QTL region were analyzed.
Family-based QTL mapping
Candidate gene
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Family-based QTL mapping
Candidate gene
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A systematic study has been conducted of all available reports in PubMed and OMIM (Online Mendelian Inheritance in Man) to examine the genetic and molecular basis of quantitative genetic loci (QTL) of diabetes with the main focus on genes and polymorphisms. The major question is, What can the QTL tell us? Specifically, we want to know whether those genome regions differ from other regions in terms of genes relevant to diabetes. Which genes are within those QTL regions, and, among them, which genes have already been linked to diabetes? whether more polymorphisms have been associated with diabetes in the QTL regions than in the non-QTL regions.Our search revealed a total of 9038 genes from 26 type 1 diabetes QTL, which cover 667,096,006 bp of the mouse genomic sequence. On one hand, a large number of candidate genes are in each of these QTL; on the other hand, we found that some obvious candidate genes of QTL have not yet been investigated. Thus, the comprehensive search of candidate genes for known QTL may provide unexpected benefit for identifying QTL genes for diabetes.
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Family-based QTL mapping
Mendelian inheritance
Genetic linkage
Polygene
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Family-based QTL mapping
Positional cloning
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Family-based QTL mapping
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Advances on methods for mapping quantitative trait loci (QTL) are firstly summarized. Then, some new methods, including mapping multiple QTL, fine mapping of QTL, and mapping QTL for dynamic traits, are mainly described. Finally, some future prospects are proposed, including how to dig novel genes in the germplasm resource, map expression QTL (eQTL) by the use of all markers, phenotypes and micro-array data, identify QTL using genetic mating designs and detect viability loci. The purpose is to direct plant geneticists to choose a suitable method in the inheritance analysis of quantitative trait and in search of novel genes in germplasm resource so that more potential genetic information can be uncovered.
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Trait
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Abstract Background Meta-analysis of quantitative trait locus (QTL) is a computational technique to identify consensus QTL and refine QTL positions on the consensus map from multiple mapping studies. The combination of meta-QTL intervals, significant SNPs and transcriptome analysis has been widely used to identify candidate genes in various plants. Results In our study, 884 QTL associated with cotton fiber quality traits from 12 studies were used for meta-QTL analysis based on reference genome TM-1, as a result, 74 meta-QTL were identified, including 19 meta-QTL for fiber length (FL), 18 meta-QTL for fiber strength (FS), 11 meta-QTL for fiber uniformity (FU), 11 meta-QTL for fiber elongation (FE), and 15 meta-QTL for micronaire (MIC). Combined with 8589 significant SNPs associated with fiber quality traits collected from 15 studies, 297 candidate genes were identified in the meta-QTL intervals, 20 of which showed high expression specifically in the developing fibers. According to the function annotations, some of the 20 key candidate genes are associated with the fiber development. Conclusions This study provides not only stable QTLs used for marker-assisted selection (MAS), but also candidate genes to uncover the molecular mechanisms for cotton fiber development.
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Family-based QTL mapping
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