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Statistical Genetics of Quantitative Traits

Linkage, Maps and QTL

  • Book
  • © 2007

Overview

Authors:
  1. Rongling Wu

    1. University of Florida, FL, USA

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    You can also search for this author in PubMed   Google Scholar

  2. George Casella

    1. University of Florida, FL, USA

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    You can also search for this author in PubMed   Google Scholar

  3. Chang-Xing Ma

    1. State University of New York at Buffalo, NY, USA

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    You can also search for this author in PubMed   Google Scholar

  • Provides basic statistical models and analytical procedures for detecting specific genes that control quantitative traits of economical and biological importance from these data
  • Includes supplementary material: sn.pub/extras

Part of the book series: Statistics for Biology and Health (SBH)

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Table of contents (14 chapters)

  1. Front Matter

    Pages I-XVI
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  2. Basic Genetics

    Pages 1-23

  3. Basic Statistics

    Pages 25-41

  4. Linkage Analysis and Map Construction

    Pages 43-75

  5. A General Model for Linkage Analysis in Controlled Crosses

    Pages 77-106

  6. Linkage Analysis with Recombinant Inbred Lines

    Pages 107-122

  7. Linkage Analysis for Distorted and Misclassified Markers

    Pages 123-143

  8. Special Considerations in Linkage Analysis

    Pages 145-170

  9. Marker Analysis of Phenotypes

    Pages 171-201

  10. The Structure of QTL Mapping

    Pages 203-221

  11. Interval Mapping with Regression Analysis

    Pages 223-235

  12. Interval Mapping by Maximum Likelihood Approach

    Pages 237-268

  13. Threshold and Precision Analysis

    Pages 269-285

  14. Composite QTL Mapping

    Pages 287-302

  15. QTL Mapping in Outbred Pedigrees

    Pages 303-329

  16. Back Matter

    Pages 331-365
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Keywords

About this book

Most traits in nature and of importance to agriculture are quantitatively inherited. These traits are di?cult to study due to the complex nature of their inheritance. However, recent developments of genomic technologies provide a revolutionary means for unraveling the secrets of genetic variation in quantitative traits. Genomic te- nologies allow the molecular characterization of polymorphic markers throughout the entire genome that are then used to identify and map the genes or quantitative trait loci (QTLs) underlying a quantitative trait based on linkage analysis. Statistical analysis is a crucial tool for analyzing genome data, which are now becoming increasingly available for a variety of species, and for giving precise exp- nations regarding genetic variation in quantitative traits occurring among species, populations, families, and individuals. In 1989, Lander and Botstein published a ha- mark methodological paper for interval mapping that enables geneticists to detect and estimate individual QTL that control the phenotype of a trait. Today, interval mappingisanimportantstatisticaltoolforstudyingthegeneticsofquantitativetraits at the molecular level, and has led to the discovery of thousands of QTLs responsible for a variety of traits in plants, animals, and humans. In a recent study published in Science, Li, Zhou, and Sang (2006, 311, 1936–1939) were able to characterize the molecular basis of the reduction of grain shattering – a fundamental selection process for rice domestication – at the detected QTL by interval mapping.

Reviews

From the Reviews:

"[I]t is a big help and guidance in the field of statistical developments for genetic mapping, synthesised all in one volume helping to build a bridge between genetics and statistics." (Lutz Bunger, Genetic Research, 89, 2007)

"...[T]his is an ideal book for a young researcher looking for an exciting and developing field to get into." (International Statistics Review, April 2008)

Authors and Affiliations

  • University of Florida, FL, USA

    Rongling Wu, George Casella

  • State University of New York at Buffalo, NY, USA

    Chang-Xing Ma

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