File Name: statistical genetics of quantitative traits linkage maps and qtl .zip
Multivalent tetraploids that include many plant species, such as potato, sugarcane, and rose, are of paramount importance to agricultural production and biological research. Quantitative trait locus QTL mapping in multivalent tetraploids is challenged by their unique cytogenetic properties, such as double reduction.
Saccharina Laminaria is one of the most important economic seaweeds. Previously, four genetic linkage maps of Saccharina have been constructed and five QTLs have been identified. However, they were not enough for its breeding. Meanwhile, QTL analysis was performed for six economic traits. A total of 29 QTLs were identified for six economic traits, which explained 1. The results of this research will improve the breeding efficiency and be beneficial for marker-assisted selection MAS schemes in Saccharina breeding. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Protocol DOI: Quantitative trait loci QTL are genetic regions that influence phenotypic variation of a complex trait, often through genetic interactions with each other and the environment. These are commonly identified through a statistical genetic analysis. These are commonly identified through a statistical genetic analysis known as QTL mapping. Here, I present a step-by-step, practical approach to QTL mapping along with a sample data file.
The linkage map comprised 17 linkage groups, covering Linkage groups were well populated and, although marker density ranged from 2. Moreover, just The present genetic linkage map was used to identify quantitative trait loci QTLs affecting fruit-related traits. To maintain this position in the future, new apple cultivars which confer desirable traits such as superior fruit quality and natural disease resistance must be developed continuously. However, genetic studies and breeding for high quality apple cultivars have always been hampered by a long juvenile phase, the space, time and cost involved in maintaining populations, and the strong selfincompatibility present in this species. Recent advances in DNA molecular markers offer breeders a rapid and precise alternative approach to conventional selection schemes to improve quantitative traits [ 1 ].
The standard procedures for constructing maps of Quantitative Trait Loci QTL are based on the estimation by maximum likelihood or minimum squares of the QTL biometrics parameters and generally require numerical methods and special software, given that they do not produce explicit estimators. The objective of the present study was to derive explicit estimators of the biometrics parameters of a QTL in an F 2 population. The derivation was based on three linear combinations of random variables with mixed normal distribution and a molecular marker. For each linear combination, its mean and variance were determined, with which estimators were derived of the additive effect and dominance effect of the QTL, as well as the frequency of recombination between the QTL and the marker. The explicit estimators obtained here were asyntotically consistent and unbiased, and do not require special software for their evaluation. Blangero, J. Williams, and L.
Statistical Genetics of Quantitative Traits. Linkage, Maps, and QTL. Authors; (view affiliations). Rongling Wu.
Estimating the effects of population size and type on the accuracy of genetic maps. Send correspondence to. Based on simulation studies, it was shown that the type and size of experimental populations can exert an influence on the accuracy of genetic maps. A hypothetical genome map one chromosome with nine equidistant molecular markers was generated for the following population types: F 2 with dominant and co-dominant markers, backcrossing, recombinant inbred lines RIL and double-haploid. The population sizes were 50, , , , and individuals and simulations were made for each population.
It seems that you're in Germany. We have a dedicated site for Germany. The book introduces the basic concepts and methods that are useful in the statistical analysis and modeling of DNA-based marker and phenotypic data that arise in agriculture, forrestry, experimental biology, and other fields.
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